Mapping of QTLs for Yield Traits Using F 2:3:4 Populations Derived From Two Alien Introgression Lines Reveals qTGW8.1 as a Consistent QTL for Grain Weight From Oryza nivara

• Published in: Frontiers in plant science 2022, Vol.13, p.790221
• Main Authors: Beerelli, Kavitha, Balakrishnan, Divya, Addanki, Krishnam Raju, Surapaneni, Malathi, Rao Yadavalli, Venkateswara, Neelamraju, Sarla
• Format: Article
• Language: English
• ISSN: 1664-462X; 1664-462X

Wild introgressions play a crucial role in crop improvement by transferring important novel alleles and broadening allelic diversity of cultivated germplasm. In this study, two stable backcross alien introgression lines 166s and 14s derived from Swarn/ IRGC81848 were used as parents to generate populations to map quantitative trait loci (QTLs) for yield-related traits. Field evaluation of yield-related traits in F , F , and F population was carried out in normal irrigated conditions during the wet season of 2015 and dry seasons of 2016 and 2018, respectively. Plant height, tiller number, productive tiller number, total dry matter, and harvest index showed a highly significant association to single plant yield in F , F , and F . In all, 21, 30, and 17 QTLs were identified in F , F , and F , respectively, for yield-related traits. QTLs with 12.54% phenotypic variance (PV) in F , with 13.01% PV, with 10.08% PV in F , and with 15.19% PV in F were identified as major effect QTLs. QTLs and were detected for grain yield in F and F with PV 8.5 and 6.7%, respectively. The trait enhancing alleles of QTLs , , , , and were from . QTLs of the yield contributing traits were found clustered in the same chromosomal region. was identified in a 2.6 Mb region between RM3480 and RM3452 in all three generations with PV 6.1 to 9.8%. This stable and consistent allele from can be fine mapped for identification of causal genes. From this population, lines C 12, C 124, C 128, and C 143 were identified with significantly higher SPY and C 103, C 116, and C 117 had consistently higher thousand-grain weight values than both the parents and Swarna across the generations and are useful in gene discovery for target traits and further crop improvement.