Minor Quantitative Trait Loci Research Articles

Novel Sources of Partial Resistance against Phytophthora sojae in Soybean PI 399036

With the rapid emergence of novel pathogen pathotypes, durable sources of resistance against Phytophthora sojae in soybean [Glycine max (L.) Merrill] are needed to manage Phytopthora stem and root rot (PRR). This study used an inoculum source composed of multiple isolates of the pathogen to characterize partial resistance (PR) to P. sojae in plant introduction (PI) 399036. Two recombinant inbred line (RIL) F5:7 populations developed by crossing PI 399036 (high PR), with two germplasm lines (low PR), AR2 (AX20925) and AR3 (AX20931), were screened. Corrected dry weights (CDW—root and shoot) and percentage root rot data were collected. Inclusive composite interval mapping identified one putative quantitative trait locus (QTL) on chromosome 2 by all disease assessment parameters in the AX20925 population that explained 6 to 14% of the total phenotypic variation and five putative minor QTL on 5 chromosomes (3, 6, 12, 15, and 19) that individually explained 5 to 9% of the phenotypic variation. In the AX20931 population, two QTL, mapped to chromosome 9 and 17, were commonly identified by CDW while the QTL identified on chromosome 9 accounted for 21 to 30% of the total phenotypic variation. Additional QTL identified by CDW on chromosomes 9, 13, 14, and 15 individually accounted for 5 to 8% of the phenotypic variation. PI 399036 contributed the favorable alleles for the majority of the identified QTL. This study demonstrates the usefulness of PI 399036 as a novel source for breeding for resistance to PRR and that an inoculum mixture of P. sojae isolates with varying pathotypes can be used to identify putative QTL for PR to P. sojae using the rice (Oryza sativa) method.

QTLs Associated with Agronomic Traits in the Cutler × AC Barrie Spring Wheat Mapping Population Using Single Nucleotide Polymorphic Markers.

We recently reported three earliness per se quantitative trait loci (QTL) associated with flowering and maturity in a recombinant inbred lines (RILs) population derived from a cross between the spring wheat (Triticum aestivum L.) cultivars ‘Cutler’ and ‘AC Barrie’ using 488 microsatellite and diversity arrays technology (DArT) markers. Here, we present QTLs associated with flowering time, maturity, plant height, and grain yield using high density single nucleotide polymorphic (SNP) markers in the same population. A mapping population of 158 RILs and the two parents were evaluated at five environments for flowering, maturity, plant height and grain yield under field conditions, at two greenhouse environments for flowering, and genotyped with a subset of 1809 SNPs out of the 90K SNP array and 2 functional markers (Ppd-D1 and Rht-D1). Using composite interval mapping on the combined phenotype data across all environments, we identified a total of 19 QTLs associated with flowering time in greenhouse (5), and field (6) conditions, maturity (5), grain yield (2) and plant height (1). We mapped these QTLs on 8 chromosomes and they individually explained between 6.3 and 37.8% of the phenotypic variation. Four of the 19 QTLs were associated with multiple traits, including a QTL on 2D associated with flowering, maturity and grain yield; two QTLs on 4A and 7A associated with flowering and maturity, and another QTL on 4D associated with maturity and plant height. However, only the QTLs on both 2D and 4D had major effects, and they mapped adjacent to well-known photoperiod response Ppd-D1 and height reducing Rht-D1 genes, respectively. The QTL on 2D reduced flowering and maturity time up to 5 days with a yield penalty of 436 kg ha-1, while the QTL on 4D reduced plant height by 13 cm, but increased maturity by 2 days. The high density SNPs allowed us to map eight moderate effect, two major effect, and nine minor effect QTLs that were not identified in our previous study using microsatellite and DArT markers. Results from this study provide additional information to wheat researchers developing early maturing and short stature spring wheat cultivars.

Detection of Novel QTLs Regulating Grain Size in Extra-Large Grain Rice (Oryza sativa L.) Lines.

