Stable QTL Research Articles

Stable quantitative trait locus (QTL) for sheath blight resistance from rice cultivar CR 1014

Sheath blight disease of rice causes substantial crop losses and resistance sources are rare. A moderately resistant genotype CR 1014 was identified and hybridized with highly susceptible genotype Swarna-Sub1. In the F2 and F2:3 generations, three QTLs (qShB-1.1, qShB-1.2 and qShB-1.3) were mapped in chromosome-1. In F5 generation of the same cross and F4 generation of an alternative mapping population (Tapaswini/CR 1014), only the major QTL qShB-1.1 was recorded consistently with high LOD score (> 5.0). This stable QTL was co-localized with qShB1 reported earlier from Oryza nivara. A typical leucine rich repeat (LRR) motif containing gene (LOC_Os01g65650) and a chitin-inducible gibberellin-responsive protein coding non-LRR gene (LOC_Os01g65900) located within qShB-1.1 with high expression levels in leaf and shoot were predicted as putative candidate genes among others. Nearly 27.8% reduction in relative lesion height was recorded among several near isogenic lines of Swarna-Sub1 carrying the QTL region from CR 1014.

Intercontinental trials reveal stable QTL for Northern corn leaf blight resistance in Europe and in Brazil

Key messageNCLB is the most devastating leaf disease in European maize, and the introduction of Brazilian resistance donors can efficiently increase the resistance levels of European maize germplasm.Northern corn leaf blight (NCLB) is one of the most devastating leaf pathogens in maize (Zea mays L.). Maize cultivars need to be equipped with broad and stable NCLB resistance to cope with production intensification and climate change. Brazilian germplasm is a great source to increase low NCLB resistance levels in European materials, but little is known about their effect in European environments. To investigate the usefulness of Brazilian germplasm as NCLB resistance donors, we conducted multi-parent QTL mapping, evaluated the potential of marker-assisted selection as well as genome-wide selection of 742 F1-derived DH lines. The line per se performance was evaluated in one location in Brazil and six location-by-year combinations (= environments) in Europe, while testcrosses were assessed in two locations in Brazil and further 10 environments in Europe. Jointly, we identified 17 QTL for NCLB resistance explaining 3.57–30.98% of the genotypic variance each. Two of these QTL were detected in both Brazilian and European environments indicating the stability of these QTL in contrasting ecosystems. We observed moderate to high genomic prediction accuracies between 0.58 and 0.83 depending on population and continent. Collectively, our study illustrates the potential use of tropical resistance sources to increase NCLB resistance level in applied European maize breeding programs.

Mapping QTL for agronomic traits under two levels of salt stress in a new constructed RIL wheat population.

QTL for 15 agronomic traits under two levels of salt stress in dry salinity field were mapped in a new constructed RIL population utilizing a Wheat55K SNP array. Furthermore, eight QTL were validated in a collected natural population. Soil salinity is one of the major abiotic stresses causing serious impact on crop growth, development and yield. As one of the three most important crops in the world, bread wheat (Triticum aestivum L.) is severely affected by salinity, too. In this study, an F7 recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 and salt-tolerant cultivar Xiaoyan 60 was constructed. The adult stage performances of the RIL population and their parent lines under low and high levels of salt stress were evaluated for three consecutive growing seasons. Utilizing a Wheat55K SNP array, a high-density genetic linkage map spinning 3250.71cM was constructed. QTL mapping showed that 90 stable QTL for 15 traits were detected, and they were distributed on all wheat chromosomes except 4D, 6B and 7D. These QTL individually explained 2.34-32.43% of the phenotypic variation with LOD values ranging from 2.68 to 47.15. It was found that four QTL clusters were located on chromosomes 2D, 3D, 4B and 6A, respectively. Notably, eight QTL from the QTL clusters were validated in a collected natural population. Among them, QPh-4B was deduced to be an allele of Rht-B1. In addition, three kompetitive allele-specific PCR (KASP) markers derived from SNPs were successfully designed for three QTL clusters. This study provides an important base for salt-tolerant QTL (gene) cloning in wheat, and the markers, especially the KASP markers, will be useful for marker-assisted selection in salt-tolerant wheat breeding.

