Massive haplotypes underlie ecotypic differentiation in sunflowers.

Species often include multiple ecotypes that are adapted to different environments1. However, it is unclear how ecotypes arise and how their distinctive combinations of adaptive alleles are maintained despite hybridization with non-adapted populations2-4. Here, by resequencing 1,506 wild sunflowers from 3 species (Helianthus annuus, Helianthus petiolaris and Helianthus argophyllus), we identify 37 large (1-100 Mbp in size), non-recombining haplotype blocks that are associated with numerous ecologically relevant traits, as well as soil and climate characteristics. Limited recombination in these haplotype blocks keeps adaptive alleles together, and these regions differentiate sunflower ecotypes. For example, haplotype blocks control a 77-day difference in flowering between ecotypes of the silverleaf sunflower H. argophyllus (probably through deletion of a homologue of FLOWERING LOCUS T (FT)), and are associated with seed size, flowering time and soil fertility in dune-adapted sunflowers. These haplotypes are highly divergent, frequently associated with structural variants and often appear to represent introgressions from other-possibly now-extinct-congeners. These results highlight a pervasive role of structural variation in ecotypic adaptation.

Elucidation of the mescaline biosynthetic pathway in peyote (Lophophora williamsii).

Peyote (Lophophora williamsii) is an entheogenic and medicinal cactus native to the Chihuahuan desert. The psychoactive and hallucinogenic properties of peyote are principally attributed to the phenethylamine derivative mescaline. Despite the isolation of mescaline from peyote over 120 years ago, the biosynthetic pathway in the plant has remained undiscovered. Here, we use a transcriptomics and homology-guided gene discovery strategy to elucidate a near-complete biosynthetic pathway from l-tyrosine to mescaline. We identified a cytochrome P450 that catalyzes the 3-hydroxylation of l-tyrosine to l-DOPA, a tyrosine/DOPA decarboxylase yielding dopamine, and four substrate-specific and regiospecific substituted phenethylamine O-methyltransferases. Biochemical assays with recombinant enzymes or functional analyses performed by feeding putative precursors to engineered yeast (Saccharomyces cerevisiae) strains expressing candidate peyote biosynthetic genes were used to determine substrate specificity, which served as the basis for pathway elucidation. Additionally, an N-methyltransferase displaying broad substrate specificity and leading to the production of N-methylated phenethylamine derivatives was identified, which could also function as an early step in the biosynthesis of tetrahydroisoquinoline alkaloids in peyote.

Conditionally Deleterious Mutation Load Accumulates in Genomic Islands of Local Adaptation but Can Be Purged with Sufficient Genotypic Redundancy.

AbstractLocal adaptation frequently evolves in patches or environments that are connected via migration. In these cases, genomic regions that are linked to a locally adapted locus experience reduced effective migration rates. Via individual-based simulations of a two-patch system, we show that this reduced effective migration results in the accumulation of conditionally deleterious mutations, but not universally deleterious mutations, adjacent to adaptive loci. When there is redundancy in the genetic basis of local adaptation (i.e., genotypic redundancy), turnover of locally adapted polymorphisms allows conditionally deleterious mutation load to be purged. The amount of mutational load that accumulates adjacent to locally adapted loci is dependent on redundancy, recombination rate, migration rate, population size, strength of selection, and the phenotypic effect size of adaptive alleles. Our results highlight the need to be cautious when interpreting patterns of local adaptation at the level of phenotype or fitness, as the genetic basis of local adaptation can be transient, and evolution may confer a degree of maladaptation to nonlocal environments.

Genetic architecture of disease resistance and tolerance in Douglas-fir trees.

Understanding the genetic basis of how plants defend against pathogens is important to monitor and maintain resilient tree populations. Swiss needle cast (SNC) and Rhabdocline needle cast (RNC) epidemics are responsible for major damage of forest ecosystems in North America. Here we investigate the genetic architecture of tolerance and resistance to needle cast diseases in Douglas-fir (Pseudotsuga menziesii) caused by two fungal pathogens: SNC caused by Nothophaeocryptopus gaeumannii, and RNC caused by Rhabdocline pseudotsugae. We performed case-control genome-wide association analyses and found disease resistance and tolerance in Douglas-fir to be polygenic and under strong selection. We show that stomatal regulation as well as ethylene and jasmonic acid pathways are important for resisting SNC infection, and secondary metabolite pathways play a role in tolerating SNC once the plant is infected. We identify a major transcriptional regulator of plant defense, ERF1, as the top candidate for RNC resistance. Our findings shed light on the highly polygenic architectures underlying fungal disease resistance and tolerance and have important implications for forestry and conservation as the climate changes.

