Age Structure,Changing Demography and Effective Population Size in Atlantic Salmon (Salmo salar)

Effective population size (N_e) is a central evolutionary concept, but its genetic estimation can be significantly complicated by age structure. Here we investigate N_e in Atlantic salmon (Salmo salar) populations that have undergone changes in demography and population dynamics, applying four different genetic estimators. For this purpose we use genetic data (14 microsatellite markers) from archived scale samples collected between 1951 and 2004. Through life table simulations we assess the genetic consequences of life history variation on N_e. Although variation in reproductive contribution by mature parr affects age structure, we find that its effect on N_e estimation may be relatively minor. A comparison of estimator models suggests that even low iteroparity may upwardly bias N_e estimates when ignored (semelparity assumed) and should thus empirically be accounted for. Our results indicate that N_e may have changed over time in relatively small populations, but otherwise remained stable. Our ability to detect changes in N_e in larger populations was, however, likely hindered by sampling limitations. An evaluation of N_e estimates in a demographic context suggests that life history diversity, density-dependent factors, and metapopulation dynamics may all affect the genetic stability of these populations.THE effective size of a population (N_e) is an evolutionary parameter that can be informative on the strength of stochastic evolutionary processes, the relevance of which relative to deterministic forces has been debated for decades (e.g., Lande 1988). Stochastic forces include environmental, demographic, and genetic components, the latter two of which are thought to be more prominent at reduced population size, with potentially detrimental consequences for average individual fitness and population persistence (Newman and Pilson 1997; Saccheri et al. 1998; Frankham 2005). The quantification of N_e in conservation programs is thus frequently advocated (e.g., Luikart and Cornuet 1998; Schwartz et al. 2007), although gene flow deserves equal consideration given its countering effects on genetic stochasticity (Frankham et al. 2003; Palstra and Ruzzante 2008).Effective population size is determined mainly by the lifetime reproductive success of individuals in a population (Wright 1938; Felsenstein 1971). Variance in reproductive success, sex ratio, and population size fluctuations can reduce N_e below census population size (Frankham 1995). Given the difficulty in directly estimating N_e through quantification of these demographic factors (reviewed by Caballero 1994), efforts have been directed at inferring N_e indirectly through measurement of its genetic consequences (see Leberg 2005, Wang 2005, and Palstra and Ruzzante 2008 for reviews). Studies employing this approach have quantified historical levels of genetic diversity and genetic threats to population persistence (e.g., Nielsen et al. 1999b; Miller and Waits 2003; Johnson et al. 2004). N_e has been extensively studied in (commercially important) fish species, due to the common availability of collections of archived samples that facilitate genetic estimation using the temporal method (e.g., Hauser et al. 2002; Shrimpton and Heath 2003; Gomez-Uchida and Banks 2006; Saillant and Gold 2006).Most models relating N_e to a population''s genetic behavior make simplifying assumptions regarding population dynamics. Chiefly among these is the assumption of discrete generations, frequently violated in practice given that most natural populations are age structured with overlapping generations. Here, theoretical predictions still apply, provided that population size and age structure are constant (Felsenstein 1971; Hill 1972). Ignored age structure can introduce bias into temporal genetic methods for the estimation of N_e, especially for samples separated by time spans that are short relative to generation interval (Jorde and Ryman 1995; Waples and Yokota 2007; Palstra and Ruzzante 2008). Moreover, estimation methods that do account for age structure (e.g., Jorde and Ryman 1995) still assume this structure to be constant. Population dynamics will, however, likely be altered as population size changes, thus making precise quantifications of the genetic consequences of acute population declines difficult (Nunney 1993; Engen et al. 2005; Waples and Yokota 2007). This problem may be particularly relevant when declines are driven by anthropogenic impacts, such as selective harvesting regimes, that can affect age structure and N_e simultaneously (Ryman et al. 1981; Allendorf et al. 2008). Demographic changes thus have broad conservation implications, as they can affect a population''s sensitivity to environmental stochasticity and years of poor recruitment (Warner and Chesson 1985; Ellner and Hairston 1994; Gaggiotti and Vetter 1999). Consequently, although there is an urgent need to elucidate the genetic consequences of population declines, relatively little is understood about the behavior of N_e when population dynamics change (but see Engen et al. 2005, 2007).Here we focus on age structure and N_e in Atlantic salmon (Salmo salar) river populations in Newfoundland and Labrador. The freshwater habitat in this part of the species'' distribution range is relatively pristine (Parrish et al. 1998), yet Atlantic salmon in this area have experienced demographic declines, associated with a commercial marine fishery, characterized by high exploitation rates (40–80% of anadromous runs; Dempson et al. 2001). A fishery moratorium was declared in 1992, with rivers displaying differential recovery patterns since then (Dempson et al. 2004b), suggesting a geographically variable impact of deterministic and stochastic factors, possibly including genetics. An evaluation of those genetic consequences thus requires accounting for potential changes in population dynamics as well as in life history. Life history in Atlantic salmon can be highly versatile (Fleming 1996; Hutchings and Jones 1998; Fleming and Reynolds 2004), as exemplified by the high variation in age-at-maturity displayed among and within populations (Hutchings and Jones 1998), partly reflecting high phenotypic plasticity (Hutchings 2004). This diversity is particularly evident in the reproductive biology of males, which can mature as parr during juvenile freshwater stages (Jones and King 1952; Fleming and Reynolds 2004) and/or at various ages as anadromous individuals, when returning to spawn in freshwater from ocean migration. Variability in life history strategies is further augmented by iteroparity, which can be viewed as a bet-hedging strategy to deal with environmental uncertainty (e.g., Orzack and Tuljapurkar 1989; Fleming and Reynolds 2004). Life history diversity and plasticity may allow salmonid fish populations to alter and optimize their life history under changing demography and population dynamics, potentially acting to stabilize N_e. Reduced variance in individual reproductive success at low breeder abundance (genetic compensation) will achieve similar effects and might be a realistic aspect of salmonid breeding systems (Ardren and Kapuscinski 2003; Fraser et al. 2007b). Little is currently known about the relationships between life history plasticity, demographic change and N_e, partly due to scarcity of the multivariate data required for these analyses.Our objective in this article is twofold. First, we use demographic data for rivers in Newfoundland to quantify how life history variation influences age structure in Atlantic salmon and hence N_e and its empirical estimation from genetic data. We find that variation in reproductive contribution by mature parr has a much smaller effect on the estimation of N_e than is often assumed. Second, we use temporal genetic data to estimate N_e and quantify the genetic consequences of demographic changes. We attempt to account for potential sources of bias, associated with (changes in) age structure and life history, by using four different analytical models to estimate N_e: a single-sample estimator using the linkage disequilibrium method (Hill 1981), the temporal model assuming discrete generations (Nei and Tajima 1981; Waples 1989), and two temporal models for species with overlapping generations (Waples 1990a,b; Jorde and Ryman 1995) that differ principally in assumptions regarding iteroparity. A comparison of results from these different estimators suggests that iteroparity may often warrant analytical consideration, even when it is presumably low. Although sometimes limited by statistical power, a quantification and comparison of temporal changes in N_e among river populations suggests a more prominent impact of demographic changes on N_e in relatively small river populations.     

Identification of an l-Arabinose Reductase Gene in Aspergillus niger and Its Role in l-Arabinose Catabolism

The first enzyme in the pathway for l-arabinose catabolism in eukaryotic microorganisms is a reductase, reducing l-arabinose to l-arabitol. The enzymes catalyzing this reduction are in general nonspecific and would also reduce d-xylose to xylitol, the first step in eukaryotic d-xylose catabolism. It is not clear whether microorganisms use different enzymes depending on the carbon source. Here we show that Aspergillus niger makes use of two different enzymes. We identified, cloned, and characterized an l-arabinose reductase, larA, that is different from the d-xylose reductase, xyrA. The larA is up-regulated on l-arabinose, while the xyrA is up-regulated on d-xylose. There is however an initial up-regulation of larA also on d-xylose but that fades away after about 4 h. The deletion of the larA gene in A. niger results in a slow growth phenotype on l-arabinose, whereas the growth on d-xylose is unaffected. The l-arabinose reductase can convert l-arabinose and d-xylose to their corresponding sugar alcohols but has a higher affinity for l-arabinose. The K_m for l-arabinose is 54 ± 6 mm and for d-xylose 155 ± 15 mm.     

Uptake of L-cystine via an ABC transporter contributes defense of oxidative stress in the L-cystine export-dependent manner in Escherichia coli

Intracellular thiols like L-cystine and L-cystine play a critical role in the regulation of cellular processes. Here we show that Escherichia coli has two L-cystine transporters, the symporter YdjN and the ATP-binding cassette importer FliY-YecSC. These proteins import L-cystine, an oxidized product of L-cystine from the periplasm to the cytoplasm. The symporter YdjN, which is expected to be a new member of the L-cystine regulon, is a low affinity L-cystine transporter (K _m = 1.1 μM) that is mainly involved in L-cystine uptake from outside as a nutrient. E. coli has only two L-cystine importers because ΔydjNΔyecS mutant cells are not capable of growing in the minimal medium containing L-cystine as a sole sulfur source. Another protein YecSC is the FliY-dependent L-cystine transporter that functions cooperatively with the L-cystine transporter YdeD, which exports L-cystine as reducing equivalents from the cytoplasm to the periplasm, to prevent E. coli cells from oxidative stress. The exported L-cystine can reduce the periplasmic hydrogen peroxide to water, and then generated L-cystine is imported back into the cytoplasm via the ATP-binding cassette transporter YecSC with a high affinity to L-cystine (K _m = 110 nM) in a manner dependent on FliY, the periplasmic L-cystine-binding protein. The double disruption of ydeD and fliY increased cellular levels of lipid peroxides. From these findings, we propose that the hydrogen peroxide-inducible L-cystine/L-cystine shuttle system plays a role of detoxification of hydrogen peroxide before lipid peroxidation occurs, and then might specific prevent damage to membrane lipids.     

