The Maize Mixed-Linkage (1→3),(1→4)-β-d-Glucan Polysaccharide Is Synthesized at the Golgi Membrane

With the exception of cellulose and callose, the cell wall polysaccharides are synthesized in Golgi membranes, packaged into vesicles, and exported to the plasma membrane where they are integrated into the microfibrillar structure. Consistent with this paradigm, several published reports have shown that the maize (Zea mays) mixed-linkage (1→3),(1→4)-β-d-glucan, a polysaccharide that among angiosperms is unique to the grasses and related Poales species, is synthesized in vitro with isolated maize coleoptile Golgi membranes and the nucleotide-sugar substrate, UDP-glucose. However, a recent study reported the inability to detect the β-glucan immunocytochemically at the Golgi, resulting in a hypothesis that the mixed-linkage β-glucan oligomers may be initiated at the Golgi but are polymerized at the plasma membrane surface. Here, we demonstrate that (1→3),(1→4)-β-d-glucans are detected immunocytochemically at the Golgi of the developing maize coleoptiles. Further, when maize seedlings at the third-leaf stage were pulse labeled with [¹⁴C]O₂ and Golgi membranes were isolated from elongating cells at the base of the developing leaves, (1→3),(1→4)-β-d-glucans of an average molecular mass of 250 kD and higher were detected in isolated Golgi membranes. When the pulse was followed by a chase period, the labeled polysaccharides of the Golgi membrane diminished with subsequent transfer to the cell wall. (1→3),(1→4)-β-d-Glucans of at least 250 kD were isolated from cell walls, but much larger aggregates were also detected, indicating a potential for intermolecular interactions with glucuronoarabinoxylans or intermolecular grafting in muro.An overwhelming body of evidence accumulated has established that the (1→4)-β-d-glucan chains of cellulose microfibrils are synthesized and assembled at the plasma membrane surface (Delmer, 1999; Saxena and Brown, 2005), whereas, with the lone exception of the (1→3)-β-d-glucan, callose, all noncellulosic pectin and cross-linking glycan polysaccharides are synthesized in Golgi membranes (Northcote and Pickett-Heaps, 1966; Ray et al., 1969, 1976; Harris and Northcote, 1971; Zhang and Staehelin, 1992). Using several plant systems, including grass species, autoradiography and membrane fractionation showed that monosaccharides from ¹⁴C-labeled substrates accumulated in cell wall polysaccharides in Golgi vesicles during a pulse were subsequently transferred to the cell wall when chased with unlabeled substrates (Northcote and Pickett-Heaps, 1966; Pickett-Heaps, 1967; Jilka et al., 1972). Early studies showed that labeled sugars from nucleotide-sugar substrates could be incorporated into alcohol-insoluble polysaccharides using microsomal membranes, and later refined by isolation of Golgi membranes and the synthesis of defined polysaccharides with combinations of nucleotide sugars (Bailey and Hassid, 1966; Ray et al., 1969, 1976; Smith and Stone, 1973; Ray, 1980; Hayashi and Matsuda, 1981a; Gordon and Maclachlan, 1989; Gibeaut and Carpita, 1993).When micromolar concentrations of substrates were used, only small chains of the glycan products were typically made in vitro. For example, xyloglucan oligomers with the characteristic α-d-Xyl-(1→6)-d-glucosyl unit, isoprimeverose, were synthesized with isolated microsomal membranes and low concentrations of UDP-Glc and UDP-Xyl (Ray et al., 1976; Hayashi and Matsuda, 1981b). When concentrations of each nucleotide sugar were increased to millimolar concentrations, then polysaccharides of about 250 kD were synthesized containing the characteristic XXXG heptasaccharide unit structure (Gordon and Maclachlan, 1989). Immunocytochemical evidence with antibodies directed against the terminal nonreducing xylosyl and fucosyl residues confirm that synthesis of the xyloglucan backbone begins in the cis-Golgi membrane and culminates with fucosylation in the trans-Golgi membrane and trans-Golgi network (Moore et al., 1991; Lynch and Staehelin, 1992; Zhang and Staehelin, 1992). The fucosyl transferase responsible for xyloglucan side chain decoration was also shown to be a Golgi-resident protein by in vitro synthesis of xyloglucan polymers (Camirand and Maclachlan, 1986).In Poales species, including all grasses, the mixed-linkage (1→3),(1→4)-β-d-glucan