Stable Quantitative Trait Loci Research Articles

Unveiling synergistic QTLs associated with slow wilting in soybean (Glycine max [L.] Merr.)

Key messageA stable QTL qSW_Gm10 works with a novel locus, qSW_Gm01, in a synergistic manner for controlling slow-wilting traits at the early vegetative stage under drought stress in soybean.Drought is one of the major environmental factors which limits soybean yield. Slow wilting is a promising trait that can enhance drought resilience in soybean without additional production costs. Recently, a Korean soybean cultivar SS2-2 was reported to exhibit slow wilting at the early vegetative stages. To find genetic loci responsible for slow wilting, in this study, quantitative trait loci (QTL) analysis was conducted using a recombinant inbred line (RIL) population derived from crossing between Taekwangkong (fast-wilting) and SS2-2 (slow-wilting). Wilting score and leaf moisture content were evaluated at the early vegetative stages for three years. Using the ICIM-MET module, a novel QTL on Chr01, qSW_Gm01 was identified, together with a previously known QTL, qSW_Gm10. These two QTLs were found to work synergistically for slow wilting of the RILs under the water-restricted condition. Furthermore, the SNP markers from the SoySNP50K dataset, located within these QTLs, were associated with the wilting phenotype in 30 diverse soybean accessions. Two genes encoding protein kinase 1b and multidrug resistance-associated protein 4 were proposed as candidate genes for qSW_Gm01 and qSW_Gm10, respectively, based on a comprehensive examination of sequence variation and gene expression differences in the parental lines under drought conditions. These genes may play a role in slow wilting by optimally regulating stomatal aperture. Our findings provide promising genetic resources for improving drought resilience in soybean and give valuable insights into the genetic mechanisms governing slow wilting.

Identification and validation of major and stable quantitative trait locus for falling number in common wheat (Triticum aestivum L.).

A major and stable QTL, QFn.sau-1B.2, which can explain 13.6% of the PVE in FN and has a positive effect on resistance in SGR, was mapped and validated. The falling number (FN) is considered one of the most important quality traits of wheat grain and is the most important quality evaluation index for wheat trade worldwide. The quantitative trait loci (QTLs) for FN were mapped in three years of experiments. 23, 30, and 58 QTLs were identified using the ICIM-BIP, ICIM-MET, and ICIM-EPI methods, respectively. Among them, seven QTLs were considered stable. QFn.sau-1B.2, which was mapped to the 1BL chromosome, can explain 13.6% of the phenotypic variation on average and is considered a major and stable QTL for FN. This QTL was mapped in a 1cM interval and is flanked by the markers AX-110409346 and AX-108743901. Epistatic analysis indicated that QFN.sau-1B.2 has a strong influence on FN through both additive and epistatic effects. The Kompetitive Allele-Specific PCR marker KASP-AX-108743901, which is closely linked to QFn.sau-1B.2, was designed. The genetic effect of QFn.sau-1B.2 on FN was successfully confirmed in Chuannong18 × T1208 and CN17 × CN11 populations. Moreover, the results of the additive effects of favorable alleles for FN showed that the QTLs for FN had significant effects not only on FN but also on the resistance to spike germination. Within the interval of QFn.sau-1B.2, 147 high-confidence genes were found. According to the gene annotation and the transcriptome data, four genes might be associated with FN. QFn.sau-1B.2 may provide a new resource for the high-quality breeding of wheat in the future.

Identifying QTL for grain protein content independent from grain yield-related traits in durum wheat

Grain protein content (GPC) is a crucial quality trait determining the nutritional, rheological, and end-use properties characteristics of wheat. Breeding programs for GPC were hindered by complex genetic control, the strong influence of environmental factors, and the negative correlation between GPC and grain yield. To identify stable quantitative trait loci (QTL) associated with increased GPC without decreasing grain yield, a recombinant inbred lines population of durum wheat was genotyped with a 25K SNP array and evaluated for GPC and yield-related traits in four field trials. Six QTL for GPC were identified on chromosomes 1B, 2B (two loci), 4B, 5A, and 6A, consistently expressed across environments, four of which had antagonistic effects on grain yield per spike (GYS). Two QTL (QGpc.mgb-5A and QGpc/TKW.mgb-2B.2) on 2B and 5A chromosomes were independent of GYS variations and could be used in marker-assisted selection (MAS) for GPC improvement. Identifying and utilizing beneficial QTL/genes for wheat improvement requires careful consideration of the inverse relationship between GPC and yield-related traits, and phenotypic data collected across multiple environments. MAS or genomic selection techniques can effectively target favorable alleles for GPC enhancement while minimizing the impact on grain yield.

