Selection is a basic principle of evolution. Many approaches and studies have identified DNA mutations rapidly selected to high frequencies, which leave pronounced signatures on the surrounding sequence (selective sweeps). However, for many important complex, quantitative traits, selection does not leave these intense signatures. Instead, hundreds or thousands of loci experience small changes in allele frequencies, a process called polygenic selection. We know that directional selection and local adaptation are actively changing genomes; however we have been unable to identify the genomic loci responding to this polygenic, complex selection. Here we show that the use of novel dependent variables in linear mixed models (which allow us to account for population structure, relatedness, inbreeding) identify complex, polygenic selection and local adaptation. Thousands of loci are responding to artificial directional selection and hundreds of loci have evidence of local adaptation. While advanced reproduction and genomic technologies are increasing the rate of directional selection, local adaptation is being lost. In a changing climate, the loss of local adaptation may be especially problematic. These selection mapping approaches can be used in evolutionary, model, and agriculture contexts.

Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent variables to map signatures of selection on complex traits and local adaptation. We identify 207 genomic loci associated with an animal’s birth date, representing ongoing selection for monogenic and polygenic traits. Additionally, hundreds of additional loci are associated with continuous and discrete environments, providing evidence for historical local adaptation. These candidate loci highlight the nervous system’s possible role in local adaptation. While advanced technologies have increased the rate of directional selection in cattle, it has likely been at the expense of historically generated local adaptation, which is especially problematic in changing climates. When applied to large, diverse cattle datasets, these selection mapping methods provide an insight into how selection on complex traits continually shapes the genome. Further, understanding the genomic loci implicated in adaptation may help us breed more adapted and efficient cattle, and begin to understand the basis for mammalian adaptation, especially in changing climates. These selection mapping approaches help clarify selective forces and loci in evolutionary, model, and agricultural contexts.

Background Heat stress and fescue toxicosis caused by ingesting tall fescue infected with the endophytic fungus Epichloë coenophiala represent two of the most prevalent stressors to beef cattle in the United States and cost the beef industry millions of dollars each year. The rate at which a beef cow sheds her winter coat early in the summer is an indicator of adaptation to heat and an economically relevant trait in temperate or subtropical parts of the world. Furthermore, research suggests that early-summer hair shedding may reflect tolerance to fescue toxicosis, since vasoconstriction induced by fescue toxicosis limits the ability of an animal to shed its winter coat. Both heat stress and fescue toxicosis reduce profitability partly via indirect maternal effects on calf weaning weight. Here, we developed parameters for routine genetic evaluation of hair shedding score in American Angus cattle, and identified genomic loci associated with variation in hair shedding score via genome-wide association analysis (GWAA). Results Hair shedding score was moderately heritable (h2 = 0.34 to 0.40), with different repeatability estimates between cattle grazing versus not grazing endophyte-infected tall fescue. Our results suggest modestly negative genetic and phenotypic correlations between a dam’s hair shedding score (lower score is earlier shedding) and the weaning weight of her calf, which is one metric of performance. Together, these results indicate that economic gains can be made by using hair shedding score breeding values to select for heat-tolerant cattle. GWAA identified 176 variants significant at FDR < 0.05. Functional enrichment analyses using genes that were located within 50 kb of these variants identified pathways involved in keratin formation, prolactin signalling, host-virus interaction, and other biological processes. Conclusions This work contributes to a continuing trend in the development of genetic evaluations for environmental adaptation. Our results will aid beef cattle producers in selecting more sustainable and climate-adapted cattle, as well as enable the development of similar routine genetic evaluations in other breeds.

The Caribbean is a genetically diverse region with heterogeneous admixture compositions influenced by local island ecologies, migrations, colonial conflicts, and demographic histories. The Commonwealth of Dominica is a mountainous island in the Lesser Antilles historically known to harbor communities with unique patterns of migration, mixture, and isolation. This community-based population genetic study adds biological evidence to inform post-colonial narrative histories in a Dominican horticultural village. High density single nucleotide polymorphism data paired with a previously compiled genealogy provide the first genome-wide insights on genetic ancestry and population structure in Dominica. We assessed family-based clustering, inferred global ancestry, and dated recent admixture by implementing the fastSTRUCTURE clustering algorithm, modeling graph-based migration with TreeMix, assessing patterns of linkage disequilibrium decay with ALDER, and visualizing data from Dominica with Human Genome Diversity Panel references. These analyses distinguish family-based genetic structure from variation in African, European, and indigenous Amerindian admixture proportions, and analyses of linkage disequilibrium decay estimate admixture dates 5–6 generations (~160 years) ago. African ancestry accounts for the largest mixture components, followed by European and then indigenous components; however, our global ancestry inferences are consistent with previous mitochondrial, Y chromosome, and ancestry marker data from Dominica that show uniquely higher proportions of indigenous ancestry and lower proportions of African ancestry relative to known admixture in other French- and English-speaking Caribbean islands. Our genetic results support local narratives about the community’s history and founding, which indicate that newly emancipated people settled in the steep, dense vegetation along Dominica’s eastern coast in the mid-19th century. Strong genetic signals of post-colonial admixture and family-based structure highlight the localized impacts of colonial forces and island ecologies in this region, and more data from other groups are needed to more broadly inform on Dominica’s complex history and present diversity.

Recently, interest has increased in augmenting current national scale cattle evaluations with precision genetic predictions tailored to specific environmental conditions. Some efforts to develop environmentally-aware predictions have focused on the use of novel phenotypes and others on the incorporation of genotype-by-environment interactions (GxE) to existing methodologies. Cattle and other mammal species molt thick winter coats at the beginning of 07 in order to prepare for the oncoming stress of warmer weather. In warm climates, cattle that shed their winter coat earlier and more completely have an adaptive advantage over later-shedding herd-mates, and previous work has demonstrated the relationship between seasonal coat shedding and production traits. Using a novel trait (early 07 hair shedding score) we develop a genetic evaluation for heat tolerance. We find that hair shedding score is moderately heritable and controlled by genomic loci involved in light sensing and metabolism. Additionally, we explore the degree to which GxE interactions across discrete ecoregions affect pre-weaning growth in American Angus cattle. We find evidence for GxE in the maternal but not direct effect of weaning weight, particularly in heat-stressed environments. Together, these efforts will help beef cattle breeders match genetics to the environmental conditions in which they are best suited.

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Cattle poorly adapted to their environment result in lost revenue and jeopardize the stability of the food supply. Genomic data now allows us to rigorously analyze adaptations and avoid the generation of animals that will not thrive. We used selection scans for local adaptation, genotype-by-environment genome-wide association analyses, creation of hair shedding genomic predictions and environmental region-specific genomic predictions of growth traits to characterize and predict local adaptation in beef cattle. Analyzing ~40,000 cattle from three breed associations with ~850,000 high-accuracy imputed SNPs, we used novel selection mapping methods to identify genomic loci responsible for adaptation. We identify 19 different loci (harboring 24 annotated genes) as responding to selection to local adaptation. In cooperation with 74 producers across the United States, over 12,000 cattle were scored on a scale of 1–5 for the early-summer hair shedding phenotype in 2016, 2017, and 2018. Participating cattle were genotyped using the GGP-F250 SNP panel developed by the University of Missouri, which contains ~170,000 candidate functional variants and ~30,000 variants in common with beef cattle industry standard genotyping assays. Genomic breeding values were generated with a repeated records model using these phenotypes. Further, we identified loci with large allele substitution effects for hair shedding. When local adaptations exist, ranking animals using a regional genetic evaluation will be different from national cattle evaluations. We developed region-specific genomic predictions using a multivariate model in which phenotypes from different regions were fit as separate dependent variables. Genetic correlations between regions were moderate, indicating substantial re-ranking between environmental regions. These genomic predictions will allow rapid identification of cattle best suited to an environment.

The GeneMax (GMX) Advantage test, developed by Zoetis, uses approximately 50,000 single nucleotide polymorphisms (SNP) to predict the genomic potential of a commercial Angus heifer. Genetic predictions are provided for Calving Ease Maternal, Weaning Weight, Heifer Pregnancy, Milk, Mature Weight, Dry Matter Intake, Carcass Weight, Marbling, and Yield. Indices of economically important traits are estimated on an index score (1-100 scale) and are divided into three indices; Cow Advantage index, Feeder Advantage index, and Total Advantage index. The indices provide a genomic prediction of the profitability of the cow's calves. Therefore, test results can inform selection and culling decisions made by commercial beef cattle producers. To measure the accuracy of the trait predictions, data from commercial Angus females and their progeny at the University of Missouri Thompson Research Center was utilized to analyze weaning weight, milk, marbling, fat, ribeye area, and carcass weight. Progeny phenotypic data was matched to the respective dam, then the cow's genomic predictions were compared to the calf's age-adjusted phenotypes using correlation and linear models. All tested GeneMax scores of the dam were significantly correlated with and predicted calf performance. Our predicted effect sizes, except for fat thickness, were similar to those reported by Zoetis. In conclusion, the GeneMax Advantage test accurately ranks animals based on their genetic merit and is an effective selection tool in commercial cowherds.