Population Structure With Localized Haplotype Clusters

We propose a multilocus version of F_ST and a measure of haplotype diversity using localized haplotype clusters. Specifically, we use haplotype clusters identified with BEAGLE, which is a program implementing a hidden Markov model for localized haplotype clustering and performing several functions including inference of haplotype phase. We apply this methodology to HapMap phase 3 data. With this haplotype-cluster approach, African populations have highest diversity and lowest divergence from the ancestral population, East Asian populations have lowest diversity and highest divergence, and other populations (European, Indian, and Mexican) have intermediate levels of diversity and divergence. These relationships accord with expectation based on other studies and accepted models of human history. In contrast, the population-specific F_ST estimates obtained directly from single-nucleotide polymorphisms (SNPs) do not reflect such expected relationships. We show that ascertainment bias of SNPs has less impact on the proposed haplotype-cluster-based F_ST than on the SNP-based version, which provides a potential explanation for these results. Thus, these new measures of F_ST and haplotype-cluster diversity provide an important new tool for population genetic analysis of high-density SNP data.GENOME-WIDE data sets from worldwide panels of individuals provide an outstanding opportunity to investigate the genetic structure of human populations (Conrad et al. 2006; International Hapmap Consortium 2007; Jakobsson et al. 2008; Auton et al. 2009). Populations around the globe form a continuum rather than discrete units (Serre and Paabo 2004; Weiss and Long 2009). However, notions of discrete populations can be appropriate when, for example, ancestral populations were separated by geographic distance or barriers such that little gene flow occurred.F_ST (Wright 1951; Weir and Cockerham 1984; Holsinger and Weir 2009) is a measure of population divergence. It measures variation between populations vs. within populations. One can calculate a global measure, assuming that all populations are equally diverged from an ancestral population, or one can calculate F_ST for specific populations or for pairs of populations while utilizing data from all populations (Weir and Hill 2002). One use of F_ST is to test for signatures of selection (reviewed in Oleksyk et al. 2010).F_ST may be calculated for single genetic markers. For multiallelic markers, such as microsatellites, this is useful, but single-nucleotide polymorphisms (SNPs) contain much less information when taken one at a time, and thus it is advantageous to calculate averages over windows of markers (Weir et al. 2005) or even over the whole genome. The advantage of windowed F_ST is that it can be used to find regions of the genome that show different patterns of divergence, indicative of selective forces at work during human history.Another measure of human evolutionary history is haplotype diversity. Haplotype diversity may be measured using a count of the number of observed haplotypes in a region or by the expected haplotype heterozygosity based on haplotype frequencies in a region. Application of this regional measure to chromosomal data can be achieved by a haplotype block strategy (Patil et al. 2001) or by windowing (Conrad et al. 2006; Auton et al. 2009).One problem with the analysis of population structure based on genome-wide panels of SNPs is that a large proportion of the SNPs were ascertained in Caucasians, potentially biasing the results of the analyses. Analysis based on haplotypes is less susceptible to such bias (Conrad et al. 2006). This is because haplotypes can be represented by multiple patterns of SNPs; thus lack of ascertainment of a particular SNP does not usually prevent observation of the haplotype. On a chromosome-wide scale, one cannot directly use entire haplotypes, because all the haplotypes in the sample will almost certainly be unique, thus providing no information on population structure. Instead one can use haplotypes on a local basis, either by using windows of adjacent markers or by using localized haplotype clusters, for example those obtained from fastPHASE (Scheet and Stephens 2006) or BEAGLE (Browning 2006; Browning and Browning 2007a).Localized haplotype clusters are a clustering of haplotypes on a localized basis. At the position of each genetic marker, haplotypes are clustered according to their similarity in the vicinity of the position. Both fastPHASE and BEAGLE use hidden Markov modeling to perform the clustering, although the specific models used by the two programs differ.Localized haplotype clusters derived from fastPHASE have been used to investigate haplotype diversity, to create neighbor-joining trees of populations, and to create multidimensional scaling (MDS) plots (Jakobsson et al. 2008). It was found that haplotype clusters showed different patterns of diversity to SNPs, while the neighbor-joining and MDS plots were similar between haplotype clusters and SNPs.In this work, we apply windowed F_ST methods to localized haplotype clusters derived from the BEAGLE program (Browning and Browning 2007a,b, 2009). We consider population-average, population-specific, and pairwise F_ST estimates (Weir and Hill 2002). Population-average F_ST''s either assume that all the populations are equally diverged from a common ancestor, which is not realistic, or represent the average of a set of population-specific values. This can be convenient in that the results are summarized by a single statistic; however, information is lost. A common procedure is to calculate F_ST for each pair of populations, and these values reflect the degree of divergence between the two populations. Different levels of divergence are allowed for each pair of populations but each estimate uses data from only that pair of populations. On the other hand, population-specific F_ST''s allow unequal levels of divergence in a single analysis that makes use of all the data.We compare results from the localized haplotype clusters to those using SNPs directly. The results of applying localized haplotype clusters to population-specific F_ST estimation are very striking, showing better separation of populations and a more realistic pattern of divergence than for population-specific F_ST estimation using SNPs directly. We also use BEAGLE''s haplotype clusters in a haplotype diversity measure and investigate the relationship between this measure of haplotype-cluster diversity and the recombination rate.     

Facilitated diffusion of CO2 across albumin solutions

The steady-state CO₂ flux across thin layers of 30 g/100 ml albumin solutions was measured in two different CO₂ partial pressure ranges (boundary PCO ₂ values 3 and 8 torr, and 160 and 650 torr, respectively). From the data the apparent diffusion coefficient for CO₂, DCO ₂, was calculated. In the high PCO ₂ range a value of DCO ₂ was found which is to be expected on the basis of diffusion of dissolved CO₂ only. In the low PCO ₂ range DCO ₂ was about 100% higher than in the high PCO ₂ range, when carbonic anhydrase was present and the pH was ∼7.7. DCO ₂ depended on the concentration of carbonic anhydrase. It increased with increasing pH. It is concluded that an additional diffusion of bound CO₂ (facilitated CO₂ diffusion) occurs in the low PCO ₂ range and that this transport involves the hydration of CO₂. From the diffusion coefficients in the two PCO ₂ ranges the rate of facilitated diffusion was determined. Approximate calculations show that this rate (at pH ≤ 7.7) can be explained on the basis of the proposed mechanism of facilitated CO₂ diffusion: bicarbonate diffusion and simultaneous proton transport by albumin diffusion. The view that facilitated CO₂ diffusion is mediated by the diffusion of albumin is supported by the experimental finding of a considerable suppression of the facilitated CO₂ flux in the presence of gelatinized agar-agar.     

Alternative Splicing Modulates Ubx Protein Function in Drosophila melanogaster

Polyploidy is an important aspect of the evolution of flowering plants. The potential of gene copies to diverge and evolve new functions is influenced by meiotic behavior of chromosomes leading to segregation as a single locus or duplicated loci. Switchgrass (Panicum virgatum) linkage maps were constructed using a full-sib population of 238 plants and SSR and STS markers to access the degree of preferential pairing and the structure of the tetraploid genome and as a step toward identification of loci underlying biomass feedstock quality and yield. The male and female framework map lengths were 1645 and 1376 cM with 97% of the genome estimated to be within 10 cM of a mapped marker in both maps. Each map coalesced into 18 linkage groups arranged into nine homeologous pairs. Comparative analysis of each homology group to the diploid sorghum genome identified clear syntenic relationships and collinear tracts. The number of markers with PCR amplicons that mapped across subgenomes was significantly fewer than expected, suggesting substantial subgenome divergence, while both the ratio of coupling to repulsion phase linkages and pattern of marker segregation indicated complete or near complete disomic inheritance. The proportion of transmission ratio distorted markers was relatively low, but the male map was more extensively affected by distorted transmission ratios and multilocus interactions, associated with spurious linkages.POLYPLOIDY is common among plants (Masterson 1994; Levin 2002) and is an important aspect of plant evolution. Widespread paleopolyploidy in flowering plant lineages suggests that ancient polyploidization events have contributed to the radiation of angiosperms (Soltis et al. 2009; Van de Peer et al. 2009a). Whole genome duplications are thought to be the sources of evolutionary novelty (Osborn et al. 2003; Freeling and Thomas 2006; Chen 2007; Hegarty and Hiscock 2008; Flagel and Wendel 2009; Leitch and Leitch 2008). Other attributes of polyploids considered to promote evolutionary success include increased vigor, masking of recessive alleles, and reproductive barriers arising from loss of one of the duplicate genes (Soltis and Soltis 2000; Comai 2005; Otto 2007; Van de Peer et al. 2009b). Among crop species, polyploidy likely contributed to trait improvement under artificial selection (Paterson 2005; Udall and Wendell 2006; Dubcovsky and Dvorak 2007; Hovav et al. 2008).Disomic inheritance in polyploids, in contrast to polysomic inheritance, presents opportunities for duplicated genes to diverge and evolve new functions. The relative age of whole genome duplications and the extent of homology between subgenomes greatly influence chromosomal pairing at meiosis (Soltis and Soltis 1995; Wolfe 2001; Ramsey and Schemske 2002). Polysomic inheritance resulting from random chromosome pairing is associated with doubling of a single set of chromosomes. Disomic inheritance resulting from preferential pairing is often associated with polyploidy arising from combinations of divergent genomes. The evolutionary process of diploidization leads to a shift from random to preferential pairing that is not well understood but is genetically defined in systems such as Ph1 of wheat (Triticum aestivum) and PrBn of Brassica napus (Riley and Chapman 1958; Vega and Feldman 1998; Jenczewski et al. 2003). The degree of preferential pairing also affects allelic diversity and the ability to detect linkage. Accurate information about chromosome pairing and whole or partial genome duplications is thus important for both evolutionary studies and in linkage analysis.Such information is extremely limited in the C4 panicoid species Panicum virgatum (switchgrass), which is now viewed as a promising energy crop in the United States and Europe (Lewandowski et al. 2003; McLaughlin and Kszos 2005) and is planted extensively for forage and soil conservation (Vogel and Jung 2001). Little is known about either its genome structure or inheritance. Much current bioenergy feedstock development is focused on tetraploid cytotypes (2n = 4x = 36) due to their higher yield potentials, and an initial segregation study indicated a high degree of preferential pairing in a single F1 mapping population (Missaoui et al. 2005). A once-dominant component of the tallgrass prairie in North America, switchgrass is largely self-incompatible (Martinez-Reyna and Vogel 2002) with predominantly tetraploid or octoploid cytotypes (Hultquist et al. 1997; Lu et al. 1998). Limited gene flow appears possible between different cytotypes suggested by DNA content variation within collection sites and seed lots (Nielsen 1944; Hultquist et al. 1997; Narasimhamoorthy et al. 2008). True diploids appear to be rare (Nielsen 1944; Young et al. 2010). Multivalents in meiosis have not been observed in tetraploids or F1 hybrids between upland and lowland tetraploids, although rare univalents occurred (Barnett and Carver 1967; Martinez-Reyna et al. 2001). However, polysomic inheritance may occur with random bivalent pairing (Howard and Swaminathan 1953).Sustainable production of switchgrass for bioenergy to meet the goal of reducing greenhouse gas emissions will require advances in feedstock production that include improvements in yield (Carroll and Somerville 2009). Switchgrass has extensive genetic diversity and potential for genetic improvements, but each cycle of phenotypic selection can take several years (McLaughlin and Kszos 2005; Parrish and Fike 2005; Bouton 2007). Detailed understanding of genome structure to enable efficient marker-assisted selection (MAS) can speed this process considerably. Complete linkage maps are therefore required to both understand chromosome pairing and allow MAS.We report the construction of the first complete linkage maps of two switchgrass genotypes. The linkage maps provide genetic evidence for disomic inheritance in lowland, tetraploid switchgrass. Gene-derived markers enabled a comparative analysis to sorghum, revealing syntenic relationships between the diploid sorghum genome and the tetraploid switchgrass subgenomes. Transmission ratio distortion and multilocus interactions were analyzed in detail to document their potential influence on map accuracy and map-based studies in switchgrass.     

