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1.
Caffeic acid O-methyltransferase (COMT) is a bifunctional enzyme that methylates the 5- and 3-hydroxyl positions on the aromatic ring of monolignol precursors, with a preference for 5-hydroxyconiferaldehyde, on the way to producing sinapyl alcohol. Lignins in COMT-deficient plants contain benzodioxane substructures due to the incorporation of 5-hydroxyconiferyl alcohol (5-OH-CA), as a monomer, into the lignin polymer. The derivatization followed by reductive cleavage method can be used to detect and determine benzodioxane structures because of their total survival under this degradation method. Moreover, partial sequencing information for 5-OH-CA incorporation into lignin can be derived from detection or isolation and structural analysis of the resulting benzodioxane products. Results from a modified derivatization followed by reductive cleavage analysis of COMT-deficient lignins provide evidence that 5-OH-CA cross couples (at its β-position) with syringyl and guaiacyl units (at their O-4-positions) in the growing lignin polymer and then either coniferyl or sinapyl alcohol, or another 5-hydroxyconiferyl monomer, adds to the resulting 5-hydroxyguaiacyl terminus, producing the benzodioxane. This new terminus may also become etherified by coupling with further monolignols, incorporating the 5-OH-CA integrally into the lignin structure.Lignins are polymeric aromatic constituents of plant cell walls, constituting about 15% to 35% of the dry mass (Freudenberg and Neish, 1968; Adler, 1977). Unlike other natural polymers such as cellulose or proteins, which have labile linkages (glycosides and peptides) between their building units, lignins’ building units are combinatorially linked with strong ether and carbon-carbon bonds (Sarkanen and Ludwig, 1971; Harkin, 1973). It is difficult to completely degrade lignins. Lignins are traditionally considered to be dehydrogenative polymers derived from three monolignols, p-coumaryl alcohol 1h (which is typically minor), coniferyl alcohol 1g, and sinapyl alcohol 1s (Fig. 1; Sarkanen, 1971). They can vary greatly in their composition in terms of their plant and tissue origins (Campbell and Sederoff, 1996). This variability is probably determined and regulated by different activities and substrate specificities of the monolignol biosynthetic enzymes from different sources, and by the carefully controlled supply of monomers to the lignifying zone (Sederoff and Chang, 1991).Open in a separate windowFigure 1.The monolignols 1, and marker compounds 2 to 4 resulting from incorporation of novel monomer 15h into lignins: thioacidolysis monomeric marker 2, dimers 3, and DFRC dimeric markers 4.Recently there has been considerable interest in genetic modification of lignins with the goal of improving the utilization of lignocellulosics in various agricultural and industrial processes (Baucher et al., 2003; Boerjan et al., 2003a, 2003b). Studies on mutant and transgenic plants with altered monolignol biosynthesis have suggested that plants have a high level of metabolic plasticity in the formation of their lignins (Sederoff et al., 1999; Ralph et al., 2004). Lignins in angiosperm plants with depressed caffeic acid O-methyltransferase (COMT) were found to derive from significant amounts of 5-hydroxyconiferyl alcohol (5-OH-CA) monomers 15h (Fig. 1) substituting for the traditional monomer, sinapyl alcohol 1s (Marita et al., 2001; Ralph et al., 2001a, 2001b; Jouanin et al., 2004; Morreel et al., 2004b). NMR analysis of a ligqnin from COMT-deficient poplar (Populus spp.) has revealed that novel benzodioxane structures are formed through β-O-4 coupling of a monolignol with 5-hydroxyguaiacyl units (resulting from coupling of 5-OH-CA), followed by internal trapping of the resultant quinone methide by the phenolic 5-hydroxyl (Ralph et al., 2001a). When the lignin was subjected to thioacidolysis, a novel 5-hydroxyguaiacyl monomer 2 (Fig. 1) was found in addition to the normal guaiacyl and syringyl thioacidolysis monomers (Jouanin et al., 2000). Also, a new compound 3g (Fig. 1) was found in the dimeric products from thioacidolysis followed by Raney nickel desulfurization (Lapierre et al., 2001; Goujon et al., 2003).Further study with the lignin using the derivatization followed by reductive cleavage (DFRC) method also confirmed the existence of benzodioxane structures, with compounds 4 (Fig. 1) being identified following synthesis of the authentic parent compounds 9 (Fig. 2). However, no 5-hydroxyguaiacyl monomer could be detected in the DFRC products. These facts imply that the DFRC method leaves the benzodioxane structures fully intact, suggesting that the method might therefore be useful as an analytical tool for determining benzodioxane structures that are linked by β-O-4 ethers. Using a modified DFRC procedure, we report here on results that provide further evidence for the existence of benzodioxane structures in lignins from COMT-deficient plants, that 5-OH-CA is behaving as a rather ideal monolignol that can be integrated into plant lignins, and demonstrate the usefulness of the DFRC method for determining these benzodioxane structures.Open in a separate windowFigure 2.Synthesis of benzodioxane DFRC products 12 (see later in Fig. 6 for their structures). i, NaH, THF. ii, Pyrrolidine. iii, 1g or 1s, benzene/acetone (4/1, v/v). iv, DIBAL-H, toluene. v, Iodomethane-K2CO3, acetone. vi, Ac2O pyridine.  相似文献   

2.
Two nonoverlapping autosomal inversions defined unusual neo-sex chromosomes in the Hessian fly (Mayetiola destructor). Like other neo-sex chromosomes, these were normally heterozygous, present only in one sex, and suppressed recombination around a sex-determining master switch. Their unusual properties originated from the anomalous Hessian fly sex determination system in which postzygotic chromosome elimination is used to establish the sex-determining karyotypes. This system permitted the evolution of a master switch (Chromosome maintenance, Cm) that acts maternally. All of the offspring of females that carry Cm-associated neo-sex chromosomes attain a female-determining somatic karyotype and develop as females. Thus, the chromosomes act as maternal effect neo-W''s, or W-prime (W′) chromosomes, where ZW′ females mate with ZZ males to engender female-producing (ZW′) and male-producing (ZZ) females in equal numbers. Genetic mapping and physical mapping identified the inversions. Their distribution was determined in nine populations. Experimental matings established the association of the inversions with Cm and measured their recombination suppression. The inversions are the functional equivalent of the sciarid X-prime chromosomes. We speculate that W′ chromosomes exist in a variety of species that produce unisexual broods.SEX chromosomes are usually classified as X, Y, Z, or W on the basis of their pattern of segregation and the gender of the heterogametic sex (Ohno 1967). However, when chromosome-based sex determination occurs postzygotically, the same nomenclature confounds important distinctions and may hide interesting evolutionary phenomena. The Hessian fly (Mayetiola destructor), a gall midge (Diptera: Cecidomyiidae) and an important insect pest of wheat, presents an excellent example (Stuart and Hatchett 1988, 1991). In this insect, all of the female gametes and all of the male gametes have the same number of X chromosomes (Figure 1A); no heterogametic sex exists. Nevertheless, Hessian fly sex determination is chromosome based; postzygotic chromosome elimination produces different X chromosome to autosome ratios in somatic cells (male A1A2X1X2/A1A2OO and female A1A2X1X2/A1A2X1X2, where A1 and A2 are the autosomes, X1 and X2 are the X chromosomes, and the paternally derived chromosomes follow the slash) (Stuart and Hatchett 1991; Marin and Baker 1998). Thus, Hessian fly “X” chromosomes are defined by their haploid condition in males, rather than by their segregation in the gametes.Open in a separate windowFigure 1.—Chromosome behavior and sex determination in the Hessian fly. (A) Syngamy (1) establishes the germ-line chromosome constitution: ∼32 maternally derived E chromosomes (represented as a single white chromosome) and both maternally derived (black) and paternally derived (gray) autosomes and X chromosomes. During embryogenesis, while the E chromosomes are eliminated, the paternally derived X chromosomes are either retained (2) or excluded (3) from the presumptive somatic cells. When the paternally derived X chromosomes are retained (2), a female-determining karyotype is established. When they are eliminated (3), a male-determining karyotype is established. Thelygenic mothers carry Cm (white arrow), which conditions all of their offspring to retain the X chromosomes. Recombination occurs during oogenesis (4). All ova contain a full complement of E chromosomes and a haploid complement of autosomes and X chromosomes. Chromosome elimination occurs during spermatogenesis (5). Sperm contain only the maternally derived autosomes and X chromosomes. (B) The segregation of Cm (white dot) on a Hessian fly autosome among monogenic families. Thelygenic females produce broods composed of equal numbers of thelygenic (Cm/−) and arrhenogenic (−/−) females (box 1). Arrhenogenic females produce males (box 2). (C) Matings between monogenic and amphigenic families. Cm (white dot) is dominant to the amphigenic-derived chromosomes (gray dot) and generates all-female offspring (box 3). Amphigenic-derived chromosomes are dominant to the arrhenogenic-derived chromosomes (no dot) and generate offspring of both sexes (box 4).An autosomal, dominant, genetic factor called Chromosome maintenance (Cm) complicates Hessian fly sex determination further (Stuart and Hatchett 1991). Cm has a maternal effect that acts upstream of X chromosome elimination during embryogenesis (Figure 1A). It prevents X chromosome elimination so that all of the offspring of Cm-bearing mothers obtain a female-determining karyotype. Cm-bearing females produce only female offspring and are therefore thelygenic. The absence of Cm usually has the opposite effect; all of the offspring of most Cm-lacking females obtain a male-determining karyotype. These Cm-lacking females produce only male offspring and are therefore arrhenogenic. Like a sex-determining master switch, Cm is usually heterozygous and present in only one sex (Figure 1B). Thus, thelygenic females (Cm/−) are “heterogametic,” as their Cm-containing gametes and Cm-lacking gametes produce thelygenic (Cm/−) and arrhenogenic (−/−) females in a 1:1 ratio. Collectively, thelygenic and arrhenogenic females are called monogenic because they produce unisexual families. However, some Hessian fly females produce broods of both sexes and are called amphigenic. No mating barrier between monogenic and amphigenic families exists (Figure 1C), but amphigenic females have always been found in lower abundance (Painter 1930; Gallun et al. 1961; Stuart and Hatchett 1991). In experimental matings, the inheritance of maternal phenotype was consistent with the segregation of three Cm alleles (Figure 1C): a dominant thelygenic allele, a hypomorphic amphigenic allele, and a null arrhenogenic allele (Stuart and Hatchett 1991).Here we report the genetic and physical mapping of Cm on Hessian fly autosome 1 (A1). Two nonoverlapping inversions were identified that segregated perfectly with Cm. The most distal inversion was present in all thelygenic females examined. The more proximal inversion extended recombination suppression. These observations suggested that successive inversions evolved to suppress recombination around Cm after it arose. The inversions therefore appear to have evolved in response to the forces that shaped vertebrate Y and W chromosomes (Charlesworth 1996; Graves and Shetty 2001; Rice and Chippindale 2001; Carvalho and Clark 2005). We therefore believe the inversion-bearing chromosomes may be classified as maternal effect neo-W''s.  相似文献   

3.
4.
Yongrui Wu  Joachim Messing 《Genetics》2010,186(4):1493-1496
Maize Mucronate1 is a dominant floury mutant based on a misfolded 16-kDa γ-zein protein. To prove its function, we applied RNA interference (RNAi) as a dominant suppressor of the mutant seed phenotype. A γ-zein RNAi transgene was able to rescue the mutation and restore normal seed phenotype. RNA interference prevents gene expression. In most cases, this is used to study gene function by creating a new phenotype. Here, we use it for the opposite purpose. We use it to reverse the creation of a mutant phenotype by restoring the normal phenotype. In the case of the maize Mucronate1 (Mc1) phenotype, interaction of a misfolded protein with other proteins is believed to be the basis for the Mc1 phenotype. If no misfolded protein is present, we can reverse the mutant to the normal phenotype. One can envision using this approach to study complex traits and in gene therapy.TRANSLUCENT or vitreous maize kernels are harder and able to sustain stronger mechanical strength during harvesting, transportation, and storage. There is a direct link between a vitreous seed phenotype and the type of storage proteins in the seed, collectively called zeins in maize. Zeins, encoded by a multigene family, constitute >60% of all maize seed proteins. They are classified into four groups (α-, β-, γ-, and δ-zein) on the basis of their structures (Esen 1987). Zeins are specifically synthesized in the endosperm ∼10 days after pollination (DAP) and deposited into protein bodies (Wolf et al. 1967; Burr and Burr 1976; Lending and Larkins 1992). Irregularly shaped protein bodies are found in floury or opaque kernel phenotypes (Coleman et al. 1997; Kim et al. 2004, 2006; Wu et al. 2010; Wu and Messing 2010). The terms “floury” and “opaque” were originally created on the basis of the genetic behaviors of the mutant allele causing the soft kernel texture. The floury mutants behave as semidominant or dominant mutants, as floury1 and floury2 do, while the opaque mutants are recessive, as opaque1 and opaque2 are (Hayes and East 1915; Lindstrom 1923; Emerson et al. 1935; Maize Genetics Cooperation 1939). Similar to floury2 with a single mutation in the signal peptide of a 22-kDa α-zein resulting in an unprocessed protein (Coleman et al. 1995), De*-B30 produces an unprocessed 19-kDa α-zein (Kim et al. 2004). It was hypothesized that the two mutant proteins with an unprocessed signal peptide are misfolded and docked in the membranes of the rough endoplasmic reticulum (RER), blocking the deposition of other zein proteins (Coleman et al. 1995; Kim et al. 2004). In Mucronate1 (Mc1), a 38-bp deletion in the C terminus of the 16-kDa γ-zein (γ16-zein) gene resulted in a frameshift and a protein with a different amino-acid tail. This modified 16-kDa γ-zein (Δγ16-zein) has altered solubility properties, which would explain the formation of irregular protein bodies. Because De*-B30 and Mc1 are semidominant and dominant, respectively, they belong to the floury mutant class.The γ-zein genes (γ27-zein and γ16-zein) are homologous copies because maize underwent allotetraploidization and both gene copies have been retained during diploidization (Xu and Messing 2008). The two γ-zeins and the 15-kDa β-zein have a redundant function in stabilizing protein-body formation (Wu and Messing 2010). Knockdown of both γ-zeins with a single RNA interference (RNAi) construct conditioned only partial opacity in the crown, the top of the kernel, as opposed to the remainder or gown area of the kernel. Consistent with its light kernel phenotype, protein bodies in such a γ-zein RNAi (γRNAi) mutant exhibited a slight alteration in morphology. This phenotype is clearly distinguishable from the Mc1 phenotype, which is far more severe. Therefore, if Mc1 is caused by a misfolded chimeric 16-kDa γ-zein, preventing its expression should restore normal kernel phenotype. Indeed, a simple cross of Mc1 with a maize line carrying the γRNAi transgene produced a non-floury phenotype, providing an example of RNAi as a dominant suppressor of a dominant phenotype and as a general tool in marker rescue.

