Epistatic Quantitative Trait Loci Research Articles

Genetic analysis of kernel weight and kernel size in wheat (Triticum aestivum L.) using unconditional and conditional QTL mapping

Thousand kernel weight (TKW) is commonly regarded as a complex trait in wheat. Both unconditional and conditional quantitative trait locus (QTL) analyses were conducted using software QTLNetwork 2.0 in four environments to evaluate the genetic relationships between TKW and kernel size. These analyses involved a set of 182 F8:9 recombinant inbred lines derived from “Shannong01-35 × Gaocheng9411” with a genetic linkage map consisting of 503 molecular markers. Additive effects, epistatic effects, and genotype-by-environment (G × E) interactions of QTLs for TKW and kernel size were analyzed. A total of nine additive QTLs for TKW and kernel size were identified using unconditional analysis, which distributed on chromosomes 1B, 1D, 3D, 4B, 5B, and 6A. Among these, four QTLs were detected to be related to several different kernel traits. QTkw4B.1-7, QTkw5B.1-12, QTkw5B.1-17, and QTkw6A.1-29 were identified through both conditional and unconditional analyses. Seven QTLs for TKW were only identified under conditional QTL mapping. These included conditional QTLs for TKW influenced by or independent of the given kernel size traits. Twelve pairs of epistatic interaction QTLs involving 18 loci for the measured kernel traits were detected in unconditional analysis. The QTLs discovered in the present study through the combination of conditional and unconditional QTL mapping could increase the understanding of the genetic interrelationships between TKW and kernel size traits at the QTL level and provide the guiding information for breeding programs.

Wide-genome QTL mapping of fruit quality traits in a tomato RIL population derived from the wild-relative species Solanum pimpinellifolium L.

QTL and candidate genes associated to fruit quality traits have been identified in a tomato genetic map derived from Solanum pimpinellifolium L., providing molecular tools for marker-assisted breeding. The study of genetic, physiological, and molecular pathways involved in fruit development and ripening has considered tomato as the model fleshy-fruited species par excellence. Fruit quality traits regarding organoleptic and nutritional properties are major goals for tomato breeding programs since they largely decide the acceptance of tomato in both fresh and processing markets. Here we report the genetic mapping of single-locus and epistatic quantitative trait loci (QTL) associated to the fruit size and content of sugars, acids, vitamins, and carotenoids from the characterization of a RIL population derived from the wild-relative Solanum pimpinellifolium TO-937. A genetic map composed of 353 molecular markers including 13 genes regulating fruit and developmental traits was generated, which spanned 1007cM with an average distance between markers of 2.8cM. Genetic analyses indicated that fruit quality traits analyzed in this work exhibited transgressive segregation and that additive and epistatic effects are the major genetic basis of fruit quality traits. Moreover, most mapped QTL showed environment interaction effects. FrW7.1 fruit size QTL co-localized with QTL involved in soluble solid, vitamin C, and glucose contents, dry weight/fresh weight, and most importantly with the Sucrose Phosphate Synthase gene, suggesting that polymorphisms in this gene could influence genetic variation in several fruit quality traits. In addition, 1-deoxy-D-xylulose 5-phosphate synthase and Tocopherol cyclase genes were identified as candidate genes underlying QTL variation in beta-carotene and vitamin C. Together, our results provide useful genetic and molecular information regarding fruit quality and new chances for tomato breeding by implementing marker-assisted selection.

Inclusive Composite Interval Mapping of QTL by Environment Interactions in Biparental Populations.

Identification of environment-specific QTL and stable QTL having consistent genetic effects across a wide range of environments is of great importance in plant breeding. Inclusive Composite Interval Mapping (ICIM) has been proposed for additive, dominant and epistatic QTL mapping in biparental populations for single environment. In this study, ICIM was extended to QTL by environment interaction (QEI) mapping for multi-environmental trials, where the QTL average effect and QEI effects could be properly estimated. Stepwise regression was firstly applied in each environment to identify the most significant marker variables which were then used to adjust the phenotypic values. One-dimensional scanning was then conducted on the adjusted phenotypic values across the environments in order to detect QTL with either average effect or QEI effects, or both average effect and QEI effects. In this way, the genetic background could be well controlled while the conventional interval mapping was applied. An empirical method to determine the threshold of logarithm of odds was developed, and the efficiency of the ICIM QEI mapping was demonstrated in simulated populations under different genetic models. One actual recombinant inbred line population was used to compare mapping results between QEI mapping and single-environment analysis.

