Minor Quantitative Trait Loci Research Articles

Research advances on the hard seededness trait of soybean and the underlying regulatory mechanisms.

Soybean is one of the world's most economically significant crops and is widely utilized as an essential source of vegetable protein and edible oil. Cultivated soybean is domesticated from its annual counterpart, wild soybean, which is considered valuable germplasm for soybean breeding. However, wild soybean accessions generally produce seeds with impermeable coats, a trait known as hard seededness (HS), which is beneficial for long-term seed survival but is undesirable for the uniform water absorption and germination of seeds, thus limiting the utilization of wild soybeans in breeding. In addition, moderate HS can isolate the embryo from the surrounding environment and is thus beneficial for long-term seed storage and germplasm preservation. The HS trait is primarily associated with the structure and chemical composition of the seed coat. Moreover, its development is also influenced by various environmental conditions, such as water and temperature. Genetic analysis has revealed that HS of soybean is a complex quantitative trait controlled by multiple genes or minor quantitative trait loci (QTL), with many QTLs and several causal genes currently identified. Investigating the physiological and molecular mechanisms underlying this trait is crucial for soybean breeding, production, and food processing. For this article, the literature was reviewed and condensed to create a well-rounded picture of the current understanding of internal and external factors, QTLs, causal genes, and the regulatory mechanisms related to the HS of soybean, with the aim of providing reference for future research and utilization of this trait.

Diversity in bread and durum wheat stigma morphology and linkage of increased stigma length to dwarfing gene Rht14

Key messageThe dwarfing allele Rht14 of durum wheat associates with greater stigma length, an important trait for hybrid breeding, whilst major dwarfing alleles Rht-B1b and Rht-D1b showed little to no effect.Although much understudied in wheat, the stigma is a crucial component for attaining grain set, the fundamental basis for yield, particularly in hybrid production systems where successful grain set relies on wind-driven pollen dispersal by the male parent and effective pollen capture by the female parent. Females with long stigma that exsert early are thought to be advantageous. Using glasshouse-grown lines, we examined variation in Total Stigma Length (TSL) across diverse panels comprising 27 durum and 116 bread wheat genotypes. Contrasting genotypes were selected for population development and genetic analysis. Quantitative trait loci (QTL) analysis was performed on a durum F2 population and a bread wheat recombinant inbred line (RIL) population. Contrasting with studies of anther length, we found no large effect on TSL of the GA-insensitive semi-dwarfing genes Rht-B1 and Rht-D1 in either durum or bread wheat. However, in durum cultivar Italo, we identified a region on chromosome 6A which is robustly associated with larger TSL and contains the Rht14 allele for reduced plant height, a trait that is favourable for female line development in hybrid systems. This dual effect locus explained 25.2 and 19.2% of TSL phenotypic variation in experiments across two growing seasons, with preliminary results suggesting this locus may increase TSL when transferred to bread wheat. In a bread wheat, RIL population minor QTL on 1A and 2A was indicated, but the strongest association was with Ppd-B1. Methods developed here, and the identification of a TSL-enhancing locus provides advances and further opportunities in the study of wheat stigma.

Mapping and validation of Fusarium wilt race 2 resistance QTL from Citrullus amarus line USVL246-FR2

