Discovery of genomic regions and candidate genes controlling shelling percentage using QTL‐seq approach in cultivated peanut (Arachis hypogaea L.)

Cultivated peanut (Arachis hypogaea L.) is an important grain legume providing high‐quality cooking oil, rich proteins and other nutrients. Shelling percentage (SP) is the 2nd most important agronomic trait after pod yield and this trait significantly affects the economic value of peanut in the market. Deployment of diagnostic markers through genomics‐assisted breeding (GAB) can accelerate the process of developing improved varieties with enhanced SP. In this context, we deployed the QTL‐seq approach to identify genomic regions and candidate genes controlling SP in a recombinant inbred line population (Yuanza 9102 × Xuzhou 68‐4). Four libraries (two parents and two extreme bulks) were constructed and sequenced, generating 456.89–790.32 million reads and achieving 91.85%–93.18% genome coverage and 14.04–21.37 mean read depth. Comprehensive analysis of two sets of data (Yuanza 9102/two bulks and Xuzhou 68‐4/two bulks) using the QTL‐seq pipeline resulted in discovery of two overlapped genomic regions (2.75 Mb on A09 and 1.1 Mb on B02). Nine candidate genes affected by 10 SNPs with non‐synonymous effects or in UTRs were identified in these regions for SP. Cost‐effective KASP (Kompetitive Allele‐Specific PCR) markers were developed for one SNP from A09 and three SNPs from B02 chromosome. Genotyping of the mapping population with these newly developed KASP markers confirmed the major control and stable expressions of these genomic regions across five environments. The identified candidate genomic regions and genes for SP further provide opportunity for gene cloning and deployment of diagnostic markers in molecular breeding for achieving high SP in improved varieties.     

QTL‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.)

Rust and late leaf spot (LLS) are the two major foliar fungal diseases in groundnut, and their co‐occurrence leads to significant yield loss in addition to the deterioration of fodder quality. To identify candidate genomic regions controlling resistance to rust and LLS, whole‐genome resequencing (WGRS)‐based approach referred as ‘QTL‐seq’ was deployed. A total of 231.67 Gb raw and 192.10 Gb of clean sequence data were generated through WGRS of resistant parent and the resistant and susceptible bulks for rust and LLS. Sequence analysis of bulks for rust and LLS with reference‐guided resistant parent assembly identified 3136 single‐nucleotide polymorphisms (SNPs) for rust and 66 SNPs for LLS with the read depth of ≥7 in the identified genomic region on pseudomolecule A03. Detailed analysis identified 30 nonsynonymous SNPs affecting 25 candidate genes for rust resistance, while 14 intronic and three synonymous SNPs affecting nine candidate genes for LLS resistance. Subsequently, allele‐specific diagnostic markers were identified for three SNPs for rust resistance and one SNP for LLS resistance. Genotyping of one RIL population (TAG 24 × GPBD 4) with these four diagnostic markers revealed higher phenotypic variation for these two diseases. These results suggest usefulness of QTL‐seq approach in precise and rapid identification of candidate genomic regions and development of diagnostic markers for breeding applications.     

Indel‐seq: a fast‐forward genetics approach for identification of trait‐associated putative candidate genomic regions and its application in pigeonpea (Cajanus cajan)

Identification of candidate genomic regions associated with target traits using conventional mapping methods is challenging and time‐consuming. In recent years, a number of single nucleotide polymorphism (SNP)‐based mapping approaches have been developed and used for identification of candidate/putative genomic regions. However, in the majority of these studies, insertion–deletion (Indel) were largely ignored. For efficient use of Indels in mapping target traits, we propose Indel‐seq approach, which is a combination of whole‐genome resequencing (WGRS) and bulked segregant analysis (BSA) and relies on the Indel frequencies in extreme bulks. Deployment of Indel‐seq approach for identification of candidate genomic regions associated with fusarium wilt (FW) and sterility mosaic disease (SMD) resistance in pigeonpea has identified 16 Indels affecting 26 putative candidate genes. Of these 26 affected putative candidate genes, 24 genes showed effect in the upstream/downstream of the genic region and two genes showed effect in the genes. Validation of these 16 candidate Indels in other FW‐ and SMD‐resistant and FW‐ and SMD‐susceptible genotypes revealed a significant association of five Indels (three for FW and two for SMD resistance). Comparative analysis of Indel‐seq with other genetic mapping approaches highlighted the importance of the approach in identification of significant genomic regions associated with target traits. Therefore, the Indel‐seq approach can be used for quick and precise identification of candidate genomic regions for any target traits in any crop species.     

