SNV discovery and functional candidate gene identification for milk composition based on whole genome resequencing of Holstein bulls with extremely high and low breeding values.

Shan Lin,Yali Hou,Lin Liu,Wenhui Li,Jianping Jiang,Dongxiao Sun,Bo Han,Hongyan Zhang,Shengli Zhang,Sujan Mamidi

doi:10.1371/journal.pone.0220629

Abstract

We have sequenced the whole genomes of eight proven Holstein bulls from the four half-sib or full-sib families with extremely high and low estimated breeding values (EBV) for milk protein percentage (PP) and fat percentage (FP) using Illumina re-sequencing technology. Consequently, 2.3 billion raw reads were obtained with an average effective depth of 8.1×. After single nucleotide variant (SNV) calling, total 10,961,243 SNVs were identified, and 57,451 of them showed opposite fixed sites between the bulls with high and low EBVs within each family (called as common differential SNVs). Next, we annotated the common differential SNVs based on the bovine reference genome, and observed that 45,188 SNVs (78.70%) were located in the intergenic region of genes and merely 11,871 SNVs (20.67%) located within the protein-coding genes. Of them, 13,099 common differential SNVs that were within or close to protein-coding genes with less than 5 kb were chosen for identification of candidate genes for milk compositions in dairy cattle. By integrated analysis of the 2,657 genes with the GO terms and pathways related to protein and fat metabolism, and the known quantitative trait loci (QTLs) for milk protein and fat traits, we identified 17 promising candidate genes: ALG14, ATP2C1, PLD1, C3H1orf85, SNX7, MTHFD2L, CDKN2D, COL5A3, FDX1L, PIN1, FIG4, EXOC7, LASP1, PGS1, SAO, GPLD1 and MGEA5. Our findings provided an important foundation for further study and a prompt for molecular breeding of dairy cattle.

Highlights

Milk yield, milk protein and fat traits are main economic traits and important breeding goals of dairy industry
Eight Holstein bulls were selected from the Beijing Dairy Cattle Center that consisted of four full-sib and/or half-sib families, and each family contain s two bulls who have extremely high and low estimated breeding values (EBV) for milk protein percentage (PP) and fat percentage (FP) with reliabilities of more than 0.85
29 genes was enriched in Mesh term of Amino Acids (MeSH:D000596) in the Chemicals and Drugs category which was associated with protein synthesis and metabolism Thereby, we identified 1,354 genes that were involved in 133 significant Gene Ontology (GO) terms, pathways and Mesh terms relevant to protein, lipid, and fatty acid synthesis and metabolism such as protein metabolic, cellular protein modification, lipid modification, phospholipid metabolic, glycerophospholipid metabolic, sphingolipid metabolism, glycerolipid metabolic, fat cell differentiation, insulin resistance, insulin secretion and MAPK signaling pathways

Summary

Introduction

Milk protein and fat traits are main economic traits and important breeding goals of dairy industry. Compared to the standard phenotypic data based methods, marker-assisted. SNV discovery and gene identification for milk composition based on whole genome resequencing of Holstein earmarked fund for Modern Agro-industry Technology Research System (CARS-36), and the Program for Changjiang Scholar and Innovation Research Team in University (IRT_15R62)

Methods

Results

Discussion

Conclusion