Host genotype-microbiota-metabolome interactions modulate semen quality in Holstein bulls

ABSTRACT Semen quality is critical for reproductive performance in dairy cattle; however, its microbial, metabolic, and genetic bases remain poorly understood. We integrated rumen microbiota, metabolome, and genome-wide variation from 55 Holstein bulls stratified into relative semen quality high (RSQH) and relative semen quality low (RSQL) groups based on semen quality records to investigate host-microbiome-metabolome interactions associated with fertility. The rumen microbiota was dominated by Bacteroidota, Firmicutes, and Proteobacteria, while Fibrobacter (phylum Fibrobacterota) was enriched in RSQH bulls and positively associated with sperm motility and density. The metabolome distinguished the two groups with 64 discriminatory metabolites, including elevated N-acetyl-L-phenylalanine and prostaglandin H2 in RSQH and sebacic acid in RSQL. Machine learning models were used to prioritize microbial and metabolic features, identifying candidate markers that may contribute to differences in semen quality. Fibrobacter , thromboxane B2, and N1-[4-(cyanomethyl)phenyl]-4-chlorobenzamide emerged as candidate indicators of semen quality, supported by machine learning, high heritability, and genome-wide association study signals. Overall, 511 single-nucleotide polymorphisms (SNPs) were jointly associated with Fibrobacter and these metabolites, including six significantly linked to sperm motility based on GWAS analysis. These SNPs were grouped into two contrasting types, with C1-type variants showing decreasing trends and C2-type variants showing increasing trends in semen quality-related traits. Structural equation modeling revealed that C2-type variants were positively associated with semen traits through microbial and metabolite enrichment, whereas C1-type variants were negatively associated with them. These findings highlight coordinated host genetic, microbial, and metabolic contributions to semen quality in Holstein bulls and provide candidate biomarkers for fertility-related research and breeding. IMPORTANCE Improving bull fertility is important for reproductive efficiency in dairy production, but the biological factors underlying semen quality remain incompletely understood. This study shows that variation in semen quality in Holstein bulls is associated with coordinated differences in rumen microbiota, metabolites, and host genetic variation. In particular, Fibrobacter , thromboxane B2, and N1-[4-(cyanomethyl)phenyl]-4-chlorobenzamide emerged as promising indicators of semen quality. These findings provide a basis for future fertility biomarker research and may support the development of genetics- and microbiota-informed strategies for bull selection and reproductive management.

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Publication Details

Journal
mSystems
Published
2026-11-03
DOI
https://doi.org/10.1128/msystems.00535-26
Primary Topic
Sperm and Testicular Function
Type
article
Field-Weighted Citation Impact
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article

Host genotype-microbiota-metabolome interactions modulate semen quality in Holstein bulls

Y. Zhang, Zhihua Ju, Jinming Huang, Jinpeng Wang et al.
mSystems
Sperm and Testicular Function
article

Host genotype-microbiota-metabolome interactions modulate semen quality in Holstein bulls

Y. Zhang, Zhihua Ju, Jinming Huang, Jinpeng Wang, Yanqin Li, Yuanpei Zhang, Yaping Gao, Chunhong Yang, Xiuge Wang, Wenhao Liu, Qiang Jiang, Yao Xiao, Xiaochao Wei
article en

Abstract

ABSTRACT Semen quality is critical for reproductive performance in dairy cattle; however, its microbial, metabolic, and genetic bases remain poorly understood. We integrated rumen microbiota, metabolome, and genome-wide variation from 55 Holstein bulls stratified into relative semen quality high (RSQH) and relative semen quality low (RSQL) groups based on semen quality records to investigate host-microbiome-metabolome interactions associated with fertility. The rumen microbiota was dominated by Bacteroidota, Firmicutes, and Proteobacteria, while Fibrobacter (phylum Fibrobacterota) was enriched in RSQH bulls and positively associated with sperm motility and density. The metabolome distinguished the two groups with 64 discriminatory metabolites, including elevated N-acetyl-L-phenylalanine and prostaglandin H2 in RSQH and sebacic acid in RSQL. Machine learning models were used to prioritize microbial and metabolic features, identifying candidate markers that may contribute to differences in semen quality. Fibrobacter , thromboxane B2, and N1-[4-(cyanomethyl)phenyl]-4-chlorobenzamide emerged as candidate indicators of semen quality, supported by machine learning, high heritability, and genome-wide association study signals. Overall, 511 single-nucleotide polymorphisms (SNPs) were jointly associated with Fibrobacter and these metabolites, including six significantly linked to sperm motility based on GWAS analysis. These SNPs were grouped into two contrasting types, with C1-type variants showing decreasing trends and C2-type variants showing increasing trends in semen quality-related traits. Structural equation modeling revealed that C2-type variants were positively associated with semen traits through microbial and metabolite enrichment, whereas C1-type variants were negatively associated with them. These findings highlight coordinated host genetic, microbial, and metabolic contributions to semen quality in Holstein bulls and provide candidate biomarkers for fertility-related research and breeding. IMPORTANCE Improving bull fertility is important for reproductive efficiency in dairy production, but the biological factors underlying semen quality remain incompletely understood. This study shows that variation in semen quality in Holstein bulls is associated with coordinated differences in rumen microbiota, metabolites, and host genetic variation. In particular, Fibrobacter , thromboxane B2, and N1-[4-(cyanomethyl)phenyl]-4-chlorobenzamide emerged as promising indicators of semen quality. These findings provide a basis for future fertility biomarker research and may support the development of genetics- and microbiota-informed strategies for bull selection and reproductive management.

mSystems
Shandong Normal University (CN), Shandong Academy of Agricultural Sciences (CN)
Openalex Percentile: Top 12%
Sperm and Testicular Function
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