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

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

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

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

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.     

Profiling Sex-Specific piRNAs in Zebrafish

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

The Functional Transfer of Genes From the Mitochondria to the Nucleus: The Effects of Selection,Mutation, Population Size and Rate of Self-Fertilization

The transfer of mitochondrial genes to the nucleus is a recurrent and consistent feature of eukaryotic genome evolution. Although many theories have been proposed to explain such transfers, little relevant data exist. The observation that clonal and self-fertilizing plants transfer more mitochondrial genes to their nuclei than do outcrossing plants contradicts predictions of major theories based on nuclear recombination and leaves a gap in our conceptual understanding how the observed pattern of gene transfer could arise. Here, with a series of deterministic and stochastic simulations, we show how epistatic selection and relative mutation rates of mitochondrial and nuclear genes influence mitochondrial-to-nuclear gene transfer. Specifically, we show that when there is a benefit to having a mitochondrial gene present in the nucleus, but absent in the mitochondria, self-fertilization dramatically increases both the rate and the probability of gene transfer. However, absent such a benefit, when mitochondrial mutation rates exceed those of the nucleus, self-fertilization decreases the rate and probability of transfer. This latter effect, however, is much weaker than the former. Our results are relevant to understanding the probabilities of fixation when loci in different genomes interact.GENOMIC investigations of obligate intracellular endosymbionts (Moran and Wernegreen 2000; Akman et al. 2002; Tamas et al. 2002; Wernegreen et al. 2002; Klasson and Andersson 2004; Foster et al. 2005) reveal a reduction in genome size and number of protein-coding genes compared to their free-living relatives (Charles et al. 1999; Gil et al. 2002; Wernegreen et al. 2002; Moran 2003; Van Ham et al. 2003; Klasson and Andersson 2004; Khachane et al. 2007). Similarly, mitochondria—ancient obligate intracellular symbionts of eukaryotes—have retained very few protein-coding genes (Boore 1999; Adams et al. 2002) [Reclinomonas americanas is at the extreme of retention of mitochondrial genes (Lang et al. 1997)]. Understanding the process of gene loss in mitochondria and other endosymbionts is a major research focus of mitochondrial and endosymbiont genomics (Moran 2003; Timmis et al. 2004; Khachane et al. 2007; Bock and Timmis 2008).The loss of endosymbiont genes can be complete, in which lost genes are absent from the host–endosymbiont complex, a substitution, in which a nuclear allele functions in place of the lost symbiont gene, or a functional transfer of an endosymbiont gene to the nucleus, followed by its loss (Adams and Palmer 2003). Such “functional transfer” involves the relocation of a mitochondrial gene to the nucleus, its acquisition of a promoter, successful targeting to the mitochondria for proper function, and the eventual loss of the gene from the mitochondrial genome altogether. Although this process is probably quite complex and requires numerous evolutionary modifications (Murcha et al. 2005), there is evidence that some mitochondrial genes are preadapted to functional transfer as they contain signals that target them to the mitochondria before functional transfer to the nucleus (Ueda et al. 2008a). The complex evolution of rps16 is an illuminating case of both functional gene transfer and substitution. In some lineages, the mitochondrial rps16 is functionally expressed in the nucleus but absent from the mitochondria (functional transfer) while in a subset of taxa, the chloroplast