Understanding quantitative genetic variation

Exome-wide comparative analyses revealed differentiating genomic regions for performance traits in Indian native buffaloes

In India, 20 breeds of buffalo have been identified and registered, yet limited studies have been conducted to explore the performance potential of these breeds, especially in the Indian native breeds. This study is a maiden attempt to delineate the important variants and unique genes through exome sequencing for milk yield, milk composition, fertility, and adaptation traits in Indian local breeds of buffalo. In the present study, whole exome sequencing was performed on Chhattisgarhi (n = 3), Chilika (n = 4), Gojri (n = 3), and Murrah (n = 4) buffalo breeds and after stringent quality control, 4333, 6829, 4130, and 4854 InDels were revealed, respectively. Exome-wide FST along 100-kb sliding windows detected 27, 98, 38, and 35 outlier windows in Chhattisgarhi, Chilika, Gojri, and Murrah, respectively. The comparative exome analysis of InDels and subsequent gene ontology revealed unique breed specific genes for milk yield (CAMSAP3), milk composition (CLCN1, NUDT3), fertility (PTGER3) and adaptation (KCNA3, TH) traits. Study provides insight into mechanism of how these breeds have evolved under natural selection, the impact of these events on their respective genomes, and their importance in maintaining purity of these breeds for the traits under study. Additionally, this result will underwrite to the genetic acquaintance of these breeds for breeding application, and in understanding of evolution of these Indian local breeds.

Polygenic dynamics underlying the response of quantitative traits to directional selection

We study the response of a quantitative trait to exponential directional selection in a finite haploid population, both at the genetic and the phenotypic level. We assume an infinite sites model, in which the number of new mutations per generation in the population follows a Poisson distribution (with mean Θ) and each mutation occurs at a new, previously monomorphic site. Mutation effects are beneficial and drawn from a distribution. Sites are unlinked and contribute additively to the trait. Assuming that selection is stronger than random genetic drift, we model the initial phase of the dynamics by a supercritical Galton-Watson process. This enables us to obtain time-dependent results. We show that the copy-number distribution of the mutant in generation n, conditioned on non-extinction until n, is described accurately by the deterministic increase from an initial distribution with mean 1. This distribution is related to the absolutely continuous part W+ of the random variable, typically denoted W, that characterizes the stochasticity accumulating during the mutant's sweep. A suitable transformation yields the approximate dynamics of the mutant frequency distribution in a Wright-Fisher population of size N. Our expression provides a very accurate approximation except when mutant frequencies are close to 1. On this basis, we derive explicitly the (approximate) time dependence of the expected mean and variance of the trait and of the expected number of segregating sites. Unexpectedly, we obtain highly accurate approximations for all times, even for the quasi-stationary phase when the expected per-generation response and the trait variance have equilibrated. The latter refine classical results. In addition, we find that Θ is the main determinant of the pattern of adaptation at the genetic level, i.e., whether the initial allele-frequency dynamics are best described by sweep-like patterns at few loci or small allele-frequency shifts at many. The number of segregating sites is an appropriate indicator for these patterns. The selection strength determines primarily the rate of adaptation. The accuracy of our results is tested by comprehensive simulations in a Wright-Fisher framework. We argue that our results apply to more complex forms of directional selection.

Genetic variation and association of yield, yield components, and carbon storage in sorghum (Sorghum bicolor [L.] Moench) genotypes

Trait heritability and the response to selection depend on genetic variation, a prerequisite to developing sorghum varieties with desirable agronomic traits and high carbon sequestration for sustainable crop production and soil health. The present study aimed to assess the extent of genetic variability and associations among agronomic and carbon storage traits in selected sorghum genotypes to identify the best candidates for production or breeding. Fifty genotypes were evaluated at Ukulinga, Bethlehem and Silverton sites in South Africa during the 2022/23 growing season. The following agronomic and carbon storage traits were collected: days to 50% heading (DTH), days to 50% maturity (DTM), plant height (PH), total plant biomass (PB), shoot biomass (SB), root biomass (RB), root-to-shoot biomass ratio (RS), grain yield (GY), harvest index (HI), shoot carbon content (SCc), root carbon content (RCc), grain carbon content (GCc), total plant carbon stock (PCs), shoot carbon stock (SCs), root carbon stock (RCs), and root-to-shoot carbon stock ratio (RCs/SCs), and grain carbon stock (GCs). Higher genotypic coefficient of variations (GCVs) were recorded for GY at 45.92%, RB (39.24%), RCs/SCs (38.45), and RCs (34.62). Higher phenotypic coefficient of variations (PCVs) were recorded for PH (68.91%), followed by GY (51.8%), RB (50.51%), RS (41.96%), RCs/SCs (44.90%), and GCs (41.90%). High broad-sense heritability and genetic advance were recorded for HI (83.76 and 24.53%), GY (78.59 and 9.98%), PB (74.14 and 13.18%) and PCs (53.63 and 37.57%), respectively, suggesting a marked genetic contribution to the traits. Grain yield exhibited positive association with HI (r = 0.76; r = 0.79), DTH (r = 0.13; r = 0.31), PH (r = 0.1; r = 0.27), PB (r = 0.01; r = 0.02), RB (r = 0.05; r = 0.06) based on genotypic and phenotypic correlations, respectively. Further, the path analysis revealed significant positive direct effects of SB (0.607) and RB (0.456) on GY. The RS exerted a positive and significant indirect effect (0.229) on grain yield through SB. The study revealed that PB, SB, RB, RS, RCs, and RCs/SCs are the principal traits when selecting sorghum genotypes with high yield and carbon storage capacity.

Meta-analytical evidence for frequency-dependent selection across the tree of life

Explaining the maintenance of genetic variation in fitness-related traits within populations is a fundamental challenge in ecology and evolutionary biology. Frequency-dependent selection (FDS) is one mechanism that can maintain such variation, especially when selection favours rare variants (negative FDS). However, our general knowledge about the occurrence of FDS, its strength and direction remain fragmented, limiting general inferences about this important evolutionary process. We systematically reviewed the published literature on FDS and assembled a database of 747 effect sizes from 101 studies to analyse the occurrence, strength, and direction of FDS, and the factors that could explain heterogeneity in FDS. Using a meta-analysis, we found that overall, FDS is more commonly negative, although not significantly when accounting for phylogeny. An analysis of absolute values of effect sizes, however, revealed the widespread occurrence of modest FDS. However, negative FDS was only significant in laboratory experiments and non-significant in mesocosms and field-based studies. Moreover, negative FDS was stronger in studies measuring fecundity and involving resource competition over studies using other fitness components or focused on other ecological interactions. Our study unveils key general patterns of FDS and points in future promising research directions that can help us understand a long-standing fundamental problem in evolutionary biology and its consequences for demography and ecological dynamics.

