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Cotton breeding for the development of early-maturing varieties is an effective way to improve multiple cropping indexes and alleviate the conflict between grains and cotton in the cultivated fields in China. In the present study, we aimed to identify upland cotton quantitative trait loci (QTLs) and candidate genes related to early-maturity traits, including whole growth period (WGP), flowering timing (FT), node of the first fruiting branch (NFFB), height of the node of the first fruiting branch (HNFFB), and plant height (PH). An early-maturing variety, CCRI50, and a late-maturing variety, Guoxinmian 11, were crossed to obtain biparental populations. These populations were used to map QTLs for the early-maturity traits for two years (2020 and 2021). With BSA-seq analysis based on the data of population 2020, the candidate regions related to early maturity were found to be located on chromosome D03. We then developed 22 polymorphic insertions or deletions (InDel) markers to further narrow down the candidate regions, resulting in the detection of five and four QTLs in the 2020 and 2021 populations, respectively. According to the results of QTL mapping, two candidate regions (InDel_G286-InDel_G144 and InDel_G24-InDel_G43) were detected. In these regions, three genes (GH_D03G0451, GH_D03G0649, and GH_D03G1180) have non-synonymous mutations in their exons and one gene (GH_D03G0450) has SNP variations in the upstream sequence between CCRI50 and Guoxinmian 11. These four genes also showed dominant expression in the floral organs. The expression levels of GH_D03G0451, GH_D03G0649 and GH_D03G1180 were significantly higher in CCRI50 than in Guoxinmian 11 during the bud differentiation stages, while GH_D03G0450 showed the opposite trend. Further functional verification of GH_D03G0451 indicated that the GH_D03G0451-silenced plants showed a delay in the flowering time. The results suggest that these are the candidate genes for cotton early maturity, and they may be used for breeding early-maturity cotton varieties.

Seed size is an important agronomic trait in melons that directly affects seed germination and subsequent seedling growth. However, the genetic mechanism underlying seed size in melon remains unclear. In the present study, we employed Bulked-Segregant Analysis sequencing (BSA-seq) to identify a candidate region (~1.35 Mb) on chromosome 6 that corresponds to seed size. This interval was confirmed by QTL mapping of three seed size-related traits from an F2 population across three environments. This mapping region represented nine QTLs that shared an overlapping region on chromosome 6, collectively referred to as qSS6.1. New InDel markers were developed in the qSS6.1 region, narrowing it down to a 68.35 kb interval that contains eight annotated genes. Sequence variation analysis of the eight genes identified a SNP with a C to T transition mutation in the promoter region of MELO3C014002, a leucine-rich repeat receptor-like kinase (LRR-RLK) gene. This mutation affected the promoter activity of the MELO3C014002 gene and was successfully used to differentiate the large-seeded accessions (C-allele) from the small-seeded accessions (T-allele). qRT-PCR revealed differential expression of MELO3C014002 between the two parental lines. Its predicted protein has typical LRR-RLK family domains, and phylogenetic analyses reveled its similarity with the homologs in several plant species. Altogether, these findings suggest MELO3C014002 as the most likely candidate gene involved in melon seed size regulation. Our results will be helpful for better understanding the genetic mechanism regulating seed size in melons and for genetically improving this important trait through molecular breeding pathways.

Barley net form net blotch (NFNB) is a destructive foliar disease caused by Pyrenophora teres f. teres. Barley line CIho5791, which harbors the broadly effective chromosome 6H resistance gene Rpt5, displays dominant resistance to P. teres f. teres. To genetically characterize P. teres f. teres avirulence/virulence on the barley line CIho5791, we generated a P. teres f. teres mapping population using a cross between the Moroccan CIho5791-virulent isolate MorSM40-3 and the avirulent reference isolate 0-1. Full genome sequences were generated for 103 progenies. Saturated chromosome-level genetic maps were generated, and quantitative trait locus (QTL) mapping identified two major QTL associated with P. teres f. teres avirulence/virulence on CIho5791. The most significant QTL mapped to chromosome (Ch) 1, where the virulent allele was contributed by MorSM40-3. A second QTL mapped to Ch8; however, this virulent allele was contributed by the avirulent parent 0-1. The Ch1 and Ch8 loci accounted for 27 and 15% of the disease variation, respectively, and the avirulent allele at the Ch1 locus was epistatic over the virulent allele at the Ch8 locus. As a validation, we used a natural P. teres f. teres population in a genome-wide association study that identified the same Ch1 and Ch8 loci. We then generated a new reference quality genome assembly of parental isolate MorSM40-3 with annotation supported by deep transcriptome sequencing of infection time points. The annotation identified candidate genes predicted to encode small, secreted proteins, one or more of which are likely responsible for overcoming the CIho5791 resistance. [Figure: see text] The author(s) have dedicated the work to the public domain under the Creative Commons CC0 “No Rights Reserved” license by waiving all of his or her rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law, 2024.

Abstract Background Phenotyping of plant traits presents a significant bottleneck in Quantitative Trait Loci (QTL) mapping and genome-wide association studies (GWAS). Computerized phenotyping using digital images promises rapid, robust, and reproducible measurements of dimension, shape, and color traits of plant organs, including grain, leaf, and floral traits. Results We introduce GRABSEEDS, which is specifically tailored to extract a comprehensive set of features from plant images based on state-of-the-art computer vision and deep learning methods. This command-line enabled tool, which is adept at managing varying light conditions, background disturbances, and overlapping objects, uses digital images to measure plant organ characteristics accurately and efficiently. GRABSEED has advanced features including label recognition and color correction in a batch setting. Conclusion GRABSEEDS streamlines the plant phenotyping process and is effective in a variety of seed, floral and leaf trait studies for association with agronomic traits and stress conditions. Source code and documentations for GRABSEEDS are available at: https://github.com/tanghaibao/jcvi/wiki/GRABSEEDS .

Abstract [Objective] The study aims to discover the genetic loci and candidate genes of seed glucosinolate content in Brassica napus, and lay a foundation for the cloning of genes involved in glucosinolate metabolism and improving the breeding of B. napus. [Methods] Using KN DH populations from four different environments as materials, the QTL mapping of seed glucosinolate content and the candidate genes were analyzed. [Results] (1) The variation coefficient of seed glucosinolate content in B. napus was high and stable, which followed the genetic characteristics of quantitative traits. (2) Seven consistent QTLs, including cqGC.A9-5, cqGC.A9-7, cqGC.A9-9, cqGC.C2-9, cqGC.C2-10, cqGC.C9-5 and cqGC.C9-6, were environmentally stable QTLs, of which cqGC.A9-5, cqGC.C2-10, and cqGC.C9-5 were major QTLs. (3) Three candidate genes, including BnaA09g05480D, BnaC09g05620D, and BnaC09g05810D, were identified in the interval of the major QTL cqGC.A9-5 and cqGC.C9-5. Based on their annotation, these candidate genes were involved in the biosynthetic pathway of glucosinolates (the biosynthesis of IAOx and 3-alkyl malic acid) and transport and distribution of glucosinolates. [Conclusion] Seed glucosinolate content in B. napus was quantitative trait. Three major QTLs for seed glucosinolate content were identified, which might be involved in the synthesis of intermediate products and the transport and distribution of glucosinolates.

