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Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.).

ABSTRACT: In rice (Oryza sativa L.), during the course of domestication, numerous beneficial alleles remain untapped in the progenitor wild species and landraces. This study aims at uncovering these promising alleles of six key genes influencing the yield, such as DEP1, Ghd7, Gn1a, GS3, qSW5 and sd1 by targeted resequencing of the 200 rice genotypes. In all, 543 nucleotide variations including single nucleotide polymorphisms and insertion and deletion polymorphisms were identified from the targeted genes. Of them, 225 were novel alleles, which identified in the present study only and 91 were beneficial alleles that showed significant association with the yield traits. Besides, we uncovered 128 population-specific alleles with indica being the highest of 79 alleles. The neutrality tests revealed that pleiotropic gene, Ghd7 and major grain size contributing gene, GS3 showed positive and balanced selection, respectively during the domestication. Further, the haplotype analysis revealed that some of the rice genotypes found to have rare haplotypes, especially the high yielding variety, BPT1768 has showed maximum of three genes such as Gn1a-8, qSW5-12 and GS3-29. The rice varieties with novel and beneficial alleles along with the rare haplotypes identified in the present study could be of immense value for yield improvement in the rice breeding programs.

SUBMITTER: Vemireddy LR

PROVIDER: S-EPMC6547710 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.).

Vemireddy Lakshminarayana R LR Kadambari Gopalakrishnamurty G Reddy G Eswar GE Kola Vijaya Sudhakara Rao VSR Ramireddy Eswarayya E Puram Venkata Ramana Rao VRR Badri Jyothi J Eslavath Suresh N SN Bollineni Swarajyalakshmi N SN Naik Bukya J BJ Chintala Sreelakshmi S Pottepalem Rameshbabu R Akkareddy Srividhya S Nagireddy Ranjithkumar R Reddy Lachagari V B LVB Bodanapu Reddaiah R Lekkala Sivarama P SP Chakravartty Navajeet N Siddiq E A EA

Scientific reports 20190603 1

In rice (Oryza sativa L.), during the course of domestication, numerous beneficial alleles remain untapped in the progenitor wild species and landraces. This study aims at uncovering these promising alleles of six key genes influencing the yield, such as DEP1, Ghd7, Gn1a, GS3, qSW5 and sd1 by targeted resequencing of the 200 rice genotypes. In all, 543 nucleotide variations including single nucleotide polymorphisms and insertion and deletion polymorphisms were identified from the targeted genes. ...[more]

PMID: 31160789

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Project description:Hybrid rice varieties can outyield the best inbred varieties by 15 - 30% with appropriate management. However, hybrid rice requires more inputs and management than inbred rice to realize a yield advantage in high-yielding environments. The development of stress-tolerant hybrid rice with lowered input requirements could increase hybrid rice yield relative to production costs. We used genomic prediction to evaluate the combining abilities of 564 stress-tolerant lines used to develop Green Super Rice with 13 male sterile lines of the International Rice Research Institute for yield-related traits. We also evaluated the performance of their F1 hybrids. We identified male sterile lines with good combining ability as well as F1 hybrids with potential further use in product development. For yield per plant, accuracies of genomic predictions of hybrid genetic values ranged from 0.490 to 0.822 in cross-validation if neither parent or up to both parents were included in the training set, and both general and specific combining abilities were modeled. The accuracy of phenotypic selection for hybrid yield per plant was 0.682. The accuracy of genomic predictions of male GCA for yield per plant was 0.241, while the accuracy of phenotypic selection was 0.562. At the observed accuracies, genomic prediction of hybrid genetic value could allow improved identification of high-performing single crosses. In a reciprocal recurrent genomic selection program with an accelerated breeding cycle, observed male GCA genomic prediction accuracies would lead to similar rates of genetic gain as phenotypic selection. It is likely that prediction accuracies of male GCA could be improved further by targeted expansion of the training set. Additionally, we tested the correlation of parental genetic distance with mid-parent heterosis in the phenotyped hybrids. We found the average mid-parent heterosis for yield per plant to be consistent with existing literature values at 32.0%. In the overall population of study, parental genetic distance was significantly negatively correlated with mid-parent heterosis for yield per plant (r = -0.131) and potential yield (r = -0.092), but within female families the correlations were non-significant and near zero. As such, positive parental genetic distance was not reliably associated with positive mid-parent heterosis.

Dataset Information

Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.).

Publications

Uncovering of natural allelic variants of key yield contributing genes by targeted resequencing in rice (Oryza sativa L.).

Similar Datasets

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