Genes Of Large Effect Research Articles

Linking plant genes to arthropod community dynamics: Current progress and future challenges.

Plant genetic variation can play a key role in shaping ecological communities. Prior work investigated the effects of coarse-grain variation among plant genotypes on their diverse arthropod communities. Several recent studies, however, have leveraged the boom of genomic resources to study how genome-wide plant variation influences associated communities. These studies have demonstrated that the effects of plant genomic variation are not just detectable but can be important drivers of arthropod communities in natural ecosystems. Field common gardens and lab-based mesocosm experiments are also revealing candidate genes that have large effects on arthropod communities. While we highlight these exciting results, we also discuss key challenges to address in future research. We argue that a major hurdle lies in the integration of genomic tools with hierarchical models of species communities (HMSC). HMSC are generative models that provide the opportunity to not only better understand the processes underlying community change, but to also predict community dynamics. We also advocate for future research to apply models of genomic prediction to explore the genetic architecture of arthropod community phenotypes. We hypothesize that this genetic architecture will follow an exponential distribution, where a few genes of large effect, but also many genes of small effect, contribute to variation in arthropod communities. The next generation of studies linking plant genes to community dynamics will require interdisciplinary collaborations to build truly predictive models of plant genetic and arthropod community change.

A complex mechanism translating variation of a simple genetic architecture into alternative life histories

Understanding the processes that link genotype to phenotype is a central challenge in biology. Despite progress in discovering genes associated with ecologically relevant traits, a poor understanding of the processes and functions via which molecules mediate evolutionary differences leaves us critically far from linking proximate and ultimate causes of evolution. This knowledge gap is particularly large in multifaceted phenotypes of ecological relevance such as life histories where multiple traits covary and influence fitness. In Atlantic salmon (Salmo salar), variation in a key life-history trait, maturation age, is largely linked to the transcription cofactor vestigial-like 3 (vgll3). Here, we show that despite this simple genetic architecture, vgll3 genotype influences maturation age through a complex regulatory mechanism whereby it controls the expression of diverse pubertal signaling pathways. Using a multiomic approach in salmon testes, we show that the vgll3 genotype conferring early maturity up-regulates key genes controlling androgen production, cellular energy and adiposity, and TGF-β signaling, thereby increasing the likelihood of earlier pubertal initiation. By mapping VGLL3 regulatory elements we further show its interaction with distinct transcription factors in a genotype-dependent manner, thus coordinating differential activation of regulatory pathways. This study reveals the proximate mechanisms through which a genetically simple association leads to functionally complex molecular differences in a spectrum of cellular traits, thus explaining the molecular basis of pleiotropy in a large-effect gene. Our results indicate that evolution in correlated phenotypes, as exemplified by alternative life history strategies, can be dictated by the function of major life-history genes.

Transcriptome-based prediction for polygenic traits in rice using different gene subsets

BackgroundTranscriptome-based prediction of complex phenotypes is a relatively new statistical method that links genetic variation to phenotypic variation. The selection of large-effect genes based on a priori biological knowledge is beneficial for predicting oligogenic traits; however, such a simple gene selection method is not applicable to polygenic traits because causal genes or large-effect loci are often unknown. Here, we used several gene-level features and tested whether it was possible to select a gene subset that resulted in better predictive ability than using all genes for predicting a polygenic trait.ResultsUsing the phenotypic values of shoot and root traits and transcript abundances in leaves and roots of 57 rice accessions, we evaluated the predictive abilities of the transcriptome-based prediction models. Leaf transcripts predicted shoot phenotypes, such as plant height, more accurately than root transcripts, whereas root transcripts predicted root phenotypes, such as crown root length, more accurately than leaf transcripts. Furthermore, we used the following three features to train the prediction model: (1) tissue specificity of the transcripts, (2) ontology annotations, and (3) co-expression modules for selecting gene subsets. Although models trained by a gene subset often resulted in lower predictive abilities than the model trained by all genes, some gene subsets showed improved predictive ability. For example, using genes expressed in roots but not in leaves, the predictive ability for crown root diameter was improved by more than 10% (R2 = 0.59 when using all genes; R2 = 0.66, using 1,554 root-specifically expressed genes). Similarly, genes annotated as “gibberellic acid sensitivity” showed higher predictive ability than using all genes for root dry weight.ConclusionsOur results highlight both the possibility and difficulty of selecting an appropriate gene subset to predict polygenic traits from transcript abundance, given the current biological knowledge and information. Further integration of multiple sources of information, as well as improvements in gene characterization, may enable the selection of an optimal gene set for the prediction of polygenic phenotypes.