Meta-QTL analysis and candidate genes for quality traits, mineral content, and abiotic-related traits in wild emmer.

Wild emmer (Triticum turgidum ssp. dicoccoides) genotypes were studied for their high-nutritional value and good tolerance to various types of stress; for this reason, several QTL (quantitative trait loci) studies have been conducted to find favorable alleles to be introgressed into modern wheat cultivars. Given the complexity of the QTL nature, their interaction with the environment, and other QTLs, a small number of genotypes have been used in wheat breeding programs. Meta-QTL (MQTL) analysis helps to simplify the existing QTL information, identifying stable genomic regions and possible candidate genes for further allele introgression. The study aimed to identify stable QTL regions across different environmental conditions and genetic backgrounds using the QTL information of the past 14 years for different traits in wild emmer based upon 17 independent studies. A total of 41 traits were classified as quality traits (16), mineral composition traits (11), abiotic-related traits (13), and disease-related traits (1). The analysis revealed 852 QTLs distributed across all 14 chromosomes of wild emmer, with an average of 61 QTLs per chromosome. Quality traits had the highest number of QTLs (35%), followed by mineral content (33%), abiotic-related traits (28%), and disease-related traits (4%). Grain protein content (GPC) and thousand kernel weight (TKW) were associated with most of the QTLs detected. A total of 43 MQTLs were identified, simplifying the information, and reducing the average confidence interval (CI) from 22.6 to 4.78 cM. These MQTLs were associated with multiple traits across different categories. Nine candidate genes were identified for several stable MQTLs, potentially contributing to traits such as quality, mineral content, and abiotic stress resistance. These genes play essential roles in various plant processes, such as carbohydrate metabolism, nitrogen assimilation, cell wall biogenesis, and cell wall extensibility. Overall, this study underscores the importance of considering MQTL analysis in wheat breeding programs, as it identifies stable genomic regions associated with multiple traits, offering potential solutions for improving wheat varieties under diverse environmental conditions.

Fhb9, a major QTL for Fusarium head blight resistance improvement in wheat

Fusarium head blight (FHB), mainly caused by Fusarium graminearum, is one of the most devastating diseases of wheat worldwide. Identification and validation of major quantitative trait loci (QTLs) for FHB resistance without negative effects on agronomic traits is critical to success in breeding FHB-resistant cultivars. In this study, a stable major QTL on chromosome arm 2DL was identified by evaluating a recombinant inbred line (RIL) population derived from Shi4185×Shijiazhuang 8 in both field and greenhouse experiments. QTL mapping and pedigree analyses indicated that the 2DL QTL is the same QTL as QFhb-2DL previously identified in Ji5265, therefore, designated Fhb9. Four kompetitive amplicon sequence polymorphism (KASP) markers were developed based on exome capture sequencing data to enhance marker density in the Fhb9 region, and it was delimited to an interval between single nucleotide polymorphism (SNP) markers KASP-12056 (533.8) and KASP-525 (525.9 Mb) explained 26.0-30.1% of the phenotypic variation. Analysis of the geographic distribution of the Fhb9 resistance allele suggested that it originated from Huang-Huai winter wheat region in China, and very low frequency of Fhb9 in modern Chinese cultivars reveals that it has not been widely deployed in breeding programs. Field and greenhouse evaluation of yield-related traits of near-isogenic lines (NILs) contrasting in Fhb9 alleles indicated that Fhb9 resistance allele did not show any adverse effects on those traits. Fhb9 showed an additive effect on enhancing FHB resistance with Fhb1. Therefore, Fhb9 is a valuable major QTL for improving FHB resistance in wheat and the near-diagnostic markers developed in this study will facilitate its deployment in wheat breeding programs.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat.

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individualsderived from residual heterozygous lines (RHLs)self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, whichprovides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

Detection of two homologous major QTLs and development of diagnostic molecular markers for sucrose content in peanut.

