Scholarlink

Background <p>Reducing nitrogen excretion in dairy cattle is crucial for improving the environmental sustainability of livestock production. Milk urea nitrogen (MUN), an established biomarker of nitrogen use efficiency, offers a practical basis for genetic selection. To our knowledge, this is the first study in Iranian Holstein cattle that applies a single-step genome-wide association study (ssGWAS) combined with random regression models to identify genomic regions and candidate genes associated with MUN levels across lactation.</p> Results <p>The dataset included 347,639 test-day records from 52,219 first-parity cows. After quality control, 41,102 SNPs from 2,187 genotyped bulls were retained for the ssGWAS. Random regression models were used to estimate daily SNP effects, and the top 50 SNPs were categorized into early, mid, and late lactation stages. Functional annotation identified seventeen significant candidate genes, such as <i>PGLYRP3</i>, <i>S100A9</i>, <i>ABCB11</i>, and <i>CYP1A1</i>, which may be involved in nitrogen metabolism, immune regulation, and transmembrane nutrient transport.</p> Conclusions <p>These findings elucidate the molecular mechanisms underlying MUN variation and highlight candidate genes for genomic selection to improve nitrogen use efficiency in dairy cattle, potentially reducing environmental nitrogen emissions in commercial herds.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Genome-wide association analysis based on random regression models for milk urea nitrogen in Iranian Holstein cattle

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月6日

查看全文
  • Mehridokht Mortazavi,
  • Mohammad Bagher Zandi,
  • Rostam Pahlavan,
  • Moradpasha Eskandari Nasab,
  • Henrique Alberto Mulim,
  • Hinayah Rojas de Oliveira

摘要

Background

Reducing nitrogen excretion in dairy cattle is crucial for improving the environmental sustainability of livestock production. Milk urea nitrogen (MUN), an established biomarker of nitrogen use efficiency, offers a practical basis for genetic selection. To our knowledge, this is the first study in Iranian Holstein cattle that applies a single-step genome-wide association study (ssGWAS) combined with random regression models to identify genomic regions and candidate genes associated with MUN levels across lactation.

Results

The dataset included 347,639 test-day records from 52,219 first-parity cows. After quality control, 41,102 SNPs from 2,187 genotyped bulls were retained for the ssGWAS. Random regression models were used to estimate daily SNP effects, and the top 50 SNPs were categorized into early, mid, and late lactation stages. Functional annotation identified seventeen significant candidate genes, such as PGLYRP3, S100A9, ABCB11, and CYP1A1, which may be involved in nitrogen metabolism, immune regulation, and transmembrane nutrient transport.

Conclusions

These findings elucidate the molecular mechanisms underlying MUN variation and highlight candidate genes for genomic selection to improve nitrogen use efficiency in dairy cattle, potentially reducing environmental nitrogen emissions in commercial herds.