SNP-based QTL mapping for panicle traits in the japonica super rice cultivar Liaoxing 1

Panicle traits directly associated with yield are a target of selection in rice breeding. Although abundant QTL for panicle traits have been identified, there is little information about the genetic basis of panicle traits in japonica super rice (JSR) cultivars. In this study, we identified QTL for panicle traits in three environments using a population of recombinant inbred lines (RILs) derived from the JSR cultivar Liaoxing 1. A total of 197 RILs were genotyped with 285 polymorphic SNP markers. Phenotypic data and best linear unbiased prediction (BLUP) value of primary branch number (BNP), secondary branch number (BNS), grain number on primary branch (GNP), grain number on secondary branch (GNS), grain number per panicle (GN), panicle length (PL) and grain density (GD) were used for QTL mapping. A total of 105 QTL for seven panicle traits were detected in single environments using their BLUP values. Individual QTL explained 0.51%–52.22% of the phenotypic variation. Of the 105, 49 were also detected by joint multi-environment analyses. Five stable QTL: qGD9, qPL9, qGNP9, qGN6, and qBNS6.2 were identified in multiple environments. qGD9, qGNP9, and qPL9, co-localizing on chromosome 9, likely correspond to the known gene DEP1. Importantly, qGN6 and qBNS6.2 in a co-localization region were identified as novel QTL, and their Liaoxing 1 alleles had a positive effect. Several RILs with the QTL allele combinations qGD9/qPL9/qGNP9 and qGN6/qBNS6.2 showed greater GN. Further investigation of the putative gene underlying qGN6/qBNS6.2 would shed light on the molecular mechanism of JSR.

Tomato near isogenic lines to unravel the genetic diversity of S. pimpinellifolium LA0722 for fruit quality and shelf life breeding

The introgression of genes from the wild species S. pimpinellifolium has the potential to improve tomato commercial varieties for numerous fruit quality traits. One of particular interest for fresh-market tomatoes is long shelf life (SL). Twenty-two near isogenic lines (NILs) were developed in three to four backcrosses using S. pimpinellifolium accession LA0722 as the donor parent, based on phenotypic selection for long SL and using a set of 28 SSRs for marker assisted selection. A total of 30 QTLs for fruit quality were found and 18 were subsequently validated in previous generations. A two year trial of the NILs homozygous for the LA0722 introgressions showed several novel QTLs. Fruit quality QTLs revealed an increased effect promoted by LA0722 alleles. A SL QTL was found on chromosome 9 and was consistent both years. A wild introgression on chromosome 3 showed a stable QTL for increased firmness and for yellow fruits. Therefore, the wild introgressions provide a source of variation with positive effects in fruit traits of commercial value. While obtaining new varieties, this strategy provided an effective method that integrates the QTL analysis and the prediction of positive alleles in wild germplasm.

EMBRYONIC FLOWER2B, coming from a stable QTL, represses the floral transition in cotton

The EMBRYONIC FLOWER 2 (EMF2) gene encodes a VEFS (VRN2–EMF2–FIS2–Su(z)12) domain protein involved in plant growth and development. Herein, genome-wide characterization of the VEFS-box gene family in Gossypium raimondii, G. arboreum, G. barbadense, and G. hirsutum was performed with a total of 3, 3, 6, and 6 homologous sequences respectively identified in the four species. The gene structure, protein motifs, and gene expression were further investigated. Based on our previous research on multiple stable quantitative trait loci for early maturity, GhEMF2B on chromosome D03 was selected as a candidate gene for further study. Quantitative real-time PCR analysis indicated that GhEMF2B was upregulated in the apical buds of late-maturing cultivars at the fourth and fifth true-leaf stages compared to that of early-maturing cultivars. Virus-induced gene silencing of GhEMF2B in cotton seedlings repressed expression by 50%–70%, which led to earlier floral bud development, young curled leaves, and abnormal petal formation. Further analysis demonstrated that the silencing of GhEMF2B enhanced the expression levels of the positive floral regulators AGAMOUS-LIKE 6 (GhAGL6), FLOWERING LOCUS T (GhFT), and APETALA 1 (GhAP1). Thus, it can be inferred that GhEMF2B plays important roles in the floral transition and development of cotton.

