Detecting selection with a genetic cross

Green revolution gene drives adaptation of Arabidopsis to the extremely high altitude

To elucidate the process of adaptation, particularly the traits subject to natural selection and the molecular mechanisms underlying their natural variation, is one of the primary objectives of evolutionary biology. The uplifted landscape offers an excellent framework for understanding how organisms adapt to dramatic climatic gradients. To investigate the genetic basis of plant adaptation to the extremely high altitude, we first compared the genomic and phenotypic variations of two closely related Arabidopsis thaliana accessions from high altitude (Xizang, also known as "Tibet") and low altitude (Yunnan), respectively. The Xizang population represents a relict group characterized by a small effective population size. Notably, the Xizang genome has more transposable elements (TEs) and more gene loss-of-function (LoF) mutations. Differentially expressed genes were enriched in biological processes of cellular response to oxygen-containing compound, regulation of defense response, and response to light intensity. Intriguingly, the phenotypic selection analysis revealed that silique density was under natural selection. Furthermore, we genetically mapped and validated that the LoF mutation of GA20ox1, the homologous gene of green revolution in rice, resulted in a higher silique density in Xizang Arabidopsis. Given that GA20ox1 is linked to Arabidopsis adaptation to the Alps Mountains, its parallel evolution plays an important role in the adaptation to Alpine habitats. Overall, our results highlight that identifying adaptive traits and elucidating the molecular mechanisms underlying natural variation of these traits is crucial for unraveling the mystery of adaptive evolution and has significant implications for crop breeding.

Disentangling variational bias: the roles of development, mutation, and selection

The extraordinary diversity and adaptive fit of organisms to their environment depends fundamentally on the availability of variation. While most population genetic frameworks assume that random mutations produce isotropic phenotypic variation, the distribution of variation available to natural selection is more restricted, as the distribution of phenotypic variation is affected by a range of factors in developmental systems. Here, we revisit the concept of developmental bias - the observation that the generation of phenotypic variation is biased due to the structure, character, composition, or dynamics of the developmental system - and argue that a more rigorous investigation into the role of developmental bias in the genotype-to-phenotype map will produce fundamental insights into evolutionary processes, with potentially important consequences on the relation between micro- and macro-evolution. We discuss the hierarchical relationships between different types of variational biases, including mutation bias and developmental bias, and their roles in shaping the realized phenotypic space. Furthermore, we highlight the challenges in studying variational bias and propose potential approaches to identify developmental bias using modern tools.

The Role of Hybridization in Species Formation and Persistence

Hybridization, or interbreeding between different taxa, was traditionally considered to be rare and to have a largely detrimental impact on biodiversity, sometimes leading to the breakdown of reproductive isolation and even to the reversal of speciation. However, modern genomic and analytical methods have shown that hybridization is common in some of the most diverse clades across the tree of life, sometimes leading to rapid increase of phenotypic variability, to introgression of adaptive alleles, to the formation of hybrid species, and even to entire species radiations. In this review, we identify consensus among diverse research programs to show how the field has progressed. Hybridization is a multifaceted evolutionary process that can strongly influence species formation and facilitate adaptation and persistence of species in a rapidly changing world. Progress on testing this hypothesis will require cooperation among different subdisciplines.

Detecting diversifying selection for a trait from within and between-species genotypes and phenotypes

To quantify selection acting on a trait, methods have been developed using either within or between-species variation. However, methods using within-species variation do not integrate the changes at the macro-evolutionary scale. Conversely, current methods using between-species variation usually discard within-species variation, thus not accounting for processes at the micro-evolutionary scale. The main goal of this study is to define a neutrality index for a quantitative trait, by combining within- and between-species variation. This neutrality index integrates nucleotide polymorphism and divergence for normalizing trait variation. As such, it does not require estimation of population size nor of time of speciation for normalization. Our index can be used to seek deviation from the null model of neutral evolution, and test for diversifying selection. Applied to brain mass and body mass at the mammalian scale, we show that brain mass is under diversifying selection. Finally, we show that our test is not sensitive to the assumption that population sizes, mutation rates and generation time are constant across the phylogeny, and automatically adjust for it.

