Mapping of additive and epistatic QTLs linked to seed longevity in bread wheat (Triticum aestivum L.)

Plant genetic resources are stored and regenerated in > 1750 gene banks storing > 7,000,000 accessions. Since seeds are the primary storage units, research on seed longevity is of particular importance. Quantitative trait loci (QTL) analysis of 15 traits related to seed longevity and dormancy using 7584 high-quality SNPs recorded across 2 years and originated from five production years revealed a total of 46 additive QTLs. Exploration of the QTLs with epistatic effect resulted in the detection of 29 pairs of epistatic QTLs. To our information, this is only the second report of epistatic QTLs for seed longevity in bread wheat. We conclude that in addition to dense genetic maps, the epistatic interaction between loci should be considered to capture more variation which remained unnoticed in additive mapping.

Mapping Resistance to Argentinean Fusarium (Graminearum) Head Blight Isolates in Wheat

Fusarium head blight (FHB) of wheat, caused by Fusarium graminearum (Schwabe), is a destructive disease worldwide, reducing wheat yield and quality. To accelerate the improvement of scab tolerance in wheat, we assessed the International Triticeae Mapping Initiative mapping population (ITMI/MP) for Type I and II resistance against a wide population of Argentinean isolates of F. graminearum. We discovered a total of 27 additive QTLs on ten different (2A, 2D, 3B, 3D, 4B, 4D, 5A, 5B, 5D and 6D) wheat chromosomes for Type I and Type II resistances explaining a maximum of 15.99% variation. Another four and two QTLs for thousand kernel weight in control and for Type II resistance, respectively, involved five different chromosomes (1B, 2D, 6A, 6D and 7D). Furthermore, three, three and five QTLs for kernel weight per spike in control, for Type I resistance and for Type II resistance, correspondingly, involved ten chromosomes (2A, 2D, 3B, 4A, 5A, 5B, 6B, 7A, 7B, 7D). We were also able to detect five and two epistasis pairs of QTLs for Type I and Type II resistance, respectively, in addition to additive QTLs that evidenced that FHB resistance in wheat is controlled by a complex network of additive and epistasis QTLs.

Mapping Revealed Two Additive QTLs and Fourteen Epistatic QTLs for Late Leaf Spot Resistance in a Cultivated Groundnut Breeding Line VG 9514.

A late leaf spot resistant breeding line VG 9514 was bred through interspecific hybridization between Arachis hypogaea L. and Arachis cardenasii. Genetic study involving segregation for late leaf spot resistance in F2 and recombinant inbred line population of a cross between VG 9514 X TAG 24 revealed duplicate recessive resistance for the disease. Integration of newly developed SSR markers from A02 chromosome with existing linkage map generated a new genetic linkage map with 278 markers and 2679.1 cM map distances. QTL mapping involving this genetic linkage map and phenotypic field score of late leaf spot identified two major consensus additive QTLs in the A02 chromosome of cultivated groundnut. Epistatic interaction between these two major QTLs was also noticed through an epistatic QTL analysis in Ici-Mapping 4.1. In all the fourteen epistatic QTLs, a common component locus was remained within the major additive QTL at 90 cM in chromosome A02. Sequence analysis within the major additive QTL peaks revealed open reading frame of genes that code LRR domain containing proteins which are involved in disease resistance in crop plants.

A novel mapping strategy utilizing mouse chromosome substitution strains identifies multiple epistatic interactions that regulate complex traits

The genetic contribution of additive versus non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate and powerful model for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTLs) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTLs regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTLs for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTLs; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.

Abstract P455: Epistatic Regulation of Hematological-related Traits and Gene Expression in Mice Reveals Additional Heritability Missed by Standard GWAS-type Analyses

The genetic contribution of additive versus non-additive (epistasis) effects in the regulation of hematologic and other complex traits is unclear. Although many variants have been associated with a range of complex traits via genome wide association studies (GWAS), these loci combined in additive models do not account for most of the trait heritability. GWAS-type analyses typically ignore gene-gene interactions, in part because of the difficulty in detecting them in complex multicellular organisms, especially humans. We have previously shown that mouse chromosome substitution strains (CSSs) are a powerful model for detecting epistasis, and that for certain complex traits the relative contribution of epistasis to heritability is as important as additivity. We have now applied the use of these CSSs to identify and map additive and epistatic loci that regulate a range of hematological-related traits and hepatic gene expression levels. A modified backcross was performed with CSS strains carrying the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. By analyzing the transcriptomes of offspring from this cross, we identified and mapped additive quantitative trait loci (QTLs) that regulated the expression of 770 genes, and epistatic QTLs for 802 genes. Similarly we performed a complete blood analysis of offspring from the cross and identified additive QTLs for platelets and percentage of granulocyte in the blood as well as epistatic QTLs controlling the percentage of lymphocytes in the blood (rs13477644, rs13478739; LOD = 3.4) and red cell distribution width (rs13477864, rs13478802; LOD = 3.7). The variance attributable to the epistatic QTLs was approximately equal to that of the additive QTLs, highlighting the importance of identifying genetic interactions. Of note, even the SNPs associated with the most significant epistatic interactions were undetected in our single loci GWAS-like association analyses, demonstrating the need to specifically test for gene-gene interactions in studies of complex traits. In summary, our studies identified epistatic loci in mice that are important regulators of hematological-related traits and gene expression. Additionally, our studies call attention to the importance of extending single loci GWAS-type analyses to include analyses of gene-gene interactions to improve our ability to identify genetic variants that regulate complex traits.

