Important Quantitative Trait Loci Research Articles

GBS-SNP and SSR based genetic mapping and QTL analysis for drought tolerance in upland cotton.

The online version contains supplementary material available at 10.1007/s12298-021-01041-y.

High-Density Linkage Map Construction and QTL Identification in a Diploid Blueberry Mapping Population.

Genotyping by sequencing approaches have been widely applied in major crops and are now being used in horticultural crops like berries and fruit trees. As the original and largest producer of cultivated blueberry, the United States maintains the most diverse blueberry germplasm resources comprised of many species of different ploidy levels. We previously constructed an interspecific mapping population of diploid blueberry by crossing the parent F1#10 (Vaccinium darrowii Fla4B × diploid V. corymbosum W85–20) with the parent W85–23 (diploid V. corymbosum). Employing the Capture-Seq technology developed by RAPiD Genomics, with an emphasis on probes designed in predicted gene regions, 117 F1 progeny, the two parents, and two grandparents of this population were sequenced, yielding 131.7 Gbp clean sequenced reads. A total of 160,535 single nucleotide polymorphisms (SNPs), referenced to 4,522 blueberry genome sequence scaffolds, were identified and subjected to a parent-dependent sliding window approach to further genotype the population. Recombination breakpoints were determined and marker bins were deduced to construct a high density linkage map. Twelve blueberry linkage groups (LGs) consisting of 17,486 SNP markers were obtained, spanning a total genetic distance of 1,539.4 cM. Among 18 horticultural traits phenotyped in this population, quantitative trait loci (QTLs) that were significant over at least 2 years were identified for chilling requirement, cold hardiness, and fruit quality traits of color, scar size, and firmness. Interestingly, in 1 year, a QTL associated with timing of early bloom, full bloom, petal fall, and early green fruit was identified in the same region harboring the major QTL for chilling requirement. In summary, we report here the first high density bin map of a diploid blueberry mapping population and the identification of several horticulturally important QTLs.

Leveraging breeding programs and genomic data in Norway spruce (Picea abies L. Karst) for GWAS analysis

BackgroundGenome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.ResultsWe identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is associated with the budburst stage, followed by diameter at breast height, wood quality, and frost damage. Two QTLs with the largest effect have a pleiotropic effect for budburst stage, frost damage, and diameter and are associated with MAP3K genes. Genotype data called from exome capture, recently developed SNP array and gene expression data indirectly support this discovery.ConclusionSeveral important QTLs associated with growth and frost damage have been verified in several southern and northern progeny plantations, indicating that these loci can be used in QTL-assisted genomic selection. Our study also demonstrates that existing heterogeneous phenotypic data from breeding programs, collected over several decades, is an important source for GWAS and that such integration into GWAS should be a major area of inquiry in the future.

Identification of a major QTL for root thickness in diploid wild sweetpotato (Ipomoea trifida) using QTL-seq

ABSTRACT Ipomoea trifida, the closest relative of sweetpotato, does not generally form storage roots, but some lines develop thick roots similar to the storage roots of the sweetpotato. Revealing the molecular mechanism of thick root development in I. trifida would help us understand the evolution of storage roots in the sweetpotato. In this study, we conducted a mapping method for quantitative trait loci (QTLs) known as QTL-seq, which is a kind of next-generation sequencing-based bulk segregant analysis. We performed QTL-seq using a backcross population (BC1F1) derived from two I. trifida lines: Mx23Hm, which does not show root-thickening; and 0431-1, which produces thick roots. The aim was to identify the QTL region involved in thick root development. As a result, a major QTL for root thickness (qRT1) was detected in the 2.94–8.71 Mb region of chr06 of Itr_r2.2, in both pot and field experiments. Six DNA markers were designed for qRT1 using InDels on chr06. Genotyping each BC1F1 individual based on these DNA markers agreed well with the SNP-Index of QTL-seq. Moreover, most individuals with 0431-1-type alleles of qRT1 developed thicker roots than individuals without 0431-1-type alleles of qRT1 in the BC2F2 population. The results of this study implied that qRT1 was an important QTL for regulating root thickness in I. trifida.

Genome-Wide Association Study Identified Novel Candidate Loci/Genes Affecting Lodging Resistance in Rice.