copy is also absent and the nuclear gene is also targeted to the chloroplast [substitution (Ueda et al. 2008b)].A number of evolutionary scenarios have been proposed to account for the massive loss of genes from endosymbionts. A subset of models argues that endosymbiont gene loss is a neutral or nearly neutral process. Since endosymbiosis reduces the strength of selection on genes that are unnecessary or redundant in an obligate intracellular environment, these genes may be quickly lost by the neutral fixation of a deletion or other loss-of-function mutations. Moreover, even when selection favors the retention of genes in endosymbionts, such selection may be ineffective because of reduction in effective population size due to recurrent bottlenecking (Rispe and Moran 2000). Additionally, frequent input of functional endosymbiont genes into the nucleus makes symbiont genes redundant, exacerbating gene loss via functional transfer (Berg and Kurland 2000).An alternative class of explanations views the loss of mitochondrial genes (be it complete loss, substitution, or functional transfer) as an adaptive process. The “mitochondrial competition theory” argues that mitochondrial genomes that either do not contain or do not express a given allele have a replicative advantage over other mitochondria, providing a within-host selective advantage to mitochondrial gene loss (Albert et al. 1996; Selosse et al. 2001; Yamauchi 2005). The “benefits of sex” model posits that the genomic diploid nuclear environment (diploid, sexual) is in some way preferable (e.g., as an escape from Muller''s ratchet or Hill–Robertson interference) to a haploid asexual mitochondrial environment (Blanchard and Lynch 2000). The epistatic model (Wade and Goodnight 2006) does not advance a specific or consistent benefit to transfer, but posits that transfer is explicitly a process of coevolution between mitochondrial and nuclear genomes, where fitness is a function of the gene combination rather than of either gene separately.Because few species are currently undergoing mitochondrial to nuclear gene transfer, these alternative hypotheses are difficult to distinguish with direct experimentation. However, the distribution of transferred genes across lineages allows for evaluation of the alternative hypotheses. For example, self-pollination reduces the rate of heteroplasmy and consequently the opportunity for competition among genetically distinct mitochondria. Thus, the mitochondrial competition theory predicts an excess of transfer events in sexual, outcrossing lineages, with high degrees of “paternal leakage.” Similarly, frequent self-fertilization diminishes the benefits of sex, and thus the benefits of sex hypothesis predicts fewer transfers in selfing and clonally reproducing plants than in outcrossing taxa. The epistatic model makes the opposite prediction. Selfing and clonal reproduction maintain cyto-nuclear gene combinations and increase the response to selection on epistatic combinations, potentially encouraging transfer. On the other hand, outcrossing tends to break apart adaptive cyto-nuclear gene combinations, potentially decreasing the amount of adaptive transfer in outcrossing lineages.Plant lineages with high levels of self-fertilization or asexual reproduction transfer more mitochondrial genes to their nuclei than predominantly sexual and outcrossing lineages (Brandvain et al. 2007). This result is consistent with predictions of the epistatic model and is contrary to predictions of the mitochondrial competition or benefits of sex models. More specific predictions allowing further empirical tests require more detailed theoretical investigations of the gene transfer process. Here, we investigate the roles of mutation, selection, and random drift in gene transfer using both deterministic models and stochastic simulations to refine and extend predictions of patterns of functional mitochondrial to nuclear gene transfer.     