QTL‐seq for rapid identification of candidate genes for 100‐seed weight and root/total plant dry weight ratio under rainfed conditions in chickpea

Terminal drought is a major constraint to chickpea productivity. Two component traits responsible for reduction in yield under drought stress include reduction in seeds size and root length/root density. QTL‐seq approach, therefore, was used to identify candidate genomic regions for 100‐seed weight (100SDW) and total dry root weight to total plant dry weight ratio (RTR) under rainfed conditions. Genomewide SNP profiling of extreme phenotypic bulks from the ICC 4958 × ICC 1882 population identified two significant genomic regions, one on CaLG01 (1.08 Mb) and another on CaLG04 (2.7 Mb) linkage groups for 100SDW. Similarly, one significant genomic region on CaLG04 (1.10 Mb) was identified for RTR. Comprehensive analysis revealed four and five putative candidate genes associated with 100SDW and RTR, respectively. Subsequently, two genes (Ca_04364 and Ca_04607) for 100SDW and one gene (Ca_04586) for RTR were validated using CAPS/dCAPS markers. Identified candidate genomic regions and genes may be useful for molecular breeding for chickpea improvement.     

Application of Genomic and Quantitative Genetic Tools to Identify Candidate Resistance Genes for Brown Rot Resistance in Peach

The availability of a complete peach genome assembly and three different peach genome sequences created by our group provide new opportunities for application of genomic data and can improve the power of the classical Quantitative Trait Loci (QTL) approaches to identify candidate genes for peach disease resistance. Brown rot caused by Monilinia spp., is the most important fungal disease of stone fruits worldwide. Improved levels of peach fruit rot resistance have been identified in some cultivars and advanced selections developed in the UC Davis and USDA breeding programs. Whole genome sequencing of the Pop-DF parents lead to discovery of high-quality SNP markers for QTL genome scanning in this experimental population. Pop-DF created by crossing a brown rot moderately resistant cultivar ‘Dr. Davis’ and a brown rot resistant introgression line, ‘F8,1–42’, derived from an initial almond × peach interspecific hybrid, was evaluated for brown rot resistance in fruit of harvest maturity over three seasons. Using the SNP linkage map of Pop-DF and phenotypic data collected with inoculated fruit, a genome scan for QTL identified several SNP markers associated with brown rot resistance. Two of these QTLs were placed on linkage group 1, covering a large (physical) region on chromosome 1. The genome scan for QTL and SNP effects predicted several candidate genes associated with disease resistance responses in other host-pathogen systems. Two potential candidate genes, ppa011763m and ppa026453m, may be the genes primarily responsible for M. fructicola recognition in peach, activating both PAMP-triggered immunity (PTI) and effector-triggered immunity (ETI) responses. Our results provide a foundation for further genetic dissection, marker assisted breeding for brown rot resistance, and development of peach cultivars resistant to brown rot.     

Uncovering QTL for resistance and survival time to Philasterides dicentrarchi in turbot (Scophthalmus maximus)

