首页> 外文期刊>Plant physiology >THE CONSTRUCTION OF ARABIDOPSIS EXPRESSED SEQUENCE TAG ASSEMBLIES - A NEW RESOURCE TO FACILITATE GENE IDENTIFICATION
【24h】

THE CONSTRUCTION OF ARABIDOPSIS EXPRESSED SEQUENCE TAG ASSEMBLIES - A NEW RESOURCE TO FACILITATE GENE IDENTIFICATION

机译:拟南芥表达序列标签组件的构建-一种便于基因鉴定的新资源。

获取原文
获取原文并翻译 | 示例
           

摘要

The generation of large numbers of partial cDNA sequences, or expressed sequence tags (ESTs), has provided a method with which to sample a large number of genes from an organism. More than 25,000 Arabidopsis thaliana ESTs have been deposited in public databases, producing the largest collection of ESTs for any plant species. We describe here the application of a method of reducing redundancy and increasing information content in this collection by grouping overlapping ESTs representing the same gene into a ''contig'' or assembly. The increased information content of these assemblies allows more putative identifications to be assigned based on the results of similarity searches with nucleotide and protein databases. The results of this analysis indicate that sequence information is available for approximately 12,600 nonoverlapping ESTs from Arabidopsis. Comparison of the assemblies with 953 Arabidopsis coding sequences indicates that up to 57% of all Arabidopsis genes are represented by an EST. Clustering analysis of these sequences suggests that between 300 and 700 gene families are represented by between 700 and 2000 sequences in the EST database. A database of the assembled sequences, their putative identifications, and cellular roles is available through the World Wide Web. [References: 25]
机译:大量的部分cDNA序列或表达的序列标签(EST)的产生,提供了一种从生物体中采样大量基因的方法。超过25,000种拟南芥ESTs已保存在公共数据库中,是所有植物物种中最大的ESTs集合。我们在这里描述了通过将代表同一基因的重叠EST分组为“重叠群”或装配体来减少此集合中的冗余并增加信息含量的方法的应用。这些程序集增加的信息内容允许基于与核苷酸和蛋白质数据库的相似性搜索结果分配更多的推定标识。该分析的结果表明,序列信息可用于拟南芥中约12,600个不重叠的EST。装配体与953个拟南芥编码序列的比较表明,所有拟南芥基因中多达57%由EST代表。这些序列的聚类分析表明,EST数据库中的700至2000个序列代表了300至700个基因家族。可以通过万维网获得组装序列,其推定标识和细胞作用的数据库。 [参考:25]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号