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QTL-BSA: A Bulked Segregant Analysis and Visualization Pipeline for QTL-seq.
Wu, Sanling; Qiu, Jie; Gao, Qikang.
Afiliação
  • Wu S; Analysis Center of Agrobiology and Environmental Sciences, Faculty of Agriculture, Life and Environment Sciences, Zhejiang University, Hangzhou, China. wusanling@zju.edu.cn.
  • Qiu J; Department of Agronomy and James D Watson Institute of Genome Science, Zhejiang University, Hangzhou, China.
  • Gao Q; Analysis Center of Agrobiology and Environmental Sciences, Faculty of Agriculture, Life and Environment Sciences, Zhejiang University, Hangzhou, China.
Interdiscip Sci ; 11(4): 730-737, 2019 Dec.
Article em En | MEDLINE | ID: mdl-31388943
In recent years, the application of Whole Genome Sequencing (WGS) on plants has generated sufficient data for the identification of trait-associated genomic loci or genes. A high-throughput genome-assisted QTL-seq strategy, combined with bulked-segregant analysis and WGS of two bulked populations from a segregating progeny with opposite phenotypic trait values, has gained increasing popularities in research community. However, there is no publicly available user friendly software for the identification and visualization. Hence, we developed a tool named QTL-BSA (QTL-bulked segregant analysis and visualization pipeline), which could facilitate the rapid identification and visualization of candidate QTLs from QTL-seq. As a proof-of-concept study, we have applied the tool for the rapid discovery and the identification of genes related with the partial blast resistance in rice. Genomic region of the major QTL identified on chromosome 6, is located between 1.52 and 4.32 Mb, which is consistent with previous studies (2.39-4.39 Mb). We also derived the gene and QTLs functional annotation of this region. QTL-BSA offers a comprehensive solution to facilitate a wide range of programming and visualization tasks in QTL-seq analysis, is expected to be used widely by the research community.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oryza / Genes de Plantas / Biologia Computacional / Polimorfismo de Nucleotídeo Único / Locos de Características Quantitativas / Resistência à Doença Tipo de estudo: Prognostic_studies Idioma: En Revista: Interdiscip Sci Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Oryza / Genes de Plantas / Biologia Computacional / Polimorfismo de Nucleotídeo Único / Locos de Características Quantitativas / Resistência à Doença Tipo de estudo: Prognostic_studies Idioma: En Revista: Interdiscip Sci Ano de publicação: 2019 Tipo de documento: Article