QTL mapping for flowering time in different latitude in soybean

Flowering represents the transition from the vegetative to reproductive phase and plays an important role in many agronomic traits. For soybean, a short day (SD) induced and photoperiod-sensitive plant, delaying flowering time under SD environments is very important and has been used by breeders to increase yields and enhance plant adaptabilities at lower latitudes. The purpose of this study was to identify quantitative trait loci (QTLs) associated with flowering time, especially QTLs underlying the long juvenile (LJ) trait which delays flowering time under SD environments. A population of 91 recombinant inbred lines derived from a cross between AGS292 and K3 was used for map construction and QTL analysis. The map covered 2546.7 cM and included 52 new promoter-specific indel and 9 new exon-specific indel markers. The phenotypic days-to-flowering data were examined in nine environments, including four short-day (SD, low latitude) and five long-day photoperiod (LD, high latitude) environments. For the SD environments, six QTLs were detected. Five of them were associated with the LJ trait. Among the five LJ QTLs, four QTLs may be attributed to the known flowering time genes, including qFT-J-1 for FT5a locus, qFT-J-2 for the FT2a locus, qFT-O for the E2 locus and qFT-L for the E3 locus. This is the first report that the E2, E3, FT2a and FT5a loci may be associated with the LJ trait. Under the five LD environments, as expected, qFT-O for the E2 locus and qFT-L for the E3 locus were identified, suggesting that E2 and E3 loci are very important for soybean adaptation in LD photoperiod. Conjoint analysis of multiple environments identified nine additive QTLs and nine pairs of epistatic QTLs, among which most were involved in interactions with the environments. In total, five QTLs (qFT-B2-1, qFT-C1-1, qFT-K, qFT-D2 and qFT-F) were identified that may represent novel flowering time genes. This provides a fundamental foundation for future studies of flowering time in soybean using fine mapping, map-based cloning, and molecular-assisted breeding.

Identification of QTLs with Additive, Epistatic, and QTL × Seed Maturity Interaction Effects for Seed Vigor in Rice

Seed maturity is a critical process of seed vigor establishment. In this study, one rice population of recombinant inbred lines (RILs) was used to determine the genetic characteristics of seed vigor, including the germination potential (GP), germination rate (GR), germination index (GI), and time for 50 % of germination (T50), at 4, 5, and 6 weeks after heading in 2 years. Significant differences of seed vigor were observed among two parents and RIL population; the heritability of four traits was more than 90 % at three maturity stages. A total of 19 additive and 2 epistatic quantitative trait loci (QTL) for seed vigor were identified using QTL Cartographer and QTLNetwork program, respectively, in 2012, while 16 simple sequence repeat (SSR) markers associated with seed vigor were detected using bulked segregant analysis (BSA) in 2013. The phenotypic variation explained by each additive, epistatic QTL, and QTL × seed maturity interaction ranged from 9.19 to 22.94 %, 7.23 to 7.75 %, and 0.05 to 0.63 %, respectively. Ten additive QTLs were stably expressed in 2 years which might play important roles in establishment of seed vigor in different environments. By comparing chromosomal positions of ten stably expressed additive QTLs with those previously identified, they might be true QTLs for seed vigor; the regions of QTLs for seed vigor are likely to coincide with QTLs for seed dormancy, seed reserve mobilization, low-temperature germinability, and seedling growth. Using four selected RILs, three cross-combinations were predicted to improve seed vigor; 9 to 10 elite alleles could be pyramided by each combination. The selected RILs and the identified QTLs might be applicable for the improvement of seed vigor by marker-assisted selection (MAS) in rice.