Rate of Adaptation in Large Sexual Populations

Adaptation often involves the acquisition of a large number of genomic changes that arise as mutations in single individuals. In asexual populations, combinations of mutations can fix only when they arise in the same lineage, but for populations in which genetic information is exchanged, beneficial mutations can arise in different individuals and be combined later. In large populations, when the product of the population size N and the total beneficial mutation rate U_b is large, many new beneficial alleles can be segregating in the population simultaneously. We calculate the rate of adaptation, v, in several models of such sexual populations and show that v is linear in NU_b only in sufficiently small populations. In large populations, v increases much more slowly as log NU_b. The prefactor of this logarithm, however, increases as the square of the recombination rate. This acceleration of adaptation by recombination implies a strong evolutionary advantage of sex.IN asexual populations, beneficial mutations arising on different genotypes compete against each other and in large populations most of the beneficial mutations are lost because they arise on mediocre genetic backgrounds or acquire further beneficial mutations less rapidly than their peers—the combined effects of clonal interference and multiple mutations (Gerrish and Lenski 1998; Desai and Fisher 2007). Exchange of genetic material between individuals allows the combination of beneficial variants that arose in different lineages and can thereby speed up the process of adaptation (Fisher 1930; Muller 1932). Indeed, most life forms engage in some form of recombination, e.g., lateral gene transfer or competence for picking up DNA in bacteria, facultative sexual reproduction in yeast and plants, or obligate sexual reproduction in most animals. Some benefits of recombination for the rate of adaptation have recently been demonstrated experimentally in Caenorhabditis reinhardtii (Colegrave 2002), Escherichia coli (Cooper 2007), and Saccharomyces cerevisiae (Goddard et al. 2005); for a review of older experiments, see Rice (2002).Yet the benefits of sex become less obvious when one considers its disadvantageous effects: recombination can separate well-adapted combinations of alleles and sexual reproduction is more costly than asexual reproduction due to resources spent for mating and, in some cases, the necessity of males. The latter—in animals often termed the twofold cost of sex—implies that sexual populations can be unstable to the invasion of asexual variants. As a result, the pros and cons of sex have been the subject of many decades of debate in the theoretical literature (Crow and Kimura 1965; Maynard Smith 1968; Felsenstein 1974; Barton 1995a; Barton and Charlesworth 1998), and several different potentially beneficial aspects of sex have been identified, including the pruning of detrimental mutations (Peck 1994; Rice 1998) and host–parasite coevolution or otherwise changing environments (Charlesworth 1993; Ladle et al. 1993; Bürger 1999; Waxman and Peck 1999; Gandon and Otto 2007; Callahan et al. 2009). In the opposite situation of relatively static populations, it has been proposed that recombination is favored in the presence of negative epistasis (Feldman et al. 1980; Kondrashov 1984, 1988)—a situation when the combined detrimental effect of two unfavorable alleles is greater than the sum of the individual effects. While this may sometimes be a significant effect, most populations, especially microbes, are likely to be under continuing selection and the benefits of sex for speeding up adaptation are likely to dominate.The Fisher–Muller hypothesis is that sex speeds up adaptation by combining beneficial variants. Moreover, it has been demonstrated by Hill and Robertson (1966) that linkage decreases the efficacy of selection. This detrimental effect of linkage, known as the “Hill–Robertson effect,” causes selection for higher recombination rates, which has been shown by analyzing recombination modifier alleles at a locus linked to two competing segregating loci (Otto and Barton 1997; Iles et al. 2003; Barton and Otto 2005; Roze and Barton 2006; Martin et al. 2006). Hitchhiking of the allele that increases the recombination rates with the sweeping linked loci results in effective selection for increased recombination.Experiments and simulation studies suggest that the Hill–Roberston effect is more pronounced and selection for recombination modifiers is stronger in large populations with many sweeping loci (Felsenstein 1974; Colegrave 2002; Iles et al. 2003). However, the quantitative understanding of the effect of recombination in large populations is limited. Rouzine and Coffin have studied the role of recombination in the context of evolution of drug resistance in human immunodeficiency virus, finding that recombination of standing variation speeds up adaptation by producing anomalously fit individuals at the high fitness edge of the distribution (Rouzine and Coffin 2005; Gheorghiu-Svirschevski et al. 2007). The effects of epistatic interactions between polymorphisms and recombination on the dynamics of selection have recently been analyzed by Neher and Shraiman (2009). Yet none of these works consider the effects of new beneficial mutations. In the absence of new mutations (and in the absence of heterozygous advantage that can maintain polymorphisms) the fitness soon saturates as most alleles become extinct and standing variation disappears. Thus the crucial point that must be addressed is the balance between selection and recombination of existing variation and the injection of additional variation by new mutations.Here, we study the dynamics of continual evolution via new mutations, selection, and recombination using several models of recombination. Our primary models most naturally apply when periods of asexual reproduction occur between matings, so that they approximate the life style of facultatively outcrossing species such as S. cerevisiae, some plants, and C. elegans, which reproduce asexually most of the time but undergo extensive recombination when outcrossing. The models enable us to study analytically the explicit dependence of the rate of adaptation and of the dynamics of the beneficial alleles on the important parameters such as the outcrossing rate and population size. In an independent study N. H. Barton and J. Coe (personal communication) calculate the rate of adaptation for obligate sexual organisms using several different multilocus models of recombination, including the free recombination model studied here. The relation of our work to theirs, as well as to that of Cohen et al. (2005, 2006) who have also studied the effects of recombination with multiple new mutations, is commented on in the discussion.When deleterious mutations can be neglected, the rate of adaptation is the product of the rate of production of favorable mutations NU_b (N being the population size and U_b the genomewide beneficial mutation rate), the magnitude of their effect, and their fixation probability. The fixation probability is dominated by the probability that the allele becomes established, i.e., that it rises to high enough numbers in the population that it is very unlikely to die out by further stochastic fluctuations. In a homogeneous population a single beneficial mutation with selective advantage s has a probability of establishment and eventual fixation of (in discrete generation models, P_e≈2s) (Moran 1959). In a heterogeneous population, however, a novel beneficial mutation can arise on different genetic backgrounds and its establishment probability will thus vary, being greater if it arises in a well-adapted individual. But even well-adapted genotypes soon fall behind due to sweeps of other beneficial mutations and combinations. To avoid extinction, descendants of the novel mutation thus have to move to fitter genetic backgrounds via recombination in outcrossing events (Rice 2002). As a result the establishment probability decreases as the rate of average fitness gain, v, in the population increases. But the rate of average fitness gain or, equivalently, the rate of adaptation itself depends on the establishment probability. These two quantities therefore have to be determined self-consistently.In this article we analyze several models via self-consistent calculations of the fixation probability of new mutations. For a given production rate of beneficial mutations NU_b, we find that interference between mutations is of minor importance if the recombination rate r exceeds . In this regime, the rate of adaption is v ≈ NU_bs² as found for sequential mutations or in the absence of linkage. At recombination rates below , however, v grows only logarithmically with log NU_b. We find this behavior in all our models and argue that it obtains more generally. The prefactor of the log NU_b increases with the square of the recombination rate, implying a strong benefit of recombination in large populations.     