Adaptive tail-length evolution in deer mice is associated with differential Hoxd13 expression in early development

Variation in the size and number of axial segments underlies much of the diversity in animal body plans. Here we investigate the evolutionary, genetic and developmental mechanisms driving tail-length differences between forest and prairie ecotypes of deer mice (Peromyscus maniculatus). We first show that long-tailed forest mice perform better in an arboreal locomotion assay, consistent with tails being important for balance during climbing. We then identify six genomic regions that contribute to differences in tail length, three of which associate with caudal vertebra length and the other three with vertebra number. For all six loci, the forest allele increases tail length, indicative of the cumulative effect of natural selection. Two of the genomic regions associated with variation in vertebra number contain Hox gene clusters. Of those, we find an allele-specific decrease in Hoxd13 expression in the embryonic tail bud of long-tailed forest mice, consistent with its role in axial elongation. Additionally, we find that forest embryos have more presomitic mesoderm than prairie embryos and that this correlates with an increase in the number of neuromesodermal progenitors, which are modulated by Hox13 paralogues. Together, these results suggest a role for Hoxd13 in the development of natural variation in adaptive morphology on a microevolutionary timescale.

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.

The ecology and quantitative genetics of seed and seedling traits in upland and lowland ecotypes of a perennial grass

Plants have evolved diverse reproductive allocation strategies and seed traits to aid in dispersal, persistence in the seed bank, and establishment. In particular, seed size, dormancy, and early seedling vigor are thought to be key functional traits with important recruitment and fitness consequences across abiotic stress gradients. Selection for favored seed-trait combinations, or against maladaptive combinations, is likely an important driver shaping recruitment strategies. Here, we test for seed-trait plasticity and patterns of recruitment using two genotypes representative of contrasting upland and lowland ecotypes of Panicum hallii with field experiments in native versus foreign habitats. Furthermore, we test whether seed traits have been under directional selection in P. hallii using the v-test based on trait variance in a genetic cross. Finally, we evaluate the genetic architecture of ecotypic divergence for these traits with quantitative trait locus (QTL) mapping. Field experiments reveal little plasticity but support a hypothesis of adaptation divergence among ecotypes based on recruitment. Patterns of segregation within recombinant hybrids provides strong support for directional selection driving ecotypic divergence in seed traits. Genetic mapping revealed a polygenic architecture with evidence of genetic correlation between seed mass, dormancy, and seedling vigor. Our results suggest that the evolution of these traits may involve constraints that affect the direction of adaptive divergence. For example, seed size and germination percentage shared two colocalized QTL with antagonistic additive effects. This supports the hypothesis of a functional genetic relationship between these traits, resulting in either large seed/strong dormancy or small seed/weak dormancy trait combinations. Overall, our study provides insights into the factors facilitating and potentially constraining ecotypic differentiation in seed traits.

A Pleiotropic Flowering Time QTL Exhibits Gene-by-Environment Interaction for Fitness in a Perennial Grass

Appropriate flowering time is a crucial adaptation impacting fitness in natural plant populations. Although the genetic basis of flowering variation has been extensively studied, its mechanisms in nonmodel organisms and its adaptive value in the field are still poorly understood. Here, we report new insights into the genetic basis of flowering time and its effect on fitness in Panicum hallii, a native perennial grass. Genetic mapping in populations derived from inland and coastal ecotypes identified flowering time quantitative trait loci (QTL) and many exhibited extensive QTL-by-environment interactions. Patterns of segregation within recombinant hybrids provide strong support for directional selection driving ecotypic divergence in flowering time. A major QTL on chromosome 5 (q-FT5) was detected in all experiments. Fine-mapping and expression studies identified a gene with orthology to a rice FLOWERING LOCUS T-like 9 (PhFTL9) as the candidate underlying q-FT5. We used a reciprocal transplant experiment to test for local adaptation and the specific impact of q-FT5 on performance. We did not observe local adaptation in terms of fitness tradeoffs when contrasting ecotypes in home versus away habitats. However, we observed that the coastal allele of q-FT5 conferred a fitness advantage only in its local habitat but not at the inland site. Sequence analyses identified an excess of low-frequency polymorphisms at the PhFTL9 promoter in the inland lineage, suggesting a role for either selection or population expansion on promoter evolution. Together, our findings demonstrate the genetic basis of flowering variation in a perennial grass and provide evidence for conditional neutrality underlying flowering time divergence.

Detecting signatures of selection on gene expression

A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.