Evolution of parasites in the Anthropocene: new pressures, new adaptive directions

The Anthropocene is seeing the human footprint rapidly spreading to all of Earth's ecosystems. The fast-changing biotic and abiotic conditions experienced by all organisms are exerting new and strong selective pressures, and there is a growing list of examples of human-induced evolution in response to anthropogenic impacts. No organism is exempt from these novel selective pressures. Here, we synthesise current knowledge on human-induced evolution in eukaryotic parasites of animals, and present a multidisciplinary framework for its study and monitoring. Parasites generally have short generation times and huge fecundity, features that predispose them for rapid evolution. We begin by reviewing evidence that parasites often have substantial standing genetic variation, and examples of their rapid evolution both under conditions of livestock production and in serial passage experiments. We then present a two-step conceptual overview of the causal chain linking anthropogenic impacts to parasite evolution. First, we review the major anthropogenic factors impacting parasites, and identify the selective pressures they exert on parasites through increased mortality of either infective stages or adult parasites, or through changes in host density, quality or immunity. Second, we discuss what new phenotypic traits are likely to be favoured by the new selective pressures resulting from altered parasite mortality or host changes; we focus mostly on parasite virulence and basic life-history traits, as these most directly influence the transmission success of parasites and the pathology they induce. To illustrate the kinds of evolutionary changes in parasites anticipated in the Anthropocene, we present a few scenarios, either already documented or hypothetical but plausible, involving parasite taxa in livestock, aquaculture and natural systems. Finally, we offer several approaches for investigations and real-time monitoring of rapid, human-induced evolution in parasites, ranging from controlled experiments to the use of state-of-the-art genomic tools. The implications of fast-evolving parasites in the Anthropocene for disease emergence and the dynamics of infections in domestic animals and wildlife are concerning. Broader recognition that it is not only the conditions for parasite transmission that are changing, but the parasites themselves, is needed to meet better the challenges ahead.

Overexpression of Liriodendron Hybrid LhGLK1 in Arabidopsis Leads to Excessive Chlorophyll Synthesis and Improved Growth

Chloroplasts is the site for photosynthesis, which is the main primary source of energy for plants. Golden2-like (GLK) is a key transcription factor that regulates chloroplast development and chlorophyll synthesis. However, most studies on GLK genes are performed in crops and model plants with less attention to woody plants. In this study, we identified the LhGLK1 and LhGLK2 genes in the woody plant Liriodendron hybrid, and they are specifically expressed in green tissues. We showed that overexpression of the LhGLK1 gene improves rosette leaf chlorophyll content and induces ectopic chlorophyll biogenesis in primary root and petal vascular tissue in Arabidopsis. Although these exhibit a late-flowering phenotype, transgenic lines accumulate more biomass in vegetative growth with improved photochemical quenching (qP) and efficiency of photosystem II. Taken together, we verified a conserved and ancient mechanism for regulating chloroplast biogenesis in Liriodendron hybrid and evaluated its effect on photosynthesis and rosette biomass accumulation in the model plant Arabidopsis.

Evolutionary computing to assemble standing genetic diversity and achieve long-term genetic gain

Loss of genetic diversity in elite crop breeding pools can severely limit long-term genetic gains and limit ability to make gains in new traits, like heat tolerance, that are becoming important as the climate changes. Here, we investigate and propose potential breeding program applications of optimal haplotype stacking (OHS), a selection method that retains useful diversity in the population. OHS selects sets of candidates containing, between them, haplotype segments with very high segment breeding values for the target trait. We compared the performance of OHS, a similar method called optimal population value (OPV), truncation selection on genomic estimated breeding values (GEBVs), and optimal contribution selection (OCS) in stochastic simulations of recurrent selection on founder wheat genotypes. After 100 generations of intercrossing and selection, OCS and truncation selection had exhausted the genetic diversity, while considerable diversity remained in the OHS population. Gain under OHS in these simulations ultimately exceeded that from truncation selection or OCS. OHS achieved faster gains when the population size was small, with many progeny per cross. A promising hybrid strategy, involving a single cycle of OHS in the first generation followed by recurrent truncation selection, substantially improved long-term gain compared with truncation selection and performed similarly to OCS. The results of this study provide initial insights into where OHS could be incorporated into breeding programs.

The genetic basis of variation in Drosophila melanogaster mating behavior

Mating behavior is an essential fitness trait. We used the inbred, sequenced lines of the Drosophila Genetic Reference Panel (DGRP) to gain insights into the evolution of mating success and to evaluate the overlap in genetic architecture of mating behavior between the sexes. We found significant genetic variation for mating success when DGRP males and females from the same line were mated together, and when DGRP males and females were mated to an unrelated strain of the opposite sex. The mating success of DGRP males and females was not correlated when they were paired with the unrelated strain, suggesting independent genetic architecture of mating success in males and females that was confirmed by genome-wide association analyses. However, the mating success between pairs of the same or different DGRP lines was predicted accurately by the respective female and male mating success with the unrelated line.

Genetic insight into a polygenic trait using a novel genome-wide association approach in a wild amphibian population

Body size variation is central in the evolution of life-history traits in amphibians, but the underlying genetic architecture of this complex trait is still largely unknown. Herein, we studied the genetic basis of body size and fecundity of the alternative morphotypes in a wild population of the Greek smooth newt (Lissotriton graecus). By combining a genome-wide association approach with linkage disequilibrium network analysis, we were able to identify clusters of highly correlated loci thus maximizing sequence data for downstream analysis. The putatively associated variants explained 12.8% to 44.5% of the total phenotypic variation in body size and were mapped to genes with functional roles in the regulation of gene expression and cell cycle processes. Our study is the first to provide insights into the genetic basis of complex traits in newts and provides a useful tool to identify loci potentially involved in fitness-related traits in small data sets from natural populations in non-model species.

Evolution of Phenotypic Variance Provides Insights into the Genetic Basis of Adaptation

Most traits are polygenic, and the contributing loci can be identified by genome-wide association studies. The genetic basis of adaptation (adaptive architecture) is, however, difficult to characterize. Here, we propose to study the adaptive architecture of traits by monitoring the evolution of their phenotypic variance during adaptation to a new environment in well-defined laboratory conditions. Extensive computer simulations show that the evolution of phenotypic variance in a replicated experimental evolution setting can distinguish between oligogenic and polygenic adaptive architectures. We compared gene expression variance in male Drosophila simulans before and after 100 generations of adaptation to a novel hot environment. The variance change in gene expression was indistinguishable for genes with and without a significant change in mean expression after 100 generations of evolution. We suggest that the majority of adaptive gene expression evolution can be explained by a polygenic architecture. We propose that tracking the evolution of phenotypic variance across generations can provide an approach to characterize the adaptive architecture.

Dominance reversals: the resolution of genetic conflict and maintenance of genetic variation

Beneficial reversals of dominance reduce the costs of genetic trade-offs and can enable selection to maintain genetic variation for fitness. Beneficial dominance reversals are characterized by the beneficial allele for a given context (e.g. habitat, developmental stage, trait or sex) being dominant in that context but recessive where deleterious. This context dependence at least partially mitigates the fitness consequence of heterozygotes carrying one non-beneficial allele for their context and can result in balancing selection that maintains alternative alleles. Dominance reversals are theoretically plausible and are supported by mounting empirical evidence. Here, we highlight the importance of beneficial dominance reversals as a mechanism for the mitigation of genetic conflict and review the theory and empirical evidence for them. We identify some areas in need of further research and development and outline three methods that could facilitate the identification of antagonistic genetic variation (dominance ordination, allele-specific expression and allele-specific ATAC-Seq (assay for transposase-accessible chromatin with sequencing)). There is ample scope for the development of new empirical methods as well as reanalysis of existing data through the lens of dominance reversals. A greater focus on this topic will expand our understanding of the mechanisms that resolve genetic conflict and whether they maintain genetic variation.