Phenotypic Consequences of Aneuploidy in Arabidopsis thaliana

Aneuploid cells are characterized by incomplete chromosome sets. The resulting imbalance in gene dosage has phenotypic consequences that are specific to each karyotype. Even in the case of Down syndrome, the most viable and studied form of human aneuploidy, the mechanisms underlying the connected phenotypes remain mostly unclear. Because of their tolerance to aneuploidy, plants provide a powerful system for a genome-wide investigation of aneuploid syndromes, an approach that is not feasible in animal systems. Indeed, in many plant species, populations of aneuploid individuals can be easily obtained from triploid individuals. We phenotyped a population of Arabidopsis thaliana aneuploid individuals containing 25 different karyotypes. Even in this highly heterogeneous population, we demonstrate that certain traits are strongly associated with the dosage of specific chromosome types and that chromosomal effects can be additive. Further, we identified subtle developmental phenotypes expressed in the diploid progeny of aneuploid parent(s) but not in euploid controls from diploid lineages. These results indicate long-term phenotypic consequences of aneuploidy that can persist after chromosomal balance has been restored. We verified the diploid nature of these individuals by whole-genome sequencing and discuss the possibility that trans-generational phenotypic effects stem from epigenetic modifications passed from aneuploid parents to their diploid progeny.THE genome of aneuploid individuals contains incomplete chromosome sets. The balance between chromosome types, and the genes they encode, is compromised, resulting in altered expression of many genes, including genes with dosage-sensitive effects on phenotypes. In humans, only a few types of aneuploid karyotypes are viable (Hassold and Hunt 2001), highlighting the deleterious effect of chromosome imbalance. The most commonly known viable form of aneuploidy in humans is Down syndrome, which results from a trisomy of chromosome 21 in an otherwise diploid background. Down syndrome patients exhibit many specific phenotypes, sometimes visible only in a subset of patients (Antonarakis et al. 2004). For phenotypes found in all Down syndrome patients, the penetrance of each phenotype varies between patients (Antonarakis et al. 2004). Despite the increasing amount of information available about the human genome and the availability of a mouse model for Down syndrome (O''Doherty et al. 2005), the genes responsible for most of the phenotypes associated with Down syndrome are still unknown (Patterson 2007; Korbel et al. 2009; Patterson 2009). Recently, detailed phenotypic analyses of as many as 30 aneuploid patients have allowed the identification of susceptibility regions for several specific phenotypes (Patterson 2007, 2009; Korbel et al. 2009; Lyle et al. 2009), but the specific genes remain to be identified. Understanding the physiology of aneuploidy is not only relevant to those individuals with aneuploid genomes but also to understanding cancer since most cancerous cells are aneuploid (Matzke et al. 2003; Pihan and Doxsey 2003; Storchova and Pellman 2004; Holland and Cleveland 2009; Williams and Amon 2009) or the consequences of copy number variation and dosage sensitivity (Dear 2009; Henrichsen et al. 2009).Plants are more tolerant of aneuploidy than animals (Matzke et al. 2003) for reasons that remain unclear. Since the discovery of the Datura trisomic “chromosome mutants” by Blakeslee (1921, 1922), viable trisomics of each chromosome type have been described in numerous species. Trisomics exhibit phenotypes specific to the identity of the triplicated chromosome (Blakeslee 1922; Khush 1973; Koornneef and Van der Veen 1983; Singh 2003). More complex aneuploids, i.e., individuals carrying more than one additional chromosome, can be viable as well and have been observed in many plants species, especially among the progeny of triploid individuals (McClintock 1929; Levan 1942; Johnsson 1945; Khush 1973). Some species appear to be more tolerant of complex aneuploidies than others, suggesting a genetic basis for aneuploidy tolerance (Satina and Blakeslee 1938; Khush 1973; Ramsey and Schemske 2002; Henry et al. 2009). Aneuploid individuals frequently appear spontaneously within polyploid plant populations, presumably due to a failure to equally partition the multiple chromosome sets at meiosis (Randolph 1935; Doyle 1986). These aneuploids exhibit few or subtle phenotypic abnormalities and can often compete with their euploid progenitors (Ramsey and Schemske 1998). Plants therefore provide an excellent opportunity for a genome-wide investigation of aneuploid syndromes: sample size is not limited, phenotypes can be described and assessed in detail, and plant aneuploid populations provide a complex mixture of viable karyotypes.In this article, we report our investigation of the relationship between phenotype and karyotype in populations of aneuploid Arabidopsis thaliana plants. All simple trisomics of A. thaliana have been previously isolated and phenotypically characterized (Steinitz-Sears 1962; Lee-Chen and Steinitz-Sears 1967; Steinitz-Sears and Lee-Chen 1970; Koornneef and Van der Veen 1983), demonstrating that they are tolerated in A. thaliana. We previously reported that aneuploid swarms—populations of aneuploid individuals of varying aneuploid karyotypes—could be obtained from the progeny of triploid A. thaliana individuals (Henry et al. 2005, 2009). Using a combination of a quantitative PCR-based method and flow cytometry, we were able to derive the full aneuploid karyotype of each of these individuals (Henry et al. 2006). We further crossed triploid A. thaliana to diploid or tetraploid individuals and demonstrated that at least 44 of the 60 possible aneuploid karyotypes that could result from these crosses (aneuploid individuals carrying between 11 and 19 chromosomes) were viable and successfully produced adult plants. Taken together, these populations and methods make it possible to explore the basis of aneuploid syndromes in A. thaliana. In this study, we were able to phenotypically characterize at least one individual from 25 different aneuploid karyotypes falling between diploidy and tetraploidy. We demonstrated that specific phenotypes are affected by the dosage of specific chromosome types. The effect of the dosage of specific chromosome types on traits was additive and could be used to predict the observed phenotype. The availability of multiple generations of aneuploid and euploid individuals allowed us to investigate potential long-term effects of aneuploidy as well as parent-of-origin effects on aneuploid phenotypes.     

