Recent advances in next generation sequencing have created opportunities to directly identify genetic loci and candidate genes for abiotic stress responses in plants. With the objective of identifying candidate genes within the previously identified QTL-hotspots, the whole genomes of two divergent cultivars for salt responses, namely At 354 and Bg 352, were re-sequenced using Illumina Hiseq 2500 100PE platform and mapped to Nipponbare and R498 genomes. The sequencing results revealed approximately 2.4 million SNPs and 0.2 million InDels with reference to Nipponbare while 1.3 million and 0.07 million with reference to R498 in two parents. In total, 32,914 genes were reported across all rice chromosomes of this study. Gene mining within QTL hotspots revealed 1236 genes, out of which 106 genes were related to abiotic stress. In addition, 27 abiotic stress-related genes were identified in non-QTL regions. Altogether, 32 genes were identified as potential genes containing polymorphic non-synonymous SNPs or InDels between two parents. Out of 10 genes detected with InDels, tolerant haplotypes of Os01g0581400, Os10g0107000, Os11g0655900, Os12g0622500, and Os12g0624200 were found in the known salinity tolerant donor varieties. Our findings on different haplotypes would be useful in developing resilient rice varieties for abiotic stress by haplotype-based breeding studies.Plants 2020, 9, 233 2 of 25 which is accumulated with excessive sodium ions cause unfavorable conditions for agriculture by adversely affecting the soil physical properties. Thus, the interaction between soil sodicity and salinity could seriously compromise the rice growth in the field [6,7]. However, due to the genetic complexity of the trait, development of resilient varieties against salinity stress cannot be achieved by a single step strategy. Due to the polygenic nature of the trait, many Quantitative Trait Loci (QTLs) and Quantitative Trait Nucleotides (QTNs) have been reported linking either with salinity tolerance or susceptibility traits distributed throughout the genome in many rice lines [8][9][10][11][12][13].Although rice is sensitive to salt, especially at the seedling stage and reproductive stage, vast diversity for this trait across the rice varieties offers a promising tool for improving salt tolerance in rice. Pokkali and Nona bokra are popular traditional salt-tolerant indica rice varieties that tolerate up to 80 mM NaCl at the seedling stage and serve as donors for rice salt tolerance [14]. The major strategies for improving salinity tolerance are reducing Na + toxicity by limited Na + net influx, Na + compartmentalization and removal of Na + into the apoplast to achieve a good Na + /K + balance in the shoot under saline condition [3]. It is reported that Pokkali, demonstrates both 'Na + exclusion' and 'ion balance' mechanisms while Nipponbare, a moderate tolerant japonica variety showed only 'ion balance' [14]. Besides, accumulation of compatible osmolytes for osmotic protection, antioxidant regulation and minimalizing the exposure ti...

Root architectural traits are governed by many genes exhibiting polygenic inheritance. The dissection of the genetic basis of root traits could be achieved by mapping of quantitative trait loci (QTLs) using molecular markers. The present study was conducted aiming at identifying root QTLs in rice using a recombinant inbred line (RIL) population derived from At354 and Bg352. At354 has less extensive, thin root structure and Bg352 has apparently large extensive, dense root structure. Ninety one RILs were phenotypically assessed for root traits namely, root volume (RV), top root girth (TRG), root dry weight (RDW) and root length (RL) under hydroponics. Frequency distributions of these traits indicated broad spectrum of genetic variability in the RIL population. Quantitative Trait Loci (QTLs) were mapped using Single Nucleotide Polymorphism (SNP) markers investigated from a previous study corresponding to same RILs. Results revealed eight QTLs associated with TRG and RDW explaining phenotypic variation ranging from 8.3% to 14.8% under non-stress hydroponics. Identified root QTLs were located within the narrow flanking SNP marker intervals of chromosome 2, 4, 5, 7, 8 and 10. Of them, six root QTLs were colocalized exactly within the same flanking regions of previously identified root QTLs under salinity stress, indicating their contribution under both stress and non-stress conditions. The same donor alleles have contributed in both set of QTLs and these results validated and confirmed the fidelity of the QTLs detected on TRG and RDW. Moreover, this study found a closely associated, user friendly, simple sequence repeat marker, RM24894 to the QTL qNTRG10 and qNRDW10 which could facilitate marker assisted breeding.

Purpose : Previously, QTL hotspots were identified for salt tolerance from a RIL population of At354 x Bg352, under a temperature-controlled environment at the International Rice Research Institute, Philippine. However, as the rice-growing environment in Sri Lanka experiences salinity stress exaggerated with high temperature, the importance of revealing QTLs under such environment of a tropical region was realized. Therefore, the present study was focused to examine QTLs under such environment, deploying SNP-based molecular map, and retrieving potential candidate genes underlying the QTLs. Research Method : RIL population was assessed at 12 dSm-1 electrical conductivity coupled with average temperature ranged from 38 to 32 °C, day and night, respectively. QTLs were mapped using SNP markers. Potential candidate genes were identified using NGS-based high-throughput QTL-seq strategy employing whole-genome re-sequencing data of At354 and Bg352 and Gene Ontology approach. Findings : The results revealed a broad spectrum of phenotypic variation and a significant coefficient of correlation among the morpho-physiological traits in the RIL population. Four QTLs were revealed on chromosome 7, 9, and 11 for shoot Na + concentration (qSNC7), shoot K + concentration (qSKC9), shoot Na + / K + ratio (qSNK9) and root length (qRL11). Five genes, Os07g0635900, Os07g0637300, Os09g0330000, Os11g0514500, and Os11g0523800 within novel QTLs with polymorphic variants between At354 and Bg352, were recognized as potential candidate genes regulating salinity stress. Originality / Value : The putative candidate genes have been reported to be involved in cellular transmembrane and growth modulating functions under stress, indicating their usefulness to be further researched.