Analysis of the progeny from the cross of Mc1 and γRNAi mutants:

Mc1 seeds (Stock ID U840I) were requested from the Maize Genetics Cooperation Stock Center. The γRNAi transgenic lines have been reported in previous work (Wu et al. 2010; Wu and Messing 2010). Twelve progeny kernels from the cross of the Mc1 mutant [homozygous for the dominant-negative mutant 16-kDa γ-zein alleles (Δγ16/Δγ16) and heterozygous for the γRNAi line (γRNAi/+)] were dissected at 18 DAP for segregation and mRNA accumulation analyses. For each kernel, the embryo and endosperm were separated for DNA and RNA extraction, respectively. As shown in Figure 1A, five and seven kernels were positive and negative for the amplification of the γRNAi gene with a specific primer set, exemplifying a 1:1 segregation of the γRNAi gene.Open in a separate windowFigure 1.—Segregation analysis of the accumulations of mRNAs and proteins from the cross of the Mc1 mutant and the γRNAi line by RT–PCR and SDS–PAGE. (A) γRNAi gene segregation from progeny (Δγ16/Δγ16 x γRNAi/+) by PCR amplification with a specific primer set (GFPF, ACAACCACTACCTGAGCAC and T35SHindIII, ATTAAGCTTTGCAGGTCACTGGATTTTGG). Kernels 3, 8, 9, 10, and 12 are positive for the γRNAi gene and the rest of them are negative. M, DNA markers from top to bottom band are 3, 2, 1.5, 1.4, and 1 kb. (B) RT–PCR analysis of mRNA accumulation from the normal γ16 and mutant Δγ16 alleles in the endosperms with the genotypes corresponding to the embryos analyzed above. Total RNA was extracted by using TRIzol reagent (Invitrogen). Two micrograms of RNA was digested with DNase I (Invitrogen) and then reverse-transcribed. Twenty-five nanograms of cDNA from each of the twelve endosperms was applied for PCR (25 cycles of 30 sec, 94 °C; 30 sec, 58 °C; and 1 min, 72 °C). A specific primer set (γ16F, ATGAAGGTGCTGATCGTTGC and γ16R, TCAGTAGTAGACACCGCCG) was designed for amplification of the full-length γ16-zein coding sequence (552 bp). The lower band (514 bp) from the mutant Δγ16 allele is 38 bp shorter than that from the normal allele (552 bp). Kernels 3, 8, 9, 10, and 12 with the γRNAi gene accumulated significantly less mRNA compared to those without the γRNAi gene (kernels 1, 2, 4, 5, 6, 7, and 11). BA, hybrid of B × A lines. M, DNA markers from top to bottom are 1 kb, 750 bp, and 500 bp. (C) Profile of zein accumulations of 20 kernels from the progeny as described in the text. The zein extraction method has been described elsewhere (Wu et al. 2009). The Δγ16-zein from Mc1 was not extracted by traditional total-zein extraction protocol (70% ethanol and 2% 2-mercaptoethanol). The γ27- and γ16-zeins were knocked down to a nondetectable level in kernels 1, 2, 3, 5, 7, 10, 12, 13, 16, and 20. In γRNAi-gene segregating progeny (kernels 4, 6, 8, 9, 11, 14, 15, 17, 18, and 19), the γ16-zein from the normal γ16 allele is marked by arrowheads. Protein loaded in each lane was equal to 500 μg fresh endosperm at 18 DAP. The size for each band is indicated by the numbers in the “kDa” columns. BA, hybrid of B × A lines; 1–20, kernels from the progeny described above; M, protein markers from top to bottom are 50, 25, 20, and 15 kDa.Due to the 38-bp deletion in the C terminus of the coding region, the Δγ16 allele is shorter than the normal one (Figure 1B). Therefore, most of Δγ16-zein was in the non-zein fraction. In progeny endosperms of another 20 kernels from the same cross described above segregating for the γRNAi gene, two types of γ16-zeins were synthesized: the normal γ16-zein in the ethanol-soluble zein fraction and the Δγ16-zein in the non-zein fraction. In progeny inheriting the γRNAi gene, the γ27- and γ16-zeins were reduced to nondetectable levels (Figure 1C). Although the Δγ16-zein is not in the ethanol-soluble zein fraction, the level of normal γ16-zein is a good indicator of the accumulation of the Δγ16-zein.

Rescue of protein-body morphologies in the Mc1 mutant:

Regular protein bodies are round with distinct membrane boundaries (Figure 2A) and 1–2 μm in diameter at maturity. In homozygous and heterozygous Mc1 mutants (Δγ16/Δγ16 and Δγ16/+), protein bodies were irregularly shaped, some without discrete boundaries (Figure 2, C and D), which is quite different from the absence of normal γ27- or γ16-zeins in maize endosperm (Figure 2B). Indeed, protein bodies of the Mc1 mutant, blocked in the accumulation of Δγ16-zein, showed morphologies with no discernible difference from those in the γRNAi/+ line (Figure 2, B and E).Open in a separate windowFigure 2.—Transmission electron micrographs of protein bodies. The method has been described elsewhere (Wu and Messing 2010). (A) Nontransgenic BA. (B) γRNAi transgenic line (γRNAi/+). (C) Mc1 (Δγ16/Δγ16). (D) Cross of Mc1 mutant and nontransgenic hybrid of B × A lines (Δγ16/+). (E) Cross of Mc1 mutant (Δγ16/Δγ16) and heterologous γRNAi transgenic line (γRNAi/+). PB, protein body; RER, rough endoplasmic reticulum; CW, cell wall; Mt, mitochondria; SG, starch granule. Bars, 500 nm.

Recovery of floury phenotype in progeny:

On the basis of these observations, it is reasoned that irregularly shaped protein bodies (Figure 2, C and D) in the Mc1 mutant cause the floury phenotype (Figure 3, A and B). Because knockdown of γ-zeins caused opacity only in the crown area (Figure 3C), one could envision that once the irregular protein bodies are restored, the kernel would become vitreous in the gown area of the kernel. Indeed, the progeny ear from the cross of Δγ16/Δγ16 and γRNAi/+ showed a 1:1 ratio of floury and vitreous kernels (Figure 3, D and F), and all kernels were vitreous when the Mc1 mutant was pollinated by a homozygous γRNAi line (Figure 3E).Open in a separate windowFigure 3.—Segregation of vitreous and floury kernels from a progeny ear. (A) Mc1 mutant with Δγ16/Δγ16 genotype. (B) The cross of the Mc1 mutant and the nontransgenic hybrid of B × A lines, showing floury phenotype as in A. (C) γRNAi transgenic line with partial opacity only in the crown area. (D) The cross of the Mc1 mutant (Δγ16/Δγ16) and the heterologous γRNAi transgenic line (γRNAi/+), showing a 1:1 ratio of vitreous and floury kernels. A row in the ear is marked with arrowheads and crosses to indicate vitreous and floury gowns of kernels. (E) Cross of the Mc1 mutant (Δγ16/Δγ16) and the γRNAi homozygous transgenic line (γRNAi/γRNAi), showing all vitreous kernels. (F) Truncated kernel phenotype. (Top) Mc1, cross of Mc1 × BA, and γRNAi transgenic line. (Bottom) Three vitreous and floury kernels from D.

Conclusions:

RNAi can be used to rescue mutations that are dominant negative with a single cross, providing a useful tool in genetic analysis, plant breeding, and potentially in gene therapy in general.  相似文献   

5.
The mosquito Anopheles gambiae has heteromorphic sex chromosomes, while the mosquito Aedes aegypti has homomorphic sex chromosomes. We use retrotransposed gene duplicates to show an excess of movement off the An. gambiae X chromosome only after the split with Ae. aegypti, suggesting that their ancestor had homomorphic sex chromosomes.HETEROMORPHIC sex chromosomes, both XX/XY and ZZ/ZW systems, have evolved independently multiple times in both animals and plants (Bull 1983; Charlesworth 1996; Rice 1996). Sex chromosomes are thought to evolve from a pair of autosomes that acquire a new sex-determining locus. Theory suggests that natural selection will favor tight linkage between the newly arisen sex-determining locus and sexually antagonistic alleles (i.e., genes that are beneficial in one sex, but detrimental in the other), which favors the suppression of recombination near the sex-determining locus (Charlesworth et al. 2005). In some species, this nonrecombining region includes only a small portion of the sex chromosome (hereafter referred to as homomorphic sex chromosomes), whereas in other species, this region encompasses most of the sex chromosomes (heteromorphic sex chromosomes). In many species the nonrecombining region progressively expands from only the portion near the sex-determining locus to nearly the full extent of the sex chromosomes (Lahn and Page 1999; Lawson Handley et al. 2004; Nicolas et al. 2005). However, the broad phylogenetic distribution of homomorphic sex chromosomes suggests that this progression does not happen in every species (e.g., Matsubara et al. 2006; Tsuda et al. 2007), although why it should occur in some lineages and not in others is unknown. As noted by Gilchrist and Haldane (1947, p. 187): “It is a striking fact that this [the suppression of recombination across the sex chromosome] has not happened in many large and successful groups.”Within the order Diptera, there are a wide variety of sex chromosomes and sex-determination mechanisms, including XY, ZW, multiple-X, and homomorphic systems, often varying within the same family (Marin and Baker 1998; Schutt and Nothiger 2000; Sanchez 2008). The mosquito Anopheles gambiae (a species in the subfamily Anophelinae) has fully differentiated heteromorphic X and Y chromosomes that show no evidence of recombination (Krzywinski et al. 2004). The mosquito Aedes aegypti (subfamily Culicinae) has a nonrecombining sex-determining region that spans only a few megabases on chromosome 1; this chromosome is homologous to chromosomes X and 2R of An. gambiae (Nene et al. 2007). An. gambiae and Ae. aegypti diverged ∼150 million years ago (Krzywinski et al. 2006).Because of the rapid turnover of sex-chromosome systems among the Diptera, it is not clear if the common ancestor of Ae. aegypti and An. gambiae had only a sex-determining region (i.e., homomorphic sex chromosomes) or fully differentiated heteromorphic sex chromosomes (Rai and Black 1999). The generally accepted model of sex-chromosome evolution, in which homomorphic sex chromosomes progressively suppress recombination and become heteromorphic, predicts that the common ancestor of Ae. aegypti and An. gambiae had homomorphic sex chromosomes (Figure 1A). This implies that evolution of heteromorphic sex chromosomes in An. gambiae occurred in a short period of time after the split between these two lineages and before the radiation of the Anophelines and that the homomorphic sex chromosomes of Ae. aegypti have been nearly static over evolutionary time. Alternatively, the common ancestor may have had nearly or fully differentiated sex chromosomes, and Ae. aegypti evolved from heteromorphic sex chromosomes to having only a small sex-determining region (Figure 1B; Rao and Rai 1987). We imagine this transition may have occurred by one of two mechanisms: either the sex-determining locus was transposed from the ancestral sex chromosome to an autosome or, in an XO sex-determination system, one of the “numerator” genes located on the X chromosome sustained an inactivating mutation, effectively making a karyotypic XX individual into a genetically male XO individual. (The precise mechanism of sex determination in Ae. aegypti is not known.)Open in a separate windowFigure 1.—Hypotheses for sex-chromosome evolution in Anopheles gambiae and Aedes aegypti. (A) The ancestor of An. gambiae and Ae. aegypti had homomorphic sex chromosomes and heteromorphism evolved along the Anopheline lineage. (B) The ancestor of An. gambiae and Ae. aegypti had heteromorphic chromosomes and homomorphism evolved along the Culicine lineage.To determine the state of the mosquito common ancestor, we examined genes duplicated by retrotransposition in the An. gambiae genome. Several organisms with heteromorphic sex chromosomes, including mammals and Drosophila, have an excess of retrotransposed genes moving from the X chromosome to autosomes compared to genes moving between autosomes or from the autosomes to the X (Betran et al. 2002; Emerson et al. 2004; Vinckenbosch et al. 2006; Meisel et al. 2009). This pattern is further found to be strongly associated with the origin of new X chromosomes in both mammals and Drosophila (Potrzebowski et al. 2008; Meisel et al. 2009), although it continues long after X chromosomes arise. While there are many hypotheses for the evolutionary forces that drive gene movement off X chromosomes—including sexual antagonism and meiotic sex-chromosome inactivation (e.g., Hense et al. 2007)—it is likely that all of these forces also act in mosquitoes, implying excess movement off the heteromorphic X in this clade as well. We reasoned that if the common ancestor of Ae. aegypti and An. gambiae had homomorphic sex chromosomes (Figure 1A), there should be an excess of retrogene movement off the X chromosome in An. gambiae only after the divergence of the two lineages (i.e., since An. gambiae evolved a differentiated X chromosome). In contrast, if the common ancestor had fully heteromorphic chromosomes (Figure 1B), then our prediction is that there will be an excess of gene movement off the An. gambiae X on both the shared ancestral branch and the Anopheles-specific branch after the split with Aedes. (Note that the Ae. aegypti genome is largely not assembled onto chromosomes, precluding a similar analysis in this species.)We collected data on all functional, intact duplicates in the An. gambiae genome and all orthologs between An. gambiae and Ae. aegypti from Ensembl version 54. When genes are retrotransposed there will be introns in the parental copy, but no introns in the daughter copy, allowing us to polarize gene movement. Although introns may be lost—and more rarely gained—over time, the rate of such changes is quite low (Coulombe-Huntington and Majewski 2007). Nevertheless, unless a parental gene loses all of its introns and the daughter gene gains introns, such changes will merely cause us to miss events rather than to assign them to an incorrect chromosome. Using gene-tree/species-tree reconciliation (Goodman et al. 1979), we identified retrotransposition events in the An. gambiae genome that have occurred since the split with Drosophila melanogaster and assigned them to a branch on the basis of the timing of the inferred duplication event in the gene tree. Calculating the expected number of movements on the basis of the equations presented in Betran et al. (2002), we find that an excess of movement off the X chromosome has in fact occurred since the split with D. melanogaster2 = 23.83, d.f. = 2, P = 6.7 × 10−6). We then divided the retrotransposition events into those that occurred before the divergence of An. gambiae and Ae. aegypti and those that occurred only in An. gambiae since the split. We determined that there is a 400% excess of retrotransposition events off the X chromosome since the An. gambiae and Ae. aegypti split (Figure 2: χ2 = 51.97, d.f. = 2, P = 5.2 × 10−12). However, there is no excess of retrotransposition off the X chromosome prior to the split between An. gambiae and Ae. aegypti (Figure 2: χ2 = 1.51, d.f. = 2, P = 0.47). This strongly suggests a recent origin of fully differentiated heteromorphic sex chromosomes in An. gambiae.Open in a separate windowFigure 2.—Retroposition events off the X chromosome. There is an excess of genes moving off the X chromosome on the An. gambiae-specific lineage, but not on the branch leading to the common ancestor of An. gambiae and Ae. aegypti.The deepest split between species within the subfamily Anophelinae—all of which have fully differentiated sex chromosomes—occurs soon after the split with the Culicinae (Krzywinski et al. 2006). This implies that the evolution of heteromorphic sex chromosomes must have occurred very soon after the split with Ae. aegypti. To determine whether there was a burst of retrotransposition off the X following this split, we examined the amino acid sequence identity between X-to-autosome retrotransposed proteins and their parental paralogs. A comparison of these distributions indicates that there is no difference in the percentage of identity of genes retrotransposed off the An. gambiae X chromosome and one-to-one orthologs between An. gambiae and Ae. aegypti (71.1% vs. 70.7%, t-test, P = 0.92; JTT amino acid distances, 0.508 vs. 0.436, t-test, P = 0.57). Given the fact that functional retrotransposed genes have been found to evolve more rapidly than single-copy genes (Betran et al. 2002), these results support the idea that these duplication events occurred soon after the split between An. gambiae and Ae. aegypti.Our results have important implications for two further areas of research. First, a recent article (Moyle et al. 2010) proposed that X-to-autosome duplication events could be partly responsible for the large X-effect—the disproportionate effect of the X chromosome on reproductive isolation (Coyne and Orr 2004). This is because gene movement between chromosomes can itself cause reproductive isolation (e.g., Masly et al. 2006), and any excess movement involving the X will lead to an excess of reproductive isolation loci mapping to this chromosome. One prediction of this model is that species showing the large X-effect should also show an excess of X-to-autosome gene movement. As An. gambiae does in fact exhibit patterns consistent with the large X-effect (Slotman et al. 2005), our demonstration of an excess of movement off the X supports this model.Second, it has been proposed that the excess movement off the X in Drosophila is the cause of the deficit of male-biased genes on the X in the same species (e.g., Vibranovski et al. 2009), although the number of retrotransposed genes is much smaller than the number of missing male-biased genes (Betran et al. 2002; Parisi et al. 2003). We have previously shown that there is no deficit of male-biased genes on the An. gambiae X chromosome, at any significance level (Hahn and Lanzaro 2005). Given the observed excess of gene movement off the X presented here, we therefore find little support for a causal link between movement and genome-wide patterns of male-biased gene expression.Our results suggest that retrogene movement is a general feature of sex-chromosome evolution and support the hypothesis that the common ancestor of An. gambiae and Ae. aegypti had homomorphic sex chromosomes. It appears that the nonrecombining region around the sex-determining locus in An. gambiae expanded rapidly after the divergence with Ae. aegypti. Further investigation into the causes of the rapid expansion in the An. gambiae lineage and the long-term stasis in the Ae. aegypti lineage is clearly warranted.  相似文献   