How useful are genomic data for predicting maladaptation to future climate?

Methods using genomic information to forecast potential population maladaptation to climate change or new environments are becoming increasingly common, yet the lack of model validation poses serious hurdles toward their incorporation into management and policy. Here, we compare the validation of maladaptation estimates derived from two methods-Gradient Forests (GFoffset) and the risk of non-adaptedness (RONA)-using exome capture pool-seq data from 35 to 39 populations across three conifer taxa: two Douglas-fir varieties and jack pine. We evaluate sensitivity of these algorithms to the source of input loci (markers selected from genotype-environment associations [GEA] or those selected at random). We validate these methods against 2- and 52-year growth and mortality measured in independent transplant experiments. Overall, we find that both methods often better predict transplant performance than climatic or geographic distances. We also find that GFoffset and RONA models are surprisingly not improved using GEA candidates. Even with promising validation results, variation in model projections to future climates makes it difficult to identify the most maladapted populations using either method. Our work advances understanding of the sensitivity and applicability of these approaches, and we discuss recommendations for their future use.

Genome-wide shifts in climate-related variation underpin responses to selective breeding in a widespread conifer.

Locally adapted temperate tree populations exhibit genetic trade-offs among climate-related traits that can be exacerbated by selective breeding and are challenging to manage under climate change. To inform climatically adaptive forest management, we investigated the genetic architecture and impacts of selective breeding on four climate-related traits in 105 natural and 20 selectively bred lodgepole pine populations from western Canada. Growth, cold injury, growth initiation, and growth cessation phenotypes were tested for associations with 18,600 single-nucleotide polymorphisms (SNPs) in natural populations to identify "positive effect alleles" (PEAs). The effects of artificial selection for faster growth on the frequency of PEAs associated with each trait were quantified in breeding populations from different climates. Substantial shifts in PEA proportions and frequencies were observed across many loci after two generations of selective breeding for height, and responses of phenology-associated PEAs differed strongly among climatic regions. Extensive genetic overlap was evident among traits. Alleles most strongly associated with greater height were often associated with greater cold injury and delayed phenology, although it is unclear whether potential trade-offs arose directly from pleiotropy or indirectly via genetic linkage. Modest variation in multilocus PEA frequencies among populations was associated with large phenotypic differences and strong climatic gradients, providing support for assisted gene flow polices. Relationships among genotypes, phenotypes, and climate in natural populations were maintained or strengthened by selective breeding. However, future adaptive phenotypes and assisted gene flow may be compromised if selective breeding further increases the PEA frequencies of SNPs involved in adaptive trade-offs among climate-related traits.

Comparative Gene Expression Analysis Reveals Mechanism of Pinus contorta Response to the Fungal Pathogen Dothistroma septosporum.

Many conifers have distributions that span wide ranges in both biotic and abiotic conditions, but the basis of response to biotic stress has received much less attention than response to abiotic stress. In this study, we investigated the gene expression response of lodgepole pine (Pinus contorta) to attack by the fungal pathogen Dothistroma septosporum, which causes Dothistroma needle blight, a disease that has caused severe climate-related outbreaks in northwestern British Columbia. We inoculated tolerant and susceptible pines with two D. septosporum isolates and analyzed the differentially expressed genes (DEGs), differential exon usage, and coexpressed gene modules using RNA-sequencing data. We found a rapid and strong transcriptomic response in tolerant lodgepole pine samples inoculated with one D. septosporum isolate, and a late and weak response in susceptible samples inoculated with another isolate. We mapped 43 of the DEG- or gene module-identified genes to the reference plant-pathogen interaction pathway deposited in the Kyoto Encyclopedia of Genes and Genomes database. These genes are present in PAMP-triggered and effector-triggered immunity pathways. Genes comprising pathways and gene modules had signatures of strong selective constraint, while the highly expressed genes in tolerant samples appear to have been favored by selection to counterattack the pathogen. We identified candidate resistance genes that may respond to D. septosporum effectors. Taken together, our results show that gene expression response to D. septosporum infection in lodgepole pine varies both among tree genotypes and pathogen strains and involves both known candidate genes and a number of genes with previously unknown functions.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Neopinone isomerase is involved in codeine and morphine biosynthesis in opium poppy.

