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利用基因组比对的ESTs进行基因结构预测和可变剪接分析。

Gene structure prediction and alternative splicing analysis using genomically aligned ESTs.

作者信息

Kan Z, Rouchka E C, Gish W R, States D J

机构信息

Center for Computational Biology, Washington University, St. Louis, Missouri 63110, USA.

出版信息

Genome Res. 2001 May;11(5):889-900. doi: 10.1101/gr.155001.

Abstract

With the availability of a nearly complete sequence of the human genome, aligning expressed sequence tags (EST) to the genomic sequence has become a practical and powerful strategy for gene prediction. Elucidating gene structure is a complex problem requiring the identification of splice junctions, gene boundaries, and alternative splicing variants. We have developed a software tool, Transcript Assembly Program (TAP), to delineate gene structures using genomically aligned EST sequences. TAP assembles the joint gene structure of the entire genomic region from individual splice junction pairs, using a novel algorithm that uses the EST-encoded connectivity and redundancy information to sort out the complex alternative splicing patterns. A method called polyadenylation site scan (PASS) has been developed to detect poly-A sites in the genome. TAP uses these predictions to identify gene boundaries by segmenting the joint gene structure at polyadenylated terminal exons. Reconstructing 1007 known transcripts, TAP scored a sensitivity (Sn) of 60% and a specificity (Sp) of 92% at the exon level. The gene boundary identification process was found to be accurate 78% of the time. also reports alternative splicing patterns in EST alignments. An analysis of alternative splicing in 1124 genic regions suggested that more than half of human genes undergo alternative splicing. Surprisingly, we saw an absolute majority of the detected alternative splicing events affect the coding region. Furthermore, the evolutionary conservation of alternative splicing between human and mouse was analyzed using an EST-based approach. (See http://stl.wustl.edu/~zkan/TAP/)

摘要

随着人类基因组几乎完整序列的可得性,将表达序列标签(EST)与基因组序列进行比对已成为一种实用且强大的基因预测策略。阐明基因结构是一个复杂的问题,需要识别剪接位点、基因边界和可变剪接变体。我们开发了一个软件工具——转录本组装程序(TAP),用于使用基因组比对的EST序列描绘基因结构。TAP利用一种新颖的算法,从单个剪接位点对组装整个基因组区域的联合基因结构,该算法利用EST编码的连通性和冗余信息来梳理复杂的可变剪接模式。已开发出一种称为聚腺苷酸化位点扫描(PASS)的方法来检测基因组中的聚腺苷酸位点。TAP利用这些预测结果,通过在聚腺苷酸化的末端外显子处分割联合基因结构来识别基因边界。在重建1007个已知转录本时,TAP在外显子水平的灵敏度(Sn)为60%,特异性(Sp)为92%。发现基因边界识别过程在78%的情况下是准确的。还报告了EST比对中的可变剪接模式。对1124个基因区域的可变剪接分析表明,超过一半的人类基因会发生可变剪接。令人惊讶的是,我们发现检测到的绝大多数可变剪接事件影响编码区。此外,使用基于EST的方法分析了人类和小鼠之间可变剪接的进化保守性。(见http://stl.wustl.edu/~zkan/TAP/)

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