Abstract Background Rapeseed (Brassica napus L.) is one of the most important oil crops and a wildly cultivated horticultural crop. The petals of B. napus serve to protect the reproductive organs and attract pollinators and tourists. Understanding the genetic basis of petal morphology regulation is necessary for B. napus breeding. Results In the present study, the quantitative trait locus (QTL) analysis for six B. napus petal morphology parameters in a double haploid (DH) population was conducted across six microenvironments. A total of 243 QTLs and five QTL hotspots were observed, including 232 novel QTLs and three novel QTL hotspots. The spatiotemporal transcriptomic analysis of the diversiform petals was also conducted, which indicated that the expression of plant hormone metabolic and cytoskeletal binding protein genes was variant among diversiform petals. Conclusions The integration of QTL and RNA-seq analysis revealed that plant hormones (including cytokinin, auxin, and gibberellin) and cytoskeleton were key regulators of the petal morphology. Subsequently, 61 high-confidence candidate genes of petal morphology regulation were identified, including Bn.SAUR10, Bn.ARF18, Bn.KIR1, Bn.NGA2, Bn.PRF1, and Bn.VLN4. The current study provided novel QTLs and candidate genes for further breeding B. napus varieties with diversiform petals.

Abstract Background Leaf morphology plays a crucial role in photosynthetic efficiency and yield potential in crops. Cigar tobacco plants, which are derived from common tobacco (Nicotiana tabacum L.), possess special leaf characteristics including thin and delicate leaves with few visible veins, making it a good system for studying the genetic basis of leaf morphological characters. Results In this study, GWAS and QTL mapping were simultaneously performed using a natural population containing 185 accessions collected worldwide and an F2 population consisting of 240 individuals, respectively. A total of 26 QTLs related to leaf morphological traits were mapped in the F2 population at three different developmental stages, and some QTL intervals were repeatedly detected for different traits and at different developmental stages. Among the 206 significant SNPs identified in the natural population using GWAS, several associated with the leaf thickness phenotype were co-mapped via QTL mapping. By analyzing linkage disequilibrium and transcriptome data from different tissues combined with gene functional annotations, 7 candidate genes from the co-mapped region were identified as the potential causative genes associated with leaf thickness. Conclusions These results presented a valuable cigar tobacco resource showing the genetic diversity regarding its leaf morphological traits at different developmental stages. It also provides valuable information for novel genes and molecular markers that will be useful for further functional verification and for molecular breeding of leaf morphological traits in crops in the future.

ABSTRACT The first step in trait introgression is to identify and assess novel sources of variation. For shrub willow (Salix) breeders, there is an abundance of understudied species within a genus that readily hybridizes. Breeding targets in shrub willow center on traits contributing to biomass yield for bioenergy. These include stem biomass, insect and pathogen resistance, and leaf architecture traits. More specifically, breeding for durable resistance to willow leaf rust (Melampsora spp.) is of particular importance as the pathogen can significantly reduce biomass yields in commercial production. The Salix F1 hybrid common parent population (Salix F1 HCP) was created to characterize the variation among eight species‐hybrid families and map QTL for targeted traits. A female and male S. purpurea were used as common parents in crosses made to male S. suchowensis, S. viminalis, S. koriyanagi, and S. udensis and female S. viminalis, S. integra, S. suchowensis to produce eight families that were planted in field trials at Cornell AgriTech in Geneva, NY and phenotyped. Using 16 previously described parental backcross linkage maps and two newly generated S. purpurea consensus maps, we identified 215 QTL across all eight families and in every parent. These included 15 leaf rust severity, 61 herbivory, 65 leaf architecture, and 74 yield component QTL, resulting in 50 unique overlapping regions within the population. These genetic loci serve as an important foundation for future shrub willow breeding, and each interspecific family was identified as a novel source of useful alleles for trait introgression into high yielding cultivars.

Sesame (Sesamum indicum L.) is an important oilseed crop widely cultivated in subtropical and tropical areas. Low genetic yield potential and susceptibility to disease contribute to low productivity in sesame. However, the genetic basis of sesame yield- and disease-related traits remains unclear. Here, we represent the construction of a high-density bin map of sesame using whole genome sequencing of an F2 population derived from ‘Yizhi’ and ‘Mingdeng Zhima’. A total of 2766 Bins were categorized into 13 linkage groups. Thirteen significant QTLs were identified, including ten QTLs related to yield, two QTLs related to Sesame Fusarium wilt (SFW) disease, and one QTL related to seed color. Among these QTLs, we found that SFW-QTL1.1 and SFW-QTL1.2 were major QTLs related to Fusarium wilt disease, explaining more than 20% of the phenotypic variation with LOD > 6. SCC-QTL1.1 was related to seed coat color, explaining 52% of the phenotypic variation with LOD equal to 25.3. This suggests that seed color traits were controlled by a major QTL. Candidate genes related to Fusarium wilt disease and seed color in the QTLs were annotated. We discovered a significant enrichment of genes associated with resistance to late blight. These genes could be spectral disease resistance genes and may have a role in the regulation of Fusarium wilt disease resistance. Our study will benefit the implementation of marker-assisted selection (MAS) for the genetic improvement of disease resistance and yield-related traits in sesame.

Background Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. Methods The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). Results A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. Conclusion The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

Goji berries are a small-fruited shrub with industrial importance whose fruit considered beneficial in both fresh and dried forms. Current germplasms of goji berries include small fruits with a short shelf life, less sweet and bitter taste, and a lack of appropriate genetic information. This study aimed to employ whole genome resequencing to generate an ultra-dense bin linkage map and to elucidate the genetic basis of goji fruit quality and size using quantitative trait loci (QTL) mapping analysis in a cross-pollinated hybrid population. To achieve this goal, human sensory tests were carried out to determine the bitter taste (BT) and sweet taste (ST), and to quantify the soluble solid content (SSC), fruit firmness (FF), and fruit size-related traits of fresh goji fruits over three or four years. The results revealed that the goji bin linkage map based on resequencing spanned a total length of 966.42 cM and an average bin interval of 0.03 cM. Subsequent variant calling and ordering resulted in 3,058 bins containing 35,331 polymorphic markers across 12 chromosomes. A total of 99 QTLs, with individual loci in different environments explaining a phenotypic variance of 1.21-16.95% were identified for the studied traits. Ten major effects, including colocalized QTLs corresponding to different traits, were identified on chromosomes 1, 3, 5, 6, 7, and 8, with a maximum Logarithm of Odds (LOD) of 29.25 and 16.95% of explained phenotypic variance (PVE). In addition, four stable loci, one for FF, one for fruit weight (FW), and two for fruit shape index (FSI), were mainly mapped on chromosomes 5, 6, and 7, elucidating 2.10-16.95% PVE. These findings offer valuable insights into the genetic architecture of goji fruit traits along with identified specific loci and markers to further improve and develop sweeter, less bitter and larger fruited goji berry cultivars with extended shelf life.