Specificity Determinants for Lysine Incorporation in Staphylococcus aureus Peptidoglycan as Revealed by the Structure of a MurE Enzyme Ternary Complex

Formation of the peptidoglycan stem pentapeptide requires the insertion of both l and d amino acids by the ATP-dependent ligase enzymes MurC, -D, -E, and -F. The stereochemical control of the third position amino acid in the pentapeptide is crucial to maintain the fidelity of later biosynthetic steps contributing to cell morphology, antibiotic resistance, and pathogenesis. Here we determined the x-ray crystal structure of Staphylococcus aureus MurE UDP-N-acetylmuramoyl-l-alanyl-d-glutamate:meso-2,6-diaminopimelate ligase (MurE) (E.C. 6.3.2.7) at 1.8 Å resolution in the presence of ADP and the reaction product, UDP-MurNAc-l-Ala-γ-d-Glu-l-Lys. This structure provides for the first time a molecular understanding of how this Gram-positive enzyme discriminates between l-lysine and d,l-diaminopimelic acid, the predominant amino acid that replaces l-lysine in Gram-negative peptidoglycan. Despite the presence of a consensus sequence previously implicated in the selection of the third position residue in the stem pentapeptide in S. aureus MurE, the structure shows that only part of this sequence is involved in the selection of l-lysine. Instead, other parts of the protein contribute substrate-selecting residues, resulting in a lysine-binding pocket based on charge characteristics. Despite the absolute specificity for l-lysine, S. aureus MurE binds this substrate relatively poorly. In vivo analysis and metabolomic data reveal that this is compensated for by high cytoplasmic l-lysine concentrations. Therefore, both metabolic and structural constraints maintain the structural integrity of the staphylococcal peptidoglycan. This study provides a novel focus for S. aureus-directed antimicrobials based on dual targeting of essential amino acid biogenesis and its linkage to cell wall assembly.     

Simple Y-Autosomal Incompatibilities Cause Hybrid Male Sterility in Reciprocal Crosses Between Drosophila virilis and D. americana

Postzygotic reproductive isolation evolves when hybrid incompatibilities accumulate between diverging populations. Here, I examine the genetic basis of hybrid male sterility between two species of Drosophila, Drosophila virilis and D. americana. From these analyses, I reach several conclusions. First, neither species carries any autosomal dominant hybrid male sterility alleles: reciprocal F₁ hybrid males are perfectly fertile. Second, later generation (backcross and F₂) hybrid male sterility between D. virilis and D. americana is not polygenic. In fact, I identified only three genetically independent incompatibilities that cause hybrid male sterility. Remarkably, each of these incompatibilities involves the Y chromosome. In one direction of the cross, the D. americana Y is incompatible with recessive D. virilis alleles at loci on chromosomes 2 and 5. In the other direction, the D. virilis Y chromosome causes hybrid male sterility in combination with recessive D. americana alleles at a single QTL on chromosome 5. Finally, in contrast with findings from other Drosophila species pairs, the X chromosome has only a modest effect on hybrid male sterility between D. virilis and D. americana.SPECIATION occurs when populations evolve one or more barriers to interbreeding (Dobzhansky 1937; Mayr 1963). One such barrier is intrinsic postzygotic isolation, which typically evolves when diverging populations accumulate different alleles at two or more loci that are incompatible when brought together in hybrid genomes; negative epistasis between these alleles renders hybrids inviable or sterile (Bateson 1909; Dobzhansky 1937; Muller 1942). Classical and recent studies in diverse animal taxa have provided support for two evolutionary patterns that often characterize the genetics of postzygotic isolation (Coyne and Orr 1989a). The first, Haldane''s rule, observes that when there is F₁ hybrid inviability or sterility that affects only one sex, it is almost always the heterogametic sex (Haldane 1922). Over the years, many researchers have tried to account for this pattern, but only two ideas are now thought to provide a general explanation: the “dominance theory,” which posits that incompatibility alleles are generally recessive in hybrids, and the “faster-male theory,” which posits that genes causing hybrid male sterility diverge more rapidly than those causing hybrid female sterility (Muller 1942; Wu and Davis 1993; Turelli and Orr 1995; reviewed in Coyne and Orr 2004). In some cases, however, additional factors might contribute to Haldane''s rule, including meiotic drive, a faster-evolving X chromosome, dosage compensation, and Y chromosome incompatibilities (reviewed in Laurie 1997; Turelli and Orr 2000; Coyne and Orr 2004).The second broad pattern affecting the evolution of postzygotic isolation is the disproportionately large effect of the X chromosome on heterogametic F₁ hybrid sterility (Coyne 1992). This “large X effect” has been documented in genetic analyses of backcross hybrid sterility (e.g., Dobzhansky 1936; Grula and Taylor 1980; Orr 1987; Masly and Presgraves 2007) and inferred from patterns of introgression across natural hybrid zones (e.g., Machado et al. 2002; Saetre et al. 2003; Payseur et al. 2004). However, in only one case has the cause of the large X effect been unambiguously determined: incompatibilities causing hybrid male sterility between Drosophila mauritiana and D. sechellia occur at a higher density on the X than on the autosomes (Masly and Presgraves 2007). Testing the generality of this pattern will require additional high-resolution genetic analyses in diverse taxa (Presgraves 2008). But whatever its causes, there is now general consensus that the X chromosome often plays a special role in the evolution of postzygotic isolation (Coyne and Orr 2004).The contribution of the Y chromosome to animal speciation is less clear. Y chromosomes have far fewer genes than the X or autosomes, and most of these genes are male specific (Lahn and Page 1997; Carvalho et al. 2009). In Drosophila species, the Y chromosome is typically required for male fertility, but not for viability (Voelker and Kojima 1971). How often, then, does the Y chromosome play a role in reproductive isolation? In crosses between Drosophila species, hybrid male sterility is frequently caused by incompatibilities between the X and Y chromosomes (Schafer 1978; Heikkinen and Lumme 1998; Mishra and Singh 2007) or between the Y and heterospecific autosomal alleles (Patterson and Stone 1952; Vigneault and Zouros 1986; Lamnissou et al. 1996). In crosses between D. yakuba and D. santomea, the Y chromosome causes F₁ hybrid male sterility, and accordingly, shows no evidence for recent introgression across a species hybrid zone (Coyne et al. 2004; Llopart et al. 2005). In mammals, reduced introgression of Y-linked loci (relative to autosomal loci) has been shown across natural hybrid zones of mice (Tucker et al. 1992) and rabbits (Geraldes et al. 2008), suggesting that the Y chromosome contributes to reproductive barriers.Here I examine the genetic basis of hybrid male sterility between two species of Drosophila, D. virilis and D. americana. These species show considerable genetic divergence (K_s ∼0.11, Morales-Hojas et al. 2008) and are currently allopatric: D. virilis is a human commensal worldwide with natural populations in Asia, and D. americana is found in riparian habitats throughout much of North America (Throckmorton 1982; McAllister 2002). Nearly 70 years ago, Patterson et al. (1942) showed that incompatibilities between the D. americana Y chromosome and the second and fifth chromosomes from D. virilis cause hybrid male sterility, a result that was confirmed in a more recent study (Lamnissou et al. 1996). Another study suggested that the X chromosome might play the predominant role in causing hybrid male sterility between D. virilis and D. americana (Orr and Coyne 1989). But because previous genetic analyses had to rely on only a few visible markers to map hybrid male sterility, they lacked the resolution to examine the genomic distribution of incompatibility loci.Using the D. virilis genome sequence, I have developed a dense set of molecular markers to investigate the genetic architecture of hybrid male sterility between D. virilis and D. americana. In this study, I perform a comprehensive set of crosses to address several key questions: What is the effect of the X chromosome on hybrid male sterility between D. virilis and D. americana? What is the effect of the Y chromosome? Approximately how many loci contribute to hybrid male sterility between these Drosophila species? Perhaps surprisingly, the answers to these questions differ dramatically from what has been found for other Drosophila species, including the well-studied D. melanogaster group.     

A Principled Approach to Deriving Approximate Conditional Sampling Distributions in Population Genetics Models with Recombination