Evaluation of genomic approaches for marker‐based improvement of lodging tolerance in triticale

AbstractLodging tolerance is an important agronomic trait as it can have a severe negative impact on grain yield and quality. Here, we used a large mapping population of 647 doubled haploid triticale lines derived from four families to dissect the genetic architecture underlying lodging tolerance and to assess different approaches for a genomics‐based improvement of the trait. The plants were evaluated for lodging in two environments and genotyped with 1710 genomewide DArT markers. We observed a large genotypic variation for lodging and transgressive segregation in all families. Employing two complementary QTL mapping approaches, we identified both main effect and epistatic QTL. Using cross‐validation, we showed that the proportion of genotypic variance explained by the detected QTL is low, thus limiting the efficiency of marker‐assisted selection to improve this trait. By contrast, the cross‐validated predictive ability of genomic prediction was approximately twice as high as that of the QTL‐based selection approaches. In conclusion, our results show that lodging tolerance is a complex trait that can be improved by classical breeding but also assisted by marker‐based approaches.

Analysis of additive and epistatic quantitative trait loci underlying fatty acid concentrations in soybean seeds across multiple environments

AbstractSoybean is one of the most important oilseed crops in the world. The soybean oil contains various fatty acids. Their concentrations determine the quality and nutritional value of soybean oil. On the other hand, quantitative trait loci (QTL) mapping for the concentrations of soybean predominant fatty acids could provide the genetic basis for soybean fatty acid composition. In this study, a soybean genetic linkage map was constructed based on 161 polymorphic SSR markers in recombinant inbred lines (RILs) derived from a cross of cv. Luheidou2 × Nanhuizao. By using this map, 35 additive QTLs underlying individual fatty acid concentrations were identified in single environment, while 17 additive QTLs were identified underlying specific fatty acids across multiple environments or underlying multiple fatty acids. Fifteen of the 52 loci were found to be novel loci, explaining 5–24 % of phenotypic variation. Moreover, 25 epistatic QTLs were identified and explained a high phenotypic variation for the fatty acid concentrations, suggesting an essential role of epistatic effect for fatty acid concentrations. The identification of additive and epistatic QTLs suggested a complex network for soybean fatty acid concentrations, and will facilitate the understanding for fatty acid accumulation.

Quantitative trait loci analysis of lateral shoot growth in tomato

Branching is an important agronomic trait to determine plant architecture and fruit yield. In tomato, the regulatory mechanisms of shoot branching patterns have been studied mainly in mutants defective in meristem identity. Little is known about quantitative trait loci (QTLs) and their genetic interaction (epistasis) in lateral shoot development. Here, the genetic control of lateral bud outgrowth initiation and subsequent lateral bud development into branches were investigated. We used a BC1F7 population developed from Solanum lycopersicum (SL) and its close wild relative Solanum pimpinellifolium (SP) to measure the number of leaves on primary shoot (LN), the proportion of nodes with lateral buds (LS0) and lateral branches longer than 5cm (LS5) and 10cm (LS10) on main axis, the proportion of nodes with secondary lateral branches longer than 1cm (LSLS1) on primary lateral branches, and the lengths of the longest primary and secondary lateral branches (LLSL1 and LLSL2, respectively). Composite interval mapping detected 17 additive QTLs; those for LS5, LS10, and LLSL1 clustered near C2_At5g49480 or LEATPACb on chromosome 1 and LEOH361 on chromosome 4. One epistatic (QTL×QTL) interaction was identified for LS10 QTLs on chromosomes 1 and 12, where recombinant-type alleles increased lateral bud development into primary lateral branches. We analyzed further the QTLs clustered on chromosome 1 using two BC3F4 populations containing introgression region from the SP, which revealed the co-location of QTLs for lateral shoot development and days to flowering time. These results suggest that lateral shoot development is regulated by some additive and epistatic QTLs, some of which possibly exhibit a pleiotropic effect on flowering time.

Genomewide mapping reveals a combination of different genetic effects causing the genetic basis of heterosis in two elite rice hybrids.