Key messageFon race 2 resistant QTLs were identified on chromosomes 8 and 9. Families homozygous for resistance alleles at a haplotype of three KASP markers had 42% lower disease severity than those with susceptible alleles in an independent, interspecific validation population confirming their utility for introgression of Fusarium wilt resistance.Fusarium oxysporum f. sp. niveum (Fon) race 2 causes Fusarium wilt in watermelon and threatens watermelon production worldwide. Chemical management options are not effective, and no resistant edible watermelon cultivars have been released. Implementation of marker-assisted selection to develop resistant cultivars requires identifying sources of resistance and the underlying quantitative trait loci (QTL), developing molecular markers associated with the QTL, and validating marker-phenotype associations with an independent population. An intraspecific Citrullus amarus recombinant inbred line population from a cross of resistant USVL246-FR2 and susceptible USVL114 was used for mapping Fon race 2 resistance QTL. KASP markers were developed (N = 51) for the major QTL on chromosome 9 and minor QTL on chromosomes 1, 6, and 8. An interspecific F2:3 population was developed from resistance donor USVL246-FR2 (C. amarus) and a susceptible cultivar ‘Sugar Baby’ (Citrullus lanatus) to validate the utility of the markers for introgression of resistance from the wild crop relative into cultivated watermelon. Only 16 KASP markers segregated in the interspecific C. amarus/lanatus validation population. Four markers showed significant differences in the separation of genotypes based on family-mean disease severity, but together explained only 16% of the phenotypic variance. Genotypes that inherited homozygous resistant parental alleles at three KASP markers had 42% lower family-mean disease severity than homozygous susceptible genotypes. Thus, haplotype analysis was more effective at predicting the mean disease severity of families than single markers. The haplotype identified in this study will be valuable for developing Fon race 2 resistant watermelon cultivars.

A comparative study of 11 non-linear regression models highlighting autoencoder, DBN, and SVR, enhanced by SHAP importance analysis in soybean branching prediction.

To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifically emphasized the significance of Support Vector Regression (SVR) and SHapley Additive exPlanations (SHAP) in predicting soybean branching. By using branching data (phenotype) of 1918 soybean accessions and 42k SNP (Single Nucleotide Polymorphism) polymorphic data (genotype), this study systematically compared 11 non-linear regression AI models, including four deep learning models (DBN (deep belief network) regression, ANN (artificial neural network) regression, Autoencoders regression, and MLP (multilayer perceptron) regression) and seven machine learning models (e.g., SVR (support vector regression), XGBoost (eXtreme Gradient Boosting) regression, Random Forest regression, LightGBM regression, GPs (Gaussian processes) regression, Decision Tree regression, and Polynomial regression). After being evaluated by four valuation metrics: R2 (R-squared), MAE (Mean Absolute Error), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error), it was found that the SVR, Polynomial Regression, DBN, and Autoencoder outperformed other models and could obtain a better prediction accuracy when they were used for phenotype prediction. In the assessment of deep learning approaches, we exemplified the SVR model, conducting analyses on feature importance and gene ontology (GO) enrichment to provide comprehensive support. After comprehensively comparing four feature importance algorithms, no notable distinction was observed in the feature importance ranking scores across the four algorithms, namely Variable Ranking, Permutation, SHAP, and Correlation Matrix, but the SHAP value could provide rich information on genes with negative contributions, and SHAP importance was chosen for feature selection. The results of this study offer valuable insights into AI-mediated plant breeding, addressing challenges faced by traditional breeding programs. The method developed has broad applicability in phenotype prediction, minor QTL (quantitative trait loci) mining, and plant smart-breeding systems, contributing significantly to the advancement of AI-based breeding practices and transitioning from experience-based to data-based breeding.

Scald resistance in hybrid rye (Secale cereale): genomic prediction and GWAS.

Rye (Secale cereale L.) is an important cereal crop used for food, beverages, and feed, especially in North-Eastern Europe. While rye is generally more tolerant to biotic and abiotic stresses than other cereals, it still can be infected by several diseases, including scald caused by Rhynchosporium secalis. The aims of this study were to investigate the genetic architecture of scald resistance, to identify genetic markers associated with scald resistance, which could be used in breeding of hybrid rye and to develop a model for genomic prediction for scald resistance. Four datasets with records of scald resistance on a population of 251 hybrid winter rye lines grown in 2 years and at 3 locations were used for this study. Four genomic models were used to obtain variance components and heritabilities of scald resistance. All genomic models included additive genetic effects of the parental components of the hybrids and three of the models included additive-by-additive epistasis and/or dominance effects. All models showed moderate to high broad sense heritabilities in the range of 0.31 (SE 0.05) to 0.76 (0.02). The model without non-additive genetic effects and the model with dominance effects had moderate narrow sense heritabilities ranging from 0.24 (0.06) to 0.55 (0.08). None of the models detected significant non-additive genomic variances, likely due to a limited data size. A genome wide association study was conducted to identify markers associated with scald resistance in hybrid winter rye. In three datasets, the study identified a total of twelve markers as being significantly associated with scald resistance. Only one marker was associated with a major quantitative trait locus (QTL) influencing scald resistance. This marker explained 11-12% of the phenotypic variance in two locations. Evidence of genotype-by-environment interactions was found for scald resistance between one location and the other two locations, which suggested that scald resistance was influenced by different QTLs in different environments. Based on the results of the genomic prediction models and GWAS, scald resistance seems to be a quantitative trait controlled by many minor QTL and one major QTL, and to be influenced by genotype-by-environment interactions.

