The quantitative genetics of gene expression in Mimulus guttatus.

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 of Mimulus guttatus and 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.

The quantitative genetics of gene expression in Mimulus guttatus.

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 of Mimulus guttatus and 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) and that 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 eQTL 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 also how it is studied by geneticists.

A few essential genetic loci distinguish Penstemon species with flowers adapted to pollination by bees or hummingbirds.

In the formation of species, adaptation by natural selection generates distinct combinations of traits that function well together. The maintenance of adaptive trait combinations in the face of gene flow depends on the strength and nature of selection acting on the underlying genetic loci. Floral pollination syndromes exemplify the evolution of trait combinations adaptive for particular pollinators. The North American wildflower genus Penstemon displays remarkable floral syndrome convergence, with at least 20 separate lineages that have evolved from ancestral bee pollination syndrome (wide blue-purple flowers that present a landing platform for bees and small amounts of nectar) to hummingbird pollination syndrome (bright red narrowly tubular flowers offering copious nectar). Related taxa that differ in floral syndrome offer an attractive opportunity to examine the genomic basis of complex trait divergence. In this study, we characterized genomic divergence among 229 individuals from a Penstemon species complex that includes both bee and hummingbird floral syndromes. Field plants are easily classified into species based on phenotypic differences and hybrids displaying intermediate floral syndromes are rare. Despite unambiguous phenotypic differences, genome-wide differentiation between species is minimal. Hummingbird-adapted populations are more genetically similar to nearby bee-adapted populations than to geographically distant hummingbird-adapted populations, in terms of genome-wide dXY. However, a small number of genetic loci are strongly differentiated between species. These approximately 20 "species-diagnostic loci," which appear to have nearly fixed differences between pollination syndromes, are sprinkled throughout the genome in high recombination regions. Several map closely to previously established floral trait quantitative trait loci (QTLs). The striking difference between the diagnostic loci and the genome as whole suggests strong selection to maintain distinct combinations of traits, but with sufficient gene flow to homogenize the genomic background. A surprisingly small number of alleles confer phenotypic differences that form the basis of species identity in this species complex.

The genetic basis of adaptation to copper pollution in Drosophila melanogaster.

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 organism Drosophila 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 near CG11825, 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 the Drosophila Synthetic Population Resource (DSPR) and the Drosophila Genetic Reference Panel (DGRP), two copper-naïve laboratory populations. In addition to CG11825, 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.

The genomic scale of fluctuating selection in a natural plant population.

This study characterizes evolution at ≈1.86 million Single Nucleotide Polymorphisms (SNPs) within a natural population of yellow monkeyflower (Mimulus guttatus). Most SNPs exhibit minimal change over a span of 23 generations (less than 1% per year), consistent with neutral evolution in a large population. However, several thousand SNPs display strong fluctuations in frequency. Multiple lines of evidence indicate that these 'Fluctuating SNPs' are driven by temporally varying selection. Unlinked loci exhibit synchronous changes with the same allele increasing consistently in certain time intervals but declining in others. This synchrony is sufficiently pronounced that we can roughly classify intervals into two categories, "green" and "yellow," corresponding to conflicting selection regimes. Alleles increasing in green intervals are associated with early life investment in vegetative tissue and delayed flowering. The alternative alleles that increase in yellow intervals are associated with rapid progression to flowering. Selection on the Fluctuating SNPs produces a strong ripple effect on variation across the genome. Accounting for estimation error, we estimate the distribution of allele frequency change per generation in this population. While change is minimal for most SNPs, diffuse hitchhiking effects generated by selected loci may be driving neutral SNPs to a much greater extent than classic genetic drift.

Sex-specific natural selection on SNPs in Silene latifolia.

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.

Pollinator loss causes rapid adaptive evolution of selfing and dramatically reduces genome-wide genetic variability.

Although selfing populations harbor little genetic variation limiting evolutionary potential, the causes are unclear. We experimentally evolved large, replicate populations of Mimulus guttatus for nine generations in greenhouses with or without pollinating bees and studied DNA polymorphism in descendants. Populations without bees adapted to produce more selfed seed yet exhibited striking reductions in DNA polymorphism despite large population sizes. Importantly, the genome-wide pattern of variation cannot be explained by a simple reduction in effective population size, but instead reflects the complicated interaction between selection, linkage, and inbreeding. Simulations demonstrate that the spread of favored alleles at few loci depresses neutral variation genome wide in large populations containing fully selfing lineages. It also generates greater heterogeneity among chromosomes than expected with neutral evolution in small populations. Genome-wide deviations from neutrality were documented in populations with bees, suggesting widespread influences of background selection. After applying outlier tests to detect loci under selection, two genome regions were found in populations with bees, yet no adaptive loci were otherwise mapped. Large amounts of stochastic change in selfing populations compromise evolutionary potential and undermine outlier tests for selection. This occurs because genetic draft in highly selfing populations makes even the largest changes in allele frequency unremarkable.

