Development of a Transcriptome map in non-small cell lun

我们已经调查了超过374,000个SAGE标签，代表来自9个不同肺组织文库的66,502个独特的转录本。这些文库包括两个来自正常大小呼吸道上皮细胞培养的文库，两个来自肺鳞癌和腺癌的文库，以及一个来自A549肺腺癌细胞系的第9个文库。我们使用新完成的人类基因组序列将识别出的SAGE标签分配到它们的染色体位置，并开发了全基因组基因表达谱，代表了九种肺组织中每个转录本的相对表达模式。在66,502个独特的转录本中，23,056个转录本在所有9个文库中多次出现，其中18,652个(81%)与Unigene簇匹配，85个标签(0.4%)与线粒体DNA/核糖体RNA序列匹配。除去4938个标签(21.4%)与一个以上的簇匹配，13714个标签(59.5%)与唯一的或位置相关的Unigene簇链接，并包括在转录组图谱中。由此得到的转录组图谱揭示了基因组特定染色体区域的高度差异表达的基因簇，并表明使用SAGE生成转录组图谱可能提供一种潜在的强大工具来帮助揭示肺癌染色体变化的候选区域。该项目的第一阶段已经完成，出版了一份手稿。我们正在与CGAP合作生成额外的SGAE标签，以增强转录图谱的可靠性，并允许更好地识别特定涉及非小细胞肺癌的染色体区域。

We have surveyed more than 374,000 SAGE tags representing 66,502 unique transcripts from nine different lung tissue libraries. These libraries included two of each from normal small or large airway epithelial cell cultures, two of each from primary squamous cell lung cancers and adenocarcinomas of the lung, and a 9th library derived from the A549 lung adenocarcinoma cell line. We assigned the identified SAGE tags to their chromosomal positions using the newly completed human genome sequence and developed a genome-wide gene expression profile representing the relative expression pattern of each transcript among the nine lung tissues. Of the 66,502 unique transcripts, 23,056 transcripts appeared more than once among all nine libraries, 18,652 (81%) of those matched to UniGene clusters while 85 tags (0.4%) matched to mitochondrial DNA/ribosomal RNA sequences. Excluding the 4,938 tags (21.4%) that matched to more than one cluster, 13,714 tags (59.5%) were linked to unique or positionally related UniGene clusters and included in the transcriptome map. The resulting transcriptome map revealed clusters of highly differentially expressed genes at specific chromosomal regions of the genome and suggested that the generation of transcriptome map using SAGE may provide a potentially powerful tool to help reveal candidate regions of chromosomal changes in lung cancer. The first phase of this project has been completed with the publication of a manuscript. We are working with CGAP to generate addtional SGAE tags to enhance the reliability of the transcriptom map and to allow better identification of chromosome regions specifically involved in NSCLC.