Using sheep genomes from diverse U.S. breeds to identify missense variants in genes affecting fecundity

利用来自美国不同品种绵羊的基因组来识别影响繁殖力的基因中的错义变异

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Abstract

Background:  Access to sheep genome sequences significantly improves the chances of identifying genes that may influence the health, welfare, and productivity of these animals.   Methods:  A public, searchable DNA sequence resource for U.S. sheep was created with whole genome sequence (WGS) of 96 rams.  The animals shared minimal pedigree relationships and represent nine popular U.S. breeds and a composite line.  The genomes are viewable online with the user-friendly Integrated Genome Viewer environment, and may be used to identify and decode gene variants present in U.S. sheep. Results:  The genomes had a combined average read depth of 16, and an average WGS genotype scoring rate and accuracy exceeding 99%.  The utility of this resource was illustrated by characterizing three genes with 14 known coding variants affecting litter size in global sheep populations: growth and differentiation factor 9 ( GDF9), bone morphogenetic protein 15 ( BMP15), and bone morphogenetic protein receptor 1B ( BMPR1B).  In the 96 U.S. rams, nine missense variants encoding 11 protein variants were identified. However, only one was previously reported to affect litter size ( GDF9 V371M, Finnsheep).  Two missense variants in BMP15 were identified that had not previously been reported:  R67Q in Dorset, and L252P in Dorper and White Dorper breeds. Also, two novel missense variants were identified in BMPR1B:  M64I in Katahdin, and T345N in Romanov and Finnsheep breeds.  Based on the strict conservation of amino acid residues across placental mammals, the four variants encoded by BMP15 and BMPR1B are predicted to interfere with their function. However, preliminary analyses of litter sizes in small samples did not reveal a correlation with variants in BMP15 and BMPR1B with daughters of these rams. Conclusions: Collectively, this report describes a new resource for discovering protein variants in silico and identifies alleles for further testing of their effects on litter size in U.S. breeds.

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