Multiplexed shotgun genotyping (MSG) data resolve phylogenetic relationships within and among archipelagos in Macaronesian Tolpis.

PREMISE: Plants endemic to oceanic archipelagos are suitable for studying evolution, being isolated on substrates of different ages. Evolution has been recent, rendering traditionally employed sequences insufficiently variable for resolving relationships. This study includes sampling in the genus Tolpis (Asteraceae) from the Azores, Madeira, and Cape Verde, and expands upon an earlier study demonstrating the efficacy of multiplexed shotgun genotyping (MSG) for resolving relationships in Canarian Tolpis. METHODS: Genomic libraries for 90 accessions of Tolpis and two from the outgroup were generated for genotyping individuals using MSG. Loci were de novo assembled with iPyrad, which clusters MSG loci within and between samples. A maximum likelihood phylogeny was generated with RAxML. Ancestral area reconstruction was inferred using R package BioGeoBEARS. RESULTS: MSG data recovered a highly resolved phylogeny from population to inter-archipelago levels. Ancestral area reconstruction provided biogeographic hypotheses for the radiation of Macaronesian Tolpis. CONCLUSIONS: Four major clades were resolved. The Madeiran endemic T. macrorhiza is sister to other Tolpis. Species from the Canaries, Cape Verdes, and the continent are sister to T. succulenta from Madeira, which has a sister subclade of Azorean populations composed of T. succulenta and T. azorica. Population-level resolution suggests unrecognized taxa on several archipelagos. Ancestral reconstruction suggests initial dispersal from the continent to Madeira, with dispersal to the Azores, then dispersal from Madeira to the Canary Islands, with both subsequent dispersal to the Cape Verdes and back-dispersal to the continent. Single-island radiations and inter-island dispersal are implicated in divergence in Macaronesian Tolpis.

Genome-wide association mapping of transcriptome variation in Mimulus guttatus indicates differing patterns of selection on cis- versus trans-acting mutations.

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.

The promise and deceit of genomic selection component analyses.

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.

Predicting evolutionary change at the DNA level in a natural Mimulus population.

Evolution by natural selection occurs when the frequencies of genetic variants change because individuals differ in Darwinian fitness components such as survival or reproductive success. Differential fitness has been demonstrated in field studies of many organisms, but it remains unclear how well we can quantitatively predict allele frequency changes from fitness measurements. Here, we characterize natural selection on millions of Single Nucleotide Polymorphisms (SNPs) across the genome of the annual plant Mimulus guttatus. We use fitness estimates to calibrate population genetic models that effectively predict allele frequency changes into the next generation. Hundreds of SNPs experienced "male selection" in 2013 with one allele at each SNP elevated in frequency among successful male gametes relative to the entire population of adults. In the following generation, allele frequencies at these SNPs consistently shifted in the predicted direction. A second year of study revealed that SNPs had effects on both viability and reproductive success with pervasive trade-offs between fitness components. SNPs favored by male selection were, on average, detrimental to survival. These trade-offs (antagonistic pleiotropy and temporal fluctuations in fitness) may be essential to the long-term maintenance of alleles. Despite the challenges of measuring selection in the wild, the strong correlation between predicted and observed allele frequency changes suggests that population genetic models have a much greater role to play in forward-time prediction of evolutionary change.

Genome-wide genotyping estimates mating system parameters and paternity in the island species Tolpis succulenta.