Fine mapping of the panicle length QTL qPL5 in rice

Panicle length is a crucial trait tightly associated with spikelets per panicle and grain yield in rice. To dissect the genetic basis of panicle length, a population of 161 recombinant inbred lines (RILs) was developed from the cross between an aus variety Chuan 7 (C7) and a tropical Geng variety Haoboka (HBK). C7 has a panicle length of 30 cm, 7 cm longer than that of HBK, and the panicle length was normally distributed in the RIL population. A total of six quantitative trait loci (QTLs) for panicle length were identified, and single QTLs explained the phenotypic variance from 4.9 to 18.1%. Among them, three QTLs were mapped to the regions harbored sd1, DLT, and Ehd1, respectively. To validate the genetic effect of a minor QTL qPL5, a near-isogenic F2 (NIF2) population segregated at qPL5 was developed. Interestingly, panicle length displayed bimodal distribution, and heading date also exhibited significant variation in the NIF2 population. qPL5 accounted for 66.5% of the panicle length variance. The C7 allele at qPL5 increased panicle length by 2.4 cm and promoted heading date by 5 days. Finally, qPL5 was narrowed down to an 80-kb region flanked by markers M2197 and M2205 using a large NIF2 population of 7600 plants. LOC_Os05g37540, encoding a phytochrome signal protein whose homolog in Arabidopsis enlarges panicle length, is regarded as the candidate gene because a single-nucleotide mutation (C1099T) caused a premature stop codon in HBK. The characterization of qPL5 with enlarging panicle length but promoting heading date makes its great value in breeding early mature varieties without yield penalty in rice.

Identification of QTLs for resistance to 10 pathotypes of Plasmodiophora brassicae in Brassica oleracea cultivar ECD11 through genotyping-by-sequencing

Key messageTwo major quantitative trait loci (QTLs) and five minor QTLs for 10 pathotypes were identified on chromosomes C01, C03, C04 and C08 through genotyping-by-sequencing from Brassica oleracea.Clubroot caused by Plasmodiophora brassicae is an important disease in brassica crops. Managing clubroot disease of canola on the Canadian prairie is challenging due to the continuous emergence of new pathotypes. Brassica oleracea is considered a major source of quantitative resistance to clubroot. Genotyping-by-sequencing (GBS) was performed in the parental lines; T010000DH3 (susceptible), ECD11 (resistant) and 124 BC1 plants. A total of 4769 high-quality polymorphic SNP loci were obtained and distributed on 9 chromosomes of B. oleracea. Evaluation of 124 BC1S1 lines for resistance to 10 pathotypes: 3A, 2B, 5C, 3D, 5G, 3H, 8J, 5K, 5L and 3O of P. brassicae, was carried out. Seven QTLs, 5 originating from ECD11 and 2 from T010000DH3, were detected. One major QTL designated as Rcr_C03-1 on C03 contributed 16.0–65.6% of phenotypic variation explained (PVE) for 8 pathotypes: 2B, 5C, 5G, 3H, 8J, 5K, 5L and 3O. Another major QTL designated as Rcr_C08-1 on C08 contributed 8.3 and 23.5% PVE for resistance to 8J and 5K, respectively. Five minor QTLs designated as Rcr_C01-1, Rcr_C03-2, Rcr_C03-3, Rcr_C04-1 and Rcr_C08-2 were detected on chromosomes C01, C03, C04 and C08 that contributed 8.3–23.5% PVE for 5 pathotypes each of 3A, 2B, 3D, 8J and 5K. There were 1, 10 and 4 genes encoding TIR-NBS-LRR/CC-NBS-LRR class disease resistance proteins in the Rcr_C01-1, Rcr_C03-1 and Rcr_C08-1 flanking regions. The syntenic regions of the two major QTLs Rcr_C03-1 and Rcr_C08-1 in the B. rapa genome ‘Chiifu’ were searched.