BackgroundGrain size is an important trait that affects rice yield. Although many genes that contribute to grain size have been cloned from mutants or by quantitative trait locus (QTL) analysis based on bi-parental mapping, the molecular mechanisms underlying grain-size determination remain poorly understood. In this study, we identified the lines with the largest grain size and detected novel QTLs affecting the grain size.ResultsWe screened the National Institute for Agrobiological Sciences Genebank database and identified two rice lines, BG23 with the widest grain and LG10 with the longest grain. Using these two lines, we performed QTL analysis for grain size. Eight QTLs were detected during the QTL analyses using F2 populations derived from crosses between the large-grain lines BG23 or LG10 and the middle-size grain cultivars Nipponbare and Kasalath. Both BG23 and LG10 possessed large-grain alleles of four major QTLs: GW2, GS3, qSW5/GW5, and GW8. Other three minor QTLs were derived from BG23. However, these QTLs did not explain the differences in grain size between these two lines. Additionally, four QTLs for grain length or width were detected in an F2 population derived from a cross between BG23 and LG10; this population lacked the strong effects of the four major QTLs shared by both parent plants. Of these newly detected QTLs, the effects of two QTLs, GL3b and GL6, were confirmed by progeny testing. Comparison of the length of inner epidermal cells in plants homozygous for BG23 and LG10 alleles indicated that GL3b and GL6 genes regulate cell elongation and cell division, respectively.ConclusionsIn this study, we detected 12 loci including 14 QTLs regulating grain size from two lines with largest grains available in Japanese stock. Of these loci, we confirmed the effect of two gene loci and mapped their candidate region. Identification of novel genes regulating grain size will contribute to our understanding of the molecular mechanisms controlling grain size.Electronic supplementary materialThe online version of this article (doi:10.1186/s12284-016-0109-2) contains supplementary material, which is available to authorized users.

Erratum to: QTLs for root traits at mid-tillering and for root and shoot traits at maturity in a RIL population of spring bread wheat grown under well-watered conditions

Root system traits have positive effects on wheat grain yield, particularly in drought environments. Root traits are difficult to manipulate using conventional selection procedures. Marker-assisted-selection (MAS) could be helpful for the improvement of root morphological traits. A recombinant inbred line (RIL) population of 168 lines derived from the cross Iran #49 × Yecora Rojo was used to map quantitative trait loci (QTLs) for root traits at mid-tillering stage for one season and for root and shoot traits at plant maturity for two seasons using two different subsets. The RILs were grown in sand-tube experiments in a glasshouse under well-watered conditions. Longest root (LR), total root length longer 30 cm (TRL30), shallow root weight (roots between 0 and 30 cm, SRW), deep root weight (roots bellow 30 cm, DRW), total root biomass (RBio), ratio of root to shoot (RTS) and to plant (RTP) biomass were measured at mid-tillering. At maturity, number of days to booting (DTB), to heading (DTH), to anthesis (DTA), and to maturity (DTM), plant height (PH), flag leaf area (FLA), number of tillers (NTP) and spikes (NSP) per plant, number of grains (NGP), grain weight (GW), grain yield (GY) per plant, LR, SRW, DRW, RBio, PBio, and RTP were measured. At mid-tillering, a total of 18 putative QTLs were detected with individual QTL accounted for between 6.5 and 26.5 % of the variation in the traits. The QTLs were distributed on chromosomes 1B, 2A, 2D, 4B, 6B, 7A, and 7D. A major and two minor QTLs were identified for LR, with the major QTL (qLR-2D) explaining 26.5 % of variation. Two QTLs were detected for DRW on chromosome 4B between markers Gwm6 and Sukkula.1220 that together explained 23.1 % of variation. One region between marker Wmc198 and Cfa2263 on chromosome 2A contained four QTLs affecting PH, SRW, RTS, and RTP. At maturity, 70 putative QTLs were detected across the two seasons with a single QTL accounted for between 7.7 and 40.6 % of variation in the traits. Three major colocalized QTLs for SRW, DRW, and RBio were identified on chromosome 2D between markers Wms515 and Wms102 that accounted for 19.8, 20.5, and 22.4 % 0f variation, respectively. Two major colocalized QTLs for SRW and RBio were detected on chromosome 3A that explained 17.8 and 13.4 % of variation, respectively. One major QTL for DRW was identified on chromosome 1B that accounted for 20.3 % of variation. Chromosome 2B harbored major QTLs for GY, NGS, and NGP. A major QTL cluster was detected on chromosome 2D and on chromosome 4A relating 11 and eight QTLs for phenological periods, root traits, RTS, and RTP, indicating pleiotropic effects on these traits. Of the four common root traits studied at mid-tillering and at maturity, only SRW had linked QTLs on chromosome 2A at both stages of plant growth, indicating selection for root traits at seedling stage alone may not be effective in changing root morphological characteristics at later stages of plant growth. It appeared that chromosome 2A, 2D, and 4B harbored genes regulating growth of root traits at early and later stages of plant growth. The molecular markers closely linked to QTLs for root and shoot traits may be used in wheat breeding program using MAS procedures.