Exome-wide association analysis identifies novel risk loci for alcohol-associated hepatitis.

Alcohol-associated hepatitis (AH) is a clinically severe, acute disease that afflicts only a fraction of patients with alcohol use disorder (AUD). Genomic studies of alcohol-associated cirrhosis (AC) have identified several genes of large effect, but the genetic and environmental factors that lead to AH and AC, and their degree of genetic overlap, remain largely unknown. This study aims to identify genes and genetic variation that contribute to the development of AH. Exome-sequencing of patients with AH (N=784) and heavy drinking controls (N=951) identified exome-wide significant association for AH at PNPLA3, as previously observed for AC in GWAS, although with a much lower effect-size. SNPs of large effect-size at ICOSLG (Chr 21) and TOX4/RAB2B (Chr 14), were also exome-wide significant. ICOSLG encodes a co-stimulatory signal for T-cell proliferation and cytokine secretion and induces B-cell proliferation and differentiation. TOX4 was previously implicated in diabetes and immune system function. Other genes previously implicated in AC did not strongly contribute to AH, and the only prominently implicated (but not exome wide significant) gene overlapping with AUD was ADH1B. Polygenic signals for AH were observed in both common and rare variant analysis and identified genes with roles associated with inflammation. This study has identified two new genes of high effect size with a previously unknown contribution to ALD, and highlights both the overlap in etiology between liver diseases, and the unique origins of AH.

Variable parallelism in the genomic basis of age at maturity across spatial scales in Atlantic Salmon.

Complex traits often exhibit complex underlying genetic architectures resulting from a combination of evolution from standing variation, hard and soft sweeps, and alleles of varying effect size. Increasingly, studies implicate both large-effect loci and polygenic patterns underpinning adaptation, but the extent that common genetic architectures are utilized during repeated adaptation is not well understood. Sea age or age at maturation represents a significant life history trait in Atlantic Salmon (Salmo salar), the genetic basis of which has been studied extensively in European Atlantic populations, with repeated identification of large-effect loci. However, the genetic basis of sea age within North American Atlantic Salmon populations remains unclear, as does the potential for a parallel trans-Atlantic genomic basis to sea age. Here, we used a large single-nucleotide polymorphism (SNP) array and low-coverage whole-genome resequencing to explore the genomic basis of sea age variation in North American Atlantic Salmon. We found significant associations at the gene and SNP level with a large-effect locus (vgll3) previously identified in European populations, indicating genetic parallelism, but found that this pattern varied based on both sex and geographic region. We also identified nonrepeated sets of highly predictive loci associated with sea age among populations and sexes within North America, indicating polygenicity and low rates of genomic parallelism. Despite low genome-wide parallelism, we uncovered a set of conserved molecular pathways associated with sea age that were consistently enriched among comparisons, including calcium signaling, MapK signaling, focal adhesion, and phosphatidylinositol signaling. Together, our results indicate parallelism of the molecular basis of sea age in North American Atlantic Salmon across large-effect genes and molecular pathways despite population-specific patterns of polygenicity. These findings reveal roles for both contingency and repeated adaptation at the molecular level in the evolution of life history 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.

EQTL Catalogue 2023: New datasets, X chromosome QTLs, and improved detection and visualisation of transcript-level QTLs.

The eQTL Catalogue is an open database of uniformly processed human molecular quantitative trait loci (QTLs). We are continuously updating the resource to further increase its utility for interpreting genetic associations with complex traits. Over the past two years, we have increased the number of uniformly processed studies from 21 to 31 and added X chromosome QTLs for 19 compatible studies. We have also implemented Leafcutter to directly identify splice-junction usage QTLs in all RNA sequencing datasets. Finally, to improve the interpretability of transcript-level QTLs, we have developed static QTL coverage plots that visualise the association between the genotype and average RNA sequencing read coverage in the region for all 1.7 million fine mapped associations. To illustrate the utility of these updates to the eQTL Catalogue, we performed colocalisation analysis between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. Although most GWAS loci colocalised both with eQTLs and transcript-level QTLs, we found that visual inspection could sometimes be used to distinguish primary splicing QTLs from those that appear to be secondary consequences of large-effect gene expression QTLs. While these visually confirmed primary splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases.

