Recessive Effect of GC-NPFFR2 rs137147462 on Somatic Cell Score (Mastitis Susceptibility) in Japanese Holsteins

We evaluated four candidate SNPs (<i>GC-NPFFR2</i> rs137147462, <i>GC-NPFFR2</i> rs109452259, <i>BRCA1</i> rs134817801, and <i>DGAT1</i> p.K232A) previously reported in relation to mastitis or milk production traits, using 10,729 test-day phenotypic records collected over 10 years from 269 Japanese Holstein cows (<i>Bos taurus</i>) enrolled in the national Dairy Herd Improvement (DHI) program. Linear mixed models were used to estimate genotypic effects on somatic cell score (SCS) and to test multiple inheritance models. To assess clinical relevance, mastitis severity was further analyzed using categories defined by somatic cell counts (SCC). Among the SNPs tested, <i>GC-NPFFR2</i> rs137147462 showed the clearest and most consistent association with SCS under a recessive model, with GG cows exhibiting higher SCS throughout lactation. Ordinal logistic regression confirmed a higher probability of progression to severe mastitis in GG cows. <i>DGAT1</i> p.K232A showed additive effects, with the A allele increasing milk yield while lowering fat and protein percentages. AA cows also showed higher SCS under a modest recessive effect. <i>BRCA1</i> rs134817801 and <i>GC-NPFFR2</i> rs109452259 had minimal effects. These findings support <i>GC-NPFFR2</i> rs137147462 as a promising marker for mastitis resistance and indicate the importance of considering not only additive but also recessive genetic models in genomic selection strategies.

Authors

Institutions

Publication Details

Journal
Animals
Published
2025-11-08
DOI
https://doi.org/10.3390/ani15223239
Citations
1
Primary Topic
Milk Quality and Mastitis in Dairy Cows
Type
article
Field-Weighted Citation Impact
1.90
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Recessive Effect of GC-NPFFR2 rs137147462 on Somatic Cell Score (Mastitis Susceptibility) in Japanese Holsteins

Shaohsu Wang, Naoki Miura, Mohammad Arif, Yoshiyuki Akiyama et al.
1 citations
Animals
Milk Quality and Mastitis in Dairy Cows
1.90
article

Recessive Effect of GC-NPFFR2 rs137147462 on Somatic Cell Score (Mastitis Susceptibility) in Japanese Holsteins

Shaohsu Wang, Naoki Miura, Mohammad Arif, Yoshiyuki Akiyama, Yutaro Ide, Takaaki ANDO, Nobuhiro Nozaki
article en
1 citations

Abstract

We evaluated four candidate SNPs (<i>GC-NPFFR2</i> rs137147462, <i>GC-NPFFR2</i> rs109452259, <i>BRCA1</i> rs134817801, and <i>DGAT1</i> p.K232A) previously reported in relation to mastitis or milk production traits, using 10,729 test-day phenotypic records collected over 10 years from 269 Japanese Holstein cows (<i>Bos taurus</i>) enrolled in the national Dairy Herd Improvement (DHI) program. Linear mixed models were used to estimate genotypic effects on somatic cell score (SCS) and to test multiple inheritance models. To assess clinical relevance, mastitis severity was further analyzed using categories defined by somatic cell counts (SCC). Among the SNPs tested, <i>GC-NPFFR2</i> rs137147462 showed the clearest and most consistent association with SCS under a recessive model, with GG cows exhibiting higher SCS throughout lactation. Ordinal logistic regression confirmed a higher probability of progression to severe mastitis in GG cows. <i>DGAT1</i> p.K232A showed additive effects, with the A allele increasing milk yield while lowering fat and protein percentages. AA cows also showed higher SCS under a modest recessive effect. <i>BRCA1</i> rs134817801 and <i>GC-NPFFR2</i> rs109452259 had minimal effects. These findings support <i>GC-NPFFR2</i> rs137147462 as a promising marker for mastitis resistance and indicate the importance of considering not only additive but also recessive genetic models in genomic selection strategies.

AnimalsVol. 15(22)
Kagoshima University (JP), Bangladesh Agricultural University (BD), National Livestock Breeding Center (JP)
Openalex Percentile: Top 11%
Milk Quality and Mastitis in Dairy Cows
1.90
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.