Identification of quantitative trait loci and associated candidate genes for pregnancy success in Angus–Brahman crossbred heifers

BackgroundIn beef cattle, more than 50% of the energy input to produce a unit of beef is consumed by the female that produced the calf. Development of genomic tools to identify females with high genetic merit for reproductive function could increase the profitability and sustainability of beef production.ResultsGenome-wide association studies (GWAS) were performed using a single-step genomic best linear unbiased prediction approach on pregnancy outcome traits from a population of Angus–Brahman crossbred heifers. Furthermore, a validation GWAS was performed using data from another farm. Heifers were genotyped with the Bovine GGP F250 array that contains 221,077 SNPs. In the discovery population, heifers were bred in winter breeding seasons involving a single round of timed artificial insemination (AI) followed by natural mating for 3 months. Two phenotypes were analyzed: pregnancy outcome to first-service AI (PAI; n = 1,481) and pregnancy status at the end of the breeding season (PEBS; n = 1,725). The heritability was estimated as 0.149 and 0.122 for PAI and PEBS, respectively. In the PAI model, one quantitative trait locus (QTL), located between 52.3 and 52.5 Mb on BTA7, explained about 3% of the genetic variation, in a region containing a cluster of γ-protocadherin genes and SLC25A2. Other QTLs explaining between 0.5% and 1% of the genetic variation were found on BTA12 and 25. In the PEBS model, a large QTL on BTA7 was synonymous with the QTL for PAI, with minor QTLs located on BTA5, 9, 10, 11, 19, and 20. The validation population for pregnancy status at the end of the breeding season were Angus–Brahman crossbred heifers bred by natural mating. In concordance with the discovery population, the large QTL on BTA7 and QTLs on BTA10 and 12 were identified.ConclusionsIn summary, QTLs and candidate SNPs identified were associated with pregnancy outcomes in beef heifers, including a large QTL associated with a group of protocadherin genes. Confirmation of these associations with larger populations could lead to the development of genomic predictions of reproductive function in beef cattle. Moreover, additional research is warranted to study the function of candidate genes associated with QTLs.

QTL analysis of traits related to seed size and shape in sesame (Sesamum indicum L.).

Seed size and shape are important traits that determine seed yield in sesame. Understanding the genetic basis of seed size and shape is essential for improving the yield of sesame. In this study, F2 and BC1 populations were developed by crossing the Yuzhi 4 and Bengal small-seed (BS) lines for detecting the quantitative trait loci (QTLs) of traits related to seed size and shape. A total of 52 QTLs, including 13 in F2 and 39 in BC1 populations, for seed length (SL), seed width (SW), and length to width ratio (L/W) were identified, explaining phenotypic variations from 3.68 to 21.64%. Of these QTLs, nine stable major QTLs were identified in the two populations. Notably, three major QTLs qSL-LG3-2, qSW-LG3-2, and qSW-LG3-F2 that accounted for 4.94-16.34% of the phenotypic variations were co-localized in a 2.08 Mb interval on chromosome 1 (chr1) with 279 candidate genes. Three stable major QTLs qSL-LG6-2, qLW-LG6, and qLW-LG6-F2 that explained 8.14-33.74% of the phenotypic variations were co-localized in a 3.27 Mb region on chr9 with 398 candidate genes. In addition, the stable major QTL qSL-LG5 was co-localized with minor QTLs qLW-LG5-3 and qSW-LG5 to a 1.82 Mb region on chr3 with 195 candidate genes. Gene annotation, orthologous gene analysis, and sequence analysis indicated that three genes are likely involved in sesame seed development. These results obtained herein provide valuable in-formation for functional gene cloning and improving the seed yield of sesame.