6.
β-Carotene biochemistry is a fundamental process in mammalian biology. Aberrations either through malnutrition or potentially through genetic variation may lead to vitamin A deficiency, which is a substantial public health burden. In addition, understanding the genetic regulation of this process may enable bovine improvement. While many bovine QTL have been reported, few of the causative genes and mutations have been identified. We discovered a QTL for milk β-carotene and subsequently identified a premature stop codon in bovine β-carotene oxygenase 2 (BCO2), which also affects serum β-carotene content. The BCO2 enzyme is thereby identified as a key regulator of β-carotene metabolism.THE metabolism of β-carotene to form vitamin A is nutritionally important, and vitamin A deficiency remains a significant public health burden. Genetic variation may underlie individual differences in β-carotene metabolism and contribute to the etiology of vitamin A deficiency. Within an agricultural species, genetic variation provides opportunity for production improvements, disease resistance, and product specialization options. We have previously shown that natural genetic variation can be successfully used to inform bovine breeding decisions (Grisart et al. 2002; Blott et al. 2003). Despite numerous reports of quantitative trait loci (QTL), few causative mutations have been identified. We discovered a QTL for milk β-carotene content and report here the identification of a mutation in the bovine β-carotene oxygenase 2 (BCO2) gene responsible for this QTL. The mutation, which results in a premature stop codon, supports a key role for BCO2 in β-carotene metabolism.The QTL trial consisted of a Holstein-Friesian × Jersey cross in an F2 design and a half-sibling family structure (Spelman et al. 2001). Six F1 sires and 850 F2 female progeny formed the trial herd. To construct the genetic map, the pedigree (including the F1 sires, F1 dams, F2 daughters, and selected F0 grandsires: n = 1679) was genotyped, initially with 237 microsatellite markers, and subsequently, with 6634 SNP markers (Affymetrix Bovine 10K SNP GeneChip). A wide range of phenotypic measures relating to growth and development, health and disease, milk composition, fertility, and metabolism were scored on the F2 animals from birth to 6 years of age.To facilitate the discovery of QTL and genes regulating β-carotene metabolism, milk concentration of β-carotene was measured during week 6 of the animals'' second lactation (n = 651). Using regression methodology in a half-sib model (Haley et al. 1994; Baret et al. 1998), a QTL on bovine chromosome 15 (P < 0.0001; Figure 1A) was discovered. The β-carotene QTL effect on chromosome 15 was also significant (P < 0.0001) at two additional time points, in months 4 and 7 of lactation. Three of the six F1 sire families segregated for the QTL, suggesting that these three F1 sires would be heterozygous for the QTL allele (“Q”). To further define the most likely region within the QTL that would harbor the causative mutation, we undertook association mapping, using the 225 SNP markers that formed the chromosome 15 genetic map (Figure 1A). One SNP (“PAR351319”) was more closely associated with the β-carotene phenotype than any other marker (P = 2.522E−18). This SNP was located beneath the QTL peak. Further, the SNP was heterozygous in the three F1 sires that segregated for the QTL, and homozygous in the remaining three sires. On this basis, we hypothesized that the milk β-carotene phenotype would differ between animals on the basis of the genotype of SNP PAR351319.Open in a separate windowFigure 1.—Discovery of BCO2 mutation affecting milk β-carotene concentration. (A) The β-carotene QTL on bovine chromosome 15 (P < 0.0001) is shown by the red line. The maximum F-value at 21 cM was 7.15. The 95% confidence interval is shown by the shaded box. The association of each marker with milk β-carotene is shown by the blue dots, and the association of the BCO2 genotype is shown by the green diamond. A total of 233 informative markers (8 microsatellite markers and 225 single nucleotide polymorphisms) were included on the genetic map for BTA15. QTL detection was conducted using regression methodology in a line of descent model (Haley et al. 1994) and a half-sib model (Baret et al. 1998). Threshold levels were determined at the chromosomewide level using permutation testing (Churchill and Doerge 1998) and confidence intervals estimated using bootstrapping (Visscher et al. 1996). (B) The haplotypes of 10 representative animals for “QQ” and “qq” are shown for the SNP markers encompassing the SNP (“PAR351319”) most closely associated with the milk β-carotene phenotype. Light and dark gray boxes represent homozygous SNPs, while white boxes represent heterozygous SNPs. The genes present within the defined region are also shown. (C) The mutation in the bovine BCO2 gene is shown. The structure of the BCO2 gene is indicated by the horizontal bar, with vertical bars representing exons 1–12. The A > G mutation in exon 3 (red) causes a premature termination codon at amino acid position 80. (D) The mean concentration of β-carotene in the milk fat of “QQ,” “Qq,” and “qq” cows is shown. β-Carotene was measured by absorbance at 450 nm as previously described (Winkelman et al. 1999). Data are means ± SEM. The statistical significance was determined using ANOVA (***P < 0.0001; n = 651).We then made the following assumptions: that the effect of the QTL was additive, that the Q allele was present in the dam population, allowing the occurrence of homozygous (“QQ”) offspring, and that the QTL was caused by a single mutation, acting with a dominant effect on the milk β-carotene phenotype. Haplotypes encompassing the PAR351319 SNP were determined in the F2 offspring. A comparison of the phenotypic effect of homozygous Q, heterozygous and homozygous q individuals revealed that indeed, animals with the “QQ” genotype had a higher concentration of milk β-carotene than animals with the “qq” genotype (Figure 1D). We predicted that the region of homozygosity was likely to contain the causative gene and mutation. The extent of this region and the candidate genes contained within it are shown in Figure 1B. A total of 10 genes with known function, including BCO2, were located within the region. This information, combined with knowledge of the role BCO2 plays in β-carotene metabolism in other species (Kiefer et al. 2001), made BCO2 a good positional candidate for the QTL. We therefore sequenced the entire coding region (12 exons, NC_007313.3) of the BCO2 gene in each of the six F1 sires. An A > G mutation, which was heterozygous in the three F1 sires that segregated for the QTL, was discovered in exon three, 240 bp from the translation initiation site (Figure 1C). The three remaining sires were homozygous for the G allele, which encodes the 530-amino-acid BCO2 protein (NP_001101987). The A allele creates a premature stop codon resulting in a truncated protein of 79 amino acids. To determine whether this mutation was associated with the QTL, the remainder of the pedigree was genotyped. The BCO2 genotype was significantly associated with the milk β-carotene phenotype (P = 8.195E−29) The AA genotype (referred to as BCO2−/−) was present in 3.4% (n = 28) of the F2 population. The AG and GG genotypes (subsequently referred to as BCO2−/+ and BCO2+/+, respectively) were present in 32.8% (n = 269) and 63.8% (n = 523), respectively, of the F2 population.The effect of the premature stop codon on milk β-carotene content was striking. BCO2−/− cows produced milk with 78 and 55% more β-carotene than homozygous (GG) and heterozygous (AG) wild-type animals, respectively (P < 0.0001; Figure 2A). Consequently, the yellow color of the milk fat varied greatly (Figure 2B). The genotype effect on milk β-carotene content was similar at the other two time points measured during lactation (78 and 68% more β-carotene in milk from BCO2−/− cows compared to BCO2+/+ cows; data not shown).Open in a separate windowFigure 2.—Effect of BCO2 genotype on milk β-carotene content. (A) The mean concentration of β-carotene in the milk fat of BCO2−/−, BCO2−/+, and BCO2+/+ cows is shown. β-Carotene was measured by absorbance at 450 nm as previously described (Winkelman et al. 1999). Data are means ± SEM. The statistical significance was determined using ANOVA (***P < 0.0001; n = 651). (B) The effect of the BCO2 genotype on milk fat color is illustrated.No adverse developmental or health affects as a result of the A allele were observed at any stage throughout the lifespan of the animals. The BCO2−/− cows were fertile and milk yield was normal throughout lactation. Interestingly, quantitative real-time PCR showed fourfold lower levels of the BCO2 mRNA in liver tissue from BCO2−/− cows (data not shown).β-Carotene and vitamin A (retinol) concentrations were also measured in serum, liver, and adipose tissue samples, and vitamin A concentration was measured in milk samples from 14 F2 cows of each genotype. Serum β-carotene concentration was higher in BCO2−/− cows compared to the heterozygous and homozygous wild-type cows (P = 0.003; Figure 3A). Thus, the effect of the mutation on β-carotene concentration was similar for both milk and serum, showing that this effect was not confined to the mammary gland. Vitamin A concentration was higher in serum from BCO2−/− cows (P = 0.001; Figure 3B); however, the concentration did not differ in milk (13.1 μg/g fat vs. 14.1 μg/g fat for BCO2−/− and BCO2+/+ cows, respectively; P > 0.1). Liver β-carotene concentration did not differ between genotype groups (Figure 3C), but liver vitamin A was lower in BCO2−/− cows compared to BCO2+/+ cows (P < 0.03; Figure 3D). β-Carotene and vitamin A concentration did not differ between the genotype groups in adipose tissue (data not shown), suggesting tissue-specific effects of the BCO2 enzyme.Open in a separate windowFigure 3.—Effect of the BCO2 genotypes on concentration of β-carotene (A and C), and retinol (B and D), in serum (A and B), and liver (C and D). Subcutaneous adipose tissue biopsies (∼500 mg tissue), liver biopsies (∼100 mg tissue), and serum samples (10 ml) were taken from a subset of 42 cows (14 animals each BCO2−/−, BCO2−/+, and BCO2+/+ genotypes). β-Carotene and retinol measurements were determined using HPLC with commercial standards, on the basis of a published method (Hulshof et al. 2006). Data shown are means ± SEM. Significant differences are indicated by asterisks (*P < 0.05; **P < 0.01; ANOVA, n = 14 per genotype).While previous studies have shown a key role for β-carotene 15, 15′ monooxygenase (BCMO1) in catalyzing the symmetrical cleavage of β-carotene to vitamin A (von Lintig and Vogt 2000; von Lintig et al. 2001; Hessel et al. 2007) similar evidence for the role of the BCO2 enzyme in β-carotene metabolism is lacking. The physiological relevance of BCO2 has therefore been a topic of debate (Wolf 1995; Lakshman 2004; Wyss 2004). BCO2 mRNA and protein have been detected in several human tissues (Lindqvist et al. 2005), and the in vitro cleavage of β-carotene to vitamin A has been demonstrated (Kiefer et al. 2001; Hu et al. 2006). Our results provide in vivo evidence for BCO2-mediated conversion of β-carotene to vitamin A. BCO2−/− cows had more β-carotene in serum and milk and less vitamin A in liver, the main storage site for this vitamin.Our results show that a simple genetic test will allow the selection of cows for milk β-carotene content. Thus, milk fat color may be increased or decreased for specific industrial applications. Market preference for milk fat color varies across the world. Further, β-carotene enriched dairy foods may assuage vitamin A deficiency. Milk may be an ideal food for delivery of β-carotene, which is fat soluble and most efficiently absorbed in the presence of a fat component (Ribaya-Mercado 2002).In conclusion, we have discovered a naturally occurring premature stop codon in the bovine BCO2 gene strongly suggesting a key role of BCO2 in β-carotene metabolism. This discovery has industrial applications in the selection of cows producing milks with β-carotene content optimized for specific dairy products or to address a widespread dietary deficiency. More speculatively, it would be interesting to investigate possible effects of BCO2 variation in humans on the etiology of vitamin A deficiency.  相似文献   

7.
8.
Active endogenous transposable elements, useful tools for gene isolation, have not been reported from any legume species. An active transposable element was suggested to reside in the W4 locus that governs flower color in soybean. Through biochemical and molecular analyses of several revertants of the w4-m allele, we have shown that the W4 locus encodes dihydroflavonol-4-reductase 2 (DFR2). w4-m has arisen through insertion of Tgm9, a 20,548-bp CACTA-like transposable element, into the second intron of DFR2. Tgm9 showed high nucleic acid sequence identity to Tgmt*. Its 5′ and 3′ terminal inverted repeats start with conserved CACTA sequence. The 3′ subterminal region is highly repetitive. Tgm9 carries TNP1- and TNP2-like transposase genes that are expressed in the mutable line, T322 (w4-m). The element excises at a high frequency from both somatic and germinal tissues. Following excision, reinsertions of Tgm9 into the DFR2 promoter generated novel stable alleles, w4-dp (dilute purple flowers) and w4-p (pale flowers). We hypothesize that the element is fractured during transposition, and truncated versions of the element in new insertion sites cause stable mutations. The highly active endogenous transposon, Tgm9, should facilitate genomics studies specifically that relate to legume biology.IN soybean [Glycine max (L.) Merr.], five loci W1, W3, W4, Wm, and Wp control the pigmentations in flowers and hypocotyls (Palmer et al. 2004). Soybean plants with genotype W1_ w3w3 W4_ Wm_ Wp_ produce wild-type purple flowers (Figure 1) and purple hypocotyls. Mutations at the W4 locus in the W1_ background result in altered pigment accumulation patterns in petals and reduced levels of purple pigments in flowers and hypocotyls. Four mutant alleles, w4, w4-m, w4-dp, and w4-p have been mapped to this locus. The w4 allele represents a spontaneous mutation, which produces near-white flowers (Figure 1) and green hypocotyls (Hartwig and Hinson 1962; Groose and Palmer 1991). The w4-m allele was identified from a cross between two experimental breeding lines with white and purple flowers, respectively (Palmer et al. 1989; Weigelt et al. 1990). w4-m is characterized by variegated flowers (Figure 1) and green hypocotyls with purple sectors (Groose et al. 1988).Open in a separate windowFigure 1.—Variation in flower color among soybean lines carrying different W4 alleles.w4-m has been proposed to harbor a class II transposable element (Palmer et al. 1989). Presumably, somatic excision of the putative transposable element results in the variegated (Groose et al. 1988) and germinal excision wild-type phenotypes, purple flowers and purple pigments on hypocotyls (Palmer et al. 1989; Groose et al. 1990). The mutable line carrying w4-m undergoes germinal reversion at a very high frequency, about 6% per generation (Groose et al. 1990). Approximately 1% of the progeny derived from germinal revertants contain new mutations in unlinked loci, presumably resulting from reinsertion of the element (Palmer et al. 1989). For example, female partial-sterile 1 (Fsp1), female partial-sterile 2 (Fsp2), female partial-sterile 3 (Fsp3), and female partial-sterile 4 (Fsp4) were isolated from progenies of germinal revertants with purple flowers and were mapped to molecular linkage groups (MLG) C2, A2, F, and G, respectively (Kato and Palmer 2004). Similarly, 36 male-sterile, female-sterile mutants mapped to the st8 region on MLG J (Kato and Palmer 2003; Palmer et al. 2008a), 24 necrotic root (rn) mutants mapped to the rn locus on MLG G (Palmer et al. 2008b), and three Mdh1-n y20 mutants, mapped to a chromosomal region on MLG H (Palmer et al. 1989; Xu and Palmer 2005b), were isolated among progenies of germinal revertants.In addition to germinal revertants with purple flowers, the w4 mutable line also generated intermediate stable revertants that produce flowers with variable pigment intensities ranging from purple to near-white (Figure 1). Two stable intermediate revertants, w4-dp and w4-p, are allelic to W4. Plants carrying w4-dp or w4-p alleles produce dilute purple flowers or pale flowers, respectively (Figure 1) (Palmer and Groose 1993; Xu and Palmer 2005a).Pigment formation requires two types of genes: structural genes that encode anthocyanin biosynthetic enzymes [e.g., CHS (chalcone synthase), F3H (flavanone 3-hydroxylase), DFR (dihydroflavonol-4-reductase), ANS (anthocyanidin synthase); Figure S1] and regulatory genes that control expression of structural genes (Holton and Cornish 1995). Among the five genes, W1, W3, W4, Wp, and Wm, controlling pigment biosynthesis in soybean, four have been characterized at the molecular level (Figure S1). W1 encodes a flavonoid 5′, 3′-hydroxylase (Zabala and Vodkin 2007). W3 cosegregates with a DFR gene, Wp encodes a flavonone 3-hydroxylase (F3H), and Wm encodes a flavonol synthase (FLS) (Fasoula et al. 1995; Zabala and Vodkin 2005; Takahashi et al. 2007).Nine CACTA-type class II transposable elements, Tgm1, Tgm2, Tgm3, Tgm4, Tgm5, Tgm6, Tgm7, Tgm-Express1, and Tgmt*, have been reported in soybean (Rhodes and Vodkin 1988; Zabala and Vodkin 2005, 2008). Tgm-Express1 causes mutation in Wp (Zabala and Vodkin 2005) and Tgmt* (EU190440) in T that encodes a flavonoid 3′ hydroxylase (F3′H) (Zabala and Vodkin 2003, 2008). The objectives of the present study were to characterize the W4 locus and then investigate whether the w4-m allele harbors an active transposable element. Our results showed that a CACTA-like transposable element located in a dihydroflavonol-4-reductase gene causes variegated flower phenotype in soybean.  相似文献   

