SNP-based discovery of salinity-tolerant QTLs in a bi-parental population of rice (Oryza sativa)

Abstract

Breeding for salt tolerance is the most promising approach to enhance the productivity of saline prone areas. However, polygenic inheritance of salt tolerance in rice acts as a bottleneck in conventional breeding for salt tolerance. Hence, we set our goals to construct a single nucleotide polymorphism (SNP)-based molecular map employing high-throughput SNP marker technology and to investigate salinity tolerant QTLs with closest flanking markers using an elite rice background. Seedling stage salinity responses were assessed in a population of 281 recombinant inbred lines (RILs) derived from the cross between At354 (salt tolerant) and Bg352 (salt susceptible), by 11 morpho-physiological indices under a hydroponic system. Selected extreme 94 RILs were genotyped using Illumina Infinium rice 6K SNP array and densely saturated molecular map spanning 1460.81 cM of the rice genome with an average interval of 1.29 cM between marker loci was constructed using 1135 polymorphic SNP markers. The results revealed 83 significant QTLs for 11 salt responsive traits explaining 12.5-46.7 % of phenotypic variation in respective traits. Of them, 72 QTLs responsible for 10 traits were co-localized together forming 14 QTL hotspots at 14 different genomic regions. The all QTL hotspots were flanked less than 1 Mb intervals and therefore the SNP loci associated with these QTL hotspots would be important in candidate gene discovery for salt tolerance.

In Silico Identification of QTL-Based Polymorphic Genes as Salt-Responsive Potential Candidates through Mapping with Two Reference Genomes in Rice

“…QTL-based screening was performed on previously identified salinity stress-related QTL hotspots [35], and we observed slight deviations (0.1 Mb to 3.0 Mb) in the corresponding locations of QTL hotspots with reference to R498 ( Figure 2). As expected, a low number of total variants were observed in R498 in each and every QTL examined compared to the Nipponbare.…”

“…In this study, abiotic stress-related genes located within previously identified QTL hotspots were analyzed to identify the variants in At 354 and Bg 352. Altogether, we used 14 QTL hotspots flanked less than 1 Mb intervals explaining 12.5-46.7% of phenotypic variation in salinity-related traits [35]. We could find 106 abiotic stress-related genes associated with these QTL hotspots.…”

“…Also, we detected the highest number of stress-related genes (19) on the QTL hotspot 2 indicating its potential contribution for salt responsive phenotypic variation. QTL hotspots were previously detected under phytotron conditions of the International Rice Research Institute, Philippines where all possible salinity-related QTLs might not have been expressed [35]. Therefore, in addition to the abiotic stress-related genes within the QTL hotspots, we considered 27 other abiotic stress-related genes which were involved in salt-tolerant pathways.…”

“…The QTL hotspot regions which were previously identified by QTL mapping of At 354 × Bg 352 were queried for prospective abiotic stress-related genes in the regions [35]. In addition, known salt tolerance-related genes were also selected.…”

“…Therefore, it appears that due to the availability of huge re-sequencing data, high-density SNPs-based maps have been developed [33,34]. Gimhani et al (2016) [35] were also able to produce SNP-based highly dense and saturated molecular maps with the C6AIR chip covering 1460. 81 hotspots and 11 solitary QTLs for salt tolerance flanked with SNP markers narrowing down to less than 1 Mb intervals indicating the potential of use in gene mining studies.…”