Quantitative Trait Locus Mapping by Whole Genome Re-Sequencing and Analysis of Candidate Genes for Heading Date in Rice

Heading date (HD) is a critical traits of rice that significantly affects yield and quality. Although researchers identified major-effect genes that involving in HD, they often have dramatic effects on HD and other vital agronomic traits, making them not easy to be applied in molecular breeding practices. To address this constraint, we focused on identifying genes with minor effects on HD that allow fine-tuning flowering time without significant yield loss. Previously, a 150-recombinant inbred lines (RILs) population was constructed from the early-heading date variety V20B and the lateheading variety CPSLO17, and the line RIL-111 showed the intermediate phenotype of heading date between V20B and CPSLO17. In our work, we applied bulked segregant analysis (BSA) with whole genome re-sequencing (WGS) to map quantitative trait locus (QTL) for heading date. In the results, a minor effect QTL, designated as qDTHR, was identified within the 647.1 kb on chromosome 1 of the F2 population, constructed from RIL-111 and V20B, associating with 14 non-synonymous mutant genes in the interval. The results provide a basis for molecular breeding to improve rice varieties, and lay a foundation for further cloning and functional analysis.

A Structure Variation in qPH8.2 Detrimentally Affects Plant Architecture and Yield in Rice.

Plant height is an important agronomic trait associated with plant architecture and grain yield in rice (Oryza sativa L.). In this study, we report the identification of quantitative trait loci (QTL) for plant height using a chromosomal segment substitution line (CSSL) population with substituted segments from japonica variety Nipponbare (NIP) in the background of the indica variety 9311. Eight stable QTLs for plant height were identified in three environments. Among them, six loci were co-localized with known genes such as semidwarf-1 (sd1) and Grain Number per Panicle1 (GNP1) involved in gibberellin biosynthesis. A minor QTL qPH8.2 on chromosome 8 was verified and fine-mapped to a 74 kb region. Sequence comparison of the genomic region revealed the presence/absence of a 42 kb insertion between NIP and 9311. This insertion occurred predominantly in temperate japonica rice. Comparisons on the near-isogenic lines showed that the qPH8.2 allele from NIP exhibits pleiotropic effects on plant growth, including reduced plant height, leaf length, photosynthetic capacity, delayed heading date, decreased yield, and increased tiller angle. These results indicate that qPH8.2 from temperate japonica triggers adverse effects on plant growth and yield when introduced into the indica rice, highlighting the importance of the inter-subspecies crossing breeding programs.

A meta-QTL analysis highlights genomic hotspots associated with phosphorus use efficiency in rice (Oryza sativa L.).

Phosphorus use efficiency (PUE) is a complex trait, governed by many minor quantitative trait loci (QTLs) with small effects. Advances in molecular marker technology have led to the identification of QTLs underlying PUE. However, their practical use in breeding programs remains challenging due to the unstable effects in different genetic backgrounds and environments, interaction with soil status, and linkage drag. Here, we compiled PUE QTL information from 16 independent studies. A total of 192 QTLs were subjected to meta-QTL (MQTL) analysis and were projected into a high-density SNP consensus map. A total of 60 MQTLs, with significantly reduced number of initial QTLs and confidence intervals (CI), were identified across the rice genome. Candidate gene (CG) mining was carried out for the 38 MQTLs supported by multiple QTLs from at least two independent studies. Genes related to amino and organic acid transport and auxin response were found to be abundant in the MQTLs linked to PUE. CGs were cross validated using a root transcriptome database (RiceXPro) and haplotype analysis. This led to the identification of the eight CGs (OsARF8, OsSPX-MFS3, OsRING141, OsMIOX, HsfC2b, OsFER2, OsWRKY64, and OsYUCCA11) modulating PUE. Potential donors for superior PUE CG haplotypes were identified through haplotype analysis. The distribution of superior haplotypes varied among subspecies being mostly found in indica but were largely scarce in japonica. Our study offers an insight on the complex genetic networks that modulate PUE in rice. The MQTLs, CGs, and superior CG haplotypes identified in our study are useful in the combination of beneficial alleles for PUE in rice.

