title: A gene expression estimator of intramuscular fat percentage for use in both cattle and sheep.
abstract: BACKGROUND
  The expression of genes encoding proteins involved in triacyglyceride and fatty acid synthesis and storage in cattle muscle are correlated with intramuscular fat (IMF)%. Are the same genes also correlated with IMF% in sheep muscle, and can the same set of genes be used to estimate IMF% in both species?
  
  
  RESULTS
  The correlation between gene expression (microarray) and IMF% in the longissimus muscle (LM) of twenty sheep was calculated. An integrated analysis of this dataset with an equivalent cattle correlation dataset and a cattle differential expression dataset was undertaken. A total of 30 genes were identified to be strongly correlated with IMF% in both cattle and sheep. The overlap of genes was highly significant, 8 of the 13 genes in the TAG gene set and 8 of the 13 genes in the FA gene set were in the top 100 and 500 genes respectively most correlated with IMF% in sheep, P-value = 0. Of the 30 genes, CIDEA, THRSP, ACSM1, DGAT2 and FABP4 had the highest average rank in both species. Using the data from two small groups of Brahman cattle (control and Hormone growth promotant-treated [known to decrease IMF% in muscle]) and 22 animals in total, the utility of a direct measure and different estimators of IMF% (ultrasound and gene expression) to differentiate between the two groups were examined. Directly measured IMF% and IMF% estimated from ultrasound scanning could not discriminate between the two groups. However, using gene expression to estimate IMF% discriminated between the two groups. Increasing the number of genes used to estimate IMF% from one to five significantly increased the discrimination power; but increasing the number of genes to 15 resulted in little further improvement.
  
  
  CONCLUSIONS
  We have demonstrated the utility of a comparative approach to identify robust estimators of IMF% in the LM in cattle and sheep. We have also demonstrated a number of approaches (potentially applicable to much smaller groups of animals than conventional methods) to using gene expression to rank animals for IMF% within a single farm/treatment, or to estimate differences in IMF% between two farms/treatments.
authors.affiliation: Key Laboratory of Meat Processing and Quality Control, Synergetic Innovation Center of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing 210095, P.R. China ; CSIRO Animal, Food and Health Sciences, St. Lucia QLD 4067, Australia.
authors.forename: Bing
authors.initials: B
authors.lastname: Guo
authors.affiliation: CSIRO Animal, Food and Health Sciences, St. Lucia QLD 4067, Australia ; Now at; National Institute of Animal Health, 50/2 Kasetklang, Ladyao, Bangkok 10900, Thailand.
authors.forename: Kritaya
authors.initials: K
authors.lastname: Kongsuwan
authors.affiliation: CSIRO Animal, Food and Health Sciences, Armidale NSW 2350, Australia ; NSW Department of primary Industries, Armidale NSW 2350, Australia.
authors.forename: Paul L
authors.initials: PL
authors.lastname: Greenwood
authors.affiliation: Key Laboratory of Meat Processing and Quality Control, Synergetic Innovation Center of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing 210095, P.R. China.
authors.forename: Guanghong
authors.initials: G
authors.lastname: Zhou
authors.affiliation: Key Laboratory of Meat Processing and Quality Control, Synergetic Innovation Center of Food Safety and Nutrition, College of Food Science and Technology, Nanjing Agriculture University, Nanjing 210095, P.R. China.
authors.forename: Wangang
authors.initials: W
authors.lastname: Zhang
authors.affiliation: CSIRO Animal, Food and Health Sciences, St. Lucia QLD 4067, Australia.
authors.forename: Brian P
authors.initials: BP
authors.lastname: Dalrymple
keywords: Cattle; Gene expression phenotype; IMF%; Sheep