Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake
Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake
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DOI：
10.1111/j.1365-2052.2011.02182.x
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发表时间：
2011-10-01
期刊：
影响因子：
2.4
通讯作者：
Vanselow, B.
中科院分区：
文献类型：
--
作者：
Chen, Y.;Gondro, C.;Vanselow, B.
饲料利用率是肉牛生产的重要经济性状。它可以被测量为剩余的饲料摄入量。这是在试验期间记录的实际采食量与基于动物的大小和生长速率的动物的预期采食量之间的差异。基于DNA的标记辅助选择将有助于肉牛育种者通过缩短世代间隔来加速饲料效率的遗传改良，并将降低测量剩余采食量的高成本。尽管随着分子遗传学的发展，许多数量性状位点和候选基因已经被鉴定出来，但我们对剩余采食量的生理机制和基因性质的了解仍然有限。这项研究的目的是使用全球基因表达谱微阵列，以确定在牛中差异表达的基因，使用遗传选择的低和高残留饲料摄入量的线，并发现残留饲料摄入量的候选基因。使用具有24000个探针的长寡核苷酸微阵列来分析44头牛的肝脏转录组，所述牛被选择用于高或低残余采食量。161个独特的基因被确定为高和低残留饲料摄入量的动物之间的差异表达。这些基因参与影响细胞生长和增殖、细胞组装和组织、细胞信号传导、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。使用转录方法的功能数据的分析，可以更好地了解潜在的生物过程中所涉及的剩余饲料摄入量，也可以识别标记辅助选择的候选基因。
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.