Disease resistance‐related traits have received increasing importance in aquaculture breeding programs worldwide. Currently, genomic information offers new possibilities in breeding to address the improvement of this kind of traits. The turbot is one of the most promising European aquaculture species, and Philasterides dicentrarchi is a scuticociliate parasite causing fatal disease in farmed turbot. An appealing approach to fight against disease is to achieve a more robust broodstock, which could prevent or diminish the devastating effects of scuticociliatosis on farmed individuals. In the present study, a genome scan for quantitative trait loci (QTL) affecting resistance and survival time to P. dicentrarchi in four turbot families was carried out. The objectives were to identify QTL using different statistical approaches [linear regression (LR) and maximum likelihood (ML)] and to locate significantly associated markers for their application in genetic breeding strategies. Several genomic regions controlling resistance and survival time to P. dicentrarchi were detected. When analyzing each family separately, significant QTL for resistance were identified by the LR method in two linkage groups (LG1 and LG9) and for survival time in LG1, while the ML methodology identified QTL for resistance in LG9 and LG23 and for survival time in LG6 and LG23. The analysis of the total data set identified an additional significant QTL for resistance and survival time in LG3 with the LR method. Significant association between disease resistance‐related traits and genotypes was detected for several markers, a single one explaining up to 22% of the phenotypic variance. Obtained results will be essential to identify candidate genes for resistance and to apply them in marker‐assisted selection programs to improve turbot production.     

QTL‐seq: rapid mapping of quantitative trait loci in rice by whole genome resequencing of DNA from two bulked populations

The majority of agronomically important crop traits are quantitative, meaning that they are controlled by multiple genes each with a small effect (quantitative trait loci, QTLs). Mapping and isolation of QTLs is important for efficient crop breeding by marker‐assisted selection (MAS) and for a better understanding of the molecular mechanisms underlying the traits. However, since it requires the development and selection of DNA markers for linkage analysis, QTL analysis has been time‐consuming and labor‐intensive. Here we report the rapid identification of plant QTLs by whole‐genome resequencing of DNAs from two populations each composed of 20–50 individuals showing extreme opposite trait values for a given phenotype in a segregating progeny. We propose to name this approach QTL‐seq as applied to plant species. We applied QTL‐seq to rice recombinant inbred lines and F₂ populations and successfully identified QTLs for important agronomic traits, such as partial resistance to the fungal rice blast disease and seedling vigor. Simulation study showed that QTL‐seq is able to detect QTLs over wide ranges of experimental variables, and the method can be generally applied in population genomics studies to rapidly identify genomic regions that underwent artificial or natural selective sweeps.     

QTL mapping for bacterial wilt resistance in peanut (<Emphasis Type="Italic">Arachis hypogaea</Emphasis> L.)

Bacterial wilt (BW) caused by Ralstonia solanacearum is a serious, global, disease of peanut (Arachis hypogaea L.), but it is especially destructive in China. Identification of DNA markers linked to the resistance to this disease will help peanut breeders efficiently develop resistant cultivars through molecular breeding. A F₂ population, from a cross between disease-resistant and disease-susceptible cultivars, was used to detect quantitative trait loci (QTL) associated with the resistance to this disease in the cultivated peanut. Genome-wide SNPs were identified from restriction-site-associated DNA sequencing tags using next-generation DNA sequencing technology. SNPs linked to disease resistance were determined in two bulks of 30 resistant and 30 susceptible plants along with two parental plants using bulk segregant analysis. Polymorphic SSR and SNP markers were utilized for construction of a linkage map and for performing the QTL analysis, and a moderately dense linkage map was constructed in the F₂ population. Two QTL (qBW-1 and qBW-2) detected for resistance to BW disease were located in the linkage groups LG1 and LG10 and account for 21 and 12 % of the bacterial wilt phenotypic variance. To confirm these QTL, the F₈ RIL population with 223 plants was utilized for genotyping and phenotyping plants by year and location as compared to the F₂ population. The QTL qBW-1 was consistent in the location of LG1 in the F₈ population though the QTL qBW-2 could not be clarified due to fewer markers used and mapped in LG10. The QTL qBW-1, including four linked SNP markers and one SSR marker within 14.4-cM interval in the F₈, was closely related to a disease resistance gene homolog and was considered as a candidate gene for resistance to BW. QTL identified in this study would be useful to conduct marker-assisted selection and may permit cloning of resistance genes. Our study shows that bulk segregant analysis of genome-wide SNPs is a useful approach to expedite the identification of genetic markers linked to disease resistance traits in the allotetraploidy species peanut.     

Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut

The subspecies fastigiata of cultivated groundnut lost fresh seed dormancy (FSD) during domestication and human‐made selection. Groundnut varieties lacking FSD experience precocious seed germination during harvest imposing severe losses. Development of easy‐to‐use genetic markers enables early‐generation selection in different molecular breeding approaches. In this context, one recombinant inbred lines (RIL) population (ICGV 00350 × ICGV 97045) segregating for FSD was used for deploying QTL‐seq approach for identification of key genomic regions and candidate genes. Whole‐genome sequencing (WGS) data (87.93 Gbp) were generated and analysed for the dormant parent (ICGV 97045) and two DNA pools (dormant and nondormant). After analysis of resequenced data from the pooled samples with dormant parent (reference genome), we calculated delta‐SNP index and identified a total of 10,759 genomewide high‐confidence SNPs. Two candidate genomic regions spanning 2.4 Mb and 0.74 Mb on the B05 and A09 pseudomolecules, respectively, were identified controlling FSD. Two candidate genes—RING‐H2 finger protein and zeaxanthin epoxidase—were identified in these two regions, which significantly express during seed development and control abscisic acid (ABA) accumulation. QTL‐seq study presented here laid out development of a marker, GMFSD1, which was validated on a diverse panel and could be used in molecular breeding to improve dormancy in groundnut.     

Identification of Quantitative Trait Loci Associated with Resistance to Viral Haemorrhagic Septicaemia (VHS) in Turbot (Scophthalmus maximus): A Comparison Between Bacterium,Parasite and Virus Diseases

One of the main objectives of genetic breeding programs in turbot industry is to reduce disease-related mortality. In the present study, a genome scan to detect quantitative trait loci (QTL) affecting resistance and survival to viral haemorrhagic septicaemia (VHS) was carried out. Three full-sib families with approximately 90 individuals each were genotyped and evaluated by linear regression and maximum likelihood approaches. In addition, a comparison between QTL detected for resistance and survival time to other important bacterial and parasite diseases affecting turbot (furunculosis and scuticociliatosis) was also carried out. Finally, the relationship between QTL affecting resistance/survival time to the virus and growth-related QTL was also evaluated. Several genomic regions controlling resistance and survival time to VHS were detected. Also significant associations between the evaluated traits and genotypes at particular markers were identified, explaining up to 14 % of the phenotypic variance. Several genomic regions controlling general and specific resistance to different diseases in turbot were detected. A preliminary gene mining approach identified candidate genes related to general or specific immunity. This information will be valuable to develop marker-assisted selection programs and to discover candidate genes related to disease resistance to improve turbot production.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

A large‐scale genomic association analysis identifies the candidate causal genes conferring stripe rust resistance under multiple field environments

The incorporation of resistance genes into wheat commercial varieties is the ideal strategy to combat stripe or yellow rust (YR). In a search for novel resistance genes, we performed a large‐scale genomic association analysis with high‐density 660K single nucleotide polymorphism (SNP) arrays to determine the genetic components of YR resistance in 411 spring wheat lines. Following quality control, 371 972 SNPs were screened, covering over 50% of the high‐confidence annotated gene space. Nineteen stable genomic regions harbouring 292 significant SNPs were associated with adult‐plant YR resistance across nine environments. Of these, 14 SNPs were localized in the proximity of known loci widely used in breeding. Obvious candidate SNP variants were identified in certain confidence intervals, such as the cloned gene Yr18 and the major locus on chromosome 2BL, despite a large extent of linkage disequilibrium. The number of causal SNP variants was refined using an independent validation panel and consideration of the estimated functional importance of each nucleotide polymorphism. Interestingly, four natural polymorphisms causing amino acid changes in the gene TraesCS2B01G513100 that encodes a serine/threonine protein kinase (STPK) were significantly involved in YR responses. Gene expression and mutation analysis confirmed that STPK played an important role in YR resistance. PCR markers were developed to identify the favourable TraesCS2B01G513100 haplotype for marker‐assisted breeding. These results demonstrate that high‐resolution SNP‐based GWAS enables the rapid identification of putative resistance genes and can be used to improve the efficiency of marker‐assisted selection in wheat disease resistance breeding.     