The isomerization of neopinone to codeinone is a critical step in the biosynthesis of opiate alkaloids in opium poppy. Previously assumed to be spontaneous, the process is in fact catalyzed enzymatically by neopinone isomerase (NISO). Without NISO the primary metabolic products in the plant, in engineered microbes and in vitro are neopine and neomorphine, which are structural isomers of codeine and morphine, respectively. Inclusion of NISO in yeast strains engineered to convert thebaine to natural or semisynthetic opiates dramatically enhances formation of the desired products at the expense of neopine and neomorphine accumulation. Along with thebaine synthase, NISO is the second member of the pathogenesis-related 10 (PR10) protein family recently implicated in the enzymatic catalysis of a presumed spontaneous conversion in morphine biosynthesis.

Quantifying how constraints limit the diversity of viable routes to adaptation.

Convergent adaptation occurs at the genome scale when independently evolving lineages use the same genes to respond to similar selection pressures. These patterns of genetic repeatability provide insights into the factors that facilitate or constrain the diversity of genetic responses that contribute to adaptive evolution. A first step in studying such factors is to quantify the observed amount of repeatability relative to expectations under a null hypothesis. Here, we formulate a novel index to quantify the constraints driving the observed amount of repeated adaptation in pairwise contrasts based on the hypergeometric distribution, and then generalize this for simultaneous analysis of multiple lineages. This index is explicitly based on the probability of observing a given amount of repeatability by chance under a given null hypothesis and is readily compared among different species and types of trait. We also formulate an index to quantify the effective proportion of genes in the genome that have the potential to contribute to adaptation. As an example of how these indices can be used to draw inferences, we assess the amount of repeatability observed in existing datasets on adaptation to stress in yeast and climate in conifers. This approach provides a method to test a wide range of hypotheses about how different kinds of factors can facilitate or constrain the diversity of genetic responses observed during adaptive evolution.

Variation in recombination rate affects detection of outliers in genome scans under neutrality.

Genome scans can potentially identify genetic loci involved in evolutionary processes such as local adaptation and gene flow. Here, we show that recombination rate variation across a neutrally evolving genome gives rise to mixed sampling distributions of mean FST ( FST^ ), a common population genetic summary statistic. In particular, we show that in regions of low recombination the distribution of FST^ estimates has more variance and a longer tail than in more highly recombining regions. Determining outliers from the genome-wide distribution without taking local recombination rate into consideration may therefore increase the frequency of false positives in low recombination regions and be overly conservative in more highly recombining ones. We perform genome scans on simulated and empirical Drosophila melanogaster data sets and, in both cases, find patterns consistent with this neutral model. Similar patterns are observed for other summary statistics used to capture variation in the coalescent process. Linked selection, particularly background selection, is often invoked to explain heterogeneity in FST^ across the genome, but here we point out that even under neutrality, statistical artefacts can arise due to variation in recombination rate. Our results highlight a flaw in the design of genome-scan studies and suggest that without estimates of local recombination rate, interpreting the genomic landscape of any summary statistic that captures variation in the coalescent process will be very difficult.

Purifying selection does not drive signatures of convergent local adaptation of lodgepole pine and interior spruce.

