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Abstract We measured the floral bud transcriptome of 151 fully sequenced lines of Mimulus guttatus from one natural population. Thousands of single nucleotide polymorphisms (SNPs) are implicated as transcription regulators, but there is a striking difference in the allele frequency spectrum of cis-acting and trans-acting mutations. Cis-SNPs have intermediate frequencies (consistent with balancing selection) while trans-SNPs exhibit a rare-alleles model (consistent with purifying selection). This pattern only becomes clear when transcript variation is normalized on a gene-to-gene basis. If a global normalization is applied, as is typically in RNAseq experiments, asymmetric transcript distributions combined with “rarity disequilibrium” produce a superabundance of false positives for trans-acting SNPs. To explore the cause of purifying selection on trans-acting mutations, we identified gene expression modules as sets of coexpressed genes. The extent to which trans-acting mutations influence modules is a strong predictor of allele frequency. Mutations altering expression of genes with high “connectedness” (those that are highly predictive of the representative module expression value) have the lowest allele frequency. The expression modules can also predict whole-plant traits such as flower size. We find that a substantial portion of the genetic (co)variance among traits can be described as an emergent property of genetic effects on expression modules. 

Abstract Selection that acts in a sex-specific manner causes the evolution of sexual dimorphism. Sex-specific phenotypic selection has been demonstrated in many taxa and can be in the same direction in the two sexes (differing only in magnitude), limited to one sex, or in opposing directions (antagonistic). Attempts to detect the signal of sex-specific selection from genomic data have confronted numerous difficulties. These challenges highlight the utility of “direct approaches,” in which fitness is predicted from individual genotype within each sex. Here, we directly measured selection on Single Nucleotide Polymorphisms (SNPs) in a natural population of the sexually dimorphic, dioecious plant, Silene latifolia. We measured flowering phenotypes, estimated fitness over one reproductive season, as well as survival to the next year, and genotyped all adults and a subset of their offspring for SNPs across the genome. We found that while phenotypic selection was congruent (fitness covaried similarly with flowering traits in both sexes), SNPs showed clear evidence for sex-specific selection. SNP-level selection was particularly strong in males and may involve an important gametic component (e.g., pollen competition). While the most significant SNPs under selection in males differed from those under selection in females, paternity selection showed a highly polygenic tradeoff with female survival. Alleles that increased male mating success tended to reduce female survival, indicating sexual antagonism at the genomic level. Perhaps most importantly, this experiment demonstrates that selection within natural populations can be strong enough to measure sex-specific fitness effects of individual loci. Males and females typically differ phenotypically, a phenomenon known as sexual dimorphism. These differences arise when selection on males differs from selection on females, either in magnitude or direction. Estimated relationships between traits and fitness indicate that sex-specific selection is widespread, occurring in both plants and animals, and explains why so many species exhibit sexual dimorphism. Finding the specific loci experiencing sex-specific selection is a challenging prospect but one worth undertaking given the extensive evolutionary consequences. Flowering plants with separate sexes are ideal organisms for such studies, given that the fitness of females can be estimated by counting the number of seeds they produce. Determination of fitness for males has been made easier as thousands of genetic markers can now be used to assign paternity to seeds. We undertook just such a study in S. latifolia, a short-lived, herbaceous plant. We identified loci under sex-specific selection in this species and found more loci affecting fitness in males than females. Importantly, loci with major effects on male fitness were distinct from the loci with major effects on females. We detected sexual antagonism only when considering the aggregate effect of many loci. Hence, even though males and females share the same genome, this does not necessarily impose a constraint on their independent evolution. 

Gene expression can be influenced by genetic variants that are closely linked to the expressed gene (cis eQTLs) and variants in other parts of the genome (trans eQTLs). We created a multiparental mapping population by sampling genotypes from a single natural population ofMimulus guttatusand scored gene expression in the leaves of 1,588 plants. We find that nearly every measured gene exhibits cis regulatory variation (91% have FDR < 0.05). cis eQTLs are usually allelic series with three or more functionally distinct alleles. The cis locus explains about two thirds of the standing genetic variance (on average) but varies among genes and tends to be greatest when there is high indel variation in the upstream regulatory region and high nucleotide diversity in the coding sequence. Despite mapping over 10,000 trans eQTL / affected gene pairs, most of the genetic variance generated by trans acting loci remains unexplained. This implies a large reservoir of trans acting genes with subtle or diffuse effects. Mapped trans eQTLs show lower allelic diversity but much higher genetic dominance than cis eQTLs. Several analyses also indicate that trans eQTLs make a substantial contribution to the genetic correlations in expression among different genes. They may thus be essential determinants of “gene expression modules,” which has important implications for the evolution of gene expression and how it is studied by geneticists. 

This article is a Commentary onAcoca‐Pidolleet al. (2024),242: 717–726. 

Introduction:Heavy metal pollutants can have long lasting negative impacts on ecosystem health and can shape the evolution of species. The persistent and ubiquitous nature of heavy metal pollution provides an opportunity to characterize the genetic mechanisms that contribute to metal resistance in natural populations. Methods:We examined variation in resistance to copper, a common heavy metal contaminant, using wild collections of the model organismDrosophila melanogaster. Flies were collected from multiple sites that varied in copper contamination risk. We characterized phenotypic variation in copper resistance within and among populations using bulked segregant analysis to identify regions of the genome that contribute to copper resistance. Results and Discussion:Copper resistance varied among wild populations with a clear correspondence between resistance level and historical exposure to copper. We identified 288 SNPs distributed across the genome associated with copper resistance. Many SNPs had population-specific effects, but some had consistent effects on copper resistance in all populations. Significant SNPs map to several novel candidate genes involved in refolding disrupted proteins, energy production, and mitochondrial function. We also identified one SNP with consistent effects on copper resistance in all populations nearCG11825, a gene involved in copper homeostasis and copper resistance. We compared the genetic signatures of copper resistance in the wild-derived populations to genetic control of copper resistance in theDrosophilaSynthetic Population Resource (DSPR) and theDrosophilaGenetic Reference Panel (DGRP), two copper-naïve laboratory populations. In addition toCG11825, which was identified as a candidate gene in the wild-derived populations and previously in the DSPR, there was modest overlap of copper-associated SNPs between the wild-derived populations and laboratory populations. Thirty-one SNPs associated with copper resistance in wild-derived populations fell within regions of the genome that were associated with copper resistance in the DSPR in a prior study. Collectively, our results demonstrate that the genetic control of copper resistance is highly polygenic, and that several loci can be clearly linked to genes involved in heavy metal toxicity response. The mixture of parallel and population-specific SNPs points to a complex interplay between genetic background and the selection regime that modifies the effects of genetic variation on copper resistance. 

Selection component analyses (SCA) relate individual genotype to fitness components such as viability, fecundity and mating success. SCA are based on population genetic models and yield selection estimates directly in terms of predicted allele frequency change. This paper explores the statistical properties of gSCA: experiments that apply SCA to genome-wide scoring of SNPs in field sampled individuals. Computer simulations indicate that gSCA involving a few thousand genotyped samples can detect allele frequency changes of the magnitude that has been documented in field experiments on diverse taxa. To detect selection, imprecise genotyping from low-level sequencing of large samples of individuals provides much greater power than precise genotyping of smaller samples. The simulations also demonstrate the efficacy of ‘haplotype matching’, a method to combine information from a limited collection of whole genome sequence (the reference panel) with the much larger sample of field individuals that are measured for fitness. Pooled sequencing is demonstrated as another way to increase statistical power. Finally, I discuss the interpretation of selection estimates in relation to the Beavis effect, the overestimation of selection intensities at significant loci.