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Mammary Transcriptome Profile during Peak and Late Lactation Reveals Differentially Expression Genes Related to Inflammation and Immunity in Chinese Holstein.


ABSTRACT: Somatic cell count (SCC) in milk is widely used in the dairy industry, as an indicator of the health of mammary gland. While the SCC of dairy cattle was higher in late lactation than in peak lactation, its association with gene expressions of mammary gland were largely unknown. In this study, a transcriptomic sequencing approach and bioinformatics analysis were used to investigate the differential expressed genes (DEGs) associated with inflammation and immunity between peak and late periods of lactation in Chinese Holstein. A total of 446 DEGs (padj < 0.05 and fold change >2) were identified, 50 of which belonged to seven pathways and five terms related to inflammation and immunity. Our data suggested that the activation of nuclear transcription factor-?B (NF-?B) pathway and Toll-like receptor signaling pathway caused inflammatory response, and the activation of chemokine signaling pathway and cytokine-cytokine receptor interaction signaling pathway caused a protective immune response to ensure dairy cows health during late lactation. Our findings deepen the understanding of the molecular mechanism and physiological functions of mammary inflammation in Chinese Holstein during late lactation.

SUBMITTER: Han Z 

PROVIDER: S-EPMC7143190 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Mammary Transcriptome Profile during Peak and Late Lactation Reveals Differentially Expression Genes Related to Inflammation and Immunity in Chinese Holstein.

Han Ziyin Z   Fan Yongliang Y   Yang Zhangping Z   Loor Juan J JJ   Yang Yi Y  

Animals : an open access journal from MDPI 20200319 3


Somatic cell count (SCC) in milk is widely used in the dairy industry, as an indicator of the health of mammary gland. While the SCC of dairy cattle was higher in late lactation than in peak lactation, its association with gene expressions of mammary gland were largely unknown. In this study, a transcriptomic sequencing approach and bioinformatics analysis were used to investigate the differential expressed genes (DEGs) associated with inflammation and immunity between peak and late periods of l  ...[more]

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