Dissection of the qTGW1.1 region into two tightly-linked minor QTLs having stable effects for grain weight in rice.

BackgroundMost agronomical traits of crop species are complex traits controlled by multiple genes and affected by environmental factors. While considerable efforts have been made to fine-map and clone major quantitative trait loci (QTLs) for yield-related traits in rice, it is not until recently that the attention has been paid to minor QTLs. Following previous dissection of QTLs for grain weight and grain size in a 12-Mb interval on the long arm of chromosome 1 in rice, this study targeted at one putative QTL region for a more precise mapping and for analyzing the genotype-by-environment interaction of minor QTLs.ResultsFour BC2F10 plants of the indica rice cross ZS97///ZS97//ZS97/MY46 were selected. They carried overlapped heterozygous segments that jointly covered the entire putative region for qTGW1.1 detected previously. Four sets of near isogenic lines (NILs) were developed from selfing progenies of the four plants. Each NIL set consisted of 32 ZS97 homozygous lines and 32 MY46 homozygous lines that differed in the corresponding heterozygous region. They were grown in two locations having distinct ecological conditions and measured for 1000-grain weight, grain length and grain width. Two QTLs were separated in an 835.2-kb interval flanked by DNA markers Wn28447 and RM11569. They both showed consistent effects across the two environments. The qTGW1.1a located within the 120.4-kb interval Wn28447 − RM11543 significantly affect all the three traits with the enhancing allele derived from ZS97, showing a stronger influence on grain weight than on grain length and width. The qTGW1.1b located in the 521.8-kb interval RM11554 − RM11569 significantly affect grain weight and length with the enhancing allele derived from MY46, having a stronger influence on grain length than on grain weight. Consistent performance of the two QTLs was confirmed in a validation experiment using five NIL-F2 populations segregated for either qTGW1.1a or qTGW1.1b.ConclusionSeparation of closely-linked QTLs having small effects is achievable in the absence of major-QTL segregation. Minor QTLs for complex traits could act consistently in diverse environments, offering the potential of pyramiding beneficial alleles of multiple minor QTLs through marker-assisted selection.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-016-0410-5) contains supplementary material, which is available to authorized users.

Identification of rice chromosome segment substitution line Z322-1-10 and mapping QTLs for agronomic traits from the F3population

Chromosome segment substitution lines (CSSLs) are powerful tools to combine naturally occurring genetic variants with favorable alleles in the same genetic backgrounds of elite cultivars. An elite CSSL Z322-1-10 was identified from advanced backcrosses between a japonica cultivar Nipponbare and an elite indica restorer Xihui 18 by SSR marker-assisted selection (MAS). The Z322-1-10 line carries five substitution segments distributed on chromosomes 1, 2, 5, 6 and 10 with an average length of 4.80 Mb. Spikilets per panicle, 1000-grain weight, grain length in the Z322-1-10 line are significantly higher than those in Nipponbare. Quantitative trait loci (QTLs) were identified and mapped for nine agronomic traits in an F3 population derived from the cross between Nipponbare and Z322-1-10 using the restricted maximum likelihood (REML) method in the HPMIXED procedure of SAS. We detected 13 QTLs whose effect ranging from 2.45% to 44.17% in terms of phenotypic variance explained. Of the 13 loci detected, three are major QTL (qGL1, qGW5-1 and qRLW5-1) and they explain 34.68%, 44.17% and 33.05% of the phenotypic variance. The qGL1 locus controls grain length with a typical Mendelian dominance inheritance of 3:1 ratio for long grain to short grain. The already cloned QTL qGW5-1 is linked with a minor QTL for grain width qGW5-2 (13.01%) in the same substitution segment. Similarly, the previously reported qRLW5-1 is also linked with a minor QTL qRLW5-2. Not only the study is important for fine mapping and cloning of the gene qGL1, but also has a great potential for molecular breeding.