Recurrent Selection on the Winters sex-ratio Genes in Drosophila simulans

Selfish genes, such as meiotic drive elements, propagate themselves through a population without increasing the fitness of host organisms. X-linked (or Y-linked) meiotic drive elements reduce the transmission of the Y (X) chromosome and skew progeny and population sex ratios, leading to intense conflict among genomic compartments. Drosophila simulans is unusual in having a least three distinct systems of X chromosome meiotic drive. Here, we characterize naturally occurring genetic variation at the Winters sex-ratio driver (Distorter on the X or Dox), its progenitor gene (Mother of Dox or MDox), and its suppressor gene (Not Much Yang or Nmy), which have been previously mapped and characterized. We survey three North American populations as well as 13 globally distributed strains and present molecular polymorphism data at the three loci. We find that all three genes show signatures of selection in North America, judging from levels of polymorphism and skews in the site-frequency spectrum. These signatures likely result from the biased transmission of the driver and selection on the suppressor for the maintenance of equal sex ratios. Coalescent modeling indicates that the timing of selection is more recent than the age of the alleles, suggesting that the driver and suppressor are coevolving under an evolutionary “arms race.” None of the Winters sex-ratio genes are fixed in D. simulans, and at all loci we find ancestral alleles, which lack the gene insertions and exhibit high levels of nucleotide polymorphism compared to the derived alleles. In addition, we find several “null” alleles that have mutations on the derived Dox background, which result in loss of drive function. We discuss the possible causes of the maintenance of presence–absence polymorphism in the Winters sex-ratio genes.MEIOTIC drive can leave signatures in the genome similar to positive natural selection without increasing the fitness of an organism (Lyttle 1993). Drive elements are preferentially transmitted during meiosis by disrupting the development or function of sperm carrying the homologous chromosome (Zimmering et al. 1970, meiotic drive sensu lato), or by true chromosome segregation defects during meiosis (Sandler and Novitski 1957, meiotic drive sensu stricto; Tao et al. 2007a). While drive elements may arise on any chromosome, sex-linked drivers have higher population invasion probabilities than autosomal drivers and are more easily detected due to their impact on progeny sex ratios (Hurst and Pomiankowski 1991). To survive, a driver must maintain tight linkage with an insensitive target locus lest it drive against itself, a condition ensured by the lack of recombination between sex chromosomes (Charlesworth and Hartl 1978). Because of the impact drive elements have on sex ratios, sex-linked drivers are often referred to as “sex-ratio distorters” and the phenotype of skewed progeny sex ratios is termed “sex-ratio.” The mere transmission advantage of a driver, unless balanced by some detrimental fitness effect or masked by a suppressor, can cause it to sweep through a population in a manner similar to a positively selected mutation (Edwards 1961; Vaz and Carvalho 2004).Obviously, a complete sweep of a sex-linked driver dooms a male-less (or female-less) population to extinction (Hamilton 1967), and natural selection strongly favors genetic factors that suppress drive and restore Mendelian segregation. Fisher (1930) presented a qualitative argument for the maintenance of an equal sex ratio, which predicts selection on any heritable variant that increases the production of the rarer