The multilocus conditional sampling distribution (CSD) describes the probability that an additionally sampled DNA sequence is of a certain type, given that a collection of sequences has already been observed. The CSD has a wide range of applications in both computational biology and population genomics analysis, including phasing genotype data into haplotype data, imputing missing data, estimating recombination rates, inferring local ancestry in admixed populations, and importance sampling of coalescent genealogies. Unfortunately, the true CSD under the coalescent with recombination is not known, so approximations, formulated as hidden Markov models, have been proposed in the past. These approximations have led to a number of useful statistical tools, but it is important to recognize that they were not derived from, though were certainly motivated by, principles underlying the coalescent process. The goal of this article is to develop a principled approach to derive improved CSDs directly from the underlying population genetics model. Our approach is based on the diffusion process approximation and the resulting mathematical expressions admit intuitive genealogical interpretations, which we utilize to introduce further approximations and make our method scalable in the number of loci. The general algorithm presented here applies to an arbitrary number of loci and an arbitrary finite-alleles recurrent mutation model. Empirical results are provided to demonstrate that our new CSDs are in general substantially more accurate than previously proposed approximations.THE probability of observing a sample of DNA sequences under a given population genetics model—which is referred to as the sampling probability or likelihood—plays an important role in a wide range of problems in a genetic variation study. When recombination is involved, however, obtaining an analytic formula for the sampling probability has hitherto remained a challenging open problem (see Jenkins and Song 2009, 2010 for recent progress on this problem). As such, much research (Griffiths and Marjoram 1996; Kuhner et al. 2000; Nielsen 2000; Stephens and Donnelly 2000; Fearnhead and Donnelly 2001; De Iorio and Griffiths 2004a,b; Fearnhead and Smith 2005; Griffiths et al. 2008; Wang and Rannala 2008) has focused on developing Monte Carlo methods on the basis of the coalescent with recombination (Griffiths 1981; Kingman 1982a,b; Hudson 1983), a well-established mathematical framework that models the genealogical history of sample chromosomes. These Monte Carlo-based full-likelihood methods mark an important development in population genetics analysis, but a well-known obstacle to their utility is that they tend to be computationally intensive. For a whole-genome variation study, approximations are often unavoidable, and it is therefore important to think of ways to minimize the trade-off between scalability and accuracy.A popular likelihood-based approximation method that has had a significant impact on population genetics analysis is the following approach introduced by Li and Stephens (2003): Given a set Φ of model parameters (e.g., mutation rate, recombination rate, etc.), the joint probability p(h₁, … , h_n | Φ) of observing a set {h₁, … , h_n} of haplotypes sampled from a population can be decomposed as a product of conditional sampling distributions (CSDs), denoted by π,(1)where π(h_k+1|h₁, …, h_k, Φ) is the probability of an additionally sampled haplotype being of type h_k+1, given a set of already observed haplotypes h₁, …, h_k. In the presence of recombination, the true CSD π is unknown, so Li and Stephens proposed using an approximate CSD in place of π, thus obtaining the following approximation of the joint probability:(2)Li and Stephens referred to this approximation as the product of approximate conditionals (PAC) model. In general, the closer is to the true CSD π, the more accurate the PAC model becomes. Notable applications and extensions of this framework include estimating crossover rates (Li and Stephens 2003; Crawford et al. 2004) and gene conversion parameters (Gay et al. 2007; Yin et al. 2009), phasing genotype data into haplotype data (Stephens and Scheet 2005; Scheet and Stephens 2006), imputing missing data to improve power in association mapping (Stephens and Scheet 2005; Li and Abecasis 2006; Marchini et al. 2007; Howie et al. 2009), inferring local ancestry in admixed populations (Price et al. 2009), inferring human colonization history (Hellenthal et al. 2008), inferring demography (Davison et al. 2009), and so on.Another problem in which the CSD plays a fundamental role is importance sampling of genealogies under the coalescent process (Stephens and Donnelly 2000; Fearnhead and Donnelly 2001; De Iorio and Griffiths 2004a,b; Fearnhead and Smith 2005; Griffiths et al. 2008). In this context, the optimal proposal distribution can be written in terms of the CSD π (Stephens and Donnelly 2000), and as in the PAC model, an approximate CSD may be used in place of π. The performance of an importance sampling scheme depends critically on the proposal distribution and therefore on the accuracy of the approximation . Often in conjunction with composite-likelihood frameworks (Hudson 2001; Fearnhead and Donnelly 2002), importance sampling has been used in estimating fine-scale recombination rates (McVean et al. 2004; Fearnhead and Smith 2005; Johnson and Slatkin 2009).So far, a significant scope of intuition has gone into choosing the approximate CSDs used in these problems (Marjoram and Tavaré 2006). In the case of completely linked loci, Stephens and Donnelly (2000) suggested constructing an approximation by assuming that the additional haplotype h_k+1 is an imperfect copy of one of the first k haplotypes, with copying errors corresponding to mutation. Fearnhead and Donnelly (2001) generalized this construction to include crossover recombination, assuming that the haplotype h_k+1 is an imperfect mosaic of the first k haplotypes (i.e., h_k+1 is obtained by copying segments from h₁, …, h_k, where crossover recombination can change the haplotype from which copying is performed). The associated CSD, which we denote by , can be interpreted as a hidden Markov model and so admits an efficient dynamic programming solution. Finally, Li and Stephens (2003) proposed a modification to Fearnhead and Donnelly''s model that limits the hidden state space, thereby providing a computational simplification; we denote the corresponding approximate CSD by .Although these approaches are computationally appealing, it is important to note that they are not derived from, though are certainly motivated by, principles underlying typical population genetics models, in particular the coalescent process (Griffiths 1981; Kingman 1982a,b; Hudson 1983). The main objective of this article is to develop a principled technique to derive an improved CSD directly from the underlying population genetics model. Rather than relying on intuition, we base our work on mathematical foundation. The theoretical framework we employ is the diffusion process. De Iorio and Griffiths (2004a,b) first introduced the diffusion-generator approximation technique to obtain an approximate CSD in the case of a single locus (i.e., no recombination). Griffiths et al. (2008) later extended the approach to two loci to include crossover recombination, assuming a parent-independent mutation model at each locus. In this article, we extend the framework to develop a general algorithm that applies to an arbitrary number of loci and an arbitrary finite-alleles recurrent mutation model.Our work can be summarized as follows. Using the diffusion-generator approximation technique, we derive a recursion relation satisfied by an approximate CSD. This recursion can be used to construct a closed system of coupled linear equations, in which the conditional sampling probability of interest appears as one of the unknown variables. The system of equations can be solved using standard numerical analysis techniques. However, the size of the system grows superexponentially with the number of loci and, consequently, so does the running time. To remedy this drawback, we introduce additional approximations to make our approach scalable in the number of loci. Specifically, the recursion admits an intuitive genealogical interpretation, and, on the basis of this interpretation, we propose modifications to the recursion, which then can be easily solved using dynamic programming. The computational complexity of the modified algorithm is polynomial in the number of loci, and, importantly, the resulting CSD has little loss of accuracy compared to that following from the full recursion.The accuracy of approximate CSDs has not been discussed much in the literature, except in the application-specific context for which they are being employed. In this article, we carry out an empirical study to explicitly test the accuracy of various CSDs and demonstrate that our new CSDs are in general substantially more accurate than previously proposed approximations. We also consider the PAC framework and show that our approximations also produce more accurate PAC-likelihood estimates. We note that for the maximum-likelihood estimation of recombination rates, the actual value of the likelihood may not be so important, as long as it is maximized near the true recombination rate. However, in many other applications—e.g., phasing genotype data into haplotype data, imputing missing data, importance sampling, and so on—the accuracy of the CSD and PAC-likelihood function over a wide range of parameter values may be important. Thus, we believe that the theoretical work presented here will have several practical implications; our method can be applied in a wide range of statistical tools that use CSDs, improving their accuracy.The remainder of this article is organized as follows. To provide intuition for the ensuing mathematics, we first describe a genealogical process that gives rise to our CSD. Using our genealogical interpretation, we consider two additional approximations and relate these to previously proposed CSDs. Then, in the following section, we derive our CSD using the diffusion-generator approach and provide mathematical statements for the additional approximations; some interesting limiting behavior is also described there. This section is self-contained and may be skipped by the reader uninterested in mathematical details. Finally, in the subsequent section, we carry out a simulation study to compare the accuracy of various approximate CSDs and demonstrate that ours are generally the most accurate.     

Identification of the Major Sex-Determining Region of Turbot (Scophthalmus maximus)

Sex determination in fish is a labile character in evolutionary terms. The sex-determining (SD) master gene can differ even between closely related fish species. This group is an interesting model for studying the evolution of the SD region and the gonadal differentiation pathway. The turbot (Scophthalmus maximus) is a flatfish of great commercial value, where a strong sexual dimorphism exists for growth rate. Following a QTL and marker association approach in five families and a natural population, we identified the main SD region of turbot at the proximal end of linkage group (LG) 5, close to the SmaUSC-E30 marker. The refined map of this region suggested that this marker would be 2.6 cM and 1.4 Mb from the putative SD gene. This region appeared mostly undifferentiated between males and females, and no relevant recombination frequency differences were detected between sexes. Comparative genomics of LG5 marker sequences against five model species showed no similarity of this chromosome to the sex chromosomes of medaka, stickleback, and fugu, but suggested a similarity to a sex-associated QTL from Oreochromis spp. The segregation analysis of the closest markers to the SD region demonstrated a ZW/ZZ model of sex determination in turbot. A small proportion of families did not fit perfectly with this model, which suggests that other minor genetic and/or environmental factors are involved in sex determination in this species.SEX ratio is a central demographic parameter directly related to the reproductive potential of individuals and populations (Penman and Piferrer 2008). The phenotypic sex depends on the processes of both sex determination and sex differentiation. Exogenous factors, such as temperature, hormones, or social behavior, can modify the gonad development pathway in fish (Baroiller and D''Cotta 2001; Piferrer and Guiguen 2008). Both genetic (GSD) and environmental sex determination has been reported in this group (Devlin and Nagahama 2002; Penman and Piferrer 2008), although primary sex determination is genetic in most species (Valenzuela et al. 2003). Among GSD, single, multiple, or polygenic sex-determining (SD) gene systems have been documented (Kallman 1984; Matsuda et al. 2002; Lee et al. 2004; Vandeputte et al. 2007).Sex determination in fish can evolve very rapidly (Woram et al. 2003; Peichel et al. 2004; Ross et al. 2009). Different sex determination mechanisms have been reported between congeneric species and even between populations of the same species (Almeida-Toledo and Foresti 2001; Lee et al. 2004; Mank et al. 2006). The evolution of sex chromosomes involves the suppression of recombination between homologous chromosomes probably to maintain sex-related coadapted gene blocks (Charlesworth et al. 2005; Tripathi et al. 2009). The sex determination pathway appears to be less conserved than other developmental processes (Penman and Piferrer 2008). However, differences are more related to the top of the hierarchy in the developmental pathway, while downstream genes are more conserved (Wilkins 1995; Marín and Baker 1998). As a consequence, the SD master gene in fish can vary among related species (Kondo et al. 2003; Tanaka et al. 2007; Alfaqih et al. 2009). In this sense, fish represent an attractive model for studying the evolution of SD mechanisms and sex chromosomes (Peichel et al. 2004; Kikuchi et al. 2007).A low proportion of fish species have demonstrated sex-associated chromosome heteromorphisms (Almeida-Toledo and Foresti 2001; Devlin and Nagahama 2002; Penman and Piferrer 2008). This is congruent with the rapid evolution of the SD region in fish, and thus in most species the male and female version of this chromosome region appears largely undifferentiated. In spite of this, indirect clues related to progenies of sex/chromosome-manipulated individuals or to segregation of morphologic/molecular sex-associated markers indicate that mechanisms of sex determination in fish are similar to other vertebrates (Penman and Piferrer 2008). With the arrival of genomics, large amounts of different genetic markers and genomic information are available for scanning genomes to look for their association with sex determination. Quantitative trait loci (QTL) (Cnaani et al. 2004; Peichel et al. 2004) or marker association (Felip et al. 2005; Chen et al. 2007) approaches have been used to identify the SD regions in some fish species. Also, microarrays constructed from gonadal ESTs have been applied to detect differentially expressed genes in the process of gonadal differentiation (Baron et al. 2005). Further, the increased genomic resources in model and aquaculture species have allowed the development of both comparative genomics (Woram et al. 2003; Kikuchi et al. 2007; Tripathi et al. 2009) and candidate gene (Shirak et al. 2006; Alfaqih et al. 2009) strategies to identify and characterize the SD region in fish. This has permitted the identification of the SD region in eight fish, including both model and aquaculture species (reviewed in Penman and Piferrer 2008).The turbot is a highly appreciated European aquaculture species, whose harvest is expected to increase from the current 9000 tons to >15,000 tons in 2012 (S. Cabaleiro, personal communication). Females of this species reach commercial size 4–6 months before males do, explaining the interest of the industry in obtaining all-female populations. Although some differences between families can be observed in the production process at farms, sex ratio is usually balanced at ∼1:1. Neither mitotic nor meiotic chromosomes have shown sex-associated heteromorphisms in turbot (Bouza et al. 1994; Cuñado et al. 2001). The proportion of sexes observed in triploid and especially gynogenetic progenies moved Cal et al. (2006a,b) to suggest an XX/XY mechanism in turbot with some additional, either environmental or genetic, factor involved. However, Haffray et al. (2009) have recently claimed a ZZ/ZW mechanism on the basis of the analysis of a large number of progenies from steroid-treated parents. These authors also suggested some (albeit low) influence of temperature in distorting sex proportions after the larval period. Finally, hybridizations between brill (Scophthalmus rhombus) and turbot render monosex progenies, depending on the direction of the cross performed, which suggests different SD mechanisms in these congeneric species (Purdom and ThaCker 1980).In this study, we used the turbot genetic map (Bouza et al. 2007, 2008; Martínez et al. 2008) to look for sex-associated QTL in this species. The identification of a major QTL in a specific linkage group (LG) in the five families analyzed prompted us to refine the genetic map at this LG and to perform a comparative genomics approach against model fish species for a precise location and characterization of the putative SD region. Also, sex-associated QTL markers were screened in a large natural population to provide additional support to our findings and to obtain population parameters at sex-related markers that could aid in interpreting the evolution of this genomic region.     

