Malathi Surapaneni, Divya Balakrishnan, Krishnamraju Addanki, Venkateswara Rao Yadavalli, Arun Prem Kumar, P. Prashanthi, R. M. Sundaram, Sarla Neelamraju
{"title":"Fine mapping of interspecific secondary CSSL populations revealed key regulators for grain weight at qTGW3.1 locus from Oryza nivara","authors":"Malathi Surapaneni, Divya Balakrishnan, Krishnamraju Addanki, Venkateswara Rao Yadavalli, Arun Prem Kumar, P. Prashanthi, R. M. Sundaram, Sarla Neelamraju","doi":"10.1007/s12298-024-01483-0","DOIUrl":null,"url":null,"abstract":"<p>Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC<sub>2</sub>F<sub>10</sub> BILs) derived from Swarna/<i>O. nivara</i> IRGC81848 (NPS) and 90 BILs from Swarna/<i>O. nivara</i> IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs <i>qTGW2.1, qTGW8.1</i> and <i>qTGW11.1</i> were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL <i>qTGW3.1</i> and <i>qTGW12.1</i> with 6 to 32% PVE. In all QTLs, <i>O. nivara</i> alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. <i>Oryza sativa</i> were selected from each population and secondary F<sub>2</sub> mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as <i>qTGW3.1</i> was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (<i>OS03go103400</i>) involved in plant growth and development located at this genomic locus might be the candidate gene for <i>qTGW3.1</i>. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in <i>Oryza</i> and lays a solid foundation for the breeding for high yield.</p>","PeriodicalId":20148,"journal":{"name":"Physiology and Molecular Biology of Plants","volume":"35 1","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physiology and Molecular Biology of Plants","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s12298-024-01483-0","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Grain weight (GW) is the most important stable trait that directly contributes to crop yield in case of cereals. A total of 105 backcross introgression lines (BC2F10 BILs) derived from Swarna/O. nivara IRGC81848 (NPS) and 90 BILs from Swarna/O. nivara IRGC81832 (NPK) were evaluated for thousand-grain weight (TGW) across four years (wet seasons 2014, 2015, 2016 and 2018) and chromosome segment substitution lines (CSSLs) were selected. From significant pair- wise mean comparison with Swarna, a total of 77 positively and 29 negatively significant NPS lines and 62 positively and 29 negatively significant NPK lines were identified. In all 4 years, 14 NPS lines and 9 NPK lines were positively significant and one-line NPS69 (IET22161) was negatively significant for TGW over Swarna consistently. NPS lines and NPK lines were genotyped using 111 and 140 polymorphic SSRs respectively. Quantitative trait locus (QTL) mapping using ICIM v4.2 software showed 13 QTLs for TGW in NPS. Three major effect QTLs qTGW2.1, qTGW8.1 and qTGW11.1 were identified in NPS for two or more years with PVE ranging from 8 to 14%. Likewise, 10 QTLs were identified in NPK and including two major effect QTL qTGW3.1 and qTGW12.1 with 6 to 32% PVE. In all QTLs, O. nivara alleles increased TGW. These consistent QTLs are very suitable for fine mapping and functional analysis of grain weight. Further in this study, CSSLs NPS1 (10-2S) and NPK61 (158 K) with significantly higher grain weight than the recurrent parent, Swarna cv. Oryza sativa were selected from each population and secondary F2 mapping populations were developed. Using Bulked Segregant QTL sequencing, a grain weight QTL, designated as qTGW3.1 was fine mapped from the cross between NPK61 and Swarna. This QTL explained 48% (logarithm of odds = 32.2) of the phenotypic variations and was fine mapped to a 31 kb interval using recombinant analysis. GRAS transcription factor gene (OS03go103400) involved in plant growth and development located at this genomic locus might be the candidate gene for qTGW3.1. The results of this study will help in further functional studies and improving the knowledge related to the molecular mechanism of grain weight in Oryza and lays a solid foundation for the breeding for high yield.
期刊介绍:
Founded in 1995, Physiology and Molecular Biology of Plants (PMBP) is a peer reviewed monthly journal co-published by Springer Nature. It contains research and review articles, short communications, commentaries, book reviews etc., in all areas of functional plant biology including, but not limited to plant physiology, biochemistry, molecular genetics, molecular pathology, biophysics, cell and molecular biology, genetics, genomics and bioinformatics. Its integrated and interdisciplinary approach reflects the global growth trajectories in functional plant biology, attracting authors/editors/reviewers from over 98 countries.