Transmission of important chromosomal regions under selection revealed in rice pedigree breeding programs

Genetic analysis across a whole plant genome based on pedigree information offers considerable potential for enhancing genetic gain from plant breeding programs through quantitative trait loci (QTL) mapping and marker-assisted selection. Here, we report its application for graphically genotyping varieties used in Chinese japonica rice (Oryza sativa L.) pedigree breeding programs. We identified 34 important chromosomal regions from the founder parent that are under selection in the breeding programs, and by comparing donor genomic regions that are under selection with QTL locations of agronomic traits, we found that QTL clustered in important genomic regions, in accordance with association analyses of natural populations and other previous studies. The convergence of genomic regions under selection with QTL locations suggests that donor genomic regions harboring key genes/QTL for important agronomic traits have been selected by plant breeders since the 1950s from the founder rice plants. The results provide better understanding of the effects of selection in breeding programs on the traits of rice cultivars. They also provide potentially valuable information for enhancing rice breeding programs through screening candidate parents for targeted molecular markers, improving crop yield potential and identifying suitable genetic material for use in future breeding programs.     

DNA marker analysis for pyramided of Fusarium head blight (FHB) resistance QTLs from different germplasm

A pyramided FHB resistance line of wheat (WSY) was previously developed from three FHB resistant cultivars (Sumai 3, Wangshuibai, and Nobeokabouzu) in the Jiangsu Academy of Agricultural Sciences, China. In the present study, we analyzed the genetic relationship between WSY and the three parental cultivars using DNA markers in order to clarify how many and which resistance genes had accumulated in WSY. We analyzed 282 DNA markers from the 21 wheat chromosomes. WSY was found to include different chromosome regions that harbored putative FHB QTLs of the three parental germplasm. Haplotypes of DNA markers on these QTL regions revealed that the 1BL, 2BL, 5AS, and 7AL QTL regions were from Sumai 3, the 2AS, 2DS, 3AS, and 6BS QTL regions were from Wangshuibai, and the 3BS QTL region was from Nobeokabouzu. This study showed that different resistance genes from the different resistant germplasm had indeed accumulated in WSY. WSY is a potential resistant resource for FHB resistance in wheat breeding programs.     

Fine mapping and development of DNA markers for the <Emphasis Type="Italic">qPDH1</Emphasis> locus associated with pod dehiscence in soybean

Pod dehiscence (shattering) is a major cause of yield loss in mechanical harvesting of soybeans. To develop useful selection markers, we conducted a high-resolution mapping of a major quantitative trait locus (QTL) controlling pod dehiscence, designated as qPDH1. The progeny of a residual heterozygous line, which was a recombinant inbred line segregating only for the genomic region around qPDH1, was screened for flanking markers to obtain various recombinants in the vicinity of the QTL. Analysis of the relationship between degree of pod dehiscence and graphical genotype of these lines confined the location of qPDH1 to a 134-kb region on chromosome 16 (formerly linkage group J), where ten putative genes were predicted to be present. None of these genes showed significant sequence homology with the Arabidopsis genes that have previously been reported to be associated with pod dehiscence, suggesting the presence of a novel gene and mechanism underlying pod dehiscence in soybean. Sequencing analysis of the parental shattering-resistant and -susceptible cultivars for the candidate genes revealed a high-frequency nucleotide polymorphism in this genomic region between the cultivars. Three markers were developed using insertion/deletion variations in the region. Polymorphism at these marker loci was basically conserved between diverse shattering-resistant and -susceptible cultivars/lines, suggesting the versatility and usefulness of these markers for marker-assisted selection.     

