Quantitative Trait Loci Markers Research Articles

Development of a QTL marker for quercetin glycoside content in onion

Development of a QTL marker for quercetin glycoside content in onion

Genotyping-by-sequencing targets genic regions and improves resolution of genome-wide association studies in autotetraploid potato

Key messageDe novo genotyping in potato using methylation-sensitive GBS discovers SNPs largely confined to genic or gene-associated regions and displays enhanced effectiveness in estimating LD decay rates, population structure and detecting GWAS associations over ‘fixed’ SNP genotyping platform. Study also reports the genetic architectures including robust sequence-tagged marker–trait associations for sixteen important potato traits potentially carrying higher transferability across a wider range of germplasm.This study deploys recent advancements in polyploid analytical approaches to perform complex trait analyses in cultivated tetraploid potato. The study employs a ‘fixed’ SNP Infinium array platform and a ‘flexible and open’ genome complexity reduction-based sequencing method (GBS, genotyping-by-sequencing) to perform genome-wide association studies (GWAS) for several key potato traits including the assessment of population structure and linkage disequilibrium (LD) in the studied population. GBS SNPs discovered here were largely confined (~ 90%) to genic or gene-associated regions of the genome demonstrating the utility of using a methylation-sensitive restriction enzyme (PstI) for library construction. As compared to Infinium array SNPs, GBS SNPs displayed enhanced effectiveness in estimating LD decay rates and discriminating population subgroups. GWAS using a combined set of 30,363 SNPs identified 189 unique QTL marker–trait associations (QTL-MTAs) covering all studied traits. The majority of the QTL-MTAs were from GBS SNPs potentially illustrating the effectiveness of marker-dense de novo genotyping platforms in overcoming ascertainment bias and providing a more accurate correction for different levels of relatedness in GWAS models. GWAS also detected QTL ‘hotspots’ for several traits at previously known as well as newly identified genomic locations. Due to the current study exploiting genome-wide genotyping and de novo SNP discovery simultaneously on a large tetraploid panel representing a greater diversity of the cultivated potato gene pool, the reported sequence-tagged MTAs are likely to have higher transferability across a wider range of potato germplasm and increased utility for expediting genomics-assisted breeding for the several complex traits studied.

Weighted single-step genome-wide association study to reveal new candidate genes for productive traits of Landrace pig in Korea.

The objective of this study was to identify genomic regions and candidate genes associated with productive traits using a total of 37,099 productive records and 6,683 single nucleotide polymorphism (SNP) data obtained from five Great-Grand-Parents (GGP) farms in Landrace. The estimated of heritabilities for days to 105 kg (AGE), average daily gain (ADG), backfat thickness (BF), and eye muscle area (EMA) were 0.49, 0.49, 0.56, and 0.23, respectively. We identified a genetic window that explained 2.05%-2.34% for each trait of the total genetic variance. We observed a clear partitioning of the four traits into two groups, and the most significant genomic region for AGE and ADG were located on the Sus scrofa chromosome (SSC) 1, while BF and EMA were located on SSC 2. We conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), which revealed results in three biological processes, four cellular component, three molecular function, and six KEGG pathway. Significant SNPs can be used as markers for quantitative trait loci (QTL) investigation and genomic selection (GS) for productive traits in Landrace pig.

Construction of a high-density genetic map and QTL localization of body weight and wool production related traits in Alpine Merino sheep based on WGR

BackgroundThe Alpine Merino is a new breed of fine-wool sheep adapted to the cold and arid climate of the plateau in the world. It has been popularized in Northwest China due to its superior adaptability as well as excellent production performance. Those traits related to body weight, wool yield, and wool fiber characteristics, which are economically essential traits in Alpine Merino sheep, are controlled by QTL (Quantitative Trait Loci). Therefore, the identification of QTL and genetic markers for these key economic traits is a critical step in establishing a MAS (Marker-Assisted Selection) breeding program.ResultsIn this study, we constructed the high-density genetic linkage map of Alpine Merino sheep by sequencing 110 F1 generation individuals using WGR (Whole Genome Resequencing) technology. 14,942 SNPs (Single Nucleotide Polymorphism) were identified and genotyped. The map spanned 2,697.86 cM, with an average genetic marker interval of 1.44 cM. A total of 1,871 high-quality SNP markers were distributed across 27 linkage groups, with an average of 69 markers per LG (Linkage Group). Among them, the smallest genetic distance is 19.62 cM for LG2, while the largest is 237.19 cM for LG19. The average genetic distance between markers in LGs ranged from 0.24 cM (LG2) to 3.57 cM (LG17). The marker density in the LGs ranged from LG14 (39 markers) to LG1 (150 markers).ConclusionsThe first genetic map of Alpine Merino sheep we constructed included 14,942 SNPs, while 46 QTLs associated with body weight, wool yield and wool fiber traits were identified, laying the foundation for genetic studies and molecular marker-assisted breeding. Notably, there were QTL intervals for overlapping traits on LG4 and LG8, providing potential opportunities for multi-trait co-breeding and further theoretical support for selection and breeding of ultra-fine and meaty Alpine Merino sheep.