Lodging reduces rice yield, but increasing lodging resistance (LR) usually limits yield potential. Stem strength and leaf type are major traits related to LR and yield, respectively. Hence, understanding the genetic basis of stem strength and leaf type is of help to reduce lodging and increase yield in LR breeding. Here, we carried out an association analysis to identify quantitative trait locus (QTLs) affecting stem strength-related traits (internode length/IL, stem wall thickness/SWT, stem outer diameter/SOD, and stem inner diameter/SID) and leaf type-associated traits (Flag leaf length/FLL, Flag leaf angle/FLA, Flag leaf width/FLW, leaf-rolling/LFR and SPAD/Soil, and plant analyzer development) using a diverse panel of 550 accessions and evaluated over two years. Genome-wide association study (GWAS) using 4,076,837 high-quality single-nucleotide polymorphisms (SNPs) identified 89 QTLs for the nine traits. Next, through “gene-based association analysis, haplotype analysis, and functional annotation”, the scope was narrowed down step by step. Finally, we identified 21 candidate genes in 9 important QTLs that included four reported genes (TUT1, OsCCC1, CFL1, and ACL-D), and seventeen novel candidate genes. Introgression of alleles, which are beneficial for both stem strength and leaf type, or pyramiding stem strength alleles and leaf type alleles, can be employed for LR breeding. All in all, the experimental data and the identified candidate genes in this study provide a useful reference for the genetic improvement of rice LR.

QTL mapping of seedling biomass and root traits under different nitrogen conditions in bread wheat (Triticum aestivum L.)

Plant nitrogen assimilation and use efficiency in the seedling's root system are beneficial for adult plants in field condition for yield enhancement. Identification of the genetic basis between root traits and N uptake plays a crucial role in wheat breeding. In the present study, 198 doubled haploid lines from the cross of Yangmai 16/Zhongmai 895 were used to identify quantitative trait loci (QTLs) underpinning four seedling biomass traits and five root system architecture (RSA) related traits. The plants were grown under hydroponic conditions with control, low and high N treatments (Ca(NO3)2·4H2O at 0, 0.05 and 2.0 mmol L−1, respectively). Significant variations among the treatments and genotypes, and positive correlations between seedling biomass and RSA traits (r=0.20 to 0.98) were observed. Inclusive composite interval mapping based on a high-density map from the Wheat 660K single nucleotide polymorphisms (SNP) array identified 51 QTLs from the three N treatments. Twelve new QTLs detected on chromosomes 1AL (1) in the control, 1DS (2) in high N treatment, 4BL (5) in low and high N treatments, and 7DS (3) and 7DL (1) in low N treatments, are first reported in influencing the root and biomass related traits for N uptake. The most stable QTLs (RRS.caas-4DS) on chromosome 4DS, which were related to ratio of root to shoot dry weight trait, was in close proximity of the Rht-D1 gene, and it showed high phenotypic effects, explaining 13.1% of the phenotypic variance. Twenty-eight QTLs were clustered in 12 genetic regions. SNP markers tightly linked to two important QTLs clusters C10 and C11 on chromosomes 6BL and 7BL were converted to kompetitive allele-specific PCR (KASP) assays that underpin important traits in root development, including root dry weight, root surface area and shoot dry weight. These QTLs, clusters and KASP assays can greatly improve the efficiency of selection for root traits in wheat breeding programmes.

An Overview of the Morphological, Genetic and Metabolic Mechanisms Regulating Phosphorus Efficiency Via Root Traits in Soybean