Identification of new QTL for yield-related traits in Chinese landrace and elite wheat varieties through a genome-wide linkage mapping

Spike length (SL), fertile spikelet number per spike (SNS), thousand grain weight (TGW) and plant height (PH) are important agronomic traits related to yield in wheat. By the 55 K SNP assay, we constructed a high-density genetic linkage map with 186 F6 recombinant inbred lines developed between Chinese landrace wheat Banmangzi and an elite variety Jimai 22. Eighteen QTLs for SL, SNS, TGW and PH were detected. A new stable major QTL for SL was located on chromosome 2DS, with physical position 19.6 Mb and explaining 20.1–27.9% of the phenotypic variances in three environments, with the favorable allele from Banmangzi. And the QTL was co-located with QSNS.saas-2D.1 and QPH.saas-2D.2 which were detected in two environments and explained up to 18.5% of phenotypic variances for SNS. In addition, an major QTL for TGW was detected on chromosome 6AS, explaining 14.6–22.3% of the phenotypic variances in three environments. Four candidate genes for yield-related traits were identified, encoding IAA-amino acid hydrolase ILR1 and growth-regulating factor for SL, flowering promoting factor-like 1 and sucrose-phosphate synthase for TGW, respectively.

Identification of genotyping-by-sequencing tags associated with bread-making quality traits in spring wheat under heat stress

The bread-making quality traits of bread wheat underlie into genetic make-up of a variety and are influenced by environmental factors and their interaction. Identifying QTL that control bread-making traits in wheat under heat stress may help to develop cultivars that are improved for those traits. Two doubled haploid (DH) populations (Yecora Rojo × Ksu106 and Klasic × Ksu105) were used to identify QTL for eight bread-making traits in wheat under heat stress. The phenotyping of bread-making traits was performed under normal and heat stress conditions in Al-Qassim and Riyadh locations, Saudi Arabia. Single nucleotide polymorphism (SNP) markers have been used to determine the number of QTLs controlling the bread-making traits. The genetic analysis of bread-making traits showed considerable variation for measurable traits with transgressive segregation under normal and heat stress conditions in both locations. A total of 60 QTL explained 10–22% of phenotypic variation in the population (Klassic × KSU105). In the population (Yecora Rojo × KSU106), the 98 QTL explained 10–23% of phenotypic variation. In the population (Klassic × KSU105), eleven co-located QTLs were identified on chromosomes 2A, 3A, 3D, 5B and5D. The BBS QTL under heat stress co-located with QTLs for BCC and BSY under heat stress and normal conditions, respectively, in Riyadh location. Nineteen QTL clusters were identified on chromosomes 1D, 2A, 2B, 2D, 3B, 3D, 4A, 4D, 5A, 5B, 6A, 7A and 7D based on Map 2 in the population (Yecora Rojo × KSU106). Interestingly, one locus (JD_c4438_839) on the chromosome 5D was identified in both populations and was considered stable QTL. This locus was associated with QLFV.hs and QSLFV.hs in the population (Klassic × KSU105) and QLFW.n in the population (Yecora Rojo × KSU106). The finding of SNP marker (JD_c4438_839) has an important significant for marker-assisted selection of bread-making quality traits under heat stress.

QGW, a Stable and Major QTL for Increasing of Grain Weight in Rice (Oryza sativa L.)

qGW, a Stable and Major QTL for Increasing of Grain Weight in Rice (Oryza sativa L.)