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver condition in the United States, encompassing a wide spectrum of liver pathologies including steatosis, steatohepatitis, fibrosis, and cirrhosis. Despite its high prevalence, there are no medications currently approved by the Food and Drug Administration for the treatment of NAFLD. Recent work has suggested that NAFLD has a strong genetic component and identifying causative genes will improve our understanding of the molecular mechanisms contributing to NAFLD and yield targets for future therapeutic investigations. Oxidative stress is known to play an important role in NAFLD pathogenesis, yet the underlying mechanisms accounting for disturbances in redox status are not entirely understood. To better understand the relationship between the glutathione redox system and signs of NAFLD in a genetically-diverse population, we measured liver weight, serum biomarkers aspartate aminotransferase (AST) and alanine aminotransferase (ALT), and graded liver pathology in a large cohort of Diversity Outbred mice. We compared hepatic endpoints to those of the glutathione redox system previously measured in the livers and kidneys of the same mice, and we screened for statistical and genetic associations using the R/qtl2 software. We discovered several novel genetic loci associated with markers of liver health, including loci that were associated with both liver steatosis and glutathione redox status. Candidate genes within each locus point to possible new mechanisms underlying the complex relationship between NAFLD and the glutathione redox system, which could have translational implications for future studies targeting NAFLD pathology.

Bulked-segregant analysis by deep sequencing (BSA-seq) is a widely used method for mapping QTL (quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2 populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F3 populations offering notable advantages over F2 populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading (DTH) in a 7200-plant rice F3 population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near 41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F3 populations and multi-environment experiments can achieve high power, resolution, and reliability.

Abstract Proper pericarp thickness protects the maize kernel against pests and diseases, moreover, thinner pericarp improves the eating quality in fresh corn. In this study, we aimed to investigate the dynamic changes in maize pericarp during kernel development and identified the major quantitative trait loci (QTLs) for maize pericarp thickness. It was observed that maize pericarp thickness first increased and then decreased. During the growth and formation stages, the pericarp thickness gradually increased and reached the maximum, after which it gradually decreased and reached the minimum during maturity. To identify the QTLs for pericarp thickness, a BC4F4 population was constructed using maize inbred lines B73 (recurrent parent with thick pericarp) and Baimaya (donor parent with thin pericarp). In addition, a high-density genetic map was constructed using maize 10 K SNP microarray. A total of 17 QTLs related to pericarp thickness were identified in combination with the phenotypic data. The results revealed that the heritability of the thickness of upper germinal side of pericarp (UG) was 0.63. The major QTL controlling UG was qPT1-1, which was located on chromosome 1 (212,215,145–212,948,882). The heritability of the thickness of upper abgerminal side of pericarp (UA) was 0.70. The major QTL controlling UA was qPT2-1, which was located on chromosome 2 (2,550,197–14,732,993). In addition, a combination of functional annotation, DNA sequencing analysis and quantitative real-time PCR (qPCR) screened two candidate genes, Zm00001d001964 and Zm00001d002283, that could potentially control maize pericarp thickness. This study provides valuable insights into the improvement of maize pericarp thickness during breeding.

The seed storage materials accumulate during seed development, and are essential for seed germination and seedling establishment. Here we employed two bi-parental populations of an F2:3 population developed from a cross of improved 220 (I220, small seeds with low starch) and PH4CV (large seeds with high starch), as well as recombinant-inbred lines (RILs) of X178 (high starch) and its improved introgression line I178 (low starch), to identify the genes that control seed storage materials. We identified a total of 12 QTLs for starch, protein and oil, which explained 3.44–10.79% of the phenotypic variances. Among them, qSTA2-1 identified in F2:3 and qSTA2-2 identified in the RILs partially overlapped at an interval of 7.314–9.554 Mb, and they explained 3.44–10.21% of the starch content variation, so they were selected for further study. Fine mapping of qSTA2-2 with the backcrossed populations of I220/PH4CV in each generation narrowed it down to a 199.7 kb interval that contains 14 open reading frames (ORFs). Transcriptomic analysis of developing seeds from the near-isogenic lines (NILs) of I220/PH4CV (BC5F2) showed that only 11 ORFs were expressed in 20 days after pollination (DAP) seeds. Five of them were upregulated and six of them were downregulated in NILI220, and the differentially expressed genes (DEGs) between NILI220 and NILPH4CV were enriched in starch metabolism, hormone signal transduction and glycosaminoglycan degradation. Of the eleven NILI220 differential expressed ORFs, ORF4 (Zm00001d002260) and ORF5 (Zm00001d002261) carry 75% protein sequence similarity, both encodes an glycolate oxidase, were the possible candidates of qSTA2-2. Further analysis and validation indicated that mutation of the qSTA2-2 locus resulted in the dysfunction of ABA accumulation, the embryo/endosperm ratio and the starch and hormone levels.

Abstract Background Powdery mildew (PM) is one of the important soybean diseases, and host resistance could practically contribute to soybean PM management. To date, only the Rmd locus on chromosome (Chr) 16 was identified through traditional QTL mapping and GWAS, and it remains unclear if the bulk segregant RNA-Seq (BSR-Seq) methodology is feasible to explore additional PM resistance that might exist in other varieties. Results BSR-Seq was applied to contrast genotypes and gene expressions between the resistant bulk (R bulk) and the susceptible bulk (S bulk), as well as the parents. The ∆(SNP-index) and G’ value identified several QTL and significant SNPs/Indels on Chr06, Chr15, and Chr16. Differentially expressed genes (DEGs) located within these QTL were identified using HISAT2 and Kallisto, and allele-specific primers (AS-primers) were designed to validate the accuracy of phenotypic prediction. While the AS-primers on Chr06 or Chr15 cannot distinguish the resistant and susceptible phenotypes, AS-primers on Chr16 exhibited 82% accuracy prediction with an additive effect, similar to the SSR marker Satt431. Conclusions Evaluation of additional AS-primers in the linkage disequilibrium (LD) block on Chr16 further confirmed the resistant locus, derived from the resistant parental variety ‘Kaohsiung 11’ (‘KS11’), not only overlaps with the Rmd locus with unique up-regulated LRR genes (Glyma.16G213700 and Glyma.16G215100), but also harbors a down-regulated MLO gene (Glyma.16G145600). Accordingly, this study exemplified the feasibility of BSR-Seq in studying biotrophic disease resistance in soybean, and showed the genetic makeup of soybean variety ‘KS11’ comprising the Rmd locus and one MLO gene.

Leaf rust, caused by the fungus Puccinia triticina Eriks (Pt), is a destructive disease affecting wheat (Triticum aestivum L.) production in many countries, and a serious threat to food security. As a result, several breeding programs have included leaf rust resistance as an important trait. The discovery and identification of new resistance genes that could aid in incorporating durable or long-lasting leaf rust resistance into wheat is fundamental in these breeding programs. The present study aimed to identify quantitative trait loci (QTLs) for leaf rust resistance in 127 recombinant inbred lines (RIL) developed from the cross between the resistant wheat cultivar Popo and the susceptible cultivar Kariega. The RIL population and parental lines were phenotyped for leaf rust infection type and severity at seedling and adult plant stage, respectively. The former in the greenhouse (in Argentina) and the latter in multiple field test environments comprising 3 locations in South Africa (in Tygerhoek in the Western Cape Province during the 2014, 2015, 2017 and 2018 cropping seasons; Clarens during 2014, 2016 and 2017 cropping seasons and in Bethlehem in the Free State Province during 2017 cropping season) and in 1 location in Argentina (during the 2017 and 2018 cropping seasons in Marcos Juárez, Córdoba Province). The population was genotyped using genotyping-by-sequencing. A total of 12,080 silicoDArT and 2,669 SNP markers were used for QTL analysis. In total, 25 putative QTLs for resistance to leaf rust at seedling and adult plant stages were identified, including 5 QTLs for seedling and 20 QTLs for adult plant resistance (APR). Interestingly, both Popo and Kariega contributed with alleles for resistance. Significant loci for reducing leaf rust infection at seedling stage were designated QLr.arc-1A, QLr.arc-2B, QLr.arc-5B, QLr.arc-6A and QLr.arc-6D. Three minor QTLs derived from Popo designated as QLr.arc-1B1, QLr.arc-2D and QLr.arc-3D were also detected from the field tests, explaining 5–10%, 10–16% and 5–7% of the phenotypic variance, respectively. The identified QTLs and their closely linked silicoDArT and SNP-based markers can be used for fine mapping and candidate gene discovery in wheat breeding programs targeting durable leaf rust resistance.