sex. Fisher''s principle has been formalized mathematically and demonstrated empirically (e.g., Bodmer and Edwards 1960; Carvalho et al. 1998). Suppressors have been identified in a wide variety of meiotic drive systems and are predicted to be strongly favored by natural selection for the maintenance of equal sex ratios (reviewed by Jaenike 2001). Furthermore, the evolution of linked enhancer genes may enable drivers to evade suppression, setting off another bout of Fisherian selection for equal sex ratios (Hartl 1975).Meiotic drive is widespread, with systems identified in mammals, insects, and plants (Jaenike 2001). Drosophila is the most extensively studied insect taxon, and sex-chromosome meiotic drive systems have been identified in more than a dozen species (Jaenike 2001). Cryptic (i.e., suppressed) distorters may be identified when the association between driver and suppressor is lost, such as in hybrids between species or populations that do not share meiotic drive systems (Mercot et al. 1995). The coevolutionary arms race between drivers and suppressors likely contributes to Haldane''s rule (the preferential sterility or inviability of heterogametic hybrids) and is a leading explanation for the importance of X-linked loci in causing hybrid male sterility (Frank 1991; Hurst and Pomiankowski 1991; Tao et al. 2007b; Presgraves 2008). Indeed, two recently characterized hybrid male sterility factors are also sex-ratio distorters—direct evidence of a link between meiotic drive and speciation (Tao et al. 2001; Orr and Irving 2005; Phadnis and Orr 2009).The three X-linked drive systems of Drosophila simulans are genetically distinct and have been termed Paris, Durham, and Winters (Tao et al. 2007a). Here, we focus on the Winters sex-ratio (SR), whose driver and suppressor have been mapped to the gene level and whose molecular and cellular features have been elucidated (Tao et al. 2007a,b). Distortion requires two genes, Distorter on the X (Dox) and Mother of Dox (MDox); Dox is a duplicate copy of MDox (Tao et al. 2007a; Y. Tao, personal communication). The dominant suppressor, Not Much Yang (Nmy), is a retrotransposed copy of Dox on chromosome 3R (Tao et al. 2007b). Nmy likely suppresses Dox through an RNA interference mechanism by forming a double stranded RNA with homology to the distorter RNAs (Tao et al. 2007b). The genes of the Winters sex-ratio are not found in D. melanogaster, which diverged from D. simulans ∼2.3 million years ago (Li et al. 1999). Initial surveys of the genes in the simulans clade indicate that a functional Nmy gene is present in D. mauritiana (Tao et al. 2007b). Thus, the Winters genes are >250,000 years old, the speciation time of D. simulans, D. mauritiana, and D. sechellia (McDermott and Kliman 2008).Signatures of positive selection have been previously detected at genomic regions linked to Drosophila sex-ratio distorters. However, this study represents the first evidence of selection acting directly on a sex-ratio distorter gene and its suppressor gene. In D. recens, driving X chromosomes show reduced nucleotide and haplotype variability relative to standard (nondriving) X chromosomes, and linkage disequilibrium extends over 130 cM of the driving chromosome (Dyer et al. 2007). The Paris driver has been localized to a pair of duplicated loci 150 kb apart; recent work shows reduced haplotype diversity and linkage disequilibrium between variants associated with drive (Derome et al. 2008). In this study, we characterize patterns of genetic variation in natural populations of North American D. simulans and find signatures of recent and strong positive selection at all three genes of the Winters sex-ratio.     