Genetic architecture of ecological divergence between Oryza rufipogon and Oryza nivara

Ecological divergence due to habitat difference plays a prominent role in the formation of new species, but the genetic architecture during ecological speciation and the mechanism underlying phenotypic divergence remain less understood. Two wild ancestors of rice (Oryza rufipogon and Oryza nivara) are a progenitor-derivative species pair with ecological divergence and provide a unique system for studying ecological adaptation/speciation. Here, we constructed a high-resolution linkage map and conducted a quantitative trait locus (QTL) analysis of 19 phenotypic traits using an F2 population generated from a cross between the two Oryza species. We identified 113 QTLs associated with interspecific divergence of 16 quantitative traits, with effect sizes ranging from 1.61% to 34.1% in terms of the percentage of variation explained (PVE). The distribution of effect sizes of QTLs followed a negative exponential, suggesting that a few genes of large effect and many genes of small effect were responsible for the phenotypic divergence. We observed 18 clusters of QTLs (QTL hotspots) on 11 chromosomes, significantly more than that expected by chance, demonstrating the importance of coinheritance of loci/genes in ecological adaptation/speciation. Analysis of effect direction and v-test statistics revealed that interspecific differentiation of most traits was driven by divergent natural selection, supporting the argument that ecological adaptation/speciation would proceed rapidly under coordinated selection on multiple traits. Our findings provide new insights into the understanding of genetic architecture of ecological adaptation and speciation in plants and help effective manipulation of specific genes or gene cluster in rice breeding.

Comparing the Predicted versus Realized Rate of Adaptation of Chamaecrista fasciculata to Climate Change

AbstractFisher's fundamental theorem of natural selection (FTNS) can be used in a quantitative genetics framework to predict the rate of adaptation in populations. Here, we estimated the capacity for a wild population of the annual legume Chamaecrista fasciculata to adapt to future environments and compared predicted and realized rates of adaptation. We planted pedigreed seeds from one population into three prairie reconstructions along an east-to-west decreasing precipitation gradient. The FTNS predicted adaptation at all sites, but we found a response to selection that was smaller at the home and westernmost sites and maladaptive at the middle site because of changes in the selective environment between generations. However, mean fitness of the progeny generation at the home and westernmost sites exceeded population replacement, which suggests that the environment was sufficiently favorable to promote population persistence. More studies employing the FTNS are needed to clarify the degree to which predictions of the rate of adaptation are realized and its utility in the conservation of populations at risk of extinction from climate change.

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts that adaptation is due to a few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and using RAD-seq genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that one to two large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling. One QTL locus was shared across all populations and another was shared across three populations. One QTL locus showed strong signatures of recent natural selection in the corresponding wild population but another QTL locus did not. Some candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Causal interpretations of family GWAS in the presence of heterogeneous effects

Family-based genome-wide association studies (GWAS) have emerged as a gold standard for assessing causal effects of alleles and polygenic scores. Notably, family studies are often claimed to provide an unbiased estimate of the average causal effect (or average treatment effect; ATE) of an allele, on the basis of an analogy between the random transmission of alleles from parents to children and a randomized controlled trial. Here, we show that this interpretation does not hold in general. Because Mendelian segregation only randomizes alleles among children of heterozygotes, the effects of alleles in the children of homozygotes are not observable. Consequently, if an allele has different average effects in the children of homozygotes and heterozygotes, as can arise in the presence of gene-by-environment interactions, gene-by-gene interactions, or differences in LD patterns, family studies provide a biased estimate of the average effect in the sample. At a single locus, family-based association studies can be thought of as providing an unbiased estimate of the average effect in the children of heterozygotes (i.e., a local average treatment effect; LATE). This interpretation does not extend to polygenic scores, however, because different sets of SNPs are heterozygous in each family. Therefore, other than under specific conditions, the within-family regression slope of a PGS cannot be assumed to provide an unbiased estimate for any subset or weighted average of families. Instead, family-based studies can be reinterpreted as enabling an unbiased estimate of the extent to which Mendelian segregation at loci in the PGS contributes to the population-level variance in the trait. Because this estimate does not include the between-family variance, however, this interpretation applies to only (roughly) half of the sample PGS variance. In practice, the potential biases of a family-based GWAS are likely smaller than those arising from confounding in a standard, population-based GWAS, and so family studies remain important for the dissection of genetic contributions to phenotypic variation. Nonetheless, the causal interpretation of family-based GWAS estimates is less straightforward than has been widely appreciated.

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons

The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.

Ecology, the pace-of-life, epistatic selection and the maintenance of genetic variation in life-history genes

Evolutionary genetics has long struggled with understanding how functional genes under selection remain polymorphic in natural populations. Taking as a starting point that natural selection is ultimately a manifestation of ecological processes, we spotlight an underemphasized and potentially ubiquitous ecological effect that may have fundamental effects on the maintenance of genetic variation. Negative frequency dependency is a well-established emergent property of density dependence in ecology, because the relative profitability of different modes of exploiting or utilizing limiting resources tends to be inversely proportional to their frequency in a population. We suggest that this may often generate negative frequency-dependent selection (NFDS) on major effect loci that affect rate-dependent physiological processes, such as metabolic rate, that are phenotypically manifested as polymorphism in pace-of-life syndromes. When such a locus under NFDS shows stable intermediate frequency polymorphism, this should generate epistatic selection potentially involving large numbers of loci with more minor effects on life-history (LH) traits. When alternative alleles at such loci show sign epistasis with a major effect locus, this associative NFDS will promote the maintenance of polygenic variation in LH genes. We provide examples of the kind of major effect loci that could be involved and suggest empirical avenues that may better inform us on the importance and reach of this process.

An investigation of the sex-specific genetic architecture of fitness in Drosophila melanogaster

In dioecious populations, the sexes employ divergent reproductive strategies to maximize fitness and, as a result, genetic variants can affect fitness differently in males and females. Moreover, recent studies have highlighted an important role of the mating environment in shaping the strength and direction of sex-specific selection. Here, we measure adult fitness for each sex of 357 lines from the Drosophila Synthetic Population Resource in two different mating environments. We analyze the data using three different approaches to gain insight into the sex-specific genetic architecture for fitness: classical quantitative genetics, genomic associations, and a mutational burden approach. The quantitative genetics analysis finds that on average segregating genetic variation in this population has concordant fitness effects both across the sexes and across mating environments. We do not find specific genomic regions with strong associations with either sexually antagonistic (SA) or sexually concordant (SC) fitness effects, yet there is modest evidence of an excess of genomic regions with weak associations, with both SA and SC fitness effects. Our examination of mutational burden indicates stronger selection against indels and loss-of-function variants in females than in males.

