Tjaden Brian, Saxena Rini Mukherjee, Stolyar Sergey, Haynor David R, Kolker Eugene, Rosenow Carsten
Department of Computer Science, University of Washington, Seattle, WA 98195, USA.
Nucleic Acids Res. 2002 Sep 1;30(17):3732-8. doi: 10.1093/nar/gkf505.
Microarrays traditionally have been used to analyze the expression behavior of large numbers of coding transcripts. Here we present a comprehensive approach for high-throughput transcript discovery in Escherichia coli focused mainly on intergenic regions which, together with analysis of coding transcripts, provides us with a more complete insight into the organism's transcriptome. Using a whole genome array, we detected expression for 4052 coding transcripts and identified 1102 additional transcripts in the intergenic regions of the E.coli genome. Further classification reveals 317 novel transcripts with unknown function. Our results show that, despite sophisticated approaches to genome annotation, many cellular transcripts remain unidentified. Through the experimental identification of all RNAs expressed under a specific condition, we gain a more thorough understanding of all cellular processes.
传统上,微阵列已被用于分析大量编码转录本的表达行为。在此,我们提出了一种全面的方法,用于在大肠杆菌中进行高通量转录本发现,主要聚焦于基因间区域,该方法与编码转录本分析一起,为我们提供了对生物体转录组更完整的洞察。使用全基因组阵列,我们检测到了4052个编码转录本的表达,并在大肠杆菌基因组的基因间区域鉴定出了另外1102个转录本。进一步分类显示有317个功能未知的新转录本。我们的结果表明,尽管有复杂的基因组注释方法,但许多细胞转录本仍未被识别。通过对特定条件下表达的所有RNA进行实验鉴定,我们对所有细胞过程有了更深入的了解。