Toll-like receptor 4 gene polymorphisms influence milk production traits in Chinese Holstein cows

作者:Wang, Mengqi; Song, Hailiang; Zhu, Xiaorui; Xing, Shiyu; Zhang, Meirong; Zhang, Huimin; Wang, Xiaolong; Yang, Zhangping; Ding, Xiangdong; Karrow, Niel A.; Koenig, Sven; Mao, Yongjiang*
来源:Journal of Dairy Research, 2018, 85(4): 407-411.
DOI:10.1017/S0022029918000535

摘要

The research reported in this Research Communication aimed to describe the influence of Toll-like receptor 4 gene polymorphisms on milk production traits in Chinese Holstein cows. Toll-like receptor 4 (TLR4) is an important member of the toll-like receptor gene family that is widely found in various organisms. Since TLR4 can identify molecular patterns from various pathogenic microorganisms and induce natural and acquired immunity, it plays an important role in disease resistance in dairy cows. Two single nucleotide polymorphisms (SNPs) of TLR4 (c. 226 G > C and c.2021 C > T) that were previously found to be associated with health traits were genotyped using Sequenom MassARRAY (Sequenom Inc., San Diego, CA) for Chinese Holstein cows (n = 866). The associations between SNPs or their haplotypes and milk production traits and somatic cell count were analyzed by the generalized linear model procedure of Statistics Analysis System software (SAS). The c.-226 G > C and c.2021 C> T showed low linkage disequilibrium (r 2 = 0192). There was no association between these two SNPs and SCC, but significant effects were found for SNP c.-226 G > C on test-day milk yield, fat content, protein content, and total solid and milk urea nitrogen (P< 0-05), and SNP c.2021 C > T and the SNP haplotypes on test-day milk yield, fat content, protein content, lactose content and total solids (P < 0.05). The software Matlnspector revealed that c. -226 G> C was located within several potential transcription factor binding sites, including transcription factor AP-2. The polymorphisms c.-226 G > C and c.2021 C > T had significant effects on the milk production for Chinese Holstein, and these SNP could be used for molecular marker-assisted selection of milk production.