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Primary cilia have essential roles in transducing signals in eukaryotes. At their core is the ciliary axoneme, a microtubule-based structure that defines cilium morphology and provides a substrate for intraflagellar transport. However, the extent to which axonemal microtubules are specialized for sensory cilium function is unknown. In the nematode Caenorhabditis elegans, primary cilia are present at the dendritic ends of most sensory neurons, where they provide a specialized environment for the transduction of particular stimuli. Here, we find that three tubulin isotypes—the α-tubulins TBA-6 and TBA-9 and the β-tubulin TBB-4—are specifically expressed in overlapping sets of C. elegans sensory neurons and localize to the sensory cilia of these cells. Although cilia still form in mutants lacking tba-6, tba-9, and tbb-4, ciliary function is often compromised: these mutants exhibit a variety of sensory deficits as well as the mislocalization of signaling components. In at least one case, that of the CEM cephalic sensory neurons, cilium architecture is disrupted in mutants lacking specific ciliary tubulins. While there is likely to be some functional redundancy among C. elegans tubulin genes, our results indicate that specific tubulins optimize the functional properties of C. elegans sensory cilia.THE fitness of all organisms depends on an ability to appropriately sense and respond to the environment. At the cellular level, many specific architectures have evolved to optimize these sensory functions. Prominent among these is the sensory cilium, a tubulin-based cytoplasmic extension that interrogates the extracellular environment in many biological contexts (Davenport and Yoder 2005; Berbari et al. 2009). Cilia are important for the transduction of a broad range of visual, auditory, mechanical, thermal, and chemical stimuli. They also function during development to receive a variety of signals, both chemical and mechanical, that regulate proliferation and differentiation (Goetz and Anderson 2010). Indeed, the disruption of cilium assembly and function can give rise to a spectrum of human diseases collectively known as ciliopathies (Berbari et al. 2009; Lancaster and Gleeson 2009). These disorders, which include autosomal dominant polycystic kidney disease (ADPKD) and autosomal recessive polycystic kidney disease (ARPKD), Bardet–Biedl syndrome, Meckel–Gruber syndrome, and Joubert syndrome, are associated with a variety of pathogenic conditions including polycystic kidneys and neurological impairments.At the core of all cilia and flagella is the microtubule axoneme. This characteristic structural element comprises nine doublet outer microtubules that may surround a central pair, the presence of which often indicates a motile cilium/flagellum. Like all microtubule-based structures, ciliary axonemes are built of heterodimers of α- and β-tubulins, highly conserved small GTP-binding proteins. The recruitment of other cilium components, including signal transduction machinery, requires a conserved assembly and maintenance process called intraflagellar transport (IFT) (Blacque et al. 2008; Pedersen and Rosenbaum 2008). IFT employs two major complexes that transport ciliary cargo bidirectionally by traveling along the axonemal microtubules. Loss of individual IFT components can cause a broad spectrum of defects in the assembly, maintenance, and function of cilia.Important insights into cilium structure and function have come from studies of genetically tractable organisms, particularly the green alga Chlamydomonas and the nematode Caenorhabditis elegans (Bae and Barr 2008; Pedersen and Rosenbaum 2008). In C. elegans, sensory cilia are found exclusively at the dendritic ends of sensory neurons. These cilia constitute a highly specialized sensory environment characterized by localized sensory receptors and specific signaling components. Cilium morphology is quite distinctive in many of these cells and likely contributes to their functional specialization (Ward et al. 1975). Recent progress has shed light on the mechanisms that confer this specialization onto more general pan-ciliary pathways (Evans et al. 2006; Mukhopadhyay et al. 2007; Jauregui et al. 2008; Mukhopadhyay et al. 2008; Silverman and Leroux 2009).The genomes of many eukaryotes harbor multiple α- and β-tubulin genes. Two hypotheses, which are not mutually exclusive, have been proposed to account for these paralogs (Cleveland 1987; Wade 2007). At one extreme, different tubulin isotypes might be functionally redundant, such that their minor coding differences are largely irrelevant. According to this model, multiple genes allow the maintenance of a stable pool of available monomers and