Identification of quantitative trait loci linked to Ceratocystis wilt resistance in cacao

Ceratocystis wilt (CW) in cacao (Theobroma cacao L.), caused by Ceratocystis cacaofunesta, is a drastic disease that results in plant death. The pathogen was recently identified in the major cacao-producing region of Brazil?CBahia. The identification of genetic markers tightly linked to disease resistance loci is a valuable tool for the development of resistant cultivars using marker-assisted selection (MAS). Branches of 143 six-year-old individuals of an F2 Sca 6?×?ICS 1 population were wounded by making a 3-mm deep cut with a sterile scalpel, and inoculated with a 20-??l drop of a spore suspension of 3?×?10⁴?CFU/ml. The inoculation method used allowed the population to be quantitatively phenotyped. The length of the xylem discoloration followed a continuous distribution. These results imply that the resistance was quantitatively inherited. Quantitative trait loci (QTL) analysis revealed two genomic regions (in linkage groups 3 and 9) associated with CW resistance. The QTL explained individually from 6.9 to 8.6?% of the phenotypic variation. The QTL identified are crucial for identifying genes for resistance and can be applied in the genetic breeding of cacao using MAS.     

Exploring the quantitative resistance to <Emphasis Type="Italic">Pseudomonas syringae</Emphasis> pv. <Emphasis Type="Italic">phaseolicola</Emphasis> in common bean (<Emphasis Type="Italic">Phaseolus vulgaris</Emphasis> L.)

Pseudomonas syringae pv. phaseolicola is an important disease that causes halo blight in common bean. The genetic mechanisms underlying quantitative halo blight resistance are poorly understood in this species, as most disease studies have focused on qualitative resistance. The present work examines the genetic basis of quantitative resistance to the nine halo blight races in different organs (primary and trifoliate leaf, stem and pod) of an Andean recombinant inbred line (RIL) progeny. Using a multi-environment quantitative trait locus (QTL) mapping approach, 76 and 101 main-effect and epistatic QTLs were identified, respectively. Most of the epistatic interactions detected were due to loci without detectable QTL additive main effects. Main and epistatic QTLs detected were mainly consistent across the environment conditions. The homologous genomic regions corresponding to 26 of the 76 main-effect detected QTLs were positive for the presence of resistance-associated gene cluster encoding nucleotide-binding and leucine-rich repeat (NL) proteins and known defence genes. Main-effect QTLs for resistance to races 3, 4 and 5 in leaf, stem and pod were located on chromosome 2 within a 3.01-Mb region, where a cluster of nine NL genes was detected. The NL gene Phvul.002G323300 is located in this region, which can be considered an important putative candidate gene for the non-organ-specific QTL identified here. The present research provides essential information not only for the better understanding of the plant-pathogen interaction but also for the application of genomic assisted breeding for halo blight resistance in common bean.     

Genotyping‐by‐sequencing‐based genome‐wide association studies on Verticillium wilt resistance in autotetraploid alfalfa (Medicago sativa L.)

Verticillium wilt (VW) is a fungal disease that causes severe yield losses in alfalfa. The most effective method to control the disease is through the development and use of resistant varieties. The identification of marker loci linked to VW resistance can facilitate breeding for disease‐resistant alfalfa. In the present investigation, we applied an integrated framework of genome‐wide association with genotyping‐by‐sequencing (GBS) to identify VW resistance loci in a panel of elite alfalfa breeding lines. Phenotyping was performed by manual inoculation of the pathogen to healthy seedlings, and scoring for disease resistance was carried out according to the standard test of the North America Alfalfa Improvement Conference (NAAIC). Marker–trait association by linkage disequilibrium identified 10 single nucleotide polymorphism (SNP) markers significantly associated with VW resistance. Alignment of the SNP marker sequences to the M. truncatula genome revealed multiple quantitative trait loci (QTLs). Three, two, one and five markers were located on chromosomes 5, 6, 7 and 8, respectively. Resistance loci found on chromosomes 7 and 8 in the present study co‐localized with the QTLs reported previously. A pairwise alignment (blastn ) using the flanking sequences of the resistance loci against the M. truncatula genome identified potential candidate genes with putative disease resistance function. With further investigation, these markers may be implemented into breeding programmes using marker‐assisted selection, ultimately leading to improved VW resistance in alfalfa.