IntroductionOwing to advances in high-throughput genome sequencing, QTL-Seq mapping of salt tolerance traits is a major platform for identifying soil-salinity tolerance QTLs to accelerate marker-assisted selection for salt-tolerant rice varieties. We performed QTL-BSA-Seq in the seedling stage of rice from a genetic cross of the extreme salt-sensitive variety, IR29, and “Jao Khao” (JK), a Thai salt-tolerant variety.MethodsA total of 462 F2 progeny grown in soil and treated with 160 mM NaCl were used as the QTL mapping population. Two high- and low-bulk sets, based on cell membrane stability (CMS) and tiller number at the recovery stage (TN), were equally sampled. The genomes of each pool were sequenced, and statistical significance of QTL was calculated using QTLseq and G prime (G′) analysis, which is based on calculating the allele frequency differences or Δ(SNP index).ResultsBoth methods detected the overlapping interval region, wherein CMS-bulk was mapped at two loci in the 38.41–38.85 Mb region with 336 SNPs on chromosome 1 (qCMS1) and the 26.13–26.80 Mb region with 1,011 SNPs on chromosome 3 (qCMS3); the Δ(SNP index) peaks were −0.2709 and 0.3127, respectively. TN-bulk was mapped at only one locus in the overlapping 38.26–38.95 Mb region on chromosome 1 with 575 SNPs (qTN1) and a Δ(SNP index) peak of −0.3544. These identified QTLs in two different genetic backgrounds of segregating populations derived from JK were validated. The results confirmed the colocalization of the qCMS1 and qTN1 traits on chromosome 1. Based on the CMS trait, qCMS1/qTN1 stably expressed 6%–18% of the phenotypic variance in the two validation populations, while qCMS1/qTN1 accounted for 16%–20% of the phenotypic variance in one validation population based on the TN trait.ConclusionThe findings confirm that the CMS and TN traits are tightly linked to the long arm of chromosome 1 rather than to chromosome 3. The validated qCMS-TN1 QTL can be used for gene/QTL pyramiding in marker-assisted selection to expedite breeding for salt resistance in rice at the seedling stage.

Abstract An increase in genetic diversity of bread wheat caused by spring x winter forms leads to an alteration of genetic control of maturity time. Maturity time (MAT) is one of major yield components in wheat, which has two components: the heading date (HD) and grain-filling period (GFP). Using the Illumina Infinium 25k platform we analyzed the genetic control of the HD, GFP and MAT in the F2 and F2:3 populations from a cross between late-ripening spring/winter line 124-1 and spring wheat cultivar Novosibirskaya 31, possessing the same allelic composition of the VRN1 and PPD-D1 genes. The phenotypic evaluation of the populations studied was performed during three years. A total of 17 QTLs were mapped, out of which 4 QTLs for MAT or its components were confirmed over two years. Two common MAT and HD QTLs were identified on the 4A chromosome, and two loci controlling GFP and MAT were found on 6B chromosome. An environmentally stable HD QTL QHd.icg-7B.1 was associated with the FT-B1 gene having a non-synonymous polymorphism [G/C] in its coding region. A novel НD QTL was identified on 7D chromosome. QTL dissection allowed to propose putative genes for QMat.icg4-A and QMat.icg6-B, namely the SPL family gene (TraesCS4A02G359500) and the TCP transcription factor (TraesCS6B02G462100), respectively. The results of this study provide information for further investigation into wheat development.

Pod quality and yield traits in snap bean (Phaseolus vulgaris L.) influence consumer preferences, crop adoption by farmers, and the ability of the product to be commercially competitive locally and globally. The objective of the study was to identify the quantitative trait loci (QTL) for pod quality and yield traits in a snap × dry bean recombinant inbred line (RIL) population. A total of 184 F6 RILs derived from a cross between Vanilla (snap bean) and MCM5001 (dry bean) were grown in three field sites in Kenya and one greenhouse environment in Davis, CA, USA. They were genotyped at 5,951 single nucleotide polymorphisms (SNPs), and composite interval mapping was conducted to identify QTL for 16 pod quality and yield traits, including pod wall fiber, pod string, pod size, and harvest metrics. A combined total of 44 QTL were identified in field and greenhouse trials. The QTL for pod quality were identified on chromosomes Pv01, Pv02, Pv03, Pv04, Pv06, and Pv07, and for pod yield were identified on Pv08. Co-localization of QTL was observed for pod quality and yield traits. Some identified QTL overlapped with previously mapped QTL for pod quality and yield traits, with several others identified as novel. The identified QTL can be used in future marker-assisted selection in snap bean.

IntroductionFusarium head blight (FHB) has a large influence on both the yield and quality of wheat grain worldwide. Host resistance is the most effective method for controlling FHB, but unfortunately, very few genetic resources on FHB resistance are available; therefore, identifying novel resistance genes or quantitative trait loci (QTLs) is valuable. MethodsHere, a recombinant inbred line (RIL) population containing 451 lines derived from the cross L661/PI672538 was sown in four different environments (2019CZa, 2019CZb, 2021QL and 2021WJ).ResultsFive QTLs, consisting of two previously reported QTLs (FhbL693a and FhbL693b) and three new QTLs (FhbL693c, FhbL693d and FhbL693e), were identified. Further investigation revealed that FhbL693b, FhbL693c and FhbL693d could be detected in all four environments, and FhbL693a and FhbL693e were detected only in 2019CZb and 2021WJ, respectively. Among the QTLs, the greatest contribution (10.5%) to the phenotypic variation effect (PVE) was FhbL693d in 2021WJ, while the smallest (1.2%) was FhbL693e and FhbL693a in 2019CZb. The selection of 5Dindel-4 for FhbL693d, 4Aindel-7 for FhbL693c and 3Bindel-24 for FhbL693b decreased the number of damaged spikelets by 2.1, and a new line resistant to FHB named H140-2 was developed by marker-assisted selection (MAS). DiscussionThese results could help to further improve FHB resistance in the future.