Detection of QTL and QTL × environment interaction for scald resistance in a two-row × six-row cross of barley

Leaf scald caused by Rhynchosporium secalis, is a serious disease of barley (Hordeum vulgare L.) in Tunisia. A doubled-haploid barley population, from a cross between the two-rowed ‘Roho’ and the six-rowed ‘L90’ cultivars, was evaluated for its reaction to scald under natural infection in replicated field trials for two years. Phenotypic variation among doubled-haploid lines was significant for disease reaction in both environments (cropping seasons) and genotype × environment interaction was also significant. Heritability estimates were high in both seasons and significant correlation was noted between scald reactions recorded in the two seasons. Segregation of 34 single sequence repeat markers was used for quantitative trait loci mapping. Single-marker analysis was applied for individual and for combined environments to determine the effect of each molecular marker on scald resistance. In total, six QTLs with additive effects were mapped on chromosomes 2H, 3H, 4H, 6H and 7H which explained from 4.4 to 11.7% of the phenotypic variance. Among these, only QTLs linked to WMS6 (4H) and to HVM31 (6H) showed significant QTL × environment interactions. QTLs associated to HVM36 (2H) and to Bmag0571 (7H) were the most significant for scald resistance and the most insensitive to the environment. Another stable QTL was identified, for the first time, in the vicinity of the Vrs1 locus on the 2H chromosome. For this QTL, the two-rowed parental allele reduced disease severity. These chromosomal regions that affect scald resistance independently of the environment would be of great interest in marker-assisted selection.

Novel peanut genotype with low behenic acid developed from recombinant inbred lines

<p indent="0mm">Peanut is an important source of edible vegetable oil in China, and improving the quality of peanut oil is an important goal in peanut breeding. In this study, the contents of very long-chain saturated fatty acids (arachidic acid, behenic acid, and tetracosanoic acid) were determined by using RIL population containing 140 lines derived from the cross between Zhonghua 10 and ICG12625 with different genetic backgrounds. The content of very long- chain saturated fatty acid in the RILs was 4.27%–7.05%, with an average of 5.54%, the minimum value was 1.46 and 1.63 percentage points lower than that of male and female parents, with reduction rates of 25.27% and 27.62%, respectively. The behenic acid content ranged from 1.86% to 3.37%, with an average of 2.53%. Three lines of QT0002, QT0075, and QT0120 had behenic acid content lower than 2%, which was 0.57, 0.51, and 0.51 percentage points lower than that of Zhonghua10 with the reduction rate of 23.45%, 20.98%, and 20.98%, respectively. A stable QTL located in 13.31–16.34 M of B04 was detected using a linkage map and WinQTLcart software. In this region of 13.31–16.34 M contained 131 prediction genes. The results lay a foundation for the genetic improvement of low behenic acid and high-oleic peanut varieties.

Transferability of Marker Trait Associations in Wheat Is Disturbed Mainly by Genotype × Year Interaction

Grain yield is the primary target for increasing soft red winter wheat production in the United States. Genome wide association studies were performed for yield-related traits using field-based evaluation of 270 elite breeding lines. Yield ranged from 3.9 to 7.5 tons·ha−1. The effect of genotype by year interaction was significant for most traits. Heritability estimates ranged from 0.21 for biomass to 0.84 for plant height. Biomass, kernel weight, and grain weight per spike were positively correlated with grain yield while days to heading and maturity were negatively correlated with grain yield. We used FarmCPU method and 45K markers to identify marker-trait associations. Fifty-nine MTAs were identified based on two-year phenotypic estimates. An association for grain yield on chromosome 7D showed a −logP value of 16.35 and explained 18% of the phenotypic variation. Associations were identified at −logP values of 6.30 and 4.08 on chromosomes 5A for thousand kernel weight and grain per spike that explained 10% and 6% of phenotypic variations, respectively. Grain yield and days to heading data from previous trials in other states were used to validate and evaluate the transferability of associations. We observed that for grain yield, only 7 out of 28 associations and for days to heading, only 8 out of 47 associations were validated across seemingly homogenous environments, indicating the majority of associations are not stable QTL across environments. This study suggests that achieving genetic gains appears to require utilizing genotype by environment interaction and local field based germplasm testing.