We identified two stable and homologous major QTLs for sucrose content in peanut, and developed breeder-friendly molecular markers for marker-assisted selection breeding. Sucrose content is a crucial quality trait for edible peanuts, and increasing sucrose content is a key breeding objective. However, the genetic basis of sucrose content in peanut remains unclear, and major quantitative trait loci (QTLs) for sucrose content have yet to be identified. In this study, a high-density genetic map was constructed based on whole-genome re-sequencing data from a peanut RIL population. This map consisted of 2,042 bins and 24,142 SNP markers, making it one of the most comprehensive maps to date in terms of marker density. Two major QTLs (qSCA06.2 and qSCB06.2) were identified, explaining 31.41% and 24.13% of the phenotypic variance, respectively. Notably, these two QTLs were located in homologous genomic regions between the A and B subgenomes. The elite allele of qSCA06.2 was exclusive to Valencia-type, while the elite allele of qSCB06.2 existed in other peanut types. Importantly, the distribution of alleles from two homologous QTLs in the RIL population and diverse germplasm accessions consistently demonstrated that only the combination of elite allelic genotypes from both QTLs/genes resulted in a significantly dominant phenotype, accompanied by a substantial increase in sucrose content. The newly developed diagnostic markers for these QTLs were confirmed to be reliable and could facilitate future breeding efforts to enhance sucrose content using marker-assisted selection techniques. Overall, this study highlights the co-regulation of sucrose content by two major homologous QTLs/genes and provides valuable insights into the genetic basis of sucrose in peanuts.

Dissection of a novel major stable QTL on chromosome 7D for grain hardness and its breeding value estimation in bread wheat.

Grain hardness (Gh) is important for wheat processing and end-product quality. Puroindolines polymorphism explains over 60% of Gh variation and the novel genetic factors remain to be exploited. In this study, a total of 153 quantitative trait loci (QTLs), clustered into 12 genomic intervals (C1-C12), for 13 quality-related traits were identified using a recombinant inbred line population derived from the cross of Zhongkemai138 (ZKM138) and Chuanmai44 (CM44). Among them, C7 (harboring eight QTLs for different quality-related traits) and C8 (mainly harboring QGh.cib-5D.1 for Gh) were attributed to the famous genes, Rht-D1 and Pina, respectively, indicating that the correlation of involved traits was supported by the pleotropic or linked genes. Notably, a novel major stable QTL for Gh was detected in the C12, QGh.cib-7D, with ZKM138-derived allele increasing grain hardness, which was simultaneously mapped by the BSE-Seq method. The geographic pattern and transmissibility of this locus revealed that the increasing-Gh allele is highly frequently present in 85.79% of 373 worldwide wheat varieties and presented 99.31% transmissibility in 144 ZKM138-derivatives, indicating the non-negative effect on yield performance and that its indirect passive selection has happened during the actual breeding process. Thus, the contribution of this new Gh-related locus was highlighted in consideration of improving the efficiency and accuracy of the soft/hard material selection in the molecular marker-assisted process. Further, TraesCS7D02G099400, TraesCS7D02G098000, and TraesCS7D02G099500 were initially deduced to be the most potential candidate genes of QGh.cib-7D. Collectively, this study provided valuable information of elucidating the genetic architecture of Gh for wheat quality improvement.

QTL mapping: insights into genomic regions governing component traits of yield under combined heat and drought stress in wheat.

Drought and heat frequently co-occur during crop growth leading to devastating yield loss. The knowledge of the genetic loci governing component traits of yield under combined drought and heat stress is essential for enhancing the climate resilience. The present study employed a mapping population of 180 recombinant inbred lines (RILs) derived from a cross between GW322 and KAUZ to identify quantitative trait loci (QTLs) governing the component traits of yield under heat and combined stress conditions. Phenotypic evaluation was conducted across two consecutive crop seasons (2021-2022 and 2022-2023) under late sown irrigation (LSIR) and late sown restricted irrigation (LSRI) conditions at the Indian Council of Agricultural Research Institute-Indian Agricultural Research Institute (ICAR-IARI), New Delhi. Various physiological and agronomic traits of importance were measured. Genotyping was carried out with 35K SNP Axiom breeder's genotyping array. The linkage map spanned a length of 6769.45cM, ranging from 2.28cM/marker in 1A to 14.21cM/marker in 5D. A total of 35 QTLs were identified across 14 chromosomes with 6B containing the highest (seven) number of QTLs. Out of 35 QTLs, 16 were major QTLs explaining the phenotypic variance greater than 10%. The study identified eight stable QTLs along with two hotspots on chromosomes 6B and 5B. Five QTLs associated with traits thousand-grain weight (TGW), normalized difference vegetation index (NDVI), and plant height (PH) were successfully validated. Candidate genes encoding antioxidant enzymes, transcription factors, and growth-related proteins were identified in the QTL regions. In silico expression analysis highlighted higher expression of transcripts TraesCS2D02G021000.1, TraesCS2D02G031000, TraesCS6A02G247900, and TraesCS6B02G421700 under stress conditions. These findings contribute to a deeper understanding of the genetic architecture underlying combined heat and drought tolerance in wheat, providing valuable insights for wheat improvement strategies under changing climatic conditions.