9.
The phage lambda-derived Red recombination system is a powerful tool for making targeted genetic changes in Escherichia coli, providing a simple and versatile method for generating insertion, deletion, and point mutations on chromosomal, plasmid, or BAC targets. However, despite the common use of this system, the detailed mechanism by which lambda Red mediates double-stranded DNA recombination remains uncertain. Current mechanisms posit a recombination intermediate in which both 5′ ends of double-stranded DNA are recessed by λ exonuclease, leaving behind 3′ overhangs. Here, we propose an alternative in which lambda exonuclease entirely degrades one strand, while leaving the other strand intact as single-stranded DNA. This single-stranded intermediate then recombines via beta recombinase-catalyzed annealing at the replication fork. We support this by showing that single-stranded gene insertion cassettes are recombinogenic and that these cassettes preferentially target the lagging strand during DNA replication. Furthermore, a double-stranded DNA cassette containing multiple internal mismatches shows strand-specific mutations cosegregating roughly 80% of the time. These observations are more consistent with our model than with previously proposed models. Finally, by using phosphorothioate linkages to protect the lagging-targeting strand of a double-stranded DNA cassette, we illustrate how our new mechanistic knowledge can be used to enhance lambda Red recombination frequency. The mechanistic insights revealed by this work may facilitate further improvements to the versatility of lambda Red recombination.OVER the past decade, lambda Red recombination (“recombineering”) has been used as a powerful technique for making precisely defined insertions, deletions, and point mutations in Escherichia coli, requiring as few as 35 bp of homology on each side of the desired alteration (Thomason et al. 2007a; Sharan et al. 2009). With this system, single-stranded DNA (ssDNA) oligonucleotides have been used to efficiently modify E. coli chromosomal targets (Ellis et al. 2001; Costantino and Court 2003), BACs (Swaminathan et al. 2001), and plasmids (Thomason et al. 2007b), as well as to rapidly optimize a metabolic pathway coding for the production of lycopene (Wang et al. 2009). Furthermore, linear double-stranded DNA (dsDNA) recombineering has been used to replace chromosomal genes (Murphy 1998; Murphy et al. 2000), to disrupt gene function (Datsenko and Wanner 2000), and to develop novel cloning methods (Lee et al. 2001; Li and Elledge 2005). Large-scale dsDNA recombineering projects include creating a library of single-gene knockout E. coli strains (Baba et al. 2006) and removing 15% of the genomic material from a single E. coli strain (Posfai et al. 2006). Linear dsDNA recombineering has also been used to insert heterologous genes and entire pathways into the E. coli chromosome (Zhang et al. 1998; Wang and Pfeifer 2008) and BACs (Lee et al. 2001; Warming et al. 2005), including those used for downstream applications in eukaryotes (Chaveroche et al. 2000; Bouvier and Cheng 2009). However, despite the broad use of this method, the mechanism of lambda Red recombination has not achieved scientific consensus, particularly in the case of dsDNA recombination. A clearer understanding of the mechanism underlying this process could suggest ways to improve the functionality, ease, and versatility of lambda Red recombination.Three phage-derived lambda Red proteins are necessary for carrying out dsDNA recombination: Gam, Exo, and Beta. Gam prevents the degradation of linear dsDNA by the E. coli RecBCD and SbcCD nucleases; lambda exonuclease (Exo) degrades dsDNA in a 5′ to 3′ manner, leaving single-stranded DNA in the recessed regions; and Beta binds to the single-stranded regions produced by Exo and facilitates recombination by promoting annealing to the homologous genomic target site (Sawitzke et al. 2007). Current mechanisms claim that Exo binds to both 5′ ends of the dsDNA and degrades in both directions simultaneously to produce a double-stranded region flanked on both sides by 3′ overhangs (Sharan et al. 2009; Szczepanska 2009). However, a comprehensive explanation of how this construct ultimately recombines with the chromosome has not yet been advanced.Initially, it was proposed that this recombination occurs via strand invasion (Thaler et al. 1987). However, it has more recently been shown that strand invasion is unlikely to be the dominant mechanism in the absence of long regions of homology, as recombination remains highly proficient in a recA- background (Yu et al. 2000). Furthermore, a detailed analysis of lambda Red recombination products showed characteristics consistent with strand annealing rather than a strand invasion model (Stahl et al. 1997). Finally, lambda Red dsDNA recombination has been shown to preferentially target the lagging strand during DNA replication, which suggests strand annealing rather than strand invasion (Lim et al. 2008; Poteete 2008).To explain these results, Court et al. (2002) proposed a strand-annealing model for insertional dsDNA recombination (Figure 1A), in which one single-stranded 3′ end anneals to its homologous target at the replication fork. The replication fork then stalls, due to the presence of a large dsDNA nonhomology (i.e., the insertion cassette). The stalled replication fork is ultimately rescued by the other replication fork traveling in the opposite direction around the circular bacterial chromosome. The other 3′ end of the recombinogenic DNA anneals to the homology region exposed by the second replication fork, forming a crossover structure, which is then resolved by unspecified E. coli enzymes (Court et al. 2002).Open in a separate windowFigure 1.—Previously proposed lambda Red-mediated dsDNA recombination mechanisms. Heterologous dsDNA is shown in green; Exo is an orange oval, and Beta is a yellow oval. In both mechanisms the recombination intermediate is proposed to be a dsDNA core flanked on either side by 3′ ssDNA overhangs. (A) The Court mechanism posits that (1) Beta facilitates annealing of one 3′ overhang to the lagging strand of the replication fork. (2) This replication fork then stalls and backtracks so that the leading strand can template switch onto the synthetic dsDNA. The heterologous dsDNA blocks further replication from this fork. (3) Once the second replication fork reaches the stalled fork, the other 3′ end of the integration cassette is annealed to the lagging strand in the same manner as prior. Finally, the crossover junctions must be resolved by unspecified E. coli enzymes (Court et al. 2002). (B) The Poteete mechanism suggests that (1) Beta facilitates 3′ overhang annealing to the lagging strand of the replication fork and (2) positions the invading strand to serve as the new template for leading-strand synthesis. This structure is resolved by an unspecified host endonuclease (red triangle), and (3) the synthetic dsDNA becomes template for both lagging and leading-strand synthesis. A second template switch must then occur at the other end of the synthetic dsDNA (Poteete 2008). The figure was adapted from the references cited.The Court mechanism was challenged by Poteete (2008), who showed that the dsDNA recombination of a linear lambda phage chromosome occurs readily onto a unidirectionally replicating plasmid, which does not have the second replication fork required by the Court mechanism (Court et al. 2002). Thus, Poteete proposed an alternate mechanism (Poteete 2008), termed “replisome invasion” (Figure 1B), in which a 3′ overhang of the Exo-processed dsDNA first anneals to its complementary sequence on the lagging strand of the recombination target. Subsequently, this overhang displaces the leading strand, thereby serving as the new template for leading-strand synthesis. The resulting structure is resolved by an unspecified endonuclease, after which the recombinogenic DNA becomes the template for the synthesis of both new strands. In the context of recombineering using a linear dsDNA cassette, the author indicates that a second strand-switching event must occur at the other end of the incoming dsDNA.While Poteete''s mechanism addresses some of the weaknesses of the Court mechanism, it remains largely speculative. This mechanism does not identify the endonuclease responsible for resolving the structure after the first template switching event, nor does it explain how the recombinogenic DNA and replication machinery form a new replication fork. Additionally, this template-switching mechanism would have to operate two times in a well-controlled manner, which may not be consistent with the high-recombination frequencies often observed (Murphy et al. 2000) for lambda Red-mediated dsDNA insertion. Finally, little experimental evidence has been advanced to directly support this hypothesis.To address the deficiencies in these mechanisms, we propose that lambda Red dsDNA recombination proceeds via a ssDNA intermediate rather than a dsDNA core flanked by 3′ overhangs (Figure 2). In this mechanism, Exo binds to one of the two dsDNA strands and degrades that strand completely, leaving behind full-length ssDNA. This ssDNA then anneals to its homology target at the lagging strand of the replication fork and is incorporated as part of the newly synthesized strand as if it were an Okazaki fragment. This process is analogous to the accepted mechanism for the lambda Red-mediated recombination of ssDNA oligonucleotides (Court et al. 2002) and, therefore, unifies the mechanisms for ssDNA and dsDNA recombination. Notably, our mechanism uses one replication fork for the incorporation of a full-length heterologous cassette, thereby addressing Poteete''s criticism of the Court mechanism.Open in a separate windowFigure 2.—Lambda Red mediated dsDNA recombination proceeds via a ssDNA intermediate. Instead of a recombination intermediate involving dsDNA flanked by 3′-ssDNA overhangs, we propose that one strand of linear dsDNA is entirely degraded by Exo (orange oval). Beta (yellow oval) then facilitates annealing to the lagging strand of the replication fork in place of an Okazaki fragment. The heterologous region does not anneal to the genomic sequence. This mechanism could account for gene replacement (as shown) or for insertions in which no genomic DNA is removed.The degradation of an entire strand by lambda Exo is feasible, given the highly processive nature of the enzyme (Subramanian et al. 2003). Whereas previously proposed mechanisms assume that both dsDNA ends are degraded approximately simultaneously, our hypothesis implies that some dsDNA molecules will be entirely degraded to ssDNA before a second Exo can bind to the other end. In this article, we demonstrate that single-stranded DNA is a viable recombinogenic intermediate with lagging-strand bias. Furthermore, we show that genetic information from one strand of a recombinogenic dsDNA cassette cosegregates during lambda Red-mediated recombination. These results provide strong support of our proposed mechanism.  相似文献   

10.
Sylvain Glémin 《Genetics》2010,185(3):939-959
GC-biased gene conversion (gBGC) is a recombination-associated process mimicking selection in favor of G and C alleles. It is increasingly recognized as a widespread force in shaping the genomic nucleotide landscape. In recombination hotspots, gBGC can lead to bursts of fixation of GC nucleotides and to accelerated nucleotide substitution rates. It was recently shown that these episodes of strong gBGC could give spurious signatures of adaptation and/or relaxed selection. There is also evidence that gBGC could drive the fixation of deleterious amino acid mutations in some primate genes. This raises the question of the potential fitness effects of gBGC. While gBGC has been metaphorically termed the “Achilles'' heel” of our genome, we do not know whether interference between gBGC and selection merely has practical consequences for the analysis of sequence data or whether it has broader fundamental implications for individuals and populations. I developed a population genetics model to predict the consequences of gBGC on the mutation load and inbreeding depression. I also used estimates available for humans to quantitatively evaluate the fitness impact of gBGC. Surprising features emerged from this model: (i) Contrary to classical mutation load models, gBGC generates a fixation load independent of population size and could contribute to a significant part of the load; (ii) gBGC can maintain recessive deleterious mutations for a long time at intermediate frequency, in a similar way to overdominance, and these mutations generate high inbreeding depression, even if they are slightly deleterious; (iii) since mating systems affect both the selection efficacy and gBGC intensity, gBGC challenges classical predictions concerning the interaction between mating systems and deleterious mutations, and gBGC could constitute an additional cost of outcrossing; and (iv) if mutations are biased toward A and T alleles, very low gBGC levels can reduce the load. A robust prediction is that the gBGC level minimizing the load depends only on the mutational bias and population size. These surprising results suggest that gBGC may have nonnegligible fitness consequences and could play a significant role in the evolution of genetic systems. They also shed light on the evolution of gBGC itself.GC-BIASED gene conversion (gBGC) is increasingly recognized as a widespread force in shaping genome evolution. In different species, gene conversion occurring during double-strand break recombination repair is thought to be biased toward G and C alleles. In heterozygotes, GC alleles undergo a kind of molecular meiotic drive that mimics selection (reviewed in Marais 2003). This process can rapidly increase the GC content, especially around recombination hotspots (Spencer et al. 2006), and, more broadly, can affect genome-wide nucleotide landscapes (Duret and Galtier 2009a). For instance, it is thought to play a role in shaping isochore structure evolution in mammals (Galtier et al. 2001; Meunier and Duret 2004; Duret et al. 2006) and birds (Webster et al. 2006). Direct experimental evidence of gBGC mainly comes from studies in yeast (Birdsell 2002; Mancera et al. 2008; but see Marsolier-Kergoat and Yeramian 2009) and humans (Brown and Jiricny 1987). However, associations between recombination and the nucleotide landscape and frequency spectra biased toward GC alleles provide indirect evidence in very diverse organisms (
OrganismsDirect evidenceIndirect evidenceAchille''s heel evidenceReferences
YeastMeiotic segregation biasMancera et al. (2008)
Mitotic and mitotic heteromismatch correction biasCorrelation between GC and recombinationBirdsell (2002)
MammalsMitotic heteromismatch correction biasBrown and Jiricny (1987)
Correlation between GC*/GC and recombinationDuret and Arndt (2008); Meunier and Duret (2004)
Biased frequency spectrum toward GC allelesGaltier et al. (2001); Spencer et al. (2006)
GC bias associated with high dN/dS near recombination hotspotBerglund et al. (2009; Galtier et al. (2009)
BirdsCorrelation between GC and recombinationInternational Chicken Genome Sequencing Consortium (2004)
TurtlesCorrelation between GC and chromosome sizeKuraku et al. (2006)
DrosophilaCorrelation between GC and recombinationMarais et al. (2003)
Biased frequency spectrum toward GC allelesGaltier et al. (2006)
NematodesCorrelation between GC and recombinationMarais et al. (2001)
GrassesCorrelation between GC and outcrossing/selfingGlémin et al. (2006)
Correlation between GC* and recombination and outcrossing/selfingOutcrossing increases dN/dS for genes with high GC*Haudry et al. (2008)
Green algaeCorrelation between GC and recombinationJancek et al. (2008)
ParameciumCorrelation between GC and chromosome sizeDuret et al. (2008)
Open in a separate windowThe impact of gBGC on noncoding sequences and synonymous sites has been studied in depth, especially because of confounding effects with selection on codon usage (Marais et al. 2001). More recently, Galtier and Duret (2007) pointed out that gBGC may also interfere with selection when affecting functional sequences. They argued that gBGC could leave spurious signatures of adaptive selection and proposed to extend the null hypothesis of molecular evolution. Indeed, gBGC can lead to a ratio of nonsynonymous (dN) over synonymous (dS) substitutions above one (Berglund et al. 2009; Galtier et al. 2009), i.e., a typical signature of positive selection (Nielsen 2005). This hypothesis has been widely debated for human-accelerated regions (HARs). These regions are extremely conserved across mammals but show evidence of accelerated evolution along the human lineage, which has been interpreted as evidence of positive selection (Pollard et al. 2006a,b; Prabhakar et al. 2006, 2008). On the contrary, other authors argued that patterns observed in HARs, such as the AT → GC substitution bias, the absence of a selective sweep signature, or the propensity to occur within or close to recombination hotspots, are more likely explained by gBGC rather than positive selection (Galtier and Duret 2007; Berglund et al. 2009; Duret and Galtier 2009b; but see also Pollard et al. 2006a who also suggested that gBGC might play a role in HARs evolution). It is thus crucial to take gBGC into account when interpreting genomic data.Moreover, Galtier and Duret (2007) initially suggested that gBGC hotspots could contribute to the fixation of slightly deleterious AT → GC mutations and could represent the Achilles'' heel of our genome. This hypothesis was reinforced later in primates, with evidence of gBGC-driven fixation of deleterious mutations in proteins (Galtier et al. 2009). A similar result was also found in some grass species, whose genomes are also supposed to be affected by gBGC (Glémin et al. 2006). Haudry et al. (2008) compared two outcrossing and two selfing grass species and showed that GC-biased genes exhibit higher dN/dS ratio in outcrossing than in selfing lineages. The reverse pattern would be expected under pure selective models because of the reduced selection efficacy in selfers (Charlesworth 1992; Glémin 2007). This pattern is in agreement with a genomic Achilles'' heel associated with outcrossing, while gBGC is inefficient in selfing species because they are mainly homozygous.Twenty years ago, Bengtsson (1990) already pointed out that biased conversion can generally affect the mutation load. The mutation load is the reduction in the mean fitness of a population due to mutation accumulation, which could lead to population extinction if it is too high (Lynch et al. 1995). At this time, Bengtsson concluded that “it is impossible to know if biased conversion plays a major role in determining the magnitude of the mutation load in organisms such as ourselves, but the possibility must be considered and further investigated (Bengtsson 1990, p. 186).” Now, one can propose gBGC could be such a widespread biased conversion process. It thus appears timely to thoroughly investigate the fitness consequences of gBGC through its potential effects on the dynamics of deleterious mutations. The fitness consequences of gBGC were also pointed out as a major future issue to be addressed by Duret and Galtier (2009a). In addition to the load, deleterious mutations have many other evolutionary consequences (for review see Charlesworth and Charlesworth 1998). They are thought to be the main determinant of inbreeding depression, i.e., the reduction in fitness of inbred individuals compared to outbred ones. They also play a key role in the evolution of genetic systems (sexual reproduction and recombination, inbreeding avoidance mechanisms, ploidy cycles), of senescence, or in the degeneration of nonrecombining regions, such as Y chromosomes. So far, we know little, if anything, about how gBGC might affect these processes.In his seminal work, Bengtsson (1990) did not address several important points. First, he did not include genetic drift in his model. Nearly neutral mutations, for which drift and selection are of similar intensities, are the most damaging ones because they can drift to fixation, unlike strongly deleterious mutations that are maintained at low frequency (Crow 1993; Lande 1994, 1998). While gBGC intensities are rather weak (Birdsell 2002; Spencer et al. 2006), they could markedly affect the fate of nearly neutral mutations (see also Galtier et al. 2009). Second, Bengtsson did not study the effect of gene conversion on inbreeding depression, while he showed that recessive mutations, mostly involved in inbreeding depression, are the most affected by gene conversion. Third, he did not envisage systematic GC bias with its opposite effects on A/T and G/C deleterious alleles. Fourth, while he noted that selfing affects both the efficacy of selection and that of conversion, he did not fully investigate the effect of mating systems. On one hand, selfing is efficient in purging strongly deleterious mutations causing inbreeding depression. However, since selfing is expected to increase drift, weakly deleterious mutations can fix in selfing species, contributing to the so-called “drift load” (Charlesworth 1992; Glémin 2007). Self-fertilizing populations are thus expected to exhibit low inbreeding depression and high drift load. On the other hand, gBGC, and thus its cost, vanishes as the selfing rate and homozygosity increase (Marais et al. 2004). gBGC could thus challenge classical views on mating systems and it was even speculated that gBGC could affect their evolution (Haudry et al. 2008).Here I present a population genetics model that includes mutation, selection, drift, and gBGC, which extends previous studies (Gutz and Leslie 1976; Lamb and Helmi 1982; Nagylaki 1983a,b; Bengtsson 1990). I specifically examine how gBGC can affect inbreeding depression and the mutation load. I also focus on the effect of mating system, which is especially interesting with regard to the interaction between biased conversion and selection. Finally, I discuss how these results could give insight into how gBGC evolved.

