Consistent Quantitative Trait Loci Research Articles

Genetic variability and QTL mapping of morphological traits and inflorescence prolificacy in African bermudagrass

AbstractAfrican bermudagrass (Cynodon transvaalensis Burtt‐Davy) (2n = 2x = 18) has unique morphological characteristics such as finer leaf blades and shorter internodes that are important to improving turf qualities (i.e., texture and density) as compared to other Cynodon species. It has been extensively used to cross with common bermudagrass (Cynodon dactylon Pers. var. dactylon) in developing high‐quality interspecific [C. dactylon (L.) Pers. × C. transvaalensis Burtt‐Davy] F1 hybrid cultivars for turf use. However, the molecular basis of its morphological variation is unknown. Accordingly, the objectives of this study were to estimate the heritability and identify quantitative trait loci (QTL) associated with morphological and reproductive traits. A first‐generation self‐pollinated (S1) population of 109 individuals was evaluated for plant height (PH), leaf blade width (LBW) and leaf blade length, stem internode diameter and length, and inflorescence prolificacy (IP) in a replicated field trial over three seasons (2018–2020). The broad‐sense heritability estimates ranged from 0.31 (PH) to 0.80 (IP). Twenty‐four QTL were identified and nine of them were consistent ones. Fifteen candidate genes were found at a major and consistent QTL region associated with LBW. Frequent QTL colocations were found among morphological traits and between morphological traits and IP, partially explaining the significant correlation. The findings provide critical information and resources toward understanding the genetic basis associated with morphological and reproductive traits within C. transvaalensis and could contribute to marker‐assisted selection for breeding new turf‐type bermudagrass cultivars.

Uncovering the Genomic Regions Associated with Yield Maintenance in Rice Under Drought Stress Using an Integrated Meta-Analysis Approach.

The complex trait of yield is controlled by several quantitative trait loci (QTLs). Given the global water deficit issue, the development of rice varieties suitable for non-flooded cultivation holds significant importance in breeding programs. The powerful approach of Meta-QTL (MQTL) analysis can be used for the genetic dissection of complicated quantitative traits. In the current study, a comprehensive MQTL analysis was conducted to identify consistent QTL regions associated with drought tolerance and yield-related traits under water deficit conditions in rice. In total, 1087 QTLs from 134 rice populations, published between 2000 to 2021, were utilized in the analysis. Distinct MQTL analysis of the relevant traits resulted in the identification of 213 stable MQTLs. The confidence interval (CI) for the detected MQTLs was between 0.12 and 19.7cM. The average CI of the identified MQTLs (4.68cM) was 2.74 times narrower compared to the average CI of the initial QTLs. Interestingly, 63 MQTLs coincided with SNP peak positions detected by genome-wide association studies for yield and drought tolerance-associated traits under water deficit conditions in rice. Considering the genes located both in the QTL-overview peaks and the SNP peak positions, 19 novel candidate genes were introduced, which are associated with drought response index, plant height, panicle number, biomass, and grain yield. Moreover, an inclusive MQTL analysis was performed on all the traits to obtain "Breeding MQTLs". This analysis resulted in the identification of 96 MQTLs with a CI ranging from 0.01 to 9.0cM. The mean CI of the obtained MQTLs (2.33cM) was 4.66 times less than the mean CI of the original QTLs. Thirteen MQTLs fulfilling the criteria of having more than 10 initial QTLs, CI < 1cM, and an average phenotypic variance explained greater than 10%, were designated as "Breeding MQTLs". These findings hold promise for assisting breeders in enhancing rice yield under drought stress conditions.

A Combination of Three Genomic Regions Conditions High Level of Adult Plant Stripe Rust Resistance in Australian Wheat Cultivar Sentinel.