Purification and Substrate Specificities of Two α-l-Arabinofuranosidases from Aspergillus awamori IFO 4033

α-l-Arabinofuranosidases I and II were purified from the culture filtrate of Aspergillus awamori IFO 4033 and had molecular weights of 81,000 and 62,000 and pIs of 3.3 and 3.6, respectively. Both enzymes had an optimum pH of 4.0 and an optimum temperature of 60°C and exhibited stability at pH values from 3 to 7 and at temperatures up to 60°C. The enzymes released arabinose from p-nitrophenyl-α-l-arabinofuranoside, O-α-l-arabinofuranosyl-(1→3)-O-β-d-xylopyranosyl-(1→4)-d-xylopyranose, and arabinose-containing polysaccharides but not from O-β-d-xylopyranosyl-(1→2)-O-α-l-arabinofuranosyl-(1→3)-O-β-d-xylopyranosyl-(1→4)-O-β-d-xylopyranosyl-(1→4)-d-xylopyranose. α-l-Arabinofuranosidase I also released arabinose from O-β-d-xylopy-ranosyl-(1→4)-[O-α-l-arabinofuranosyl-(1→3)]-O-β-d-xylopyranosyl-(1→4)-d-xylopyranose. However, α-l-arabinofuranosidase II did not readily catalyze this hydrolysis reaction. α-l-Arabinofuranosidase I hydrolyzed all linkages that can occur between two α-l-arabinofuranosyl residues in the following order: (1→5) linkage > (1→3) linkage > (1→2) linkage. α-l-Arabinofuranosidase II hydrolyzed the linkages in the following order: (1→5) linkage > (1→2) linkage > (1→3) linkage. α-l-Arabinofuranosidase I preferentially hydrolyzed the (1→5) linkage of branched arabinotrisaccharide. On the other hand, α-l-arabinofuranosidase II preferentially hydrolyzed the (1→3) linkage in the same substrate. α-l-Arabinofuranosidase I released arabinose from the nonreducing terminus of arabinan, whereas α-l-arabinofuranosidase II preferentially hydrolyzed the arabinosyl side chain linkage of arabinan.Recently, it has been proven that l-arabinose selectively inhibits intestinal sucrase in a noncompetitive manner and reduces the glycemic response after sucrose ingestion in animals (33). Based on this observation, l-arabinose can be used as a physiologically functional sugar that inhibits sucrose digestion. Effective l-arabinose production is therefore important in the food industry. l-Arabinosyl residues are widely distributed in hemicelluloses, such as arabinan, arabinoxylan, gum arabic, and arabinogalactan, and the α-l-arabinofuranosidases (α-l-AFases) (EC 3.2.1.55) have proven to be essential tools for enzymatic degradation of hemicelluloses and structural studies of these compounds.α-l-AFases have been classified into two families of glycanases (families 51 and 54) on the basis of amino acid sequence similarities (11). The two families of α-l-AFases also differ in substrate specificity for arabinose-containing polysaccharides. Beldman et al. summarized the α-l-AFase classification based on substrate specificities (3). One group contains the Arafur A (family 51) enzymes, which exhibit very little or no activity with arabinose-containing polysaccharides. The other group contains the Arafur B (family 54) enzymes, which cleave arabinosyl side chains from polymers. However, this classification is too broad to define the substrate specificities of α-l-AFases. There have been many studies of the α-l-AFases (3, 12), especially the α-l-AFases of Aspergillus species (2–8, 12–15, 17, 22, 23, 28–32, 36–39, 41–43, 46). However, there have been only a few studies of the precise specificities of these α-l-AFases. In previous work, we elucidated the substrate specificities of α-l-AFases from Aspergillus niger 5-16 (17) and Bacillus subtilis 3-6 (16, 18), which should be classified in the Arafur A group and exhibit activity with arabinoxylooligosaccharides, synthetic methyl 2-O-, 3-O-, and 5-O-arabinofuranosyl-α-l-arabinofuranosides (arabinofuranobiosides) (20), and methyl 3,5-di-O-α-l-arabinofuranosyl-α-l-arabinofuranoside (arabinofuranotrioside) (19).In the present work, we purified two α-l-AFases from a culture filtrate of Aspergillus awamori IFO 4033 and determined the substrate specificities of these α-l-AFases by using arabinose-containing polysaccharides and the core oligosaccharides of arabinoxylan and arabinan.     

A Hidden Markov Model Combining Linkage and Linkage Disequilibrium Information for Haplotype Reconstruction and Quantitative Trait Locus Fine Mapping

Faithful reconstruction of haplotypes from diploid marker data (phasing) is important for many kinds of genetic analyses, including mapping of trait loci, prediction of genomic breeding values, and identification of signatures of selection. In human genetics, phasing most often exploits population information (linkage disequilibrium), while in animal genetics the primary source of information is familial (Mendelian segregation and linkage). We herein develop and evaluate a method that simultaneously exploits both sources of information. It builds on hidden Markov models that were initially developed to exploit population information only. We demonstrate that the approach improves the accuracy of allele phasing as well as imputation of missing genotypes. Reconstructed haplotypes are assigned to hidden states that are shown to correspond to clusters of genealogically related chromosomes. We show that these cluster states can directly be used to fine map QTL. The method is computationally effective at handling large data sets based on high-density SNP panels.ARRAY technology now allows genotyping of large cohorts for thousands to millions of single nucleotide polymorphisms (SNPs), which are becoming available for a growing list of organisms including human and domestic animals. Among other applications, these advances permit systematic scanning of the genome to map trait loci by association (e.g., Wellcome Trust Case Control Consortium 2007; Charlier et al. 2008), to predict genomic breeding values for complex traits (Meuwissen et al. 2001; Goddard and Hayes 2009), or to identify signatures of selection (e.g., Voight et al. 2006).Present-day genotyping platforms do not directly provide information about linkage phase; i.e., co-inherited alleles at adjacent heterozygous markers (haplotypes) are not identified as such. As haplotype information may considerably empower genetic analyses, indirect phasing strategies have been devised: haplotypes can be reconstructed from unphased genotypes using either familial information (Mendelian segregation and linkage) and/or population information (linkage disequilibrium, LD, and surrogate parents) (e.g., Windig and Meuwissen 2004; Scheet and Stephens 2006; Kong et al. 2008).Haplotype-based approaches are routinely applied in animal genetics for combined linkage and LD mapping of QTL (e.g., Meuwissen and Goddard 2000; Blott et al. 2003). In these studies, phasing has so far relied on familial information provided by the extended pedigrees typical of livestock (e.g., Windig and Meuwissen 2004). This approach, however, leaves a nonnegligible proportion of genotypes unphased, especially for the less connected individuals. After phasing, identity-by-descent (IBD) probabilities conditional on haplotype data—needed for QTL mapping—are computed for all chromosome pairs, using familial as well as population information (hence combined linkage and LD mapping – L + LD) (e.g., Meuwissen and Goddard 2001). However, the use of high-density SNP chips and the analysis of ever larger cohorts render the computation of pairwise IBD probabilities a bottleneck.We herein propose a more efficient, heuristic approach based on hidden Markov models (HMM). It simultaneously phases and sorts haplotypes in clusters that can be used directly for mapping or other purposes. The proposed method exploits familial as well as population information, and imputes missing genotypes. We herein describe the accuracy of the proposed method and its use for L + LD mapping of QTL.     