Detecting parallel polygenic adaptation to novel evolutionary pressure in wild populations: a case study in Atlantic cod (Gadus morhua).

Populations can adapt to novel selection pressures through dramatic frequency changes in a few genes of large effect or subtle shifts in many genes of small effect. The latter (polygenic adaptation) is expected to be the primary mode of evolution for many life-history traits but tends to be more difficult to detect than changes in genes of large effect. Atlantic cod (Gadus morhua) were subjected to intense fishing pressure over the twentieth century, leading to abundance crashes and a phenotypic shift toward earlier maturation across many populations. Here, we use spatially replicated temporal genomic data to test for a shared polygenic adaptive response to fishing using methods previously applied to evolve-and-resequence experiments. Cod populations on either side of the Atlantic show covariance in allele frequency change across the genome that are characteristic of recent polygenic adaptation. Using simulations, we demonstrate that the degree of covariance in allele frequency change observed in cod is unlikely to be explained by neutral processes or background selection. As human pressures on wild populations continue to increase, understanding and attributing modes of adaptation using methods similar to those demonstrated here will be important in identifying the capacity for adaptive responses and evolutionary rescue. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Polygenic architecture of rare coding variation across 394,783 exomes.

Both common and rare genetic variants influence complex traits and common diseases. Genome-wide association studies have identified thousands of common-variant associations, and more recently, large-scale exome sequencing studies have identified rare-variant associations in hundreds of genes1-3. However, rare-variant genetic architecture is not well characterized, and the relationship between common-variant and rare-variant architecture is unclear4. Here we quantify the heritability explained by the gene-wise burden of rare coding variants across 22 common traits and diseases in 394,783 UK Biobank exomes5. Rare coding variants (allele frequency < 1 × 10-3) explain 1.3% (s.e. = 0.03%) of phenotypic variance on average-much less than common variants-and most burden heritability is explained by ultrarare loss-of-function variants (allele frequency < 1 × 10-5). Common and rare variants implicate the same cell types, with similar enrichments, and they have pleiotropic effects on the same pairs of traits, with similar genetic correlations. They partially colocalize at individual genes and loci, but not to the same extent: burden heritability is strongly concentrated in significant genes, while common-variant heritability is more polygenic, and burden heritability is also more strongly concentrated in constrained genes. Finally, we find that burden heritability for schizophrenia and bipolar disorder6,7 is approximately 2%. Our results indicate that rare coding variants will implicate a tractable number of large-effect genes, that common and rare associations are mechanistically convergent, and that rare coding variants will contribute only modestly to missing heritability and population risk stratification.

Leveraging prior biological knowledge improves prediction of tocochromanols in maize grain.

With an essential role in human health, tocochromanols are mostly obtained by consuming seed oils; however, the vitamin E content of the most abundant tocochromanols in maize (Zea mays L.) grain is low. Several large-effect genes with cis-acting variants affecting messenger RNA (mRNA) expression are mostly responsible for tocochromanol variation in maize grain, with other relevant associated quantitative trait loci (QTL) yet to be fully resolved. Leveraging existing genomic and transcriptomic information for maize inbreds could improve prediction when selecting for higher vitamin E content. Here, we first evaluated a multikernel genomic best linear unbiased prediction (MK-GBLUP) approach for modeling known QTL in the prediction of nine tocochromanol grain phenotypes (12-21 QTL per trait) within and between two panels of 1,462 and 242 maize inbred lines. On average, MK-GBLUP models improved predictive abilities by 7.0-13.6% when compared with GBLUP. In a second approach with a subset of 545 lines from the larger panel, the highest average improvement in predictive ability relative to GBLUP was achieved with a multi-trait GBLUP model (15.4%) that had a tocochromanol phenotype and transcript abundances in developing grain for a few large-effect candidate causal genes (1-3 genes per trait) as multiple response variables. Taken together, our study illustrates the enhancement of prediction models when informed by existing biological knowledge pertaining to QTL and candidate causal genes.

The rapid appearance of homostyly in a cultivated distylous population of Primula forbesii.

