Mapping QTLs for tolerance to salt stress at the early seedling stage in rice (Oryza sativa L.) using a newly identified donor ‘Madina Koyo’

Open Access Article; Published online: 13 Sep 2020Salt stress is a menace to rice production and a threat to food security worldwide. We evaluated 308 F4 families from Sahel 317/Madina Koyo for tolerance to salt stress at the early seedling stage. To better understand genomic regions controlling tolerance in the population, we genotyped the progenies and the two parents using single nucleotide polymorphism (SNP) markers and regressed the genotypic data on their phenotype to detect QTLs. An average reduction of 63.4% was observed for all fitness-related traits among the F4 families. A total of 46 progenies recorded an average salt injury score (SIS) between 1–3 and were rated as tolerant to salt stress at the early seedling stage. A high-density genetic map was constructed for the 12 rice chromosomes using 3698 SNP markers. Multiple interval mapping identified 13 QTLs for SIS, shoot length, shoot dry weight and root length on chromosomes 2, 3, 4, 6, 7, 10 and 12, with trait increasing alleles coming from both parents. Two (qSDW2 and qRL2.2) and three (qSL2, qRL2.1 and qSIS2) QTLs at different regions on chromosome 2 and another two on chromosome 7 (qSDW7 and qSL7) were tightly linked. These QTLs could facilitate breeding for salt tolerance at the early seedling stage as direct selection for one, would mean indirectly selecting for the other. Fine mapping of these novel QTLs in a different genetic background is necessary to confirm their stability and usefulness in breeding for tolerance to salinity in rice

Mapping chromosomal regions associated with anther indehiscence with exerted stigmas in CRI-48 and Jasmine 85 cross of rice (Oryza sativa L)

Anther indehiscence in certain wide crosses combines male sterility with stigma exertion, a phenomenon that is desirable for hybrid rice seed production. This study sought to identify chromosomal region(s) that combine anther indehiscence with exerted stigmas. A mapping population consisting of 189 BC1F1 plants was derived from a cross between CRI-48 and Jasmine 85 and backcrossing the resulting F1 to Jasmine 85. Contrary to the three complementary genes mode of inheritance reported earlier, a single locus (AI6-1) was mapped on chromosome 6 at 27.4 cM for anther indehiscence with exerted stigmas through a mixed model-based composite interval mapping (MCIM). This locus was flanked by two single nucleotide polymorphism (SNP) markers, K_ID6002884 and K_ID6003341 within a range of 23.1–28.9 cM. The allele at the locus was contributed by the CRI-48 parent which has Oryza glaberrima ancestry. This locus is suggested to control anther indehiscence and stigma exertion through pleiotropic gene action or cluster of genes

Development of species diagnostic SNP markers for quality control genotyping in four rice (Oryza L.) species

Species misclassification (misidentification) and handling errors have been frequently reported in various plant species conserved at diverse gene banks, which could restrict use of germplasm for correct purpose. The objectives of the present study were to (i) determine the extent of genotyping error (reproducibility) on DArTseq-based single-nucleotide polymorphisms (SNPs); (ii) determine the proportion of misclassified accessions across 3134 samples representing three African rice species complex (Oryza glaberrima, O. barthii, and O. longistaminata) and an Asian rice (O. sativa), which are conserved at the AfricaRice gene bank; and (iii) develop species- and sub-species (ecotype)-specific diagnostic SNP markers for rapid and low-cost quality control (QC) analysis. Genotyping error estimated from 15 accessions, each replicated from 2 to 16 times, varied from 0.2 to 3.1%, with an overall average of 0.8%. Using a total of 3134 accessions genotyped with 31,739 SNPs, the proportion of misclassified samples was 3.1% (97 of the 3134 accessions). Excluding the 97 misclassified accessions, we identified a total of 332 diagnostic SNPs that clearly discriminated the three indigenous African species complex from Asian rice (156 SNPs), O. longistaminata accessions from both O. barthii and O. glaberrima (131 SNPs), and O. sativa spp. indica from O. sativa spp. japonica (45 SNPs). Using chromosomal position, minor allele frequency, and polymorphic information content as selection criteria, we recommended a subset of 24 to 36 of the 332 diagnostic SNPs for routine QC genotyping, which would be highly useful in determining the genetic identity of each species and correct human errors during routine gene bank operations

Identification of QTLs for Drought-Related Traits in Alien Introgression Lines Derived from Crosses of Rice (Oryza sativa cv. IR64) × O. glaberrima under Lowland Moisture Stress

Drought is a major abiotic stress that limits rice productivity in rain-fed and upland ecosystems. African rice, Oryza glaberrima, has low yields but is tolerant to drought and other stresses. We evaluated 513 BC2F3 progenies from alien introgression lines (AILs) that were derived from crosses of Oryza sativa (IR64) × O. glaberrima. They were assessed for yield and other traits when grown under drought at two locations. Such conditions reduced grain production by 59% compared with the recurrent parent (IR64). However, 33 AILs had higher yields, thus demonstrating their potential as genetic material for transferring drought-related traits from O. glaberrima to O. sativa. A set of 200 AILs was selectively genotyped with 173 simple sequence repeat and sequenced tagged site markers. Molecular analysis showed that a mean of 4.5% of the O. glaberrima genome was introgressed in BC2F3 AILs. Our analysis revealed 33 quantitative trait loci (QTLs; including 10 novel) for different traits. O. glaberrima contributed 50% of the alleles to those newly identified QTLs, with one for grain yield per plant (ypp9.1) being new. A QTL at RM208 on chromosome 2 positively affected yield under stress, accounting for 22% of the genetic variation. Our identification of drought-related QTLs for yield and yield components will be useful to future research efforts in marker-assisted selectio