IntroductionThe coconut tree crop (Cocos nucifera L.) provides vital resources for millions of people worldwide. Coconut germplasm is largely classified into ‘Tall’ (Typica) and ‘Dwarf’ (Nana) types. While Tall coconuts are outcrossing, stress tolerant, and late flowering, Dwarf coconuts are inbred and flower early with a high rate of bunch emission. Precocity determines the earlier production of a plantation and facilitates management and harvest.MethodsA unique outbred F2 population was used, generated by intercrossing F1 hybrids between Brazilian Green Dwarf from Jiqui (BGDJ) and West African Tall (WAT) cultivars. Single-nucleotide polymorphism (SNP) markers fixed for alternative alleles in the two varieties, segregating in an F2 configuration, were used to build a high-density linkage map with ~3,000 SNPs, anchored to the existing chromosome-level genome assemblies, and a quantitative trait locus (QTL) mapping analysis was carried out.ResultsThe linkage map established the chromosome numbering correspondence between the two reference genome versions and the relationship between recombination rate, physical distance, and gene density in the coconut genomes. Leveraging the strong segregation for precocity inherited from the Dwarf cultivar in the F2, a major effect QTL with incomplete dominance was mapped for flowering time. FLOWERING LOCUS T (FT) gene homologs of coconut previously described as putatively involved in flowering time by alternative splice variant analysis were colocalized within a ~200-kb window of the major effect QTL [logarithm of the odds (LOD) = 11.86].DiscussionOur work provides strong phenotype-based evidence for the role of the FT locus as the putative underlying functional variant for the flowering time difference between Dwarf and Tall coconuts. Major effect QTLs were also detected for developmental traits of the palm, plausibly suggesting pleiotropism of the FT locus for other precocity traits. Haplotypes of the two SNPs flanking the flowering time QTL inherited from the Dwarf parent BGDJ caused a reduction in the time to flower of approximately 400 days. These SNPs could be used for high-throughput marker-assisted selection of early-flowering and higher-productivity recombinant lines, providing innovative genetic material to the coconut industry.

Downy mildew (DM), caused by Plasmopara viticola, is one of the most serious diseases that affects grape production worldwide. Utilizing host resistance, commonly known as 'R' genes, is considered the most effective way to cure the disease. The identification of the R gene in well-known table grape cultivars is conducive to breeding varieties with better quality. In this study, a population of F1 with 246 progenies was obtained from the cross of two widely grown table grapes 'Moldova' and 'Shine Muscat', in which 'Moldova' appeared resistant to P. viticola resistance. According to the sequencing data from GBTS, a high-density genetic map containing 826 SNPs, which spanned 1,515.99 cM, was constructed. Through the analysis of MapQTL and GWAS, a resistant locus for P. viticola was mapped, located at 27.534−30.729 Mbp in chr18, and was named Rpv34. A total of 21 Resistance Gene Analogues (RGA) distributed in three clusters were identified in this locus. A SNP marker chr18_29062596 was proved to be highly associated with resistance to P. viticola. This work will improve the mechanism of resistance understanding of P. viticola in grapevine and facilitate the use of resistant germplasm in breeding.

Growth traits are among the most important economic traits in pigs and are regulated by polygenes with complex regulatory mechanisms. As the major indicators of growth performance, the backfat thickness (BFT), loin eye area (LEA), and days to 100 kg (D100) traits are commonly used to the genetics improvement in pigs. However, the available genetic markers for these traits are limited. To uncover novel loci and candidate genes associated with growth performance, we collected the phenotypic information of BFT, LEA, and D100 in 1,186 pigs and genotyped all these individuals using the Neogen GGP porcine 80K BeadChip. We performed a genome-wide association study (GWAS) using 4 statistical models, including mixed linear models (MLM), fixed and random model circulating probability unification (FarmCPU), settlement of MLM under progressively exclusive relationships (SUPER), Bayesian-information and linkage-disequilibrium Iteratively nested keyway (Blink), and identified 5, 3, and 6 high-confidence single nucleotide polymorphisms (SNPs) associated with BFT, LEA, and D100, respectively. Variant annotation and quantitative trait locus (QTL) mapping analysis suggested that 6 genes (SKAP2, SATB1, PDE7B, PPP1R16B, WNT3, and WNT9B) were potentially associated with growth performance in pigs. Transcriptome analysis suggested that the expression of Src Kinase Associated Phosphoprotein 2 (SKAP2) was higher in prenatal muscles than in postnatal muscles, and the expression of Phosphodiesterase 7B (PDE7B) continuously increased during the prenatal stages and gradually decreased after birth, implying their potential roles in prenatal skeletal muscle development. Overall, this study provides new candidate loci and genes for the genetic improvement of pigs.

Grain weight is one of the key components of wheat (Triticum aestivum L.) yield. Genetic manipulation of grain weight is an efficient approach for improving yield potential in breeding programs. A recombinant inbred line (RIL) population derived from a cross between W7268 and Chuanyu 12 (CY12) was employed to detect quantitative trait loci (QTLs) for thousand-grain weight (TGW), grain length (GL), grain width (GW), and the ratio of grain length to width (GLW) in six environments. Seven major QTLs, QGl.cib-2D, QGw.cib-2D, QGw.cib-3B, QGw.cib-4B.1, QGlw.cib-2D.1, QTgw.cib-2D.1 and QTgw.cib-3B.1, were consistently identified in at least four environments and the best linear unbiased estimation (BLUE) datasets, and they explained 2.61 to 34.85% of the phenotypic variance. Significant interactions were detected between the two major TGW QTLs and three major GW loci. In addition, QTgw.cib-3B.1 and QGw.cib-3B were co-located, and the improved TGW at this locus was contributed by GW. Unlike other loci, QTgw.cib-3B.1/QGw.cib-3B had no effect on grain number per spike (GNS). They were further validated in advanced lines using Kompetitive Allele Specific PCR (KASP) markers, and a comparison analysis indicated that QTgw.cib-3B.1/QGw.cib-3B is likely a novel locus. Six haplotypes were identified in the region of this QTL and their distribution frequencies varied between the landraces and cultivars. According to gene annotation, spatial expression patterns, ortholog analysis and sequence variation, the candidate gene of QTgw.cib-3B.1/QGw.cib-3B was predicted. Collectively, the major QTLs and KASP markers reported here provide valuable information for elucidating the genetic architecture of grain weight and for molecular marker-assisted breeding in grain yield improvement.

AbstractExploring the genetic basis of adaptive divergence at fine spatial scales can broaden our basic understanding of evolution and how organisms may adapt to changing environments in the future. Cave-associated microhabitats provide a unique opportunity to gain insight into microgeographic adaptation. We studied the genetic architecture of microhabitat-related divergence in flower phenology and leaf traits between two sister species of Primulina, P. depressa and P. danxiaensis, which live in sympatry but occupy contrasting microhabitats. We identified 40 significant quantitative trait loci (QTLs) associated with the interspecific differences in these microhabitat adaptation traits. Flowering time was controlled by one major-effect and six minor-effect QTLs, while leaf traits were influenced by 9–12 QTLs of small to moderate effect. The genetic architecture of the flowering time and the specific leaf area was genetically independent of other traits. Our results suggest that microhabitat adaptation in sympatric populations of Primulina differs according to different traits, with leaf traits diverging with the accumulation of many small changes and flowering phenology being driven by major effect variance.