PREMISE: The mating system has profound consequences, not only for ecology and evolution, but also for the conservation of threatened or endangered species. Unfortunately, small populations are difficult to study owing to limits on sample size and genetic marker diversity. Here, we estimated mating system parameters in three small populations of an island plant using genomic genotyping. Although self-incompatible (SI) species are known to often set some self-seed, little is known about how "leaky SI" affects selfing rates in nature or the role that multiple paternity plays in small populations. METHODS: We generalized the BORICE mating system program to determine the siring pattern within maternal families. We applied this algorithm to maternal families from three populations of Tolpis succulenta from Madeira Island and genotyped the progeny using RADseq. We applied BORICE to estimate each individual offspring as outcrossed or selfed, the paternity of each outcrossed offspring, and the level of inbreeding of each maternal plant. RESULTS: Despite a functional self-incompatibility system, these data establish T. succulenta as a pseudo-self-compatible (PSC) species. Two of 75 offspring were strongly indicated as products of self-fertilization. Despite selfing, all adult maternal plants were fully outbred. There was high differentiation among and low variation within populations, consistent with a history of genetic isolation of these small populations. There were generally multiple sires per maternal family. Twenty-two percent of sib contrasts (between outcrossed offspring within maternal families) shared the same sire. CONCLUSIONS: Genome-wide genotyping, combined with appropriate analytical methods, enables estimation of mating system and multiple paternity in small populations. These data address questions about the evolution of reproductive traits and the conservation of threatened populations.

How rapidly do self-compatible populations evolve selfing? Mating system estimation within recently evolved self-compatible populations of Azorean Tolpis succulenta (Asteraceae).

Genome-wide genotyping and Bayesian inference method (BORICE) were employed to estimate outcrossing rates and paternity in two small plant populations of Tolpis succulenta (Asteraceae) on Graciosa island in the Azores. These two known extant populations of T. succulenta on Graciosa have recently evolved self-compatibility. Despite the expectation that selfing would occur at an appreciable rate (self-incompatible populations of the same species show low but nonzero selfing), high outcrossing was found in progeny arrays from maternal plants in both populations. This is inconsistent with an immediate transition to high selfing following the breakdown of a genetic incompatibility system. This finding is surprising given the small population sizes and the recent colonization of an island from self-incompatible colonists of T. succulenta from another island in the Azores, and a potential paucity of pollinators, all factors selecting for selfing through reproductive assurance. The self-compatible lineage(s) likely have high inbreeding depression (ID) that effectively halts the evolution of increased selfing, but this remains to be determined. Like their progeny, all maternal plants in both populations are fully outbred, which is consistent with but not proof of high ID. High multiple paternity was found in both populations, which may be due in part to the abundant pollinators observed during the flowering season.

Individualized mating system estimation using genomic data.

The estimation of outcrossing rates in hermaphroditic species has been a major focus in the evolutionary study of reproductive strategies, and is also essential for plant breeding and conservation. Surprisingly, genomics has thus far minimally influenced outcrossing rate studies. In this article, we generalize a Bayesian inference method (BORICE) to accommodate genomic data from multiple subpopulations of a species. As an empirical demonstration, BORICE is applied to 115 maternal families of Mimulus guttatus. The analysis shows that low-level whole genome sequencing of parents and offspring is sufficient for individualized mating system estimation: 208 offspring (88.5%) were definitively called as outcrossed, 23 (9.8%) as selfed. After mating system parameters are established (each offspring as outcrossed or selfed and the inbreeding level of maternal plants), BORICE outputs posterior genotype probabilities for each SNP genomewide. Individual SNP calls are often burdened with considerable uncertainty and distilling information from closely linked sites (within genomic windows) can be a useful strategy. For the Mimulus data, principal components based on window statistics were sufficient to diagnose inversion polymorphisms and estimate their effects on spatial structure, phenotypic and fitness measures. More generally, mating system estimation with BORICE can set the stage for population and quantitative genomic analyses, particularly researchers collect phenotypic or fitness data from maternal individuals.

Severe inbreeding depression is predicted by the "rare allele load" in Mimulus guttatus.

Most flowering plants are hermaphroditic and experience strong pressures to evolve self-pollination (automatic selection and reproductive assurance). Inbreeding depression (ID) can oppose selection for selfing, but it remains unclear if ID is typically strong enough to maintain outcrossing. To measure the full cost of sustained inbreeding on fitness, and its genomic basis, we planted highly homozygous, fully genome-sequenced inbred lines of yellow monkeyflower (Mimulus guttatus) in the field next to outbred plants from crosses between the same lines. The cost of full homozygosity is severe: 65% for survival and 86% for lifetime seed production. Accounting for the unmeasured effect of lethal and sterile mutations, we estimate that the average fitness of fully inbred genotypes is only 3-4% that of outbred competitors. The genome sequence data provide no indication of simple overdominance, but the number of rare alleles carried by a line, especially within rare allele clusters nonrandomly distributed across the genome, is a significant negative predictor of fitness measurements. These findings are consistent with a deleterious allele model for ID. High variance in rare allele load among lines and the genomic distribution of rare alleles both suggest that migration might be an important source of deleterious alleles to local populations.