dimers. The small amount of sequence variation within the α- and β-tubulin families supports this idea, as do studies of functionally redundant mitotic tubulins in C. elegans (Ellis et al. 2004; Lu et al. 2004; Phillips et al. 2004; Lu and Mains 2005). The alternative hypothesis proposes that specific structures, e.g., ciliary axonemes or axonal microtubules, rely on tubulins optimized for specific roles. Support for this idea has come from studies of cultured mammalian neurons (Joshi and Cleveland 1989), Drosophila (Hutchens et al. 1997; Raff et al. 1997), and human tubulins (Vent et al. 2005; Jaglin et al. 2009). In Drosophila, studies of motile sperm flagella have revealed that the sperm-specific β2 tubulin isoform builds not only the specialized motile axoneme but also all other tubulin-based structures (Kemphues et al. 1982). However, sequences both within and outside the axoneme motif in the C-terminal tail of this tubulin isoform are required for the flagellar axoneme, and other closely related β-tubulins cannot support this role (Fuller et al. 1987; Raff et al. 1997; Popodi et al. 2008). Genetic interactions have provided evidence that β2 tubulin heterodimerizes with the α-tubulin 84B (Hays et al. 1989), which also possesses specific functional properties not provided by structurally similar α-tubulins (Hutchens et al. 1997). In C. elegans, a specific role for tubulin isoforms has been described in the six touch receptor neurons. These nonciliated cells harbor unusual 15-filament microtubules composed of dimers of the α-tubulin MEC-12 and the β-tubulin MEC-7. The loss of mec-7 or mec-12, the expression of which is largely restricted to these cells, results in the conversion of 15-filament microtubules to the standard 11-microfilament variety and a commensurate loss of light-touch response (Savage et al. 1989; Fukushige et al. 1999; Bounoutas et al. 2009). Thus experimental support exists for both of these opposing views, and it seems likely that the role of specific tubulin isoforms in regulating microtubule structure and function differs according to cell and organelle type.The C. elegans genome encodes nine α- and six β-tubulin genes (Gogonea et al. 1999). Some of these genes, particularly tba-1, tba-2, tbb-1, and tbb-2, are expressed broadly during embryogenesis and function redundantly in spindle assembly and positioning (Ellis et al. 2004; Lu et al. 2004; Phillips et al. 2004; Lu and Mains 2005). tba-1 and tbb-2 have also been recently shown to be important for axon outgrowth and synaptogenesis (Baran et al. 2010). Several others, including mec-7, mec-12, and the β-tubulin ben-1, have been identified through genetic screens for particular phenotypes, such as touch insensitivity or benzimidazole resistance (Driscoll et al. 1989; Savage et al. 1989; Fukushige et al. 1999). However, the extent to which specific tubulin isoforms are required for structural and functional diversity in the C. elegans nervous system remains unknown. Here, taking advantage of several existing genome-wide data sets, we identify the α-tubulins TBA-6 and TBA-9 and the β-tubulin TBB-4 as strong candidates for tubulins that have roles in sensory cilia. We find that each of these genes are expressed in characteristic, partially overlapping, sets of sensory neurons, where their products localize to ciliary axonemes. While the loss of any one (or all three) of these genes does not abolish ciliogenesis, tubulin mutants exhibit significant defects in the localization of cilium proteins and in some cilium-dependent behavioral responses. Together, our results indicate that specific α- and β-tubulin isoforms are important, although not essential, for the efficient assembly and function of specific classes of C. elegans sensory cilia. Sensory cilia throughout the animal kingdom may therefore employ specific tubulin isoforms to optimize their function.  相似文献   

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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   

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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   