With the development of new technologies in recent years, researchers have made significant progress in crop breeding. Modern breeding differs from traditional breeding because of great changes in technical means and breeding concepts. Whereas traditional breeding initially focused on high yields, modern breeding focuses on breeding orientations based on different crops’ audiences or by-products. The process of modern breeding starts from the creation of material populations, which can be constructed by natural mutagenesis, chemical mutagenesis, physical mutagenesis transfer DNA (T-DNA), Tos17 (endogenous retrotransposon), etc. Then, gene function can be mined through QTL mapping, Bulked-segregant analysis (BSA), Genome-wide association studies (GWASs), RNA interference (RNAi), and gene editing. Then, at the transcriptional, post-transcriptional, and translational levels, the functions of genes are described in terms of post-translational aspects. This article mainly discusses the application of the above modern scientific and technological methods of breeding and the advantages and limitations of crop breeding and diversity. In particular, the development of gene editing technology has contributed to modern breeding research.

The size of peanut pods and seeds, which directly affects yield and quality, also has significant implications for mechanized production and market efficiency. Identifying relevant loci and mining candidate genes is crucial for cultivating high-yield peanut varieties. In this study, we employed advanced generation recombinant inbred lines developed by crossbreeding Huayu 44 and DF12 as the experimental material. Quantitative trait locus (QTL) mapping for traits related to pod and seed size was conducted across six environments. A total of 44 QTLs were detected, distributed on chromosomes A02, A05, B04, B08, and B10. An enrichment region for multiple QTLs was also identified on chromosome A05 (19.28~52.32 cm). In this region, 10 KASP markers were developed, narrowing the enrichment area to two candidate gene hotspot regions of 600.9 kb and 721.2 kb. By combining gene prediction and functional annotation within the intervals, 10 candidate genes, including those encoding cytochrome P450 protein, polyamine synthase, mannose-1-phosphate guanylyltransferase, pentatricopeptide repeat protein, and E2F transcription factor, were identified as regulators of pod and seed size. This study provides technical support for the genetic improvement and key gene identification of peanut pod and seed size.

Leaf angle (LA) is closely related to plant architecture, photosynthesis and density tolerance in maize. In the current study, we used a recombinant inbred line population constructed by two maize-inbred lines to detect quantitative trait loci (QTLs) controlling LA. Based on the average LA in three environments, 13 QTLs were detected, with the logarithm of odds ranging from 2.7 to 7.21, and the phenotypic variation explained by a single QTL ranged from 3.93% to 12.64%. A stable QTL, qLA2-3, on chromosome 2 was detected and was considered to be the major QTL controlling the LA. On the basis of verifying the genetic effect of qLA2-3, a fine map was used to narrow the candidate interval, and finally, the target segment was located at a physical distance of approximately 338.46 kb (B73 RefGen_v4 version), containing 16 genes. Re-sequencing and transcriptome results revealed that five candidate genes may be involved in the regulation of LA. The results enrich the information for molecular marker-assisted selection of maize LA and provide genetic resources for the breeding of dense planting varieties.

Candidate genes related to first pod height (FPH) traits in faba bean plants are crucial for mechanised breeding. However, reports on quantitative trait locus (QTL) mapping related to the FPH of faba bean are few, thus limiting the high-quality development of the faba bean industry to a certain extent. The identification and screening of candidate genes related to FPH is extremely urgent for the advancement of mechanised breeding for faba bean. In this study, a high-density genetic linkage map was constructed using genotyping-by-sequencing (GBS) of an F3 population and QTLs (genes) related to FPH were identified. The genetic linkage map contained seven linkage groups with 3012 SNP markers with an overall length of 4089.13 centimorgan (cM) and an average marker density of 1.36 cM. Thirty-eight QTLs for the first pod node (FPN) and FPH were identified (19 each for FPN and FPH). The 19 QTLs associated with FPN were located on chromosomes 1L, 1S, 2, 3, 4, 5, and 6; the 19 QTLs associated with FPH were located on chromosomes 1L, 1S, 2, 3, 5, and 6. There was a co-localisation interval of qFPN6-1 and qFPH6-1 on chromosome 6. By annotating the QTL qFPH6-1 interval, 36 genes that may be related to FPH were identified, these genes are related to plant growth and development. The results provide a basis for the precise location of QTLs related to FPH and could accelerate the breeding of faba bean varieties adapted to mechanised harvesting.

High-quality genetic maps are effective tools for elucidating the genetic mechanisms of complex quantitative traits and facilitating marker-assisted breeding. Species within the genus Liquidambar (commonly called sweetgum), particularly Liquidambar styraciflua and Liquidambar formosana, are significant forest resources worldwide. These sweetgum trees have been extensively utilized in medical and cosmetic applications for centuries as they contain large amounts of valuable secondary metabolites. Among these, shikimic acid is a notable metabolite with significant pharmaceutical applications. Despite advances in conventional breeding and propagation techniques for sweetgum, the genetic basis and regulatory mechanisms of valuable traits remain largely unexplored. In this study, we constructed the first high-density genetic map for sweetgum using whole-genome resequencing (WGR) of 220 progeny individuals derived from a cross of L. styraciflua × L. formosana. The genetic map spanned a total distance of 1428.51 centimorgans (cM) with an average inter-marker distance of 0.33 cM, incorporating 4268 bin markers across 16 linkage groups. To identify the genetic loci controlling the shikimic acid content, quantitative trait locus (QTL) mapping was carried out based on the genetic map. Two QTLs located on linkage group (LG) 12 were detected, encompassing a total of 213 genes within the QTL interval. Some of these genes are closely related to secondary metabolism in plants, including YUCCA and DXS genes. This study presents the first high-quality genetic map of sweetgum and provides a preliminary QTL analysis for shikimic acid content. Our findings establish a foundational framework for the genetic improvement of sweetgum through marker-assisted breeding and offer valuable insights for further research in sweetgum genetics.

Smallholder maize farming systems in sub-Saharan Africa (SSA) are vulnerable to drought-induced yield losses, which significantly impact food security and livelihoods within these communities. Mapping and characterizing genomic regions associated with water stress tolerance in tropical maize is essential for future breeding initiatives targeting this region. In this study, three biparental F3 populations composed of 753 families were evaluated in Kenya and Zimbabwe and genotyped with high-density single nucleotide polymorphism (SNP) markers. Quantitative trait loci maping was performed on these genotypes to dissect the genetic architecture for grain yield (GY), plant height (PH), ear height (EH) and anthesis-silking interval (ASI) under well-watered (WW) and water-stressed (WS) conditions. Across the studied maize populations, mean GY exhibited a range of 4.55–8.55 t/ha under WW and 1.29–5.59 t/ha under WS, reflecting a 31–59% reduction range under WS conditions. Genotypic and genotype-by-environment (G × E) variances were significant for all traits except ASI. Overall broad sense heritabilities for GY were low to high (0.25–0.60). For GY, these genetic parameters were decreased under WS conditions. Linkage mapping revealed a significant difference in the number of QTLs detected, with 93 identified under WW conditions and 41 under WS conditions. These QTLs were distributed across all maize chromosomes. For GY, eight and two major effect QTLs (>10% phenotypic variation explained) were detected under WW and WS conditions, respectively. Under WS conditions, Joint Linkage Association Mapping (JLAM) identified several QTLs with minor effects for GY and revealed genomic region overlaps in the studied populations. Across the studied water regimes, five-fold cross-validation showed moderate to high prediction accuracies (−0.15–0.90) for GY and other agronomic traits. Our findings demonstrate the polygenic nature of WS tolerance and highlights the immense potential of using genomic selection in improving genetic gain in maize breeding.

