Industry & Investment NSW - Primary Industries, Beef Industry Centre, Armidale, NSW 2351, Australia. yizhou.chen@.industry.nsw.gov.au
Anim Genet. 2011 Oct;42(5):475-90. doi: 10.1111/j.1365-2052.2011.02182.x. Epub 2011 Mar 31.
Feed efficiency is an economically important trait in beef production. It can be measured as residual feed intake. This is the difference between actual feed intake recorded over a test period and the expected feed intake of an animal based on its size and growth rate. DNA-based marker-assisted selection would help beef breeders to accelerate genetic improvement for feed efficiency by reducing the generation interval and would obviate the high cost of measuring residual feed intake. Although numbers of quantitative trait loci and candidate genes have been identified with the advance of molecular genetics, our understanding of the physiological mechanisms and the nature of genes underlying residual feed intake is limited. The aim of the study was to use global gene expression profiling by microarray to identify genes that are differentially expressed in cattle, using lines genetically selected for low and high residual feed intake, and to uncover candidate genes for residual feed intake. A long-oligo microarray with 24 000 probes was used to profile the liver transcriptome of 44 cattle selected for high or low residual feed intake. One hundred and sixty-one unique genes were identified as being differentially expressed between animals with high and low residual feed intake. These genes were involved in seven gene networks affecting cellular growth and proliferation, cellular assembly and organization, cell signalling, drug metabolism, protein synthesis, lipid metabolism, and carbohydrate metabolism. Analysis of functional data using a transcriptional approach allows a better understanding of the underlying biological processes involved in residual feed intake and also allows the identification of candidate genes for marker-assisted selection.
饲料效率是牛肉生产中一个具有重要经济意义的特征。它可以通过剩余饲料摄入量来衡量。这是在测试期内实际饲料摄入量与基于动物大小和生长速度的预期饲料摄入量之间的差异。基于 DNA 的标记辅助选择将通过减少世代间隔帮助肉牛饲养者加速饲料效率的遗传改良,并避免测量剩余饲料摄入量的高成本。尽管随着分子遗传学的进步已经确定了许多数量性状位点和候选基因,但我们对剩余饲料摄入量的生理机制和潜在基因的性质的理解是有限的。本研究的目的是使用微阵列进行的全基因表达谱分析,使用遗传上选择低和高剩余饲料摄入量的品系,来鉴定在牛中差异表达的基因,并揭示剩余饲料摄入量的候选基因。使用带有 24000 个探针的长寡核苷酸微阵列来描绘 44 头因剩余饲料摄入量高低而选择的牛的肝脏转录组。鉴定出 161 个独特的基因在高和低剩余饲料摄入量的动物之间存在差异表达。这些基因参与了影响细胞生长和增殖、细胞组装和组织、细胞信号转导、药物代谢、蛋白质合成、脂质代谢和碳水化合物代谢的七个基因网络。使用转录方法对功能数据进行分析可以更好地理解剩余饲料摄入量所涉及的潜在生物学过程,并允许鉴定用于标记辅助选择的候选基因。