is a major cross-linking glycan that appears transiently during cell elongation in growing tissues and accumulates to large amounts in the cell walls of the endosperm of certain grains (Stone and Clarke, 1992; Trethewey et al., 2005). Bailey and Hassid (1966) demonstrated the synthesis in vitro of noncellulosic glucans with microsomal membranes from grasses. Henry and Stone (1982) used the Bacillus subtilis endoglucanase, an enzyme that generates diagnostic cellodextrin-(1→3)-β-Glc units from (1→3),(1→4)-β-d-glucan to show that the mixed-linkage β-glucan was made specifically with UDP-Glc and microsomal membranes. We used flotation centrifugation to obtain highly enriched Golgi membranes from which (1→3),(1→4)-β-d-glucans of an average of about 250 kD were synthesized (Gibeaut and Carpita, 1993).The BG1 monoclonal antibody recognizes the (1→3),(1→4)-β-d-glucan with high specificity (Meikle et al., 1994). This monoclonal antibody has been used to show dramatic changes in epitope abundance of (1→3),(1→4)-β-d-glucan in the cell walls of developing tissues (Meikle et al., 1994; Trethewey et al., 2005; McCann et al., 2007) and its appearance in the cell walls of Arabidopsis (Arabidopsis thaliana) following heterologous expression of genes thought to encode its synthases (Burton et al., 2006; Doblin et al., 2009). The failure to detect (1→3),(1→4)-β-d-glucan in Golgi membranes and only in the cell wall prompted Fincher (2009) to conclude that cellodextrin oligomers of the (1→3),(1→4)-β-d-glucan may be initiated in the Golgi membrane, but the actual polymerization of the polysaccharide occurs at the plasma membrane.While there is little question that synthesis of full-length polymers is possible in vitro with isolated Golgi membranes and UDP-Glc (Gibeaut and Carpita, 1993; Buckeridge et al., 1999, 2001; Urbanowicz et al., 2004), Fincher (2009) asserts correctly that there exists no experimental evidence that the polymer is made in vivo within the Golgi membrane in intact tissues. In fact, earlier work showing the paucity of immunolabeling of (1→3),(1→4)-β-d-glucan in Golgi membranes of developing wheat (Triticum aestivum) endosperm at a time of active deposition called to question the site of synthesis in vivo (Philippe et al., 2006). There is precedence for the synthesis of chitin in vitro with precociously activated chitisomes (Bracker et al., 1976), a vesicular package of chitin synthase that in vivo is quiescent until reaching the plasma membrane. No activity of chitin synthase from isolated plasma membranes could be demonstrated. In a similar way, the Golgi synthase activity of (1→3),(1→4)-β-d-glucan could be a precocious activation in vitro of a plasma membrane activity.As in vitro synthesis studies clearly show synthesis of full-length (1→3),(1→4)-β-d-glucan only at the Golgi, we reexamined the puzzling finding of its absence from Golgi bodies to determine the true site of synthesis in vivo. In contrast to Fincher (2009), our own immunocytochemistry shows (1→3),(1→4)-β-d-glucan is indeed in the Golgi membrane in 2-d-old coleoptiles, when rapid growth is just beginning. However, we are unable to detect the β-glucan in Golgi after the peak rate of elongation. We pulse labeled maize (Zea mays) seedlings with radiolabeled CO₂ and followed the fate of label captured by photosynthesis and translocated to elongating cells at the base of the seedling. We found by flotation centrifugation that Golgi membranes contain (1→3),(1→4)-β-d-glucan of at least 250 kD, similar to that of the product of in vitro synthesis at optimal UDP-Glc concentrations and commercial preparations of barley (Hordeum vulgare) endosperm (1→3),(1→4)-β-d-glucan (Gibeaut and Carpita, 1993; Buckeridge et al., 1999, 2001; Urbanowicz et al., 2004). When polysaccharides are extracted sequentially from the cell walls by hot ammonium oxalate, and increasing concentrations of NaOH to 4 m, the (1→3),(1→4)-β-d-glucans are found mostly in the higher concentrations of alkali fractions. While 250 kD polymers are observed, most of the (1→3),(1→4)-β-d-glucans eluted in fractions containing glucuronoarabinoxylans (GAXs), which are much larger, indicating either that an aggregation with GAXs increase the apparent size or that trans-glucosylation events increase the degree of polymerization of the (1→3),(1→4)-β-d-glucans.     

