Jorge E C, Melo C M R, Rosário M F, Rossi J R S, Ledur M C, Moura A S A M T, Coutinho L L
Departamento de Zootecnia, Escola Superior de Agricultura "Luiz de Queiroz", Universidade de São Paulo, Piracicaba, SP, Brasil.
Genet Mol Res. 2010 Feb 2;9(1):188-207. doi: 10.4238/vol9-1gmr712.
Macro- and microarrays are well-established technologies to determine gene functions through repeated measurements of transcript abundance. We constructed a chicken skeletal muscle-associated array based on a muscle-specific EST database, which was used to generate a tissue expression dataset of ~4500 chicken genes across 5 adult tissues (skeletal muscle, heart, liver, brain, and skin). Only a small number of ESTs were sufficiently well characterized by BLAST searches to determine their probable cellular functions. Evidence of a particular tissue-characteristic expression can be considered an indication that the transcript is likely to be functionally significant. The skeletal muscle macroarray platform was first used to search for evidence of tissue-specific expression, focusing on the biological function of genes/transcripts, since gene expression profiles generated across tissues were found to be reliable and consistent. Hierarchical clustering analysis revealed consistent clustering among genes assigned to 'developmental growth', such as the ontology genes and germ layers. Accuracy of the expression data was supported by comparing information from known transcripts and tissue from which the transcript was derived with macroarray data. Hybridization assays resulted in consistent tissue expression profile, which will be useful to dissect tissue-regulatory networks and to predict functions of novel genes identified after extensive sequencing of the genomes of model organisms. Screening our skeletal-muscle platform using 5 chicken adult tissues allowed us identifying 43 'tissue-specific' transcripts, and 112 co-expressed uncharacterized transcripts with 62 putative motifs. This platform also represents an important tool for functional investigation of novel genes; to determine expression pattern according to developmental stages; to evaluate differences in muscular growth potential between chicken lines, and to identify tissue-specific genes.
宏阵列和微阵列是通过对转录本丰度进行重复测量来确定基因功能的成熟技术。我们基于肌肉特异性EST数据库构建了一个鸡骨骼肌相关阵列,该阵列用于生成约4500个鸡基因在5种成年组织(骨骼肌、心脏、肝脏、脑和皮肤)中的组织表达数据集。通过BLAST搜索,只有少数EST得到了充分表征,从而确定其可能的细胞功能。特定组织特征性表达的证据可被视为该转录本可能具有功能重要性的一个指标。骨骼肌宏阵列平台首先用于寻找组织特异性表达的证据,重点关注基因/转录本的生物学功能,因为发现跨组织生成的基因表达谱是可靠且一致的。层次聚类分析揭示了分配给“发育生长”的基因之间一致的聚类,如本体基因和胚层。通过将来自已知转录本的信息以及转录本所源自的组织与宏阵列数据进行比较,支持了表达数据的准确性。杂交试验产生了一致的组织表达谱,这将有助于剖析组织调控网络,并预测在对模式生物基因组进行广泛测序后鉴定出的新基因的功能。使用5种鸡成年组织筛选我们的骨骼肌平台,使我们能够鉴定出43个“组织特异性”转录本,以及112个共表达的未表征转录本和62个推定基序。该平台也是对新基因进行功能研究的重要工具;用于根据发育阶段确定表达模式;评估鸡品系之间肌肉生长潜力的差异,并鉴定组织特异性基因。