Genetic Parameters and QTLs for Total Phenolic Content and Yield of Wheat Mapping Population of CSDH Lines under Drought Stress.

A doubled haploid population of 94 lines from the Chinese Spring × SQ1 wheat cross (CSDH) was used to evaluate additive and epistatic gene action effects on total phenolic content, grain yield of the main stem, grain number per plant, thousand grain weight, and dry weight per plant at harvest based on phenotypic and genotypic observations of CSDH lines. These traits were evaluated under moderate and severe drought stress and compared with well-watered plants. Plants were grown in pots in an open-sided greenhouse. Genetic parameters, such as additive and epistatic effects, affecting total phenolic content, were estimated for eight year-by-drought combinations. Twenty-one markers showed a significant additive effect on total phenolic content in all eight year-by-drought combinations. These markers were located on chromosomes: 1A, 1B, 2A, 2B, 2D, 3A, 3B, 3D, 4A, and 4D. A region on 4AL with a stable QTL controlling the phenolic content, confirmed by various statistical methods is particularly noteworthy. In all years and treatments, three markers significantly linked to QTLs have been identified for both phenols and yield. Thirteen markers were coincident with candidate genes. Our results indicated the importance of both additive and epistatic gene effects on total phenolic content in eight year-by-drought combinations.

Mining QTLs and candidate genes for seed protein and oil contents across multiple environments and backgrounds in soybean

Soybean is important due to its seed protein and oil, but its seed protein and oil contents need to be improved. In view of this, two genetically related F6:7 recombinant inbred line (RIL) populations, derived from Zheng92116×Qihuang30 (ZQ) and Zheng92116× Liaodou14 (ZL), were genotyped with a SoySNP 6K chip and evaluated for seed protein and oil contents in four different environments. In total, ten stable collocating or overlapping additive QTL clusters, which explained 2.6~23.3% of the phenotypic variation, were identified in the ZQ population in different environments, four of which were further verified in the ZL population. One major and stable QTL controlling seed oil content, qOIL-A1, was detected in all four environments in ZQ and was validated in three environments in the ZL population, with the PVE (phenotypic variation explained) ranging from 4.8 to 22.1% and four of the PVE values exceeding 10% (22.1%, 19.3%, 10.9%, and 12.9%). Another major and stable QTL controlling seed protein content, qPRO-J, was detected in different environments in ZQ and was further verified in the ZL population, with a PVE of 14.1% and 23.2% in ZQ and a PVE of 9.5% in ZL. Moreover, the individuals in the RIL population and another cultivar-based population (320 varieties and landraces) with different genotypes at the common flanking markers for the QTL clusters showed extremely significantly different protein and oil contents, which further validated the QTL mapping results. Based on these findings, eight novel candidate genes with very different expression levels at different soybean seed growth and developmental stages between ZQ and ZL RIL parents were identified in the qOIL-A1 region through transcriptome sequencing and were finally verified by real-time qPCR. Thus, these stable QTL clusters can be applied in marker-assisted selection breeding or map-based candidate gene cloning in soybean for seed protein and oil genetic improvements in the future.

Flag leaf size and posture of bread wheat: genetic dissection, QTL validation and their relationships with yield-related traits.