Genetic dissection of popping quality traits in tropical popcorn (Zea mays L. var. everta)

Mapping quantitative trait loci (QTL) for popping-related traits viz., popping percentage (PP), popping expansion volume (PEV), flake volume (FV) and seed index (SI), is important in popcorn breeding. Therefore, 198 recombinant inbred lines (RILs) developed from a cross of popcorn and field corn lines were phenotyped for popping traits and genotyped using genotyping-by-sequencing (GBS). In the RILs, mean values for PP, FV, PEV and SI ranged from 15.7 to 95.4%, 14.0–484.4 cm, 1.6–21.4 cm and 9.0–28.6 g, respectively. The broad sense heritability (H2%) of the target traits ranged from 82.2 to 96.1% within and 58.9–71.0% between environments. The linkage map based on 6627 filtered single nucleotide polymorphism (SNP) was 2124.30 cM with an average markers interval of 0.33 cM. We mapped four major stable QTLs, one for each SI, PEV, PP and FV on chromosomes 3, 5, 6 and 9, and one minor stable QTL for FV on Chromosome 9 explaining 9.30–29.29% of the phenotypic variance. One major and two minor environment-specific QTLs were mapped on chromosomes 1 and 4 for PEV and SI. In addition, genes involved in kernel endosperm development and metabolic processes were identified and these all can be explored in popcorn improvement.

QTL Mapping and Transcriptome Analysis Reveal Candidate Genes Regulating Seed Color in Brassica napus.

Yellow seeds are desirable in rapeseed breeding because of their higher oil content and better nutritional quality than black seeds. However, the underlying genes and formation mechanism of yellow seeds remain unclear. Here, a novel yellow-seeded rapeseed line (Huangaizao, HAZ) was crossed with a black-seeded rapeseed line (Zhongshuang11, ZS11) to construct a mapping population of 196 F2 individuals, based on which, a high-density genetic linkage map was constructed. This map, comprising 4174 bin markers, was 1618.33 cM in length and had an average distance of 0.39 cM between its adjacent markers. To assess the seed color of the F2 population, three methods (imaging, spectrophotometry, and visual scoring) were used and a common major quantitative trait locus (QTL) on chromosome A09, explaining 10.91-21.83% of the phenotypic variance, was detected. Another minor QTL, accounting for 6.19-6.69% of the phenotypic variance, was detected on chromosome C03, only by means of imaging and spectrophotometry. Furthermore, a dynamic analysis of the differential expressions between the parental lines showed that flavonoid biosynthesis-related genes were down-regulated in the yellow seed coats at 25 and 35 days after flowering. A coexpression network between the differentially expressed genes identified 17 candidate genes for the QTL intervals, including a flavonoid structure gene, novel4557 (BnaC03.TT4), and two transcription factor genes, namely, BnaA09G0616800ZS (BnaA09.NFYA8) and BnaC03G0060200ZS (BnaC03.NAC083), that may regulate flavonoid biosynthesis. Our study lays a foundation for further identifying the genes responsible for and understanding the regulatory mechanism of yellow seed formation in Brassica napus.

Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize.

Maize productivity is significantly impacted by drought; therefore, improvement of drought tolerance is a critical goal in maize breeding. To achieve this, a better understanding of the genetic basis of drought tolerance is necessary. Our study aimed to identify genomic regions associated with drought tolerance-related traits by phenotyping a mapping population of recombinant inbred lines (RILs) for two seasons under well-watered (WW) and water-deficit (WD) conditions. We also used single nucleotide polymorphism (SNP) genotyping through genotyping-by-sequencing to map these regions and attempted to identify candidate genes responsible for the observed phenotypic variation. Phenotyping of the RILs population revealed significant variability in most of the traits, with normal frequency distributions, indicating their polygenic nature. We generated a linkage map using 1,241 polymorphic SNPs distributed over 10 chromosomes (chrs), covering a total genetic distance of 5,471.55cM. We identified 27 quantitative trait loci (QTLs) associated with various morphophysiological and yield-related traits, with 13 QTLs identified under WW conditions and 12 under WD conditions. We found one common major QTL (qCW2-1) for cob weight and a minor QTL (qCH1-1) for cob height that were consistently identified under both water regimes. We also detected one major and one minor QTL for the Normalized Difference Vegetation Index (NDVI) trait under WD conditions on chr 2, bin 2.10. Furthermore, we identified one major QTL (qCH1-2) and one minor QTL (qCH1-1) on chr 1 that were located at different genomic positions to those identified in earlier studies. We found co-localized QTLs for stomatal conductance and grain yield on chr 6 (qgs6-2 and qGY6-1), while co-localized QTLs for stomatal conductance and transpiration rate were identified on chr 7 (qgs7-1 and qTR7-1). We also attempted to identify the candidate genes responsible for the observed phenotypic variation; our analysis revealed that the major candidate genes associated with QTLs detected under water deficit conditions were related to growth and development, senescence, abscisic acid (ABA) signaling, signal transduction, and transporter activity in stress tolerance. The QTL regions identified in this study may be useful in designing markers that can be utilized in marker-assisted selection breeding. In addition, the putative candidate genes can be isolated and functionally characterized so that their role in imparting drought tolerance can be more fully understood.