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We consider neutral evolution of a large population subject to changes in its population size. For a population with a time-variable carrying capacity we study the distribution of the total branch lengths of its sample genealogies. Within the coalescent approximation we have obtained a general expression—Equation 20—for the moments of this distribution with a given arbitrary dependence of the population size on time. We investigate how the frequency of population-size variations alters the total branch length.MODELS for gene genealogies of biological populations often assume a constant, time-independent population size N. This is the case for the Wright–Fisher model (Fisher 1930; Wright 1931), for the Moran model (Moran 1958), and for their representation in terms of the coalescent (Kingman 1982). In real biological populations, by contrast, the population size changes over time. Such fluctuations may be due to catastrophic events (bottlenecks) and subsequent population expansions or just reflect the randomness in the factors determining the population dynamics. Many authors have argued that genetic variation in a population subject to size fluctuations may nevertheless be described by the Wright–Fisher model, if one replaces the constant population size in this model by an effective population size of the form(1)where Nl stands for the population size in generation l. The harmonic average in Equation 1 is argued to capture the significant effect of catastrophic events on patterns of genetic variation in a population: if, for example, a population went through a recent bottleneck, a large fraction of individuals in a given sample would originate from few parents. This in turn would lead to significantly reduced genetic variation, parameterized by a small value of Neff. (See, e.g., Ewens 1982 for a review of different measures of the effective population size and Sjödin et al. 2005 and Wakeley and Sargsyan 2009 for recent developments of this concept.)The concept of an effective population size has been frequently used in the literature, implicitly assuming that the distribution of neutral mutations in a large population of fluctuating size is identical to the distribution in a Wright–Fisher model with the corresponding constant effective population size given by Equation 1. However, recently it was shown that this is true only under certain circumstances (Kaj and Krone 2003; Nordborg and Krone 2003; Jagers and Sagitov 2004). It is argued by Sjödin et al. (2005) that the concept of an effective population size is appropriate when the timescale of fluctuations of Nl is either much smaller or much larger than the typical time between coalescent events in the sample genealogy. In these limits it can be proved that the distribution of the sample genealogies is exactly given by that of the coalescent with a constant, effective population size.More importantly, it follows from these results that, in populations with variable size, the coalescent with a constant effective population size is not always a valid approximation for the sample genealogies. Deviations between the predictions of the standard coalescent model and empirical data are frequently observed, and there are a number of different statistical tests quantifying the corresponding discrepancies (see, for example, Tajima 1989, Fu and Li 1993, and Zeng et al. 2006). The analysis of such deviations is of crucial importance in understanding, for example, human genetic history (Garrigan and Hammer 2006). But while there is a substantial amount of work numerically quantifying deviations, often in terms of a single number, little is known about their qualitative origins and their effect upon summary statistics in the population in question.The question is thus to understand the effect of population-size fluctuations on the patterns of genetic variation, in particular for the case where the scale of the population-size fluctuations is comparable to the time between coalescent events in the ancestral tree. As is well known, many empirical measures of genetic variation can be computed from the total branch length of the sample genealogy (the expected number of single-nucleotide polymorphisms, for example, is proportional to the average total branch length).The aim of this article is to analyze the distribution of the scaled total branch length Tn for a sample genealogy in a population of fluctuating size, as illustrated in Figure 1. For the genealogy of n ≥ 2 lineages sampled at the present time, the expression ⌊NTn⌋ gives the total branch length in terms of generations. Here ⌊Nt⌋ is the largest integer ≤Nt, and the scaling factor N is a suitable measure of the number of genes in the population and serves as a counterpart of the constant generation size of the standard Wright–Fisher model.Open in a separate windowFigure 1.