BACKGROUND: Lodgepole pine (Pinus contorta) and interior spruce (Picea glauca, Picea engelmannii, and their hybrids) are distantly related conifer species. Previous studies identified 47 genes containing variants associated with environmental variables in both species, providing evidence of convergent local adaptation. However, if the intensity of purifying selection varies with the environment, clines in nucleotide diversity could evolve through linked (background) selection that would yield allele frequency-environment signatures resembling local adaptation. If similar geographic patterns in the strength of purifying selection occur in these species, this could result in the convergent signatures of local adaptation, especially if the landscape of recombination is conserved. In the present study, we investigated whether spatially/environmentally varying purifying selection could give rise to the convergent signatures of local adaptation that had previously reported. RESULTS: We analyzed 86 lodgepole pine and 50 interior spruce natural populations spanning heterogeneous environments in western Canada where previous analyses had found signatures of convergent local adaptation. We estimated nucleotide diversity and Tajima's D for each gene within each population and calculated the strength of correlations between nucleotide diversity and environmental variables. Overall, these estimates in the genes with previously identified convergent local adaptation signatures had no similar pattern between pine and spruce. Clines in nucleotide diversity along environmental variables were found for interior spruce, but not for lodgepole pine. In spruce, genes with convergent adaption signatures showed a higher strength of correlations than genes without convergent adaption signatures, but there was no such disparity in pine, which suggests the pattern in spruce may have arisen due to a combination of selection and hybridization. CONCLUSIONS: The results rule out purifying/background selection as a driver of convergent local adaption signatures in lodgepole pine and interior spruce.

Unpacking Conditional Neutrality: Genomic Signatures of Selection on Conditionally Beneficial and Conditionally Deleterious Mutations.

It is common to look for signatures of local adaptation in genomes by identifying loci with extreme levels of allele frequency divergence among populations. This approach to finding genes associated with local adaptation often assumes antagonistic pleiotropy, wherein alternative alleles are strongly favored in alternative environments. Conditional neutrality has been proposed as an alternative to antagonistic pleiotropy, but conditionally neutral polymorphisms are transient, and it is unclear how much outlier signal would be maintained under different forms of conditional neutrality. Here, we use individual-based simulations and a simple analytical heuristic to show that a pattern that mimics local adaptation at the phenotypic level, where each genotype has the highest fitness in its home environment, can be produced by the accumulation of mutations that are neutral in their home environment and deleterious in nonlocal environments. Because conditionally deleterious mutations likely arise at a rate many times higher than conditionally beneficial mutations, they can have a significant cumulative effect on fitness even when individual effect sizes are small. We show that conditionally deleterious mutations driving nonlocal maladaptation may be undetectable by even the most powerful genome scans, as differences in allele frequency between populations are typically small. We also explore the evolutionary effects of conditionally beneficial mutations and find that they can maintain significant signals of local adaptation, and they would be more readily detectable than conditionally deleterious mutations using conventional genome scan approaches. We discuss implications for interpreting outcomes of transplant experiments and genome scans that are used to study the genetic basis of local adaptation.

Mating system impacts the genetic architecture of adaptation to heterogeneous environments.

Self-fertilisation has consequences for variation across the genome as it reduces effective population size, effect recombination rates and pollen flow, with implications for local adaptation. We conducted simulations of divergent stabilising selection on a quantitative trait with drift, pollen flow, mutation, recombination and different outcrossing rates. We quantified trait divergence and the genetic architecture of adaptation. We conducted an FST outlier analysis to identify candidate loci and quantified the impact of mating system on detectability. Selfing promoted trait divergence mainly through reductions in pollen flow. Moreover, trait architecture became more diffuse with selfing. Average effect size of trait loci was lower, while the number of loci, and their clustering distance increased. The genetic architecture of selfers was also more diffuse than outcrossers for equivalent migration rates. However, when deleterious alleles were included, architectures became more concentrated in selfers, likely to be because of reductions in population size caused by mutational meltdown and impacts of background selection on Ne . Our simulations demonstrate that mating system has important impacts on adaptive divergence of traits and the genetic landscape underlying that divergence. Selfing has a significant effect on detectability of regions of the genome important for adaptation because of neutral divergence and diffuse trait architecture.

Effect of migration and environmental heterogeneity on the maintenance of quantitative genetic variation: a simulation study.