A recombinant inbred line (RIL) population derived from wheat landrace Qingxinmai and breeding line 041133 exhibited segregation in resistance to powdery mildew and stripe rust in five and three field tests, respectively. A 16K genotyping by target sequencing (GBTS) single-nucleotide polymorphism (SNP) array-based genetic linkage map was used to dissect the quantitative trait loci (QTLs) for disease resistance. Four and seven QTLs were identified for adult-plant resistance (APR) against powdery mildew and stripe rust. QPm.caas-1B and QPm.caas-5A on chromosomes 1B and 5A were responsible for the APR against powdery mildew in line 041133. QYr.caas-1B, QYr.caas-3B, QYr.caas-4B, QYr.caas-6B.1, QYr.caas-6B.2, and QYr.caas-7B detected on the five B-genome chromosomes of line 041133 conferred its APR to stripe rust. QPm.caas-1B and QYr.caas.1B were co-localized with the pleiotropic locus Lr46/Yr29/Sr58/Pm39/Ltn2. A Kompetitive Allele Specific Polymorphic (KASP) marker KASP_1B_668028290 was developed to trace QPm/Yr.caas.1B. Four lines pyramiding six major disease resistance loci, PmQ, Yr041133, QPm/Yr.caas-1B, QPm.caas-2B.1, QYr.caas-3B, and QPm.caas-6B, were developed. They displayed effective resistance against both powdery mildew and stripe rust at the seedling and adult-plant stages.

Tobacco (Nicotiana tabacum L.) use is the leading cause of preventable death, due to deleterious chemical components and smoke from tobacco products, and therefore reducing harmful chemical components in tobacco is one of the crucial tobacco breeding targets. However, due to complexity of tobacco smoke and unavailability of high-density genetic maps, the genetic architecture of representative hazardous smoke has not been fully dissected. The present study aimed to explore the genetic architecture of nine hazardous component traits of mainstream smoke through QTL mapping using 271 recombinant inbred lines (RILs) derived from K326 and Y3 in multiple environments. The analysis of genotype and genotype by environment interaction (GE) revealed substantially greater heritability over 95% contributed mostly by GE interaction effects. We also observed strong genetic correlations among most studied hazardous smoke traits, with the highest correlation coefficient of 0.84 between carbon monoxide and crotonaldehyde. Based on a published high-density genetic map, a total of 19 novel QTLs were detected for eight traits using a full QTL model, of which 17 QTLs showed significant additive effects, six showed significant additive-by-environment interaction effects, and one pair showed significant epistasis-by-environment interaction effect. Bioinformatics analysis of sequence in QTL region predicted six genes as candidates for four traits, of which Nt21g04598.1, Nt21g04600.1, and Nt21g04601.1 had pleiotropic effects on PHE and TAR.

IntroductionPlant height (PH) and ear height (EH) are key plant architectural traits in maize, which will affect the photosynthetic efficiency, high plant density tolerance, suitability for mechanical harvestingMethodsQTL mapping were conducted for PH and EH using a recombinant inbred line (RIL) population and two corresponding immortalized backcross (IB) populations obtained from crosses between the RIL population and the two parental lines.ResultsA total of 17 and 15 QTL were detected in the RIL and IB populations, respectively. Two QTL, qPH1-1 (qEH1-1) and qPH1-2 (qEH1-4) in the RIL, were simultaneously identified for PH and EH. Combing reported genome-wide association and cloned PH-related genes, co-expression network analyses were constructed, then five candidate genes with high confidence in major QTL were identified including Zm00001d011117 and Zm00001d011108, whose homologs have been confirmed to play a role in determining PH in maize and soybean.DiscussionQTL mapping used a immortalized backcross population is a new strategy. These identified genes in this study can provide new insights for improving the plant architecture in maize.

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.

Abstract Takifugu fasciatus is an aquaculture species with high economic value. In recent years, problems such as environmental pollution and inbreeding have caused a serious decline in T. fasciatus germplasm resources. In this study, a high-density genetic linkage map was constructed by whole-genome resequencing. The map consists of 4891 bin markers distributed across 22 linkage groups (LGs), with a total genetic coverage of 2381.353 cM and a mean density of 0.535 cM. Quantitative trait locus (QTL) localization analysis showed that a total of 19 QTLs associated with growth traits of T. fasciatus in the genome-wide significance threshold range, distributed on 11 LGs. In addition, 11 QTLs associated with cold tolerance traits were identified, each scattered on a different LG. Furthermore, we used QTL localization analysis to screen out three candidate genes (IGF1, IGF2, ADGRB) related to growth in T. fasciatus. Meanwhile, we screened three candidate genes (HSP90, HSP70, and HMGB1) related to T. fasciatus cold tolerance. Our study can provide a theoretical basis for the selection and breeding of cold-tolerant or fast-growing T. fasciatus.

Abstract Background Ongoing large-scale shift towards direct seeded rice (DSR) necessitates a convergence of breeding and genetic approaches for its sustenance and harnessing natural resources and environmental benefits. Improving seedling vigour remains key objective for breeders working with DSR. The present study aims to understand the genetic control of seedling vigour in deep sown DSR. Combined genome-wide association mapping, linkage mapping, fine mapping, RNA-sequencing to identify candidate genes and validation of putative candidate genes were performed in the present study. Results Significant phenotypic variations were observed among genotypes in both F3:4:5 and BC2F2:3 populations. The mesocotyl length showed significant positive correlation with %germination, root and shoot length. The 881 kb region on chromosome 7 reported to be associated with mesocotyl elongation. RNA-seq data and RT-PCR results identified and validated seven potential candidate genes. The four promising introgression lines free from linkage drag and with longer mesocotyl length, longer root length, semi-dwarf plant height have been identified. Conclusion The study will provide rice breeders (1) the pre breeding material in the form of anticipated DSR adapted introgression lines possessing useful traits and alleles improving germination under deep sown DSR field conditions (2) the base for the studies involving functional characterization of candidate genes. The development and utilization of improved introgression lines and molecular markers may play an important role in genomics-assisted breeding (GAB) during the pyramiding of valuable genes providing adaptation to rice under DSR. Our results offer a robust and reliable package that can contribute towards enhancing genetic gains in direct seeded rice breeding programs.

To break the narrow diversity bottleneck of the wheat D genome, a set of Aegilops tauschii-wheat introgression (A-WI) lines was developed by crossing Ae. tauschii accession T015 with common wheat elite cultivar Zhoumai 18 (Zhou18). A high-density genetic map was constructed based on Single Nucleotide Polymorphism (SNP) markers and 15 yield-related traits were evaluated in 11 environments for detecting quantitative trait loci (QTL). A total of 27 environmentally stable QTL were identified in at least five environments, 20 of which were derived from Ae. tauschii T015, explaining up to 24.27% of the phenotypic variations. The major QTL for kernel length (KL), QKl-2D.5, was delimited to a physical interval of approximately 2.6 Mb harboring 52 candidate genes. Three Kompetitive Allele Specific PCR (KASP) markers were successfully developed based on nonsynonymous nucleotide mutations of candidate gene AetT093_2Dv1G100900.1 and showed that A-WI lines with the T015 haplotype had significantly longer KL than the Zhou18 haplotype across all 11 environments. Four primary valuable A-WIs with good trait performance and carrying yield-related QTL were selected for breeding improvement. The results will facilitate the efficient transfer of beneficial genes from Ae. tauschii into wheat cultivars to improve wheat yield and other traits.

