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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #300974

Title: The challenges and importance of structural variation detection in livestock

item Bickhart, Derek
item Liu, Ge - George

Submitted to: Frontiers in Genetics
Publication Type: Review Article
Publication Acceptance Date: 1/31/2014
Publication Date: 2/18/2014
Citation: Bickhart, D.M., Liu, G. 2014. The challenges and importance of structural variation detection in livestock. Frontiers in Genetics. 5:37.

Interpretive Summary:

Technical Abstract: Recent studies in humans and other model organisms have demonstrated that structural variants (SVs) comprise a substantial proportion of variation among individuals of each species. Many of these variants have been linked to debilitating diseases in humans, thereby cementing the importance of refining methods for their detection. Despite progress in the field, reliable detection of SVs still remains a problem even for human subjects. Many of the underlying problems that make SVs difficult to detect in humans are amplified in livestock species, whose lower quality genome assemblies and incomplete gene annotation can often give rise to false positive SV discoveries. Regardless of the challenges, SV detection is just as important for livestock researchers as it is for human researchers, given that several productive traits and diseases have been linked to Copy Number Variations (CNVs) in cattle, sheep and pig. Already, there is evidence that many beneficial SVs have been artificially selected in livestock such as a duplication of the ASIP gene that causes white coat color in sheep. In this review, we will list current SV and CNV discoveries in livestock and discuss the problems that hinder routine discovery and tracking of these polymorphisms. We will also discuss the putative impacts of selective breeding on CNV and SV frequencies and mention how SV genotyping could be used in the future to improve genetic selection.