The Genetic Basis of Phenotypic Adaptation II: The Distribution of Adaptive Substitutions in the Moving Optimum Model

We consider a population that adapts to a gradually changing environment. Our aim is to describe how ecological and genetic factors combine to determine the genetic basis of adaptation. Specifically, we consider the evolution of a polygenic trait that is under stabilizing selection with a moving optimum. The ecological dynamics are defined by the strength of selection, , and the speed of the optimum, ; the key genetic parameters are the mutation rate Θ and the variance of the effects of new mutations, ω. We develop analytical approximations within an “adaptive-walk” framework and describe how selection acts as a sieve that transforms a given distribution of new mutations into the distribution of adaptive substitutions. Our analytical results are complemented by individual-based simulations. We find that (i) the ecological dynamics have a strong effect on the distribution of adaptive substitutions and their impact depends largely on a single composite measure , which combines the ecological and genetic parameters; (ii) depending on γ, we can distinguish two distinct adaptive regimes: for large γ the adaptive process is mutation limited and dominated by genetic constraints, whereas for small γ it is environmentally limited and dominated by the external ecological dynamics; (iii) deviations from the adaptive-walk approximation occur for large mutation rates, when different mutant alleles interact via linkage or epistasis; and (iv) in contrast to predictions from previous models assuming constant selection, the distribution of adaptive substitutions is generally not exponential.AN important aim for both empirical and theoretical evolutionary biologists is to better understand the genetics of adaptation (e.g., Orr 2005a). For example, among the multitude of mutations that arise in a population, which ones are eventually fixed and contribute to evolutionary change? That is, given a distribution of new mutations, what is the distribution of adaptive substitutions (or fixed mutations)? Here, distribution means the probability distribution of the effects of mutations on either the phenotype or the fitness of their carriers. In principle, both the distribution of new mutations and the distribution of adaptive substitutions can be measured empirically, the former from mutation accumulation experiments (Eyre-Walker and Keightley 2007) and the latter from QTL (e.g., Bradshaw et al. 1998) or experimental evolution (Elena and Lenski 2003) studies. However, as only a small subset of all mutations is beneficial, such measurements are difficult. Therefore, a large role in studying the genetics of adaptation has to be played by theoretical modeling.In recent years, several different approaches have emerged for modeling the process of adaptation. Considerable work exists, in particular, in the context of Fisher''s geometric model (e.g., Fisher 1930; Kimura 1983; Orr 1998; Welch and Waxman 2005; Martin and Lenormand 2006), Gillespie''s mutational landscape model (e.g., Gillespie 1983, 1984; Orr 2002), various models of so-called “adaptive walks” on rugged fitness landscapes (e.g., Kauffman and Levin 1987; Kauffman 1993), and models of clonal interference in asexual populations (e.g., Gerrish and Lenski 1998; Park and Krug 2007). Together, these models have yielded several robust predictions. For example, both Fisher''s geometric model and the mutational landscape model predict that the distribution of adaptive substitutions should be approximately exponential (with respect to either phenotype or fitness) (Orr 1998, 2002, 2005a,b). This means that most substitutions have little effect, but that a significant fraction of the overall evolutionary change is due to a small number of substitutions with large effects. These results are in qualitative agreement with empirical data (Orr 2005a; Elena and Lenski 2003) and have shed new light on the classical debate about micro- vs. macromutationalism (Fisher 1930; Provine 2001).One way to look at adaptation is to view selection as a sieve that transforms the distribution of new mutations into the distribution of adaptive substitutions (Turner 1981; Orr and Betancourt 2001). This perspective emphasizes the role of environmental factors and directly leads to the question of how different selective regimes (sieves) affect the adaptive process. Yet, almost all studies to date have focused on the simplest possible ecological scenario: a population that, after a sudden change in the environment, is now under constant stabilizing selection.In reality, however, environmental change is often gradual rather than sudden (e.g., Hairston et al. 2005; Thompson 2005; Parmesan 2006; Perron et al. 2008). To account for this possibility, several authors (Bello and Waxman 2006; Collins et al. 2007; Kopp and Hermisson 2007; Sato and Waxman 2008; Kopp and Hermisson 2009) have recently turned to the so-called moving optimum model, which was originally devised in the field of quantitative genetics (e.g., Lynch et al. 1991; Lynch and Lande 1993; Bürger and Lynch 1995; Bürger 1999; Waxman and Peck 1999; Bürger and Gimelfarb 2002; Nunney 2003; Jones et al. 2004). In this model, the selectively favored value of a quantitative trait changes over time, such that the trait is under a mixture of stabilizing and directional selection. An important aspect of the moving optimum model is that it introduces an additional timescale (the timescale of environmental change), which is absent in the previous models.In a recent article (Kopp and Hermisson 2009) and a previous note (Kopp and Hermisson 2007), we have used the moving optimum model to investigate the time to fixation of a single mutation and the order in which mutations of different phenotypic effect go to fixation. However, the fastest mutations in the short term are not necessarily those that dominate evolution in the long term. The present article focuses on this long-term evolution, which can be characterized by the distribution of adaptive substitutions.     