Evolutionary breakdown from rigorous outbreeding to self-fertilization frequently occurs in angiosperms. Since the pollinators are not necessary, self-compatible populations often reduce investment in floral display characteristics and pollination reward. Primula forbesii is a biennial herb with distribution restricted to southwest China; it was initially a self-incompatible distylous species, but after 20 years of artificial domestication, homostyly appeared. This change in style provides an ideal material to explore the time required for plant mating systems to adapt to new environmental changes and test whether flower attraction has reduced following transitions to selfing. We did a survey in wild populations of P. forbesii where its seeds were originally collected 20 years ago and recorded the floral morph frequencies and morphologies. The floral morphologies, self-incompatibility, floral scent, and pollinator visitation between distyly and homostyly were compared in greenhouse. Floral morph frequencies of wild populations did not change, while the cultivated population was inclined to L-morph and produced homostyly. Evidence from stigma papillae and pollen size supports the hypothesis that the homostyly possibly originated from mutations of large effect genes in distylous linkage region. Transitions to self-compatible homostyly are accompanied by smaller corolla size, lower amounts of terpenoids, especially linalool and higher amounts of fatty acid derivatives. The main pollinators in the greenhouse were short-tongued Apis cerana. However, homostyly had reduced visiting frequency. The mating system of P. forbesii changed rapidly in just about 20 years of domestication, and our findings confirm the hypothesis that the transition to selfing is accompanied by decreased flower attraction.

376 Genetic Approaches to Improve Reproductive Performance in the U.S. Sheep Industry

Abstract The U.S. sheep industry has experienced many changes over the last 50 years, the most prominent being a 75% reduction in the national breeding ewe inventory. Wool now accounts for ~10% of enterprise returns compared to ~80% from the sale of market lambs. Most breeding objective work indicates greatest emphasis should be placed on traits associated with ewe reproductive efficiency [e.g., number of lambs born/weaned (NLB/NLW), lamb survival]. Still, average NLB across the U.S. (1.07 lambs/ewe) and within geographic regions (East = 1.13, Midwest = 1.25, West = 1.09, Southwest = 0.79 lambs/ewe) remains low. Several genetic technologies are available to improve reproductive performance. Introgression of large effect gene variants, such as those within BMPR-1B, have increased NLB by ~1.0 and ~1.5 lambs in heterozygous and homozygous ewes, respectively. However, without joint improvement in maternal ability and/or husbandry, advantages in NLW are less pronounced and few U.S. producers utilize such variants in practice. Reproductive efficiency traits present challenges in selection programs as they are lowly heritable (&amp;lt; 0.15) and sex-limited. Previous single-trait selection experiments had modest improvement in NLB (0.01 – 0.02 lambs/yr). Selection accuracy is greatly improved by including pedigree and/or genomic relationships when deriving estimated breeding values (EBV). Since 2000, NLW EBV have increased by 0.01 lambs/yr with concurrent improvement in direct (0.02 kg/yr) and maternal (0.04 kg/yr) weaning weight for Polypay flocks enrolled in the National Sheep Improvement Program (NSIP). Still, NSIP flocks represent &amp;lt; 1% of production-oriented U.S. flocks so considerable expansion is needed to realize within-breed genetic improvement at a national level. Perhaps most importantly, large differences in reproductive efficiency traits exist across breeds and should be utilized to a greater extent in strategic crossbreeding systems. Optimizing reproductive performance for specific production environments is essential for the sustainability of the U.S. sheep industry.

Genome-wide marker effect heterogeneity is associated with a large effect dormancy locus in winter malting barley.

Prediction of trait values in plant breeding populations typically relies on assumptions about marker effect homogeneity across populations. Evidence is presented for winter malting barley (Hordeum vulgare L.) germination traits that a single, causative, large-effect gene in the Seed dormancy 1 region on Chromosome 5H, HvAlaAT1 (Qsd1), leads to heterogeneous estimated marker effects genome wide between groups of otherwise related individuals carrying different Qsd1 alleles. This led to reduced prediction accuracy across alleles when a model was trained either on individuals carrying both alleles or one allele. Several genomic prediction models were tested to increase prediction accuracy within the Qsd1 allele groups. Small gains (5-12%) in prediction accuracy were realized using structured genomic best linear unbiased predictor models when information about the Qsd1 allele was used to stratify the population. We concluded that a single large-effect locus can lead to heterogeneous marker effects in the same breeding family. Variance partitioning based on large-effect loci can be used to inform best practices in designing genomic prediction models; however, there are likely few cases for which it may be practical to do this. For malting barley, if germination traits are highly associated with malting quality traits, then similar steps should be considered for malting quality trait prediction.

