Evidence-based gene predictions in plant genomes

文献类型： 外文期刊

第一作者： Liang, Chengzhi

作者： Liang, Chengzhi;Ware, Doreen;Stein, Lincoln;Liang, Chengzhi;Mao, Long;Ware, Doreen

作者机构：

期刊名称：GENOME RESEARCH （ 影响因子：9.043； 五年影响因子：12.808 ）

ISSN： 1088-9051

年卷期： 2009 年 19 卷 10 期

页码：

收录情况： SCI

摘要： Automated evidence-based gene building is a rapid and cost-effective way to provide reliable gene annotations on newly sequenced genomes. One of the limitations of evidence-based gene builders, however, is their requirement for transcriptional evidence-known proteins, full-length cDNAs, or expressed sequence tags (ESTs)-in the species of interest. This limitation is of particular concern for plant genomes, where the rate of genome sequencing is greatly outpacing the rate of EST-and cDNA-sequencing projects. To overcome this limitation, we have developed an evidence-based gene build system (the Gramene pipeline) that can use transcriptional evidence across related species. The Gramene pipeline uses the Ensembl computing infrastructure with a novel data processing scheme. Using the previously annotated plant genomes, the dicot Arabidopsis thaliana and the monocot Oryza sativa, we show that the cross-species ESTs from within monocot or dicot class are a valuable source of evidence for gene predictions. We also find that, using only EST and cross-species evidence, the Gramene pipeline can generate a plant gene set that is comparable in quality to the human genes based on known proteins and full-length cDNAs. We compare the Gramene pipeline to several widely used ab initio gene prediction programs in rice; this comparison shows the pipeline performs favorably at both the gene and exon levels with cross-species gene products only. We discuss the results of testing the pipeline on a 22-Mb region of the newly sequenced maize genome and discuss potential application of the pipeline to other genomes.

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