Polymorphic Genes of Major Effect: Consequences for Variation,Selection and Evolution in Arabidopsis thaliana

The importance of genes of major effect for evolutionary trajectories within and among natural populations has long been the subject of intense debate. For example, if allelic variation at a major-effect locus fundamentally alters the structure of quantitative trait variation, then fixation of a single locus can have rapid and profound effects on the rate or direction of subsequent evolutionary change. Using an Arabidopsis thaliana RIL mapping population, we compare G-matrix structure between lines possessing different alleles at ERECTA, a locus known to affect ecologically relevant variation in plant architecture. We find that the allele present at ERECTA significantly alters G-matrix structure—in particular the genetic correlations between branch number and flowering time traits—and may also modulate the strength of natural selection on these traits. Despite these differences, however, when we extend our analysis to determine how evolution might differ depending on the ERECTA allele, we find that predicted responses to selection are similar. To compare responses to selection between allele classes, we developed a resampling strategy that incorporates uncertainty in estimates of selection that can also be used for statistical comparisons of G matrices.THE structure of the genetic variation that underlies phenotypic traits has important consequences for understanding the evolution of quantitative traits (Fisher 1930; Lande 1979; Bulmer 1980; Kimura 1983; Orr 1998; Agrawal et al. 2001). Despite the infinitesimal model''s allure and theoretical tractability (see Orr and Coyne 1992; Orr 1998, 2005a,b for reviews of its influence), evidence has accumulated from several sources (artificial selection experiments, experimental evolution, and QTL mapping) to suggest that genes of major effect often contribute to quantitative traits. Thus, the frequency and role of genes of major effect in evolutionary quantitative genetics have been a subject of intense debate and investigation for close to 80 years (Fisher 1930; Kimura 1983; Orr 1998, 2005a,b). Beyond the conceptual implications, the prevalence of major-effect loci also affects our ability to determine the genetic basis of adaptations and species differences (e.g., Bradshaw et al. 1995, 1998).Although the existence of genes of major effect is no longer in doubt, we still lack basic empirical data on how segregating variation at such genes affects key components of evolutionary process (but see Carrière and Roff 1995). In other words, How does polymorphism at genes of major effect alter patterns of genetic variation and covariation, natural selection, and the likely response to selection? The lack of data stems, in part, from the methods used to detect genes of major effect: experimental evolution (e.g., Bull et al. 1997; Zeyl 2005) and QTL analysis (see Erickson et al. 2004 for a review) often detect such genes retrospectively after they have become fixed in experimental populations or the species pairs used to generate the mapping population. The consequences of polymorphism at these genes on patterns of variation, covariation, selection, and the response to selection—which can be transient (Agrawal et al. 2001)—are thus often unobserved.A partial exception to the absence of data on the effects of major genes comes from artificial selection experiments, in which a substantial evolutionary response to selection in the phenotype after a plateau is often interpreted as evidence for the fixation of a major-effect locus (Frankham et al. 1968; Yoo 1980a,b; Frankham 1980; Shrimpton and Robertson 1988a,b; Caballero et al. 1991; Keightley 1998; see Mackay 1990 and Hill and Caballero 1992 for reviews). However, many of these experiments report only data on the selected phenotype (e.g., bristle number) or, alternatively, the selected phenotype and some measure of fitness (e.g., Frankham et al. 1968, Yoo 1980b; Caballero et al. 1991; Mackay et al. 1994; Fry et al. 1995; Nuzhdin et al. 1995; Zur Lage et al. 1997), making it difficult to infer how a mutation will affect variation, covariation, selection, and evolutionary responses for a suite of traits that might affect fitness themselves. One approach is to document how variation at individual genes of major effect affects the genetic variance–covariance matrix (“G matrix”; Lande 1979), which represents the additive genetic variance and covariance between traits.Although direct evidence for variation at major-effect genes altering patterns of genetic variation, covariation, and selection is rare, there is abundant evidence for the genetic mechanisms that could produce these dynamics. A gene of major effect could have these consequences due to any of at least three genetic mechanisms: (1) pleiotropy, where a gene of major effect influences several traits, including potentially fitness, simultaneously, (2) physical linkage or linkage disequilibrium (LD), in which a gene of major effect is either physically linked or in LD with other genes that influence other traits under selection, and (3) epistasis, in which the allele present at a major-effect gene alters the phenotypic effect of other loci and potentially phenotypes under selection. Evidence for these three evolutionary genetic mechanisms leading to changes in suites of traits comes from a variety of sources, including