Genetic Architecture of Flowering Time Differs Between Populations With Contrasting Demographic and Selective Histories

Understanding the evolutionary factors that impact the genetic architecture of traits is a central goal of evolutionary genetics. Here, we investigate how quantitative trait variation accumulated over time in populations that colonized a novel environment. We compare the genetic architecture of flowering time in Arabidopsis populations from the drought-prone Cape Verde Islands and their closest outgroup population from North Africa. We find that trait polygenicity is severely reduced in the island populations compared to the continental North African population. Further, trait architectures and reconstructed allelic histories best fit a model of strong directional selection in the islands in accord with a Fisher-Orr adaptive walk. Consistent with this, we find that large-effect variants that disrupt major flowering time genes (FRI and FLC) arose first, followed by smaller effect variants, including ATX2 L125F, which is associated with a 4-day reduction in flowering time. The most recently arising flowering time-associated loci are not known to be directly involved in flowering time, consistent with an omnigenic signature developing as the population approaches its trait optimum. Surprisingly, we find no effect in the natural population of EDI-Cvi-0 (CRY2 V367M), an allele for which an effect was previously validated by introgression into a Eurasian line. Instead, our results suggest the previously observed effect of the EDI-Cvi-0 allele on flowering time likely depends on genetic background, due to an epistatic interaction. Altogether, our results provide an empirical example of the effects demographic history and selection has on trait architecture.

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

A sexually selected male weapon characterized by strong additive genetic variance and no evidence for sexually antagonistic polyphenic maintenance

Sexual selection and sexual antagonism are important drivers of eco-evolutionary processes. The evolution of traits shaped by these processes depends on their genetic architecture, which remains poorly studied. Here, implementing a quantitative genetics approach using diallel crosses of the bulb mite, Rhizoglyphus robini, we investigated the genetic variance that underlies a sexually selected weapon that is dimorphic among males and female fecundity. Previous studies indicated that a negative genetic correlation between these two traits likely exists. We found male morph showed considerable additive genetic variance, which is unlikely to be explained solely by mutation-selection balance, indicating the likely presence of large-effect loci. However, a significant magnitude of inbreeding depression also indicates that morph expression is likely to be condition-dependent to some degree and that deleterious recessives can simultaneously contribute to morph expression. Female fecundity also showed a high degree of inbreeding depression, but the variance in female fecundity was mostly explained by epistatic effects, with very little contribution from additive effects. We found no significant genetic correlation, nor any evidence for dominance reversal, between male morph and female fecundity. The complex genetic architecture underlying male morph and female fecundity in this system has important implications for our understanding of the evolutionary interplay between purifying selection and sexually antagonistic selection.

Genetic analysis and QTL mapping of domestication-related traits in chili pepper (Capsicum annuum L.)

Chili pepper (Capsicum annuum L.) is one of the oldest and most phenotypically diverse pre-Columbian crops of the Americas. Despite the abundance of genetic resources, the use of wild germplasm and landraces in chili pepper breeding is limited. A better understanding of the evolutionary history in chili peppers, particularly in the context of traits of agronomic interest, can contribute to future improvement and conservation of genetic resources. In this study, an F₂:₃ mapping population derived from a cross between a C. annuum wild accession (Chiltepin) and a cultivated variety (Puya) was used to identify genomic regions associated with 19 domestication and agronomic traits. A genetic map was constructed consisting of 1023 single nucleotide polymorphism (SNP) markers clustered into 12 linkage groups and spanning a total of 1,263.87 cM. A reciprocal translocation that differentiates the domesticated genome from its wild ancestor and other related species was identified between chromosomes 1 and 8. Quantitative trait locus (QTL) analysis detected 20 marker-trait associations for 13 phenotypes, from which 14 corresponded to previously identified loci, and six were novel genomic regions related to previously unexplored domestication-syndrome traits, including form of unripe fruit, seedlessness, deciduous fruit, and growth habit. Our results revealed that the genetic architecture of Capsicum domestication is similar to other domesticated species with few loci with large effects, the presence of QTLs clusters in different genomic regions, and the predominance of domesticated recessive alleles. Our analysis indicates the domestication process in chili pepper has also had an effect on traits not directly related to the domestication syndrome. The information obtained in this study provides a more complete understanding of the genetic basis of Capsicum domestication that can potentially guide strategies for the exploitation of wild alleles.

Adaptation of a quantitative trait to a changing environment: New analytical insights on the asexual and infinitesimal sexual models

Predicting the adaptation of populations to a changing environment is crucial to assess the impact of human activities on biodiversity. Many theoretical studies have tackled this issue by modeling the evolution of quantitative traits subject to stabilizing selection around an optimal phenotype, whose value is shifted continuously through time. In this context, the population fate results from the equilibrium distribution of the trait, relative to the moving optimum. Such a distribution may vary with the shape of selection, the system of reproduction, the number of loci, the mutation kernel or their interactions. Here, we develop a methodology that provides quantitative measures of population maladaptation and potential of survival directly from the entire profile of the phenotypic distribution, without any a priori on its shape. We investigate two different systems of reproduction (asexual and infinitesimal sexual models of inheritance), with various forms of selection. In particular, we recover that fitness functions such that selection weakens away from the optimum lead to evolutionary tipping points, with an abrupt collapse of the population when the speed of environmental change is too high. Our unified framework allows deciphering the mechanisms that lead to this phenomenon. More generally, it allows discussing similarities and discrepancies between the two systems of reproduction, which are ultimately explained by different constraints on the evolution of the phenotypic variance. We demonstrate that the mean fitness in the population crucially depends on the shape of the selection function in the infinitesimal sexual model, in contrast with the asexual model. In the asexual model, we also investigate the effect of the mutation kernel and we show that kernels with higher kurtosis tend to reduce maladaptation and improve fitness, especially in fast changing environments.

Natural genetic variation in a dopamine receptor is associated with variation in female fertility in Drosophila melanogaster

Fertility is a major component of fitness but its genetic architecture remains poorly understood. Using a full diallel cross of 50 Drosophila Genetic Reference Panel inbred lines with whole genome sequences, we found substantial genetic variation in fertility largely attributable to females. We mapped genes associated with variation in female fertility by genome-wide association analysis of common variants in the fly genome. Validation of candidate genes by RNAi knockdown confirmed the role of the dopamine 2-like receptor (Dop2R) in promoting egg laying. We replicated the Dop2R effect in an independently collected productivity dataset and showed that the effect of the Dop2R variant was mediated in part by regulatory gene expression variation. This study demonstrates the strong potential of genome-wide association analysis in this diverse panel of inbred strains and subsequent functional analyses for understanding the genetic architecture of fitness traits.

Independently evolved pollution resistance in four killifish populations is largely explained by few variants of large effect

The genetic architecture of phenotypic traits can affect the mode and tempo of trait evolution. Human-altered environments can impose strong natural selection, where successful evolutionary adaptation requires swift and large phenotypic shifts. In these scenarios, theory predicts the influence of few adaptive variants of large effect, but empirical studies that have revealed the genetic architecture of rapidly evolved phenotypes are rare, especially for populations inhabiting polluted environments. Fundulus killifish have repeatedly evolved adaptive resistance to extreme pollution in urban estuaries. Prior studies, including genome scans for signatures of natural selection, have revealed some of the genes and pathways important for evolved pollution resistance, and provide context for the genotype-phenotype association studies reported here. We created multiple quantitative trait locus (QTL) mapping families using progenitors from four different resistant populations, and genetically mapped variation in sensitivity (developmental perturbations) following embryonic exposure to a model toxicant PCB-126. We found that a few large-effect QTL loci accounted for resistance to PCB-mediated developmental toxicity. QTLs harbored candidate genes that govern the regulation of aryl hydrocarbon receptor (AHR) signaling, where some (but not all) of these QTL loci were shared across all populations, and some (but not all) of these loci showed signatures of recent natural selection in the corresponding wild population. Some strong candidate genes for PCB resistance inferred from genome scans in wild populations were identified as QTL, but some key candidate genes were not. We conclude that rapidly evolved resistance to the developmental defects normally caused by PCB-126 is governed by few genes of large effect. However, other aspects of resistance beyond developmental phenotypes may be governed by additional loci, such that comprehensive resistance to PCB-126, and to the mixtures of chemicals that distinguish urban estuaries more broadly, may be more genetically complex.