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.     

Defining and Mapping Mammalian Coat Pattern Genes: Multiple Genomic Regions Implicated in Domestic Cat Stripes and Spots

Mammalian coat patterns (e.g., spots, stripes) are hypothesized to play important roles in camouflage and other relevant processes, yet the genetic and developmental bases for these phenotypes are completely unknown. The domestic cat, with its diversity of coat patterns, is an excellent model organism to investigate these phenomena. We have established three independent pedigrees to map the four recognized pattern variants classically considered to be specified by a single locus, Tabby; in order of dominance, these are the unpatterned agouti form called “Abyssinian” or “ticked” (T^a), followed by Spotted (T^s), Mackerel (T^M), and Blotched (t^b). We demonstrate that at least three different loci control the coat markings of the domestic cat. One locus, responsible for the Abyssinian form (herein termed the Ticked locus), maps to an ∼3.8-Mb region on cat chromosome B1. A second locus controls the Tabby alleles T^M and t^b, and maps to an ∼5-Mb genomic region on cat chromosome A1. One or more additional loci act as modifiers and create a spotted coat by altering mackerel stripes. On the basis of our results and associated observations, we hypothesize that mammalian patterned coats are formed by two distinct processes: a spatially oriented developmental mechanism that lays down a species-specific pattern of skin cell differentiation and a pigmentation-oriented mechanism that uses information from the preestablished pattern to regulate the synthesis of melanin profiles.PATTERNED coats are typical of many mammalian groups, whose spots, stripes, and other markings have been hypothesized to play important adaptive roles in camouflage, predator evasion, and social communication (Cott 1940; Searle 1968; Ortolani and Caro 1996). Many mammals bear striped or spotted coats, and these phenotypes have historically drawn attention from many fields of human science and culture (e.g., the leopard''s spots, or the stripes seen in tigers and zebras). Although several theoretical studies have proposed mathematical models that could underlie the developmental dynamics of coat pattern formation in mammals (Murray and Oster 1984; Oyehaug et al. 2002), no direct investigation of the genetic basis of these phenotypes has yet been performed, so that their mechanistic causes remain a mystery. Recent advances in genomics, molecular biology, and evolutionary developmental biology (Evo-Devo) have revealed genes and pathways involved in skin pattern formation in Drosophila (Schug et al. 1998; Gompel et al. 2005; Prud''homme et al. 2006; Parchem et al. 2007), butterflies (Joron et al. 2006a,b), and zebrafish (Iwashita et al. 2006; Watanabe et al. 2006; Svetic et al. 2007). In contrast, despite the relevance of characterizing equivalent processes in mammals, little progress toward this goal has been accomplished, perhaps due to the lack of adequate mammalian models exhibiting variation in skin pattern and for which genetic and genomic tools were available.The domestic cat is a very promising model in this regard, as it presents several coat pattern variants and a growing body of genetic and genomic tools suitable for gene identification (Menotti-Raymond et al. 2003; Murphy et al. 2007; Pontius et al. 2007; Pontius and O''Brien 2007; Davis et al. 2009). Classic work on domestic cat coat color (Robinson 1958; Lomax and Robinson 1988) has suggested that there is a monogenic allelic series of coat patterns in the domestic cat, controlled by the Tabby (T) locus: in order of dominance, the four recognized alleles would be Abyssinian or “ticked” (T^a), Spotted (T^s), Mackerel (T^M), and Blotched (t^b) (Figure 1). Although there has been little doubt among breeders that the “mackerel” and “blotched” forms segregate as a single autosomal locus, this may not be the case for the other two phenotypes (T^a and T^s), which so far have not been tested thoroughly for allelism relative to the more common Tabby variants T^M and t^b. Some breeding data have suggested that these variants may not be allelic with the main Tabby locus (Lorimer 1995), but further scrutiny is required to test this hypothesis. A recent genetic study (Lyons et al. 2006) considered the Abyssinian variant as an allele of Tabby, reflecting the prevalent perception that they are coded by the same locus. Testing this hypothesis, and identifying the implicated genomic region (or regions), is a first step in the process of dissecting the molecular and developmental basis for these pattern-formation phenotypes.Open in a separate windowFigure 1.—Major coat pattern phenotypes of the domestic cat (Felis silvestris catus). A “hierarchy” of pelage patterns is observed in this species, with the absence of markings seen in Abyssinian cats (A) dominating over a spotted coat (B), which dominates over a “mackerel” (striped) coat (C), itself dominant over the blotched pattern (D). The classical, single-locus model for this phenotypic variation proposed the allelic series T^a > T^s > T^M > t^b for these respective variants.Aiming to investigate the genetic basis of pattern formation on the domestic cat pelage by genomic, positional methods, we established three separate pedigrees segregating for different combinations of coat pattern phenotypes. Our results demonstrate that at least three different loci underlie the striping and spotting patterns observed in domestic cats and identify the genomic location of two of them.     

