Patrick J. Monnahan

Epistasis Is a Major Determinant of the Additive Genetic Variance in Mimulus guttatus

The influence of genetic interactions (epistasis) on the genetic variance of quantitative traits is a major unresolved problem relevant to medical, agricultural, and evolutionary genetics. The additive genetic component is typically a high proportion of the total genetic variance in quantitative traits, despite that underlying genes must interact to determine phenotype. This study estimates direct and interaction effects for 11 pairs of Quantitative Trait Loci (QTLs) affecting floral traits within a single population of Mimulus guttatus. With estimates of all 9 genotypes for each QTL pair, we are able to map from QTL effects to variance components as a function of population allele frequencies, and thus predict changes in variance components as allele frequencies change. This mapping requires an analytical framework that properly accounts for bias introduced by estimation errors. We find that even with abundant interactions between QTLs, most of the genetic variance is likely to be additive. However, the strong dependency of allelic average effects on genetic background implies that epistasis is a major determinant of the additive genetic variance, and thus, the population’s ability to respond to selection.

A High-Resolution Genetic Map of Yellow Monkeyflower Identifies Chemical Defense QTLs and Recombination Rate Variation

Genotyping-by-sequencing methods have vastly improved the resolution and accuracy of genetic linkage maps by increasing both the number of marker loci as well as the number of individuals genotyped at these loci. Using restriction-associated DNA sequencing, we construct a dense linkage map for a panel of recombinant inbred lines derived from a cross between divergent ecotypes of Mimulus guttatus. We used this map to estimate recombination rate across the genome and to identify quantitative trait loci for the production of several secondary compounds (PPGs) of the phenylpropanoid pathway implicated in defense against herbivores. Levels of different PPGs are correlated across recombinant inbred lines suggesting joint regulation of the phenylpropanoid pathway. However, the three quantitative trait loci identified in this study each act on a distinct PPG. Finally, we map three putative genomic inversions differentiating the two parental populations, including a previously characterized inversion that contributes to life-history differences between the annual/perennial ecotypes.

Sun skink landscape genomics: assessing the roles of micro‐evolutionary processes in shaping genetic and phenotypic diversity across a heterogeneous and fragmented landscape

Incorporating genomic data sets into landscape genetic analyses allows for powerful insights into population genetics, explicitly geographical correlates of selection, and morphological diversification of organisms across the geographical template. Here, we utilize an integrative approach to examine gene flow and detect selection, and we relate these processes to genetic and phenotypic population differentiation across South‐East Asia in the common sun skink, Eutropis multifasciata. We quantify the relative effects of geographic and ecological isolation in this system and find elevated genetic differentiation between populations from island archipelagos compared to those on the adjacent South‐East Asian continent, which is consistent with expectations concerning landscape fragmentation in island archipelagos. We also identify a pattern of isolation by distance, but find no substantial effect of ecological/environmental variables on genetic differentiation. To assess whether morphological conservatism in skinks may result from stabilizing selection on morphological traits, we perform FST–PST comparisons, but observe that results are highly dependent on the method of comparison. Taken together, this work provides novel insights into the manner by which micro‐evolutionary processes may impact macro‐evolutionary scale biodiversity patterns across diverse landscapes, and provide genomewide confirmation of classic predictions from biogeographical and landscape ecological theory.

A genomic selection component analysis characterizes migration-selection balance.

The genetic differentiation of populations in response to local selection pressures has long been studied by evolutionary biologists, but key details about the process remain obscure. How rapidly can local adaptation evolve, how extensive is the process across the genome, and how strong are the opposing forces of natural selection and gene flow? Here, we combine direct measurement of survival and reproduction with whole‐genome genotyping of a plant species (Mimulus guttatus) that has recently invaded a novel habitat (the Quarry population). We renovate the classic selection component method to accommodate genomic data and observe selection at SNPs throughout the genome. SNPs showing viability selection in Quarry exhibit elevated divergence from neighboring populations relative to neutral SNPs. We also find that nonsignificant SNPs exhibit a subtle, but still significant, change in allele frequency toward neighboring populations, a predicted effect of gene flow. Given that the Quarry population is most probably only 30–40 generations old, the alleles conferring local advantage are almost certainly older than the population itself. Thus, local adaptation owes to the recruitment of standing genetic variation.

