Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows

Author:

Sun Hui-Zeng12ORCID,Zhou Mi2,Wang Ou2,Chen Yanhong2,Liu Jian-Xin1ORCID,Guan Le Luo2

Affiliation:

1. Institute of Dairy Science, MoE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University, Hangzhou 310058, P. R. China

2. Department of Agricultural, Food & Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada

Abstract

Abstract Motivation Enhancing the utilization of human-inedible crop by-products by ruminants to produce high-quality milk for human consumption is an emerging global task. We performed a multi-omics-based study to decipher the regulatory biological processes of milk production when cows fed low-quality crop by-products with the aim to improve their utilization. Results Seven types of different high-throughput omics data were generated across three central organs [rumen, liver and mammary gland (MG)] and biofluids (rumen fluid and blood) that involved in milk production. The integrated multi-omics analysis including metabolomics, metagenomics and transcriptomics showed altered microbiome at compositional and functional levels, microbial metabolites in the rumen, down-regulated genes and associated functions in liver and MG. These changes simultaneously contributed to down-regulated three key metabolic nodes (propionate, glucose and amino acid) across these organs and biofluids that led to lowered milk yield and quality when cows consumed corn stover (CS). Hippuric acid was identified as a biomarker that led to low milk production in CS-fed cows, suggesting a future evaluation parameter related to the metabolic mechanism of low-quality forage utilization. This study unveils the milk production-related biological mechanism across different biofluids and tissues under a low-quality forage diet, which provides a novel understanding and potential improvement strategies for future crop by-products utilization and sustainable ruminant production. Availability and implementation The raw files of metagenomics, metabolomics, and transcriptomics data can be accessed at NCBI SRA (No. SRR5028206), EMBI-EBI (No. MTBLS411), and GEO (NO. GSE78524) databases respectively. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Natural Science Foundation of China

China Agriculture Research System

China Opportunity Fund

University of Alberta, Canada

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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