Candidate pathway association and genome-wide association approaches reveal alternative genetic architectures of carotenoid content in cultivated sunflower (Helianthus annuus)

Premise

The explosion of available genomic data poses significant opportunities and challenges for genome-wide association studies. Current approaches via linear mixed models (LMM) are straightforward but prevent flexible assumptions of an a priori genomic architecture, while Bayesian sparse LMMs (BSLMMs) allow this flexibility. Complex traits, such as specialized metabolites, are subject to various hierarchical effects, including gene regulation, enzyme efficiency, and the availability of reactants.

Methods

To identify alternative genetic architectures, we examined the genetic architecture underlying the carotenoid content of an association mapping panel of Helianthus annuus individuals using multiple BSLMM and LMM frameworks.

Results

The LMMs of genome-wide single-nucleotide polymorphisms (SNPs) identified a single transcription factor responsible for the observed variations in the carotenoid content; however, a BSLMM of the SNPs with the bottom 1% of effect sizes from the results of the LMM identified multiple biologically relevant quantitative trait loci (QTLs) for carotenoid content external to the known (annotated) carotenoid pathway. A candidate pathway analysis (CPA) suggested a β-carotene isomerase to be the enzyme with the highest impact on the observed carotenoid content within the carotenoid pathway.

Discussion

While traditional LMM approaches suggested a single unknown transcription factor associated with carotenoid content variation in sunflower petals, BSLMM proposed several QTLs with interpretable biological relevance to this trait. In addition, the CPA allowed for the dissection of the regulatory vs. biosynthetic genetic architectures underlying this metabolic trait.

A polygenic architecture with habitat-dependent effects underlies ecological differentiation in Silene

Ecological differentiation can drive speciation but it is unclear how the genetic architecture of habitat-dependent fitness contributes to lineage divergence. We investigated the genetic architecture of cumulative flowering, a fitness component, in second-generation hybrids between Silene dioica and Silene latifolia transplanted into the natural habitat of each species. We used reduced-representation sequencing and Bayesian sparse linear mixed models (BSLMMs) to analyze the genetic control of cumulative flowering in each habitat. Our results point to a polygenic architecture of cumulative flowering. Allelic effects were mostly beneficial or deleterious in one habitat and neutral in the other. Positive-effect alleles often were derived from the native species, whereas negative-effect alleles, at other loci, tended to originate from the non-native species. We conclude that ecological differentiation is governed and maintained by many loci with small, habitat-dependent effects consistent with conditional neutrality. This pattern may result from differences in selection targets in the two habitats and from environmentally dependent deleterious load. Our results further suggest that selection for native alleles and against non-native alleles acts as a barrier to gene flow between species.

The short-term, genome-wide effects of indirect selection deserve study: A response to Charlesworth and Jensen (2022)

We recently published a paper quantifying the genome-wide consequences of natural selection, including the effects of indirect selection due to the correlation of genetic regions (neutral or selected) with directly selected regions (Gompert et al., 2022). In their critique of our paper, Charlesworth and Jensen (2022) make two main points: (i) indirect selection is equivalent to hitchhiking and thus well documented (i.e., our results are not novel) and (ii) that we do not demonstrate the source of linkage disequilibrium (LD) between SNPs and the Mel-Stripe locus in the Timema cristinae experiment we analyse. As we discuss in detail below, neither of these are substantial criticisms of our work.

Natural selection drives genome-wide evolution via chance genetic associations

Understanding selection's impact on the genome is a major theme in biology. Functionally neutral genetic regions can be affected indirectly by natural selection, via their statistical association with genes under direct selection. The genomic extent of such indirect selection, particularly across loci not physically linked to those under direct selection, remains poorly understood, as does the time scale at which indirect selection occurs. Here, we use field experiments and genomic data in stick insects, deer mice and stickleback fish to show that widespread statistical associations with genes known to affect fitness cause many genetic loci across the genome to be impacted indirectly by selection. This includes regions physically distant from those directly under selection. Then, focusing on the stick insect system, we show that statistical associations between SNPs and other unknown, causal variants result in additional indirect selection in general and specifically within genomic regions of physically linked loci. This widespread indirect selection necessarily makes aspects of evolution more predictable. Thus, natural selection combines with chance genetic associations to affect genome-wide evolution across linked and unlinked loci and even in modest-sized populations. This process has implications for the application of evolutionary principles in basic and applied science.