Impacts of gBGC on inbreeding depression:

Inbreeding depression is defined as the reduction in fitness of selfed (and more generally inbred) individuals compared to outcrossed individuals,(15)where and are the mean fitness of outcrosses and selfcrosses, respectively (Charlesworth and Charlesworth 1987; Charlesworth and Willis 2009). The approximation is very good in most conditions, because under weak (s ≪ 1) and strong selection (x ≪ 1) (see Glémin et al. 2003). Similar to the load, considering both sites for which either S or W alleles are deleterious, in proportion q and 1 – q, respectively, we get(16)
gBGC and the genetic basis of inbreeding depression in panmictic populations:
In infinite panmictic populations without gBGC, inbreeding depression depends only on mutation rates and dominance levels. Partially recessive mutations () contribute only to inbreeding depression, and the more recessive they are, the higher the inbreeding depression (Charlesworth and Charlesworth 1987). In finite populations, deterministic results hold for strongly deleterious mutations (s ≫ 1/Ne), which contribute mostly to inbreeding depression. Contrary to the load, weakly deleterious mutations (∼s ≤ 1/Ne) contribute little to inbreeding depression (Figure 4, a and c, and see Bataillon and Kirkpatrick 2000).Open in a separate windowFigure 4.—Inbreeding depression (×106) as a function of s without (a and c) or with (b and d) gBGC (b = 0.0002). (a and b) h = 0.2: thick lines, N = 5000; thin lines, N = 10,000; dashed lines, N = 50,000; dotted lines, N = 100,000. (c and d) N = 10,000: thick lines, h = 0.4; thin lines, h = 0.2; dashed lines, h = 0.1; dotted lines, h = 0.05. u = 10−6, λ = 2.Like the load, gBGC affects both the magnitude and the structure of inbreeding depression. In infinite populations, and more generally for strongly deleterious alleles (Nes ≫ 1), replacing x by xeq given by Equations 4 in Equations 15 and 16 leads to(17a)(17b)(17c)The effect of gBGC on inbreeding depression is not monotonic. Like the load, gBGC increases inbreeding depression if b > hs(1 − 2q/(q + λ − qλ)). However, contrary to the load, a strong gBGC decreases inbreeding depression, which tends to 0 as b increases, while the load tends to qs (Equation 10c). An analysis of Equation 17b shows that mutations that maximize inbreeding depression are those that also maximize the load, i.e., S deleterious mutations with s ≈ 2b.In finite populations, inbreeding depression must be integrated over the Φ distribution, which leads to(18)(see also Glémin et al. 2003). While it is not possible to get an analytical expression of (18), numerical computations (see appendix b) show that S deleterious mutations with s ≈ 2b also maximize inbreeding depression in finite populations (Figure 4). More broadly, inbreeding depression is maximal under the overdominant-like selection regime (gray area in Figure 2). Once again, even low to moderate gBGC markedly affects the genetic structure of inbreeding depression. First, mutations of intermediate effects contribute the most to inbreeding depression, i.e., up to one order of magnitude higher than strongly deleterious mutations (compare Figure 4a with 4b). Second, even nearly additive mutations can have a substantial effect (compare Figure 4c with 4d).Since little is known about the distribution of dominance coefficients, especially the dominance of mildly deleterious mutations (of the order of b), it is difficult to quantitatively predict the full impact of gBGC on inbreeding depression. We can conclude that, on average, gBGC should increase inbreeding depression. However, further insight into mutational parameters is crucial to assess the quantitative impact of gBGC.

Joint effect of gBGC and mating system on the load and inbreeding depression:

Selfing, or more generally inbreeding, slightly reduces the segregating load through the purging of recessive mutations (Ohta and Cockerham 1974), but can substantially increase the fixation load because of the effective population size reduction under inbreeding: (see above and Pollak 1987; Nordborg 1997; Glémin 2007). In numerical examples, I assumed that α decreases with F according to the background selection model (Charlesworth et al. 1993; Nordborg et al. 1996), as in Glémin (2007). With gBGC, selfing thus has two opposite effects on the fixation load. Selfing increases the drift load sensu stricto but decreases the fixation load due to gBGC. A surprising consequence is that the load can be higher in outcrossing than in selfing populations (Figure 5). Quantitatively this is also expected, even with a gBGC hotspot affecting just 3% of the genome (Figure 5 and Open in a separate windowFigure 5.—Effective population size (a and b) and the load (×106) (c–f) as a function of F for different gBGC intensities (thick lines, b = 0; thin lines, b = 0.0001; dashed lines, b = 0.0002; dotted lines, b = 0.0005). The effective population size depends on F under the background selection (BS) model (Charlesworth et al. 1993), using Equations 16 and 17 in Glémin (2007): , where U is the genomic deleterious mutation rate, R is the genomic recombination rate, sd is the mean selection coefficient against strongly deleterious mutations, and hd is their dominance coefficient. N = 10,000, U = 0.2, hd = 0.1, and sd = 0.05. (a, c, and e) R = 5, “weak” BS; (b, d, and f) R = 0.5, “strong” BS. (c and d) Load averaged over half GC and half AT deleterious alleles, with a bias in favor of AT alleles. (e and f) Load averaged over 10% of GC deleterious alleles and 90% of AT deleterious alleles with a bias in favor of AT alleles; see Figure 3. h = 0.5, u = 10−6, and λ = 2.Generally, the effect of selfing is simpler for inbreeding depression. Purging, Ne reduction, and suppression of gBGC contribute to decreasing inbreeding depression in selfing populations (Figure 6a). However, there are special cases in which maximum inbreeding depression is reached for intermediate selfing rates (Figure 6b). In such cases, in outcrossing populations, gBGC is strong enough to sweep polymorphism out and reduce inbreeding depression (b > s, regime 1 in Figure 2). As the selfing rate increases, gBGC declines, and the selection dynamics become overdominant-like (regime 2, Figure 2), thus maximizing inbreeding depression. For high selfing rates, gBGC vanishes (regime 3 in Figure 2) and deleterious alleles are either purged or fixed if there is substantial drift. This is similar to the effect of selfing on inbreeding depression caused by asymmetrical overdominance, where inbreeding depression also peaks for intermediate selfing rates (Ziehe and Roberds 1989; Charlesworth and Charlesworth 1990). In the present case, the range of parameters leading to this peculiar behavior is narrow because the overdominant-like region depends on the selfing rates and can vanish either for low or for high selfing rates (Figure 2).Open in a separate windowFigure 6.—Inbreeding depression (×106) as a function of F for different gBGC intensities (thick lines, b = 0; thin lines, b = 0.0001; dashed lines, b = 0.0002; dotted lines, b = 0.0005). Inbreeding depression is averaged over half GC and half AT deleterious alleles. The effective population size depends on F as in Figure 5 (same parameters). (a) s = 0.002; (b) s = 0.0005; (c) s = 0.0002. h = 0.2, u = 10−6, and λ = 2.

Minimum load and the evolution of gBGC and recombination landscapes:

Although gBGC may have deleterious fitness consequences, it is surprising that it evolved in many taxa (Duret and Galtier 2009a). Birdsell (2002) initially suggested that gBGC may have evolved as a response to mutational bias toward AT (λ > 1, here). Indeed, I show that a minimum load is reached for weak gBGC (b ≈ ln(λ)/4N, Equation 14). This result is very general whatever the distribution of fitness effects of mutations (appendix d). However, the range of optimal gBGC is narrow, and gBGC increases the load as far as b > ln(λ)/2N (appendix c). In humans, using N = 10,000 and λ = 2, gBGC levels that minimize the load are ∼1.17 × 10−5, i.e., one order of magnitude lower than the average bias observed in recombination hotspots (Myers et al. 2005). However, selection on conversion modifiers will not necessarily minimize the load because of gametic disequilibrium generated between modifiers and fitness loci (Bengtsson and Uyenoyama 1990). Selection for limitation of somatic AT-biased mutations could also have selected for GC-biased mismatch repair machinery (Brown and Jiricny 1987). If the bias level that would be selected for somatic reasons is >ln(λ)/2N, a side effect would be the generation of a substantial load at the population level. Finally, it is interesting to note that when synonymous codon positions are under selection for translation accuracy, optimal gBGC levels can be higher than gBGC levels that minimize the protein load, especially when most optimal codons end in G or C ().Conversely, gBGC could also affect the evolution of recombination landscapes, which could evolve to reduce the gBGC load. Surprisingly, for a given recombination/conversion level, the hotspot distribution does not appear to be optimal (Nishant and Rao 2005), one can speculate that the hotspot localization outside genes could be a response to avoid the deleterious effects of gBGC.Up to now, these verbal arguments have not been assessed theoretically (but see Bengtsson and Uyenoyama 1990 for a different kind of conversion bias). Population genetics models are necessary to test these hypotheses concerning the evolution of gBGC and recombination landscapes and to pinpoint the key parameters that might govern their evolution.

gBGC and the evolution of mating systems:

Deleterious mutations also play a crucial role in the evolution of mating systems. They are the main source of inbreeding depression, which balances the automatic advantage of selfing. The drift load is also thought to contribute to the extinction of selfing species. Since they are mainly homozygous, selfing species are mostly free from gBGC and its deleterious impacts. I discuss below how this might affect the evolution of mating systems.
Inbreeding depression and the shift in mating systems:
Inbreeding depression plays a key role in the evolution of mating systems (Charlesworth and Charlesworth 1987; Charlesworth 2006b). Since it balances the automatic advantage of selfing, high inbreeding depression favors outcrossing, while selfing can evolve when it is low. Moreover, selfing helps to purge strongly deleterious mutations, thus decreasing inbreeding depression. This positive feedback reinforces the disruptive selection on the selfing rate and prevents the transition from selfing to outcrossing (Lande and Schemske 1985).Theoretical results suggest that, in most conditions, gBGC would reinforce inbreeding depression in outcrossing populations (Figure 6), which would prevent the evolution of selfing. In reverse, if selfing is initially selected for, recurrent selfing would reduce the load through both purging and avoidance of gBGC. Under this scenario, gBGC would reinforce disruptive selection on mating systems. However, under some conditions (see Figure 6), inbreeding depression peaks at intermediate selfing rates, as observed for asymmetrical overdominance (Ziehe and Roberds 1989; Charlesworth and Charlesworth 1990). In theory, this could prevent the shift toward complete selfing and maintain stable mixed mating systems (Charlesworth and Charlesworth 1990; Uyenoyama and Waller 1991). However, this pattern is observed under restrictive conditions and it is very unlikely on the whole-genome scale. Dominance patterns are crucial for predicting inbreeding depression, especially with gBGC. Contrary to the load, it is thus difficult to evaluate the quantitative impact of gBGC on inbreeding depression. However, increased inbreeding depression in outcrossing species subject to gBGC seems to be the most likely scenario.
gBGC and the long-term evolution of mating systems:
In the long term, the gBGC-induced load also challenges the “dead-end hypothesis,” which posits that, because of the reduction of selection efficacy, self-fertilizing species would accumulate weakly deleterious mutations in the long term, eventually leading to extinction (Takebayashi and Morrell 2001). Because of gBGC, not drift, outcrossing species could also accumulate a load of weakly deleterious mutations (Figure 7), and they could suffer from a higher load than highly self-fertilizing species (Haudry et al. (2008) found that in two outcrossing grass species, but not in two self-fertilizing ones, the dN/dS ratio is significantly higher for genes exhibiting GC enrichment. They speculated that substitutions in these genes might contribute to increasing the load in these two outcrossing grass species. Such results are still very sparse. In plants, evidence of strong gBGC is mainly restricted to grasses (but see Wright et al. 2007). It will be necessary to conduct more in-depth studies to assess the phylogenetic distribution of gBGC in plants and other hermaphrodite organisms and to further test the genomic Achilles'' heel hypothesis in relation to mating systems. While theoretically possible, the quantitative effect of gBGC on the evolution of mating systems remains a new, open, and challenging question.

Conclusion:

I showed that the interaction between gBGC and selection might have surprising qualitative consequences on load and inbreeding depression patterns. Given the few quantitative data available on gBGC levels and selection intensities (mainly in humans), it turns out that even weak genome-wide gBGC can have significant fitness impacts. gBGC should be taken into account not only for sequence analyses (Berglund et al. 2009; Galtier et al. 2009), but also for its potential fitness consequences, for instance concerning genetic diseases. Interferences between gBGC and selection also give rise to new questions on the evolution of mating systems. However, most of the challenging conclusions given here have yet to be quantitatively evaluated. Quantification of gBGC and its interaction with selection in various organisms will be crucial in the future.  相似文献   

11.
Epithelial Polarity: Interactions Between Junctions and Apical–Basal Machinery          下载免费PDF全文
Nicole A. Kaplan  Xiaoping Liu  Nicholas S. Tolwinski 《Genetics》2009,183(3):897-904
Epithelial polarity is established and maintained by competition between determinants that define the apical and basolateral domains. Cell–cell adhesion complexes, or adherens junctions, form at the interface of these regions. Mutations in adhesion components as well as apical determinants normally lead to an expansion of the basolateral domain. Here we investigate the genetic relationship between the polarity determinants and adhesion and show that the levels of the adhesion protein Armadillo affect competition. We find that in arm mutants, even a modest reduction in the basolateral component lgl leads to a full apical domain expansion or lgl phenotype. By using an allelic series of Armadillo mutations, we show that there is a threshold at which basolateral expansion can be reversed. Further, in embryos lacking the Wingless signaling component zw3, the same full apical expansion occurs again with only a reduction in lgl. We propose a model where zw3 regulates protein levels of apical and adhesion components and suggest that a reciprocal interaction between junctions and polarity modules functions to maintain stable apical and basolateral domains.A major reason that epithelial cells require apical–basal polarity is to differentiate between the interior of the organism and the external environment. To accomplish this, epithelial cells generate molecularly distinct domains along their plasma membranes: an apical domain that is exposed to the outside, a basolateral domain that contacts the interior, and, in between, an adhesion complex that holds the cell sheet together. In Drosophila embryos, at least three polarity complexes are used to establish and maintain this subcellular organization commonly known as apical–basal cell polarity. On the apical side, the Crumbs (Crb) and Stardust (Std, Pals) proteins form one complex (Jurgens et al. 1984; Tepass et al. 1990; Tepass and Knust 1993; Wodarz et al. 1995; Muller and Wieschaus 1996). The second one is composed of Bazooka (Baz, Par-3), Par-6, and atypical protein kinase C (aPKC) (Wieschaus et al. 1984; Muller and Wieschaus 1996; Wodarz et al. 2000; Hutterer et al. 2004). On the opposite or basolateral side of the cell, Lethal giant larvae (Lgl), Discs large (Dlg), and Scribble (Scrib) determine the basolateral domain of the plasma membrane (Gateff and Schneiderman 1974; Mechler et al. 1985; Woods and Bryant 1989; Bilder and Perrimon 2000). In between the complexes lie the adherens junctions (AJ) composed of E-cadherin, Armadillo (Arm, β-catenin), and α-catenin (Oda et al. 1993, 1994; Peifer et al. 1993; Tepass et al. 1996).In Drosophila embryos, mutations that affect apical components often lead to the crumbs phenotype, where ectodermal cells lose integrity and many die through apoptosis. The surviving cells secrete cuticle in a discontinuous fashion, leaving pieces apparently floating within the eggshell (Tepass et al. 1990; Tanentzapf and Tepass 2003). This phenotype is also seen in embryos deficient for AJ proteins (Oda et al. 1993; Cox et al. 1996; Magie et al. 2002). On the other hand, mutations that affect the basolateral genes display a very different phenotype. Zygotic only (Z) mutants for scrib, lgl, and dlg have a significant maternal mRNA contribution that allows normal embryonic development to proceed. Phenotypes are observed only in larvae, which die with significantly overgrown imaginal discs (Gateff 1978; Bilder and Perrimon 2000). Removal of the maternal mRNA complement, as well as the zygotic contribution (M/Z) through the induction of germline clones, leads to a poorly differentiated and convoluted cuticle with a bubbly appearance (Figure 1) (Bilder et al. 2003; Tanentzapf and Tepass 2003).Open in a separate windowFigure 1.—Schema and cuticles representing wild-type vs. the opposing phenotypes of apical and basolateral expansion. (A) A wild-type cuticle shows rows of denticles separated by naked regions in a highly organized or patterned fashion. The apical determinants localize to the apical surface of cells, establishing the apical domain (green), the basolateral determinants localize to the basolateral surface of cells, establishing the basolateral domain (blue), and the adherens junctions (red) form at the interface between these two opposing regions. (B) The crumbs phenotype is observed when an apical determinant is mutated, causing an expansion of the basolateral domain. (C) The lgl phenotype, or bubble phenotype, is observed when a basolateral determinant is mutated, causing an expansion of the apical domain.These studies led to a comprehensive competition model where apical and basal components opposed each other (Figure 1, schema); however, a strangely neglected topic was the interaction of junctions and the apical and basal determinants. Therefore, we used a genetic approach to investigate the interaction of apical–basal polarity proteins and adherens junctions.  相似文献   