Genome-Wide Association Study of Anthracnose Resistance in Andean Beans (Phaseolus vulgaris).

Anthracnose is a seed-borne disease of common bean (Phaseolus vulgaris L.) caused by the fungus Colletotrichum lindemuthianum, and the pathogen is cosmopolitan in distribution. The objectives of this study were to identify new sources of anthracnose resistance in a diverse panel of 230 Andean beans comprised of multiple seed types and market classes from the Americas, Africa, and Europe, and explore the genetic basis of this resistance using genome-wide association mapping analysis (GWAS). Twenty-eight of the 230 lines tested were resistant to six out of the eight races screened, but only one cultivar Uyole98 was resistant to all eight races (7, 39, 55, 65, 73, 109, 2047, and 3481) included in the study. Outputs from the GWAS indicated major quantitative trait loci (QTL) for resistance on chromosomes, Pv01, Pv02, and Pv04 and two minor QTL on Pv10 and Pv11. Candidate genes associated with the significant SNPs were detected on all five chromosomes. An independent QTL study was conducted to confirm the physical location of the Co-1 locus identified on Pv01 in an F4:6 recombinant inbred line (RIL) population. Resistance was determined to be conditioned by the single dominant gene Co-1 that mapped between 50.16 and 50.30 Mb on Pv01, and an InDel marker (NDSU_IND_1_50.2219) tightly linked to the gene was developed. The information reported will provide breeders with new and diverse sources of resistance and genomic regions to target in the development of anthracnose resistance in Andean beans.

Multi-environment QTL analysis of grain morphology traits and fine mapping of a kernel-width QTL in Zheng58 × SK maize population

Sixteen major QTLs regulating maize kernel traits were mapped in multiple environments and one of them, qKW - 9.2 , was restricted to 630Kb, harboring 28 putative gene models. To elucidate the genetic basis of kernel traits, a quantitative trait locus (QTL) analysis was conducted in a maize recombinant inbred line population derived from a cross between two diverse parents Zheng58 and SK, evaluated across eight environments. Construction of a high-density linkage map was based on 13,703 single-nucleotide polymorphism markers, covering 1860.9cM of the whole genome. In total, 18, 26, 23, and 19 QTLs for kernel length, width, thickness, and 100-kernel weight, respectively, were detected on the basis of a single-environment analysis, and each QTL explained 3.2-23.7% of the phenotypic variance. Sixteen major QTLs, which could explain greater than 10% of the phenotypic variation, were mapped in multiple environments, implying that kernel traits might be controlled by many minor and multiple major QTLs. The major QTL qKW-9.2 with physical confidence interval of 1.68Mbp, affecting kernel width, was then selected for fine mapping using heterogeneous inbred families. At final, the location of the underlying gene was narrowed down to 630Kb, harboring 28 putative candidate-gene models. This information will enhance molecular breeding for kernel traits and simultaneously assist the gene cloning underlying this QTL, helping to reveal the genetic basis of kernel development in maize.

Identification of novel major and minor QTLs associated with Xanthomonas oryzae pv. oryzae (African strains) resistance in rice (Oryza sativa L.).