Phosphorus (P) is an essential macronutrient for optimum productivity of several crops including soybean, but it is largely limited in most arable lands. The persistent depletion of phosphate rocks is a major constraint for plant growth and development. Improved P efficiency (PE, uptake and use efficiency) drives an enhanced biological nitrogen fixation in soybean, which could consequently lead to an increased grain and biomass production. Thus, to mitigate P limitation in soybean production, a wide range of genetic approaches have been deployed. These approaches have unravelled the morphological, genetic, phytohormonal and metabolic mechanisms involved in soybean adaptations to P-deficient conditions. Most of the approaches are targeted at root modifications due to the importance of roots in the mediation of early responses to P-deficient conditions. PE among soybean genotypes in P-deficient conditions is mostly dependent on the root plasticity, development of shallow root architecture, symbiosis with arbuscular mycorrhizal fungi and exudation of phosphatases and organic acid anions. Genetic manipulation of soybean has revealed a number of important genes (GmPAPs, GmPTs, GmPLDZ2, GmIPS1 and GmExPB2), transcription factors (C2H2 zinc finger protein, WRKY and MYB) and quantitative trait loci (q14-2 and q19-2) modulating P mobilisation, uptake and utilization under P limiting conditions. Through the modification of root traits, the hormonal (biosynthesis, transport and secretion of ethylene, auxin and jasmonic acid) and metabolic (phenylpropanoid biosynthesis and phenylalanine metabolisms) pathways also modulate PE in soybean. Recent advances in genetic manipulations of root traits offer promising ways for enhancing soybean production, particularly in a P limiting environment.

NGS-based multiplex assay of trait-linked molecular markers revealed the genetic diversity of Iranian bread wheat landraces and cultivars

NGS-based multiplex assay has accomplished a valuable status as a means of high throughput research, rapid screening functional markers in wheat breeding programs. Accordingly, we applied a total of 42 locus-specific markers from Indel and SNP-mediated categorisations coupled with the agronomic important genes or quantitative trait loci (QTL) in bread wheat. The amplicons were analysed by an Ion Torrent Proton Sequencer. Then, an allele detection custom pipeline was applied to process the genotype of a total of 99 Iranian cultivars and 270 landraces. On the whole, 29 markers were positively incorporated and achieved 100% SNP call rates. Assessment of sequence-tagged site (STS) and competitive allele-specific PCR (KASP) markers concerning the same loci confirmed the genotype calls of all markers altogether. It was revealed that the Iranian cultivars and landraces supply a rich genetic resource capable of resisting Hessian fly, leaf rust, fusarium head blight, adult plant leaf diseases, stem rust, wheat soilborne mosaic virus, wheat streak mosaic, pre-harvest sprouting, high grain protein, and gluten strength traits. This finding can be developed to improve and enrich bread wheat. Further, it is advocated that NGS-based multiplex assay can be a promising approach for high throughput in examining trait-linked markers in wheat germplasm collections.

Coadaptation of the chemosensory system with voluntary exercise behavior in mice.

Ethologically relevant chemical senses and behavioral habits are likely to coadapt in response to selection. As olfaction is involved in intrinsically motivated behaviors in mice, we hypothesized that selective breeding for a voluntary behavior would enable us to identify novel roles of the chemosensory system. Voluntary wheel running (VWR) is an intrinsically motivated and naturally rewarding behavior, and even wild mice run on a wheel placed in nature. We have established 4 independent, artificially evolved mouse lines by selectively breeding individuals showing high VWR activity (High Runners; HRs), together with 4 non-selected Control lines, over 88 generations. We found that several sensory receptors in specific receptor clusters were differentially expressed between the vomeronasal organ (VNO) of HRs and Controls. Moreover, one of those clusters contains multiple single-nucleotide polymorphism loci for which the allele frequencies were significantly divergent between the HR and Control lines, i.e., loci that were affected by the selective breeding protocol. These results indicate that the VNO has become genetically differentiated between HR and Control lines during the selective breeding process. Although the role of the vomeronasal chemosensory receptors in VWR activity remains to be determined, the current results suggest that these vomeronasal chemosensory receptors are important quantitative trait loci for voluntary exercise in mice. We propose that olfaction may play an important role in motivation for voluntary exercise in mammals.

QTL mapping for soybean (Glycine max L.) leaf chlorophyll-content traits in a genotyped RIL population by using RAD-seq based high-density linkage map

