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Database (Oxford). 2015 Aug 19;2015. doi: 10.1093/database/bav078. Print 2015.

CicArVarDB: SNP and InDel database for advancing genetics research and breeding applications in chickpea.

Database : the journal of biological databases and curation

Dadakhalandar Doddamani, Aamir W Khan, Mohan A V S K Katta, Gaurav Agarwal, Mahendar Thudi, Pradeep Ruperao, David Edwards, Rajeev K Varshney

Affiliations

  1. Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India.
  2. School of Agriculture and Food Sciences, University of Queensland, St Lucia, Queensland, Australia 4072, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and.
  3. School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and Institute of Agriculture, The University of Western Australia, Perth, Western Australia, Australia 6009.
  4. Research Program Grain Legumes, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad 502 324, Telangana State, India, School of Plant Biology, The University of Western Australia, Perth, Western Australia, Australia 6009 and [email protected].

PMID: 26289427 PMCID: PMC4541373 DOI: 10.1093/database/bav078

Abstract

Molecular markers are valuable tools for breeders to help accelerate crop improvement. High throughput sequencing technologies facilitate the discovery of large-scale variations such as single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs). Sequencing of chickpea genome along with re-sequencing of several chickpea lines has enabled the discovery of 4.4 million variations including SNPs and InDels. Here we report a repository of 1.9 million variations (SNPs and InDels) anchored on eight pseudomolecules in a custom database, referred as CicArVarDB that can be accessed at http://cicarvardb.icrisat.org/. It includes an easy interface for users to select variations around specific regions associated with quantitative trait loci, with embedded webBLAST search and JBrowse visualisation. We hope that this database will be immensely useful for the chickpea research community for both advancing genetics research as well as breeding applications for crop improvement. Database URL: http://cicarvardb.icrisat.org.

© The Author(s) 2015. Published by Oxford University Press.

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