Identification and validation of two major QTL for grain number per spike on chromosomes 2B and 2D in bread wheat (Triticum aestivum L.).

Major QTL for grain number per spike were identified on chromosomes 2B and 2D. Haplotypes and candidate genes of QGns.cib-2B.1 were analyzed. Grain number per spike (GNS) is one of the main components of wheat yield. Genetic dissection of their regulatory factors is essential to improve the yield potential. In present study, a recombinant inbred line population comprising 180 lines developed from the cross between a high GNS line W7268 and a cultivar Chuanyu12 was employed to identify quantitative trait loci (QTL) associated with GNS across six environments. Two major QTL, QGns.cib-2B.1 and QGns.cib-2D.1, were detected in at least four environments with the phenotypic variations of 12.99-27.07% and 8.50-13.79%, respectively. And significant interactions were observed between the two major QTL. In addition, QGns.cib-2B.1 is a QTL cluster for GNS, grain number per spikelet and fertile tiller number, and they were validated in different genetic backgrounds using Kompetitive Allele Specific PCR (KASP) markers. QGns.cib-2B.1 showed pleotropic effects on other yield-related traits including plant height, spike length, and spikelet number per spike, but did not significantly affect thousand grain weight which suggested that it might be potentially applicable in breeding program. Comparison analysis suggested that QGns.cib-2B.1 might be a novel QTL. Furthermore, haplotype analysis of QGns.cib-2B.1 indicated that it is a hot spot of artificial selection during wheat improvement. Based on the expression patterns, gene annotation, orthologs analysis and sequence variations, the candidate genes of QGns.cib-2B.1 were predicted. Collectively, the major QTL and KASP markers reported here provided a wealth of information for the genetic basis of GNS and grain yield improvement.

Identification of a pleiotropic QTL and development KASP markers for HPW, HSW, and SP in peanut

High yield has always been the primary objective of peanut breeding. 100-pod weight (HPW), 100-seed weight (HSW), and shelling percentage (SP), are crucial components of peanut yield. This study aimed to construct a high-density linkage map by resequencing the recombined inbred lines (RILs) derived from a cross between “Silihong” (A. hypogaea var. fastigiate) and “Jinonghei 3” (A. hypogaea var. hypogaea). The map consisted of 4,499 bins spread across 20 chromosomes, totaling 1712.32 cM in length with an average inter-marker distance of 0.38 cM. A total of 46 quantitative trait loci (QTLs) were identified across three environments. The major QTLs, including qHPW5.2, qHPW18.1, qSP7.1, qSP8.1, qSP8.2, qSP18.1, and qSP18.2, exhibited PVE (phenotypic variation explained) of 12.04, 11.41, 16.53, 24.17, 10.49, 10.82, and 29.89%, respectively. Fourteen QTLs identified across multiple environments were considered stable. One QTL (qHPW7, qHSW7.1, qSP7) was associated with all three traits, with the PVE value of 8.91, 9.04, and 16.53% for HPW, HSW, and SP, respectively. The genome-wide association study was conducted using the US mini-core collection to validate the accuracy of QTL mapping. Across two environments, 115 single-nucleotide polymorphisms (SNPs) were significantly associated with HPW, HSW, and SP in the association panel. Six SNPs were associated with two traits, explaining an average phenotypic variation of 13.84%. Combining the two mapping populations, AX-176802178, detected on chromosome 7 in the association panel, which controlled SP, was located within the QTL qSP7 confidence interval defined by the RILs. Moreover, three KASP markers were developed and validated in peanut landraces and varieties. These QTLs might offer valuable insights for understanding the genetic basis of HPW, HSW, and SP and provide useful molecular markers for marker-assisted breeding in peanuts.