Sexually antagonistic selection maintains genetic variance when sexual dimorphism evolves

Genetic variance (VG) in fitness related traits is often unexpectedly high, evoking the question how VG can be maintained in the face of selection. Sexually antagonistic (SA) selection favouring alternative alleles in the sexes is common and predicted to maintain VG, while directional selection should erode it. Both SA and sex-limited directional selection can lead to sex-specific adaptations but how each affect VG when sexual dimorphism evolves remain experimentally untested. Using replicated artificial selection on the seed beetle Callosobruchus maculatus body size we recently demonstrated an increase in size dimorphism under SA and male-limited (ML) selection by 50% and 32%, respectively. Here we test their consequences on genetic variation. We show that SA selection maintained significantly more ancestral, autosomal additive genetic variance than ML selection, while both eroded sex-linked additive variation equally. Ancestral female-specific dominance variance was completely lost under ML, while SA selection consistently sustained it. Further, both forms of selection preserved a high genetic correlation between the sexes (rm,f). These results demonstrate the potential for sexual antagonism to maintain more genetic variance while fuelling sex-specific adaptation in a short evolutionary time scale, and are in line with predicted importance of sex-specific dominance reducing sexual conflict over alternative alleles.

Rapid, nonparallel genomic evolution of Brassica rapa (field mustard) under experimental drought

While we know that climate change can potentially cause rapid phenotypic evolution, our understanding of the genetic basis and degree of genetic parallelism of rapid evolutionary responses to climate change is limited. In this study, we combined the resurrection approach with an evolve-and-resequence design to examine genome-wide evolutionary changes following drought. We exposed genetically similar replicate populations of the annual plant Brassica rapa derived from a field population in southern California to four generations of experimental drought or watered conditions in a greenhouse. Genome-wide sequencing of ancestral and descendant population pools identified hundreds of SNPs that showed evidence of rapidly evolving in response to drought. Several of these were in stress response genes, and two were identified in a prior study of drought response in this species. However, almost all genetic changes were unique among experimental populations, indicating that the evolutionary changes were largely nonparallel, despite the fact that genetically similar replicates of the same founder population had experienced controlled and consistent selection regimes. This nonparallelism of evolution at the genetic level is potentially because of polygenetic adaptation allowing for multiple different genetic routes to similar phenotypic outcomes. Our findings help to elucidate the relationship between rapid phenotypic and genomic evolution and shed light on the degree of parallelism and predictability of genomic evolution to environmental change.

Polygenic adaptation dynamics in large, finite populations

Although many phenotypic traits are determined by a large number of genetic variants, how a polygenic trait adapts in response to a change in the environment is not completely understood. In the framework of diffusion theory, we study the steady state and the adaptation dynamics of a large but finite population evolving under stabilizing selection and symmetric mutations when selection and mutation are moderately large. We find that in the stationary state, the allele frequency distribution at a locus is unimodal if its effect size is below a threshold effect and bimodal otherwise; these results are the stochastic analog of the deterministic ones where the stable allele frequency becomes bistable when the effect size exceeds a threshold. It is known that following a sudden shift in the phenotypic optimum, in an infinitely large population, selective sweeps at a large-effect locus are prevented and adaptation proceeds exclusively via subtle changes in the allele frequency; in contrast, we find that the chance of sweep is substantially enhanced in large, finite populations and the allele frequency at a large-effect locus can reach a high frequency at short times even for small shifts in the phenotypic optimum.

Population Genomic Time Series Data of a Natural Population Suggests Adaptive Tracking of Fluctuating Environmental Changes

Natural populations are constantly exposed to fluctuating environmental changes that negatively affect their fitness in unpredictable ways. While theoretical models show the possibility of counteracting these environmental changes through rapid evolutionary adaptations, there have been few empirical studies demonstrating such adaptive tracking in natural populations. Here, we analyzed environmental data, fitness-related phenotyping and genomic time-series data sampled over 3 years from a natural Chironomus riparius (Diptera, Insecta) population to address this question. We show that the population's environment varied significantly on the time scale of the sampling in many selectively relevant dimensions, independently of each other. Similarly, phenotypic fitness components evolved significantly on the same temporal scale (mean 0.32 Haldanes), likewise independent from each other. The allele frequencies of 367,446 SNPs across the genome showed evidence of positive selection. Using temporal correlation of spatially coherent allele frequency changes revealed 35,574 haplotypes with more than one selected SNP. The mean selection coefficient for these haplotypes was 0.30 (s.d. = 0.68). The frequency changes of these haplotypes clustered in 46 different temporal patterns, indicating concerted, independent evolution of many polygenic traits. Nine of these patterns were strongly correlated with measured environmental variables. Enrichment analysis of affected genes suggested the implication of a wide variety of biological processes. Thus, our results suggest overall that the natural population of C. riparius tracks environmental change through rapid polygenic adaptation in many independent dimensions. This is further evidence that natural selection is pervasive at the genomic level and that evolutionary and ecological time scales may not differ at all, at least in some organisms.

The impact of SNP density on quantitative genetic analyses of body size traits in a wild population of Soay sheep

Understanding the genetic architecture underpinning quantitative traits in wild populations is pivotal to understanding the processes behind trait evolution. The 'animal model' is a popular method for estimating quantitative genetic parameters such as heritability and genetic correlation and involves fitting an estimate of relatedness between individuals in the study population. Genotypes at genome-wide markers can be used to estimate relatedness; however, relatedness estimates vary with marker density, potentially affecting results. Increasing density of markers is also expected to increase the power to detect quantitative trait loci (QTL). In order to understand how the density of genetic markers affects the results of quantitative genetic analyses, we estimated heritability and performed genome-wide association studies (GWAS) on five body size traits in an unmanaged population of Soay sheep using two different SNP densities: a dataset of 37,037 genotyped SNPs and an imputed dataset of 417,373 SNPs. Heritability estimates did not differ between the two SNP densities, but the high-density imputed SNP dataset revealed four new SNP-trait associations that were not found with the lower density dataset, as well as confirming all previously-found QTL. We also demonstrated that fitting fixed and random effects in the same step as performing GWAS is a more powerful approach than pre-correcting for covariates in a separate model.