Inversion invasions: when the genetic basis of local adaptation is concentrated within inversions in the face of gene flow.

Across many species where inversions have been implicated in local adaptation, genomes often evolve to contain multiple, large inversions that arise early in divergence. Why this occurs has yet to be resolved. To address this gap, we built forward-time simulations in which inversions have flexible characteristics and can invade a metapopulation undergoing spatially divergent selection for a highly polygenic trait. In our simulations, inversions typically arose early in divergence, captured standing genetic variation upon mutation, and then accumulated many small-effect loci over time. Under special conditions, inversions could also arise late in adaptation and capture locally adapted alleles. Polygenic inversions behaved similarly to a single supergene of large effect and were detectable by genome scans. Our results show that characteristics of adaptive inversions found in empirical studies (e.g. multiple large, old inversions that are FST outliers, sometimes overlapping with other inversions) are consistent with a highly polygenic architecture, and inversions do not need to contain any large-effect genes to play an important role in local adaptation. By combining a population and quantitative genetic framework, our results give a deeper understanding of the specific conditions needed for inversions to be involved in adaptation when the genetic architecture is polygenic. This article is part of the theme issue 'Genomic architecture of supergenes: causes and evolutionary consequences'.

Clock-linked genes underlie seasonal migratory timing in a diurnal raptor.

Seasonal migration is a dynamic natural phenomenon that allows organisms to exploit favourable habitats across the annual cycle. While the morphological, physiological and behavioural changes associated with migratory behaviour are well characterized, the genetic basis of migration and its link to endogenous biological time-keeping pathways are poorly understood. Historically, genome-wide research has focused on genes of large effect, whereas many genes of small effect may work together to regulate complex traits like migratory behaviour. Here, we explicitly relax stringent outlier detection thresholds and, as a result, discover how multiple biological time-keeping genes are important to migratory timing in an iconic raptor species, the American kestrel (Falco sparverius). To validate the role of candidate loci in migratory timing, we genotyped kestrels captured across autumn migration and found significant associations between migratory timing and genetic variation in metabolic and light-input pathway genes that modulate biological clocks (top1, phlpp1, cpne4 and peak1). Further, we demonstrate that migrating individuals originated from a single panmictic source population, suggesting the existence of distinct early and late migratory genotypes (i.e. chronotypes). Overall, our results provide empirical support for the existence of a within-population-level polymorphism in genes underlying migratory timing in a diurnally migrating raptor.

The immediate costs and long-term benefits of assisted gene flow in large populations.

With the genetic health of many plant and animal populations deteriorating due to climate change outpacing adaptation, interventions, such as assisted gene flow (AGF), may provide genetic variation necessary for populations to adapt to climate change. We ran genetic simulations to mimic different AGF scenarios in large populations and measured their outcomes on population-level fitness to determine circumstances in which it is worthwhile to perform AGF. In the absence of inbreeding depression, AGF was beneficial within a few generations only when introduced genotypes had much higher fitness than local individuals and traits affecting fitness were controlled by a few genes of large effect. AGF was harmful over short periods (e.g., first ∼10-20 generations) if there was strong outbreeding depression or introduced deleterious genetic variation. When the adaptive trait was controlled by many loci of small effect, the benefits of AGF took over 10 generations to realize-potentially too long for most climate-related management scenarios. The genomic integrity of the recipient population typically remained intact following AGF; the amount of genetic material from the donor population usually constituted no more of the recipient population's genome than the fraction of the population introduced. Significant genomic turnover (e.g., >50% replacement) only occurred when the selective advantage of the adaptive trait and translocation fraction were extremely high. Our results will be useful when adaptive management is used to maintain the genetic health and productivity of large populations under climate change.

