Literature DB >> 33098552

Discovery of genomic regions and candidate genes for grain weight employing next generation sequencing based QTL-seq approach in rice (Oryza sativa L.).

Reddyyamini Bommisetty1, Navajeet Chakravartty2, Reddaiah Bodanapu2, Jeevula B Naik3, Sanjib K Panda4, Sivarama P Lekkala2, Krishna Lalam2, George Thomas2, S J Mallikarjuna1, G R Eswar1, Gopalakrishna M Kadambari1, Swarajyalakshmi N Bollineni3, Keerthi Issa3, Srividhya Akkareddy3, C Srilakshmi5, K Hariprasadreddy1, P Rameshbabu1, P Sudhakar6, Saurabh Gupta2, V B R Lachagari7, Lakshminarayana R Vemireddy8.   

Abstract

Rice (Oryza sativa L.) yield enhancement is one of the prime objectives of plant breeders. Elucidation of the inheritance of grain weight, a key yield component trait, is of paramount importance for raising the yield thresholds in rice. In the present investigation, we employed Next-Generation Sequencing based QTL-seq approach to identify major genomic regions associated with grain weight using mapping populations derived from a cross between BPT5204 and MTU3626. QTL-seq analysis identified three grain weight quantitative trait loci (QTL) viz., qGW1 (35-40 Mb), qGW7 (10-18 Mb), and qGW8 (2-5 Mb) on chromosomes 1, 7 and 8, respectively and all are found to be novel. Further, qGW8 was confirmed through conventional QTL mapping in F2, F3 and BC1F2 populations and found to explain the phenotypic variance of 17.88%, 16.70% and 15.00%, respectively, indicating a major QTL for grain weight. Based on previous reports, two candidate genes in the qGW8 QTL were predicted i.e., LOC_Os08g01490 (Cytochrome P450), and LOC_Os08g01680 (WD domain, G-beta repeat domain containing protein) and through in silico analysis they were found to be highly expressed in reproductive organs during different stages of grain development. Here, we have demonstrated that QTL-seq is one of the rapid approaches to uncover novel QTLs controlling complex traits. The candidate genes identified in the present study undoubtedly enhance our understanding of the mechanism and inheritance of the grain weight. These candidate genes can be exploited for yield enhancement after confirmation through complementary studies.

Entities:  

Keywords:  Grain weight; INDELs; Mapping; Next-generation sequencing; QTL-seq; Rice; SNPs; ∆SNP-Index

Mesh:

Substances:

Year:  2020        PMID: 33098552     DOI: 10.1007/s11033-020-05904-7

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


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