Standing Genetic Diversity and Transmission Bottleneck Size Drive Adaptation in Bacteriophage Qβ

A critical issue to understanding how populations adapt to new selective pressures is the relative contribution of the initial standing genetic diversity versus that generated de novo. RNA viruses are an excellent model to study this question, as they form highly heterogeneous populations whose genetic diversity can be modulated by factors such as the number of generations, the size of population bottlenecks, or exposure to new environment conditions. In this work, we propagated at nonoptimal temperature (43 °C) two bacteriophage Qβ populations differing in their degree of heterogeneity. Deep sequencing analysis showed that, prior to the temperature change, the most heterogeneous population contained some low-frequency mutations that had previously been detected in the consensus sequences of other Qβ populations adapted to 43 °C. Evolved populations with origin in this ancestor reached similar growth rates, but the adaptive pathways depended on the frequency of these standing mutations and the transmission bottleneck size. In contrast, the growth rate achieved by populations with origin in the less heterogeneous ancestor did depend on the transmission bottleneck size. The conclusion is that viral diversification in a particular environment may lead to the emergence of mutants capable of accelerating adaptation when the environment changes.

Structural plasticity in I-Ag7 links autoreactivity to hybrid insulin peptides in type I diabetes

We recently provided evidence for promiscuous recognition of several different hybrid insulin peptides (HIPs) by the highly diabetogenic, I-Ag7-restricted 4.1-T cell receptor (TCR). To understand the structural determinants of this phenomenon, we solved the structure of an agonistic HIP/I-Ag7 complex, both in isolation as well as bound to the 4.1-TCR. We find that HIP promiscuity of the 4.1-TCR is dictated, on the one hand, by an amino acid sequence pattern that ensures I-Ag7 binding and, on the other hand, by the presence of three acidic residues at positions P5, P7 and P8 that favor an optimal engagement by the 4.1-TCR’s complementary determining regions. Surprisingly, comparison of the TCR-bound and unbound HIP/I-Ag7 structures reveals that 4.1-TCR binding triggers several novel and unique structural motions in both the I-Ag7 molecule and the peptide that are essential for docking. This observation indicates that the type 1 diabetes-associated I-Ag7 molecule is structurally malleable and that this plasticity allows the recognition of multiple peptides by individual TCRs that would otherwise be unable to do so.

Lineage dynamics in growing biofilms: Spatial patterns of standing vs. de novo diversity

Microbial biofilms show high phenotypic and genetic diversity, yet the mechanisms underlying diversity generation and maintenance remain unclear. Here, we investigate how spatial patterns of growth activity within a biofilm lead to spatial patterns of genetic diversity. Using individual-based computer simulations, we show that the active layer of growing cells at the biofilm interface controls the distribution of lineages within the biofilm, and therefore the patterns of standing and de novo diversity. Comparing biofilms of equal size, those with a thick active layer retain more standing diversity, while de novo diversity is more evenly distributed within the biofilm. In contrast, equal-sized biofilms with a thin active layer retain less standing diversity, and their de novo diversity is concentrated at the top of the biofilm, and in fewer lineages. In the context of antimicrobial resistance, biofilms with a thin active layer may be more prone to generate lineages with multiple resistance mutations, and to seed new resistant biofilms via sloughing of resistant cells from the upper layers. Our study reveals fundamental "baseline" mechanisms underlying the patterning of diversity within biofilms.

Key features of the genetic architecture and evolution of host-microbe interactions revealed by high-resolution genetic mapping of the mucosa-associated gut microbiome in hybrid mice

Determining the forces that shape diversity in host-associated bacterial communities is critical to understanding the evolution and maintenance of metaorganisms. To gain deeper understanding of the role of host genetics in shaping gut microbial traits, we employed a powerful genetic mapping approach using inbred lines derived from the hybrid zone of two incipient house mouse species. Furthermore, we uniquely performed our analysis on microbial traits measured at the gut mucosal interface, which is in more direct contact with host cells and the immune system. Several mucosa-associated bacterial taxa have high heritability estimates, and interestingly, 16S rRNA transcript-based heritability estimates are positively correlated with cospeciation rate estimates. Genome-wide association mapping identifies 428 loci influencing 120 taxa, with narrow genomic intervals pinpointing promising candidate genes and pathways. Importantly, we identified an enrichment of candidate genes associated with several human diseases, including inflammatory bowel disease, and functional categories including innate immunity and G-protein-coupled receptors. These results highlight key features of the genetic architecture of mammalian host-microbe interactions and how they diverge as new species form.

The digestive system, particularly the large intestine, hosts many types of bacteria which together form the gut microbiome. The exact makeup of different bacterial species is specific to an individual, but microbiomes are often more similar between related individuals, and more generally, across related species. Whether this is because individuals share similar environments or similar genetic backgrounds remains unclear. These two factors can be disentangled by breeding different animal lineages – which have different genetic backgrounds while belonging to the same species – and then raising the progeny in the same environment.

To investigate this question, Doms et al. studied the genes and microbiomes of mice resulting from breeding strains from multiple locations in a natural hybrid zone between different subspecies. The experiments showed that 428 genetic regions affected the makeup of the microbiome, many of which were known to be associated with human diseases. Further analysis revealed 79 genes that were particularly interesting, as they were involved in recognition and communication with bacteria. These results show how the influence of the host genome on microbiome composition becomes more specialized as animals evolve.

Overall, the work by Doms et al. helps to pinpoint the genes that impact the microbiome; this knowledge could be helpful to examine how these interactions contribute to the emergence of conditions such as diabetes or inflammatory bowel disease, which are linked to perturbations in gut bacteria.

Population differentiation of polygenic score predictions under stabilizing selection

Given the many small-effect loci uncovered by genome-wide association studies (GWAS), polygenic scores have become central to genomic medicine, and have found application in diverse settings including evolutionary studies of adaptation. Despite their promise, polygenic scores have been found to suffer from limited portability across human populations. This at first seems in conflict with the observation that most common genetic variation is shared among populations. We investigate one potential cause of this discrepancy: stabilizing selection on complex traits. Counterintuitively, while stabilizing selection constrains phenotypic evolution, it accelerates the loss and fixation of alleles underlying trait variation within populations (GWAS loci). Thus even when populations share an optimum phenotype, stabilizing selection erodes the variance contributed by their shared GWAS loci, such that predictions from GWAS in one population explain less of the phenotypic variation in another. We develop theory to quantify how stabilizing selection is expected to reduce the prediction accuracy of polygenic scores in populations not represented in GWAS samples. In addition, we find that polygenic scores can substantially overstate average genetic differences of phenotypes among populations. We emphasize stabilizing selection around a common optimum as a useful null model to connect patterns of allele frequency and polygenic score differentiation. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Association Studies and Genomic Prediction for Genetic Improvements in Agriculture

To feed the fast growing global population with sufficient food using limited global resources, it is urgent to develop and utilize cutting-edge technologies and improve efficiency of agricultural production. In this review, we specifically introduce the concepts, theories, methods, applications and future implications of association studies and predicting unknown genetic value or future phenotypic events using genomics in the area of breeding in agriculture. Genome wide association studies can identify the quantitative genetic loci associated with phenotypes of importance in agriculture, while genomic prediction utilizes individual genetic value to rank selection candidates to improve the next generation of plants or animals. These technologies and methods have improved the efficiency of genetic improvement programs for agricultural production via elite animal breeds and plant varieties. With the development of new data acquisition technologies, there will be more and more data collected from high-through-put technologies to assist agricultural breeding. It will be crucial to extract useful information among these large amounts of data and to face this challenge, more efficient algorithms need to be developed and utilized for analyzing these data. Such development will require knowledge from multiple disciplines of research.