Identification of Putative Quantitative Trait Loci for Improved Seed Oil Quality in Peanuts.

Improving seed oil quality in peanut (Arachis hypogaea) has long been an aim of breeding programs worldwide. The genetic resources to achieve this goal are limited. We used an advanced recombinant inbred line (RIL) population derived from JH5 × KX01-6 to explore quantitative trait loci (QTL) affecting peanut oil quality and their additive effects, epistatic effects, and QTL × environment interactions. Gas chromatography (GC) analysis suggested seven fatty acids components were obviously detected in both parents and analyzed in a follow-up QTL analysis. The major components, palmitic acid (C16:0), oleic acid (C18:1), and linoleic acid (C18:2), exhibited considerable phenotypic variation and fit the two major gene and minor gene mixed-inheritance model. Seventeen QTL explained 2.57-38.72% of the phenotypic variation in these major components, with LOD values of 4.12-37.56 in six environments, and thirty-five QTL explained 0.94-32.21% of the phenotypic variation, with LOD values of 5.99-150.38 in multiple environments. Sixteen of these QTL were detected in both individual and multiple environments. Among these, qFA_08_1 was a novel QTL with stable, valuable and major effect. Two other major-effect QTL, qFA_09_2 and qFA_19_3, share the same physical position as FAD2A and FAD2B, respectively. Eleven stable epistatic QTL involving nine loci explained 1.30-34.97% of the phenotypic variation, with epistatic effects ranging from 0.09 to 6.13. These QTL could be valuable for breeding varieties with improved oil quality.

Efficient identification of QTL for agronomic traits in foxtail millet (Setaria italica) using RTM- and MLM-GWAS.

Eleven QTLs for agronomic traits were identified by RTM- and MLM-GWAS, putative candidate genes were predicted and two markers for grain weight were developed and validated. Foxtail millet (Setaria italica), the second most cultivated millet crop after pearl millet, is an important grain crop in arid regions. Seven agronomic traits of 408 diverse foxtail millet accessions from 15 provinces in China were evaluated in three environments. They were clustered into two divergent groups based on genotypic data using ADMIXTURE, which was highly consistent with their geographical distribution. Two models for genome-wide association studies (GWAS), namely restricted two-stage multi-locus multi-allele (RTM)-GWAS and mixed linear model (MLM)-GWAS, were used to dissect the genetic architecture of the agronomic traits based on 13,723 SNPs. Eleven quantitative trait loci (QTLs) for seven traits were identified using two models (RTM- and MLM-GWAS). Among them, five were considered stable QTLs that were identified in at least two environments using MLM-GWAS. One putative candidate gene (SETIT_006045mg, Chr4: 744,701-746,852) that can enhance grain weight per panicle was identified based on homologous gene comparison and gene expression analysis and was validated by haplotype analysis of 330 accessions with high-depth (10×) resequencing data (unpublished). In addition, homologous gene comparison and haplotype analysis identified one putative foxtail millet ortholog (SETIT_032906mg, Chr2:5,020,600-5,029,771) with rice affecting the target traits. Two markers (cGWP6045 and kTGW2906) were developed and validated and can be used for marker-assisted selection of foxtail millet with high grain weight. The results provide a fundamental resource for foxtail millet genetic research and breeding and demonstrate the power of integrating RTM- and MLM-GWAS approaches as a complementary strategy for investigating complex traits in foxtail millet.

Genomic and co-expression network analyses reveal candidate genes for oil accumulation based on an introgression population in Upland cotton (Gossypium hirsutum).