12.
RecG Protein and Single-Strand DNA Exonucleases Avoid Cell Lethality Associated With PriA Helicase Activity in Escherichia coli     
Christian J. Rudolph  Akeel A. Mahdi  Amy L. Upton  Robert G. Lloyd 《Genetics》2010,186(2):473-492
  相似文献   

13.
Novel Growth Regime of MDCK II Model Tissues on Soft Substrates     
Sara Kaliman  Christina Jayachandran  Florian Rehfeldt  Ana-Sun?ana Smith 《Biophysical journal》2014,106(7):L25-L28
It is well established that MDCK II cells grow in circular colonies that densify until contact inhibition takes place. Here, we show that this behavior is only typical for colonies developing on hard substrates and report a new growth phase of MDCK II cells on soft gels. At the onset, the new phase is characterized by small, three-dimensional droplets of cells attached to the substrate. When the contact area between the agglomerate and the substrate becomes sufficiently large, a very dense monolayer nucleates in the center of the colony. This monolayer, surrounded by a belt of three-dimensionally packed cells, has a well-defined structure, independent of time and cluster size, as well as a density that is twice the steady-state density found on hard substrates. To release stress in such dense packing, extrusions of viable cells take place several days after seeding. The extruded cells create second-generation clusters, as evidenced by an archipelago of aggregates found in a vicinity of mother colonies, which points to a mechanically regulated migratory behavior.Studying the growth of cell colonies is an important step in the understanding of processes involving coordinated cell behavior such as tissue development, wound healing, and cancer progression. Apart from extremely challenging in vivo studies, artificial tissue models are proven to be very useful in determining the main physical factors that affect the cooperativity of cells, simply because the conditions of growth can be very well controlled. One of the most established cell types in this field of research is the Madin-Darby canine kidney epithelial cell (MDCK), originating from the kidney distal tube (1). A great advantage of this polarized epithelial cell line is that it retained the ability for contact inhibition (2), which makes it a perfect model system for studies of epithelial morphogenesis.Organization of MDCK cells in colonies have been studied in a number of circumstances. For example, it was shown that in three-dimensional soft Matrigel, MDCK cells form a spherical enclosure of a lumen that is enfolded by one layer of polarized cells with an apical membrane exposed to the lumen side (3). These structures can be altered by introducing the hepatocyte growth factor, which induces the formation of linear tubes (4). However, the best-studied regime of growth is performed on two-dimensional surfaces where MDCK II cells form sheets and exhibit contact inhibition. Consequently, the obtained monolayers are well characterized in context of development (5), mechanical properties (6), and obstructed cell migration (7–9).Surprisingly, in the context of mechanics, several studies of monolayer formation showed that different rigidities of polydimethylsiloxane gels (5) and polyacrylamide (PA) gels (9) do not influence the nature of monolayer formation nor the attainable steady-state density. This is supposedly due to long-range forces between cells transmitted by the underlying elastic substrate (9). These results were found to agree well with earlier works on bovine aortic endothelial cells (10) and vascular smooth muscle cells (11), both reporting a lack of sensitivity of monolayers to substrate elasticity. Yet, these results are in stark contrast with single-cell experiments (12–15) that show a clear response of cell morphology, focal adhesions, and cytoskeleton organization to substrate elasticity. Furthermore, sensitivity to the presence of growth factors that are dependent on the elasticity of the substrate in two (16) and three dimensions (4) makes this result even more astonishing. Therefore, we readdress the issue of sensitivity of tissues to the elasticity of the underlying substrate and show that sufficiently soft gels induce a clearly different tissue organization.We plated MDCK II cells on soft PA gels (Young’s modulus E = 0.6 ± 0.2 kPa), harder PA gels (E = 5, 11, 20, 34 kPa), and glass, all coated with Collagen-I. Gels were prepared following the procedure described in Rehfeldt et al. (17); rigidity and homogeneity of the gels was confirmed by bulk and microrheology (see the Supporting Material for comparison). Seeding of MDCK II cells involved a highly concentrated solution dropped in the middle of a hydrated gel or glass sample. For single-cell experiments, cells were dispersed over the entire dish. Samples were periodically fixed up to Day 12, stained for nuclei and actin, and imaged with an epifluorescence microscope. Details are described in the Supporting Material.On hard substrates and glass it was found previously that the area of small clusters expands exponentially until the movement of the edge cannot keep up with the proliferation in the bulk (5). Consequently, the bulk density increases toward the steady state, whereas the density of the edge remains low. At the same time, the colony size grows subexponentially (5). This is what we denote “the classical regime of growth”. Our experiments support these observations for substrates with E ≥ 5 kPa. Specifically, on glass, colonies start as small clusters of very low density of 700 ± 200 cells/mm2 (Fig. 1, A and B), typically surrounded by a strong actin cable (Fig. 1, B and C). Interestingly, the spreading area of single cells (Fig. 1 A) on glass was found to be significantly larger, i.e., (2.0 ± 0.9) × 10−3 mm2. After Day 4 (corresponding cluster area of 600 ± 100 mm2), the density in the center of the colony reached the steady state with 6,800 ± 500 cells/mm2, whereas the mean density of the edge profile grew to 4,000 ± 500 cells/mm2. This density was retained until Day 12 (cluster area 1800 ± 100 mm2), which is in agreement with previous work (9).Open in a separate windowFigure 1Early phase of cluster growth on hard substrates. (A) Well-spread single cells, and small clusters with a visible actin cable 6 h after seeding. (B) Within one day, clusters densify and merge, making small colonies. (C) Edge of clusters from panel B.In colonies grown on 0.6 kPa gels, however, we encounter a very different growth scenario. The average spreading area of single cells is (0.34 ± 0.3) × 10−3 mm2, which is six times smaller than on glass substrates (Fig. 2 A). Clusters of only few cells show that cells have a preference for cell-cell contacts (a well-established flat contact zone can be seen at the cell-cell interface in Fig. 2 A) rather than for cell-substrate contacts (contact zone is diffusive and the shape of the cells appears curved). The same conclusion emerges from the fact that dropletlike agglomerates, resting on the substrate, form spontaneously (Fig. 2 A), and that attempts to seed one single cluster of 90,000 cells fail, resulting in a number of three-dimensional colonies (Fig. 2 A). When the contact area with the substrate exceeds 4.7 × 10−3 mm2, a monolayer appears in the center of such colonies (Fig. 2 B). The colonies can merge, and if individual colonies are small, the collapse into a single domain is associated with the formation of transient irregular structures (Fig. 2 B). Ultimately, large elliptical colonies (average major/minor axis of e = 1.8 ± 0.6) with a smooth edge are formed (Fig. 2 C), unlike on hard substrates where circular clusters (e = 1.06 ± 0.06) with a ragged edge comprise the characteristic phenotype.Open in a separate windowFigure 2Early phase of cluster growth on soft substrates. (A) Twelve hours after seeding, single cells remain mostly round and small. They are found as individual, or within small, three-dimensional structures (top). The latter nucleate a monolayer in their center (bottom), if the contact area with the substrate exceeds ∼5 × 10−3 mm2. (B) Irregularly-shaped clusters appear due to merging of smaller droplets. A stable monolayer surrounded by a three-dimensional belt of densely packed cells is clearly visible, even in larger structures. (C) All colonies are recorded on Day 4.Irrespective of cluster size, in the new regime of growth, the internal structure is built of two compartments (Fig. 2 B):
  • 1.The first is the edge (0.019 ± 0.05-mm wide), a three-dimensional structure of densely packed cells. This belt is a signature of the new regime because on hard substrates the edge is strictly two-dimensional (Fig. 1 C).
  • 2.The other is the centrally placed monolayer with a spatially constant density that is very weakly dependent on cluster size and age (Fig. 3). The mean monolayer density is 13,000 ± 2,000 cells/mm2, which is an average over 130 clusters that are up to 12 days old and have a size in the range of 10−3 to 10 mm2, each shown by a data point in Fig. 3. This density is twice the steady-state density of the bulk tissue in the classical regime of growth.Open in a separate windowFigure 3Monolayer densities in colonies grown on 0.6 kPa substrates, as a function of the cluster size and age. Each cluster is represented by a single data point signifying its mean monolayer density. (Black lines) Bulk and (red dashed lines) edge of steady-state densities from monolayers grown on glass substrates. Error bars are omitted for clarity, but are discussed in the Supporting Material.
Until Day 4, the monolayer is very homogeneous, showing a nearly hexagonal arrangement of cells. From Day 4, however, defects start to appear in the form of small holes (typical size of (0.3 ± 0.1) × 10−3 mm2). These could be attributed to the extrusions of viable cells, from either the belt or areas of increased local density in the monolayer (inset in Fig. 4). This suggests that extrusions serve to release stress built in the tissue, and, as a consequence, the overall density is decreased.Open in a separate windowFigure 4Cell nuclei within the mother colony and in the neighboring archipelago of second-generation clusters grown on 0.6 kPa gels at Day 12. (Inset; scale bar = 10 μm) Scar in the tissue, a result of a cell-extrusion event. (Main image; scale bar = 100 μm) From the image of cell nuclei (left), it is clear that there are no cells within the scar, whereas the image of actin (right) shows that the cytoplasm of the cells at the edge has closed the hole.Previous reports suggest that isolated MDCK cells undergo anoikis 8 h after losing contact with their neighbors (18). However, in this case, it appears that instead of dying, the extruded cells create new colonies, which can be seen as an archipelago surrounding the mother cluster (Fig. 4). The viability of off-cast cells is further evidenced by the appearance of single cells and second-generation colonies with sizes varying over five orders of magnitude, from Day 4 until the end of the experiment, Day 12. Importantly, no morphological differences were found in the first- and second-generation colonies.In conclusion, we show what we believe to be a novel phase of growth of MDCK model tissue on soft PA gels (E = 0.6 kPa) that, to our knowledge, despite previous similar efforts (9), has not been observed before. This finding is especially interesting in the context of elasticity of real kidneys, for which a Young’s modulus has been found to be between 0.05 and 5 kPa (19,20). This coincides with the elasticity of substrates studied herein, and opens the possibility that the newly found phase of growth has a particular biological relevance. Likewise, the ability to extrude viable cells may point to a new migratory pathway regulated mechanically by the stresses in the tissue, the implication of which we hope to investigate in the future.  相似文献   

14.
A Drosophila Resource of Transgenic RNAi Lines for Neurogenetics          下载免费PDF全文
Jian-Quan Ni  Lu-Ping Liu  Richard Binari  Robert Hardy  Hye-Seok Shim  Amanda Cavallaro  Matthew Booker  Barret D. Pfeiffer  Michele Markstein  Hui Wang  Christians Villalta  Todd R. Laverty  Lizabeth A. Perkins  Norbert Perrimon 《Genetics》2009,182(4):1089-1100
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15.
Ratiometric Imaging of the T-Cell Actin Cytoskeleton Reveals the Nature of Receptor-Induced Cytoskeletal Enrichment     
Alexander?A. Smoligovets  Adam?W. Smith  Jay?T. Groves 《Biophysical journal》2013,105(3):L11-L13
The T-cell actin cytoskeleton mediates adaptive immune system responses to peptide antigens by physically directing the motion and clustering of T-cell receptors (TCRs) on the cell surface. When TCR movement is impeded by externally applied physical barriers, the actin network exhibits transient enrichment near the trapped receptors. The coordinated nature of the actin density fluctuations suggests that they are composed of filamentous actin, but it has not been possible to eliminate de novo polymerization at TCR-associated actin polymerizing factors as an alternative cause. Here, we use a dual-probe cytoskeleton labeling strategy to distinguish between stable and polymerizing pools of actin. Our results suggest that TCR-associated actin consists of a relatively high proportion of the stable cytoskeletal fraction and extends away from the cell membrane into the cell. This implies that actin enrichment at mechanically trapped TCRs results from three-dimensional bunching of the existing filamentous actin network.The T-cell actin cytoskeleton is critical for proper antigen recognition by the mammalian adaptive immune system. During T-cell receptor (TCR) triggering by antigen peptides presented on major histocompatibility proteins (pMHCs) on the surfaces of antigen-presenting cells (APCs), the T-cell actin cytoskeleton adopts a pattern of centrosymmetric retrograde flow (1–3). This simultaneously promotes further TCR triggering (4) and rearranges various T-cell membrane proteins and their APC counterparts into an organized cell-cell interface termed the immunological synapse (IS) (5–7). During this process, TCRs form microclusters that move to the center of the IS in an actin-dependent manner (8,9). When engineered physical barriers interrupt the centripetal motion of TCR clusters, actin flow slows near the pinned microclusters, and the cytoskeletal network transiently accumulates and dissipates at the sites (10,11). The amplitude and duration of the induced cytoskeletal fluctuations are much greater than would be expected for a random distribution of independent objects, indicating that the actin in the local environment is coordinated. Whether this coordination arises from a rearrangement in the existing F-actin network or represents de novo polymerization of the cytoskeleton, as predicted by the association of TCRs with actin polymerizing factors (12), remains unclear. Here, we use a dual-probe cytoskeleton labeling approach that has previously been applied to distinguish between stable and dynamic populations of actin by exploiting the different relative affinities of monomeric actin and actin-binding proteins toward each population (13). This strategy reveals that TCR-associated actin is composed primarily of the stable cytoskeletal fraction and that local enrichment results from three-dimensional bunching of the existing filamentous actin network.Primary T cells from mice transgenic for the AND TCR were triggered using synthetic APCs consisting of supported lipid bilayers functionalized with pMHC and the integrin ligand intercellular adhesion molecule 1. Nanopatterned metal grids on the bilayer substrate acted as diffusion barriers that prevented lateral transport of TCR-pMHC complexes (14,15). Transient enrichment of actin at TCR clusters trapped at these barriers was visualized using fluorescent fusions of actin itself (mKate2-β-actin) and the F-actin binding domain of utrophin (EGFP-UtrCH). Such a dual-probe strategy theoretically allows for discrimination between different pools of actin: dynamic populations characterized by high polymerization and/or short filament fragments tend to be relatively better labeled by direct actin fusions whereas stable populations composed of longer filaments can support higher labeling by fluorescent fusions of F-actin binding proteins. This visualization method has been validated in Xenopus oocytes, where it distinguishes actin populations during wound healing (13). It has not been explicitly applied to T cells; however, simultaneous labeling of the Jurkat cell cytoskeleton using EGFP-actin and Alexa 568-phalloidin reveals distinct populations of actin consistent with the results expected from Xenopus (13,16).Our results show that the T-cell periphery is relatively enriched in mKate2-β-actin (Fig. 1 C, box 1), while EGFP-UtrCH dominates toward the center of the IS (Fig. 1 C, box 2). We infer from this probe distribution that the cytoskeleton at the T-cell periphery is composed of short fragments and is a site of active polymerization, whereas at the center of the IS, actin filaments are longer and predominantly stable. This is consistent with previous models of the T-cell actin network (3,16). An effective way to highlight each of these cytoskeletal regions is to consider the relative ratios of the two probes at each location. In this case, a high UtrCH/actin ratio corresponds to stable actin, and a high actin/UtrCH ratio corresponds to dynamic actin (Fig. 1 D). When T cells are treated with cytochalasin D, an inhibitor of actin polymerization, the overall UtrCH/actin ratio of the cell decreases as would be expected from a general decrease in polymerized actin (see Movie S7 and Movie S8 in the Supporting Material). However, it should be noted that photobleaching can also shift the UtrCH/actin ratio over time. We limit quantitative analysis of the ratio to its spatial gradients at a single time point, but such analysis is possible in systems that permit rigorous calibration for probe expression and photobleaching.Open in a separate windowFigure 1Ratiometric imaging of the cytoskeleton in live T cells distinguishes between dynamic and stable actin populations. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell show different actin pools. The cutouts in panel C correspond to (1) a region high in dynamic actin featuring short, polymerizing filaments and/or actin monomers and (2) a region with a stable actin population featuring longer filaments to which UtrCH can bind. (D) The UtrCH/actin ratio image highlights pools of relatively high UtrCH (red) or actin (blue). (Scale bars: 5 μm.)Actin enrichment at trapped TCR clusters incorporates both mKate2-β-actin (Fig. 2, A and C) and EGFP-UtrCH (Fig. 2, B and C). The relative UtrCH/actin ratio at these sites (Fig. 2 D, box 2) is quite high relative to nearby background areas (Fig. 2 D, box 1), indicating that the actin is derived primarily from the stable actin population.Open in a separate windowFigure 2Receptor-induced cytoskeletal enrichment at sites of pinned TCRs corresponds to a primarily stable actin fraction. (A) mKate2-β-actin, (B) EGFP-UtrCH, and (C) merged images of a triggered T cell interacting with a nanopatterned supported lipid bilayer show actin enrichment corresponding to putative sites of pinned TCRs. (D) The UtrCH/actin ratio is high at sites displaying actin enrichment, indicating a primarily stable actin fraction in (1) these regions compared to (2) nearby background areas. (Scale bars: 5 μm.)The three-dimensional distribution of TCR-associated actin was analyzed in dual-labeled live T cells using a spinning disk confocal microscope. The recordings show actin extending away from the cell membrane in the vicinity of trapped TCRs, while the rest of the actin cytoskeleton remains relatively flat (Fig. 3 and see Fig. S1 in the Supporting Material). These protrusions of actin away from the membrane surface are predominantly composed of stable, filamentous actin, as indicated by their relatively high UtrCH/actin ratio (Fig. 3 B).Open in a separate windowFigure 3Three-dimensional ratiometric imaging shows that actin enrichment extends away from the cell membrane. Single planes from (A) merged mKate2-β-actin and EGFP-UtrCH and (B) UtrCH/actin ratio three-dimensional stacks show actin enrichment at the cell membrane. Cutouts represent Z projections passing through sites of (1) enrichment and (2) nearby background regions. The color distribution in panel B is analogous to that in Figs. 1D and and22D, and is omitted for clarity. (Scale bar: 5 μm in the x axis only. Scale box: 1 μm.)Our interpretation of these results is that the filamentous actin network is relatively dense at sites of pinned TCRs. This is the simplest explanation out of several possibilities, one of which is formin-mediated mKate2-β-actin-deficient actin nucleation (17). Filament bunching at pinned TCRs can arise from consistent biophysical properties without assuming heterogeneity between the biochemistry of these receptors and other actin-associated proteins such as those at the cell edge, where locally high probe ratios are absent.Although TCRs are intentionally trapped as part of this experimental strategy, it is likely APCs can naturally impede TCR ligand mobilities under certain circumstances, and this has been shown to impact T-cell signaling (18,19). Actin architecture near cell surface proteins has been extensively studied in focal adhesions of fibroblasts (20), but the lack of stress fibers in T cells makes it unlikely that the two structures are similar. Thus, receptor-induced cytoskeletal enrichment at TCR clusters adds to the catalog of actin behaviors in situ, which is conveniently probed by techniques such as ratiometric dual-probe imaging in live cells. These techniques can be coupled to various spatial analysis algorithms to further extend their utility.  相似文献   