mutation accumulation experiments (Clark et al. 1995; Fernandez and Lopez-Fanjul 1996), mutation induction experiments (Keightley and Ohnishi 1998), artificial selection experiments (Long et al. 1995), and transposable element insertions (Rollmann et al. 2006). For pleiotropy in particular, major-effect genes that have consequences on several phenotypic traits are well known from the domestication and livestock breeding literature [e.g., myostatin mutations in Belgian blue cattle and whippets (Arthur 1995; Grobet et al. 1997; Mosher et al. 2007), halothane genes in pigs (Christian and Rothschild 1991; Fujii et al. 1991), and Booroola and Inverdale genes in sheep (Amer et al. 1999; Visscher et al. 2000)]. While these data suggest that variation at major-effect genes could—and probably does—influence variation, covariation, and selection on quantitative traits, data on the magnitude of these consequences remain lacking.Recombinant inbred line (RIL) populations are a promising tool for investigating the influence of major-effect loci. During advancement of the lines from F₂''s to RILs, alternate alleles at major-effect genes (and most of the rest of the genome) will be made homozygous, simplifying comparisons among genotypic classes. Because of the high homozygosity, individuals within RILs are nearly genetically identical, facilitating phenotyping of many genotypes under a range of environments. In addition, because of recombination, alternative alleles are randomized across genetic backgrounds—facilitating robust comparisons between sets of lines differing at a major-effect locus.Here we investigate how polymorphism at an artificially induced mutation, the erecta locus in Arabidopsis thaliana, affects the magnitude of these important evolutionary genetic parameters under ecologically realistic field conditions. We use the Landsberg erecta (Ler) × Columbia (Col) RIL population of A. thaliana to examine how variation at a gene of major effect influences genetic variation, covariation, and selection on quantitative traits in a field setting. The Ler × Col RIL population is particularly suitable, because it segregates for an artificially induced mutation at the erecta locus, which has been shown to influence a wide variety of plant traits. The Ler × Col population thus allows a powerful test of the effects of segregating variation at a gene—chosen a priori—with numerous pleiotropic effects. The ERECTA gene is a leucine-rich receptor-like kinase (LRR-RLK) (Torii et al. 1996) and has been shown to affect plant growth rates (El-Lithy et al. 2004), stomatal patterning and transpiration efficiency (Masle et al. 2005; Shpak et al. 2005), bacterial pathogen resistance (Godiard et al. 2003), inflorescence and floral organ size and shape (Douglas et al. 2002; Shpak et al. 2003, 2004), and leaf polarity (Xu et al. 2003; Qi et al. 2004).Specifically, we sought to answer the following questions: (1) Is variation at erecta significantly associated with changes to the G matrix? (2) Is variation at erecta associated with changes in natural selection on genetically variable traits? And (3) is variation at erecta associated with significantly different projected evolutionary responses to selection?     

The Conserved miR-51 microRNA Family Is Redundantly Required for Embryonic Development and Pharynx Attachment in Caenorhabditis elegans

A major question about cytokinesis concerns the role of the septin proteins, which localize to the division site in all animal and fungal cells but are essential for cytokinesis only in some cell types. For example, in Schizosaccharomyces pombe, four septins localize to the division site, but deletion of the four genes produces only a modest delay in cell separation. To ask if the S. pombe septins function redundantly in cytokinesis, we conducted a synthetic-lethal screen in a septin-deficient strain and identified seven mutations. One mutation affects Cdc4, a myosin light chain that is an essential component of the cytokinetic actomyosin ring. Five others cause frequent cell lysis during cell separation and map to two loci. These mutations and their dosage suppressors define a signaling pathway (including Rho1 and a novel arrestin) for repairing cell-wall damage. The seventh mutation affects the poorly understood RNA-binding protein Scw1 and severely delays cell separation when combined either with a septin mutation or with a mutation affecting the septin-interacting, anillin-like protein Mid2, suggesting that Scw1 functions in a pathway parallel to that of the septins. Taken together, our results suggest that the S. pombe septins participate redundantly in one or more pathways that cooperate with the actomyosin ring during cytokinesis and that a septin defect causes septum defects that can be repaired effectively only when the cell-integrity pathway is intact.THE fission yeast Schizosaccharomyces pombe provides an outstanding model system for studies of cytokinesis (McCollum and Gould 2001; Balasubramanian et al. 2004; Pollard and Wu 2010). As in most animal cells, successful cytokinesis in S. pombe requires an actomyosin ring (AMR). The AMR begins to assemble at the G₂/M transition and involves the type II myosin heavy chains Myo2 and Myp2 and the light chains Cdc4 and Rlc1 (Wu et al. 2003). Myo2 and Cdc4 are essential for cytokinesis under all known conditions, Rlc1 is important at all temperatures but essential only at low temperatures, and Myp2 is