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

Abstract

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...

Mitigating Soil Salinity Stress with Gypsum and Bio-Organic Amendments: A Review

“…Soil salinity reduces the soil organic matter content, soil water-holding capacity, water infiltration, weakens the soil structure and disrupts the soil aggregate stability [24][25][26]. Other common negative impacts of salinity on soil properties include increased soil pH, exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR), as well as reduced cation exchange capacity (CEC) and soil microbial community [26][27][28]. Due to high Na + concentrations in the soil solution or at the cations exchange site, salinesodic soil may arise, causing loss of inherent soil quality [27,29].…”

“…Other common negative impacts of salinity on soil properties include increased soil pH, exchangeable sodium percentage (ESP) and sodium adsorption ratio (SAR), as well as reduced cation exchange capacity (CEC) and soil microbial community [26][27][28]. Due to high Na + concentrations in the soil solution or at the cations exchange site, salinesodic soil may arise, causing loss of inherent soil quality [27,29]. Saline-sodic soils are negatively affected by high salt concentrations with an ESP and SAR of greater than 15% and 13 mmol c kg −1 , respectively.…”

Pharmaceutical, food potential, and molecular data of Hancornia speciosa Gomes: a systematic review

“…It is worth mentioning that the availability of molecular data from public banks allows this to be used for the development of in silico studies (Bezerra et al 2018 ). Additionally, for the prospecting of disease resistance genes (Debibakas et al 2014 ), pests (Joukhadar et al 2013 ), and tolerance to different abiotic stresses (Das et al 2019 ; Abhayawickrama et al 2020 ; Tripathi et al 2020 ). Moreover, it is relevant for phylogenetic analysis (Karakülah and Pavlopoulou 2018 ; Bauwens et al 2018 ), primer design for diversity studies (Feng et al 2016 ; Thatikunta et al 2016 ), and gene expression (Bustin and Huggett 2017 ; Alonso et al 2018 ).…”

Utilization of SNP-based Highly Saturated Molecular Map of a RIL Population for the Detection of QTLs and Mining of Candidate Genes for Salinity Tolerance in Rice

“…To detect the candidate genes responsible for salinity tolerance, located within the novel QTLs identified in this study, we used wholegenome data of At354 and Bg352 re-sequenced with reference to Nipponbare genome obtained from our previous study (Abhayawickrama et al, 2020). The total number of genes was first examined separately within each QTL-enriched region and out of them, genes related to abiotic stress were identified based on Gramene (http:// www.gramene.org/) and NCBI GenBank Databases (https://www.ncbi.nlm.nih.gov/ genbank/).…”

“…Therefore, the present study was focused to identify putative salinity responsive QTLs under the environment, which experiences both salinity stress and high temperature utilizing the same RIL population and SNP-based high density saturated molecular map, which was previously developed. Also, usually, SNP-based high-density molecular maps provide the opportunity to directly identify candidate genes if NGS based high-throughput QTL-seq approach is employed (Das et al, 2015;Srivastava et al, 2017;Gudys et al, 2018;Su et al, 2019;Abhayawickrama et al, 2020;Liu et al, 2020). Accordingly, this study was extended to mine the candidate genes underlying the salinity responsive QTLs detected under salt stress coupled with the high-temperature environment by employing whole-genomic data of At354 and Bg352 parents re-sequenced from our previous study (Abhayawickrama et al, 2020) and Gene Ontology (GO) enrichment approach.…”