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Gramene数量性状基因座数据库:开发、内容与应用

Gramene QTL database: development, content and applications.

作者信息

Ni Junjian, Pujar Anuradha, Youens-Clark Ken, Yap Immanuel, Jaiswal Pankaj, Tecle Isaak, Tung Chih-Wei, Ren Liya, Spooner William, Wei Xuehong, Avraham Shuly, Ware Doreen, Stein Lincoln, McCouch Susan

机构信息

Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853-1901, USA and Cold Spring Harbor Labs, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA.

出版信息

Database (Oxford). 2009;2009:bap005. doi: 10.1093/database/bap005. Epub 2009 May 8.

Abstract

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.

摘要

Gramene是一个植物比较信息资源库,整合了跨不同数据领域的数据。在本文中,我们描述了一个数量性状基因座(QTL)数据库的开发,并说明了如何利用它来促进正向和反向遗传学研究。该QTL数据库包含了世界上最大的水稻QTL数据在线集合。以侧翼标记为锚点,最初在单个遗传图谱上报道的QTL已被系统地比对到水稻序列上,在那里它们可以作为标准基因组特征进行搜索。研究人员可以确定一个QTL是否与在独立实验中检测到的其他QTL共定位,并可以整合来自多项研究的数据以提高QTL定位的分辨率。可以识别位于QTL区间内的候选基因,并根据本体术语提供的功能注释推断它们与特定表型的关系。在功能基因组群体和关联作图群体中鉴定出的突变可以与QTL区域比对,以促进基因-表型关联的精细定位和验证。通过跨物种和生物复杂程度层次组装和整合不同类型的数据和信息,QTL数据库增强了在生物学研究中理解和利用QTL信息的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c553/2790302/d26a30e433ad/bap005f1.jpg

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