North Carolina design III (NCIII) is one of the most powerful and widely used mating designs for understanding the genetic basis of heterosis. However, the quantitative trait mapping (QTL) conducted in previous studies with this design was mainly based on analysis of variance (ANOVA), composite interval or multiple interval mapping methods. These methodologies could not investigate all kinds of genetic effects, especially epistatic effects, simultaneously on the whole genome. In this study, with a statistical method for mapping epistatic QTL associated with heterosis using the recombinant inbred line (RIL)-based NCIII design, we conducted QTL mapping for nine agronomic traits of two elite hybrids to characterize the mode of gene action contributing to heterosis on a whole genomewide scale. In total, 23 main-effect QTL (M-QTL) and 23 digenic interactions in IJ (indica x japonica) hybrids, 11 M-QTL and 82 digenic interactions in II (indica x indica) hybrid QTLs were identified in the present study. The variation explained by individual M-QTL or interactions ranged from 2.3 to 11.0%. The number of digenic interactions and the total variation explained by interactions of each trait were larger than those of M-QTL. The augmented genetic effect ratio of most M-QTL and digenic interactions in (L1 - L2) data of two backcross populations (L1 and L2) showed complete dominance or overdominance, and in (L1 + L2) data showed an additive effect. Our results indicated that the dominance, overdominance and epistatic effect were important in conditioning the genetic basis of heterosis of the two elite hybrids. The relative contributions of the genetic components varied with traits and the genetic basis of the two hybrids was different.

Single nucleotide polymorphism markers linked to QTL for wheat yield traits

Continuous improvement in grain yield is one of the major challenges for wheat (Triticum aestivum L.) breeding worldwide. This study characterized quantitative trait loci (QTL) underlying wheat grain yield and its components using a high-density genetic linkage map developed from a recombinant inbred line (RIL) population derived from ‘Ning7840’ × ‘Clark’. The map consisted of 594 single nucleotide polymorphism and 404 simple sequence repeat markers covering a genetic distance of 4225.7 cM. The RIL population was evaluated for grain yield (GY), spike number per m2 (SNPM), kernel number per spike (KNPS), and thousand-kernel weight (TKW) in three Oklahoma locations from 2001 to 2003. A total of 29 additive QTL (eight for GY, two for SNPM, five for KNPS, and 14 for TKW) were mapped on 13 chromosomes. Eight pairs of epistatic QTL were detected for different yield components: four for GY, two for KNPS, and two for TKW. Four additive QTL, including two for GY and two for KNPS, showed additive × environment interactions. QTL that were repeatable in multiple environments were identified for all traits except SNPM. Positive alleles were dispersed between the two parents for all traits, with ‘Clark’ contributing slightly more. Seven pleiotropic loci were co-localized for at least two traits. Interestingly, all co-localized loci overlapped for TKW, and four of them overlapped for GY. Thus, selecting QTL for TKW may simultaneously select for or against yield or other yield components in breeding.

Genetic mapping of QTLs controlling fatty acids provided insights into the genetic control of fatty acid synthesis pathway in peanut (Arachis hypogaea L.).

Peanut, a high-oil crop with about 50% oil content, is either crushed for oil or used as edible products. Fatty acid composition determines the oil quality which has high relevance to consumer health, flavor, and shelf life of commercial products. In addition to the major fatty acids, oleic acid (C18:1) and linoleic acid (C18:2) accounting for about 80% of peanut oil, the six other fatty acids namely palmitic acid (C16:0), stearic acid (C18:0), arachidic acid (C20:0), gadoleic acid (C20:1), behenic acid (C22:0), and lignoceric acid (C24:0) are accounted for the rest 20%. To determine the genetic basis and to improve further understanding on effect of FAD2 genes on these fatty acids, two recombinant inbred line (RIL) populations namely S-population (high oleic line ‘SunOleic 97R’ × low oleic line ‘NC94022’) and T-population (normal oleic line ‘Tifrunner’ × low oleic line ‘GT-C20’) were developed. Genetic maps with 206 and 378 marker loci for the S- and the T-population, respectively were used for quantitative trait locus (QTL) analysis. As a result, a total of 164 main-effect (M-QTLs) and 27 epistatic (E-QTLs) QTLs associated with the minor fatty acids were identified with 0.16% to 40.56% phenotypic variation explained (PVE). Thirty four major QTLs (>10% of PVE) mapped on five linkage groups and 28 clusters containing more than three QTLs were also identified. These results suggest that the major QTLs with large additive effects would play an important role in controlling composition of these minor fatty acids in addition to the oleic and linoleic acids in peanut oil. The interrelationship among these fatty acids should be considered while breeding for improved peanut genotypes with good oil quality and desired fatty acid composition.

Uncovering the genetic architecture of Colletotrichum lindemuthianum resistance through QTL mapping and epistatic interaction analysis in common bean.