A seedling susceptible Australian common wheat cultivar Sentinel showed resistance to stripe rust under field conditions. A Sentinel/Nyabing3 (Nyb3)-derived recombinant inbred line (RIL) population was phenotyped. A DArTseq marker-based linkage map of the Sentinel/Nyb3 RIL population was used to determine the chromosomal location of the adult plant stripe rust resistance possessed by Sentinel. Three consistent quantitative trait loci (QTL); QYr.sun-1BL, QYr.sun-2AS and QYr.sun-3BS were detected, and they on an average explained 18%, 15.6% and 10.6% of the variation in stripe rust response, respectively. All three QTL were contributed by Sentinel. QYr.sun-1B corresponded to the previously characterized gene Yr29. Sentinel expressed resistance at the four-leaf stage at 21 ± 2 °C in the greenhouse. Monogenic segregation among the RIL population was observed when screened at the four-leaf stage at 21 ± 2 °C in the greenhouse, and the underlying resistance locus was temporarily named YrSen. QYr.sun-3BS peaked on YrSen. QYr.sun-2AS was mendelized by generating and phenotyping a mongenically sgregating F6 RIL population, and it was temporarily designated YrSen2. RILs carrying Yr29, YrSen and YrSen2 in combination exhibited responses like the parent Sentinel. Based on a comparison of the genomic locations and resistance expression with stripe rust resistance genes previously located in their respective chromosomes, QYr.sun-2AS (YrSen2) and QYr.sun-3BS (YrSen) were concluded to represent new loci.

Genome-wide association analysis identifies a consistent QTL for powdery mildew resistance on chromosome 3A in Nordic and Baltic spring wheat

Key messageQPm.NOBAL-3A is an important QTL providing robust adult plant powdery mildew resistance in Nordic and Baltic spring wheat, aiding sustainable crop protection and breeding.Powdery mildew, caused by the biotrophic fungal pathogen Blumeria graminis f. sp. tritici, poses a significant threat to bread wheat (Triticum aestivum L.), one of the world’s most crucial cereal crops. Enhancing cultivar resistance against this devastating disease requires a comprehensive understanding of the genetic basis of powdery mildew resistance. In this study, we performed a genome-wide association study (GWAS) using extensive field trial data from multiple environments across Estonia, Latvia, Lithuania, and Norway. The study involved a diverse panel of recent wheat cultivars and breeding lines sourced from the Baltic region and Norway. We identified a major quantitative trait locus (QTL) on chromosome 3A, designated as QPm.NOBAL-3A, which consistently conferred high resistance to powdery mildew across various environments and countries. Furthermore, the consistency of the QTL haplotype effect was validated using an independent Norwegian spring wheat panel. Subsequent greenhouse seedling inoculations with 15 representative powdery mildew isolates on a subset of the GWAS panel indicated that this QTL provides adult plant resistance and is likely of race non-specific nature. Moreover, we developed and validated KASP markers for QPm.NOBAL-3A tailored for use in breeding. These findings provide a critical foundation for marker-assisted selection in breeding programs aimed at pyramiding resistance QTL/genes to achieve durable and broad-spectrum resistance against powdery mildew.

BSA-seq identified candidate genes and diagnostic KASP markers for anemone type flower in chrysanthemum

