solGS: a web-based tool for genomic selection

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• 作者：Isaak Y Tecle (1)
  Jeremy D Edwards (1)
  Naama Menda (1)
  Chiedozie Egesi (2)
  Ismail Y Rabbi (3)
  Peter Kulakow (3)
  Robert Kawuki (4)
  Jean-Luc Jannink (5)
  Lukas A Mueller (1)
  
  1. Boyce Thompson Institute for Plant Research ; Cornell University ; Ithaca ; NY ; USA
  2. National Root Crops Research Institute (NRCRI) ; Umudike ; Nigeria
  3. International Institute of Tropical Agriculture (IITA) ; Ibadan ; Oyo State ; Nigeria
  4. National Crops Resources Research Institute ; Kampala ; Uganda
  5. USDA-ARS ; Robert W. Holley Center for Agriculture and Health ; Cornell University ; Ithaca ; NY ; USA
  
• 关键词：Genomic selection ; RR ; BLUP ; Bioinformatics ; Database ; Web ; based tool
• 刊名：BMC Bioinformatics
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：15
• 期：1
• 全文大小：1,118 KB
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• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Combinatorial Libraries; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105

文摘

Background Genomic selection (GS) promises to improve accuracy in estimating breeding values and genetic gain for quantitative traits compared to traditional breeding methods. Its reliance on high-throughput genome-wide markers and statistical complexity, however, is a serious challenge in data management, analysis, and sharing. A bioinformatics infrastructure for data storage and access, and user-friendly web-based tool for analysis and sharing output is needed to make GS more practical for breeders. Results We have developed a web-based tool, called solGS, for predicting genomic estimated breeding values (GEBVs) of individuals, using a Ridge-Regression Best Linear Unbiased Predictor (RR-BLUP) model. It has an intuitive web-interface for selecting a training population for modeling and estimating genomic estimated breeding values of selection candidates. It estimates phenotypic correlation and heritability of traits and selection indices of individuals. Raw data is stored in a generic database schema, Chado Natural Diversity, co-developed by multiple database groups. Analysis output is graphically visualized and can be interactively explored online or downloaded in text format. An instance of its implementation can be accessed at the NEXTGEN Cassava breeding database, http://cassavabase.org/solgs. Conclusions solGS enables breeders to store raw data and estimate GEBVs of individuals online, in an intuitive and interactive workflow. It can be adapted to any breeding program.