essential only under stress conditions. As the AMR constricts, a septum of cell wall is formed between the daughter cells. The primary septum is sandwiched by secondary septa and subsequently digested to allow cell separation (Humbel et al. 2001; Sipiczki 2007). Because of the internal turgor pressure of the cells, the proper assembly and structural integrity of the septal layers are essential for cell survival.Septum formation involves the β-glucan synthases Bgs1/Cps1/Drc1, Bgs3, and Bgs4 (Ishiguro et al. 1997; Le Goff et al. 1999; Liu et al. 1999, 2002; Martín et al. 2003; Cortés et al. 2005) and the α-glucan synthase Ags1/Mok1 (Hochstenbach et al. 1998; Katayama et al. 1999). These synthases are regulated by the Rho GTPases Rho1 and Rho2 and the protein kinase C isoforms Pck1 and Pck2 (Arellano et al. 1996, 1997, 1999; Nakano et al. 1997; Hirata et al. 1998; Calonge et al. 2000; Sayers et al. 2000; Ma et al. 2006; Barba et al. 2008; García et al. 2009b). The Rho GTPases themselves appear to be regulated by both GTPase-activating proteins (GAPs) and guanine-nucleotide-exchange factors (GEFs) (Nakano et al. 2001; Calonge et al. 2003; Iwaki et al. 2003; Tajadura et al. 2004; Morrell-Falvey et al. 2005; Mutoh et al. 2005; García et al. 2006, 2009a,b). In addition, septum formation and AMR function appear to be interdependent. In the absence of a normal AMR, cells form aberrant septa and/or deposit septal materials at random locations, whereas a mutant defective in septum formation (bgs1) is also defective in AMR constriction (Gould and Simanis 1997; Le Goff et al. 1999; Liu et al. 1999, 2000). Both AMR constriction and septum formation also depend on the septation initiation network involving the small GTPase Spg1 (McCollum and Gould 2001; Krapp and Simanis 2008). Despite this considerable progress, many questions remain about the mechanisms and regulation of septum formation and its relationships to the function of the AMR.One major question concerns the role(s) of the septins. Proteins of this family are ubiquitous in fungal and animal cells and typically localize to the cell cortex, where they appear to serve as scaffolds and diffusion barriers for other proteins that participate in a wide variety of cellular processes (Longtine et al. 1996; Gladfelter et al. 2001; Hall et al. 2008; Caudron and Barral 2009). Despite the recent progress in elucidating the mechanisms of septin assembly (John et al. 2007; Sirajuddin et al. 2007; Bertin et al. 2008; McMurray and Thorner 2008), the details of septin function remain obscure. However, one prominent role of the septins and associated proteins is in cytokinesis. Septins concentrate at the division site in every cell type that has been examined, and in Saccharomyces cerevisiae (Hartwell 1971; Longtine et al. 1996; Lippincott et al. 2001; Dobbelaere and Barral 2004) and at least some Drosophila (Neufeld and Rubin 1994; Adam et al. 2000) and mammalian (Kinoshita et al. 1997; Surka et al. 2002) cell types, the septins are essential for cytokinesis. In S. cerevisiae, the septins are required for formation of the AMR (Bi et al. 1998; Lippincott and Li 1998). However, this cannot be their only role, because the AMR itself is not essential for cytokinesis in this organism (Bi et al. 1998; Korinek et al. 2000; Schmidt et al. 2002). Moreover, there is no evidence that the septins are necessary for AMR formation or function in any other organism. A further complication is that in some cell types, including most Caenorhabditis elegans cells (Nguyen et al. 2000; Maddox et al. 2007) and some Drosophila cells (Adam et al. 2000; Field et al. 2008), the septins do not appear to be essential for cytokinesis even though they localize to the division site.S. pombe has seven septins, four of which (Spn1, Spn2, Spn3, and Spn4) are expressed in vegetative cells and localize to the division site shortly before AMR constriction and septum formation (Longtine et al. 1996; Berlin et al. 2003; Tasto et al. 2003; Wu et al. 2003; An et al. 2004; Petit et al. 2005; Pan et al. 2007; Onishi et al. 2010). Spn1 and Spn4 appear to be the core members of the septin complex (An et al. 2004; McMurray and Thorner 2008), and mutants lacking either of these proteins do not assemble the others at the division site. Assembly of a normal septin ring also depends on the anillin-like protein Mid2, which colocalizes with the septins (Berlin et al. 2003; Tasto et al. 2003). Surprisingly, mutants lacking the septins are viable and form seemingly complete septa with approximately normal timing. These mutants do, however, display a variable delay in separation of the daughter cells, suggesting that the septins play some role(s) in the proper completion of the septum or in subsequent processes necessary for cell separation (Longtine et al. 1996; An et al. 2004; Martín-Cuadrado et al. 2005).It is possible that the septins localize to the division site and yet are nonessential for division in some cell types because their role is redundant with that of some other protein(s) or pathway(s). To explore this possibility in S. pombe, we screened for mutations that were lethal in combination with a lack of septins. The results suggest that the septins cooperate with the AMR during cytokinesis and that, in the absence of septin function, the septum is not formed properly, so that an intact system for recognizing and repairing cell-wall damage becomes critical for cell survival.     