Physiological and genetic analysis of a mapping population responsiveness to plant growth-promoting Azospirillum in wheat

Azospirillum brasilense is a plant growth-promoting rhizobacteria (PGPR) with the potential of being employed as an inoculant to decrease the use of chemical fertilizers. We investigated the ef fect of A. brasilense inoculation on a doubled haploid population derived from Opata / WSHD67.2(257) cross and detected Quantitative Trait Loci (QTL) for seven agronomic traits. The population was segregated, concerning their response to inoculation, into three subgroups: neutral, positive, and negative in a proportion of 60:25:15. A total of 18 major QTL and 83 minor QTL controlled the expression of measured traits. Nineteen QTL showed pleiotropic characteristics; chromosomes 5A, 7A, 7B, and 7D were distinguished as those with QTL controlling four of the seven phenotypes measured. The sequences of nearest markers to major QTL detected synteny to rice sequences that codified for at least 38 candidate genes described and discussed as a first step to understanding the interaction of wheat with A. brasilense.

Genome-Wide Association Analysis Identified Newly Natural Variation for Photosynthesis-Related Traits in a Large Maize Panel

High-yielding cultivars with high water use efficiency are a main target in maize breeding; yet, no comprehensive study about the genetic regulation of photosynthesis, or about the ranges of variability for gas exchange-related parameters in maize has been published. Here, a large maize panel of 731 inbred lines previously genotyped was evaluated to elucidate the genetic basis of photosynthesis-related parameters, measured 15–30 days after silking, across three years. Large phenotypic and genotypic variations were observed in this panel with dramatic fluctuations in heritability for various traits. We detected 27 minor Quantitative Trait Loci (QTL), comprising 39 significant trait-Single Nucleotide Polymorphisms (SNPs), located mostly on chromosomes 5 and 8. Most candidates genes were novel, though a few of them were functionally associated with the theory of source-to-sink translocation presented in previous studies. Genomic selection of favorable alleles to enhance photosynthesis, along with other tools, could be a practical, and a promising, approach in the future. Leaf net photosynthesis and stomatal conductance are the most promising targets for breeding programs. We did not find any marker associated with intrinsic water use efficiency, which highlights that developing maize cultivars with more efficient use of water by genomic selection is not straightforward; however, given the high heritability value for this trait, phenotypic selection could be implemented.

QUANTITATIVE GENETIC ANALYSIS OF PHENOLIC ACIDS IN OILSEED RAPE MEAL

Rapeseed meal, a by-product of oilseed extraction related to the agri-food and biofuel industries due to its favourable composition of essential amino acids, is currently utilised for animal feed. In this study, 166 doubled haploid (DH) rapeseed lines from the segregating Brassica napus doubled haploid population YE2-DH were genetically and chemically analysed for phenolic acids. The relationship between seed colour and phenolic acid fractions in B. napus was investigated using these analyses to improve the quality of rapeseed meal. High-performance liquid chromatography assays were used to estimate phenolic acid content, and the outcomes were used to identify quantitative trait loci (QTL). Nine quantitative feature loci for three distinct phenolic acid compounds were mapped to seven linkage groups. A minor QTL for sinapine was located on linkage group C05 in the same interval as the QTL for seed colour. On chromosome A09, two loci for phenolic acids colocalised with the main QTL for seed colour. Closely linked molecular markers for the target traits (seed colour, phenolic acids) identified during this study could be useful tools for breeding new oilseed rape cultivars with lower levels of antinutritive compounds.