Evolutionary Ecology of Plant-Arthropod Interactions in Light of the "Omics" Sciences: A Broad Guide

Aboveground plant-arthropod interactions are typically complex, involving herbivores, predators, pollinators, and various other guilds that can strongly affect plant fitness, directly or indirectly, and individually, synergistically, or antagonistically. However, little is known about how ongoing natural selection by these interacting guilds shapes the evolution of plants, i.e., how they affect the differential survival and reproduction of genotypes due to differences in phenotypes in an environment. Recent technological advances, including next-generation sequencing, metabolomics, and gene-editing technologies along with traditional experimental approaches (e.g., quantitative genetics experiments), have enabled far more comprehensive exploration of the genes and traits involved in complex ecological interactions. Connecting different levels of biological organization (genes to communities) will enhance the understanding of evolutionary interactions in complex communities, but this requires a multidisciplinary approach. Here, we review traditional and modern methods and concepts, then highlight future avenues for studying the evolution of plant-arthropod interactions (e.g., plant-herbivore-pollinator interactions). Besides promoting a fundamental understanding of plant-associated arthropod communities' genetic background and evolution, such knowledge can also help address many current global environmental challenges.

Barcoded Bulk QTL mapping reveals highly polygenic and epistatic architecture of complex traits in yeast

Mapping the genetic basis of complex traits is critical to uncovering the biological mechanisms that underlie disease and other phenotypes. Genome-wide association studies (GWAS) in humans and quantitative trait locus (QTL) mapping in model organisms can now explain much of the observed heritability in many traits, allowing us to predict phenotype from genotype. However, constraints on power due to statistical confounders in large GWAS and smaller sample sizes in QTL studies still limit our ability to resolve numerous small-effect variants, map them to causal genes, identify pleiotropic effects across multiple traits, and infer non-additive interactions between loci (epistasis). Here, we introduce barcoded bulk quantitative trait locus (BB-QTL) mapping, which allows us to construct, genotype, and phenotype 100,000 offspring of a budding yeast cross, two orders of magnitude larger than the previous state of the art. We use this panel to map the genetic basis of eighteen complex traits, finding that the genetic architecture of these traits involves hundreds of small-effect loci densely spaced throughout the genome, many with widespread pleiotropic effects across multiple traits. Epistasis plays a central role, with thousands of interactions that provide insight into genetic networks. By dramatically increasing sample size, BB-QTL mapping demonstrates the potential of natural variants in high-powered QTL studies to reveal the highly polygenic, pleiotropic, and epistatic architecture of complex traits.

Modularity and selection of nectar traits in the evolution of the selfing syndrome in Ipomoea lacunosa (Convolvulaceae)

Although the evolution of the selfing syndrome often involves reductions in floral size, pollen and nectar, few studies of selfing syndrome divergence have examined nectar. We investigate whether nectar traits have evolved independently of other floral size traits in the selfing syndrome, whether nectar traits diverged due to drift or selection, and the extent to which quantitative trait locus (QTL) analyses predict genetic correlations. We use F5 recombinant inbred lines (RILs) generated from a cross between Ipomoea cordatotriloba and Ipomoea lacunosa. We calculate genetic correlations to identify evolutionary modules, test whether trait divergence was due to selection, identify QTLs and perform correlation analyses to evaluate how well QTL properties reflect genetic correlations. Nectar and floral size traits form separate evolutionary modules. Selection has acted to reduce nectar traits in the selfing I. lacunosa. Genetic correlations predicted from QTL properties are consistent with observed genetic correlations. Changes in floral traits associated with the selfing syndrome reflect independent evolution of at least two evolutionary modules: nectar and floral size traits. We also demonstrate directional selection on nectar traits, which is likely to be independent of selection on floral size traits. Our study also supports the expected mechanistic link between QTL properties and genetic correlations.

Divergent patterns of selection on metabolite levels and gene expression

Background

Natural selection can act on multiple genes in the same pathway, leading to polygenic adaptation. For example, adaptive changes were found to down-regulate six genes involved in ergosterol biosynthesis—an essential pathway targeted by many antifungal drugs—in some strains of the yeast Saccharomyces cerevisiae. However, the impact of this polygenic adaptation on metabolite levels was unknown. Here, we performed targeted mass spectrometry to measure the levels of eight metabolites in this pathway in 74 yeast strains from a genetic cross.

Results

Through quantitative trait locus (QTL) mapping we identified 19 loci affecting ergosterol pathway metabolite levels, many of which overlap loci that also impact gene expression within the pathway. We then used the recently developed v-test, which identified selection acting upon three metabolite levels within the pathway, none of which were predictable from the gene expression adaptation.

Conclusions

These data showed that effects of selection on metabolite levels were complex and not predictable from gene expression data. This suggests that a deeper understanding of metabolism is necessary before we can understand the impacts of even relatively straightforward gene expression adaptations on metabolic pathways.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01915-5.