16.
Assessing the Influence of Adjacent Gene Orientation on the Evolution of Gene Upstream Regions in Arabidopsis thaliana     
Fei He  Wei-Hua Chen  Sinéad Collins  Claudia Acquisti  Ulrike Goebel  Sebastian Ramos-Onsins  Martin J. Lercher  Juliette de Meaux 《Genetics》2010,185(2):695-701
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17.
Conformational States of Melittin at a Bilayer Interface     
Magnus Andersson  Jakob?P. Ulmschneider  Martin?B. Ulmschneider  Stephen?H. White 《Biophysical journal》2013,104(6):L12-L14
The distribution of peptide conformations in the membrane interface is central to partitioning energetics. Molecular-dynamics simulations enable characterization of in-membrane structural dynamics. Here, we describe melittin partitioning into dioleoylphosphatidylcholine lipids using CHARMM and OPLS force fields. Although the OPLS simulation failed to reproduce experimental results, the CHARMM simulation reported was consistent with experiments. The CHARMM simulation showed melittin to be represented by a narrow distribution of folding states in the membrane interface.Unstructured peptides fold into the membrane interface because partitioned hydrogen-bonded peptide bonds are energetically favorable compared to free peptide bonds (1–3). This folding process is central to the mechanisms of antimicrobial and cell-penetrating peptides, as well as to lipid interactions and stabilities of larger membrane proteins (4). The energetics of peptide partitioning into membrane interfaces can be described by a thermodynamic cycle (Fig. 1). State A is a theoretical state representing the fully unfolded peptide in water, B is the unfolded peptide in the membrane interface, C is the peptide in water, and D is the folded peptide in the membrane. The population of peptides in solution (State C) is best described as an ensemble of folded and unfolded conformations, whereas the population of peptides in State D generally is assumed to have a single, well-defined helicity, as shown in Fig. 1 A (5). Given that, in principle, folding in solution and in the membrane interface should follow the same basic rules, peptides in state D could reasonably be assumed to also be an ensemble. A fundamental question (5) is therefore whether peptides in state D can be correctly described as having a single helicity. Because differentiating an ensemble of conformations and a single conformation may be an impossible experimental task (5), molecular-dynamics (MD) simulations provide a unique high-resolution view of the phenomenon.Open in a separate windowFigure 1Thermodynamic cycles for peptide partitioning into a membrane interface. States A and B correspond to the fully unfolded peptide in solution and membrane interface, respectively. The folded peptide in solution is best described as an ensemble of unfolded and folded conformations (State C). State D is generally assumed to be one of peptides with a narrow range of conformations, but the state could actually be an ensemble of states as in the case of State C.Melittin is a 26-residue, amphipathic peptide that partitions strongly into membrane interfaces and therefore has become a model system for describing folding energetics (3,6–8). Here, we describe the structural dynamics of melittin in a dioleoylphosphatidylcholine (DOPC) bilayer by means of two extensive MD simulations using two different force fields.We extended a 12-ns equilibrated melittin-DOPC system (9) by 17 μs using the Anton specialized hardware (10) with the CHARMM22/36 protein/lipid force field and CMAP correction (11,12) (see Fig. S1 and Fig. S2 in the Supporting Material). To explore force-field effects, a similar system was simulated for 2 μs using the OPLS force field (13) (see Methods in the Supporting Material). In agreement with x-ray diffraction measurements on melittin in DOPC multilayers (14), melittin partitioned spontaneously into the lipid headgroups at a position below the phosphate groups at similar depth as glycerol/carbonyl groups (Fig. 2).Open in a separate windowFigure 2Melittin partitioned into the polar headgroup region of the lipid bilayer. (A) Snapshot of the simulation cell showing two melittin molecules (MLT1 and MLT2, in yellow) at the lipid-water interface. (B) Density cross-section of the simulation cell extracted from the 17-μs simulation. The peptides are typically located below the lipid phosphate (PO4) groups, in a similar depth as the glycerol/carbonyl (G/C) groups.To describe the secondary structure for each residue, we defined helicity by backbone dihedral angles (φ, ψ) within 30° from the ideal α-helical values (–57°, –47°). The per-residue helicity in the CHARMM simulation displays excellent agreement with amide exchange rates from NMR measurements that show a proline residue to separate two helical segments, which are unfolded below Ala5 and above Arg22 (15) (Fig. 3 A). In contrast, the OPLS simulation failed to reproduce the per-residue helicity except for a short central segment (see Fig. S3).Open in a separate windowFigure 3Helicity and conformational distribution of melittin as determined via MD simulation. (A) Helicity per residue for MLT1 and MLT2. (B) Corresponding evolution of the helicity. (C) Conformational distributions over the entire 17-μs simulation.Circular dichroism experiments typically report an average helicity of ∼70% for melittin at membrane interfaces (3,6,16,17), but other methods yield average helicities as high as 85% (15,18). Our CHARMM simulations are generally consistent with the experimental results, especially amide-exchange measurements (15); melittin helicity averaged to 78% for MLT1, whereas MLT2 transitioned from 75% to 89% helicity at t ≈ 8 μs, with an overall average helicity of 82% (Fig. 3 B). However, in the OPLS simulation, melittin steadily unfolds over the first 1.3 μs, after which the peptide remains only partly folded, with an average helicity of 33% (see Fig. S3). Similar force-field-related differences in peptide helicity were recently reported, albeit at shorter timescales (19). Although suitable NMR data are not presently available, we have computed NMR quadrupolar splittings for future reference (see Fig. S4).To answer the question asked in this article—whether the conformational space of folded melittin in the membrane interface can be described by a narrow distribution—the helicity distributions for the equilibrated trajectories are shown in Fig. 3 C. Whereas MLT1 in the CHARMM simulation produces a single, narrow distribution of the helicity, MLT2 has a bimodal distribution as a consequence of the folding event at t ≈ 8 μs (Fig. 3 C). We note that CHARMM force fields have a propensity for helix-formation and this transition might therefore be an artifact. We performed a cluster analysis to describe the structure of the peptide in the membrane interface. The four most populated conformations in the CHARMM simulation are shown in Fig. 4. The dominant conformation for both peptides was a helix kinked at G12 and unfolded at the last 5–6 residues of the C-terminus. The folding transition of MLT2 into a complete helix is visible by the 48% occupancy of a fully folded helix.Open in a separate windowFigure 4Conformational clusters of the two melittin peptides (MLT1 and MLT2) from the 17-μs CHARMM simulation in DOPC. Clustering is based on Cα-RMSD with a cutoff criterion of 2 Å.We conclude that the general assumption when calculating folding energetics holds: Folded melittin partitioned into membrane interfaces can be described by a narrow distribution of conformations. Furthermore, extended (several microsecond) simulations are needed to differentiate force-field effects. Although the CHARMM and OPLS simulations would seem to agree for the first few hundred nanoseconds, the structural conclusions differ drastically with longer trajectories, with CHARMM parameters being more consistent with experiments. However, as implied by the difference in substate distributions between MLT1 and MLT2, 17 μs might not be sufficient to observe the fully equilibrated partitioning process. The abrupt change in MLT2 might indicate that the helicity will increase to greater than experimentally observed in a sufficiently long simulation. On the other hand, it could be nothing more than a transient fluctuation. Increased sampling will provide further indicators of convergence of the helix partitioning process.  相似文献   

18.
The Power of the Methods for Detecting Interlocus Gene Conversion     
Sayaka P. Mansai  Hideki Innan 《Genetics》2010,184(2):517-527
Interlocus gene conversion can homogenize DNA sequences of duplicated regions with high homology. Such nonvertical events sometimes cause a misleading evolutionary interpretation of data when the effect of gene conversion is ignored. To avoid this problem, it is crucial to test the data for the presence of gene conversion. Here, we performed extensive simulations to compare four major methods to detect gene conversion. One might expect that the power increases with increase of the gene conversion rate. However, we found this is true for only two methods. For the other two, limited power is expected when gene conversion is too frequent. We suggest using multiple methods to minimize the chance of missing the footprint of gene conversion.INTERLOCUS (ectopic or nonallelic) gene conversion occurs between paralogous regions such that their DNA sequences are shuffled and homogenized (Petes and Hill 1988; Harris et al. 1993; Goldman and Lichten 1996). As a consequence, the DNA sequences of paralogous genes become similar (i.e., concerted evolution, Ohta 1980; Dover 1982; Arnheim 1983). This homogenizing effect of gene conversion sometimes causes problems in the inference of the evolutionary history of duplicated genes or multigene family. Common misleading inferences include an underestimation of the age of duplicated genes (Gao and Innan 2004; Teshima and Innan 2004). This is largely because the concept of the molecular clock is automatically incorporated in most software of phylogenetic analyses, and those software are frequently applied to multigene families without careful consideration of the potential effect of gene conversion.To understand the evolutionary roles of gene duplication, it is crucial to date each duplication event. To do this, we first need to know precisely the action of gene conversion among the gene family of interest. There have been a number of methods for detecting gene conversion, but their power has not been fully explored. Here, we systematically compare their performance by simulations to provide a guideline on which method works best under what condition. Our simulations show that some methods have a serious problem that causes a misleading interpretation: they do not detect any evidence for gene conversion when the gene conversion rate is too high. Thus, as is always true, lack of evidence is no evidence for absence, and we must be very careful about this effect when analyzing data with those tests, as is demonstrated below.There seem to be four major ideas behind the methods for detecting gene conversion, which are summarized below. A number of methods have been developed to detect interlocus gene conversion, and they belong to one of these four broad categories.
  1. Incompatibility between an estimated gene tree and the true duplication history: Figure 1A illustrates a simple situation of a pair of duplicated genes, X and Y, that arose before the speciation event of species A and B. The upper tree of Figure 1A shows a tree representing the true history. When a gene tree is estimated from their DNA sequences, it should be consistent with the true tree when genes X and Y have accumulated mutations independently. Gene conversion potentially violates this relationship. When genes X and Y are subject to frequent gene conversion, the two paralogous genes in each species should be more closely related, resulting in a gene tree illustrated in the bottom tree in Figure 1A. Thus, incongruence between the real tree and an inferred gene tree can provide strong evidence for gene conversion (unless there is no lineage sorting or misinference of the gene tree).Open in a separate windowFigure 1.—Summary of the simulations in the two-species two-locus model. (A) Illustration of the model. (B–E) The power of the four approaches. The average gene conversion tract length (1/q) is assumed to be 100 bp. See Figure S1 for the results with 1/q = 1000 bp.It should be noted that a single gene conversion event usually transfers a short fragment. Consequently, it occasionally happens that incongruence is detected only in a part of the duplicated region. Thus, searching local regions of incongruence has been a well-recognized method for detecting nonvertical evolutionary events such as recombination, gene conversion, and horizontal gene transfer (Farris 1971; Brown et al. 1972), and some computational methods based on this idea have been developed (Balding et al. 1992).
  2. Incompatibility of gene trees in different subregions: The idea of (i) can work even without knowing the real history. As mentioned above, incompatibility in the tree shape between different subregions can be evidence for local gene conversion because those subregions should have different histories of gene conversion (Sneath et al. 1975; Stephens 1985). A number of statistical algorithms incorporate this idea (e.g., Jakobsen et al. 1997; McGuire et al. 1997; Weiller 1998).
  3. GENECONV: A local gene conversion also leaves its trace in the alignment of sequences. GENECONV is a software developed by Sawyer (1989) to detect such signatures (http://www.math.wustl.edu/∼sawyer/geneconv/). GENECONV looks at an alignment of multiple sequences in a pairwise manner and searches unusually long regions of high identity between the focal pair conditional on the pattern of variable sites in the other sequences, which are candidates of recent gene conversion (a similar idea is also seen in Sneath et al. 1975). The statistical significance is determined by random shuffling of variable sites in the alignment.
  4. Shared polymorphism: Suppose polymorphism data are available in both of the duplicated genes. Then, with gene conversion, there could be polymorphisms shared by the two genes, which can be evidence for gene conversion (Innan 2003a). It should be noted that parallel mutations can create shared polymorphism even without gene conversion, but the chance should be very low when the point mutation rate is usually very low. Polymorphism data usually have tremendous amounts of information on very recent events and can be a powerful means to detect gene conversion (e.g., Stephens 1985; Betrán et al. 1997; Innan 2002).
In this study, we investigate and compare the performance of the methods based on these four ideas with simple settings. It should be noted that because our primary focus is on interlocus gene conversion, we ignore methods that can be used for detecting only allelic gene conversion, such as Fearnhead and Donnelly (2001), Hudson (2001), and Gay et al. (2007).  相似文献   

