Exploratory identification of candidate SNP markers associated with recurrent clinical mastitis in Holstein cattle

Mastitis remains one of the most prevalent and economically significant diseases in dairy cattle worldwide. Although somatic cell count (SCC) is widely used as an indicator for mastitis diagnosis, its physiological variability limits its utility for predicting individual susceptibility. In this study, we aimed to identify genomic markers associated with recurrent clinical mastitis by defining mastitis-susceptible cows as those experiencing three or more episodes within a single lactation. Whole-genome resequencing was conducted on 50 Holstein cows (25 mastitis-susceptible and 25 healthy controls), yielding 536,184 high-quality SNPs after stringent quality control. A genome-wide association analysis identified 86 SNPs surpassing the significance threshold (-log₁₀P > 5.0), and seven candidate SNPs were evaluated in an independent cohort of 100 cows. Notably, the majority of candidate SNPs were localized on the X chromosome, suggesting a potential role for X-linked variation in mastitis immune response and disease resistance. While the candidate marker panel combining SNP1, SNP2, and SNP7 demonstrated moderate sensitivity (47%), its high specificity (98%) highlights its potential utility as a preliminary screening tool for identifying individuals at increased risk of recurrent mastitis. These findings provide a foundation for further functional validation and large-scale replication studies, which are essential for implementing effective genomic selection strategies to mitigate mastitis incidence in dairy herds.

Authors

Institutions

Publication Details

Journal
PLoS ONE
Published
2026-07-30
DOI
https://doi.org/10.1371/journal.pone.0355230
Primary Topic
Milk Quality and Mastitis in Dairy Cows
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploratory identification of candidate SNP markers associated with recurrent clinical mastitis in Holstein cattle

Shiho Miyata, Jun Kambe, Kentaro Nagaoka, Satoshi Takemoto et al.
PLoS ONE
Milk Quality and Mastitis in Dairy Cows
article

Exploratory identification of candidate SNP markers associated with recurrent clinical mastitis in Holstein cattle

Shiho Miyata, Jun Kambe, Kentaro Nagaoka, Satoshi Takemoto, Masahiko Ito, Lijie Fan, Chunmei Li, Yuki Yamamoto
article en

Abstract

Mastitis remains one of the most prevalent and economically significant diseases in dairy cattle worldwide. Although somatic cell count (SCC) is widely used as an indicator for mastitis diagnosis, its physiological variability limits its utility for predicting individual susceptibility. In this study, we aimed to identify genomic markers associated with recurrent clinical mastitis by defining mastitis-susceptible cows as those experiencing three or more episodes within a single lactation. Whole-genome resequencing was conducted on 50 Holstein cows (25 mastitis-susceptible and 25 healthy controls), yielding 536,184 high-quality SNPs after stringent quality control. A genome-wide association analysis identified 86 SNPs surpassing the significance threshold (-log₁₀P > 5.0), and seven candidate SNPs were evaluated in an independent cohort of 100 cows. Notably, the majority of candidate SNPs were localized on the X chromosome, suggesting a potential role for X-linked variation in mastitis immune response and disease resistance. While the candidate marker panel combining SNP1, SNP2, and SNP7 demonstrated moderate sensitivity (47%), its high specificity (98%) highlights its potential utility as a preliminary screening tool for identifying individuals at increased risk of recurrent mastitis. These findings provide a foundation for further functional validation and large-scale replication studies, which are essential for implementing effective genomic selection strategies to mitigate mastitis incidence in dairy herds.

PLoS ONEVol. 21(7)
Nanjing Agricultural University (CN), Zen-Noh (Japan) (JP), Hamamatsu University School of Medicine (JP), Tokyo University of Agriculture and Technology (JP)
Japan Racing Association
Openalex Percentile: Top 8%
Milk Quality and Mastitis in Dairy Cows
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.