Chrysanthemum is one of the most leading commercial flower crops well-known for its flower shape diversity. Anemone type chrysanthemums receive increasing market attention that are distinguished by their pigmented and elongated disk florets. However, there are few reports on quantitative trait loci (QTL) mapping and the identification genes for anemone in chrysanthemum. In this study, bulked segregant analysis coupled with whole-genome sequencing (BSA-seq) approach was employed to detect candidate genomic regions controlling anemone type flower. Two mixed DNA pools composed of 28 anemone type and 20 non-anemone type F1 lines derived from a cross between ‘Nannong Xuefeng’ and ‘Monalisa’ together with two parents were used for high-throughput sequencing. A total of 42 consistent QTLs covering 30.00 Mb were simultaneously identified by |△(SNP/InDel-index)| and Euclidean distance (ED) algorithms based on 15,783,313 SNPs (single-nucleotide polymorphisms) and 1,546,200 small InDels (insertions and deletions). Twenty-two key candidate genes were screened out by a combination of gene functional annotation and transcriptome analysis, in which evm.model.scaffold_915.436 (CBF5), evm.model.scaffold_24.208 (U2AF65A), and a uncharacterized gene evm.model.scaffold_260.201 were highlighted by qRT-PCR. Furtherly, four associations were successfully converted to KASP (kompetitive allele specific PCR) markers, among them, the KASP markers developed for SNP locus Chr6__33961007 and Chr6__179207697 were proven to efficiently discriminate anemone and non-anemone type chrysanthemums being a couple of diagnostic markers in two populations. The results presented herein provide insights for further research on elucidating the formation mechanism of anemone type flower, and the anemone-specific KASP marker will be highly useful for applying MAS to accelerate breeding improvement of chrysanthemum.

Genetic mapping of dynamic control of leaf angle across multiple canopy levels in maize.

Optimizing leaf angle and other canopy architecture traits has helped modern maize (Zea mays L.) become adapted to higher planting densities over the last 60 years. Traditional investigations into genetic control of leaf angle have focused on one leaf or the average of multiple leaves; as a result, our understanding of genetic control across multiple canopy levels is still limited. To address this, genetic mapping across four canopy levels was conducted in the present study to investigate the genetic control of leaf angle across the canopy. We developed two populations of doubled haploid lines derived from three inbreds with distinct leaf angle phenotypes. These populations were genotyped with genotyping-by-sequencing and phenotyped for leaf angle at four different canopy levels over multiple years. To understand how leaf angle changes across the canopy, the four measurements were used to derive three additional traits. Composite interval mapping was conducted with the leaf-specific measurements and the derived traits. A set of 59 quantitative trait loci (QTLs) were uncovered for seven traits, and two genomic regions were consistently detected across multiple canopy levels. Additionally, seven genomic regions were found to contain consistent QTLs with either relatively stable or dynamic effects at different canopy levels. Prioritizing the selection of QTLs with dynamic effects across the canopy will aid breeders in selecting maize hybrids with the ideal canopy architecture that continues to maximize yield on a per area basis under increasing planting densities.

Genetic mapping of quantitative trait loci controlling smut resistance in Louisiana sugarcane using a bi-parental mapping population

Sugarcane smut, caused by Sporisorium scitamineum, is a major disease worldwide. Breeding resistant cultivars is the main management strategy. However, occasional failure to detect susceptible clones due to unfavorable environmental conditions, inconsistency in disease ratings between experiments, and continued clone losses due to pathogen adaptability are some of the challenges for this strategy. The development and use of molecular markers associated with smut resistance may overcome these limitations allowing more accurate identification of resistant parents and progeny. A genetic analysis was conducted using an inoculated population of 162 F1 progeny from a biparental cross between susceptible/female and resistant/male parents to identify quantitative trait loci (QTLs) associated with resistance. A total of 1574 single dose (SD) single-nucleotide polymorphisms (SNP) markers used to construct a genetic map resulted in 253 linkage groups (LGs) of which 150 LGs were assigned to the female parent and 204 LG to the male parent with a genome coverage of 24,580 cM. (Composite) interval mapping with selective sub-populations identified six consistent QTLs that cumulatively explained 25.74% of the phenotypic variance with LOD scores ranging from 3.17 to 23.7. Four out of 12 SNP markers closest to the QTL peaks had effect >10 for resistance in the heterozygous condition. Genes known to be involved in disease resistance, such as cellulose synthase, expansin, protein degradation, and receptor-kinase were linked to the genomic regions associated with smut resistance. The markers upon validation in different populations can be utilized for marker-assisted selection.

A consistent 100-seed weight QTL with pleiotropy for seed number/plant in soybean (Glycine max L.)