Integrated QTL mapping and WGCNA condense the potential gene regulatory network involved in oil accumulation. A glycosyl hydrolases gene (GhHSD1) for oil biosynthesis was confirmed in Arabidopsis, which will provide useful knowledge to understand the functional mechanism of oil biosynthesis in cotton. Cotton is an economical source of edible oil for the food industry. The genetic mechanism that regulates oil biosynthesis in cottonseeds is essential for the genetic enhancement of oil content (OC). To explore the functional genomics of OC, this study utilized an interspecific backcross inbred line population to dissect the quantitative trait locus (QTL) interlinked with OC. In total, nine OC QTLs were identified, four of which were novel, and each QTL explained 3.62-34.73% of the phenotypic variation of OC. The comprehensive transcript profiling of developing cottonseeds revealed 3,646 core genes differentially expressed in both inbred parents. Functional enrichment analysis determined 43 genes were annotated with oil biosynthesis processes. Implementation of weighted gene co-expression network analysis showed that 803 differential genes had a significant correlation with the OC phenotype. Further integrated analysis identified seven important genes located in OC QTLs. Of which, the GhHSD1 gene located in stable QTL qOC-Dt3-1 exhibited the highest functional linkages with the other network genes. Phylogenetic analysis showed significant evolutionary differences in the HSD1 sequences between oilseed- and starch- crops. Furthermore, the overexpression of GhHSD1 in Arabidopsis yielded almost 6.78% higher seed oil. This study not only uncovers important genetic loci for oil accumulation in cottonseed, but also provides a set of new candidate genes that potentially influence the oil biosynthesis pathway in cottonseed.

Development of Gossypium hirsutum-Gossypium raimondii introgression lines and its usages in QTL mapping of agricultural traits

Gossypium raimondii (2n=2x=26, D5), an untapped wild species, is the putative progenitor of the D-subgenome of G. hirsutum (2n=4x=52, AD1), an extensively cultivated species. Here, we developed a G. hirsutum (recipient)-G. raimondii (donor) introgression population to exploit favorable QTLs/genes and mapped potential quantitative trait loci (QTLs) from wild cotton species. The introgression population consists of 256 lines with an introgression rate of 52.33% of the genome G. raimondii. The range of introgression segment length was 0.03-19.12 Mb, with an average of 1.22 Mb. The coverage of total introgression fragments was 386.98 Mb from G. raimondii. Further genome-wide association analysis (Q+K+MLM) and QTL mapping (RSTEP-LRT) identified 59 common QTLs, including 14 stable QTLs and 6 common QTL (co-QTL) clusters, and one hotspot of MIC. The common QTLs for seed index showed all positive additive effects, while the common QTLs for boll weight were all negative additive effects, indicating that the linkage between seed index and boll weight could be broken. QTLs for lint percentage showed positive effect and could be beneficial for improving cotton yield. Most QTLs for fiber quality had negative additive effects, implying these QTLs were domesticated/improved in G. hirsutum. A few fiber quality QTLs showed positive additive effects, which could be used to improve cotton fiber quality. These introgression lines developed would be useful for molecular marker-assisted breeding and facilitate us to map QTLs precisely for mining desirable genes from the wild species G. raimondii to improve cultivated cotton in future via a design-breeding approach.

The MADS-box transcription factor CsAGL9 plays essential roles in seed setting in Camellia sinensis

The number of seed setting (NSS) is an important biological trait that affects tea propagation and yield. In this study, the NSS of an F1 tea population (n = 324) generated via a cross between ‘Longjing 43’ and ‘Baihaozao’ was investigated at two locations in two consecutive years. Quantitative trait locus (QTL) mapping of the NSS was performed, and 10 major QTLs were identified. In total, 318 genes were found in these 10 QTLs intervals, and 11 key candidate genes were preliminarily identified. Among them, the MADS-box transcription factor AGAMOUS LIKE 9 (CsAGL9, CSS0037962) located in the most stable QTL (qNSS2) was identified as a key gene affecting the NSS. CsAGL9 overexpression in Arabidopsis promoted early flowering and significantly decreased the length and number of pods and number of seeds per pod. Transcriptome analysis demonstrated that the auxin pathway, a key hormone pathway regulating plant reproduction, was highly affected in the transgenic lines. The auxin pathway was likewise the most prominent in the gene co-expression network study of CsAGL9 in tea plants. In summary, we identified CsAGL9 is essential for seed setting using QTL mapping integrated with RNA-seq, which shed a new light on the mechanism NSS of seed setting in tea plants.