The paradox of high genetic variation observed in traits under stabilizing selection is a long-standing problem in evolutionary theory, as mutation rates appear too low to explain observed levels of standing genetic variation under classic models of mutation-selection balance. Spatially or temporally heterogeneous environments can maintain more standing genetic variation within populations than homogeneous environments, but it is unclear whether such conditions can resolve the above discrepancy between theory and observation. Here, we use individual-based simulations to explore the effect of various types of environmental heterogeneity on the maintenance of genetic variation (VA ) for a quantitative trait under stabilizing selection. We find that VA is maximized at intermediate migration rates in spatially heterogeneous environments and that the observed patterns are robust to changes in population size. Spatial environmental heterogeneity increased variation by as much as 10-fold over mutation-selection balance alone, whereas pure temporal environmental heterogeneity increased variance by only 45% at max. Our results show that some combinations of spatial heterogeneity and migration can maintain considerably more variation than mutation-selection balance, potentially reconciling the discrepancy between theoretical predictions and empirical observations. However, given the narrow regions of parameter space required for this effect, this is unlikely to provide a general explanation for the maintenance of variation. Nonetheless, our results suggest that habitat fragmentation may affect the maintenance of VA and thereby reduce the adaptive capacity of populations.

Bioinformatically predicted deleterious mutations reveal complementation in the interior spruce hybrid complex.

BACKGROUND: Mutation load is expected to be reduced in hybrids via complementation of deleterious alleles. While local adaptation of hybrids confounds phenotypic tests for reduced mutation load, it may be possible to assess variation in load by analyzing the distribution of putatively deleterious alleles. Here, we use this approach in the interior spruce (Picea glauca x P. engelmannii) hybrid complex, a group likely to suffer from high mutation load and in which hybrids exhibit local adaptation to intermediate conditions. We used PROVEAN to bioinformatically predict whether non-synonymous alleles are deleterious, based on conservation of the position and abnormality of the amino acid change. RESULTS: As expected, we found that predicted deleterious alleles were at lower average allele frequencies than alleles not predicted to be deleterious. We were unable to detect a phenotypic effect on juvenile growth rate of the many rare alleles predicted to be deleterious. Both the proportion of alleles predicted to be deleterious and the proportion of loci homozygous for predicted deleterious alleles were higher in P. engelmannii (Engelmann spruce) than in P. glauca (white spruce), due to higher diversity and frequencies of rare alleles in Engelmann. Relative to parental species, the proportion of alleles predicted to be deleterious was intermediate in hybrids, and the proportion of loci homozygous for predicted deleterious alleles was lowest. CONCLUSION: Given that most deleterious alleles are recessive, this suggests that mutation load is reduced in hybrids due to complementation of deleterious alleles. This effect may enhance the fitness of hybrids.

Expression Divergence Is Correlated with Sequence Evolution but Not Positive Selection in Conifers.

The evolutionary and genomic determinants of sequence evolution in conifers are poorly understood, and previous studies have found only limited evidence for positive selection. Using RNAseq data, we compared gene expression profiles to patterns of divergence and polymorphism in 44 seedlings of lodgepole pine (Pinus contorta) and 39 seedlings of interior spruce (Picea glauca × engelmannii) to elucidate the evolutionary forces that shape their genomes and their plastic responses to abiotic stress. We found that rapidly diverging genes tend to have greater expression divergence, lower expression levels, reduced levels of synonymous site diversity, and longer proteins than slowly diverging genes. Similar patterns were identified for the untranslated regions, but with some exceptions. We found evidence that genes with low expression levels had a larger fraction of nearly neutral sites, suggesting a primary role for negative selection in determining the association between evolutionary rate and expression level. There was limited evidence for differences in the rate of positive selection among genes with divergent versus conserved expression profiles and some evidence supporting relaxed selection in genes diverging in expression between the species. Finally, we identified a small number of genes that showed evidence of site-specific positive selection using divergence data alone. However, estimates of the proportion of sites fixed by positive selection (α) were in the range of other plant species with large effective population sizes suggesting relatively high rates of adaptive divergence among conifers.

The evolution of genomic islands by increased establishment probability of linked alleles.