Seed weight and seed number/plant are important determinants of seed yield in soybean (Glycine max L.). A recombinant inbred line (RIL) population of cross EC538828 x JS97-52 was phenotyped for 100-seed weight (100-SW), seed number/plant (SNPP) and seed yield/plant (SYPP) for identifying quantitative trait loci (QTL) governing these traits. Linkage analysis using SSRs from reported QTL hotspots for 100-SW identified a consistent but pleiotropic QTL on chromosome 10. The QTL showed pleiotropy for SNPP with opposite phenotypic effect, while the pleotropic QTL doesn’t affect seed yield in consistent manner.

Genetic mapping of quantitative trait loci associated with drought tolerance in chickpea (Cicer arietinum L.)

Elucidation of the genetic basis of drought tolerance is vital for genomics-assisted breeding of drought tolerant crop varieties. Here, we used genotyping-by-sequencing (GBS) to identify single nucleotide polymorphisms (SNPs) in recombinant inbred lines (RILs) derived from a cross between a drought tolerant chickpea variety, Pusa 362 and a drought sensitive variety, SBD 377. The GBS identified a total of 35,502 SNPs and subsequent filtering of these resulted in 3237 high-quality SNPs included in the eight linkage groups. Fifty-one percent of these SNPs were located in the genic regions distributed throughout the genome. The high density linkage map has total map length of 1069 cm with an average marker interval of 0.33 cm. The linkage map was used to identify 9 robust and consistent QTLs for four drought related traits viz. membrane stability index, relative water content, seed weight and yield under drought, with percent variance explained within the range of 6.29%–90.68% and LOD scores of 2.64 to 6.38, which were located on five of the eight linkage groups. A genomic region on LG 7 harbors quantitative trait loci (QTLs) explaining > 90% phenotypic variance for membrane stability index, and > 10% PVE for yield. This study also provides the first report of major QTLs for physiological traits such as membrane stability index and relative water content for drought stress in chickpea. A total of 369 putative candidate genes were identified in the 6.6 Mb genomic region spanning these QTLs. In-silico expression profiling based on the available transcriptome data revealed that 326 of these genes were differentially expressed under drought stress. KEGG analysis resulted in reduction of candidate genes from 369 to 99, revealing enrichment in various signaling pathways. Haplotype analysis confirmed 5 QTLs among the initially identified 9 QTLs. Two QTLs, qRWC1.1 and qYLD7.1, were chosen based on high SNP density. Candidate gene-based analysis revealed distinct haplotypes in qYLD7.1 associated with significant phenotypic differences, potentially linked to pathways for secondary metabolite biosynthesis. These identified candidate genes bolster defenses through flavonoids and phenylalanine-derived compounds, aiding UV protection, pathogen resistance, and plant structure.The study provides novel genomic regions and candidate genes which can be utilized in genomics-assisted breeding of superior drought tolerant chickpea cultivars.

Advanced backcross QTL analysis and comparative mapping with RIL QTL studies and GWAS provide an overview of QTL and marker haplotype diversity for resistance to Aphanomyces root rot in pea (Pisum sativum).