Coat score. A possible explanation for the zebuine selective sweep located on bovine chromosome 5: 47,670,001–48,100,000 bp

Over 65% of the world's cattle population resides in warm areas where heat stress conditions limit the breed of European taurine cattle. Composite breeds were developed to retain the main traits of both parental breeds. The skin plays a central role in animal response to heat stress. Research on the genetic architecture of skin traits has identified genes and regions related to warm resistance skin features. The aim of this study was to determine whether the indicine proportion accounted for coat type or whether there were genes of large effect segregating in Brangus. Bulls (n = 108) were genotyped using microarrays and their coat score and hair length were evaluated. Indicine-taurine genome-wide composition was estimated and GWAS was performed. Although significant correlations between indicine proportion and traits were not observed, four windows of SNPs on BTA4 and BTA5 explained more than 2% of the trait variance. The GWAS for coat score in summer showed the main peak on BTA5:46,941,446–48,030,219 bp, accounting for 4.65% of the variance. Our results suggest that the variation in coat score and undercoat hair length in Argentinian Brangus bulls is associated with the presence of some particular gene variants, rather than with the whole indicine genetic content.

Cortex cis-regulatory switches establish scale colour identity and pattern diversity in Heliconius.

In Heliconius butterflies, wing colour pattern diversity and scale types are controlled by a few genes of large effect that regulate colour pattern switches between morphs and species across a large mimetic radiation. One of these genes, cortex, has been repeatedly associated with colour pattern evolution in butterflies. Here we carried out CRISPR knockouts in multiple Heliconius species and show that cortex is a major determinant of scale cell identity. Chromatin accessibility profiling and introgression scans identified cis-regulatory regions associated with discrete phenotypic switches. CRISPR perturbation of these regions in black hindwing genotypes recreated a yellow bar, revealing their spatially limited activity. In the H. melpomene/timareta lineage, the candidate CRE from yellow-barred phenotype morphs is interrupted by a transposable element, suggesting that cis-regulatory structural variation underlies these mimetic adaptations. Our work shows that cortex functionally controls scale colour fate and that its cis-regulatory regions control a phenotypic switch in a modular and pattern-specific fashion.

Fine Mapping of a Major Pleiotropic QTL Associated with Sesamin and Sesamolin Variation in Sesame (Sesamum indicum L.).

Deciphering the genetic basis of quantitative agronomic traits is a prerequisite for their improvement. Herein, we identified loci governing the main sesame lignans, sesamin and sesamolin variation in a recombinant inbred lines (RILs, F8) population under two environments. The content of the two lignans in the seeds was investigated by HPLC. The sesamin and sesamolin contents ranged from 0.33 to 7.52 mg/g and 0.36 to 2.70 mg/g, respectively. In total, we revealed 26 QTLs on a linkage map comprising 424 SSR markers, including 16 and 10 loci associated with sesamin and sesamolin variation, respectively. Among them, qSmin_11.1 and qSmol_11.1 detected in both the two environments explained 67.69% and 46.05% of the phenotypic variation of sesamin and sesamolin, respectively. Notably, qSmin11-1 and qSmol11-1 were located in the same interval of 127–127.21 cM on LG11 between markers ZMM1776 and ZM918 and acted as a pleiotropic locus. Furthermore, two potential candidate genes (SIN_1005755 and SIN_1005756) at the same locus were identified based on comparative transcriptome analysis. Our results suggest the existence of a single gene of large effect that controls expression, both of sesamin and sesamolin, and provide genetic information for further investigation of the regulation of lignan biosynthesis in sesame.

Introgression between Sphyrapicus nuchalis and S. varius sapsuckers in a hybrid zone in west‐central Alberta

Studying species interactions at hybrid zones allows biologists to understand the forces that promote speciation. Hybridization among Sphyrapicus nuchalis, S. varius and S. ruber has long been acknowledged, and hybrid zones between S. nuchalis/S. ruber and S. varius/S. ruber have been characterized with both genetic and genomic data. Using a combination of next‐generation restriction site‐associated DNA sequencing (RAD‐Seq) and traditional genetic methods, we examined patterns of introgression in the poorly characterized S. nuchalis/S. varius contact zone; the two most similar species in the complex, though they are not each other's closest relatives. We found high introgression rates, with several early and many advanced generation hybrids along a 275 km stretch of Rocky Mountain foothill, pointing to a well‐established hybrid zone with hybrid individuals backcrossing with individuals from the parental species and each other. Plumage colouration in the hybrid zone was a relatively poor indicator of parental or hybrid status, which could be attributed to the possible involvement of few large effect genes.