19.
Signatures of Recent Directional Selection Under Different Models of Population Expansion During Colonization of New Selective Environments     
Yuseob Kim  Davorka Gulisija 《Genetics》2010,184(2):571-585
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20.
Gene Genealogies Strongly Distorted by Weakly Interfering Mutations in Constant Environments     
Jon Seger  Wendy A. Smith  Jarom J. Perry  Jessalynn Hunn  Zofia A. Kaliszewska  Luciano La Sala  Luciana Pozzi  Victoria J. Rowntree  Frederick R. Adler 《Genetics》2010,184(2):529-545
Neutral nucleotide diversity does not scale with population size as expected, and this “paradox of variation” is especially severe for animal mitochondria. Adaptive selective sweeps are often proposed as a major cause, but a plausible alternative is selection against large numbers of weakly deleterious mutations subject to Hill–Robertson interference. The mitochondrial genealogies of several species of whale lice (Amphipoda: Cyamus) are consistently too short relative to neutral-theory expectations, and they are also distorted in shape (branch-length proportions) and topology (relative sister-clade sizes). This pattern is not easily explained by adaptive sweeps or demographic history, but it can be reproduced in models of interference among forward and back mutations at large numbers of sites on a nonrecombining chromosome. A coalescent simulation algorithm was used to study this model over a wide range of parameter values. The genealogical distortions are all maximized when the selection coefficients are of critical intermediate sizes, such that Muller''s ratchet begins to turn. In this regime, linked neutral nucleotide diversity becomes nearly insensitive to N. Mutations of this size dominate the dynamics even if there are also large numbers of more strongly and more weakly selected sites in the genome. A genealogical perspective on Hill–Robertson interference leads directly to a generalized background-selection model in which the effective population size is progressively reduced going back in time from the present.OBSERVED levels of apparently neutral nucleotide diversity (πn) are typically lower than expected under the assumptions of standard equilibrium theories, and they vary much less among species than do estimates of long-term effective population sizes (Nei and Grauer 1984; Bazin et al. 2006; Nabholz et al. 2008). Many explanations have been proposed for the apparent shortfalls and the lack of proportionality with population size, including (1) complex demographic histories (e.g., recurring population bottlenecks), (2) adaptive selective sweeps (Maynard Smith and Haigh 1974; Gillespie 1999), and (3) selection against deleterious mutations (Charlesworth et al. 1993, 1995; McVean and Charlesworth 2000; Comeron et al. 2008). Of these three possibilities, bottlenecks and sweeps are by far the most frequently mentioned, even though deleterious mutations occur at high rates in all species, regardless of ecological circumstances (Eyre-Walker and Keightley 2007). Here we show that weakly deleterious mutations can distort genealogies in three different ways and dramatically reduce nucleotide diversities in large populations of nonrecombining chromosomes. The mitochondrial genealogies of several species of whale lice (Kaliszewska et al. 2005) are distorted in exactly these ways, and several lines of evidence suggest that bottlenecks and adaptive sweeps are not likely to be the primary causes.Mitochondria have been proposed to be especially sensitive to selective sweeps. Animal mitochondrial genomes contain more than three dozen essential protein and structural RNA genes, so they are large targets for both mutation and selection (Ballard and Whitlock 2004). They do not undergo sexual recombination, so every advantageous mutation that fixes will reduce variation throughout the genome. Mitochondrial nucleotide diversity therefore could depend strongly on rates of environmental change, which could be similar for species with very different population sizes. Indeed, if rates of mitochondrial adaptation were mutation limited, then larger populations might actually experience higher rates of adaptive substitution and as a result show lower average levels of neutral diversity than smaller populations (Gillespie 2000, 2001). This idea was recently invoked to explain the remarkable similarity of average levels of mitochondrial nucleotide diversity among the major animal classes which appear to have very different average population sizes and substantially different average levels of nuclear nucleotide and amino acid diversity (Bazin et al. 2006).Unconditionally deleterious mutations can also depress linked neutral diversity by reducing the effective population size either through (1) background selection against relatively strongly selected mutations (Charlesworth et al. 1993, 1995) or (2) Hill–Robertson interference (Hill and Robertson 1966) among large numbers of relatively weakly selected mutations (reviewed by Comeron et al. 2008). The second of these processes, called “weak-selection Hill–Robertson interference” (wsHRi) by McVean and Charlesworth (2000) and “interference selection” (IS) by Comeron and Kreitman (2002), can shorten genealogies, give them strongly nonneutral branch-length proportions, and skew their topologies (Higgs and Woodcock 1995; Maia et al. 2004).To date, weak interference has mainly been studied by forward simulation, with the aim of assessing its possible effects on patterns of optimal synonymous codon use within eukaryotic nuclear genes and genomes, in the presence of recombination (Comeron and Guthrie 2005; Loewe and Charlesworth 2007; Comeron et al. 2008). In an attempt to understand the striking genealogical distortions seen in whale-louse mitochondria (Kaliszewska et al. 2005), we have developed a structured-coalescent algorithm that accurately models selection of arbitrary strength on a nonrecombining chromosome of finite length. All of the distortions seen in the whale-louse mitochondria are replicated under parameters that might plausibly apply to whale lice and many other animal species, and these distortions scale only weakly with population size.Whale lice are permanent, obligate ectoparasites of cetaceans. They feed on the dead outer surface of their host''s skin, and they appear to be harmless. They are amphipod Crustacea comprising a monophyletic family, Cyamidae, with ∼50 described species in several genera. Three of these species (Cyamus ovalis, C. gracilis, and C. erraticus) occur on right whales (Eubalaena spp.) but not regularly on any other hosts. Most adult right whales carry large populations of all three species.Right whales in the North Pacific, the North Atlantic, and the southern hemisphere have been separated for ∼5 million years, and so have their cyamids (Rosenbaum et al. 2000; Gaines et al. 2005; Kaliszewska et al. 2005). For this reason the right whales in different ocean systems are now considered distinct species (Eubalaena japonica, E. glacialis, and E. australis), and we refer to their cyamids as North Pacific C. ovalis, North Atlantic C. ovalis, southern C. ovalis, and so on, in anticipation that a future revision of the genus Cyamus will recognize them as “triplet” sibling species (3 × 3 = 9 species in all). We studied their mitochondrial population genetics with the initial aim of quantifying patterns of genetic differentiation among the cyamid populations on individual whales within local populations (Kaliszewska et al. 2005).We had reasoned (incorrectly) that the pattern of differentiation among whales might say something about their social interactions, since cyamids can transfer only between whales that are in direct physical contact with each other. We found very low levels of differentiation among whales and to our surprise literally no differentiation among the major southern hemisphere breeding aggregations that calve off the coasts of South America, South Africa, Australia, and New Zealand (Kaliszewska et al. 2005). This absence of population structure seems remarkable by terrestrial standards but is easily explained by modest rates of cyamid exchange among whales within local populations and between the major breeding aggregations, given the enormous sizes of cyamid populations. Right whales are highly gregarious (spending hours per day in social interactions), mobile (traveling thousands of kilometers per year on annual foraging migrations), and mortal (carrying their cyamid populations to the sea floor when they die). Thus cyamids have many opportunities to transfer between whales, and they might be expected to have evolved an inclination to do so when the opportunity presents itself (Hamilton and May 1977).The well-defined ecology of right-whale cyamids allows their population sizes to be estimated directly. The number of adult cyamids per whale (∼500–10,000, varying by species) times the number of whales per ocean (∼50,000–200,000, prior to human exploitation) equals the number of cyamids per species (Kaliszewska et al. 2005). Thus for all three nominal species of right-whale cyamids, long-term census population sizes are expected to have been in the range 2.5 × 107–2 × 109. Given conservative estimates of the per-generation mitochondrial mutation rate, even the lower end of this range predicts levels of synonymous nucleotide diversity at least an order of magnitude larger than those actually seen in the cyamids, which are consistently modest and similar to those seen in typical terrestrial arthropods (Kaliszewska et al. 2005). The three North Atlantic and southern hemisphere sibling-species pairs are strongly reciprocally monophyletic, as illustrated for C. ovalis in Figure 1. This is not expected at mutation–drift equilibrium, given their very large population sizes.Open in a separate windowFigure 1.—Mitochondrial gene genealogies for North Atlantic and southern hemisphere Cyamus ovalis, estimated by UPGMA from partial COI sequences. Left: The intraspecific genealogies coalesce globally at ∼0.5 and 1 MY and share an ancestor at ∼5 MY (Kaliszewska et al. 2005). Center and right: Each intraspecific genealogy is aligned with a generalized skyline plot (Strimmer and Pybus 2001) showing estimates of θ at different times in the past under a piecewise constant model of population size change fit by GENIE 3.0 (Pybus and Rambaut 2002). Three different point estimates of present-day θ are also indicated on the plots (synonymous-site nucleotide diversity π, Watterson''s θ estimated from synonymous sites, and θ estimated jointly with the apparent exponential growth rate by the MCMC coalescent algorithm in LAMARC). Values of Tajima''s D are lower (−1.5 to −1.6) when estimated from the sequences than when estimated from the branch lengths of the trees (−2.1 to −2.4), as expected because multiple substitutions occur at some sites. Similar values of DT (−2.3 for both species) were obtained from the highest-likelihood trees found by BEAST with a fully parameterized GTR substitution model and a coalescent prior. Those trees have standardized imbalance statistics (−IS) of −3.7 (southern hemisphere C. ovalis) and −2.2 (North Atlantic C. ovalis). The trees shown here have more extreme values of −IS (−5.5 and −4.0, respectively), probably as a consequence of artificially pectinate branching orders induced by UPGMA among sets of identical sequences. Slightly different sets of sequences were used to make the two-species genealogy on the left and the single-species genealogies in the center. The long interspecific branches in the two-species tree are based on a multispecies maximum-likelihood analysis involving smaller numbers of much longer (4.1 kb) sequences (Kaliszewskaet al. 2005, Figure 3).These dramatic deficits of variation are not easily explained by population bottlenecks or adaptive selective sweeps. The bottleneck hypothesis is especially problematic because it requires the long-term near extinction of right whales in all three ocean systems. (Short bottlenecks such as those caused by human exploitation of right whales are not expected to have a noticeable effect on cyamid genetic diversity because cyamid populations remain large, and rates of genetic drift low, even when there are few whales.) That all three right whales have survived for millions of years suggests that they have maintained reasonably large population sizes, and the mitochondrial nucleotide diversity of southern right whales is consistent with this assumption (Kaliszewska et al. 2005), as is the nucleotide diversity of a cyamid nuclear gene (described below). Right whales eat copepods and krill, which are relatively close to the base of marine food webs, and right-whale populations are thought to be food limited. Thus a long-term, severe depression of their numbers would also seem to imply a collapse of marine ecosystems worldwide, for which there is no evidence.Several features of cyamid mitochondrial nucleotide diversity are also inconsistent with the bottleneck model and with adaptive sweeps as well. The most obvious of these features is the uniformity of cyamid mitochondrial diversity among species (π = 0.007–0.015 for COI sequences in the seven species surveyed by Kaliszewska et al. 2005). Gene genealogies estimated from these sequences also seem remarkably uniform in total depth, with last common ancestors differing in age by only a factor of 3 and in six of the seven species by less than a factor of 2 (see Kaliszewska et al. 2005, Figure 4). Adaptive sweeps might be expected to occur at roughly random intervals and not to be well coordinated in time among seven species in three different ocean systems. Interspecific coordination of such sweeps (over the whole globe) would seem to be required if they were to be a plausible primary cause of the genealogical shortening.Open in a separate windowFigure 4.—Apparent average effective sizes of ancestral populations, for models with different values of s. Values of Ne are given on the vertical axis (logarithmically scaled). They are estimated from the variance of expected contributions to the present, for the adults of any given generation. The parameters are those of Figure 2 (N = 65,536 = “64k,” μ = 1.5 × 10−6, Ls = 2048, U = 0.0031). In theory the curve for s = 0 should be perfectly horizontal. The discrepancy appears to be caused by subtle flaws in the shape of the very broad “idealized” simulated distribution that was used in this calculation. The curves for strong-selection cases are perfectly horizontal at times beyond a few thousand generations because the mutation-number distributions are compact, with little stochastic variation. The two lowest curves are those for the selection coefficients (s = 2−10, U/s = 3.2, and s = 2−11, U/s = 6.3) that produce the most extreme values of the polymorphism and tree-shape statistics, given the other parameters (Figure 2).In addition to showing too little nucleotide variation, the cyamid mitochondrial genomes show strong and consistent excesses of rare nucleotide states, reflecting the “comb-like” or “star-like” shapes of the genealogies, in which deeper branches tend to be much too short relative to terminal branches (as if the trees had been “squished” from behind). This kind of distortion causes negative values of Tajima''s (1989) D and related statistics. It can be caused by population expansion from a bottleneck or by lineage expansion under positive selection (Kaplan et al. 1989; Slatkin and Hudson 1991; Rogers and Harpending 1992; Bamshad and Wooding 2003). However, the form of branch-length distortion seen in the cyamid genealogies suggests a slow, steady, roughly exponential form of population or lineage growth, not the relatively sudden increases suggested by the bottleneck and selective-sweep hypotheses. Generalized skyline plots (Strimmer and Pybus 2001) describing the histories of population size implied by the shapes of the northern and southern C. ovalis gene genealogies are shown in Figure 1. They are remarkably similar, as are the growth rates and estimates of present-day θ (= 2Nfμn) obtained by fitting exponential growth models using the coalescent algorithms in LAMARC (Kuhner et al. 1998, 2004) or BEAST (Drummond and Rambaut 2007).Cyamid populations cannot have grown in numbers as seemingly implied by these analyses. The number of cyamids on each whale appears to be set mainly by microhabitat limitations (e.g., by the area of rough callosity tissue on the head, where C. ovalis and C. gracilis live), and these features of their environment have hardly changed for millions of years, as demonstrated by the strong similarities of northern and southern right whales and their cyamids. Likewise, the numbers of right whales cannot have increased gradually from vanishingly small numbers over several hundred thousand years, for the reasons discussed above.The genealogical signals of “growth” therefore seem likely to be caused by selection. Environmental change is the most obvious potential cause of selection, but the apparent rate of growth seen here is strangely slow—in fact, slower than glacial. The orbitally forced Plio-Pleistocene glacial climate cycles have a major period of ∼100,000 years (Lambert et al. 2008 and references therein), but all seven of the right-whale cyamids for which we have mitochondrial population samples appear to have been “expanding,” more or less continuously, through at least several such cycles. The seemingly fairly consistent rate of branch-length foreshortening seen in the genealogies therefore suggests the action of a process that is relatively homogeneous in time, in addition to being very slow overall.The cyamid mitochondrial genealogies also appear to be topologically skewed, with sister clades too unequal in size, on average. In random bifurcating trees, the distribution of sister-clade sizes is uniform (Yule 1924; Heard 1992; Rogers 1994). Deviations from this null expectation can be quantified by statistics such as Colless''s (1982) index of tree imbalance (Shao and Sokal 1990; Rogers 1996). Our estimates of the cyamid genealogies tend to be excessively imbalanced (Figure 1). Strong topological imbalance is not caused by classic adaptive sweeps or by population growth following a bottleneck, but previous theoretical work has indicated that it can be caused by selection (Higgs and Woodcock 1995; Maia et al. 2004).To summarize, the cyamid mitochondrial genealogies are consistently much too short, too squished, and too skewed, relative to neutral-theory expectations. Owing to several special features of cyamid and right-whale biology, selection seems to be the only plausible explanation for this set of distortions, but conventional adaptive sweeps do not seem likely to be the primary cause. We therefore asked whether weakly deleterious mutations might be sufficient to generate the observed combination of patterns, in the absence of environmental change. Previous work (mentioned above) showed that interference among weak mutations at many sites can strongly affect linked neutral variation, but this work did not fully explore the parameter space relevant to our system or connect all the patterns in a genealogical setting.To address this question we first carried out forward simulations of populations of nonrecombining chromosomes with large numbers of nucleotide positions subject to forward and back mutations with unconditional fitness effects of size s. Large numbers of linked neutral sites were used to estimate genealogies and to calculate population statistics of interest. We found that for a range of intermediate values of s, considerable fitness variation was maintained and all three of the genealogical distortions (and the signal of apparent exponential growth) seen in the cyamid genealogies reached impressively large maxima. However, the computational burden of full forward simulation prevented us from considering realistic parameter values (i.e., large N and small μ), and it was not obvious that extrapolations based on compound parameters (e.g., Nμ and Ns) would work as hoped in all respects (see Comeron et al. 2008). We developed an equivalent coalescent algorithm that accurately reproduces all results of the forward simulations and allows for realistic parameter values. Under parameters relevant to cyamid mitochondria, the distortions of genealogical depth, proportions, and topology can be even more extreme than those seen in the cyamids, and the mean pairwise coalescence times (and resulting neutral nucleotide diversities) associated with maximally distorting intermediate values of s (Us/s ∼ 5, where Us is the total genomic mutation rate at sites with selection coefficents of size s) depend only weakly on N.All parameters of this model (including those of the environment) remain constant over time, yet in some respects it displays apparently nonequilibirum behavior. Under weak to intermediate selection (Us/s > 10), the effective population size appears to become progressively smaller as time recedes into the past, giving rise to the illusion of growth. And in the maximally distorting range of intermediate selection coefficients, the distributions of deleterious mutation numbers and the shapes of genealogies show conspicuous dynamical instability of a form that could be taken to suggest “adaptive evolution” in response to episodes of environmental change. Adaptive mutations contribute importantly to this process, but they are reversions at some of the many sites previously mutated to mildly deleterious states. Subtle patterns of environmental change that converted previously optimal nucleotide states to slightly suboptimal states could give rise to a category of “virtual reversions” that would augment (or even outnumber) simple reversions, and the effects of such a process might well be consistent with the distortions seen in the cyamid mitochondrial genealogies. However, models with no environmental change of any kind appear to explain the observations surprisingly well.  相似文献   

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