—The effect of population-size oscillations on the genealogy of a sample of size n = 17 (schematic). Left, genealogy described by Kingman''s coalescent for a large population of constant size, illustrated by the light blue rectangle; right, sinusoidally varying population size. Coalescence is accelerated in regions of small population sizes and vice versa. This significantly alters the tree and gives rise to changes in the distribution of the number of mutations and of the population homozygosity.A motivating example is given in Figure 2, which shows numerically computed distributions ρ(Tn) of the total branch lengths Tn for a particular population model with a time-dependent carrying capacity. The model is described briefly in the Figure 2 legend and in detail in a model for a population with time-dependent carrying capacity. As Figure 2 shows, the distributions depend in a complex manner on the form of the size changes. We observe that when the frequency of the population-size fluctuations is very small (Figure 2a), the distribution is well described by the standard coalescent result(2)(Hein et al. 2005). When the frequency is very large (Figure 2e), Equation 2 also applies, but with a different time scaling reflecting an effective population size: t on the right-hand side (rhs) in Equation 2 is replaced by t/c with c = N/Neff. Apart from these special limits, however, the form of the distributions appears to depend in a complicated manner upon the frequency of the population-size variation. The observed behavior is caused by the fact that coalescence proceeds faster for smaller population sizes and more slowly for larger population sizes, as illustrated in Figure 1. But the question is how to quantitatively account for the changes shown in Figure 2.Open in a separate windowFigure 2.—Numerically computed distributions of the scaled total branch lengths Tn in genealogies of samples of size n = 10. The model employed in the simulations is outlined in a model for a population with time-dependent carrying capacity. It describes a population subject to a time-varying carrying capacity, Kl = K0(1 + ɛ sin(2πνl)). The frequency of the time changes is determined by ν, and l = 1, 2, 3, … labels discrete generations forward in time. The parameter N = K0 describes the typical population size, which is taken here to be equal to the time-averaged carrying capacity. a–e show for populations with increasingly rapidly oscillating carrying capacity. The dashed red line in a shows that in the limit of low frequencies the standard coalescent result, Equation 2, is obtained. The dashed red line in e shows that also in the limit of large frequencies the standard coalescent result is obtained, but now with an effective population size. The dashed red line in d is a two-parameter distribution, Equation 41, derived in comparison between numerical simulations and coalescent predictions. Further numerical and analytical results on the frequency dependence of the moments of these distributions are shown in Figure 4. Parameter values used: K0 = 10,000, ɛ = 0.9, and r = 1 (see a model for a population with time-dependent carrying capacity for the exact meaning of the intrinsic growth rate r) and (a) νN = 0.001, (b) νN = 0.1, (c) νN = 0.316, (d) νN = 1, and (e) νN = 100.We show in this article that the results of the simulations displayed in Figure 2 are explained by a general expression—Equation 20—for the moments of the distributions shown in Figure 2. Our general result is obtained within the coalescent approximation valid in the limit of large population size. But we find that in most cases, the coalescent approximation works very well down to small population sizes (a few hundred individuals). Our result enables us to understand and quantitatively describe how the distributions shown in Figure 2 depend upon the frequency of the population-size oscillations. It makes possible to determine, for example, how the variance, skewness, and the kurtosis of these distributions depend upon the frequency of demographic fluctuations. This in turn allows us to compute the population homozygosity and to characterize genetic variation in populations with size fluctuations.The remainder of this article is organized as follows. The next section summarizes our analytical results for the moments of the total branch length. Following that, we describe the model employed in the computer simulations. Then, corresponding numerical results are compared to the analytical predictions. And finally, we summarize how population-size fluctuations influence the distribution of total branch lengths and conclude with an outlook.  相似文献   

12.
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   

13.
14.
15.
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   

16.
Direct Evidence for Postmeiotic Transcription During Drosophila melanogaster Spermatogenesis     
Maria D. Vibranovski  Domitille S. Chalopin  Hedibert F. Lopes  Manyuan Long  Timothy L. Karr 《Genetics》2010,186(1):431-433
  相似文献   

17.
Lambda Red Recombineering in Escherichia coli Occurs Through a Fully Single-Stranded Intermediate     
J. A. Mosberg  M. J. Lajoie  G. M. Church 《Genetics》2010,186(3):791-799
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   

18.