Aphanomyces euteiches is the most damaging soilborne pea pathogen in France. Breeding of pea resistant varieties combining a diversity of quantitative trait loci (QTL) is a promising strategy considering previous research achievements in dissecting polygenic resistance to A. euteiches. The objective of this study was to provide an overview of the diversity of QTL and marker haplotypes for resistance to A. euteiches, by integrating a novel QTL mapping study in advanced backcross (AB) populations with previous QTL analyses and genome-wide association study (GWAS) using common markers. QTL analysis was performed in two AB populations derived from the cross between the susceptible spring pea variety "Eden" and the two new sources of partial resistance "E11" and "LISA". The two AB populations were genotyped using 993 and 478 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for resistance to A. euteiches in controlled conditions and in infested fields at two locations. GWAS and QTL mapping previously reported in the pea-Aphanomyces collection and from four recombinant inbred line (RIL) populations, respectively, were updated using a total of 1,850 additional markers, including the markers used in the Eden x E11 and Eden x LISA populations analysis. A total of 29 resistance-associated SNPs and 171 resistance QTL were identified by GWAS and RIL or AB QTL analyses, respectively, which highlighted 10 consistent genetic regions confirming the previously reported QTL. No new consistent resistance QTL was detected from both Eden x E11 and Eden x LISA AB populations. However, a high diversity of resistance haplotypes was identified at 11 linkage disequilibrium (LD) blocks underlying consistent genetic regions, especially in 14 new sources of resistance from the pea-Aphanomyces collection. An accumulation of favorable haplotypes at these 11 blocks was confirmed in the most resistant pea lines of the collection. This study provides new SNP markers and rare haplotypes associated with the diversity of Aphanomyces root rot resistance QTL investigated, which will be useful for QTL pyramiding strategies to increase resistance levels in future pea varieties.

Mapping QTL for Yield and Its Component Traits Using Wheat (Triticum aestivum L.) RIL Mapping Population from TAM 113 × Gallagher

Understanding genetic architectures of yield and yield-related traits of wheat (Triticum aestivum L.) grown under dryland or irrigated conditions is pivotal for developing modern high-yielding germplasm and cultivars. The objectives of this study were to detect quantitative trait loci (QTL) linked to yield and yield components using a mapping population derived from ‘TAM 113’/‘Gallagher’, including 191 recombinant inbred lines (RILs). The population was grown in McGregor, College Station, and Bushland, Texas, for three consecutive years from 2019 to 2021. A high-density genetic map covering all 21 chromosomes was constructed using a set of 8,075 single nucleotide polymorphisms (SNPs) obtained using genotyping-by-sequencing (GBS). A total of 147 QTLs for 16 yield-related traits were identified, which included 16 QTLs consistently detected in multiple experiments and 8 QTLs that showed pleiotropic effects. Of them, five pleiotropic QTLs overlapped with the consistent QTL. They increased grain yield (YLD) up to 37.64 g m−2, thousand kernel weight (TKW) up to 1.33 g, harvest (HI) up to 0.97%, kernel length up to 0.08 mm, and kernel width up to 0.04 mm with Gallagher alleles and increased YLD up to 22.21 g m−2, kernels spike−1 up to 1.77, TKW up to 1.14 g, and HI up to 3.72% with TAM 113 alleles. One major and consistent QTL on chromosome 2D at 34.4 Mbp overlapped with the major photoperiod gene Ppd-D1 and was affected by multiple traits, including kernel diameter (DIAM), TKW, kernel hardness index (KHI), heading date (HD), and plant height (PH). Another QTL cluster region on 7D between 52 and 66 Mbp, encompassing one consistent and three pleiotropic QTLs. One of the pleiotropic QTLs at 52 Mbp increased YLD up to 24.16 g m−2, HI up to 1%, and DIAM up to 0.03 mm. This study dissected genetic loci associated with yield and yield-related traits, providing valuable information on wheat improvement using marker-assisted selection (MAS).

Quantitative trait loci for rolled leaf in a wheat EMS mutant from Jagger.

