Identification of key contributors to increase phasing accuracy in complex population structures

• Knowledge of the genetic contribution of individuals is essential to select informative individuals for genotype imputation. Based on the Eigen Value Decomposition (EVD) of a relationship matrix we describe a novel approach to determine the genetic contribution of individuals within populations. The approach was applied and validated in four disparate datasets including simulated population, a highly structured experimental sheep population and two large complex pedigreed populations namely horse and cattle. In the simulated and sheep datasets, we identified all known key contributors within the populations, whilst in the horse and cattle dataset we applied the method to select small reference populations that increased phasing accuracy. Compared to commonly applied strategies to select informative individuals for genotype imputation including the identification of marginal gene contributions (PEDIG) and the optimization of genetic relatedness (REL) the selection of key contributors provided the highest phasing accuracies within the selected reference populations. Therefore, this method provides a valuable complement to common applied tools to select individuals for re-sequencing.

Ämnesord

LANTBRUKSVETENSKAPER  -- Bioteknologi med applikationer på växter och djur -- Genetik och förädling inom lantbruksvetenskap (hsv//swe)

AGRICULTURAL SCIENCES  -- Agricultural Biotechnology -- Genetics and Breeding in Agricultural Sciences (hsv//eng)

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