Regulation of root growth and elongation in wheat.

Currently, the control of rhizosphere selection on farms has been applied to achieve enhancements in phenotype, extending from improvements in single root characteristics to the dynamic nature of entire crop systems. Several specific signals, regulatory elements, and mechanisms that regulate the initiation, morphogenesis, and growth of new lateral or adventitious root species have been identified, but much more work remains. Today, phenotyping technology drives the development of root traits. Available models for simulation can support all phenotyping decisions (root trait improvement). The detection and use of markers for quantitative trait loci (QTLs) are effective for enhancing selection efficiency and increasing reproductive genetic gains. Furthermore, QTLs may help wheat breeders select the appropriate roots for efficient nutrient acquisition. Single-nucleotide polymorphisms (SNPs) or alignment of sequences can only be helpful when they are associated with phenotypic variation for root development and elongation. Here, we focus on major root development processes and detail important new insights recently generated regarding the wheat genome. The first part of this review paper discusses the root morphology, apical meristem, transcriptional control, auxin distribution, phenotyping of the root system, and simulation models. In the second part, the molecular genetics of the wheat root system, SNPs, TFs, and QTLs related to root development as well as genome editing (GE) techniques for the improvement of root traits in wheat are discussed. Finally, we address the effect of omics strategies on root biomass production and summarize existing knowledge of the main molecular mechanisms involved in wheat root development and elongation.

Genome-Wide Association Study Reveals a QTL Region for Ashy Stem Blight Resistance in PRA154 Andean Common Bean.

Ashy stem blight (ASB) caused by Macrophomina phaseolina (Tassi) Goidanich affects the common bean (Phaseolus vulgaris L.) at all growing stages. Higher levels of resistance were observed in Andean common beans, but specific resistant quantitative trait loci (QTLs) conferring resistance to this pathogen have not been reported in this gene pool. The objectives of this research were to: (i) conduct a genome-wide association study (GWAS) and QTL mapping for resistance in the Andean breeding line PRA154; and (ii) identify single nucleotide polymorphism (SNP) markers and candidate genes for ASB resistance. Phenotyping was conducted under greenhouse conditions by inoculating the 107 F6:7 recombinant inbred lines (RILs) derived from the cross between the susceptible cultivar 'Verano' and the partial-resistant breeding line PRA154 twice with the M. phaseolina isolate PRI21. Genotyping was performed with 109,040 SNPs distributed across all 11 P. vulgaris chromosomes. A novel major QTL was located between 28,761,668 and 31,263,845 bp, extending 2.5 Mbp on chromosome Pv07, and the highest significant SNP markers were Chr07_28761668_A_G, Chr07_29131720_G_A, and Chr07_31263845_C_T with the highest LOD (more than 10 in most of the cases) and R-squared values, explaining 40% of the phenotypic variance of the PRI21 isolate. The gene Phvul.007G173900 (methylcrotonyl-CoA carboxylase alpha chain and mitochondrial 3-methylcrotonyl-CoA carboxylase 1 [MCCA]) with a size of 10,891 bp, located between 29,131,591 and 29,142,481 bp on Pv07, was identified as one candidate for ASB resistance in PRA154, and it contained Chr07_29131720_G_A. The QTL and genetic marker information could be used to assist common bean breeders to develop germplasm and cultivars with ASB resistance through molecular breeding.

Molecular Mapping of Putative Genomic Regions Controlling Fruit and Seed Morphology of Watermelon.

The genetic regulatory basis of qualitative and quantitative phenotypes of watermelon is being investigated in different types of molecular and genetic breeding studies around the world. In this study, biparental F2 mapping populations were developed over two experimental years, and the collected datasets of fruit and seed traits exhibited highly significant correlations. Whole-genome resequencing of comparative parental lines was performed and detected single nucleotide polymorphism (SNP) loci were converted into cleaved amplified polymorphic sequence (CAPS) markers. The screened polymorphic markers were genotyped in segregating populations and two genetic linkage maps were constructed, which covered a total of 2834.28 and 2721.45 centimorgan (cM) genetic lengths, respectively. A total of 22 quantitative trait loci (QTLs) for seven phenotypic traits were mapped; among them, five stable and major-effect QTLs (PC-8-1, SL-9-1, SWi-9-1, SSi-9-1, and SW-6-1) and four minor-effect QTLs (PC-2-1 and PC-2-2; PT-2-1 and PT-2-2; SL-6-1 and SSi-6-2; and SWi-6-1 and SWi-6-2) were observed with 3.77-38.98% PVE. The adjacent QTL markers showed a good fit marker-trait association, and a significant allele-specific contribution was also noticed for genetic inheritance of traits. Further, a total of four candidate genes (Cla97C09G179150, Cla97C09G179350, Cla97C09G180040, and Cla97C09G180100) were spotted in the stable colocalized QTLs of seed size linked traits (SL-9-1 and SWi-9-1) that showed non-synonymous type mutations. The gene expression trends indicated that the seed morphology had been formed in the early developmental stage and showed the genetic regulation of seed shape formation. Hence, we think that our identified QTLs and genes would provide powerful genetic insights for marker-assisted breeding aimed at improving the quality traits of watermelon.