Two QTLs with major effects on rolled leaf trait were consistently detected on chromosomes 1A (QRl.hwwg-1AS) and 5A (QRl.hwwg-5AL) in the field experiments. Rolled leaf (RL) is a morphological strategy to protect plants from dehydration under stressed field conditions. Identification of quantitative trait loci (QTLs) underlining RL is essential to breed drought-tolerant wheat cultivars. A mapping population of 154 recombinant inbred lines was developed from the cross between JagMut1095, a mutant of Jagger, and Jagger to identify quantitative trait loci (QTLs) for the RL trait. A linkage map of 3106cM was constructed with 1003 unique SNPs from 21 wheat chromosomes. Two consistent QTLs were identified for RL on chromosomes 1A (QRl.hwwg-1AS) and 5A (QRl.hwwg-5AL) in all field experiments. QRl.hwwg-1AS explained 24-56% of the phenotypic variation and QRl.hwwg-5AL explained up to 20% of the phenotypic variation. The combined percent phenotypic variation associated with the two QTLs was up to 61%. Analyses of phenotypic and genotypic data of recombinants generated from heterogeneous inbred families of JagMut1095 × Jagger delimited QRl.hwwg-1AS to a 6.04Mb physical interval. This work lays solid foundation for further fine mapping and map-based cloning of QRl.hwwg-1AS.

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection.

SLAF marker based QTL mapping of fruit-related traits reveals a major-effect candidate locus ff2.1 for flesh firmness in melon

Flesh firmness (FF) is an important and complex trait for melon breeders and consumers. However, the genetic mechanism underlying FF is unclear. Here, a soft fruit melon (P5) and a hard fruit melon (P10) were crossed to generate F2, and the FF and fruit-related traits were recorded for two years. By performing quantitative trait locus (QTL) specific-locus amplified fragment (SLAF) (QTL-SLAF) sequencing and molecular marker-linkage analysis, 112 844 SLAF markers were identified, and 5 919 SNPs were used to construct a genetic linkage map with a total genetic distance of 1 356.49 cM. Ten FF- and fruit-related QTLs were identified. Consistent QTLs were detected for fruit length (FL) and fruit diameter (FD) in both years, and QTLs for single fruit weight (SFW) were detected on two separate chromosomes in both years. For FF, the consistent major locus (ff2.1) was located in a 0.17-Mb candidate region on chromosome 2. Using 429 F2 individuals derived from a cross between P5 and P10, we refined the ff2.1 locus to a 28.3-kb region harboring three functional genes. These results provide not only a new candidate QTL for melon FF breeding but also a theoretical foundation for research on the mechanism underlying melon gene function.

Mapping of QTLs and Screening Candidate Genes Associated with the Ability of Sugarcane Tillering and Ratooning.

The processes of sugarcane tillering and ratooning, which directly affect the yield of plant cane and ratoon, are of vital importance to the population establishment and the effective stalk number per unit area. In the present study, the phenotypic data of 285 F1 progenies from a cross of sugarcane varieties YT93-159 × ROC22 were collected in eight environments, which consisted of plant cane and ratoon cultivated in three different ecological sites. The broad sense heritability (H2) of the tillering and the ratoon sprouting was 0.64 and 0.63, respectively, indicating that they were middle to middle-high heritable traits, and there is a significantly positive correlation between the two traits. Furthermore, a total of 26 quantitative trait loci (QTLs) related to the tillering ability and 11 QTLs associated with the ratooning ability were mapped on two high-quality genetic maps derived from a 100K SNP chip, and their phenotypic variance explained (PVE) ranged from 4.27-25.70% and 6.20-13.54%, respectively. Among them, four consistent QTLs of qPCTR-R9, qPCTR-Y28, qPCTR-Y60/qRSR-Y60 and PCTR-Y8-1/qRSR-Y8 were mapped in two environments, of which, qPCTR-Y8-1/qRSR-Y8 had the PVEs of 11.90% in the plant cane and 7.88% in the ratoon. Furthermore, a total of 25 candidate genes were identified in the interval of the above four consistent QTLs and four major QTLs of qPCTR-Y8-1, qPCTR-Y8-2, qRSR-R51 and qRSR-Y43-2, with the PVEs from 11.73-25.70%. All these genes were associated with tillering, including eight transcription factors (TFs), while 15 of them were associated with ratooning, of which there were five TFs. These QTLs and genes can provide a scientific reference for genetic improvement of tillering and ratooning traits in sugarcane.