BackgroundXanthomonas oryzae pv. oryzae (Xoo) is the causal agent of Bacterial Leaf Blight (BB), an emerging disease in rice in West-Africa which can induce up to 50 % of yield losses. So far, no specific resistance gene or QTL to African Xoo were mapped. The objectives of this study were to identify and map novels and specific resistance QTLs to African Xoo strains.ResultsThe reference recombinant inbred lines (RIL) mapping population derived from the cross between IR64 and Azucena was used to investigate Xoo resistance. Resistance to African and Philippine Xoo strains representing different races was assessed on the RIL population under greenhouse conditions. Five major quantitative trait loci (QTL) for resistance against African Xoo were located on different chromosomes. Loci on chromosomes 1, 7, 9, 10 and 11 explained as much as 13 %, 37 %, 13 %, 11 % and 15 % of resistance variation, respectively. A major novel QTL located on chromosome 7 explained 37 % of the phenotypic variance to the African Xoo corresponding to race A3 whereas that on chromosome 11 is effective to all African races tested. Together with genes and QTLs for resistance to bacterial blight previously described, the QTLs described here were mapped onto the reference O. sativa subs japonica (var. Nipponbare) physical map.ConclusionWe characterized new resistance QTLs. While some co-localize with known resistance genes/QTLs to Asian strains, others are specific to African strains. We result with new information on genes and QTLs for resistance to bacterial blight that will be useful for controlling the disease.

Considering causal genes in the genetic dissection of kernel traits in common wheat.

Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m2 (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

QTL analysis and the development of closely linked markers for days to flowering in spring oilseed rape (Brassica napus L.)

Days to flowering (DTF) is an important trait impacting cultivar performance in oilseed rape (Brassica napus L.), but the interaction of all loci controlling this trait in spring-type oilseed rape is not fully understood. We identified quantitative trait loci (QTL) for variation in DTF in a doubled haploid (DH) population from the Qinghai–Tibet Plateau that includes 217 lines derived from a cross between spring-type oilseed rape (B. napus L.) line No. 5246 and line No. 4512, the latter of which is responsive to the effective accumulated temperature (EAT). A linkage map was constructed for the DH population, using 202 SSR and 293 AFLP markers. At least 22 DTF QTL were found in multiple environments. Four major QTL were located on linkage groups A7, C2, C8 and C8. Among these QTL, cqDTFA7a and cqDTFC2a were identified in five environments and individually explained 10.4 and 23.0 % of the trait variation, respectively. cqDTFC8, a major QTL observed in spring environments, and a unique winter environment QTL, qDTFC8-3, were identified; these QTL explained 10.0 and 46.5 % of the phenotypic variation, respectively. Minor QTL (for example, cqDTFC2c) and epistatic interactions seemed evident in this population. Two closely linked SSR markers for cqDTFA7a and cqDTFC8 were developed (G1803 and S034). BnAP1, a B. napus gene with homology to Arabidopsis thaliana that was identified as a cqDTFA7a candidate gene, played a major role in this study. The allelic effects of the major and minor QTL on DTF were further validated in the DH population and in 93 breeding genotypes.

Quantitative trait loci affecting pathogen resistance and ripening of grapevines.

Grapevines (Vitis vinifera L.) form the basis of viticulture, and are susceptible to diseases such as downy mildew (Plasmopara viticola) and powdery mildew (Erysiphe necator). Therefore, successful viticulture programs require the use of pesticides. Breeding for resistance is the only eco-friendly solution. Marker-assisted selection is currently widely used for grapevine breeding. Consequently, traits of interest must be tagged with molecular markers linked to quantitative trait loci (QTL). We herein present our findings regarding genetic mapping and QTL analysis of resistance to downy and powdery mildew diseases in the progenies of the GF.GA-47-42 ('Bacchus'×'Seyval')×'Villard blanc' cross. Simple sequence repeats and single nucleotide polymorphisms of 151 individuals were analyzed. A map consisting of 543 loci was screened for QTL analyses based on phenotypic variations observed in plants grown in the field or under controlled conditions. A major QTL for downy mildew resistance was detected on chromosome 18. For powdery mildew resistance, a QTL was identified on chromosome 15. This QTL was replaced by a novel QTL on chromosome 18 in 2003 (abnormally high temperatures) and 2004. Subsequently, both QTLs functioned together. Additionally, variations in the timing of the onset of veraison, which is a crucial step during grape ripening, were studied to identify genomic regions affecting this trait. A major QTL was detected on linkage group 16, which was supplemented by a minor QTL on linkage group 18. This study provides useful information regarding novel QTL-linked markers relevant for the breeding of disease-resistant grapevines adapted to current climatic conditions.