Breeding design in wheat by combining the QTL information in a GWAS panel with a general genetic map and computer simulation

A large amount of genome-wide association study (GWAS) panels together with quantitative-trait locus (QTL) information associated with breeding-targeted traits have been described in wheat (Triticum aestivum L.). However, the application of mapping results from a GWAS panel to conventional wheat breeding remains a challenge. In this study, we first report a general genetic map which was constructed from 44 published linkage maps. It permits the estimation of genetic distances between any two genetic loci with physical map positions, thereby unifying the linkage relationships between QTL, genes, and genomic markers from multiple genetic populations. Second, we describe QTL mapping in a wheat GWAS panel of 688 accessions, identifying 77 QTL associated with 12 yield and grain-quality traits. Because these QTL have known physical map positions, they could be mapped onto the general map. Finally, we present a design approach to wheat breeding by using known QTL information and computer simulation. Potential crosses between parents in the GWAS panel may be evaluated by the relative frequency of the target genotype, trait correlations in simulated progeny populations, and genetic gain of selected progenies. It is possible to simultaneously improve yield and grain quality by suitable parental selection, progeny population size, and progeny selection scheme. Applying the design approach will allow identifying the most promising crosses and selection schemes in advance of the field experiment, increasing predictability and efficiency in wheat breeding.

Cytological and genetic effects of rye chromosomes 1RS and 3R on the wheat-breeding founder parent Chuanmai 42 from southwestern China.

The online version contains supplementary material available at 10.1007/s11032-023-01386-0.

Preselection of QTL markers enhances accuracy of genomic selection in Norway spruce

Genomic prediction (GP) or genomic selection is a method to predict the accumulative effect of all quantitative trait loci (QTLs) in a population by estimating the realized genomic relationships between the individuals and by capturing the linkage disequilibrium between markers and QTLs. Thus, marker preselection is considered a promising method to capture Mendelian segregation effects. Using QTLs detected in a genome-wide association study (GWAS) may improve GP. Here, we performed GWAS and GP in a population with 904 clones from 32 full-sib families using a newly developed 50 k SNP Norway spruce array. Through GWAS we identified 41 SNPs associated with budburst stage (BB) and the largest effect association explained 5.1% of the phenotypic variation (PVE). For the other five traits such as growth and wood quality traits, only 2 – 13 associations were observed and the PVE of the strongest effects ranged from 1.2% to 2.0%. GP using approximately 100 preselected SNPs, based on the smallest p-values from GWAS showed the greatest predictive ability (PA) for the trait BB. For the other traits, a preselection of 2000–4000 SNPs, was found to offer the best model fit according to the Akaike information criterion being minimized. But PA-magnitudes from GP using such selections were still similar to that of GP using all markers. Analyses on both real-life and simulated data also showed that the inclusion of a large QTL SNP in the model as a fixed effect could improve PA and accuracy of GP provided that the PVE of the QTL was ≥ 2.5%.

Identification of a stable major sucrose-related QTL and diagnostic marker for flavor improvement in peanut.