Quantitative Genetic Mapping and Genome Assembly in the Lesser Wax Moth Achroia grisella.

Specific characteristics of the male Achroia grisella acoustic mating signal determine a male's attractiveness toward females. These features are genetically variable in populations, and mapping experiments have been used to identify loci contributing to song variation, and understand the evolutionary forces acting on this important sexual trait. Here we built on this foundation and carried out QTL (Quantitative Trait Locus) mapping using >1,000 recombinant individuals, genotyping this large cohort at thousands of sequence-based markers covering the entire collection of 30 A. grisella chromosomes. This dense marker set, coupled with our development of an annotated, draft genome of A. grisella, allowed us to link >3,000 genome scaffolds, >10,000 predicted genes, and close to 275Mb of genome sequence to chromosomes. Our QTL mapping confirmed a fraction of the QTL identified in a previous study, and additionally revealed novel loci. Collectively, QTL explained only small fractions of the phenotypic variance, suggesting many more causative factors remain below the detection threshold of our study. A surprising, and ultimately challenging feature of our study was the low level of intrachromosomal recombination present in our mapping population. This led to difficulty ordering markers along linkage groups, necessitating a chromosome-by-chromosome mapping approach, rather than true interval mapping, and precluded confident ordering/orienting of scaffolds along each chromosome. Nonetheless, our study increased the genomic resources available for the A. grisella system. Enabled by ever more powerful technologies, future investigators will be able to leverage our data to provide more detailed genetic dissection of male song variation in A. grisella.

GOOGA: A platform to synthesize mapping experiments and identify genomic structural diversity.

Understanding genomic structural variation such as inversions and translocations is a key challenge in evolutionary genetics. We develop a novel statistical approach to comparative genetic mapping to detect large-scale structural mutations from low-level sequencing data. The procedure, called Genome Order Optimization by Genetic Algorithm (GOOGA), couples a Hidden Markov Model with a Genetic Algorithm to analyze data from genetic mapping populations. We demonstrate the method using both simulated data (calibrated from experiments on Drosophila melanogaster) and real data from five distinct crosses within the flowering plant genus Mimulus. Application of GOOGA to the Mimulus data corrects numerous errors (misplaced sequences) in the M. guttatus reference genome and confirms or detects eight large inversions polymorphic within the species complex. Finally, we show how this method can be applied in genomic scans to improve the accuracy and resolution of Quantitative Trait Locus (QTL) mapping.

Extreme copy number variation at a tRNA ligase gene affecting phenology and fitness in yellow monkeyflowers.

Copy number variation (CNV) is a major part of the genetic diversity segregating within populations, but remains poorly understood relative to single nucleotide variation. Here, we report on a tRNA ligase gene (Migut.N02091; RLG1a) exhibiting unprecedented, and fitness-relevant, CNV within an annual population of the yellow monkeyflower Mimulus guttatus. RLG1a variation was associated with multiple traits in pooled population sequencing (PoolSeq) scans of phenotypic and phenological cohorts. Resequencing of inbred lines revealed intermediate-frequency three-copy variants of RLG1a (trip+; 5/35 = 14%), and trip+ lines exhibited elevated RLG1a expression under multiple conditions. trip+ carriers, in addition to being over-represented in late-flowering and large-flowered PoolSeq populations, flowered later under stressful conditions in a greenhouse experiment (p < 0.05). In wild population samples, we discovered an additional rare RLG1a variant (high+) that carries 250-300 copies of RLG1a totalling ~5.7 Mb (20-40% of a chromosome). In the progeny of a high+ carrier, Mendelian segregation of diagnostic alleles and qPCR-based copy counts indicate that high+ is a single tandem array unlinked to the single-copy RLG1a locus. In the wild, high+ carriers had highest fitness in two particularly dry and/or hot years (2015 and 2017; both p < 0.01), while single-copy individuals were twice as fecund as either CNV type in a lush year (2016: p < 0.005). Our results demonstrate fluctuating selection on CNVs affecting phenological traits in a wild population, suggest that plant tRNA ligases mediate stress-responsive life-history traits, and introduce a novel system for investigating the molecular mechanisms of gene amplification.