Two QTLs govern the resistance to Sclerotinia minor in an interspecific peanut RIL population

AbstractSclerotinia blight is a soilborne disease caused by Sclerotinia minor Jagger and can produce severe decrease in yield. Cultural management strategies and chemical treatment are not completely effective; therefore, growing peanut‐resistant varieties is likely to be the most effective control method for this disease. Sclerotinia blight resistance has been identified in wild Arachis species and further transferred to peanut elite cultivars. To identify the genome regions conferring Sclerotinia blight resistance within a tetraploid genetic background, this study evaluated a population of recombinant inbred lines (RIL) with introgressed genes from three wild diploid species: A. cardenasii, A. correntina, and A. batizocoi. Two consistent quantitative trait loci (QTLs), qSbIA04 and qSbIB04 located on chromosomes A04 and B04, respectively, were identified. The QTL qSbIA04 was mapped at 56.39 cM explaining 29% of the phenotypic variance and qSbIB04 was mapped at 13.38 cM explaining 22% of the overall phenotypic variance.

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.

Identification of Genomic Regions Associated with High Grain Zn Content in Polished Rice Using Genotyping-by-Sequencing (GBS).

Globally, micronutrient (iron and zinc) enriched rice has been a sustainable and cost-effective solution to overcome malnutrition or hidden hunger. Understanding the genetic basis and identifying the genomic regions for grain zinc (Zn) across diverse genetic backgrounds is an important step to develop biofortified rice varieties. In this case, an RIL population (306 RILs) obtained from a cross between the high-yielding rice variety MTU1010 and the high-zinc rice variety Ranbir Basmati was utilized to pinpoint the genomic region(s) and QTL(s) responsible for grain zinc (Zn) content. A total of 2746 SNP markers spanning a genetic distance of 2445 cM were employed for quantitative trait loci (QTL) analysis, which resulted in the identification of 47 QTLs for mineral (Zn and Fe) and agronomic traits with 3.5-36.0% phenotypic variance explained (PVE) over the seasons. On Chr02, consistent QTLs for grain Zn polished (qZnPR.2.1) and Zn brown (qZnBR.2.2) were identified. On Chr09, two additional reliable QTLs for grain Zn brown (qZnBR.9.1 and qZnBR.9.2) were identified. The major-effect QTLs identified in this study were associated with few key genes related to Zn and Fe transporter activity. The genomic regions, candidate genes, and molecular markers associated with these major QTLs will be useful for genomic-assisted breeding for developing Zn-biofortified varieties.

QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster.

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.

Genome-wide association analysis identified consistent QTL for seed yield in a soybean diversity panel tested across multiple environments.

Improving seed yield is one of the main targets of soybean [Glycine max (L.) Merr.] breeding. Identification of loci that influence productivity and understanding their genetic mechanism will help marker-assisted trait introgression. The present study evaluated a diverse panel of 541 soybean genotypes consisting of three maturity groups (MGs III-V) in four environments in Kansas, U.S. Data on seed yield, seed weight, shattering resistance, days to maturity, and plant height showed significant genotype, environmental, and genotype × environment interaction variations. Seed yield and shattering had moderate broad-sense heritability (<85%), while the rest of the traits showed high broad-sense heritability (>90%). The SoySNP50K iSelect BeadChip dataset was used to identify significantly associated loci via genome-wide association studies (GWAS). A total of 19 single-nucleotide polymorphisms (SNPs) were significantly associated with seed yield. Particularly, two stable seed yield quantitative trait loci (QTL) on chromosomes 9 and 17 were consistently detected in at least three out of four environments. Candidate gene analysis surrounding seed yield QTL on chromosome 9 showed that Glyma.09G048900, an oxygen binding protein, was the closest to the QTL peak. Similarly, Glyma.17G090200 and Glyma.17G090400 were within 20-kb region of the seed yield QTL on chromosome 17. The candidate genes warrant further analysis to determine their functional mechanisms and develop markers for seed yield improvement.