Major and environmentally stable QTL for flag leaf-related traits in wheat were identified and validated across ten environments using six populations with different genetic backgrounds. Flag leaf size and posture are two important factors of "ideotype" in wheat. Despite numerous studies on genetic analysis of flag leaf size including flag leaf length (FLL), width (FLW), area (FLA) and the ratio of length/width (FLR), few have focused on flag leaf posture including flag leaf angle (FLANG), opening angle (FLOA) and bend angle (FLBA). Further, the numbers of major, environmentally stable and verified genetic loci for flag leaf-related traits are limited. In this study, QTL for FLL, FLW, FLA, FLR, FLANG, FLOA and FLBA were identified based on a recombinant inbred line population together with values from up to ten different environments. Totally, eight major and stably expressed QTL were identified. Three co-located chromosomal intervals for seven major QTL were identified. The five major QTL QFll.sicau-5B.3 and QFll.sicau-2D.3 for FLL, QFlr.sicau-5B for FLR, QFlw.sicau-2D for FLW and QFla.sicau-2D for FLA were successfully validated by the tightly linked Kompetitive Allele Specific PCR (KASP) markers in the other five populations with different genetic backgrounds. A few genes related to leaf growth and development in intervals for these major QTL were predicated. Significant relationships between flag leaf- and yield-related traits were evidenced by analyses of Pearson correlations, conditional QTL and genetic mapping. Taken together, these results provide valuable information for understanding flag leaf size and posture of "ideotype" as well as fine mapping and breeding utilization of promising loci in bread wheat.

Genotyping-by-sequencing based QTL mapping for rice grain yield under reproductive stage drought stress tolerance

QTLs for rice grain yield under reproductive stage drought stress (qDTY) identified earlier with low density markers have shown linkage drag and need to be fine mapped before their utilization in breeding programs. In this study, genotyping-by-sequencing (GBS) based high-density linkage map of rice was developed using two BC1F3 mapping populations namely Swarna*2/Dular (3929 SNPs covering 1454.68 cM) and IR11N121*2/Aus196 (1191 SNPs covering 1399.68 cM) with average marker density of 0.37 cM to 1.18 cM respectively. In total, six qDTY QTLs including three consistent effect QTLs were identified in Swarna*2/Dular while eight qDTY QTLs including two consistent effect QTLs were identified in IR11N121*2/Aus 196 mapping population. Comparative analysis revealed four stable and novel QTLs (qDTY2.4, qDTY3.3, qDTY6.3, and qDTY11.2) which explained 8.62 to 14.92% PVE. However, one of the identified stable grain yield QTL qDTY1.1 in both the populations was located nearly at the same physical position of an earlier mapped major qDTY QTL. Further, the effect of the identified qDTY1.1 was validated in a subset of lines derived from five mapping populations confirming robustness of qDTY1.1 across various genetic backgrounds/seasons. The study successfully identified stable grain yield QTLs free from undesirable linkages of tall plant height/early maturity utilizing high density linkage maps.

Genetic mapping of quantitative trait locus for the leaf morphological traits in a recombinant inbred line population by ultra‐high–density maps across multi‐environments of maize (Zea mays)

AbstractLeaf is the main organ of photosynthetic reaction of plants. Studying the genetic mechanism that affects the leaf shape is very important for the improvement of maize production. In this study, a RIL population, derived from a cross between Ye478 and Qi319, was planted in four different environments, and six leaf morphological traits were measured, including the leaf angle of first leaf above ear, the leaf angle of first leaf below ear, leaf orientation value, leaf area of first leaf above ear, leaf area of ear and leaf area of first leaf below ear. By combining with a genetic map containing 4,602 bin markers, 39 QTLs associated with leaf morphological traits were identified. Among them, four QTLs explained more than 10% of the phenotypic variance, and the QTL qLOV8‐2 which controlled LOV not only had a phenotypic contribution rate of 13.86% but also was detected in four environments, which could be considered as a stable major QTL. These results provide useful information for understanding the molecular mechanisms controlling maize leaf morphological traits.

