Abstract
BackgroundSalinity is one of the most severe and widespread abiotic stresses that affect rice production. The identification of major-effect quantitative trait loci (QTLs) for traits related to salinity tolerance and understanding of QTL × environment interactions (QEIs) can help in more precise and faster development of salinity-tolerant rice varieties through marker-assisted breeding. Recombinant inbred lines (RILs) derived from IR29/Hasawi (a novel source of salinity) were screened for salinity tolerance in the IRRI phytotron in the Philippines (E1) and in two other diverse environments in Senegal (E2) and Tanzania (E3). QTLs were mapped for traits related to salinity tolerance at the seedling stage.ResultsThe RILs were genotyped using 194 polymorphic SNPs (single nucleotide polymorphisms). After removing segregation distortion markers (SDM), a total of 145 and 135 SNPs were used to construct a genetic linkage map with a length of 1655 and 1662 cM, with an average marker density of 11.4 cM in E1 and 12.3 cM in E2 and E3, respectively. A total of 34 QTLs were identified on 10 chromosomes for five traits using ICIM-ADD and segregation distortion locus (SDL) mapping (IM-ADD) under salinity stress across environments. Eight major genomic regions on chromosome 1 between 170 and 175 cM (qSES1.3, qSES1.4, qSL1.2, qSL1.3, qRL1.1, qRL1.2, qFWsht1.2, qDWsht1.2), chromosome 4 at 32 cM (qSES4.1, qFWsht4.2, qDWsht4.2), chromosome 6 at 115 cM (qFWsht6.1, qDWsht6.1), chromosome 8 at 105 cM (qFWsht8.1, qDWsht8.1), and chromosome 12 at 78 cM (qFWsht12.1, qDWsht12.1) have co-localized QTLs for the multiple traits that might be governing seedling stage salinity tolerance through multiple traits in different phenotyping environments, thus suggesting these as hot spots for tolerance of salinity. Forty-nine and 30 significant pair-wise epistatic interactions were detected between QTL-linked and QTL-unlinked regions using single-environment and multi-environment analyses.ConclusionsThe identification of genomic regions for salinity tolerance in the RILs showed that Hasawi possesses alleles that are novel for salinity tolerance. The common regions for the multiple QTLs across environments as co-localized regions on chromosomes 1, 4, 6, 8, and 12 could be due to linkage or pleiotropic effect, which might be helpful for multiple QTL introgression for marker-assisted breeding programs to improve the salinity tolerance of adaptive and popular but otherwise salinity-sensitive rice varieties.
Highlights
Salinity is one of the most severe and widespread abiotic stresses that affect rice production
The Quantitative trait loci (QTLs) and QTL × environment interactions (QEIs) identified by inclusive composite interval mapping (ICIM) in the IR29/Hasawi Recombinant inbred lines (RILs) population were based on phenotypic evaluation in three different environments
Correlation analysis between traits in the F6 RIL population Significant negative correlations were observed between the standard evaluation system (SES) and all other parameters related to salt tolerance such as Shoot length (SL), Root length (RL), Fresh weight of shoot (FWsht), and Dry weight of shoot (DWsht) (Table 1), which is expected because a lower SES score indicates higher tolerance, which is based on seedling survival and vigor
Summary
Salinity is one of the most severe and widespread abiotic stresses that affect rice production. QTLs were mapped for traits related to salinity tolerance at the seedling stage Unfavorable environmental conditions such as salinity, drought, heat, and submergence pose a huge threat to agricultural production and productivity and challenge future food security. Salinity tolerance at the seedling stage is crucial for good crop establishment, especially in coastal areas. Various mechanisms such as preferential uptake of potassium ions (K+), sodium exclusion from roots, and its restricted transport to shoots have been reported to confer salinity tolerance in rice (Kader et al 2006; Wu et al 2009; Singh and Flowers 2010; Rahman et al 2016). Salinity tolerance is a complex trait governed by genetic factors such as multiple QTLs and their interactions (epistasis), and is significantly influenced by environmental factors (Wurschum et al 2013; Roy et al 2014; Khan et al 2016; Liu et al 2016)
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