Genomic Tools in Groundnut Breeding Program: Status and Perspectives.

Groundnut, a nutrient-rich food legume, is cultivated world over. It is valued for its good quality cooking oil, energy and protein rich food, and nutrient-rich fodder. Globally, groundnut improvement programs have developed varieties to meet the preferences of farmers, traders, processors, and consumers. Enhanced yield, tolerance to biotic and abiotic stresses and quality parameters have been the target traits. Spurt in genetic information of groundnut was facilitated by development of molecular markers, genetic, and physical maps, generation of expressed sequence tags (EST), discovery of genes, and identification of quantitative trait loci (QTL) for some important biotic and abiotic stresses and quality traits. The first groundnut variety developed using marker assisted breeding (MAB) was registered in 2003. Since then, USA, China, Japan, and India have begun to use genomic tools in routine groundnut improvement programs. Introgression lines that combine foliar fungal disease resistance and early maturity were developed using MAB. Establishment of marker-trait associations (MTA) paved way to integrate genomic tools in groundnut breeding for accelerated genetic gain. Genomic Selection (GS) tools are employed to improve drought tolerance and pod yield, governed by several minor effect QTLs. Draft genome sequence and low cost genotyping tools such as genotyping by sequencing (GBS) are expected to accelerate use of genomic tools to enhance genetic gains for target traits in groundnut.

Quantitative resistance against Bemisia tabaci in Solanum pennellii: Genetics and metabolomics.

The whitefly Bemisia tabaci is a serious threat in tomato cultivation worldwide as all varieties grown today are highly susceptible to this devastating herbivorous insect. Many accessions of the tomato wild relative Solanum pennellii show a high resistance towards B. tabaci. A mapping approach was used to elucidate the genetic background of whitefly-resistance related traits and associated biochemical traits in this species. Minor quantitative trait loci (QTLs) for whitefly adult survival (AS) and oviposition rate (OR) were identified and some were confirmed in an F2 BC1 population, where they showed increased percentages of explained variance (more than 30%). Bulked segregant analyses on pools of whitefly-resistant and -susceptible F2 plants enabled the identification of metabolites that correlate either with resistance or susceptibility. Genetic mapping of these metabolites showed that a large number of them co-localize with whitefly-resistance QTLs. Some of these whitefly-resistance QTLs are hotspots for metabolite QTLs. Although a large number of metabolite QTLs correlated to whitefly resistance or susceptibility, most of them are yet unknown compounds and further studies are needed to identify the metabolic pathways and genes involved. The results indicate a direct genetic correlation between biochemical-based resistance characteristics and reduced whitefly incidence in S. pennellii.

Quantitative trait loci underlying host responses of soybean to Fusarium virguliforme toxins that cause foliar sudden death syndrome.

Soybean deploys multiple genetic mechanisms to confer tolerance to Fusarium virguliforme toxins. This study revealed that F. virguliforme culture filtrates could be used in mapping QTL underlying foliar SDS resistance. Sudden death syndrome (SDS) is a major soybean disease throughout most of the soybean growing regions in the world including the United States. The disease is caused by the fungal pathogen, Fusarium virguliforme (Fv). The fungus produces several toxins that are responsible for development of interveinal leaf chlorosis and necrosis, which are typical foliar SDS symptoms. Growing of resistant cultivars has been the most effective method in controlling the disease. The objective of the present study was to identify quantitative trait loci (QTL) underlying host responses of soybean to Fv toxins present in culture filtrates. To accomplish this objective, two recombinant inbred line (RIL) populations, AX19286 (A95-684043 × LS94-3207) and AX19287 (A95-684043 × LS98-0582), segregating for SDS resistance were evaluated for foliar symptom development by applying two screening protocols, the stem cutting and the root feeding assays. The AX19286 population revealed two major and seven minor QTL for SDS resistance. In the AX19287 population, we identified five major QTL and three minor QTL. The two QTL mapped to Chromosome 7 [molecular linkage group (MLG) M] and Chromosome 20 (MLG I) are most likely novel, and were detected through screening of the AX19287 population with stem cutting and root feeding assays, respectively. This study established that Fv culture filtrates could be employed in mapping QTL underlying foliar SDS resistance. The outcomes of the research also suggest that multiple genetic mechanisms might be used by soybean to overcome the toxic effects of the toxins secreted by the pathogen into culture filtrates.