An InDel marker closely linked with a major and stable quantitative trait locus (QTL) on chromosome A08, qSUCA08.2, controlling sucrose content will benefit peanut flavor improvement. Sucrose is the main soluble sugar in mature peanut kernel, and its content is a key determinant of flavor. However, the genetic basis of sucrose content in peanut remains poorly understood, which limits the progress of flavor improvement. In the present study, two genomic regions (qSUCA08a and qSUCB06a) for sucrose content on chromosomes A08 and B06 were identified by QTL-seq in a RIL population derived from a cross between Zhonghua 10 and ICG 12625. In the interval of qSUCB06a, QTL qSUCB06.2 was detected through QTL mapping in a single environment. The qSUCA08a was further dissected into 3 adjacent genomic regions using linkage analysis including a major QTL qSUCA08.2 explaining 5.43-17.84% phenotypic variation across five environments. A 61-bp insertion at position 35,099,320 in the higher sucrose parent ICG 12625 was found in qSUCA08.2. An InDel marker SUC.InDel.A08 based on the insertion/deletion polymorphism was developed and validated within a natural population containing 172 peanut cultivars in two environments. The mean sucrose content of 93 cultivars with ICG 12625 allele was significantly higher than that of 79 cultivars with Zhonghua 10 allele. The qSUCA08.2 corresponding to a 2.11Mb interval harbored 110 genes. Among these genes, a total of 19 genes were considered as candidate genes including 5 non-synonymous mutation genes and 14 differentially expressed genes during seed development. These results provide new insights into the genetic basis of sucrose regulation in peanut and benefit the breeding program for developing new varieties with excellent flavor.

Genetics of destemming in pepper: A step towards mechanical harvesting.

Introduction: The majority of peppers in the US for fresh market and processing are handpicked, and harvesting can account for 20-50% of production costs. Innovation in mechanical harvesting would increase availability; lower the costs of local, healthy vegetable products; and perhaps improve food safety and expand markets. Most processed peppers require removal of pedicels (stem and calyx) from the fruit, but lack of an efficient mechanical process for this operation has hindered adoption of mechanical harvest. In this paper, we present characterization and advancements in breeding green chile peppers for mechanical harvesting. Specifically, we describe inheritance and expression of an easy-destemming trait derived from the landrace UCD-14 that facilitates machine harvest of green chiles. Methods: A torque gauge was used for measuring bending forces similar to those of a harvester and applied to two biparental populations segregating for destemming force and rate. Genotyping by sequencing was used to generate genetic maps for quantitative trait locus (QTL) analyses. Results: A major destemming QTL was found on chromosome 10 across populations and environments. Eight additional population and/or environment-specific QTL were also identified. Chromosome 10 QTL markers were used to help introgress the destemming trait into jalapeño-type peppers. Low destemming force lines combined with improvements in transplant production enabled mechanical harvest of destemmed fruit at a rate of 41% versus 2% with a commercial jalapeńo hybrid. Staining for the presence of lignin at the pedicel/fruit boundary indicated the presence of an abscission zone and homologs of genes known to affect organ abscission were found under several QTL, suggesting that the easy-destemming trait may be due to the presence and activation of a pedicel/fruit abscission zone. Conclusion: Presented here are tools to measure the easy-destemming trait, its physiological basis, possible molecular pathways, and expression of the trait in various genetic backgrounds. Mechanical harvest of destemmed mature green chile fruits was achieved by combining easy-destemming with transplant management.

QTL cluster analysis and marker development for kernel traits based on DArT markers in spring bread wheat (Triticum aestivum L.).

Genetic dissection of yield component traits including kernel characteristics is essential for the continuous improvement in wheat yield. In the present study, one recombinant inbred line (RIL) F6 population derived from a cross between Avocet and Chilero was used to evaluate the phenotypes of kernel traits of thousand-kernel weight (TKW), kernel length (KL), and kernel width (KW) in four environments at three experimental stations during the 2018-2020 wheat growing seasons. The high-density genetic linkage map was constructed with the diversity arrays technology (DArT) markers and the inclusive composite interval mapping (ICIM) method to identify the quantitative trait loci (QTLs) for TKW, KL, and KW. A total of 48 QTLs for three traits were identified in the RIL population on the 21 chromosomes besides 2A, 4D, and 5B, accounting for 3.00%-33.85% of the phenotypic variances. Based on the physical positions of each QTL, nine stable QTL clusters were identified in the RILs, and among these QTL clusters, TaTKW-1A was tightly linked to the DArT marker interval 3950546-1213099, explaining 10.31%-33.85% of the phenotypic variances. A total of 347 high-confidence genes were identified in a 34.74-Mb physical interval. TraesCS1A02G045300 and TraesCS1A02G058400 were among the putative candidate genes associated with kernel traits, and they were expressed during grain development. Moreover, we also developed high-throughput kompetitive allele-specific PCR (KASP) markers of TaTKW-1A, validated in a natural population of 114 wheat varieties. The study provides a basis for cloning the functional genes underlying the QTL for kernel traits and a practical and accurate marker for molecular breeding.

