Candidate Genes Identification And Their Genetic Effects Analysis On Milk Composition Traits In Chinese Holstein

Detection and identification of key genes or causal variations on milk composition is the base and precondition to cultivate new strain of low-fat and high-protein for dairy cattle using molecular breeding strategies. This study aims at identifying candidate gens or SNPs on milk composition traits (Milk fatty acids and milk protein) by genomics, transcriptomics, bioinformatics and statistical genetics, etc., and conducting the genetic effect analysis in a large population, so as to obtain the causal genes or the candidate genes with great effects on target traits.GWAS was conducted to identify candidate genes on milk fatty acids. The Chinese Holstein population in this study comprised 784 cows from 18 farms of Beijing Sanyuan Dairy Farm Center, the daughters of 21 sire families. Genotypes were obtained with the Illumina BovineSNP50 Bead chip and a total of 22 milk fatty acids were determined by gas chromatography as phenotypes, and GWAS was conducted by PLINK software. Totally,83 genome-wise significant SNPs and 314 suggestive significant SNPs associated with 18 milk fatty acid traits were detected. Chromosome regions that affect milk fatty acids were mainly observed on BTA5,10,14,17 and 26. Several SNPs are close to or within a total of 18 genes such as DGAT1, SCD and FASN, which are well-known to affect milk composition traits of dairy cattle. Combined with the previously reported QTL regions and the biological functions of the genes,20 novel promising candidates for C10:0, C12:0, C14:0, C14.1, C14 index, C18:0, C18:1n9c, C18index, SFA, UFA and SFA/UFA were found, which composed oiHTRIB, CPM, PRKG1, MINPP1, LIPJ, LIPK, EHHADH, MOGAT1, ECHS1, STAT1, SORBS1, NFKB2, AGPAT3, CHUK, OSBPL8, PRLR, IGF1R, ACSL3, GHR and OXCT1.RNA-Seq was conducted to identify candidate genes on milk protein traits. Paired-end RNA-Seq was used to explore the bovine transcriptome from the biopsied mammary glands of 12 Chinese Holstein cows with 6 extremely high and 6 low phenotypic values for milk protein percentage during the peak lactation and the non-lactating period. Approximate 20,000 of 27,544 genes annotated in NCBI UMD3.1 bovine genome assembly were ubiquitously expressed in mammary glands. We identified 157, 497 and 5,488 differentially expressed genes between the three comparison groups, extremely high and low milk protein percentage during the peak lactation (HP vs LP), during the non-lactating period (HD vs LD) and different milk lactation stage (P vs D). Integrated interpretation of differential gene expression indicated that WAP, NARS, MARS, GARS, CDO1, GATM, INSR, IGF1R, IGFBP3 and CR1M1 are the 10 well-known genes affecting milk protein traits, and SERPINA1, CLU, CNTFR, ERBB2, NEDD4L, ANG, GALE, HSPA8, LPAR6 and CD14 are the 10 most promising candidate genes affecting milk protein concentration.Based on the above identified candidate genes on milk composition traits, we selected five candidate genes of SCD, FASN, PPARGC1A, ABCG2 and IGF1 affecting milk fatty acids to conduct the genetic effect analysis in a large Chinese Holstein population. The population consisted of 346 cows from 13 farms across Beijing district, the daughters of 13 sire families. The results indicated that the significant associations of SNPs detected in GWAS were indirectly caused by the genetic effects of thatFASN, SCD and PPARGC1A on the milk fatty acid traits. We found the significant effects of the SCD on milk medium-and long-chain unsaturated fatty acids, special for C14:l and C14 index in dairy cattle. The FASN, PPARGC1A, ABCG2 and IGF1 were mainly associated with medium-chain saturated fatty acids and long-chain unsaturated fatty acids. In addition, we selected four candidate genes affecting milk protein traits to conduct the genetic effect analysis in a large Chinese Holstein population, which are comprised of 1,027 cows from 17 farms across Beijing district, the daughters of 17 sire families. The results demonstrated the significant genetic effects of SERPMA1, GALE, HSPA8 and ERBB2 on milk protein concentration from the genomic level.Our findings revealed narrower chromosomal regions for candidate genes affecting milk composition traits, which is helpful for follow-up studies to fine-mapping to unravel causal mutations. Putative genes including well-known and novel promising candidate genes will facilitate the understanding of the molecular mechanisms on milk fatty acids and milk protein synthesis, transportation and metabolism, and also provide compacted sound basis for designing better breeding strategies such as maker-assisted selection (MAS) to optimize the contents of milk protein and milk fat to cultivate new strain of low-fat and high-protein dairy cattle.