A high density SLAF-seq SNP genetic map and QTL for seed size, oil and protein content in upland cotton

BackgroundCotton is a leading natural fiber crop. Beyond its fiber, cottonseed is a valuable source of plant protein and oil. Due to the much higher value of cotton fiber, there is less consideration of cottonseed quality despite its potential value. Though some QTL controlling cottonseed quality have been identified, few of them that warrant further study are known. Identifying stable QTL controlling seed size, oil and protein content is necessary for improvement of cottonseed quality.ResultsIn this study, a recombinant inbred line (RIL) population was developed from a cross between upland cotton cultivars/lines Yumian 1 and M11. Specific locus amplified fragment sequencing (SLAF-seq) technology was used to construct a genetic map that covered 3353.15 cM with an average distance between consecutive markers of 0.48 cM. The seed index, together with kernel size, oil and protein content were further used to identify QTL. In total, 58 QTL associated with six traits were detected, including 13 stable QTL detected in all three environments and 11 in two environments.ConclusionA high resolution genetic map including 7033 SNP loci was constructed through specific locus amplified fragment sequencing technology. A total of 13 stable QTL associated with six cottonseed quality traits were detected. These stable QTL have the potential for fine mapping, identifying candidate genes, elaborating molecular mechanisms of cottonseed development, and application in cotton breeding programs.

Transcriptome and QTL analyses reveal candidate genes for fiber quality in Upland cotton

With increasing demand for high-quality cotton, it is desirable to identify genes involved in fiber development for molecular improvement of cotton. In this study, 780 differentially expressed genes (DEGs) were identified in developing fibers at 10 days post-anthesis (DPA) in Gossypium hirsutum acc. DH962 and G. hirsutum cv. Jimian 5 using RNA-seq. Of 15 stable QTL for fiber quality identified in the same two parents in previous studies, 4, 3, 6, 1, and 1 QTL were associated with fiber length (FL), fiber strength (FS), micronaire (MIC), fiber elongation (FE) and fiber length uniformity ratio (FU), respectively. Integration of DEGs and QTL allowed the identification of 31 genes in 9 QTL regions, of which 25 were highly expressed in fibers based on the transcriptome datasets and 9 were preferentially expressed in different stages of fiber development. Gh_A01G0453 (GhDTX19), Gh_D07G1581 and Gh_D04G0942 were expressed specifically in 5 and 10 DPA fibers, with Gh_D04G0942 showing low expression in other tissues except pistil. Gh_D07G1799 (GhGAUT9), Gh_D11G0326 (GhVPS29), Gh_D11G0333 (GhTCP14), and Gh_D11G0334 (GhNRP2) were preferentially expressed in 5 or 10 DPA fibers; Gh_A01G0397 (GhABCG10) and Gh_D07G1744 were expressed specifically in 20 and 25 DPA fibers. These results suggest candidate genes for molecular improvement of cotton fiber quality.

Mapping QTLs with main and epistatic effect on Seri ‘M82 × Babax‘wheat population under salt stress

The population of this research included 167 recombinant inbred lines (RILs) derived from a Seri/Babax cross. In order to map and visualize the genetic architecture of the agricultural traits, an experiment was conducted in an alpha lattice under normal (2 ds m−1) and saline (12–14 ds m−1) conditions at the Research Farm of Agricultural and Natural Resource Station of Zabol, Iran for 2 years (2012–2013). in this study, a total of 20 QTLs with additive effects and of 24 QTLs with epistatic effects for these traits were identified and distributed across all 21 chromosomes of wheat. Twenty stable QTL regions were detected on chromosomes 1B, 1D, 2A, 3B, 4A, 6A, 7A and 7D, which could significantly affect traits in all experiments. The QTLs detected on chromosomes 7D and 1D were not only significant and consistent but also co-localized for days to heading and days to anthesis. Several colocalized and additive QTLs with variability in QTL regions of chromosome 3B were also identified, which included the QTLs for final dry biomass (BY, straw + grain), grain yield and water-soluble carbohydrate content. The only two QTLs on chromosome 1B identified for the two traits were chlorophyll Florence (FV/FM) and thousand grain weight in different regions. Most of the identified QTLs had significant additive and epistatic effects with QTL and environments (QEIs) interactions.