Primary mapping of quantitative trait loci regulating multivariate horticultural phenotypes of watermelon (Citrullus lanatus L.).

Watermelon fruits exhibit a remarkable diversity of important horticultural phenotypes. In this study, we initiated a primary quantitative trait loci (QTL) mapping to identify the candidate regions controlling the ovary, fruit, and seed phenotypes. Whole genome sequencing (WGS) was carried out for two differentiated watermelon lines, and 350 Mb (96%) and 354 Mb (97%) of re-sequenced reads covered the reference de novo genome assembly, individually. A total of 45.53% non-synonymous single nucleotide polymorphism (nsSNPs) and 54.47% synonymous SNPs (sSNPs) were spotted, which produced 210 sets of novel SNP-based cleaved amplified polymorphism sequence (CAPS) markers by depicting 46.25% co-dominant polymorphism among parent lines and offspring. A biparental F2:3 mapping population comprised of 100 families was used for trait phenotyping and CAPS genotyping, respectively. The constructed genetic map spanned a total of 2,398.40 centimorgans (cM) in length and averaged 11.42 cM, with 95.99% genome collinearity. A total of 33 QTLs were identified at different genetic positions across the eight chromosomes of watermelon (Chr-01, Chr-02, Chr-04, Chr-05, Chr-06, Chr-07, Chr-10, and Chr-11); among them, eight QTLs of the ovary, sixteen QTLs of the fruit, and nine QTLs of the seed related phenotypes were classified with 5.32-25.99% phenotypic variance explained (PVE). However, twenty-four QTLs were identified as major-effect and nine QTLs were mapped as minor-effect QTLs across the flanking regions of CAPS markers. Some QTLs were exhibited as tightly localized across the nearby genetic regions and explained the pleiotropic effects of multigenic nature. The flanking QTL markers also depicted significant allele specific contributions and accountable genes were predicted for respective traits. Gene Ontology (GO) functional enrichment was categorized in molecular function (MF), cellular components (CC), and biological process (BP); however, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were classified into three main classes of metabolism, genetic information processing, and brite hierarchies. The principal component analysis (PCA) of multivariate phenotypes widely demonstrated the major variability, consistent with the identified QTL regions. In short, we assumed that our identified QTL regions provide valuable genetic insights regarding the watermelon phenotypes and fine genetic mapping could be used to confirm them.

Mapping QTLs for Super-Earliness and Agro-Morphological Traits in RILs Population Derived from Interspecific Crosses between Pisum sativum × P. fulvum.

Earliness in crop plants has a vital role in prevention of heat-induced drought stress and in combating global warming, which is predicted to exacerbate in the near future. Furthermore, earliness may expand production into northern areas or higher altitudes, having relatively shorter growing season and may also expand arable lands to meet global food demands. The primary objective of the present study was to investigate quantitative trait loci (QTLs) for super-earliness and important agro-morphological traits in a recombinant inbred line (RIL) population derived from an interspecific cross. A population of 114 RILs developed through single-seed descent from an interspecific cross involving Pisum sativum L. and P. fulvum Sibth. et Sm. was evaluated to identify QTLs for super-earliness and important agro-morphological traits. A genetic map was constructed with 44 SSRs markers representing seven chromosomes with a total length of 262.6 cM. Of the 14 QTLs identified, two were for super-earliness on LG2, one for plant height on LG3, six for number of pods per plant on LG2, LG4, LG5 and LG6, one for number of seeds per pod on LG6, one for pod length on LG4 and three for harvest index on LG3, LG5, and LG6. AA205 and AA372-1 flanking markers for super-earliness QTLs were suggested for marker-assisted selection (MAS) in pea breeding programs due to high heritability of the trait. This is the first study to map QTLs originating from P. sativum and P. fulvum recently identified species with super-earliness character and the markers (AA205 and AA372-1) linked to QTLs were valuable molecular tools for pea breeding.

Construction of a genome-wide genetic linkage map and identification of quantitative trait loci for powdery mildew resistance in Gerbera daisy.

