Drought is an important factor limiting the growth and development of rice and thereby seriously affects rice yield. The problem may be effectively solved by dissecting the drought-resistance mechanism of rice, creating excellent drought-resistant germplasm, and mining new drought-resistant genes. In this study, 305 accessions (189 Xian, 104 Geng, 5 Aus, and 7 Basmati) were used to identify drought-related phenotypes such as grain yield per plant (GYP), grain number per panicle (GNP), panicle number per plant (PNP), and plant height (PH) under two-year drought stress. The 2017 GYP and 2018 GNP were Xian max, 2018 GYP, 2017 GNP, 2017 and 2018 PNP, and 2018 PH were Basmati max, and only the 2017 PH was Geng max. The population genetic diversity and population structure were analyzed by combining 404,388 single nucleotide polymorphism (SNP) markers distributed on 12 chromosomes. A total of 42 QTLs with significant correlations was identified, among which 10 were adjacent to the loci reported to be associated with drought resistance. Four candidate genes, LOC_Os03g48890, LOC_Os04g35114, LOC_Os11g45924, and LOC_Os06g38950, were identified by functional annotation and haplotype analysis. The R2 of qGYP3.1 was 11.53%, the R2 of qGNP4.2 was 12.09%, the R2 of qPNP11.1 was 10.01%, and the R2 of qPH6.1 was 13.06%. The results have an important theoretical significance and practical application value for the improvement of drought resistance in rice.
Root architecture is a determinant factor of drought resistance in rice and plays essential roles in the absorption of water and nutrients for the survival of rice plants. Dissection of the genetic basis for root structure can help to improve stress-resistance and grain yield in rice breeding. In this study, a total of 391 rice (Oryz asativa L.) accessions were used to perform a genome-wide association study (GWAS) on three root-related traits in rice, including main root length (MRL), average root length (ARL), and total root number (TRN). As a result, 13 quantitative trait loci (QTLs) (qMRL1.1, qMRL1.2, qMRL3.1, qMRL3.2, qMRL3.3, qMRL4.1, qMRL7.1, qMRL8.1, qARL1.1, qARL9.1, qTRN9.1, qTRN9.2, and qTRN11.1) significantly associated with the three traits were identified, among which three (qMRL3.2, qMRL4.1 and qMRL8.1) were overlapped with OsGNOM1, OsARF12 and qRL8.1, respectively, and ten were novel QTLs. Moreover, we also detected epistatic interactions affecting root-related traits and identified 19 related genetic interactions. These results lay a foundation for cloning the corresponding genes for rice root structure, as well as provide important genomic resources for breeding high yield rice varieties.
Drought is one of the key environmental factors affecting the growth and yield potential of rice. Grain shape, on the other hand, is an important factor determining the appearance, quality, and yield of rice grains. Here, we re-sequenced 275 Xian accessions and then conducted a genome-wide association study (GWAS) on six agronomic traits with the 404,411 single nucleotide polymorphisms (SNPs) derived by the best linear unbiased prediction (BLUP) for each trait. Under two years of drought stress (DS) and normal water (NW) treatments, a total of 16 QTLs associated with rice grain shape and grain weight were detected on chromosomes 1, 2, 3, 4, 5, 7, 8, 11, and 12. In addition, these QTLs were analyzed by haplotype analysis and functional annotation, and one clone (GSN1) and five new candidate genes were identified in the candidate interval. The findings provide important genetic information for the molecular improvement of grain shape and weight in rice.
Rice (Oryza sativa L.) appearance quality, which is mainly defined by grain shape and chalkiness, is an important target in rice breeding. In this study, we first re-sequenced 137 indica accessions and then conducted a genome-wide association study (GWAS) for six agronomic traits with the 2,998,034 derived single nucleotide polymorphisms (SNPs) by using the best linear unbiased prediction (BLUP) values for each trait. The results revealed that 195 SNPs had significant associations with the six agronomic traits. Based on the genome-wide linkage disequilibrium (LD) blocks, candidate genes for the target traits were detected within 100 kb upstream and downstream of the relevant SNP loci. Results indicate that six quantitative trait loci (QTLs) significantly associated with six traits (qTGW4.1, qTGW4.2, qGL4.1, qGL12.1, qGL12.2, qGW2.1, qGW4.1, qGW6.1, qGW8.1, qGW8.2, qGW9.1, qGW11.1, qGLWR2.1, qGLWR2.2, qGLWR4.2, qPGWC5.1 and qDEC6.1) were identified for haplotype analysis. Among these QTLs, two (qTGW4.2 and qGW6.1), were overlapped with FLO19 and OsbZIP47, respectively, and the remaining four were novel QTLs. These candidate genes were further validated by haplotype block construction.
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