Linking How Horses Run to Their Alleles

A paper in PLoS Genetics has identified a selection of genetic variants that clearly distinguish horses breeds that pace (running with the two legs on the same side move together) and those that trot (opposite front and back move together). Thought no physiological role has been demonstrated for the these mutations, yet, they appear to be good candidates for connecting single nucleotide changes to discrete and clearly recognizable inherited differences in behavior—and maybe a step towards understanding instincts.

McCoy, et al. (2019) Identification and validation of genetic variants predictive of gait in standardbred horses. PLoS Genetics

Author summary

Certain horse breeds have been developed over generations specifically for the ability to perform alternative patterns of movement, or gaits. Current understanding of the genetic basis for these gaits is limited to one known mutation apparently necessary, but not sufficient, for explaining variability in “gaitedness.” The Standardbred breed includes two distinct groups, trotters, which exhibit a two-beat gait in which the opposite forelimb and hind limb move together, and pacers, which exhibit an alternative two-beat gait where the legs on the same side of the body move together. Our long-term objective is to identify variants underlying the ability of certain Standardbreds to pace. In this study, we were able to identify several regions of the genome highly associated with pacing and, within these regions, a number of specific highly associated variants. Although the biological function of these variants has yet to be determined, we developed a model based on seven variants that was > 99% accurate in predicting whether an individual was a pacer or a trotter in two independent populations. This predictive model can be used by horse owners to make breeding and training decisions related to this economically important trait, and by scientists interested in understanding the biology of coordinated gait development.

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Population Structure: A Key Concept for Understanding Genetic Variation

It is common for articles to claim that “the gene for” some trait or disease has been identified. Usually they actually mean that an association has been found between an uncommon genetic variant found in, or near, a gene and some trait or disease. These kinds of articles are becoming increasingly common because Genome-Wide Association Studies (GWAS) are becoming cheaper and more common. Though GWAS yield important insights their results can be misleading because ancestral relationships between individuals in the study can create signals that can be misinterpreted as association with the trait being studied. This phenomenon is very powerful and one reason why it is important to have a diverse group of individuals in any genetic study. Underlying ancestral relationships are known as “population structure” and serious thought is required to ensure that it doesn’t skew GWAS results. The paper below is a scientific review article (in an excellent journal with exceptional authors) and not exactly easy reading, but it was written for a broad audience and worth considering the next time you see an article discussing the identification of “the genes for” something or other, even if it appears in Genome-Media.

-RPR

Population Genetics: Why structure matters

Abstract

Great care is needed when interpreting claims about the genetic basis of human variation based on data from genome-wide association studies.

Main text

Human height is the classic example of a quantitative trait: its distribution is continuous, presumably because it is influenced by variation at a very large number of genes, most with a small effect (Fisher, 1918). Yet height is also strongly affected by the environment: average height in many countries increased during the last century and the children of immigrants are often taller than relatives in their country of origin – in both cases presumably due to changing diet and other environmental factors (Cavalli-Sforza and Bodmer, 1971; Grasgruber et al., 2016; NCD Risk Factor Collaboration, 2016). This makes it very difficult to determine the cause of geographic patterns for height, such as the ‘latitudinal cline’ seen in Europe (Figure 1).

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Population genomic and evolutionary modeling analyses find QTL relevant to global health (BMC Genomics)

Population genomic and evolutionary modeling analyses reveal a single major QTL for ivermectin drug resistance in the pathogenic nematode, Haemonchus contortus

Stephen R. Doyle†Email authorView ORCID ID profile, Christopher J. R. Illingworth†, Roz Laing, David J. Bartley, Elizabeth Redman, Axel Martinelli, Nancy Holroyd, Alison A. Morrison, Andrew Rezansoff, Alan Tracey, Eileen Devaney, Matthew Berriman, Neil Sargison, James A. Cotton,and John S. Gilleard

BMC Genomics (Research Article)

Infections with helminths cause an enormous disease burden in billions of animals and plants worldwide. Large scale use of anthelmintics has driven the evolution of resistance in a number of species that infect livestock and companion animals, and there are growing concerns regarding the reduced efficacy in some human-infective helminths. Understanding the mechanisms by which resistance evolves is the focus of increasing interest; robust genetic analysis of helminths is challenging, and although many candidate genes have been proposed, the genetic basis of resistance remains poorly resolved.

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