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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Research Project #430498

Research Project: Sequence-Based Big Data Genomic Discovery and Application to Improve Dairy Fertility

Location: Animal Genomics and Improvement Laboratory

Project Number: 8042-31000-002-05-R
Project Type: Reimbursable Cooperative Agreement

Start Date: Feb 15, 2016
End Date: Feb 14, 2020

The overall goal of this research is to discover causative genomic variations and apply those genomic discoveries to improve dairy fertility. Specific aims supporting the overall objective are: 1) Identify genomic regions associated with dairy fertility using sequencing-based GWAS and selection signature analysis of contemporary Holsteins and those unselected for 50 years; and 2) Pinpoint and apply causative genetic variants to develop optimal strategies of genomic selection to improve dairy fertility.

ARS will process 110 semen samples from sires of importance, and genomic DNA will be extracted from semen using an adapted protocol from Qiagen. These 110 bulls will be sequenced to a coverage depth of 10X using the established NGS facility at USDA AGIL. The 125 libraries will be pooled by group and within-SNP effect and trait to target a depth of about 10X sequence coverage per animal (30 billion base pairs) using paired end 150-bp reads on the NextSeq. The goal of the SNP and sequence-based GWAS analysis is to identify locations of causal loci affecting fertility traits. The SNP-based GWAS analysis includes 60K SNP genotype and 15 PTA phenotypes of more than 760,000 Holstein cows and bulls, while the sequence-based GWAS includes millions of SNPs and 15 yield deviation (YD) phenotypes of over 10,000. The SNP-based analysis will use PTA to test for additive effects and additive × additive interactions, while the sequence-based analysis will use YD to test for additional effects including dominance, additive × dominance, dominance × dominance, and imprinting effects. Selection signature analysis will be conducted within each of the three groups to identify loci under selection.