BanSatDB, a whole-genome-based database of putative and experimentally validated microsatellite markers of three Musa species

Vasu Arora; Neera Kapoor; Samar Fatma; Sarika Jaiswal; Mir Asif Iquebal; Anil Rai; Dinesh Kumar

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BanSatDB, a whole-genome-based database of putative and experimentally validated microsatellite markers of three Musa species

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The genus Musa is one of three genera in the family Musaceae,which includes bananas and plantains,which are monocotyledonous plants.Bananas have valuable nutritional content of vitamin C,B6,minerals,and dietary fiber and are a rich food energy source,given that carbohydrates account for 22％-32％ of fruit weight.Molecular markers are valuable for crop improvement and population genetics studies.The availabihty of whole-genome sequence and in silico approaches has revolutionized bulk marker discovery.We describe an online web genomic resource,BanSatDB (http://webtom.cabgrid.resin/bansatdb/) having the highest number (＞341,000) of putative STR markers from Musa genera so far,represented by three species:M.acuminata (110,000),M.balbisiana (107,000),and M.itinerans (124,000)from 11 chromosomes of each species.BanSatDB has also been populated with 580 validated STR markers from the published literature.It is based on a three-tier architecture using MySQL,PHP and Apache.The markers can be retrieved by use of multiple search parameters including chromosome number(s),microsatellite types (simple or compound),repeat nucleotides (1-6),copy number,microsatellite length,pattern of repeat motif,and chromosome location.These markers can be used for Distinctness,Uniformity and Stability (DUS) tests of variety identification and for marker assisted selection (MAS) in variety improvement and management.These STRs have also proved to be helpful in classification of Musa germplasm to distinguish individual accessions and in the development of a standardized procedure for genotyping.These markers can also be used in gene discovery and QTL mapping.The database represents a source of markers for developing and implementing new approaches for molecular breeding,which are required to enhance banana productivity.

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《作物学报（英文版）》 |2018年第6期|642-650|共9页
作者
Vasu Arora; Neera Kapoor; Samar Fatma; Sarika Jaiswal; Mir Asif Iquebal; Anil Rai; Dinesh Kumar;
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Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

School of Sciences, Indira Gandhi National Open University, New Delhi 110068, India;

Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

Center for Agricultural Bioinformatics, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110012, India;

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BanSatDB, a whole-genome-based database of putative and experimentally validated microsatellite markers of three Musa species

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