{"doi":"10.1111/pbi.12836","title":"Development and evaluation of high‐density Axiom<sup>®</sup><i>Cicer<scp>SNP</scp></i> Array for high‐resolution genetic mapping and breeding applications in chickpea","abstract":"<jats:title>Summary</jats:title><jats:p>To accelerate genomics research and molecular breeding applications in chickpea, a high‐throughput <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content> genotyping platform ‘Axiom<jats:sup>®</jats:sup><jats:italic>Cicer<jats:styled-content style=\"fixed-case\">SNP</jats:styled-content></jats:italic> Array’ has been designed, developed and validated. Screening of whole‐genome resequencing data from 429 chickpea lines identified 4.9 million <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s, from which a subset of 70 463 high‐quality nonredundant <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s was selected using different stringent filter criteria. This was further narrowed down to 61 174 <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s based on <jats:italic>p</jats:italic>‐convert score ≥0.3, of which 50 590 <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s could be tiled on array. Among these tiled <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s, a total of 11 245 <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s (22.23%) were from the coding regions of 3673 different genes. The developed Axiom<jats:sup>®</jats:sup><jats:italic>Cicer<jats:styled-content style=\"fixed-case\">SNP</jats:styled-content></jats:italic> Array was used for genotyping two recombinant inbred line populations, namely <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>03 (<jats:styled-content style=\"fixed-case\">ICC</jats:styled-content> 4958 × <jats:styled-content style=\"fixed-case\">ICC</jats:styled-content> 1882) and <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>04 (<jats:styled-content style=\"fixed-case\">ICC</jats:styled-content> 283 × <jats:styled-content style=\"fixed-case\">ICC</jats:styled-content> 8261). Genotyping data reflected high success and polymorphic rate, with 15 140 (29.93%; <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>03) and 20 018 (39.57%; <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>04) polymorphic <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s. High‐density genetic maps comprising 13 679 <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s spanning 1033.67 <jats:styled-content style=\"fixed-case\">cM</jats:styled-content> and 7769 <jats:styled-content style=\"fixed-case\">SNP</jats:styled-content>s spanning 1076.35 cM were developed for <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>03 and <jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>04 populations, respectively. QTL analysis using multilocation, multiseason phenotyping data on these <jats:styled-content style=\"fixed-case\">RIL</jats:styled-content>s identified 70 (<jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>03) and 120 (<jats:styled-content style=\"fixed-case\">ICCRIL</jats:styled-content>04) main‐effect <jats:styled-content style=\"fixed-case\">QTL</jats:styled-content>s on genetic map. Higher precision and potential of this array is expected to advance chickpea genetics and breeding applications.</jats:p>","journal":"Plant Biotechnology Journal","year":2018,"id":15023,"datarank":2.5068503002428404,"base_score":4.68213122712422,"endowment":4.68213122712422,"self_citation_contribution":0.7023196840686331,"citation_network_contribution":1.8045306161742074,"self_endowment_contribution":0.7023196840686331,"citer_contribution":1.8045306161742074,"corpus_percentile":null,"corpus_rank":null,"citation_count":107,"citer_count":73,"citers_with_citation_signal":62,"citers_with_endowment":62,"datacite_reuse_total":6,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":116181,"name":"Ankit Jain","orcid":null,"position":1,"is_corresponding":false},{"id":116182,"name":"Sandip M. Kale","orcid":null,"position":2,"is_corresponding":false},{"id":116183,"name":"Dadakhalandar Doddamani","orcid":null,"position":3,"is_corresponding":false},{"id":116184,"name":"Annapurna Chitikineni","orcid":null,"position":4,"is_corresponding":false},{"id":116185,"name":"Mahendar Thudi","orcid":null,"position":5,"is_corresponding":false},{"id":56282,"name":"Rajeev K. Varshney","orcid":"0000-0002-4562-9131","position":6,"is_corresponding":false},{"id":116180,"name":"Manish Roorkiwal","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"base_score":4.68213122712422,"endowment":4.68213122712422,"datacite_reuse_total":6,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"28913885","pmcid":"PMC5866945","openalex_id":"https://openalex.org/W2754222093","authors":[],"funders":[{"funder_name":"Bill and Melinda Gates 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