Dataset Information

Genome-wide association mapping revealed numerous novel genomic loci for grain nutritional and yield-related traits in rice (Oryza sativa L.) landraces.

ABSTRACT: A core set of 190 rice landraces were used to decipher the genetic structure and to discover the chromosomal regions containing QTLs, affecting the grain micro-nutrients, fatty acids, and yield-related traits by using 148 molecular markers in this study. Landraces were categorized into three sub-groups based on population stratification study and followed by neighbor-joining tree and principal component analysis. Analysis of variance revealed abundant variations among the landraces for studied traits with less influence of environmental factors. Genome Wide Association Studies (GWAS) revealed 22 significant and consistent QTLs through marker trait association (MTAs) for 12 traits based on 2 years and pooled analysis. Out of 22 QTLs, three have been reported earlier while 19 QTLs are novel. Interestingly, 13 QTLs out of 22 were explained more than 10% phenotypic variance. Association of RM1148 and RM205 with Days to 50% flowering was comparable with flowering control genes Ghd8/qDTH8 and qDTH9, respectively. Similarly, Zn content was associated with RM44, which is situated within the QTL qZn8-1. Moreover, significant association of RM25 with oleic acid content was closely positioned with QTL qOle8. Association of RM7434 with grain yield/plant; RM184 with spikelet fertility %; R3M10, R9M42 with hundred seed weight; RM536, RM17467, RM484, RM26063 with Fe content; RM44, RM6839 with Zn content are the major outcomes of this study. In addition, association of R11M23 with days to 50% flowering, panicle length and total spikelets per panicle are explained the possible occurrence of pleiotropism among these traits. Prominent rice landraces viz., Anjani (early maturity); Sihar (extra dwarf); Gangabaru (highest grain yield/plant); Karhani (highest iron content); Byalo-2 (highest zinc content) and Kadamphool (highest oleic acid) were identified through this study. The present study will open many avenues towards utilization of these QTLs and superior landraces in rice breeding for developing nutrition-rich high yielding varieties.

SUBMITTER: Sahu PK

PROVIDER: S-EPMC7585584 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

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.

Project description:Rice is an important grain that is the staple food for most of the world's population. Drought is one of the major stresses that negatively affects rice yield. The nature of drought tolerance in rice is complex as it is determined by various components and has low heritability. Therefore, to ensure success in breeding programs for drought tolerant rice, QTLs (quantitative trait loci) of interest must be stable in a variety of plant genotypes and environments. This study identified stable QTLs in rice chromosomes in a variety of backgrounds and environments and conducted a meta-QTL analysis of stable QTLs that have been reported by previous research for use in breeding programs. A total of 653 QTLs for drought tolerance in rice from 27 genetic maps were recorded for analysis. The QTLs recorded were related to 13 traits in rice that respond to drought. Through the use of BioMercartor V4.2, a consensus map containing QTLs and molecular markers were generated using 27 genetic maps that were extracted from the previous 20 studies and meta-QTL analysis was conducted on the consensus map. A total of 70 MQTLs were identified and a total of 453 QTLs were mapped into the meta-QTL areas. Five meta-QTLs from chromosome 1 (MQTL 1.5 and MQTL 1.6), chromosome 2 (MQTL2.1 and MQTL 2.2) and chromosome 3 (MQTL 3.1) were selected for functional annotation as these regions have high number of QTLs and include many traits in rice that respond to drought. A number of genes in MQTL1.5 (268 genes), MQTL1.6 (640 genes), MQTL 2.1 (319 genes), MQTL 2.2 (19 genes) and MQTL 3.1 (787 genes) were annotated through Blast2GO. Few major proteins that respond to drought stress were identified in the meta-QTL areas which are Abscisic Acid-Insensitive Protein 5 (ABI5), the G-box binding factor 4 (GBF4), protein kinase PINOID (PID), histidine kinase 2 (AHK2), protein related to autophagy 18A (ATG18A), mitochondrial transcription termination factor (MTERF), aquaporin PIP 1-2, protein detoxification 48 (DTX48) and inositol-tetrakisphosphate 1-kinase 2 (ITPK2). These proteins are regulatory proteins involved in the regulation of signal transduction and gene expression that respond to drought stress. The meta-QTLs derived from this study and the genes that have been identified can be used effectively in molecular breeding and in genetic engineering for drought resistance/tolerance in rice.

Project description:BackgroundRice, the most important crop in Asia, has been cultivated in Taiwan for more than 5000 years. The landraces preserved by indigenous peoples and brought by immigrants from China hundreds of years ago exhibit large variation in morphology, implying that they comprise rich genetic resources. Breeding goals according to the preferences of farmers, consumers and government policies also alter gene pools and genetic diversity of improved varieties. To unveil how genetic diversity is affected by natural, farmers', and breeders' selections is crucial for germplasm conservation and crop improvement.ResultsA diversity panel of 148 rice accessions, including 47 cultivars and 59 landraces from Taiwan and 42 accessions from other countries, were genotyped by using 75 molecular markers that revealed an average of 12.7 alleles per locus with mean polymorphism information content of 0.72. These accessions could be grouped into five subpopulations corresponding to wild rice, japonica landraces, indica landraces, indica cultivars, and japonica cultivars. The genetic diversity within subpopulations was: wild rices > landraces > cultivars; and indica rice > japonica rice. Despite having less variation among cultivars, japonica landraces had greater genetic variation than indica landraces because the majority of Taiwanese japonica landraces preserved by indigenous peoples were classified as tropical japonica. Two major clusters of indica landraces were formed by phylogenetic analysis, in accordance with immigration from two origins. Genetic erosion had occurred in later japonica varieties due to a narrow selection of germplasm being incorporated into breeding programs for premium grain quality. Genetic differentiation between early and late cultivars was significant in japonica (FST = 0.3751) but not in indica (FST = 0.0045), indicating effects of different breeding goals on modern germplasm. Indigenous landraces with unique intermediate and admixed genetic backgrounds were untapped, representing valuable resources for rice breeding.ConclusionsThe genetic diversity of improved rice varieties has been substantially shaped by breeding goals, leading to differentiation between indica and japonica cultivars. Taiwanese landraces with different origins possess various and unique genetic backgrounds. Taiwanese rice germplasm provides diverse genetic variation for association mapping to unveil useful genes and is a precious genetic reservoir for rice improvement.

Dataset Information

Genome-wide association mapping revealed numerous novel genomic loci for grain nutritional and yield-related traits in rice (Oryza sativa L.) landraces.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets