Meta‐analysis and validation of genomic loci governing seedling and reproductive stage salinity tolerance in rice

Abstract

Identification of concurrent genomic regions contributing tolerance to salinity at the seedling and reproductive stages were done using 45 quantitative trait loci (QTL) mapping studies reporting 915 individual QTLs. The QTL-data were used to perform a meta-analysis to predict, validate and analyze the Meta-QTLs governing component traits contributing to salinity tolerance. We predicted a total of 65 and 49 Meta-QTLs distributed across the genome governing seedling and reproductive stage salinity tolerance, respectively. Salinity stress (EC ~10.0 dSm À1 ) was evaluated in a set of 32 genotypes grown hydroponically, from these eight extreme (highly tolerant and highly susceptible) genotypes were selected for validation of significant Meta-QTLs.Another set of eight previously known and reported (highly tolerant and highly susceptible) genotypes were evaluated under saline micro plot conditions (EC ~8.0 dSm À1 ) and used for validation of significant Meta-QTLs for reproductive stage salinity tolerance. The microsatellite marker "RM5635" linked to MSQTL4.2 (~295.43 kb) was able to clearly differentiate contrasting genotypes for seedling stage salinity tolerance, whereas at the reproductive stage, none of the markers were able to validate the predicted Meta-QTL for salinity tolerance. Earlier reported, gene expression studies were used for candidate gene analysis of validated MSQTL4.2, which indicated the down regulation of Os04g0423100, a gene encoding Monooxygenase-FAD binding domain containing protein. The traits associated with this Meta-QTL were root and shoot sodium and potassium concentration and leaf chlorophyll content. The identified and validated genomic region assumes a great significant role in seedling stage salinity tolerance in rice, and it can be used for marker-assisted backcross breeding programs.

Understanding complex genetic architecture of rice grain weight through QTL-meta analysis and candidate gene identification

“…Significant association of marker alleles with phenotypes ensures the presence of at least a few alleles of QTL present in the MQTL. Several researchers validated identified MQTL following the aforesaid approach 14 , 32 , 60 . In the present study, MQTL associated peak-SSR markers from each MQTL were opted for validation on a set of 14 genotypes, comprising seven genotypes each from extreme low and high grain weight categories available at ICAR-National Rice Research Institute Cuttack.…”

Consensus genomic regions associated with multiple abiotic stress tolerance in wheat and implications for wheat breeding

“…Several meta-QTL analyses for various traits in cereal crops such as maize 39 , rice 41,46,20 , and barley have already been conducted 35 . In wheat, meta-QTL studies have been undertaken for four different abiotic stresses, including PHS 54 , SS 30 , DS 32 , and HS 33 , but no meta-analysis has been conducted for the traits contributing to WS and AS stresses.…”

“…Detailed information related to maize and rice orthologues of wheat genes and ortho-MQTLs is presented in Table S9. Some earlier studies 46,35 did not provide physical positions of MQTLs; thus, these studies could not be used to mine ortho-MQTLs.…”

Identification of QTLs for Morpho-Physiological Traits under Saline Stress in Indica MAGIC Rice Population

“…Moreover, seedling stage salinity facilitates early plant establishment, which ensures good vegetative growth at the reproductive stage [5]. To identify the genes responsible for salinity tolerance, several QTL mapping studies have been conducted in the past [6,7]. Major Saltol, QTL mapped on chromosome 1, was successfully transferred to a wide array of high yielding genotypes through a series of marker-assisted breeding programs [8][9][10].…”