Profiling Sex-Specific piRNAs in Zebrafish

Piwi proteins and their partner small RNAs play an essential role in fertility, germ-line stem cell development, and the basic control and evolution of animal genomes. However, little knowledge exists regarding piRNA biogenesis. Utilizing microfluidic chip analysis, we present a quantitative profile of zebrafish piRNAs expressed differentially between testis and ovary. The sex-specific piRNAs are derived from separate loci of repeat elements in the genome. Ovarian piRNAs can be categorized into groups that reach up to 92 members, indicating a sex-specific arrangement of piRNA genes in the genome. Furthermore, precursor piRNAs preferentially form a hairpin structure at the 3′end, which seem to favor the generation of mature sex-specific piRNAs. In addition, the mature piRNAs from both the testis and the ovary are 2′-O-methylated at their 3′ ends.SMALL RNAs, ranging from 19 to 30 nucleotides (nt) in length, constitute a large family of regulatory molecules with diverse functions in invertebrates, vertebrates, plants, and fungi (Bartel 2004; Nakayashiki 2005). Two major classes of small RNAs are microRNAs (miRNAs) and small interfering RNAs (siRNAs). The functions of small RNAs have been conserved through evolution; they have been shown to inhibit gene expression at the levels of mRNA degradation, translational repression, chromatin modification, heterochromatin formation, and DNA elimination (Mochizuki et al. 2002; Bartel 2004; Kim et al. 2005; Brodersen and Voinnet 2006; Lee and Collins 2006; Vaucheret 2006).Over the past few years, focus on the genetics of small RNAs has helped clarify the mechanisms behind the regulation of these molecules. While hundreds of small RNAs have been identified from mammalian somatic tissues, relatively little is known about small RNAs in germ cells. A recent breakthrough has been the identification of small RNAs that associate with Piwi proteins (piRNAs) from Drosophila and mammalian gonads (Aravin et al. 2001, 2006; Girard et al. 2006; Grivna et al. 2006; Vagin et al. 2006; Watanabe et al. 2006). piRNAs and their interacting proteins Ziwi/Zili have also been identified in zebrafish (Houwing et al. 2007, 2008). Increasing evidence indicates that piRNAs play roles mainly in germ cell differentiation and genomic stability (Carthew 2006; Lau et al. 2006; Vagin et al. 2006; Brennecke et al. 2007; Chambeyron et al. 2008; Klattenhoff and Theurkauf 2008; Kuramochi-Miyagawa et al. 2008; Kim et al. 2009; Lim et al. 2009; Unhavaithaya et al. 2009). Moreover, although piRNAs are mostly expressed in germ line cells, recent studies showed piRNA expression in nongerm cells, for example, T-cell lines (Jurkat cells and MT4) (Azuma-Mukai et al. 2008; Yeung et al. 2009), indicating other functions such as in the immune system. piRNAs do not appear to be derived from double-stranded RNA precursors, and their biogenesis mechanisms, although unclear, may be distinct from those of siRNA and miRNA. Recently, two distinct piRNA production pathways were further proposed: the “ping-pong” model (Brennecke et al. 2007; Gunawardane et al. 2007) and the Ago3-independent piRNA pathway centered on Piwi in somatic cells (Li et al. 2009; Malone et al. 2009). However, the mechanistic pathways of piRNA activity and their biogenesis are still largely unknown.Teleost fishes comprise >24,000 species, accounting for more than half of extant vertebrate species, displaying remarkable variation in morphological and physiological adaptations (see review in Zhou et al. 2001). Recently, Houwing et al. (2007, 2008) reported findings on Ziwi/Zili and associated piRNAs, implicating roles in germ cell differentiation, meiosis, and transposon silencing in the germline of the zebrafish. However, some of the identified zebrafish piRNAs are nonrepetitive and nontransposon-related piRNAs, suggesting that piRNAs may have additional unknown roles. In this study, we show that for males and females, piRNAs are specifically derived from separate loci of the repeat elements, and that ovarian piRNAs are far more often associated in groups. Genomic analysis of piRNAs indicates a tendency to folding at the 3′ end of the piRNA precursor, which may favor cleavage of the piRNA precursor to generate mature sex-specific piRNAs. Furthermore, methylation modification occurs at the 2′-O-hydroxyl group on the ribose of the final 3′ nucleotide in both the testis and the ovary.     