A Bayesian method for the joint estimation of outcrossing rate and inbreeding depression

The population outcrossing rate (t) and adult inbreeding coefficient (F) are key parameters in mating system evolution. The magnitude of inbreeding depression as expressed in the field can be estimated given t and F via the method of Ritland (1990). For a given total sample size, the optimal design for the joint estimation of t and F requires sampling large numbers of families (100–400) with fewer offspring (1–4) per family. Unfortunately, the standard inference procedure (MLTR) yields significantly biased estimates for t and F when family sizes are small and maternal genotypes are unknown (a common occurrence when sampling natural populations). Here, we present a Bayesian method implemented in the program BORICE (Bayesian Outcrossing Rate and Inbreeding Coefficient Estimation) that effectively estimates t and F when family sizes are small and maternal genotype information is lacking. BORICE should enable wider use of the Ritland approach for field-based estimates of inbreeding depression. As proof of concept, we estimate t and F in a natural population of Mimulus guttatus. In addition, we describe how individual maternal inbreeding histories inferred by BORICE may prove useful in studies of inbreeding and its consequences.

Gene expression plasticity resulting from parental leaf damage in Mimulus guttatus

Leaf trichome density in Mimulus guttatus can be altered by the parental environment. In this study, we compared global gene expression patterns in progeny of damaged and control plants. Significant differences in gene expression probably explain the observed trichome response, and identify additional responsive pathways. Using whole transcriptome RNA sequencing, we estimated differential gene expression between isogenic seedlings whose parents had, or had not, been subject to leaf damage. We identified over 900 genes that were differentially expressed in response to parental wounding. These genes clustered into groups involved in cell wall and cell membrane development, stress response pathways, and secondary metabolism. Gene expression is modified as a consequence of the parental environment in a targeted way that probably alters multiple developmental pathways, and may increase progeny fitness if they experience environments similar to that of their parents.

Naturally segregating loci exhibit epistasis for fitness

The extent to which gene interaction or epistasis contributes to fitness variation within populations remains poorly understood, despite its importance to a myriad of evolutionary questions. Here, we report a multi-year field study estimating fitness of Mimulus guttatus genetic lines in which pairs of naturally segregating loci exist in an otherwise uniform background. An allele at QTL x5b—a locus originally mapped for its effect on flower size—positively affects survival if combined with one genotype at quantitative trait locus x10a (aa) but has negative effects when combined with the other genotypes (Aa and AA). The viability differences between genotypes parallel phenotypic differences for the time and node at which a plant flowers. Viability is negatively correlated with fecundity across genotypes, indicating antagonistic pleiotropy for fitness components. This trade-off reduces the genetic variance for total fitness relative to the individual fitness components and thus may serve to maintain variation. Additionally, we find that the effects of each locus and their interaction often vary with the environment.

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.

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

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

A genomic selection component analysis characterizes migration-selection balance: A GENOMIC SELECTION ANALYSIS

The genetic differentiation of populations in response to local selection pressures has long been studied by evolutionary biologists, but key details about the process remain obscure. How rapidly can local adaptation evolve, how extensive is the process across the genome, and how strong are the opposing forces of natural selection and gene flow? Here, we combine direct measurement of survival and reproduction with whole‐genome genotyping of a plant species (Mimulus guttatus) that has recently invaded a novel habitat (the Quarry population). We renovate the classic selection component method to accommodate genomic data and observe selection at SNPs throughout the genome. SNPs showing viability selection in Quarry exhibit elevated divergence from neighboring populations relative to neutral SNPs. We also find that nonsignificant SNPs exhibit a subtle, but still significant, change in allele frequency toward neighboring populations, a predicted effect of gene flow. Given that the Quarry population is most probably only 30–40 generations old, the alleles conferring local advantage are almost certainly older than the population itself. Thus, local adaptation owes to the recruitment of standing genetic variation.