Allele frequency divergence reveals ubiquitous influence of positive selection in Drosophila

Resolving the role of natural selection is a basic objective of evolutionary biology. It is generally difficult to detect the influence of selection because ubiquitous non-selective stochastic change in allele frequencies (genetic drift) degrades evidence of selection. As a result, selection scans typically only identify genomic regions that have undergone episodes of intense selection. Yet it seems likely such episodes are the exception; the norm is more likely to involve subtle, concurrent selective changes at a large number of loci. We develop a new theoretical approach that uncovers a previously undocumented genome-wide signature of selection in the collective divergence of allele frequencies over time. Applying our approach to temporally resolved allele frequency measurements from laboratory and wild Drosophila populations, we quantify the selective contribution to allele frequency divergence and find that selection has substantial effects on much of the genome. We further quantify the magnitude of the total selection coefficient (a measure of the combined effects of direct and linked selection) at a typical polymorphic locus, and find this to be large (of order 1%) even though most mutations are not directly under selection. We find that selective allele frequency divergence is substantially elevated at intermediate allele frequencies, which we argue is most parsimoniously explained by positive-not negative-selection. Thus, in these populations most mutations are far from evolving neutrally in the short term (tens of generations), including mutations with neutral fitness effects, and the result cannot be explained simply as an ongoing purging of deleterious mutations.

A population-genomic approach for estimating selection on polygenic traits in heterogeneous environments

Strong selection can cause rapid evolutionary change, but temporal fluctuations in the form, direction and intensity of selection can limit net evolutionary change over longer time periods. Fluctuating selection could affect molecular diversity levels and the evolution of plasticity and ecological specialization. Nonetheless, this phenomenon remains understudied, in part because of analytical limitations and the general difficulty of detecting selection that does not occur in a consistent manner. Herein, I fill this analytical gap by presenting an approximate Bayesian computation (ABC) method to detect and quantify fluctuating selection on polygenic traits from population genomic time-series data. I propose a model for environment-dependent phenotypic selection. The evolutionary genetic consequences of selection are then modelled based on a genotype-phenotype map. Using simulations, I show that the proposed method generates accurate and precise estimates of selection when the generative model for the data is similar to the model assumed by the method. The performance of the method when applied to an evolve-and-resequence study of host adaptation in the cowpea seed beetle (Callosobruchus maculatus) was more idiosyncratic and depended on specific analytical choices. Despite some limitations, these results suggest the proposed method provides a powerful approach to connect the causes of (variable) selection to traits and genome-wide patterns of evolution. Documentation and open-source computer software (fsabc) implementing this method are available from github (https://github.com/zgompert/fsabc.git).

Phenotypic expression of floral traits in hybrid zones provides insights into their genetic architecture

Information on the genetic architecture of phenotypic traits is helpful for constructing and testing models of the ecoevolutionary dynamics of natural populations. For plant groups with long life cycles there is a lack of line cross experiments that can unravel the genetic architecture of loci underlying quantitative traits. To fill this gap, we propose the use of variation for phenotypic traits expressed in natural hybrid zones as an alternative approach. We used data from orchid hybrid zones and compared expected and observed patterns of phenotypic trait expression in different early-generation hybrid classes identified by molecular genetic markers. We found evidence of additivity, dominance, and epistatic interactions for different phenotypic traits. We discuss the potential of this approach along with its limitations and suggest that it may represent a realistic way to gain an initial insight into the heritability and genomic architecture of traits in organismal groups with complex life history, such as orchids and many others.

Evolution of strong reproductive isolation in plants: broad-scale patterns and lessons from a perennial model group

Many recent studies have addressed the mechanisms operating during the early stages of speciation, but surprisingly few studies have tested theoretical predictions on the evolution of strong reproductive isolation (RI). To help address this gap, we first undertook a quantitative review of the hybrid zone literature for flowering plants in relation to reproductive barriers. Then, using Populus as an exemplary model group, we analysed genome-wide variation for phylogenetic tree topologies in both early- and late-stage speciation taxa to determine how these patterns may be related to the genomic architecture of RI. Our plant literature survey revealed variation in barrier complexity and an association between barrier number and introgressive gene flow. Focusing on Populus, our genome-wide analysis of tree topologies in speciating poplar taxa points to unusually complex genomic architectures of RI, consistent with earlier genome-wide association studies. These architectures appear to facilitate the 'escape' of introgressed genome segments from polygenic barriers even with strong RI, thus affecting their relationships with recombination rates. Placed within the context of the broader literature, our data illustrate how phylogenomic approaches hold great promise for addressing the evolution and temporary breakdown of RI during late stages of speciation. This article is part of the theme issue 'Towards the completion of speciation: the evolution of reproductive isolation beyond the first barriers'.