High Sensitivity to Auxin is a Common Feature of Hairy Root

The responses to auxin of Lycopersicon esculentum roots transformed by (T_l+T_r)-DNA of the Ri plasmid of agropine-type Agrobacterium rhizogenes strain 15834 and Catharanthus trichophyllus roots transformed by the (T_l+T_r)-DNA, and by T_l- or T_r- DNA alone of the same bacterial strain were compared to that of their normal counterparts. The transmembrane electrical potential difference of root protoplasts was measured as a function of the concentration of exogenous naphthalene acetic acid. The sensitivity to auxin expressed by this response was shown to be independent of the measurement conditions and of the basal polarization of isolated protoplasts. According to this electrical response, as well as to the modulation by auxin of proton excretion by root tips and root tip elongation, roots transformed by (T_l+T_r) DNA are 100 to 1000 times more sensitive to exogenous auxin than normal roots, as is the case with normal and transformed roots from Lotus corniculatus (WH Shen, A Petit, J Guern, J Tempé [1988] Proc Natl Acad Sci USA 85: 3417-3421). Further-more, transformed roots of C. trichophyllus are not modified in their sensitivity to fusicoccin, illustrating the specificity of the modification of the auxin sensitivity. Roots transformed by the T_r-DNA alone showed the same sensitivity to auxin as normal roots, whereas the roots transformed by the T_l-DNA alone exhibited an auxin sensitivity as high as the roots transformed by (T_l+T_r)-DNA. It was concluded that the high sensitivity to auxin is controlled by the T_l-DNA in agropine type Ri plasmids.     

Sex-Linked Inheritance in Macaque Monkeys: Implications for Effective Population Size and Dispersal to Sulawesi

Sex-specific differences in dispersal, survival, reproductive success, and natural selection differentially affect the effective population size (N_e) of genomic regions with different modes of inheritance such as sex chromosomes and mitochondrial DNA. In papionin monkeys (macaques, baboons, geladas, mandrills, drills, and mangabeys), for example, these factors are expected to reduce N_e of paternally inherited portions of the genome compared to maternally inherited portions. To explore this further, we quantified relative N_e of autosomal DNA, X and Y chromosomes, and mitochondrial DNA using molecular polymorphism and divergence information from pigtail macaque monkeys (Macaca nemestrina). Consistent with demographic expectations, we found that N_e of the Y is lower than expected from a Wright–Fisher idealized population with an equal proportion of males and females, whereas N_e of mitochondrial DNA is higher. However, N_e of 11 loci on the X chromosome was lower than expected, a finding that could be explained by pervasive hitchhiking effects on this chromosome. We evaluated the fit of these data to various models involving natural selection or sex-biased demography. Significant support was recovered for natural selection acting on the Y chromosome. A demographic model with a skewed sex ratio was more likely than one with sex-biased migration and explained the data about as well as an ideal model without sex-biased demography. We then incorporated these results into an evaluation of macaque divergence and migration on Borneo and Sulawesi islands. One X-linked locus was not monophyletic on Sulawesi, but multilocus data analyzed in a coalescent framework failed to reject a model without migration between these islands after both were colonized.THE effective size of a population (N_e) determines the relative impact of genetic drift and natural selection on mutations with mild effects on fitness (Charlesworth 2009). Differences in N_e are hypothesized to affect virtually every aspect of genome evolution, including rates of molecular evolution, abundance of introns and transposable elements, and persistence of duplicate genes, and this has important implications for the evolution of complexity via both adaptive and degenerative processes (Lynch 2007). Of relevance are not only the number of different individuals in a population, but also the number of copies of a gene within each individual. In diploid species with separate sexes, sex chromosomes and mitochondrial DNA (mtDNA) differ in copy number from autosomal DNA (aDNA): both sexes have two alleles at autosomal loci whereas in species with male heterogamy, males have one X and one Y chromosome, females have two Xs, and a female/male pair has effectively only one copy of mtDNA due to maternal inheritance. Sex-specific differences in demographic parameters such as migration, adult sex ratio, and variance in reproductive success also affect relative copy number and associated levels of neutral polymorphism at mtDNA, aDNA, the X chromosome (xDNA), and the Y chromosome (yDNA) (Hedrick 2007).The effective population size is the number of individuals in a Wright–Fisher idealized population (Fisher 1930; Wright 1931) that have the same magnitude of genetic drift as an observed population, where ideal individuals are diploid, and have discrete (nonoverlapping) generations, constant population size, and random mating. N_e can be quantified in terms of variance in allele frequency over generations (variance N_e) or variance in inbreeding over time (inbreeding N_e). If population size is constant with random mating, these approaches for quantifying N_e produce identical results (Kimura and Crow 1963; Whitlock and Barton 1997). At mutation–drift equilibrium with an equal number of males and females and a Poisson distributed number of offspring with a mean of two offspring per individual, N_e-aDNA and N_e-xDNA are expected to be four and three times as large, respectively, as N_e-yDNA and N_e-mtDNA; we refer to this as the “ideal expectation with an equal proportion of males and females.”Demography can alter relationships between N_e of different parts of the genome. For example, extreme skew in adult sex ratio can cause N_e of uniparentally inherited portions of the genome to exceed N_e of biparentally inherited portions (Figure 1A; Nunney 1993; Caballero 1994; Hoelzer 1997; Hedrick 2007). With a skewed sex ratio, the more common sex has a higher variance in reproductive success than the rare one, and this causes the overall variance in reproductive success to increase as the sex-ratio bias increases (Nunney 1993). Sex-biased dispersal such as female philopatry also alters relationships between N_e-aDNA, N_e-xDNA, N_e-yDNA, and N_e-mtDNA (Figure 1B), causing N_e of portions of the genome that disperse less to increase (Nei and Takahata 1993; Hoelzer 1997; Wang and Caballero 1999).Open in a separate windowFigure 1.—N_e of aDNA, xDNA, mtDNA, and yDNA as a function of (A) sex ratio skew and (B) the probability of female dispersal. In B, a finite island model of subdivided populations of constant size is assumed with a population size of 10,000 individuals, 10 subpopulations, and a male probability of migration equal to 0.1.At least five factors related to natural selection also can cause the relative N_e of aDNA, xDNA, yDNA, and mtDNA to depart from expectations: (1) very low or absent recombination in mtDNA and a portion of yDNA, (2) haploidy of mtDNA and yDNA, (3) hemizygosity of xDNA in males, (4) sexual selection and differences in gene content, and (5) differences in the rate and variance of mutation. “Selective sweeps” in which an advantageous mutation is fixed by natural selection, reduces N_e of linked sites (Maynard Smith and Haigh 1974) and this can affect the entire mitochondrial genome and nonrecombining portion of the Y chromosome. Nonrecombining portions of yDNA and mtDNA are also affected by stochastic loss of alleles containing the fewest deleterious mutations (“Muller''s ratchet”; Muller 1964; Felsenstein 1974), which results in a gradual decline of fitness of these chromosomes over time. N_e of nonrecombining DNA is further reduced by elimination of variation linked to substantially deleterious mutations (“background selection”; Charlesworth et al. 1993), by interference between linked polymorphisms that impedes fixation of advantageous alleles and extinction of deleterious ones (the “Hill–Robertson effect”; Hill and Robertson 1966; McVean and Charlesworth 2000), and by increased frequency of deleterious mutations linked to advantageous ones during a selective sweep (“genetic hitchhiking”; Rice 1987). Hemizygous X-linked and haploid Y-linked loci in males and mtDNA loci in both sexes are more vulnerable to recessive deleterious mutations because they are not masked by a second allele (Otto and Goldstein 1992). Hemizygosity on the X chromosome can also increase the rate of selective sweeps when advantageous mutations are recessive (Charlesworth et al. 1987). Similarly, these loci are also susceptible to recessive species incompatibilities—a factor that at least partially accounts for Haldane''s rule for hybrid sterility (Haldane 1922; Orr 1997). Sexual selection differentially influences the probability of fixation of mutations depending on mode of inheritance (Wade and Shuster 2004), especially mutations with antagonistic fitness effects between the sexes (Gibson et al. 2002). Additionally, the rate of evolution of animal mtDNA is much higher than aDNA, xDNA, and yDNA (Haag-Liautard et al. 2008) and this presumably contributes to variation in the frequency of nonneutral mutations in different parts of the genome.Differences among N_e of mtDNA, yDNA, xDNA, and aDNA are thought to be particularly pronounced in papionin monkeys (macaques, baboons, geladas, mandrills, drills, and mangabeys). These monkeys have a highly sex-biased adult demography; females form stable philopatric groups of close relatives, whereas males generally change social groups and disperse more widely (Dittus 1975). Often adult sex ratio of papionins is female biased (Dittus 1975; Melnick and Pearl 1987; O''Brien and Kinnard 1997; Okamoto and Matsumura 2001), and males have higher variance in reproductive success than females (Dittus 1975; de Ruiter et al. 1992; Keane et al. 1997; Van Noordwijk and Van Schaik 2002; Widdig et al. 2004). These sex differences predict strong population subdivision of mtDNA with little or no subdivision of aDNA, deep mtDNA coalescence times, and frequent mtDNA paraphyly among species, and discordant genealogical relationships between mtDNA and yDNA—and this has been observed in multiple studies (Melnick and Pearl 1987; Melnick 1988; Melnick and Hoelzer 1992; Melnick et al. 1993; Hoelzer et al. 1994; Evans et al. 1999, 2001, 2003; Tosi et al. 2000, 2002, 2003; Newman et al. 2004). Female philopatry and obligate male migration is a common social system in mammals (Greenwood 1980; Dobson 1982; Johnson 1986), though less so in humans (Seielstad et al. 1998), and molecular variation provides an effective tool for exploring the impact of natural selection and demography on aDNA, the sex chromosomes, and mtDNA (Nachman 1997; Bachtrog and Charlesworth 2002; Stone et al. 2002; Berlin and Ellegren 2004; Hellborg and Ellegren 2004; Wilder et al. 2004; Hammer et al. 2008).We explored the genetic effects of demography and linked selection in structuring sequence polymorphism of a papionin monkey—the macaques—at two levels. We first tested whether levels of polymorphism in aDNA, xDNA, yDNA, and mtDNA in a Bornean population of the pigtail macaque, Macaca nemestrina, match expectations under scenarios involving natural selection and also whether the data might be explained by simple demographic models with sex-specific dispersal or a biased sex ratio. We then explored demography on a larger, inter-island scale by estimating the time of divergence between macaques on Borneo and Sulawesi islands and by testing for evidence of ongoing migration between these islands.     