Decreased Energy Metabolism Extends Life Span in Caenorhabditis elegans Without Reducing Oxidative Damage     
Jeremy Michael Van Raamsdonk  Yan Meng  Darius Camp  Wen Yang  Xihua Jia  Claire Bénard  Siegfried Hekimi 《Genetics》2010,185(2):559-571
On the basis of the free radical and rate of living theories of aging, it has been proposed that decreased metabolism leads to increased longevity through a decreased production of reactive oxygen species (ROS). In this article, we examine the relationship between mitochondrial energy metabolism and life span by using the Clk mutants in Caenorhabditis elegans. Clk mutants are characterized by slow physiologic rates, delayed development, and increased life span. This phenotype suggests that increased life span may be achieved by decreasing energy expenditure. To test this hypothesis, we identified six novel Clk mutants in a screen for worms that have slow defecation and slow development and that can be maternally rescued. Interestingly, all 11 Clk mutants have increased life span despite the fact that slow physiologic rates were used as the only screening criterion. Although mitochondrial function is decreased in the Clk mutants, ATP levels are normal or increased, suggesting decreased energy utilization. To determine whether the longevity of the Clk mutants results from decreased production of ROS, we examined sensitivity to oxidative stress and oxidative damage. We found no evidence for systematically increased resistance to oxidative stress or decreased oxidative damage in the Clk mutants despite normal or elevated levels of superoxide dismutases. Overall, our findings suggest that decreased energy metabolism can lead to increased life span without decreased production of ROS.MUTATIONS in clk-1 have been shown to increase longevity in both worms and mice, suggesting that these mutations affect an evolutionarily conserved mechanism of life span extension (Lakowski and Hekimi 1996; Liu et al. 2005; Lapointe et al. 2009). The CLK-1 protein encodes a hydroxylase involved in the synthesis of ubiquinone (Ewbank et al. 1997), a multifunctional, lipid-like molecule that transfers electrons in the electron transport chain and may also act as an intracellular antioxidant (Maroz et al. 2009). clk-1 was originally identified in worms in a screen for maternally rescued mutations that result in abnormal development and behavior. In addition to slow development and slow defecation, clk-1 mutants show decreased brood size, a decreased rate of thrashing, and a decreased rate of pharyngeal pumping (Wong et al. 1995). It was a surprise, however, that clk-1 worms also displayed extended longevity, because, at the time that it was discovered, only two other mutants, age-1 and daf-2, with very different phenotypes, had been found to extend longevity (Friedman and Johnson 1988; Kenyon et al. 1993).It is currently uncertain how mutations in clk-1 result in the overall slowing of development and physiologic rates as well as an extended life span. One classic theory of aging, called the rate of living theory, postulates the existence of a link between energy metabolism and aging (Pearl 1922; Speakman 2005). This theory proposes that what determines the life span of an organism is the rate at which it produces and uses energy at the cellular level. Thus, the fact that clk-1 worms exhibit slow physiologic rates and development suggests a decrease in the rate that these worms utilize energy, and, by the rate of living theory, this could account for their long life span.In support of the rate of living theory, the loss of clk-1 has been shown to result in decreased whole-worm oxygen consumption (Felkai et al. 1999; Yang et al. 2007) and decreased electron transfer from complex I to complex III in the electron transport chain (Kayser et al. 2004b), although this has not been observed by all investigators (Miyadera et al. 2001). While some reports have suggested that energy consumption is not reduced in clk-1 worms, at least under liquid culture conditions (Braeckman et al. 2002), the observation that clk-1 worms have higher levels of ATP than wild-type worms (Braeckman et al. 1999) suggests a decreased use of energy in clk-1 worms regardless of whether energy production is normal or decreased. It has also been found that clk-1 double-mutant combinations that exhibit slower development than clk-1 worms live even longer than clk-1 worms (Lakowski and Hekimi 1996). In addition, overexpression of clk-1 prevents the slowing of the defecation rate with age, increases mitochondrial function, and decreases life span (Felkai et al. 1999).Drawing on ideas from the free radical theory of aging (Harman 1956), it has been suggested that a possible mechanism underlying the rate of living theory is that decreased metabolism results in a lower rate of production of reactive oxygen species (ROS). As the free radical theory of aging proposes that aging results from the accumulation of molecular damage caused by ROS, then lower ROS production should result in slower aging. In clk-1 worms, it has not been possible to directly measure levels of ROS in vivo; however, measurement of hydrogen peroxide production from submitochondrial particles has demonstrated increased ROS generation in clk-1 mitochondria compared to wild type (Yang et al. 2009). In addition, the superoxide production potential is increased in clk-1 worms compared to wild-type N2 worms (Braeckman et al. 2002). Despite showing increased levels of ROS production, clk-1 worms have been found to have normal or decreased levels of oxidative damage (Kayser et al. 2004a; Yang et al. 2007, 2009) and decreased accumulation of lipofuscin (Braeckman et al. 2002). The decrease in oxidative damage that occurs in spite of increased ROS production likely results from increased antioxidant defenses. In support of this conclusion, sod-2 and sod-3 mRNA are increased in clk-1 worms compared to wild type (Yang et al. 2007).Clearly, the levels of ROS production and antioxidant defense are altered in clk-1 worms and likely contribute to the physiology and life span of these worms. Evidence supporting a role for altered ROS levels in determining the clk-1 phenotype comes from the demonstration that increasing the levels of ROS through decreasing superoxide dismutase expression has been shown to modulate a variety of phenotypes in clk-1 worms (Shibata et al. 2003; Yang et al. 2007). It is important to note, however, that the decrease in oxidative damage in clk-1 worms appears not to contribute to their long life as it is possible to experimentally increase oxidative damage in clk-1 worms beyond wild-type levels without reducing life span (Yang et al. 2007).In addition to clk-1, four other genes have been identified that yield a clk-1-like phenotype (Clk phenotype), which includes slow development, slow defecation, slow pharyngeal pumping, decreased brood size and long life span coupled with maternal rescue (homozygous mutants from heterozygous mothers are phenotypically normal) (Hekimi et al. 1995; Lemieux et al. 2001). The Clk phenotype has been studied in most detail in clk-1 worms (Wong et al. 1995) and, subsequently, with gro-1 (Lemieux et al. 2001), clk-2 (Benard et al. 2001), and tpk-1 worms (de Jong et al. 2004), while clk-3 worms have not been extensively studied [although clk-3 worm energy metabolism and oxygen consumption have been examined (Braeckman et al. 2002; Shoyama et al. 2009)]. Despite the phenotypic similarity of these mutants, the mutations that have been identified thus far have been shown to occur in genes encoding proteins with a wide range of functions with no obvious relationship to one another. gro-1 encodes a tRNA-modifying enzyme (Lemieux et al. 2001), clk-2 encodes a homolog of yeast Tel2p and a regulator of several PI3K-related protein kinases (Ahmed et al. 2001; Benard et al. 2001; Jiang et al. 2003; Takai et al. 2007), and tpk-1 encodes thiamine pyrophosphokinase, which is necessary for the assimilation of thiamine (vitamin B1) (de Jong et al. 2004).All of the Clk mutants that have been identified exhibit slow physiologic rates and increased life span, suggesting that one may be sufficient for the other. To test this hypothesis, we identified six novel Clk mutants and demonstrate that these strains bear all of the characteristic features of the Clk phenotype, including extended longevity. We further show that mitochondrial function is decreased in the Clk mutants but that this decrease does not result in increased resistance to oxidative stress or decreased oxidative damage. Our results provide a plausible explanation for the extended life span observed in the Clk mutants and support aspects of the rate of living theory of aging while casting further doubt on the free radical theory of aging.  相似文献   

19.
Retrogenes Reveal the Direction of Sex-Chromosome Evolution in Mosquitoes     
Melissa A. Toups  Matthew W. Hahn 《Genetics》2010,186(2):763-766
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   

20.
Genetic Evidence for an Essential Oscillation of Transmembrane-Spanning Segment 5 in the Escherichia coli Ammonium Channel AmtB     
William B. Inwood  Jason A. Hall  Kwang-Seo Kim  Rebecca Fong  Sydney Kustu 《Genetics》2009,183(4):1341-1355