Regions of the bread wheat D genome associated with variation in key photosynthesis traits and shoot biomass under both well watered and water deficient conditions.

A quantitative trait locus (QTL) approach was taken to reveal the genetic basis in wheat of traits associated with photosynthesis during a period of exposure to water deficit stress. The performance, with respect to shoot biomass, gas exchange and chlorophyll fluorescence, leaf pigment content and the activity of various ascorbate-glutathione cycle enzymes and catalase, of a set of 80 wheat lines, each containing a single chromosomal segment introgressed from the bread wheat D genome progenitor Aegilops tauschii, was monitored in plants exposed to various water regimes. Four of the seven D genome chromosomes (1D, 2D, 5D, and 7D) carried clusters of both major (LOD >3.0) and minor (LOD between 2.0 and 3.0) QTL. A major QTL underlying the activity of glutathione reductase was located on chromosome 2D, and another, controlling the activity of ascorbate peroxidase, on chromosome 7D. A region of chromosome 2D defined by the microsatellite locus Xgwm539 and a second on chromosome 7D flanked by the marker loci Xgwm1242 and Xgwm44 harbored a number of QTL associated with the water deficit stress response.

Identification of stable QTLs for vegetative and reproductive traits in the microvine (Vitis vinifera L.) using the 18 K Infinium chip

BackgroundThe increasing temperature associated with climate change impacts grapevine phenology and development with critical effects on grape yield and composition. Plant breeding has the potential to deliver new cultivars with stable yield and quality under warmer climate conditions, but this requires the identification of stable genetic determinants. This study tested the potentialities of the microvine to boost genetics in grapevine. A mapping population of 129 microvines derived from Picovine x Ugni Blanc flb, was genotyped with the Illumina® 18 K SNP (Single Nucleotide Polymorphism) chip. Forty-three vegetative and reproductive traits were phenotyped outdoors over four cropping cycles, and a subset of 22 traits over two cropping cycles in growth rooms with two contrasted temperatures, in order to map stable QTLs (Quantitative Trait Loci).ResultsTen stable QTLs for berry development and quality or leaf area were identified on the parental maps. A new major QTL explaining up to 44 % of total variance of berry weight was identified on chromosome 7 in Ugni Blanc flb, and co-localized with QTLs for seed number (up to 76 % total variance), major berry acids at green lag phase (up to 35 %), and other yield components (up to 25 %). In addition, a minor QTL for leaf area was found on chromosome 4 of the same parent. In contrast, only minor QTLs for berry acidity and leaf area could be found as moderately stable in Picovine. None of the transporters recently identified as mutated in low acidity apples or Cucurbits were included in the several hundreds of candidate genes underlying the above berry QTLs, which could be reduced to a few dozen candidate genes when a priori pertinent biological functions and organ specific expression were considered.ConclusionsThis study combining the use of microvine and a high throughput genotyping technology was innovative for grapevine genetics. It allowed the identification of 10 stable QTLs, including the first berry acidity QTLs reported so far in a Vitis vinifera intra-specific cross. Robustness of a set of QTLs was assessed with respect to temperature variation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-015-0588-0) contains supplementary material, which is available to authorized users.

Establishment of a 100-seed weight quantitative trait locus-allele matrix of the germplasm population for optimal recombination design in soybean breeding programmes.