Genetic basis of speciation and adaptation: from loci to causative mutations

Does evolution proceed in small steps or large leaps? How repeatable is evolution? How constrained is the evolutionary process? Answering these long-standing questions in evolutionary biology is indispensable for both understanding how extant biodiversity has evolved and predicting how organisms and ecosystems will respond to changing environments in the future. Understanding the genetic basis of phenotypic diversification and speciation in natural populations is key to properly answering these questions. The leap forward in genome sequencing technologies has made it increasingly easier to not only investigate the genetic architecture but also identify the variant sites underlying adaptation and speciation in natural populations. Furthermore, recent advances in genome editing technologies are making it possible to investigate the functions of each candidate gene in organisms from natural populations. In this article, we discuss how these recent technological advances enable the analysis of causative genes and mutations and how such analysis can help answer long-standing evolutionary biology questions.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

A two-step adaptive walk rewires nutrient transport in a challenging edaphic environment

Most well-characterized cases of adaptation involve single genetic loci. Theory suggests that multilocus adaptive walks should be common, but these are challenging to identify in natural populations. Here, we combine trait mapping with population genetic modeling to show that a two-step process rewired nutrient homeostasis in a population of Arabidopsis as it colonized the base of an active stratovolcano characterized by extremely low soil manganese (Mn). First, a variant that disrupted the primary iron (Fe) uptake transporter gene (IRT1) swept quickly to fixation in a hard selective sweep, increasing Mn but limiting Fe in the leaves. Second, multiple independent tandem duplications occurred at NRAMP1 and together rose to near fixation in the island population, compensating the loss of IRT1 by improving Fe homeostasis. This study provides a clear case of a multilocus adaptive walk and reveals how genetic variants reshaped a phenotype and spread over space and time.

Implications of Large-Effect Loci for Conservation: A Review and Case Study with Pacific Salmon

The increasing feasibility of assembling large genomic datasets for non-model species presents both opportunities and challenges for applied conservation and management. A popular theme in recent studies is the search for large-effect loci that explain substantial portions of phenotypic variance for a key trait(s). If such loci can be linked to adaptations, 2 important questions arise: 1) Should information from these loci be used to reconfigure conservation units (CUs), even if this conflicts with overall patterns of genetic differentiation? 2) How should this information be used in viability assessments of populations and larger CUs? In this review, we address these questions in the context of recent studies of Chinook salmon and steelhead (anadromous form of rainbow trout) that show strong associations between adult migration timing and specific alleles in one small genomic region. Based on the polygenic paradigm (most traits are controlled by many genes of small effect) and genetic data available at the time showing that early-migrating populations are most closely related to nearby late-migrating populations, adult migration differences in Pacific salmon and steelhead were considered to reflect diversity within CUs rather than separate CUs. Recent data, however, suggest that specific alleles are required for early migration, and that these alleles are lost in populations where conditions do not support early-migrating phenotypes. Contrasting determinations under the US Endangered Species Act and the State of California's equivalent legislation illustrate the complexities of incorporating genomics data into CU configuration decisions. Regardless how CUs are defined, viability assessments should consider that 1) early-migrating phenotypes experience disproportionate risks across large geographic areas, so it becomes important to identify early-migrating populations that can serve as reliable sources for these valuable genetic resources; and 2) genetic architecture, especially the existence of large-effect loci, can affect evolutionary potential and adaptability.

A long evolutionary reach for fishing nets

Earlier maturation of Atlantic salmon is linked to indirect effects of fisheries on its prey.

Causes of variability in estimates of mutational variance from mutation accumulation experiments

Characteristics of the new phenotypic variation introduced via mutation have broad implications in evolutionary and medical genetics. Standardized estimates of this mutational variance, V_M, span 2 orders of magnitude, but the causes of this remain poorly resolved. We investigated estimate heterogeneity using 2 approaches. First, meta-analyses of ∼150 estimates of standardized V_M from 37 mutation accumulation studies did not support a difference among taxa (which differ in mutation rate) but provided equivocal support for differences among trait types (life history vs morphology, predicted to differ in mutation rate). Notably, several experimental factors were confounded with taxon and trait, and further empirical data are required to resolve their influences. Second, we analyzed morphological data from an experiment in Drosophila serrata to determine the potential for unintentional heterogeneity among environments in which phenotypes were measured (i.e. among laboratories or time points) or transient segregation of mutations within mutation accumulation lines to affect standardized V_M. Approximating the size of an average mutation accumulation experiment, variability among repeated estimates of (accumulated) mutational variance was comparable to variation among published estimates of standardized V_M. This heterogeneity was (partially) attributable to unintended environmental variation or within line segregation of mutations only for wing size, not wing shape traits. We conclude that sampling error contributed substantial variation within this experiment, and infer that it will also contribute substantially to differences among published estimates. We suggest a logistically permissive approach to improve the precision of estimates, and consequently our understanding of the dynamics of mutational variance of quantitative traits.

Lottery, luck, or legacy. A review of "The Genetic Lottery: Why DNA matters for social equality"

A book review of "The genetic lottery: why DNA matters for social equality." (Princeton University Press, 2021) by Kathryn Paige Harden.

Parallel reduction in flowering time from de novo mutations enable evolutionary rescue in colonizing lineages

Understanding how populations adapt to abrupt environmental change is necessary to predict responses to future challenges, but identifying specific adaptive variants, quantifying their responses to selection and reconstructing their detailed histories is challenging in natural populations. Here, we use Arabidopsis from the Cape Verde Islands as a model to investigate the mechanisms of adaptation after a sudden shift to a more arid climate. We find genome-wide evidence of adaptation after a multivariate change in selection pressures. In particular, time to flowering is reduced in parallel across islands, substantially increasing fitness. This change is mediated by convergent de novo loss of function of two core flowering time genes: FRI on one island and FLC on the other. Evolutionary reconstructions reveal a case where expansion of the new populations coincided with the emergence and proliferation of these variants, consistent with models of rapid adaptation and evolutionary rescue.

Detailing how populations adapted to environmental change is needed to predict future responses, but identifying adaptive variants and detailing their fitness effects is rare. Here, the authors show that parallel loss of FRI and FLC function reduces time to flowering and drives adaptation in a drought prone environment.

On the genetic architecture of rapidly adapting and convergent life history traits in guppies

The genetic basis of traits shapes and constrains how adaptation proceeds in nature; rapid adaptation can proceed using stores of polygenic standing genetic variation or hard selective sweeps, and increasing polygenicity fuels genetic redundancy, reducing gene re-use (genetic convergence). Guppy life history traits evolve rapidly and convergently among natural high- and low-predation environments in northern Trinidad. This system has been studied extensively at the phenotypic level, but little is known about the underlying genetic architecture. Here, we use four independent F2 QTL crosses to examine the genetic basis of seven (five female, two male) guppy life history phenotypes and discuss how these genetic architectures may facilitate or constrain rapid adaptation and convergence. We use RAD-sequencing data (16,539 SNPs) from 370 male and 267 female F2 individuals. We perform linkage mapping, estimates of genome-wide and per-chromosome heritability (multi-locus associations), and QTL mapping (single-locus associations). Our results are consistent with architectures of many loci of small-effect for male age and size at maturity and female interbrood period. Male trait associations are clustered on specific chromosomes, but female interbrood period exhibits a weak genome-wide signal suggesting a potentially highly polygenic component. Offspring weight and female size at maturity are also associated with a single significant QTL each. These results suggest rapid, repeatable phenotypic evolution of guppies may be facilitated by polygenic trait architectures, but subsequent genetic redundancy may limit gene re-use across populations, in agreement with an absence of strong signatures of genetic convergence from recent analyses of wild guppies.