BackgroundDifferent soybean (Glycine max L.) leaf chlorophyll-content traits are considered to be significantly linked to soybean yield. To map the quantitative trait loci (QTLs) of soybean leaf chlorophyll-content traits, an advanced recombinant inbred line (RIL, ZH, Zhonghuang 24 × Huaxia 3) population was adopted to phenotypic data acquisitions for the target traits across six distinct environments (seasons and soybean growth stages). Moreover, the restriction site-associated DNA sequencing (RAD-seq) based high-density genetic linkage map of the RIL population was utilized for QTL mapping by carrying out the composite interval mapping (CIM) approach.ResultsCorrelation analyses showed that most traits were correlated with each other under specific chlorophyll assessing method and were regulated both by hereditary and environmental factors. In this study, 78 QTLs for soybean leaf chlorophyll-content traits were identified. Furthermore, 13 major QTLs and five important QTL hotspots were classified and highlighted from the detected QTLs. Finally, Glyma01g15506, Glyma02g08910, Glyma02g11110, Glyma07g15960, Glyma15g19670 and Glyma15g19810 were predicted from the genetic intervals of the major QTLs and important QTL hotspots.ConclusionsThe detected QTLs and candidate genes may facilitate to gain a better understanding of the hereditary basis of soybean leaf chlorophyll-content traits and may be valuable to pave the way for the marker-assisted selection (MAS) breeding of the target traits.

Identification of fruit size associated quantitative trait loci featuring SLAF based high-density linkage map of goji berry (Lycium spp.)

BackgroundGoji (Lycium spp., 2n = 24) is a fruit bearing woody plant popular as a superfood for extensive medicinal and nutritional advantages. Fruit size associated attributes are important for evaluating small-fruited goji berry and plant architecture. The domestication traits are regulated quantitatively in crop plants but few studies have attempted on genomic regions corresponding to fruit traits.ResultsIn this study, we established high-resolution map using specific locus amplified fragment (SLAF) sequencing for de novo SNPs detection based on 305 F1 individuals derived from L. chinense and L. barbarum and performed quantitative trait loci (QTL) analysis of fruit size related traits in goji berry. The genetic map contained 3495 SLAF markers on 12 LGs, spanning 1649.03 cM with 0.47 cM average interval. Female and male parents and F1 individuals` sequencing depth was 111.85-fold and 168.72-fold and 35.80-fold, respectively. The phenotype data were collected for 2 successive years (2018–2019); however, two-year mean data were combined in an extra year (1819). Total 117 QTLs were detected corresponding to multiple traits, of which 78 QTLs in 2 individual years and 36 QTLs in extra year. Six Promising QTLs (qFW10–6.1, qFL10–2.1, qLL10–2.1, qLD10–2.1, qLD12–4.1, qLA10–2.1) were discovered influencing fruit weight, fruit length and leaf related attributes covering an interval ranged from 27.32–71.59 cM on LG10 with peak LOD of 10.48 and 14.6% PVE. Three QTLs targeting fruit sweetness (qFS3–1, qFS5–2) and fruit firmness (qFF10–1) were also identified. Strikingly, various traits QTLs were overlapped on LG10, in particular, qFL10–2.1 was co-located with qLL10–2.1, qLD10–2.1 and qLA10–2.1 among stable QTLs, harbored tightly linked markers, while qLL10–1 was one major QTL with 14.21 highest LOD and 19.3% variance. As LG10 harbored important traits QTLs, we might speculate that it could be hotspot region regulating fruit size and plant architectures.ConclusionsThis report highlights the extremely saturated linkage map using SLAF-seq and novel loci contributing fruit size-related attributes in goji berry. Our results will shed light on domestication traits and further strengthen molecular and genetic underpinnings of goji berry; moreover, these findings would better facilitate to assemble the reference genome, determining potential candidate genes and marker-assisted breeding.

A high-density SNP-based linkage map using genotyping-by-sequencing and its utilization for improved genome assembly of chickpea (Cicer arietinum L.).

Genotyping-by-sequencing (GBS) allows rapid identification of markers for use in development of linkage maps, which expedite efficient breeding programs. In the present study, we have utilized GBS approach to identify and genotype single-nucleotide polymorphism (SNP) markers in an inter-specific RIL population of Cicer arietinum L. X C. reticulatum. A total of 141,639 raw SNPs were identified using the TASSEL-GBS pipeline. After stringent filtering, 8208 candidate SNPs were identified of which ~ 37% were localized in the intragenic regions followed by genic regions (~ 30%) and intergenic regions (~ 27%). We then utilized 6920 stringent selected SNPs from present study and 6714 SNPs and microsatellite markers available from previous studies for construction of linkage map. The resulting high-density linkage map comprising of eight linkage groups contained 13,590 markers which spanned 1299.14 cM of map length with an average marker density of 0.095 cM. Further, the derived linkage map was used to improve the available assembly of desi chickpea genome by anchoring 443 previously unplaced scaffolds onto eight linkage groups. The present efforts have refined anchoring of the desi chickpea genome assembly to 55.57% of the ~ 520 Mb of assembled desi genome. To the best of our knowledge, the linkage map generated in the present study represents one of the most dense linkage map developed for the crop till date. It will serve as a valuable resource for fine mapping and positional cloning of important quantitative trait loci (QTLs) associated with agronomical traits and also for anchoring and ordering of future genome sequence assemblies.

Comparison of GWA statistical methods for traits under different genetic structures: A simulation study

Several methods have been used to perform genome wide association (GWA) studies, aiming to map quantitative trait loci (QTL) and candidate variants. The single-step genomic best linear unbiased prediction (ssGBLUP) method is one alternative to perform GWA, which allows the simultaneous use of genotypic, pedigree and phenotypic information. Bayesian multiple regression models have also been used to perform GWA, allowing specifying different priori distribution for the molecular marker effects. The aim of the present study was to evaluate, through simulation, the performance of different methods in the identification of QTLs for polygenic and major gene traits, under different heritabilities when only relatively few animals were genotyped. We also investigated the consequence of considering the agreement among results from different methods as a strategy to decrease errors associated with false positives in QTL mapping. For polygenic scenarios, results showed low power to detect QTL, irrespective of the method, and the use of phenotypes from non-genotyped animals slightly helped QTL detection of ssGBLUP and weighted ssGBLUP (wssGBLUP). For scenarios with major gene effects, there was greater power in QTL detection, with a slight superiority of Bayes C over the other methods. The inclusion of additional phenotypic information (from non-genotyped animals) harmed the performance of wssGBLUP in the presence of major QTL. When only consensus regions identified by different methods were considered as evidence of QTL, the percentage of top windows containing a true QTL tended to increase with the number of methods that identified a top window, for all scenarios. However, an important proportion of true QTL were identified only by a single or few methods. Despite the small differences among methods in the QTL detection, for polygenic traits, the ssGBLUP and wssGBLUP methods seemed to show better results in comparison to the other methods mainly in the low heritability scenario. For traits with major gene effects, the Bayes C method is expected to present better results, compared to the other methods evaluated, given a limited number of genotyped animals. The strategy to use agreement of GWA results among methods to map QTL helps to reduce false positives but comes at a cost of missing important QTL, irrespective of the genetic structure of the trait.

Validation of a SNP-KASP marker for the Fusarium head blight resistance quantitative trait loci on chromosome 5AS

Fusarium head blight (FHB) is a devastating wheat disease with a significant economic impact. Fhb5 is an important quantitative trait loci (QTL) conferring type I resistance to FHB. In this study, we accessed the usability of a Kompetitive allele-specific polymerase chain reaction (KASP) marker for the QTL on Fhb-5AS. The KASP clustering results were compared with the linked simple sequence repeat marker, wmc705 for Qfhb-5AS. Our results indicate that the single-nucleotide polymorphic locus wsnp_Ra_c24707_34262900 (IWA7777) provides reliable information for Qfhb-5AS-based resistance and would be amenable to masker-assisted selection, introgression of the resistance loci, and pyramiding of FHB resistance in wheat cultivars.

Genome-Wide Association Study and Gene Specific Markers Identified 51 Genes or QTL for Resistance to Stripe Rust in U.S. Winter Wheat Cultivars and Breeding Lines.