Genetic dissection of flour whiteness by unconditional and conditional quantitative trait locus mapping in wheat

SUMMARYFlour whiteness (FW) is an important factor in assessing flour quality and determining the end product quality. It is an integrated sensory indicator reflecting flour colour and is negatively correlated with protein content. In order to dissect the genetic relationship between FW and its five related traits at the quantitative trait locus (QTL)/gene level, a recombinant inbred line population was evaluated under three environments. Quantitative trait loci for FW were analysed by unconditional and conditional QTL mapping. Four unconditional additive QTLs and 16 conditional additive QTLs were detected across the three environments. Of these QTLs, only one major additive QTL (Qfw1D1-1) was consistently identified using both unconditional and conditional QTL analysis. This QTL was independent of flour colour a* (a function of red-green with a positive a* for redness and negative for greenness) and b* (a green-blue value with positive value for yellowness and negative for blueness) and was only slightly affected by flour protein content. A minor additive QTL (Qfw4A-4) was also detected using these two QTL mapping methods, being independent of flour colour a* and b*. Five unconditional and ten conditional epistatic minor QTLs were detected, from which only one pair (Qfw3A-10/Qfw6B-6) was identified by both unconditional and conditional QTL mapping, also independent of flour colour a* and b*. The major QTL (Qfw1D1-1) identified in the current study for the first time can be used for improving wheat FW in marker-assisted breeding.

Genetic dissection of the developmental behaviour of total starch content and its components in wheat grain

Starch in wheat is an important component of flour and is related to grain yield and wheat end-products. In this study, a doubled haploid (DH) population with 168 lines derived from a cross of elite Chinese wheat (Triticum aestivum L.) cultivars Huapei 3 and Yumai 57 was used to identify dynamic quantitative trait loci (QTLs) for total starch content (TSC), amylose (AMS) and amylopectin (AMP) in wheat grain. Traits were measured at stages, grown under three treatments in two seasons, and were assessed by unconditional and conditional QTL analyses. Thirty-three additive QTLs and 21 pairs of epistatic QTLs for TSC, AMS and AMP were detected by unconditional mapping, whereas 19 additive QTLs and 15 pairs of epistatic QTLs were identified by conditional mapping. Of these, QTsc4A.1 and QAms4A.1 were detected continuously at five stages under three treatments in two seasons by unconditional mapping, indicating that the accumulated effects of these QTLs were expressed stably from 12 days after flowering (DAF) and were little affected by nitrogen and water agronomic treatment. These two QTLs also showed net expression from 12 to 22 DAF by conditional mapping. The results indicate that the two loci play an important role in starch synthesis. Most of the epistatic QTLs belonged to a minor QTL, but played an important role in the target traits. Therefore, the development of starch is mainly affected by additive effects besides the epistasis effect. The data are useful for potential marker-assisted selection and cloning of the target gene in further fine mapping, and provide a foundation to understand the genetic mechanism underlying the development of starch in wheat and to increase yield.

Quantitative trait loci mapping for traits related to the progression of wheat flag leaf senescence

SUMMARYDelayed senescence, or stay-green, contributes to a longer grain-filling period and has been regarded as a desirable characteristic for the production of a number of crops including wheat. In the present study, in order to identify quantitative trait loci (QTLs) for traits related to the progression of wheat flag leaf senescence, green leaf area duration (GLAD) of a doubled haploid (DH) population, derived from two winter wheat varieties Hanxuan10 and Lumai14, was visually estimated under two water conditions and was recorded at 3-day intervals from 10 days after anthesis to physiological maturity using a 0–9 scale. According to GLAD, parameters related to the progression of senescence of DH lines and their parents were estimated by the Gompertz statistical model. Based on the model parameters, DH lines were categorized into three groups under drought stress and four groups under well-watered conditions. A total of 24 additive QTLs and 23 pairs of epistatic QTLs for parameters related to the progression of senescence were identified on 18 chromosomes, except for 3B, 1D and 6D. Of the QTLs detected, 14 and 10 additive QTLs were associated with the investigated traits under drought stress and well-watered conditions, respectively. Furthermore, 4, 7, 6, 2 and 2 additive QTLs for traits related to progression of senescence were clustered around the same or similar regions of chromosomes 1A, 1B, 5A, 5B and 7A, respectively. The present data provided the genetic basis for high phenotypic correlations among traits related to the progression of wheat flag leaf senescence. In addition, 17 loci were co-located or linked with previously reported QTLs regulating chlorophyll fluorescence, high-light-induced photo-oxidation, or heat stress and dark-induced senescence. The marker Xwmc336 on chromosome 1A, responsible for the onset and end times of leaf senescence, the time to maximum rate of senescence, the time to reach 75% senescence and chlorophyll content under drought stress may be helpful for marker-assisted selection breeding of wheat.