Genomic regions involved in the control of 1,000-kernel weight in wild relative-derived populations of durum wheat

Terminal drought is one of the most common and devastating climatic stress factors affecting durum wheat (Triticum durum Desf.) production worldwide. The wild relatives of this crop are deemed a vast potential source of useful alleles to adapt to this stress. A nested association mapping (NAM) panel was generated using as a recurrent parent the Moroccan variety ‘Nachit’ derived from Triticum dicoccoides and known for its large grain size. This was recombined to three top-performing lines derived from T. dicoccoides, T. araraticum, and Aegilops speltoides, for a total of 426 inbred progenies. This NAM was evaluated across eight environments (Syria, Lebanon, and Morocco) experiencing different degrees of terminal moisture stress over two crop seasons. Our results showed that drought stress caused on average 41% loss in yield and that 1,000-kernel weight (TKW) was the most important trait for adaptation to it. Genotyping with the 25K TraitGenetics array resulted in a consensus map of 1,678 polymorphic SNPs, spanning 1,723 cM aligned to the reference ‘Svevo’ genome assembly. Kinship distinguished the progenies in three clades matching the parent of origin. A total of 18 stable quantitative trait loci (QTLs) were identified as controlling various traits but independent from flowering time. The most significant genomic regions were named Q.ICD.NAM-04, Q.ICD.NAM-14, and Q.ICD.NAM-16. Allelic investigation in a second germplasm panel confirmed that carrying the positive allele at all three loci produced an average TKW advantage of 25.6% when field-tested under drought conditions. The underlying SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers and successfully validated in a third germplasm set, where they explained up to 19% of phenotypic variation for TKW under moisture stress. These findings confirm the identification of critical loci for drought adaptation derived from wild relatives that can now be readily exploited via molecular breeding.

A QTL allele from wild soybean enhances protein content without reducing the oil content

Abstract Soybean is one of the chief crops producing protein and oil for human consumption. Wild soybean, the ancestor of cultivated soybean, possesses high seed protein content; therefore, it is a valuable genetic resource that could enhance protein content in the cultivated varieties. To identify the genes responsible for increasing protein content in wild soybean, a population comprising 113 BC4F6 chromosome segment substitution lines (CSSL) was developed from a cross between soybean cultivar ‘Jackson’ and wild soybean accession JWS156-1. The CSSL population was cultivated in the field conditions for 3 years (2018, 2019 and 2020), and the seeds harvested from each line were analysed for protein and oil contents by InfraTec Nova instrument. Quantitative trait locus (QTL) analysis with 243 SSR markers identified 12 QTLs associated with seed protein, oil and protein + oil contents. Among these QTLs, qPro8 and qPro19, two major and stable QTLs for protein content, were detected on chromosomes 8 and 19, respectively. No QTL for oil content was detected in the vicinity of qPro19, indicating that qPro19 did not influence the seed oil content. The effect of qPro19 was validated using near-isogenic lines (NILs) of qPro19. By introducing the qPro19 allele from wild soybean into another soybean variety, ‘Tachiyutaka’, a BC4 line, T-678, that showed enhanced seed protein content, without reducing the seed oil content. This study implied that the qPro19 allele from wild soybean could be a potential genetic resource for breeding programmes aimed to improve soybean seed quality.

QTL mapping for seedling and adult plant resistance to stripe and leaf rust in two winter wheat populations

The two recombinant inbred line (RIL) populations developed by crossing Almaly × Avocet S (206 RILs) and Almaly × Anza (162 RILs) were used to detect the novel genomic regions associated with adult plant resistance (APR) and seedling or all-stage resistance (ASR) to yellow rust (YR) and leaf rust (LR). The quantitative trait loci (QTLs) were detected through multi-year phenotypic evaluations (2018–2020) and using high-throughput DArTseq genotyping technology. RILs exhibited significant genetic variation with p < 0.001, and the coefficient of variation ranged from 9.79% to 47.99% for both LR and YR in all Environments and stages of evaluations. The heritability is quite high and ranged between 0.47 and 0.98. We identified nine stable QTLs for YR APR on chromosomes 1B, 2A, 2B, 3D, and 4D and four stable QTLs for LR APR on chromosomes 2B, 3B, 4A, and 5A. Furthermore, in silico analysis revealed that the key putative candidate genes such as cytochrome P450, protein kinase-like domain superfamily, zinc-binding ribosomal protein, SANT/Myb domain, WRKY transcription factor, nucleotide sugar transporter, and NAC domain superfamily were in the QTL regions and probably involved in the regulation of host response toward pathogen infection. The stable QTLs identified in this study are useful for developing rust-resistant varieties through marker-assisted selection (MAS).