Colletotrichum lindemuthianum is a hemibiotrophic fungal pathogen that causes anthracnose disease in common bean. Despite the genetics of anthracnose resistance has been studied for a long time, few quantitative trait loci (QTLs) studies have been conducted on this species. The present work examines the genetic basis of quantitative resistance to races 23 and 1545 of C. lindemuthianum in different organs (stem, leaf and petiole). A population of 185 recombinant inbred lines (RIL) derived from the cross PMB0225 × PHA1037 was evaluated for anthracnose resistance under natural and artificial photoperiod growth conditions. Using multi-environment QTL mapping approach, 10 and 16 main effect QTLs were identified for resistance to anthracnose races 23 and 1545, respectively. The homologous genomic regions corresponding to 17 of the 26 main effect QTLs detected were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins. Among them, it is worth noting that the main effect QTLs detected on linkage group 05 for resistance to race 1545 in stem, petiole and leaf were located within a 1.2 Mb region. The NL gene Phvul.005G117900 is located in this region, which can be considered an important candidate gene for the non-organ-specific QTL identified here. Furthermore, a total of 39 epistatic QTL (E-QTLs) (21 for resistance to race 23 and 18 for resistance to race 1545) involved in 20 epistatic interactions (eleven and nine interactions for resistance to races 23 and 1545, respectively) were identified. None of the main and epistatic QTLs detected displayed significant environment interaction effects. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for anthracnose resistance improvement in common bean through application of marker-assisted selection (MAS).

Marker-assisted breeding for transgressive seed protein content in soybean [Glycine max (L.) Merr

After two cycles of marker-assisted breeding on three loci, lines with transgressive segregation of 8.22-9.32 % protein content were developed based on four original soybean parents with 35.35-44.83 % protein content. Marker-assisted breeding has been an innovative approach in conventional breeding, which is to be further demonstrated, especially for quantitative traits. A study on continuous transgressive breeding for seed protein content (SPC) in soybean using marker-assisted procedures is reported here. The SPC of the recombinant inbred line (RIL) population XG varied in 38.04-47.54 % under five environments with P 1 of 35.35 %, P 2 of 44.34 % and total heritability of 89.11 %. A transgressive segregant XG30 with SPC 45.53 % was selected for further improvement. The linkage mapping of XG showed its genetic constitution composed of five additive QTL (32.16 % of phenotypic variation or PV) and two pairs of epistatic QTL (2.96 % PV) using 400 SSR markers with the remnant heritability 53.99 % attributed to the undetected collective of minor QTL. Another transgressive segregant WT133 with SPC 48.39 % was selected from the RIL population WT (44.83 % SPC for both parents). XG30 and WT133 were genotyped on the three major additive QTL (Prot-08-1, Prot-14-1 and Prot-19-2) as A 2 A 2 B 2 B 2 L 1 L 1 and A 1 A 1 B 1 B 1 L 2 L 2 , respectively. From WT133×XG30, surprising transgressive progenies were obtained, among which the recombinants with all three positive alleles A 2 _B 2 _L 2 _ performed the highest SPC, especially that of Prot-08-1. The five F 2-derived superior families showed their means higher than the high parent value in F 2:3 and F 2:4 and more transgressive effect in F 2:5:6, with the highest as high as 54.15 %, or 4.82 and 9.32 % more than WT133 and its original high parent, respectively. This study demonstrated the efficiency of marker-assisted procedure in breeding for transgressive segregation of quantitative trait.

Mapping isoflavone QTL with main, epistatic and QTL × environment effects in recombinant inbred lines of soybean.