Ammonium channels, called Amt or Mep, concentrate against a gradient. Each monomer of the trimer has a pore through which substrate passes and a C-terminal cytoplasmic extension. The importance of the C-terminal extension to AmtB activity remains unclear. We have described lesions in conserved C-terminal residues that inactivate AmtB and here characterize 38 intragenic suppressors upstream of the C terminus (∼1/3 of total suppressors). Three that occurred repeatedly, including the previously characterized W148L at the pore entry, restored growth at low NH3 to nearly wild-type levels and hence restored high activity. V116L completely restored function to two of the mutant proteins and, when separated from other lesions, did not damage wild-type AmtB. A179E notably altered folding of AmtB, compensated for all inactivating C-terminal lesions, and damaged wild-type AmtB. V116L and A179E lie at the cytoplasmic end of transmembrane-spanning segments (TM) 3 and 5, respectively, and the proximal part of the C-terminal tail makes intimate contacts with the loops following them before crossing to the adjacent monomer. Collectively, the properties of intragenic suppressor strains lead us to postulate that the C-terminal tail facilitates an oscillation of TM 5 that is required for coordinated pore function and high AmtB activity. Movement of TM 5 appears to control the opening of both the periplasmic entry and the cytoplasmic exit to the pore.Amt proteins are trimeric inner membrane channels for the hydrated gas (Andrade and Einsle 2007; Fong et al. 2007; Ludewig et al. 2007). They concentrate their substrate against a gradient (Kleiner and Fitzke 1981; Boussiba et al. 1984) and, to our knowledge, are the only active channels described. Each monomer of the Amt trimer contains a pore through which the substrate passes. Although the substrate for Amt channels appears to be , structural studies and molecular dynamics simulations indicate that neutral NH3 passes through the pore (Khademi et al. 2004; Zheng et al. 2004; Andrade et al. 2005; Lin et al. 2006; Nygaard et al. 2006; Javelle et al. 2007). Hence the pathway for the proton accompanying NH3 is not clear, but the two appear to separate during their passage through the channel (Mayer et al. 2006). Despite general similarities in charge and size to , K+ is neither a substrate for Amt proteins nor an inhibitor of their function (Fong et al. 2007; Javelle et al. 2008). It is for this reason that we refer to as a hydrated gas.The partly stacked phenyl rings of F107 and F215 block entry of NH3 into the Amt pore, and F215 appears to play a critical role in deprotonation of (Javelle et al. 2008). It has a high structural temperature (B) factor, indicating that it is mobile. The constriction at the periplasmic opening to the pore has been referred to as the “phe gate,” but we prefer the term “phe flap” because GlnK serves as a gate in the classical sense (Andrade et al. 2005; Javelle and Merrick 2005; Durand and Merrick 2006; Conroy et al. 2007; Gruswitz et al. 2007; and see below) and the two should not be confused. We will use the mechanical analogy that the “phe flap” is “open” as a shorthand way of designating that can somehow enter the channel. Although pores were sterically open when F215 (see discussion and Figure 7) was replaced with A, the channel was inactive (Javelle et al. 2008) and hence the mechanical analogy is not sufficient. Above the phe flap is a collar of residues that appears to bind [at the site designated S1 (Khademi et al. 2004)]. This collar, which includes the aromatic residues W148 and F107, has been proposed to play an essential role in recruitment of by π-cation interactions. However, we have shown that W148 restricts entry of into the channel and have proposed instead that the role of the collar is to restrict movement of through the channel (Fong et al. 2007). As the external concentration declines, increased flexibility of the collar/phe flap may allow more rapid entry of into the channel. At this time, it is not clear how much the functions of the collar and the phe flap overlap or can be distinguished.Open in a separate windowFigure 7.—Three-dimensional locations of intragenic suppressors of AmtBL394A (A) and AmtBfs (B). Stick models of AmtB were created using PyMOL as in Figure 1. Sections along the pore are perpendicular to the membrane. The periplasmic entry to the pore, which is marked by W148 in lime green, is at the left, and the cytoplasmic exit, which is marked by R47 of GlnK in red stick, is at the right. The threefold axis of the trimer is at the top and the lipid interface is at the bottom. The twin histidine residues at the center of the pore are in green stick, and there is a dot between them. F107 and F215 at the pore entrance are in green and are marked with asterisks. TM 3 is in cyan and TM 5 is in bright pink. TMs 1, 2, and 4 are in light shades of gray, TMs 6–10 are in dark shades of gray, and TM 11 is in brown. Interior loops are in shades of cyan and exterior loops are in shades of light pink. The C terminus is not in the plane of the section, but the C termini of adjacent monomers are in blue and gold. Positions at which suppressor lesions were obtained are space-filled and numbered in order. (A) Numbers correspond to the following: 1, Y32; 2, G113; 3, V116; 4, A118; 