Stress-induced changes in body surface temperature are repeatable, but do not differ between urban and rural birds

Urbanisation can alter local microclimates, thus creating new thermal challenges for resident species. However, urban environments also present residents with frequent, novel stressors (e.g., noise, human interaction) which may demand investment in costly, self-preserving responses (e.g., the fight-or-flight response). One way that urban residents might cope with this combination of demands is by using regional heterothermy to reduce costs of thermoregulation during the stress response. In this study, we used black-capped chickadees (n_urban = 9; n_rural = 10) to test whether known heterothermic responses to stress exposure (here, at the bare skin around the eye): (1) varied consistently among individuals (i.e., were repeatable), and (2) were most pronounced among urban individuals compared with rural individuals. Further, to gather evidence for selection on stress-induced heterothermic responses in urban settings, we tested: (3) whether repeatability of this response was lower among birds sampled from urban environments compared with those sampled from rural environments. For the first time, we show that heterothermic responses to stress exposures (i.e. changes in body surface temperature) were highly repeatable across chronic time periods (R = 0.58) but not acute time periods (R = 0.13). However, we also show that these responses did not differ between urban and rural birds, nor were our repeatability estimates any lower in our urban sample. Thus, while regional heterothermy during stress exposure may provide energetic benefits to some, but not all, individuals, enhanced use of this response to cope with urban pressures appears unlikely in our study species.

Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula

Heavy metals are an increasing problem due to contamination from human sources that and can enter the food chain by being taken up by plants. Understanding the genetic basis of accumulation and tolerance in plants is important for reducing the uptake of toxic metals in crops and crop relatives, as well as for removing heavy metals from soils by means of phytoremediation. Following exposure of Medicago truncatula seedlings to cadmium (Cd) and mercury (Hg), we conducted a genome-wide association study using relative root growth (RRG) and leaf accumulation measurements. Cd and Hg accumulation and RRG had heritability ranging 0.44 - 0.72 indicating high genetic diversity for these traits. The Cd and Hg trait associations were broadly distributed throughout the genome, indicated the traits are polygenic and involve several quantitative loci. For all traits, candidate genes included several membrane associated ATP-binding cassette transporters, P-type ATPase transporters, oxidative stress response genes, and stress related UDP-glycosyltransferases. The P-type ATPase transporters and ATP-binding cassette protein-families have roles in vacuole transport of heavy metals, and our findings support their wide use in physiological plant responses to heavy metals and abiotic stresses. We also found associations between Cd RRG with the genes CAX3 and PDR3, two linked adjacent genes, and leaf accumulation of Hg associated with the genes NRAMP6 and CAX9. When plant genotypes with the most extreme phenotypes were compared, we found significant divergence in genomic regions using population genomics methods that contained metal transport and stress response gene ontologies. Several of these genomic regions show high linkage disequilibrium (LD) among candidate genes suggesting they have evolved together. Minor allele frequency (MAF) and effect size of the most significant SNPs was negatively correlated with large effect alleles being most rare. This is consistent with purifying selection against alleles that increase toxicity and abiotic stress. Conversely, the alleles with large affect that had higher frequencies that were associated with the exclusion of Cd and Hg. Overall, macroevolutionary conservation of heavy metal and stress response genes is important for improvement of forage crops by harnessing wild genetic variants in gene banks such as the Medicago HapMap collection.

Genome resequencing reveals rapid, repeated evolution in the Colorado potato beetle

Insecticide resistance and rapid pest evolution threatens food security and the development of sustainable agricultural practices, yet the evolutionary mechanisms that allow pests to rapidly adapt to control tactics remains unclear. Here we examine how a global super-pest, the Colorado potato beetle (CPB), Leptinotarsa decemlineata, rapidly evolves resistance to insecticides. Using whole genome resequencing and transcriptomic data focused on its ancestral and pest range in North America, we assess evidence for three, non-mutually exclusive models of rapid evolution: pervasive selection on novel mutations, rapid regulatory evolution, and repeated selection on standing genetic variation. Population genomic analysis demonstrates that CPB is geographically structured, even among recently established pest populations. Pest populations exhibit similar levels of nucleotide diversity, relative to non-pest populations, and show evidence of recent expansion. Genome scans provide clear signatures of repeated adaptation across CPB populations, with especially strong evidence of selection on insecticide resistance genes in different populations. Analyses of gene expression show that constitutive upregulation of candidate insecticide resistance genes drives distinctive population patterns. CPB evolves insecticide resistance repeatedly across agricultural regions, leveraging similar genetic pathways but different genes, demonstrating a polygenic trait architecture for insecticide resistance that can evolve from standing genetic variation. Despite expectations, we do not find support for strong selection on novel mutations, or rapid evolution from selection on regulatory genes. These results suggest that integrated pest management practices must mitigate the evolution of polygenic resistance phenotypes among local pest populations, in order to maintain the efficacy and sustainability of novel control techniques.

Genetic Bases of Complex Traits: From Quantitative Trait Loci to Prediction

Conceived as a general introduction to the book, this chapter is a reminder of the core concepts of genetic mapping and molecular marker-based prediction. It provides an overview of the principles and the evolution of methods for mapping the variation of complex traits, and methods for QTL-based prediction of human disease risk and animal and plant breeding value. The principles of linkage-based and linkage disequilibrium-based QTL mapping methods are described in the context of the simplest, single-marker, methods. Methodological evolutions are analysed in relation with their ability to account for the complexity of the genotype-phenotype relations. Main characteristics of the genetic architecture of complex traits, drawn from QTL mapping works using large populations of unrelated individuals, are presented. Methods combining marker-QTL association data into polygenic risk score that captures part of an individual's susceptibility to complex diseases are reviewed. Principles of best linear mixed model-based prediction of breeding value in animal- and plant-breeding programs using phenotypic and pedigree data, are summarized and methods for moving from BLUP to marker-QTL BLUP are presented. Factors influencing the additional genetic progress achieved by using molecular data and rules for their optimization are discussed.

Polygenic adaptation after a sudden change in environment

Polygenic adaptation is thought to be ubiquitous, yet remains poorly understood. Here, we model this process analytically, in the plausible setting of a highly polygenic, quantitative trait that experiences a sudden shift in the fitness optimum. We show how the mean phenotype changes over time, depending on the effect sizes of loci that contribute to variance in the trait, and characterize the allele dynamics at these loci. Notably, we describe the two phases of the allele dynamics: The first is a rapid phase, in which directional selection introduces small frequency differences between alleles whose effects are aligned with or opposed to the shift, ultimately leading to small differences in their probability of fixation during a second, longer phase, governed by stabilizing selection. As we discuss, key results should hold in more general settings and have important implications for efforts to identify the genetic basis of adaptation in humans and other species.