Stripe (yellow) rust, caused by fungal pathogen Puccinia striiformis f. sp. tritici (Pst), is a serious disease of wheat in the United States and many other countries. Growing resistant cultivars has been approved to be the best approach for control of stripe rust. To determine stripe rust resistance genes in U.S. winter wheat cultivars and breeding lines, we analyzed a winter wheat panel of 857 cultivars and breeding lines in a genome-wide association study (GWAS) using genotyping by multiplexed sequencing (GMS) and by genotyping with molecular markers of 18 important stripe rust resistance genes or quantitative trait loci (QTL). The accessions were phenotyped for stripe rust response at adult-plant stage under natural infection in Pullman and Mount Vernon, Washington in 2018 and 2019, and in the seedling stage with six predominant or most virulent races of Pst. A total of 51 loci were identified to be related to stripe rust resistance, and at least 10 of them (QYrww.wgp.1D-3, QYrww.wgp.2B-2, QYrww.wgp.2B-3, QYrww.wgp.2B-4, QYrww.wgp.3A, QYrww.wgp.5A, QYrww.wgp.5B, QYrww.wgp.5D, QYrww.wgp.6A-2 and QYrww.wgp.7B-3) were previously reported. These genes or QTL were found to be present at different frequencies in breeding lines and cultivars developed by breeding programs in various winter wheat growing regions. Both Yr5 and Yr15, which are highly resistant to all races identified thus far in the U.S., as well as Yr46 providing resistance to many races, were found absent in the breeding lines and commercially grown cultivars. The identified genes or QTL and their markers are useful in breeding programs to improve the level and durability of resistance to stripe rust.

Genetic variants that influence SARS-CoV-2 receptor TMPRSS2 expression among population cohorts from multiple continents

The World Health Organization recently announced that pandemic status has been achieved for coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exponential increases in patient numbers have been reported around the world, along with proportional increases in the number of COVID-19-related deaths. The SARS-CoV-2 infection rate in a population is expected to be influenced by social practices, availability of vaccines or prophylactics, and the prevalence of susceptibility genes in the population. Previous work revealed that cellular uptake of SARS-CoV-2 requires Angiotensin Converting Enzyme 2 (ACE-2) and a cellular protease. The spike (S) protein on SARS-CoV-2 binds ACE-2, which functions as an entry receptor. Following receptor binding, transmembrane protease serine 2 (encoded by TMPRSS2) primes the S protein to allow cellular uptake. Therefore, individual expression of TMPRSS2 may be a crucial determinant of SARS-CoV-2 infection susceptibility. Here, we utilized multiple large genome databases, including the GTEx portal, SNP nexus, and Ensembl genome project, to identify gene expression profiles for TMPRSS2 and its important expression quantitative trait loci. Our results show that four variants (rs464397, rs469390, rs2070788 and rs383510) affect expression of TMPRSS2 in lung tissue. The allele frequency of each variant was then assessed in regional populations, including African, American, European, and three Asian cohorts (China, Japan and Taiwan). Interestingly, our data shows that TMPRSS2-upregulating variants are at higher frequencies in European and American populations than in the Asian populations, which implies that these populations might be relatively susceptible to SARS-CoV-2 infection.

Polyploidization events shaped the transcription factor repertoires in legumes (Fabaceae).

Transcription factors (TFs) are essential for plant growth and development. Several legumes (e.g. soybean) are rich sources of protein and oil and have great economic importance. Here we report a phylogenomic analysis of TF families in legumes and their potential association with important traits (e.g. nitrogen fixation). We used TF DNA-binding domains to systematically screen the genomes of 15 leguminous and five non-leguminous species. Transcription factor orthologous groups (OGs) were used to estimate OG sizes in ancestral nodes using a gene birth-death model, which allowed the identification of lineage-specific expansions. The OG analysis and rate of synonymous substitutions show that major TF expansions are strongly associated with whole-genome duplication (WGD) events in the legume (approximately 58 million years ago) and Glycine (approximately 13 million years ago) lineages, which account for a large fraction of the Phaseolus vulgaris and Glycine max TF repertoires. Of the 3407 G.max TFs, 1808 and 676 have homeologs within single syntenic regions in Phaseolus vulgaris and Vitis vinifera, respectively. We found a trend for TFs expanded in legumes to be preferentially transcribed in roots and nodules, supporting their recruitment early in the evolution of nodulation in the legume clade. Some families also showed count differences between G.max and the wild soybean Glycine soja, including genes located within important quantitative trait loci. Our findings strongly support the roles of two WGDs in shaping the TF repertoires in the legume and Glycine lineages, and these are probably related to important aspects of legume and soybean biology.