5, L119, 6, W148; 7, G175; and 8, A179. F125 is not visible. (B) Numbers correspond to the following: 1, L35; 2, G113; 3, G117; 4, A120; 5, W148; 6, V166; 7, A179; 8, R185; 9, P199; 10, G211; 11, R307; 12, C312; 13, V314; and 14, I359. Suppressors 2, 3, 9, 10, 12, and 13 are in yellow to make the numbers more visible.In addition to the pore, each monomer of the Amt trimer carries a cytoplasmic C-terminal extension of somewhat mysterious function. The cytoplasmic C-terminal extension of the Escherichia coli AmtB protein is ∼25 residues long and can fold precisely against cytoplasmic loops of the same monomer (loops 3, 5, and 1) and the adjacent monomer (loops 7 and 5) (Andrade et al. 2005; Conroy et al. 2007; Gruswitz et al. 2007) (Figure 1). After crossing between monomers, the distal end of the C-terminal extension completes the cytoplasmic vestibule of the adjacent monomer. Although it is known that C-terminal extensions are required for binding of the regulatory protein GlnK, which gates the channel when sufficient internal glutamine is available, it is not known precisely how the extension contributes to AmtB activity. A protein lacking the entire C-terminal tail (AmtBΔC-term) fails to bind GlnK but retains intermediate levels of activity, despite the fact that its three pores must be acting independently of one another (Coutts et al. 2002; Severi et al. 2007; Inwood et al. 2009).Open in a separate windowFigure 1.—View of the cytoplasmic face of AmtB and locations of polar connections at the cytoplasmic pore exit. (A) Space-filling model of the cytoplasmic face of E. coli AmtB. The model was created using PyMOL (Delano 2002) from Protein Data Bank entry 2NUU deposited by Conroy et al. (2007) and is similar to that of Neuhäuser et al. (2007). The cytoplasmic C-terminal tails are brown and the three monomers are in different shades of gray. Loop 5 of a single monomer is in pink, loop 1 is in yellow, and the cytoplasmic pore exit is indicated by a large black dot. Note the contacts between the tail and both the proximal and distal ends of loop 5 within a monomer. The tails cross from one monomer to another (counterclockwise) and make an additional contact with the distal end of loop 5 in the adjacent monomer (Conroy et al. 2007; Gruswitz et al. 2007). (B) Polar connections between cytoplasmic loop residues and R185 at the proximal end of loop 5. The stick representation, which is indicated by a box in A, was created using PyMOL. The C-terminal tail is in aqua, with the exception of L394, which is in gold. Residues making polar connections are numbered, and hydrogen bonds are indicated with dotted yellow lines. The cytoplasmic pore exit is indicated by R47 of GlnK, which is in red. Y404, which contacts the distal end of loop 5 in the monomer to which it is covalently attached, is indicated for all three monomers and marks the threefold symmetry axis for the trimer.Surprisingly, mutations that change residues in a kink about half way through the C-terminal tail inactivate AmtB. The kink is the point at which the tail crosses from one monomer to the next, and altering it even conservatively (e.g., the L394A substitution) inactivates AmtB. We have shown that the damaging effects of mutant C-terminal tails are relieved if the chaperone HflB cannot “tack” them (Inwood et al. 2009). Preventing “tacking,” or abnormal folding, can be effected either by extragenic lesions in the ATPase domain of HflB or by intragenic lesions that shorten the AmtB tail so that HflB cannot bind it. Both types of lesions mimic complete deletion of the tail and yield the intermediate level of activity of AmtBΔC-term.In this work, we examine intragenic suppressors of inactivating C-terminal lesions in amtB that affect regions upstream of the C terminus. Those that occur most frequently differ from C-terminal truncations and hflB suppressors in restoring activity toward wild type, i.e., to a much higher level than deletion of the C terminus. They indicate that the proximal portion of the C-terminal tail, which can bind precisely to cytoplasmic loops 3, 5, and 1 of the monomer to which it is covalently attached (Figure 1), plays a central role in channel activity. Analysis of upstream intragenic suppressors leads us to postulate that the proximal region of the tail may facilitate a movement of TM 5 (Andrade et al. 2005) that allows opening of the “phe flap” at the periplasmic entry to the pore. For this communication between the bottom and the top of the pore, the distal portion of the tail need not be normal; its sequence can apparently be randomized as long as it can be “tacked” by HflB to the adjacent monomer (Inwood et al. 2009). Inactivating C-terminal lesions in amtB appear to restrict the oscillation of TM 5, which is essential for channel function.  相似文献   

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