Natural selection on the Arabidopsis thaliana genome in present and future climates

Through the lens of evolution, climate change is an agent of natural selection that forces populations to change and adapt, or face extinction. However, current assessments of the risk of biodiversity associated with climate change¹ do not typically take into account how natural selection influences populations differently depending on their genetic makeup². Here we make use of the extensive genome information that is available for Arabidopsis thaliana and measure how manipulation of the amount of rainfall affected the fitness of 517 natural Arabidopsis lines that were grown in Spain and Germany. This allowed us to directly infer selection along the genome³. Natural selection was particularly strong in the hot-dry location in Spain, where 63% of lines were killed and where natural selection substantially changed the frequency of approximately 5% of all genome-wide variants. A significant portion of this climate-driven natural selection of variants was predictable from signatures of local adaptation (R² = 29-52%), as genetic variants that were found in geographical areas with climates more similar to the experimental sites were positively selected. Field-validated predictions across the species range indicated that Mediterranean and western Siberian populations-at the edges of the environmental limits of this species-currently experience the strongest climate-driven selection. With more frequent droughts and rising temperatures in Europe⁴, we forecast an increase in directional natural selection moving northwards from the southern end of Europe, putting many native A. thaliana populations at evolutionary risk.

Rare genetic variation and balanced polymorphisms are important for survival in global change conditions

Standing genetic variation is important for population persistence in extreme environmental conditions. While some species may have the capacity to adapt to predicted average future global change conditions, the ability to survive extreme events is largely unknown. We used single-generation selection experiments on hundreds of thousands of Strongylocentrotus purpuratus sea urchin larvae generated from wild-caught adults to identify adaptive genetic variation responsive to moderate (pH 8.0) and extreme (pH 7.5) low-pH conditions. Sequencing genomic DNA from pools of larvae, we identified consistent changes in allele frequencies across replicate cultures for each pH condition and observed increased linkage disequilibrium around selected loci, revealing selection on recombined standing genetic variation. We found that loci responding uniquely to either selection regime were at low starting allele frequencies while variants that responded to both pH conditions (11.6% of selected variants) started at high frequencies. Loci under selection performed functions related to energetics, pH tolerance, cell growth and actin/cytoskeleton dynamics. These results highlight that persistence in future conditions will require two classes of genetic variation: common, pH-responsive variants maintained by balancing selection in a heterogeneous environment, and rare variants, particularly for extreme conditions, that must be maintained by large population sizes.

Adaptive introgression: a plant perspective

Introgression is emerging as an important source of novel genetic variation, alongside standing variation and mutation. It is adaptive when such introgressed alleles are maintained by natural selection. Recently, there has been an explosion in the number of studies on adaptive introgression. In this review, we take a plant perspective centred on four lines of evidence: (i) introgression, (ii) selection, (iii) phenotype and (iv) fitness. While advances in genomics have contributed to our understanding of introgression and porous species boundaries (task 1), and the detection of signatures of selection in introgression (task 2), the investigation of adaptive introgression critically requires links to phenotypic variation and fitness (tasks 3 and 4). We also discuss the conservation implications of adaptive introgression in the face of climate change. Adaptive introgression is particularly important in rapidly changing environments, when standing genetic variation and mutation alone may only offer limited potential for adaptation. We conclude that clarifying the magnitude and fitness effects of introgression with improved statistical techniques, coupled with phenotypic evidence, has great potential for conservation and management efforts.

Genomic transitions during host race and species formation

Darwin recognized species as discontinuous, yet considered them to be formed by an incremental process of natural selection. Recent theoretical work on 'genome-wide congealing' is bridging this gap between the gradualism of divergent selection and rapid genome-wide divergence, particularly during ecological speciation-with-gene-flow. Host races and species of phytophagous insects, displaying a spectrum of divergence and gene flow among member taxa, provide model systems for testing predicted non-linear transitions from 'genic' divergence at a few uncoupled loci to 'genomic' divergence with genome-wide coupling of selected loci and strong reproductive isolation. Integrating across natural history, genomics, and evolutionary theory, emerging research suggests a tipping point from 'genic' to 'genomic' divergence between host races and species, during both sympatric speciation and secondary contact.