Genomic islands are clusters of loci with elevated divergence that are commonly found in population genomic studies of local adaptation and speciation. One explanation for their evolution is that linkage between selected alleles confers a benefit, which increases the establishment probability of new mutations that are linked to existing locally adapted polymorphisms. Previous theory suggested there is only limited potential for the evolution of islands via this mechanism, but involved some simplifying assumptions that may limit the accuracy of this inference. Here, we extend previous analytical approaches to study the effect of linkage on the establishment probability of new mutations and identify parameter regimes that are most likely to lead to evolution of islands via this mechanism. We show how the interplay between migration and selection affects the establishment probability of linked vs. unlinked alleles, the expected maximum size of genomic islands, and the expected time required for their evolution. Our results agree with previous studies, suggesting that this mechanism alone is unlikely to be a general explanation for the evolution of genomic islands. However, this mechanism could occur more readily if there were other pre-adaptations to reduce local rates of recombination or increase the local density of mutational targets within the region of the island. We also show that island formation via erosion following secondary contact is much more rapid than island formation from de novo mutations, suggesting that this mechanism may be more likely.

Genomic rearrangements and the evolution of clusters of locally adaptive loci.

Numerous studies of ecological genetics have found that alleles contributing to local adaptation sometimes cluster together, forming "genomic islands of divergence." Divergence hitchhiking theory posits that these clusters evolve by the preferential establishment of tightly linked locally adapted mutations, because such linkage reduces the rate that recombination breaks up locally favorable combinations of alleles. Here, I use calculations based on previously developed analytical models of divergence hitchhiking to show that very few clustered mutations should be expected in a single bout of adaptation, relative to the number of unlinked mutations, suggesting that divergence hitchhiking theory alone may often be insufficient to explain empirical observations. Using individual-based simulations that allow for the transposition of a single genetic locus from one position on a chromosome to another, I then show that tight clustering of the loci involved in local adaptation tends to evolve on biologically realistic time scales. These results suggest that genomic rearrangements may often be an important component of local adaptation and the evolution of genomic islands of divergence. More generally, these results suggest that genomic architecture and functional neighborhoods of genes may be actively shaped by natural selection in heterogeneous environments. Because small-scale changes in gene order are relatively common in some taxa, comparative genomic studies could be coupled with studies of adaptation to explore how commonly such rearrangements are involved in local adaptation.

Local Adaptation by Alleles of Small Effect.

Population genetic models predict that alleles with small selection coefficients may be swamped by migration and will not contribute to local adaptation. But if most alleles contributing to standing variation are of small effect, how does local adaptation proceed? Here I review predictions of population and quantitative genetic models and use individual-based simulations to illustrate how the architecture of local adaptation depends on the genetic redundancy of the trait, the maintenance of standing genetic variation (V(G)), and the susceptibility of alleles to swamping. Even when population genetic models predict swamping for individual alleles, considerable local adaptation can evolve at the phenotypic level if there is sufficient V(G). However, in such cases the underlying architecture of divergence is transient: F(ST) is low across all loci, and no locus makes an important contribution for very long. Because this kind of local adaptation is mainly due to transient frequency changes and allelic covariances, these architectures will be difficult--if not impossible--to detect using current approaches to studying the genomic basis of adaptation. Even when alleles are large and resistant to swamping, architectures can be highly transient if genetic redundancy and mutation rates are high. These results suggest that drift can play a critical role in shaping the architecture of local adaptation, both through eroding V(G) and affecting the rate of turnover of polymorphisms with redundant phenotypic effects.

Evolution of Quantitative Traits under a Migration-Selection Balance: When Does Skew Matter?

Quantitative-genetic models of differentiation under migration-selection balance often rely on the assumption of normally distributed genotypic and phenotypic values. When a population is subdivided into demes with selection toward different local optima, migration between demes may result in asymmetric, or skewed, local distributions. Using a simplified two-habitat model, we derive formulas without a priori assuming a Gaussian distribution of genotypic values, and we find expressions that naturally incorporate higher moments, such as skew. These formulas yield predictions of the expected divergence under migration-selection balance that are more accurate than models assuming Gaussian distributions, which illustrates the importance of incorporating these higher moments to assess the response to selection in heterogeneous environments. We further show with simulations that traits with loci of large effect display the largest skew in their distribution at migration-selection balance.