Soybean (Glycine max (L.) Merr.) isoflavone is important for human health and plant defense system. To identify novel quantitative trait loci (QTL) and epistatic QTL underlying isoflavone content in soybean, F5:6, F5:7 and F5:8 populations of 130 recombinant inbred (RI) lines, derived from the cross of soybean cultivar ‘Zhong Dou 27′ (high isoflavone) and ‘Jiu Nong 20′ (low isoflavone), were analyzed with 95 new SSR markers. A new linkage map including 194 SSR markers and covering 2,312 cM with mean distance of about 12 cM between markers was constructed. Thirty four QTL for both individual and total seed isoflavone contents of soybean were identified. Six, seven, ten and eleven QTL were associated with daidzein (DZ), glycitein (GC), genistein (GT) and total isoflavone (TI), respectively. Of them 23 QTL were newly identified. The qTIF_1 between Satt423 and Satt569 shared the same marker Satt569 with qDZF_2, qGTF_1 and qTIF_2. The qGTD2_1 between Satt186 and Satt226 was detected in four environments and explained 3.41%-10.98% of the phenotypic variation. The qGTA2_1, overlapped with qGCA2_1 and detected in four environments, was close to the previously identified major QTL for GT, which were responsible for large a effects. QTL (qDZF_2, qGTF_1 and qTIF_2) between Satt144-Satt569 were either clustered or pleiotropic. The qGCM_1, qGTM_1 and qTIM_1 between Satt540-Sat_244 explained 2.02%–9.12% of the phenotypic variation over six environments. Moreover, the qGCE_1 overlapped with qGTE_1 and qTIE_1, the qTIH_2 overlapped with qGTH_1, qGCI_1 overlapped with qDZI_1, qTIL_1 overlapped with qGTL_1, and qTIO_1 overlapped with qGTO_1. In this study, some of unstable QTL were detected in different environments, which were due to weak expression of QTL, QTL by environment interaction in the opposite direction to a effects, and/or epistasis. The markers identified in multi-environments in this study could be applied in the selection of soybean cultivars for higher isoflavone content and in the map-based gene cloning.

Genetic variants in root architecture-related genes in a Glycine soja accession, a potential resource to improve cultivated soybean.

BackgroundRoot system architecture is important for water acquisition and nutrient acquisition for all crops. In soybean breeding programs, wild soybean alleles have been used successfully to enhance yield and seed composition traits, but have never been investigated to improve root system architecture. Therefore, in this study, high-density single-feature polymorphic markers and simple sequence repeats were used to map quantitative trait loci (QTLs) governing root system architecture in an inter-specific soybean mapping population developed from a cross between Glycine max and Glycine soja.ResultsWild and cultivated soybean both contributed alleles towards significant additive large effect QTLs on chromosome 6 and 7 for a longer total root length and root distribution, respectively. Epistatic effect QTLs were also identified for taproot length, average diameter, and root distribution. These root traits will influence the water and nutrient uptake in soybean. Two cell division-related genes (D type cyclin and auxin efflux carrier protein) with insertion/deletion variations might contribute to the shorter root phenotypes observed in G. soja compared with cultivated soybean. Based on the location of the QTLs and sequence information from a second G. soja accession, three genes (slow anion channel associated 1 like, Auxin responsive NEDD8-activating complex and peroxidase), each with a non-synonymous single nucleotide polymorphism mutation were identified, which may also contribute to changes in root architecture in the cultivated soybean. In addition, Apoptosis inhibitor 5-like on chromosome 7 and slow anion channel associated 1-like on chromosome 15 had epistatic interactions for taproot length QTLs in soybean.ConclusionRare alleles from a G. soja accession are expected to enhance our understanding of the genetic components involved in root architecture traits, and could be combined to improve root system and drought adaptation in soybean.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1334-6) contains supplementary material, which is available to authorized users.

Genetic control of plant height in European winter wheat cultivars.

Plant height variation in European winter wheat cultivars is mainly controlled by the Rht - D1 and Rht - B1 semi-dwarfing genes, but also by other medium- or small-effect QTL and potentially epistatic QTL enabling fine adjustments of plant height. Plant height is an important goal in wheat (Triticum aestivum L.) breeding as it affects crop performance and thus yield and quality. The aim of this study was to investigate the genetic control of plant height in European winter wheat cultivars. To this end, a panel of 410 winter wheat varieties from across Europe was evaluated for plant height in multi-location field trials and genotyped for the candidate loci Rht-B1, Rht-D1, Rht8, Ppd-B1 copy number variation and Ppd-D1 as well as by a genotyping-by-sequencing approach yielding 23,371 markers with known map position. We found that Rht-D1 and Rht-B1 had the largest effects on plant height in this cultivar collection explaining 40.9 and 15.5% of the genotypic variance, respectively, while Ppd-D1 and Rht8 accounted for 3.0 and 2.0% of the variance, respectively. A genome-wide scan for marker-trait associations yielded two additional medium-effect QTL located on chromosomes 6A and 5B explaining 11.0 and 5.7% of the genotypic variance after the effects of the candidate loci were accounted for. In addition, we identified several small-effect QTL as well as epistatic QTL contributing to the genetic architecture of plant height. Taken together, our results show that the two Rht-1 semi-dwarfing genes are the major sources of variation in European winter wheat cultivars and that other small- or medium-effect QTL and potentially epistatic QTL enable fine adjustments in plant height.

