Yin Yang 1 and adipogenic gene network expression in longissimus muscle of beef cattle in response to nutritional management

Sonia J. Moisá, Daniel W. Shike, William T. Meteer, Duane Keisler, Dan B. Faulkner, Juan J. Loor

    Research output: Contribution to journalArticlepeer-review

    9 Scopus citations


    Among 36 differentially-expressed genes during growth in longissimus muscle (LM) of Angus steers, Yin Yang 1 (YY1) had the most relationships with other genes including some associated with adipocyte differentiation. The objective of this study was to examine the effect of nutritional management on mRNA expression of YY1 along with its targets genes PPARG, GTF2B, KAT2B, IGFBP5 and STAT5B. Longissimus from Angus and Angus×Simmental steers (7 total/treatment) on early weaning plus high-starch (EWS), normal weaning plus starch creep feeding (NWS), or normal weaning without starch creep feeding (NWN) was biopsied at 0, 96, and 240days on treatments. Results suggest that YY1 does not exert control of adipogenesis in LM, and its expression is not sensitive to weaning age. Among the YY1-related genes, EWS led to greater IGFBP5 during growing and finishing phases. Pro-adipogenic transcriptional regulation was detected in EWS due to greater PPARG and VDR at 96 and 240 d vs. 0 d. GTF2B and KAT2B expression was lower in response to NWS and EWS than NWN, and was most pronounced at 240 d. The increase in PPARG and GTF2B expression between 96 and 240 d underscored the existence of a molecular programming mechanism that was sensitive to age and dietary starch. Such response partly explains the greater carcass fat deposition observed in response to NWS.

    Original languageEnglish (US)
    Pages (from-to)71-83
    Number of pages13
    JournalGene Regulation and Systems Biology
    Issue number7
    StatePublished - 2013


    • Adipogenesis
    • Early weaning
    • Gene expression
    • Nutrition
    • Steers
    • Yin Yang 1

    ASJC Scopus subject areas

    • Ecology, Evolution, Behavior and Systematics
    • Molecular Biology
    • Genetics
    • Computer Science Applications


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