Time- and population-dependent genetic patterns underlie bovine milk somatic cell count.

J Dairy Sci

Department of Animal Science, Cornell University, Ithaca, NY 14853. Electronic address:

Published: September 2020

AI Article Synopsis

  • The study aimed to investigate how genetic factors influence bovine milk somatic cell count (SCC) during lactation and identify genes linked to chronic mastitis vs. healthy cows.
  • 471 cows were genotyped and milk samples were collected at various stages of lactation to assess SCC, resulting in 167 significant SNPs associated with SCC.
  • Researchers identified candidate genes related to the immune system and discerned three cow populations (healthy, chronically mastitic, and average), highlighting 12 SNPs with strong associations to these groups.

Article Abstract

The objective of this study was to determine whether genetic regulation of bovine milk somatic cell count (SCC) varied throughout the course of an individual lactation and to identify quantitative trait loci (QTL) that may differentiate populations of chronically mastitic and robustly healthy cows. Milk SCC has long been a proxy for clinical mastitis diagnosis in management and genetic improvement strategies to control the disease. Cows (n = 471) were genotyped on the Illumina BovineHD 777K BeadChip (Illumina Inc., San Diego, CA), and composite milk samples were collected for SCC at 0-1 d in milk (DIM), 3-5 DIM, 10-14 DIM, 90-110 DIM, and 210-230 DIM, with each time span representing key physiological transitions for the cow. Median lactation somatic cell score (SCS) and area under the SCS curve were calculated from farm test data. A total of 8 genome-wide associations were performed and 167 SNP spanning the genome were significantly associated (false discovery rate <0.05). Of these associated regions, 27 of 48 associated QTL were novel for clinical mastitis or SCC. The linkage disequilibrium block surrounding the associated QTL or a 1-Mb window in the absence of linkage disequilibrium was interrogated for candidate genes, and many of those identified were related to multiple arms of the immune system, including toll-like receptor signaling, macrophage activation, B-cell maturation, T-cell recruitment, and the complement pathway. These genes included EXOC4, BAMBI, ITSN2, IL34, FCN3, CD8A, and CD8B. In addition, we identified populations of robustly healthy (SCS ≤4 from 10-14 DIM until study end), chronically mastitic (SCS >4 from 10-14 DIM until study end), and average cows with fluctuating SCS, and calculated fixation indices to identify regions of the genome differentiating these 3 populations. A total of 12 SNP were identified that showed moderate allelic differentiation (Wright's F statistic, F ≥ 0.4) between the "chronic," "healthy," and "average" populations of cows. Candidate genes in the region surrounding differentiated QTL were related to cell signaling and immune response, such as JAKMIP1 and MADCAM1. The wide range of significantly associated QTL spanning the genome and the diversity of gene functions reinforces that mastitis is a complex trait and suggests that selection based on lactation stage-specific SCS rather than a generalized score may lead to greater success in breeding mastitis-resistant cows.

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http://dx.doi.org/10.3168/jds.2020-18322DOI Listing

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