Photoacoustic Study of Changes in the Energy Storage of Photosystems I and II during State 1-State 2 Transitions

Using photoacoustic spectroscopy, state 1-state 2 transitions were demonstrated in vivo in intact sugar maple leaves (Acer saccharum Marsh.) by following the changes in energy storage of photosystems (PS) I and II. Energy storage measured with 650 nm modulated light (light 2) in the presence of background white light indicated the total energy stored by both photosystems (ES_t), and in the presence of background far-red light showed the energy stored by PSI (ES_psi). The difference between ES_t and ES_psi gave the energy stored by PSII (ES_psii). While ES_t remained nearly constant during state transitions, both ES_psi and ES_psii changed considerably. The ratio of ES_psii to ES_psi, an indicator of the energy distribution between the two photosystems, decreased or increased during transition to state 2 or state 1, respectively. State transitions were completed in about 20 min and were fully reversible. During transition from state 1 to state 2, the fraction of excitation energy gained by PSI was nearly equal to that lost by PSII. This fraction of excitation energy transferred from PSII to PSI accounted for about 5% of the absorbed light (fluorescence is not considered), 19% of ES_t, 34% of ES_psii, and 43% of ES_psi in state 2. NaF treatment inhibited the transition to state 1. Data in the present study confirm the concept of changes in absorption cross-section of photosystems during state transitions.     

Mating-System Variation,Demographic History and Patterns of Nucleotide Diversity in the Tristylous Plant Eichhornia paniculata

Inbreeding in highly selfing populations reduces effective size and, combined with demographic conditions associated with selfing, this can erode genetic diversity and increase population differentiation. Here we investigate the role that variation in mating patterns and demographic history play in shaping the distribution of nucleotide variation within and among populations of the annual neotropical colonizing plant Eichhornia paniculata, a species with wide variation in selfing rates. We sequenced 10 EST-derived nuclear loci in 225 individuals from 25 populations sampled from much of the geographic range and used coalescent simulations to investigate demographic history. Highly selfing populations exhibited moderate reductions in diversity but there was no significant difference in variation between outcrossing and mixed mating populations. Population size interacted strongly with mating system and explained more of the variation in diversity within populations. Bayesian structure analysis revealed strong regional clustering and selfing populations were highly differentiated on the basis of an analysis of F_st. There was no evidence for a significant loss of within-locus linkage disequilibrium within populations, but regional samples revealed greater breakdown in Brazil than in selfing populations from the Caribbean. Coalescent simulations indicate a moderate bottleneck associated with colonization of the Caribbean from Brazil ∼125,000 years before the present. Our results suggest that the recent multiple origins of selfing in E. paniculata from diverse outcrossing populations result in higher diversity than expected under long-term equilibrium.THE rate of self-fertilization in hermaphrodite organisms is expected to affect a number of important features of population genetic structure and diversity. Most directly, homozygosity increases as a function of the selfing rate and thus reduces the effective population size (N_e), up to twofold with complete selfing (Pollak 1987; Charlesworth et al. 1993; Nordborg 2000). Further, because of increased homozygosity, crossing over rarely occurs between heterozygous sites, thus increasing linkage disequilibrium (LD). Higher LD causes stronger hitchhiking effects such as selective sweeps, background selection, and Hill–Robertson interference, all of which are expected to further reduce the amount of neutral genetic variation within populations (reviewed in Charlesworth and Wright 2001).Population genetic processes resulting from inbreeding may be further augmented by demographic and life-history characteristics associated with the selfing habit. In particular, selfing populations can be founded by single individuals, resulting in striking reductions in diversity as a result of genetic bottlenecks and reproductive isolation. The capacity for uniparental reproduction gives many selfers prolific colonizing ability and the capacity to establish after long-distance dispersal, especially in comparison with obligate outcrossers (Baker 1955; Pannell and Barrett 1998). The colonization–extinction dynamics typical of many selfing species and limited pollen-mediated gene flow also increase differentiation among populations, resulting in considerable population subdivision (Hamrick and Godt 1990, 1996; Schoen and Brown 1991). Although the total amounts of among-population variation may be less affected by these processes (Pannell and Charlesworth 1999; Ingvarsson 2002), the demographic and life-history characteristics of many selfing species are likely to result in nonequilibrium conditions occurring in selfing populations.In many taxa where selfing has evolved it may be of relatively recent origin (Schoen et al. 1997; Takebayashi and Morrell 2001; Foxe et al. 2009; Guo et al. 2009). Where selfing has recently established, demographic forces associated with colonization may be as important as the mating system per se in structuring patterns of diversity. For example, if selfing originates through the establishment of a small number of founders, we would expect a sharp reduction in diversity relative to the outcrossing progenitor and a strong signature of a genetic bottleneck. In contrast, if selfing has evolved recently through the spread of genetic modifiers of small effect, newly established populations may retain significant amounts of ancestral polymorphism from their outcrossing progenitors. In this latter case populations may retain considerably more variation than expected under long-term equilibrium predictions.Molecular evidence for reduced nucleotide diversity and greater differentiation among populations of selfing taxa compared to populations of related outcrossing taxa has been reported from Leavenworthia (Liu et al. 1998, 1999), Arabidopsis (Savolainen et al. 2000; Wright et al. 2002), Solanum (Baudry et al. 2001), Mimulus (Sweigart and Willis 2003), Amsinckia (Perusse and Schoen 2004), and Caenorhabditis (Graustein et al. 2002; Cutter et al. 2006; Cutter 2008). In each case the reduction in diversity was more severe than the twofold reduction predicted for selfing populations at equilibrium. This indicates that factors in addition to the mating system are reducing diversity, but it has been difficult to uncouple the relative importance of genetic hitchhiking from the ecology and demographic history of selfing taxa. This challenge parallels similar difficulties in efforts to distinguish selective from demographic explanations in population genetic studies of Drosophila (Haddrill et al. 2005; Ometto et al. 2005; Thornton and Andolfatto 2006; Jensen et al. 2008). However, in many plant populations, especially those with annual life histories and small structured populations, demographic processes may play a more prominent role in causing reduced diversity than increased hitchhiking associated with selfing.Molecular population genetic studies of selfing in plants have generally focused on either small samples from a large number of populations (e.g., Sweigart and Willis 2003; Nordborg et al. 2005) or relatively large within-population samples from a small number of populations (e.g., Baudry et al. 2001). Ideally, a deeper sampling both within and among populations combined with independent ecological and historical information is required to improve understanding of the interplay of demographic and selective factors. Here we address these issues by examining patterns of nucleotide diversity within a large sample of populations of Eichhornia paniculata (Pontederiaceae), an annual species for which there is considerable ecological and demographic information (reviewed in Barrett and Husband 1997).E. paniculata occurs primarily in northeastern (N.E.) Brazil and the Caribbean islands of Cuba and Jamaica. Various lines of evidence suggest that Brazil is the original source region for Caribbean populations (reviewed in Barrett et al. 2009). Populations of E. paniculata exhibit striking mating-system diversity, ranging from predominantly outcrossing to those that are highly selfing (outcrossing rate, t = 0.002–0.96; n = 54 populations) (Barrett and Husband 1990; Barrett et al. 1992). Variation in mating system is associated with the evolutionary breakdown of the species'' tristylous genetic polymorphism and the spread and fixation of selfing variants capable of autonomous self-pollination (Barrett et al. 1989). Populations of E. paniculata are characterized by three morph structures: trimorphic with long-, mid-, and short-styled morphs (hereafter L-, M-, and S-morphs); dimorphic, with two floral morphs, most commonly the L- and M-morphs; and monomorphic, primarily composed of selfing variants of the M-morph. The morph structure and presence of selfing variants within populations explain ∼60% of the variation in outcrossing rates among populations (Barrett and Husband 1990). Trimorphic populations are largely outcrossing, dimorphic populations display mixed mating, and monomorphic populations are highly selfing. Patterns of allozyme variation indicate a reduction in diversity with increased selfing rates and greater among-population differentiation (Glover and Barrett 1987; Barrett and Husband 1990; Husband and Barrett 1993). Finally, studies of the inheritance of mating-system modifiers (Fenster and Barrett 1994; Vallejo-Marín and Barrett 2009) in combination with allozyme (Husband and Barrett 1993) and molecular evidence (Barrett et al. 2009) indicate that the transition from outcrossing to selfing in E. paniculata has occurred on multiple occasions.The goal of our study was to investigate the relation between mating-system variation and neutral molecular diversity for a large sample of E. paniculata populations encompassing most of the geographical range. This was accomplished by collecting multilocus nucleotide sequence data from 225 individuals sampled from 25 populations including trimorphic, dimorphic, and monomorphic populations. Because it has been previously demonstrated that this sequence of morph structures is strongly associated with increasing rates of self-fertilization (see Barrett and Husband 1990), we predicted a decrease in neutral diversity and increases in F_st and linkage disequilibrium from floral trimorphism to monomorphism. This extensive population-level sampling across a wide range of selfing rates allowed us to investigate the relative importance of mating system, geography, and current population size in structuring genetic variation. We also applied the approaches of Bayesian clustering (Pritchard et al. 2000; Falush et al. 2003; Gao et al. 2007) and divergence population genetics (Wakeley and Hey 1997; Hey and Nielsen 2004; Becquet and Przeworski 2007) to investigate the demographic history of E. paniculata and to provide a framework for understanding island colonization and the transition from outcrossing to selfing.