Powdery mildew (PM) is a common fungal disease in many important crops. The PM caused by Podosphaera xanthii has been the most challenging problem in commercial Gerbera (Gerbera hybrida) production globally, often leading to severe losses of crop yield and quality. A small number of PM-resistant breeding lines and cultivars have been reported in Gerbera, but the underlying genetics for PM resistance in Gerbera is largely unknown. Scarcity of genomic resources such as genetic linkage maps and molecular markers has severely hindered the effort to understand the genetic basis and locate loci controlling PM resistance in Gerbera. This study aimed to construct a genome-wide genetic linkage map, identify quantitative trait loci (QTL), and molecular markers for PM resistance in Gerbera. A segregating mapping population was developed by crossing PM-resistant and -susceptible Gerbera breeding lines, genotyped by sequencing, and phenotyped for PM resistance. A genome-wide genetic linkage map constructed with 791 single polymorphic site (SNP) markers spans 1912.30 cM across 27 linkage groups (LG) and reaches a density of 1 marker per 2.42 cM. One major consistent QTL was discovered in LG16, explaining more than 16.6% of the phenotypic variance for PM resistance. The QTL was tagged with two flanking SNP markers. The availability of this genetic linkage map will be very useful for locating and tagging QTLs for other important traits in Gerbera, and the newly discovered QTL and SNP markers will enable development of molecular markers for improving Gerbera for resistance to PM.

Genetic mapping and confirmation of the Rdm3 locus underlying resistance to southern stem canker in soybean

AbstractSouthern stem canker (SSC) in soybean [Glycine max (L.) Merrill], caused by the fungal pathogen Diaporthe aspalathi, is a major disease in the southern United States. It can cause up to 80% yield loss in severely infected fields. Plant introduction (PI) 398469, a Maturity Group VI soybean accession from South Korea, is one of six known sources of resistance to SSC. To determine the genetics of the resistance provided by PI 398469, F2:3 and F5‐derived recombinant inbred line (RIL) populations were developed from a cross with the susceptible breeding line G81‐2057. Both populations were phenotyped in the greenhouse using a modified toothpick method. The SSC‐resistant and susceptible DNA bulks consisting of 20 resistant and 18 susceptible families were created from the F2:3 population and genotyped using the Infinium SoySNP50K BeadChips for a bulked segregant analysis (BSA). Based on BSA results, 22 Kompetitive allele specific polymerase chain reaction (KASP) markers were designed to genotype the RIL population. Quantitative trait locus (QTL) analysis identified qRdm_14, on chromosome (Chr) 14 with an R2 of 62%. Linkage mapping in the F2:3 population confirmed the presence of a QTL on Chr 14. F5‐derived RILs derived from G81‐2057 × Crockett were phenotyped for SSC resistance and genotyped with the KASP markers to examine the relationship between Rdm3 from Crockett and qRdm_14 from PI 398469. Both PI 398469 and Crockett carried realleles at the Rdm3 locus for resistance to SSC. The QTL and KASP marker information could be used to screen breeding lines for resistance to SSC.

Identification of a QTL region for ashy stem blight resistance using genome-wide association and linage analysis in common bean recombinant inbred lines derived from BAT 477 and NY6020-4.

Ashy stem blight (ASB), caused by the fungus Macrophomina phaseolina (Tassi) Goidanich is an important disease of the common bean (Phaseolus vulgaris L.). It is important to identify quantitative trait loci (QTL) for ASB resistance and introgress into susceptible cultivars of the common bean. The objective of this research was to identify QTL and single nucleotide polymorphism (SNP) markers associated with ASB resistance in recombinant inbred lines (RIL) derived from a cross between BAT 477 and NY6020-4 common bean. One hundred and twenty-six F6:7 RIL were phenotyped for ASB in the greenhouse. Disease severity was scored on a scale of 1-9. Genotyping was performed using whole genome resequencing with 2x common bean genome size coverage, and over six million SNPs were obtained. After being filtered, 72,017 SNPs distributed on 11 chromosomes were used to conduct the genome-wide association study (GWAS) and QTL mapping. A novel QTL region of ~4.28 Mbp from 35,546,329 bp to 39,826,434 bp on chromosome Pv03 was identified for ASB resistance. The two SNPs, Chr03_39824257 and Chr03_39824268 located at 39,824,257 bp and 39,824,268 bp on Pv03, respectively, were identified as the strongest markers associated with ASB resistance. The gene Phvul.003G175900 (drought sensitive, WD repeat-containing protein 76) located at 39,822,021 - 39,824,655 bp on Pv03 was recognized as one candidate for ASB resistance in the RIL, and the gene contained the two SNP markers. QTL and SNP markers may be used to select plants and lines for ASB resistance through marker-assisted selection (MAS) in common bean breeding.