Linkage mapping and genome-wide association study reveals conservative QTL and candidate genes for Fusarium rot resistance in maize

BackgroundFusarium ear rot (FER) caused by Fusarium verticillioides is a major disease of maize that reduces grain yield and quality globally. However, there have been few reports of major loci for FER were verified and cloned.ResultTo gain a comprehensive understanding of the genetic basis of natural variation in FER resistance, a recombinant inbred lines (RIL) population and one panel of inbred lines were used to map quantitative trait loci (QTL) for resistance. As a result, a total of 10 QTL were identified by linkage mapping under four environments, which were located on six chromosomes and explained 1.0–7.1% of the phenotypic variation. Epistatic mapping detected four pairs of QTL that showed significant epistasis effects, explaining 2.1–3.0% of the phenotypic variation. Additionally, 18 single nucleotide polymorphisms (SNPs) were identified across the whole genome by genome-wide association study (GWAS) under five environments. Compared linkage and association mapping revealed five common intervals located on chromosomes 3, 4, and 5 associated with FER resistance, four of which were verified in different near-isogenic lines (NILs) populations. GWAS identified three candidate genes in these consistent intervals, which belonged to the Glutaredoxin protein family, actin-depolymerizing factors (ADFs), and AMP-binding proteins. In addition, two verified FER QTL regions were found consistent with Fusarium cob rot (FCR) and Fusarium seed rot (FSR).ConclusionsThese results revealed that multi pathways were involved in FER resistance, which was a complex trait that was controlled by multiple genes with minor effects, and provided important QTL and genes, which could be used in molecular breeding for resistance.

WFhb1-1 plays an important role in resistance against Fusarium head blight in wheat

Fusarium head blight (FHB) is a severe disease of wheat (Triticum aestivum L.). Qfhb1 is the most important quantitative trait locus (QTL) for FHB resistance. We previously identified wheat gene WFhb1-1 (aka WFhb1-c1) as a candidate for FHB resistance gene. Here we report that WFhb1-1 has been cloned. The gene (GenBank # KU304333.1) consists of a single exon, encoding a putative membrane protein of 127 amino acids. WFhb1-1 protein produced in Pichia pastoris inhibits growth of both F. graminearum and P. pastoris in culture. Western Blotting with anti- WFhb1-1 antibody revealed a significant decrease (p < 0.01) in WFhb1-1 accumulation, 12 hours post Fusarium inoculation in non-Qfhb1-carrier wheat but not in Qfhb1-carrier wheat. Overexpressing WFhb1-1 in non-Qfhb1-carrier wheat led to a significant decrease (p < 0.01) in Fusarium-damaged rachis rate, Fusarium-diseased kernel rate and DON content in harvested kernels, while silencing WFhb1-1 in Qfhb1-carrier wheat resulted in a significant increase (p < 0.01) in FHB severity. Therefore, WFhb1-1 is an important FHB resistance gene with a potential antifungal function and probably a key functional component of Qfhb1 in wheat. A model regarding how WFhb1-1 functions in FHB resistance/susceptibility is hypothesized and discussed.

A QTL hot spot region on chromosome 1B for nine important traits under terminal drought stress conditions in wheat

Drought tolerance is a polygenic trait and is considered as one of the most important limiting factors to productivity of wheat and other crops around the world. Identifying drought-responsive genes using quantitative trait loci (QTL) and association analysis is one of the ways of developing drought tolerance cultivars. In order to detect QTLs for terminal drought tolerance in wheat, QTL analyses were conducted using an F12 recombinant inbred line population. A total of 53 main effects QTLs on 15 different chromosomes and 12 QTL by QTL (QQ) interactions on 13 different chromosomes were detected for yield, yield components and some agronomic traits using composite interval mapping and mixed-model based composite interval mapping analysis. The most significant QTL for grain yield was QYld.1A1 on 1A1, explaining 19.7% of the phenotypic variance under terminal drought stress. In addition, a QTL hot-spot region including important QTLs for grain yield, biological yield, grain number per spike, thousand grain weight, spike length, spike weight, stem weight and plant height was identified in the same region on chromosome 1B and clustered within the marker interval between wpt-3465 and wpt-2019. The DArT marker Wpt-5801 at the position of 67.7 cM showed linkage with all traits using single marker regression analysis. The BLAST search of markers sequences on the wheat genome identified 390 gene stable identifiers. Gene ontology analysis showed that the most dominant terms were ‘binding’ and ‘single-organism catabolic process’ for molecular function and biological process categories, respectively. This QTL hot-spot region with nine important QTLs could be used to improve drought tolerance after validation.