Unraveling the Complex Trait of Crop Yield With Quantitative Trait Loci Mapping in Brassica napus

Yield is the most important and complex trait for the genetic improvement of crops. Although much research into the genetic basis of yield and yield-associated traits has been reported, in each such experiment the genetic architecture and determinants of yield have remained ambiguous. One of the most intractable problems is the interaction between genes and the environment. We identified 85 quantitative trait loci (QTL) for seed yield along with 785 QTL for eight yield-associated traits, from 10 natural environments and two related populations of rapeseed. A trait-by-trait meta-analysis revealed 401 consensus QTL, of which 82.5% were clustered and integrated into 111 pleiotropic unique QTL by meta-analysis, 47 of which were relevant for seed yield. The complexity of the genetic architecture of yield was demonstrated, illustrating the pleiotropy, synthesis, variability, and plasticity of yield QTL. The idea of estimating indicator QTL for yield QTL and identifying potential candidate genes for yield provides an advance in methodology for complex traits.YIELD is the most important and complex trait in crops. It reflects the interaction of the environment with all growth and development processes that occur throughout the life cycle (Quarrie et al. 2006). Crop yield is directly and multiply determined by yield-component traits (such as seed weight and seed number). Yield-related traits (such as biomass, harvest index, plant architecture, adaptation, resistance to biotic and abiotic constraints) may also indirectly affect yield by affecting the yield-component traits or by other, unknown mechanisms. Increasing evidence suggests that “fine-mapped” quantitative trait loci (QTL) or genes identified as affecting crop yield involve diverse pathways, such as seed number (Ashikari et al. 2005; Tian et al. 2006b; Burstin et al. 2007; Xie et al. 2008; Xing et al. 2008; Xue et al. 2008), seed weight (Ishimaru 2003; Song et al. 2005; Shomura et al. 2008; Wang et al. 2008; Xie et al. 2006, 2008; Xing et al. 2008; Xue et al. 2008), flowering time (Cockram et al. 2007; Song et al. 2007; Xie et al. 2008; Xue et al. 2008), plant height (Salamini 2003; Ashikari et al. 2005; Xie et al. 2008; Xue et al. 2008), branching (Clark et al. 2006; Burstin et al. 2007; Xing et al. 2008), biomass yield (Quarrie et al. 2006; Burstin et al. 2007), resistance and tolerance to biotic and abiotic stresses (Khush 2001; Brown 2002; Yuan et al. 2002; Waller et al. 2005; Zhang 2007; Warrington et al. 2008), and root architecture (Hochholdinger et al. 2008).Many experiments have explored the genetic basis of yield and yield-associated traits (yield components and yield-related traits) in crops. Summaries of identified QTL have been published for wheat (MacCaferri et al. 2008), barley (Von Korff et al. 2008), rice, and maize (http://www.gramene.org/). The results show several common patterns. First, QTL for yield and yield-associated traits tend to be clustered in the genome, which suggests that the QTL of the yield-associated traits have pleiotropic effects on yield. Second, this kind of pleiotropy has not been well analyzed genetically. The QTL for yield (complicated factor), therefore, have not been associated with any yield-associated traits (relatively simple factors, such as plant height). Therefore, they are unlikely to predict accurately potential candidate genes for yield. Third, only a few loci (rarely >10) have been found for each of these traits. Thus, the genetic architecture of yield has remained ambiguous. Fourth, trials were carried out in a few environments and how the mode of expression of QTL for these complex traits might respond in different environments is unclear.In this study, the genetic architecture of crop yield was analyzed through the QTL mapping of seed yield and eight yield-associated traits in two related populations of rapeseed (Brassica napus) that were grown in 10 natural environments. The complexity of the genetic architecture of seed yield was demonstrated by QTL meta-analysis. The idea of estimating indicator QTL (QTL of yield-associated traits, which are defined as the potential genetic determinants of the colocalized QTL for yield) for yield QTL in conjunction with the identification of candidate genes is described.