Sexual Isolation in Acinetobacter baylyi Is Locus-Specific and Varies 10,000-Fold Over the Genome

Naturally transformable bacteria acquire chromosomal DNA from related species at lower frequencies than from cognate DNA sources. To determine how genome location affects heterogamic transformation in bacteria, we inserted an nptI marker into random chromosome locations in 19 different strains of the Acinetobacter genus (>24% divergent at the mutS/trpE loci). DNA from a total of 95 nptI-tagged isolates was used to transform the recipient Acinetobacter baylyi strain ADP1. A total of >1300 transformation assays revealed that at least one nptI-tagged isolate for each of the strains/species tested resulted in detectable integration of the nptI marker into the ADP1 genome. Transformation frequencies varied up to ∼10,000-fold among independent nptI insertions within a strain. The location and local sequence divergence of the nptI flanking regions were determined in the transformants. Heterogamic transformation depended on RecA and was hampered by DNA mismatch repair. Our studies suggest that single-locus-based studies, and inference of transfer frequencies from general estimates of genomic sequence divergence, is insufficient to predict the recombination potential of chromosomal DNA fragments between more divergent genomes. Interspecies differences in overall gene content, and conflicts in local gene organization and synteny are likely important determinants of the genomewide variation in recombination rates between bacterial species.HORIZONTAL gene transfer (HGT) contributes to bacterial evolution by providing access to DNA evolved and retained in separate species or strains (Cohan 1994a,b; Bergstrom et al. 2000; Ochman et al. 2000; Feil et al. 2001; Koonin 2003; Lawrence and Hendrickson 2003; Fraser et al. 2007). Multilocus sequence typing (MLST) has provided strong evidence for frequent transfer and recombination of chromosomal DNA between related bacterial strains within the same species (Maiden et al. 1998; Enright et al. 2002). HGT occurring by natural transformation allows bacteria to exploit the presence of nucleic acids in their environment for the purposes of nutrition, DNA repair, reacquisition of lost genes, and/or acquisition of novel genetic diversity (Redfield 1993; Mehr and Seifert 1998; Dubnau 1999; Claverys et al. 2000; Szöllösi et al. 2006; Johnsen et al. 2009). It can be inferred from observations of the presence of extracellular DNA in most environments that bacteria are constantly exposed to DNA from a variety of sources, without such exposure necessarily producing observable changes in the genetic compositions of bacterial populations over evolutionary time (Thomas and Nielsen 2005; Nielsen et al. 2007a,b).The absence of sequence similarity between the donor DNA and the DNA of the recipient bacterium is the strongest barrier to the horizontal acquisition of chromosomal genes in bacteria (Matic et al. 1996; Vulic et al. 1997; Majewski 2001; Townsend et al. 2003) as illegitimate recombination occurs only at extremely low frequencies in bacteria (Hülter and Wackernagel 2008a). Single-locus transfer models have been extensively applied and have demonstrated a log-linear decrease in recombination frequencies with increasing sequence divergence for Bacillus subtilis (Roberts and Cohan, 1993; Zawadzki et al. 1995), Acinetobacter baylyi (Young and Ornston 2001), Escherichia coli (Shen and Huang 1986; Vulic et al. 1997), and Streptococcus pneumoniae (Majewski et al. 2000). For instance, heterogamic transformation between nonmutator isolates at the rpoB locus of B. mojavensis is undetectable at sequence divergences >16.7% (Zawadzki et al. 1995) and between S. pneumoniae isolates with sequence divergences >18% (Majewski et al. 2000). In A. baylyi, the nonmutator sequence divergence limit for detectable transformation at the pcaH locus of strain ADP1 was found to be 20% (Young and Ornston 2001), and up to 24% overall divergence yielded transformants at 16S rRNA loci in strain DSM587 (Strätz et al. 1996).Several recent studies also show that short stretches (<200 bp) of DNA sequence identity can facilitate additive or substitutive integration of longer stretches (>1000 bp) of heterologous DNA in bacteria (Prudhomme et al. 1991, 2002; de Vries and Wackernagel 2002; Hülter and Wackernagel 2008a). Thus, the uptake of DNA in bacteria can facilitate larger substitutions within gene sequences and the integration of additional DNA material on the basis of recombination initiated in flanking DNA stretches (either at one or both ends) with high sequence similarity (Nielsen et al. 2000). On the other hand, segments of heterologous DNA interrupting the synteny of homologous DNA have also been shown to be a barrier in intraspecies transformation in S. pneumoniae (Pasta and Sicard 1996, 1999).The various studies of the interspecies transfer potential of single genes demonstrate that the immediate local sequence divergence of the transferred locus is of high importance in determining recombination frequencies in hosts up to 20% divergent (at the housekeeping gene level). However, it can be hypothesized that the broader structural, organizational, and biochemical properties of the genome region surrounding a particular locus will determine its transfer potential to more divergent host species (Cohan 2001; Lawrence 2002). The interspecies transfer potential of various genome regions/loci between more diverged species (>20% at the housekeeping gene level) may therefore differ substantially from a log-linear model (determined experimentally for more closely related species) as local gene organization becomes less conserved with evolutionary time. The barriers to gene exchange between divergent bacterial species is likely a combination of inefficient recombination due to both mismatched base pairs (the main determinator in the log-linear model) and conflicting gene order and organization across the local recombining DNA regions. In addition, selective barriers due to negative effects on host fitness of the transferred DNA regions may become increasingly important for the removal of recombination events from the bacterial population. Recent bioinformatics-based genome analysis of E. coli and Salmonella genomes suggests various parts of the bacterial genome may have different suceptibilities to undergo evolutionarily successful recombination leading to temporal fragmentation of speciation (Lawrence 2002; Retchless and Lawrence 2007). Nevertheless, few studies have experimentally tested the effect of variable species and chromosome locations of genes on their transfer potential between bacteria (Ravin and Chen 1967; Ravin and Chakrabarti 1975; Siddiqui and Goldberg 1975; Cohan et al. 1991; Huang et al. 1991; Fall et al. 2007).Here, we determine to what extent genome location contributes to sexual isolation between the recipient A. baylyi strain ADP1 and 19 sequence divergent (24–27% divergent at the mutS/trpE loci) donor Acinetobacter strains and species (carrying a selectable nptI gene in a total of 95 random genome locations).