Fine mapping and cloning of a novel BrSCC1 gene for seed coat color in Brassica rapa L.

A novel BrSCC1 gene for seed coat color was fine mapped within a 41.1-kb interval on chromosome A03 in Brassica rapa and functionally validated by ectopic expression analysis. Yellow seed is a valuable breeding trait that can be potentiality applied for improving seed quality and oil productivity in oilseed Brassica crops. However, only few genes for yellow seed have been identified in B. rapa. We previously identified a minor quantitative trait locus (QTL), qSC3.1, for seed coat color on chromosome A03 in B. rapa. In order to isolate the seed coat color gene, a brown-seeded chromosome segment substitution line, CSSL-38, harboring the qSC3.1, was selected and crossed with the yellow-seeded recurrent parent, a rapid cycling inbred line of B. rapa (RcBr), to construct the secondary F2 population. Metabolite identification suggested that seed coat coloration in CSSL-38 was independent of proanthocyanidins (PAs) accumulation. Genetic analysis revealed that yellow seed was controlled by a single recessive gene, Seed Coat Color 1 (BrSCC1). Utilizing bulked segregant analysis (BSA)-seq and secondary F2 and F2:3 recombinants analysis, BrSCC1 was fine mapped within a 41.1-kb interval. By integrating gene expression profiling, genome sequence comparison, metabolite analysis, and functional validation through ectopic expression in Arabidopsis, the BraA03g040800.3C gene was confirmed to be BrSCC1, which positively correlated with the seed coat coloration. Our study provides a novel gene resource for the genetic improvement of yellow seeds in oilseed B. rapa.

QTL analysis identified two major all-internodes solidness loci from a completely solid-stemmed spring wheat line.

The culms of solid-stemmed wheat cultivars are filled with "pith" - a parenchymatous tissue largely composed of soft, spongy, and compact parenchyma cells. Breeding solid-stemmed cultivars is the most effective way to decrease the detrimental impact of wheat stem sawfly (WSS), Cephus cinctus Norton (Hymenoptera: Cephidae) on wheat production. Althougha major solid stem gene has been previously identified from durum wheat, it produces an intermediate level of stem solidness in common wheat which is insufficient to provide the required level of WSS resistance. The maximum resistance is achieved when stems are totally filled with pith. Thus, to identify a secondary source of solidness in common wheat, we developed three mapping populations from wheat cvs. Sadash, 'AAC Innova' and 'AAC Cameron', each crossed separatelywith P2711, a completely solid-stemmed hexaploid wheat breeding line. All populations were genotyped using either wheat 15K or 90K Infinium iSelect SNP Assay and high-density linkage maps were generated from individual populations along with consensus maps for chromosomes 3B and 3D from all populations. 'Sadash/P2711' and 'AAC Innova/P2711' populations were subjected to extensive phenotyping in ≥3 environments followed by quantitative trait loci (QTL) analyses using population-specific and consensus linkage maps. We identified two major solid stem QTLs in the distal regions of chromosome arms 3BL and 3DL in both populations in addition to several population-specific or common minor QTLs. Internode-specific QTL analyses detected both major QTLs of chromosomes 3B and 3D across internodes, from top to bottom of the stalk, but minor QTLs were largely detected in upper or middle internodes. Our results suggest that both major QTLs are sufficient to develop highly solid-stemmed cvs; however, the minor loci, which additively enhance the pith expression, can be coupled with major genes to achieve a complete solid stem phenotype in common wheat. Comparative and haplotype analyses showed that the 3B locus is homoeologous to 3D, the former being mapped to a 1.1 Mb genomic region. Major QTLs identified in this study can be incorporated in modern wheat cultivars to achieve maximum WSS resistance from high pith expression.