The Genetic Architecture of Fluctuating Asymmetry of Mandible Size and Shape in a Population of Mice: Another Look

Fluctuating asymmetry (FA), typically measured by variation in the differences between right and left sides of bilateral traits, is commonly used to assess developmental instability (DI) in populations. A previous quantitative trait locus (QTL) investigation using an F2 intercross mouse population found little evidence of individual loci affecting FA in mandible size, but an abundance of epistatic interactions between loci. Here we extend this work by testing whether these patterns replicate in an F3 population derived from the same intercross. Using a large number of molecular markers genotyped in over 1200 mice, we uncovered significant interactions between loci (QTLs) affecting FA in mandible size (and shape). Epistasis contributed roughly 20% of the variation in FASIZE and 19% of the variation in FASHAPE at the 0.0001 probability level alone, and was comparable to that previously estimated for the F2 mice, and much greater than that generated from the few single-locus QTLs affecting the mandible FA traits. The positions of the single-locus and epistatic QTLs for FA that we discovered suggested that logical candidate genes for DI are those controlling size or shape in the traits themselves, and that they may be interacting with genes for heat shock proteins.

Mapping and Epistatic Interactions of QTLs for Pericarp Thickness in Sweet Corn

Pericarp thickness is of great importance to the sensory quality of sweet corn. Mining the gene for pericarp thickness and understanding its genetic mechanism can provide a base for instructing breeding. Quantitative trait locus(QTL) for pericarp thickness was detected based on two genetic models using a population comprising 190 BC1F2 families derived from the cross of Richao-1(thin pericarp, 56.57 μm) ×1021(thick pericarp, 100.23 μm) in the present study. Three QTLs for pericarp thickness were identified on bin 3.01, 6.01, and 8.05 using the Composite interval mapping(CIM) method, explained 8.6%, 16.0%, and 7.2% of phenotypic variation, respectively. Based on the MCIM(mixed-model based CIM) method, we identified five QTLs for pericarp thickness, comprising one additive QTL and two pairs of epistatic QTLs. The additive QTL was located on bin 8.05. Additive × additive epistatic effects for pericarp thickness were showed between QTL in 2.01 and QTL in 6.05 with estimated 6.63% of the phenotypic variation and between QTL in 5.06 and QTL in 6.01 with the estimated phenotypic variation of 12.48%. The results indicated that epistasis and additive effects play an important role in the genetic basis of pericarp thickness. The MCIM model with the ability to detect epistatic QTLs is more suitable for pericarp thickness QTL mapping. In addition, candidate genes encoding proteins that play important role for pigment biosynthesis and cell transformation in endosperm were contained in four QTL regions of all, suggesting the likely relations between the expressions of these candidate genes and pericarp thickness variation.

Analysis of quantitative trait loci for main plant traits in soybean.

Plant traits are important indices for regulating and controlling yield ability in soybean varieties. It is important to comprehensively study the quantitative trait locus (QTL) mapping for soybean plant traits, cloning related genes, and marker assistant breeding. In this study, 236 F2 generation plants and a derivative group were constructed by using Jiyu50 and Jinong18, obtained from Jilin Province. A total of 102 simple sequence repeat markers were used to construct a genetic linkage map. With 2 years of molecular and phenotypic data, QTL analyses and mapping were conducted for soybean maturity, plant height, main stem node, main stem branch, seed weight per plant, and more. Five main plant traits were analyzed via inclusive composite interval mapping using QTL IciMapping v2.2. Using one-dimensional scanning, a total of 30 QTLs were detected and distributed across 1 (A1), 4 (C2), and 12 (G). There were 9 linkage groups, including 16 major QTLs. Using two-dimensional scanning, 7 pairs of epistatic QTL interactions for maturity and plant height were detected in the soybean.

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.