Unraveling the genetic basis of grain number-related traits in a wheat-Agropyron cristatum introgressed line through high-resolution linkage mapping

BackgroundGrain number per spike (GNS) is a pivotal determinant of grain yield in wheat. Pubing 3228 (PB3228), a wheat-Agropyron cristatum germplasm, exhibits a notably higher GNS.ResultsIn this study, we developed a recombinant inbred line (RIL) population derived from PB3228/Gao8901 (PG-RIL) and constructed a high-density genetic map comprising 101,136 loci, spanning 4357.3 cM using the Wheat 660 K SNP array. The genetic map demonstrated high collinearity with the wheat assembly IWGSC RefSeq v1.0. Traits related to grain number and spikelet number per spike were evaluated in seven environments for quantitative trait locus (QTL) analysis. Five environmentally stable QTLs were detected in at least three environments. Among these, two major QTLs, QGns-4A.2 and QGns-1A.1, associated with GNS, exhibited positive alleles contributed by PB3228. Further, the conditional QTL analysis revealed a predominant contribution of PB3228 to the GNS QTLs, with both grain number per spikelet (GNSL) and spikelet number per spike (SNS) contributing to the overall GNS trait. Four kompetitive allele-specific PCR (KASP) markers that linked to QGns-4A.2 and QGns-1A.1 were developed and found to be effective in verifying the QTL effect within a diversity panel. Compared to previous studies, QGns-4A.2 exhibited stability across different trials, while QGns-1A.1 represents a novel QTL. The results from unconditional and conditional QTL analyses are valuable for dissecting the genetic contribution of the component traits to GNS at the individual QTL level and for understanding the genetic basis of the superior grain number character in PB3228. The KASP markers can be utilized in marker-assisted selection for enhancing GNS.ConclusionsFive environmentally stable QTLs related to grain number and spikelet number per spike were identified. PB3228 contributed to the majority of the QTLs associated with GNS.

Berry texture QTL and candidate gene analysis in grape (Vitis vinifera L.).

Berry texture is a noteworthy economic trait for grape; however, the genetic bases and the complex gene expression and regulatory mechanism for the diverse changes in berry texture are still poorly understood. In this study, the results suggest that it is difficult to obtain high-mesocarp firmness (MesF) and high-pericarp puncture hardness (PPH) grape cultivars with high pericarp brittleness (PerB). The high-density linkage map was constructed using whole-genome resequencing based on 151 F1 individuals originating from intraspecific hybridization between the firm-flesh cultivar 'Red Globe' and soft-flesh cultivar 'Muscat Hamburg'. The total length of the consensus map was 1613.17cM, with a mean genetic distance between adjacent bin markers of 0.59cM. Twenty-seven quantitative trait loci (QTLs) for berry MesF, PPH, and PerB were identified in linkage groups (LGs) 1, 3, 4, 6, 8, 9, 10, 11, 14, 16, and 17, including twelve QTLs that were firstly detected in LGs 6, 11, and 14. Fourteen promising candidate genes were identified from the stable QTL regions in LGs 10, 11, 14, and 17. In particular, VvWARK2 and VvWARK8 refer to chromosome 17 and are two promising candidate genes for MesF and PPH, as the VvWARK8 gene may increase pectin residue binding with WARK for high berry firmness maintenance and the allele for VvWARK2 carrying the 'CC' and 'GA' genotypes at Chr17:1836764 and Chr17:1836770 may be associated with non-hard texture grape cultivars. In addition, real-time quantitative polymerase chain reaction (RT-qPCR) verification revealed that the promising candidate transcription factor genes VvMYB4-like, VvERF113, VvWRKY31, VvWRKY1, and VvNAC83 may regulate cell wall metabolism candidate gene expression for grape berry texture changes.

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.