A representative sample comprising 366 accessions from the Chinese soybean landrace population (CSLRP) was tested under four growth environments for determination of the whole-genome quantitative trait loci (QTLs) system of the 100-seed weight trait (ranging from 4.59g to 40.35g) through genome-wide association study (GWAS). A total of 116 769 single nucleotide polymorphisms (SNPs) were identified and organized into 29 121 SNP linkage disequilibrium blocks (SNPLDBs) to fit the property of multiple alleles/haplotypes per locus in germplasm. An innovative two-stage GWAS was conducted using a single locus model for shrinking the marker number followed by a multiple loci model utilizing a stepwise regression for the whole-genome QTL identification. In total, 98.45% of the phenotypic variance (PV) was accounted for by four large-contribution major QTLs (36.33%), 51 small-contribution major QTLs (43.24%), and a number of unmapped minor QTLs (18.88%), with the QTL×environment variance representing only 1.01% of the PV. The allele numbers of each QTL ranged from two to 10. A total of 263 alleles along with the respective allele effects were estimated and organized into a 263×366 matrix, giving the compact genetic constitution of the CSLRP. Differentiations among the ecoregion matrices were found. No landrace had alleles which were all positive or all negative, indicating a hidden potential for recombination. The optimal crosses within and among ecoregions were predicted, and showed great transgressive potential. From the QTL system, 39 candidate genes were annotated, of which 26 were involved with the gene ontology categories of biological process, cellular component, and molecular function, indicating that diverse genes are involved in directing the 100-seed weight.

The Negative Correlation between Fiber Color and Quality Traits Revealed by QTL Analysis.

Naturally existing colored cotton was far from perfection due to having genetic factors for lower yield, poor fiber quality and monotonous color. These factors posed a challenge to colored cotton breeding and innovation. To identify novel quantitative trait loci (QTL) for fiber color along with understanding of correlation between fiber color and quality in colored cotton, a RIL and two F2 populations were generated from crosses among Zong128 (Brown fiber cotton) and two white fiber cotton lines which were then analyzed in four environments. Two stable and major QTLs (qLC-7-1, qFC-7-1) for fiber lint and fuzz color were detected accounting for 16.01%-59.85% of the phenotypic variation across multiple generations and environments. Meanwhile, some minor QTLs were also identified on chromosomes 5, 14, 21 and 24 providing low phenotypic variation (<5%) from only F2 populations, not from the RILs population. Especially, a multiple-effect locus for fiber color and quality has been detected between flanking markers NAU1043 and NAU3654 on chromosome 7 (A genome) over multiple environments. Of which, qLC-7-1, qFC-7-1 were responsible for positive effects and improved fiber color in offsprings. Meanwhile, the QTLs (qFL-7-1, qFU-7-1, qFF-7-1, qFE-7-1, and qFS-7-1) for fiber quality had negative effects and explained 2.19%-8.78% of the phenotypic variation. This multiple-effect locus for fiber color and quality may reveal the negative correlation between the two types of above traits, so paving the way towards cotton genetic improvement.

QTL analysis of dehydration tolerance at seedling stage in rice (Oryza sativa L..)

Dehydration tolerant QTLs at the seedling stage in rice (Oryza sativa L.) was studied using green shoot length as a parameter, which was measured during the recovery period after dehydration stress. According to the results of pilot experiment carried out to evaluate the two parental rice cultivars for the level of dehydration tolerance, at 4 - day and 5-day dehydration stress, Japonica parent Hyogokithanishiki (HGKN) showed more tolerance than that of Hokuriku-142 Indica parent (HOK). Quantitative trait loci (QTLs) associated with dehydration tolerance was identified using 163 recombinant inbred lines derived from these parents on a linkage map constructed with 95 simple sequence repeat (SSR) markers. Three dehydration tolerant minor QTLs were identified on chromosome 1, 2 and 3 at composite interval mapping by WinQTLCARTOGRAHER. According to the additive effect plots the QTLs on chromosome 1 and 2 have the allelic effect from the Indica parent Hokuriku-142 and QTL on chro- mosome 3 has allelic effect from Hyogokithanishiki Japonica parent. However, according to the 1000 time permutation test, these QTLs didn’t exceed the threshold LOD value. Tropical Agricultural Research and Extension 15(4): 2012: page 98-104