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    Genetic Mapping to Detect Stringent QTLs Using 1k-RiCA SNP Genotyping Platform from the New Landrace Associated with Salt Tolerance at the Seedling Stage in Rice
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    Abstract:
    Rice is the world's most important food crop, providing the daily calorie intake for more than half of the world's population. Rice breeding has always been preoccupied with maximizing yield potential. However, numerous abiotic factors, such as salt, cold, drought, and heat, significantly reduce rice productivity. Salinity, one of the major abiotic stresses, reduces rice yield worldwide. This study was conducted to determine new quantitative trait loci (QTLs) that regulate salt tolerance in rice seedlings. One F2:3 mapping population was derived from a cross between BRRI dhan49 (a popular but sensitive rainfed rice variety) and Akundi (a salt-tolerant rice landrace in Bangladesh used as a donor parent). The 1k-Rice Custom Amplicon (1k-RiCA) single-nucleotide polymorphism (SNP) markers were used to genotype this mapping population. After removing segregation distortion and monomorphic markers, 884 SNPs generated a 1526.8 cM-long genetic linkage map with a mean marker density of 1.7 cM for the 12 linkage groups. By exploiting QGene and ICIM-ADD, a sum of 15 QTLs for nine traits was identified in salt stress on seven chromosomes. Four important genomic loci were identified (qSES1, qSL1, qSUR1 and qRL1) on chromosome 1. Out of these 15 QTLs, 14 QTLs are unique, as no other study has mapped in the same chromosomal location. We also detected 15 putative candidate genes and their functions. The ICIM-EPI approach identified 43 significant pairwise epistasis interactions between regions associated with and unassociated with QTLs. Apart from more well-known donors, Akundi serves as an important new donor source for global salt tolerance breeding initiatives, including Bangladesh. The introgression of the novel QTLs identified in this study will accelerate the development of new salt-tolerant varieties that are highly resistant to salt stress using marker-enabled breeding.
    Keywords:
    Epistasis
    SNP genotyping
    Candidate gene
    Genome-wide mapping analyses are now commonplace in many species and several networks of interacting loci have been reported. However, relatively few details regarding epistatic interactions and their contribution to complex trait variation in multicellular organisms are available and the identification of positional candidate loci for epistatic QTL (epiQTL) is hampered, especially in mammals, by the limited genetic resolution inherent in most study designs. Here we further investigate the genetic architecture of reproductive fatpad weight in mice using the F(10) generation of the LG,SM advanced intercross (AI) line. We apply multiple mapping techniques including a single-locus model, locus-specific composite interval mapping (CIM), and tests for multiple QTL per chromosome to the 12 chromosomes known to harbor single-locus QTL (slQTL) affecting obesity in this cross. We also perform a genome-wide scan for pairwise epistasis. Using this combination of approaches we detect 199 peaks spread over all 19 autosomes, which potentially contribute to trait variation including all eight original F(2) loci (Adip1-8), novel slQTL peaks on chromosomes 7 and 9, and several novel epistatic loci. Extensive epistasis is confirmed involving both slQTL confidence intervals (C.I.) as well as regions that show no significant additive or dominance effects. These results provide important new insights into mapping complex genetic architectures and the role of epistasis in complex trait variation.
    Epistasis
    Genetic architecture
    Family-based QTL mapping
    Association mapping
    Genome-wide Association Study
    Citations (26)
    The interaction between segregation distortion loci (SDL) has been often observed in all kinds of mapping populations. However, little has been known about the effect of epistatic SDL on quantitative trait locus (QTL) mapping. Here we proposed a multi-QTL mapping approach using epistatic distorted markers. Using the corrected linkage groups, epistatic SDL was identified. Then, these SDL parameters were used to correct the conditional probabilities of QTL genotypes, and these corrections were further incorporated into the new QTL mapping approach. Finally, a set of simulated datasets and a real data in 304 mouse F2 individuals were used to validate the new method. As compared with the old method, the new one corrects genetic distance between distorted markers, and considers epistasis between two linked SDL. As a result, the power in the detection of QTL is higher for the new method than for the old one, and significant differences for estimates of QTL parameters between the two methods were observed, except for QTL position. Among two QTL for mouse weight, one significant difference for QTL additive effect between the above two methods was observed, because epistatic SDL between markers C66 and T93 exists (P = 2.94e-4).