Genomic Differentiation during Speciation-with-Gene-Flow: Comparing Geographic and Host-Related Variation in Divergent Life History Adaptation in Rhagoletis pomonella

A major goal of evolutionary biology is to understand how variation within populations gets partitioned into differences between reproductively isolated species. Here, we examine the degree to which diapause life history timing, a critical adaptation promoting population divergence, explains geographic and host-related genetic variation in ancestral hawthorn and recently derived apple-infesting races of Rhagoletis pomonella. Our strategy involved combining experiments on two different aspects of diapause (initial diapause intensity and adult eclosion time) with a geographic survey of genomic variation across four sites where apple and hawthorn flies co-occur from north to south in the Midwestern USA. The results demonstrated that the majority of the genome showing significant geographic and host-related variation can be accounted for by initial diapause intensity and eclosion time. Local genomic differences between sympatric apple and hawthorn flies were subsumed within broader geographic clines; allele frequency differences within the races across the Midwest were two to three-fold greater than those between the races in sympatry. As a result, sympatric apple and hawthorn populations displayed more limited genomic clustering compared to geographic populations within the races. The findings suggest that with reduced gene flow and increased selection on diapause equivalent to that seen between geographic sites, the host races may be recognized as different genotypic entities in sympatry, and perhaps species, a hypothesis requiring future genomic analysis of related sibling species to R. pomonella to test. Our findings concerning the way selection and geography interplay could be of broad significance for many cases of earlier stages of divergence-with-gene flow, including (1) where only modest increases in geographic isolation and the strength of selection may greatly impact genetic coupling and (2) the dynamics of how spatial and temporal standing variation is extracted by selection to generate differences between new and discrete units of biodiversity.

Navigating the Interface Between Landscape Genetics and Landscape Genomics

As next-generation sequencing data become increasingly available for non-model organisms, a shift has occurred in the focus of studies of the geographic distribution of genetic variation. Whereas landscape genetics studies primarily focus on testing the effects of landscape variables on gene flow and genetic population structure, landscape genomics studies focus on detecting candidate genes under selection that indicate possible local adaptation. Navigating the transition between landscape genomics and landscape genetics can be challenging. The number of molecular markers analyzed has shifted from what used to be a few dozen loci to thousands of loci and even full genomes. Although genome scale data can be separated into sets of neutral loci for analyses of gene flow and population structure and putative loci under selection for inference of local adaptation, there are inherent differences in the questions that are addressed in the two study frameworks. We discuss these differences and their implications for study design, marker choice and downstream analysis methods. Similar to the rapid proliferation of analysis methods in the early development of landscape genetics, new analytical methods for detection of selection in landscape genomics studies are burgeoning. We focus on genome scan methods for detection of selection, and in particular, outlier differentiation methods and genetic-environment association tests because they are the most widely used. Use of genome scan methods requires an understanding of the potential mismatches between the biology of a species and assumptions inherent in analytical methods used, which can lead to high false positive rates of detected loci under selection. Key to choosing appropriate genome scan methods is an understanding of the underlying demographic structure of study populations, and such data can be obtained using neutral loci from the generated genome-wide data or prior knowledge of a species' phylogeographic history. To this end, we summarize recent simulation studies that test the power and accuracy of genome scan methods under a variety of demographic scenarios and sampling designs. We conclude with a discussion of additional considerations for future method development, and a summary of methods that show promise for landscape genomics studies but are not yet widely used.

Evolution as an ecosystem process: insights from genomics

Evolution is a fundamental ecosystem process. The study of genomic variation of organisms can not only improve our understanding of evolutionary processes, but also of contemporary and future ecosystem dynamics. We argue that integrative research between the fields of genomics and ecosystem ecology could generate new insights. Specifically, studies of biodiversity and ecosystem functioning, evolutionary rescue, and eco-evolutionary dynamics could all benefit from information about variation in genome structure and the genetic architecture of traits, whereas genomic studies could benefit from information about the ecological context of evolutionary dynamics. We propose new ways to help link research on functional genomic diversity with (reciprocal) interactions between phenotypic evolution and ecosystem change. Despite numerous challenges, we anticipate that the wealth of genomic data being collected on natural populations will improve our understanding of ecosystems.

The Genomic Architecture of Flowering Time Varies Across Space and Time in Mimulus guttatus

The degree to which genomic architecture varies across space and time is central to the evolution of genomes in response to natural selection. Bulked-segregant mapping combined with pooled sequencing provides an efficient means to estimate the effect of genetic variants on quantitative traits. We develop a novel likelihood framework to identify segregating variation within multiple populations and generations while accommodating estimation error on a sample- and SNP-specific basis. We use this method to map loci for flowering time within natural populations of Mimulus guttatus, collecting the early- and late-flowering plants from each of three neighboring populations and two consecutive generations. Structural variants, such as inversions, and genes from multiple flowering-time pathways exhibit the strongest associations with flowering time. We find appreciable variation in genetic effects on flowering time across both time and space; the greatest differences evident between populations, where numerous factors (environmental variation, genomic background, and private polymorphisms) likely contribute to heterogeneity. However, the changes across years within populations clearly identify genotype-by-environment interactions as an important influence on flowering time variation.