4.1 Article

A systems approach to determine the effect of changes in gene expression in adipose tissue on productive and reproductive efficiency in dairy cattle

Journal

ANIMAL PRODUCTION SCIENCE
Volume 54, Issue 9, Pages 1224-1227

Publisher

CSIRO PUBLISHING
DOI: 10.1071/AN14209

Keywords

agricultural systems; animal reproduction; dairy nutrition; system analysis

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In order to assess the patterns of metabolism that affect efficiency, an existing mechanistic metabolic model of dairy cows (Molly) was expanded to include transcriptional control of metabolism in adipose tissue and reproductive processes. Our objective was to test the effects of changes in gene transcription in adipose tissue on patterns of metabolism, reproductive processes and efficiency. The model describes the substrate sensitivity and maximum velocity for lipogenesis, esterification and lipolysis. Data were collected from first and second parity cows from various studies, and included nutrient intake, milk component output, changes in adipose tissue lipid, visceral and body protein and lipid, and metabolism rates in adipose tissue and gene transcription. The lipogenic pathways were primarily controlled by transcriptional changes, whereas lipolysis varied primarily by post-translational control. We used the difference in transcriptional and post-translational metabolic control to alter V-max and K-s for lipogenesis and lipolysis; in addition, we modelled a range of energy costs for ion transport and protein turnover in liver, muscle and adipose tissues. Changing rates of lipogenesis and lipolysis (similar to four-fold) did not affect milk production or feed intake, but altered maintenance costs, fat accretion, energetic efficiency and reproduction. Increases in lipogenesis decreased postpartum interval to first ovulation; increases in rates of lipolysis increased the interval. Changes in metabolic rate from changing either adipose tissue metabolism or rate of ion transport and protein turnover affected rates of oestrogen and progesterone degradation, which affected follicular growth and corpus luteum function. This model may be used to help interpret genomic and transcriptomic data to pinpoint the most effective ways to select and manage for changes in productive and reproductive efficiency.

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