    Epistasis
    Family-based QTL mapping
    Linkage (software)
    Genetic linkage
    How to map quantitative trait loci (QTL) with epistasis efficiently and reliably has been a persistent problem for QTL mapping analysis. There are a number of difficulties for studying epistatic QTL. Linkage can impose a significant challenge for finding epistatic QTL reliably. If multiple QTL are in linkage and have interactions, searching for QTL can become a very delicate issue. A commonly used strategy that performs a two-dimensional genome scan to search for a pair of QTL with epistasis can suffer from low statistical power and also may lead to false identification due to complex linkage disequilibrium and interaction patterns.To tackle the problem of complex interaction of multiple QTL with linkage, we developed a three-stage search strategy. In the first stage, main effect QTL are searched and mapped. In the second stage, epistatic QTL that interact significantly with other identified QTL are searched. In the third stage, new epistatic QTL are searched in pairs. This strategy is based on the consideration that most genetic variance is due to the main effects of QTL. Thus by first mapping those main-effect QTL, the statistical power for the second and third stages of analysis for mapping epistatic QTL can be maximized. The search for main effect QTL is robust and does not bias the search for epistatic QTL due to a genetic property associated with the orthogonal genetic model that the additive and additive by additive variances are independent despite of linkage. The model search criterion is empirically and dynamically evaluated by using a score-statistic based resampling procedure. We demonstrate through simulations that the method has good power and low false positive in the identification of QTL and epistasis.This method provides an effective and powerful solution to map multiple QTL with complex epistatic pattern. The method has been implemented in the user-friendly computer software Windows QTL Cartographer. This will greatly facilitate the application of the method for QTL mapping data analysis.
    Epistasis
    Family-based QTL mapping
    Linkage (software)
    Genetic architecture
    Linkage Disequilibrium
    Trait
    Genetic linkage
    Citations (29)
    Epistasis
    Family-based QTL mapping
    Genetic architecture
    Genome Scan
    Bonferroni correction
    Trait
    False Discovery Rate
    Candidate gene
    Citations (4)
    To avoid the endless accumulation of QTL effects during pyramiding breeding, QTL epistasis plays a role of homeostasis. Four single-segment substitution lines with heading date QTLs were utilized to construct pyramiding materials with dual QTLs and triple QTLs, allowing for the estimation of QTL epistatic effects on heading date in rice. The epistatic components of dual QTL and triple QTL interactions were analyzed using data from three seasons of two years. All four QTLs can be considered as dominant loci, demonstrating superdominance. 75% of dual QTL interactions and 81.25% of triple QTL interactions obtained statistically significant results, reaffirming the prevalence of epistasis. Interactions of four QTLs with three positive effects and one negative effect generated 62.5% negative dual QTL epistatic effects and 57.7% positive triple QTL epistatic effects, forming the balance relationship “positive-negative-positive”. In fact, QTL effects were consistently partially neutralized by mixed QTL epistatic effects so as to control the infinite accumulation of QTL effects. QTL epistasis plays a role of homeostasis on heading date in rice. However, there were two exceptions. The directions of OsMADS50 and Hd3a-2 effects were consistently aligned with those of their mixed epistases, suggesting that the QTL or gene could be employed in pyramiding breeding with different objectives. This study elucidated the mechanism of epistatic interactions among four QTLs and provided valuable genetic resources for improving heading date in rice.
    Epistasis
    Family-based QTL mapping
    Family-based QTL mapping
    Positional cloning
    Linkage (software)
    Genetic linkage
    Association mapping
    Candidate gene
    Citations (42)
    Family-based QTL mapping
    Triticeae
    Genetic linkage
    Association mapping
    Linkage (software)
    Positional cloning
    Citations (10)