Gramene QTL database: development, content and applications.

Gramene QTL database: development, content and applications.
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Gramene QTL数据库:开发,内容和应用程序。

DOI:
10.1093/database/bap005
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发表时间:
2009
期刊:
Database : the journal of biological databases and curation
影响因子:
--
通讯作者:
McCouch S
McCouch S
中科院分区:
其他
文献类型:
--
作者:
Ni J;Pujar A;Youens-Clark K;Yap I;Jaiswal P;Tecle I;Tung CW;Ren L;Spooner W;Wei X;Avraham S;Ware D;Stein L;McCouch S

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Gramene是植物的比较信息资源,它整合了不同数据域的数据。在这篇文章中,我们描述了一个数量性状基因座(QTL)数据库的发展,并说明它如何可以用来促进正向和反向遗传学研究。QTL数据库包含世界上最大的水稻QTL数据在线收集。利用侧翼标记作为锚,最初在个体遗传图谱上报道的QTL已经系统地与水稻序列比对,在那里它们可以作为标准基因组特征被搜索。研究人员可以确定一个QTL是否与独立实验中检测到的其他QTL共定位,并可以将多个研究的数据联合收割机以提高QTL位置的分辨率。可以鉴定落在QTL区间内的候选基因,并且可以基于本体术语提供的功能注释来推断它们与特定表型的关系。在功能基因组学群体和关联作图小组中鉴定的突变可以与QTL区域比对,以促进基因-表型关联的精细作图和验证。通过组装和整合不同类型的数据和信息,跨物种和生物复杂性的水平,QTL数据库提高了理解和利用QTL信息在生物研究中的潜力。
Gramene is a comparative information resource for plants that integrates data across diverse data domains. In this article, we describe the development of a quantitative trait loci (QTL) database and illustrate how it can be used to facilitate both the forward and reverse genetics research. The QTL database contains the largest online collection of rice QTL data in the world. Using flanking markers as anchors, QTLs originally reported on individual genetic maps have been systematically aligned to the rice sequence where they can be searched as standard genomic features. Researchers can determine whether a QTL co-localizes with other QTLs detected in independent experiments and can combine data from multiple studies to improve the resolution of a QTL position. Candidate genes falling within a QTL interval can be identified and their relationship to particular phenotypes can be inferred based on functional annotations provided by ontology terms. Mutations identified in functional genomics populations and association mapping panels can be aligned with QTL regions to facilitate fine mapping and validation of gene–phenotype associations. By assembling and integrating diverse types of data and information across species and levels of biological complexity, the QTL database enhances the potential to understand and utilize QTL information in biological research.
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