As important yield-related traits, thousand-grain weight (TGW), grain number per spike (GNS) and grain weight per spike (GWS) are crucial components of wheat production. To dissect their underlying genetic basis, a double haploid (DH) population comprised of 198 lines derived from 8762/Keyi 5214 was constructed. We then used genechip to genotype the DH population and integrated the yield-related traits TGW, GNS and GWS for QTL mapping. Finally, we obtained a total of 18 942 polymorphic SNP markers and identified 41 crucial QTLs for these traits. Three stable QTLs for TGW were identified on chromosomes 2D (QTgw-2D.3 and QTgw-2D.4) and 6A (QTgw-6A.1), with additive alleles all from the parent 8762, explaining 4.81–18.67% of the phenotypic variations. Five stable QTLs for GNS on chromosomes 3D, 5B, 5D and 6A were identified. QGns-5D.1 was from parent 8762, while the other four QTLs were from parent Keyi 5214, explaining 5.89–7.08% of the GNS phenotypic variations. In addition, a stable GWS genetic locus QGws-4A.3 was detected from the parent 8762, which explained 6.08–6.14% of the phenotypic variations. To utilize the identified QTLs, we developed STARP markers for four important QTLs, Tgw2D.3-2, Tgw2D.4-1, Tgw6A.1 and Gns3D.1. Our results provide important basic resources and references for the identification and cloning of genes related to TGW, GNS and GWS in wheat.

Owing to the limitation of a large genome size (~13 Gb), the genetic and gene mapping studies on faba bean (Vicia faba L.) are lagging far behind those for other legumes. In this study, we selected three purified faba bean lines (Yundou 8137, H0003712, and H000572) as parents and constructed two F2 populations. These two F2 populations, namely 167 F2 plants in Pop1 (Yundou 8137×H0003712) and 204 F2 plants in Pop2 (H000572×Yundou 8137), were genotyped using a targeted next-generation sequencing (TNGS) genotyping platform, and two high-density single nucleotide polymorphisms (SNP) genetic linkage maps of faba bean were constructed. The map constructed from Pop1 contained 5 103 SNPs with a length of 1 333.31 cM and an average marker density of 0.26 cM. The map constructed from Pop2 contained 1 904 SNPs with a greater length of 1 610.61 cM. In these two F2 populations, QTL mapping identified 98 QTLs for 14 agronomic traits related to the flowers, pods, plant types and grains. The two maps were then merged into an integrated genetic linkage map containing 6 895 SNPs, with a length of 3 324.48 cM. These results not only lay the foundation for fine mapping and map-based cloning of related genes, but can also accelerate the molecular marker-assisted breeding of faba bean.

Starch is the main component that determines the yield and quality of Tartary buckwheat. As a quantitative trait, using quantitative trait locus (QTL) mapping to excavate genes associated with starch-related traits is crucial for understanding the genetic mechanisms involved in starch synthesis and molecular breeding of Tartary buckwheat varieties with high-quality starch. Employing a recombinant inbred line population as research material, this study used QTL mapping to investigate the amylose, amylopectin, and total starch contents across four distinct environments. The results identified a total of 20 QTLs spanning six chromosomes, which explained 4.07% to 14.41% of the phenotypic variation. One major QTL cluster containing three stable QTLs governing both amylose and amylopectin content, qClu-4-1, was identified and located in the physical interval of 39.85–43.34 Mbp on chromosome Ft4. Within this cluster, we predicted 239 candidate genes and analyzed their SNP/InDel mutations, expression patterns, and enriched KEGG pathways. Ultimately, five key candidate genes, namely FtPinG0004897100.01, FtPinG0002636200.01, FtPinG0009329200.01, FtPinG0007371600.01, and FtPinG0005109900.01, were highlighted, which are potentially involved in starch synthesis and regulation, paving the way for further investigative studies. This study, for the first time, utilized QTL mapping to detect major QTLs controlling amylose, amylopectin, and total starch contents in Tartary buckwheat. The QTLs and candidate genes would provide valuable insights into the genetic mechanisms underlying starch synthesis and improving starch-related traits of Tartary buckwheat.

Leaf angle (LA) is an important trait of plant architecture, and individuals with narrow LA can better capture canopy light under high-density planting, which is beneficial for increasing the overall yield per unit area. To study the genetic basis and molecular regulation mechanism of leaf angle in rapeseed, we carried out a series of experiments. Quantitative trait loci (QTL) mapping was performed using the RIL population, and seven QTLs were identified. Transcriptome analysis showed that the cell wall formation/biogenesis processes and biosynthesis/metabolism of cell wall components were the most enrichment classes. Most differentially expressed genes (DEGs) involved in the synthesis of lignin, xylan, and cellulose showed down-regulated expression in narrow leaf material. Microscopic analysis suggested that the cell size affected by the cell wall in the junction area of the stem and petiole was the main factor in leaf petiole angle (LPA) differences. Combining QTL mapping and RNA sequencing, five promising candidate genes BnaA01G0125600ZS, BnaA01G0135700ZS, BnaA01G0154600ZS, BnaA10G0154200ZS, and BnaC03G0294200ZS were identified in rapeseed, and most of them were involved in cell wall biogenesis and the synthesis/metabolism of cell wall components. The results of QTL, transcriptome analysis, and cytological analysis were highly consistent, collectively revealing that genes related to cell wall function played a crucial role in regulating the LA trait in rapeseed. The study provides further insights into LA traits, and the discovery of new QTLs and candidate genes is highly beneficial for genetic improvement.

Superior fiber quality is one of the most important objectives in cotton breeding. To detect the genetic basis underlying fiber quality, an F2 population containing 413 plants was constructed by crossing Jifeng 914 and Jifeng 173, both of which have superior fiber quality, with Jifeng 173 being better. Five fiber quality traits were investigated in the F2, F2:3, F2:4, and F2:5 populations. Quantitative trait loci (QTL) mapping was conducted based on a high-density genetic map containing 11,488 single nucleotide polymorphisms (SNPs) and spanning 4202.12 cM in length. Transgressive segregation patterns and complex correlations in the five tested traits were observed. A total of 108 QTLs were found, including 13 major effect QTLs that contributed more than 10% toward phenotypic variation (PV) and 9 stable QTLs that could be repeatedly mapped in different generations. Chromosome A7 contained 12 QTL, ranking the first. No QTL was found on chromosomes D1 and D11. Two QTLs could be repeatedly detected in three populations, including qFL-D3-2 in F2, F2:4, and F2:5 with 9.18–21.45% of PV and qFS-A11-1 in F2:3, F2:4, and F2:5 with 6.05–10.41% of PV. Another seven stable QTLs could be detected in two populations, including four major effect QTLs: qFL-A12-3, qFS-D10-2, qMC-D6-2, and qMC-D8-1. Fourteen QTL-overlapping regions were found, which might explain the complex correlations among the five phenotypic traits. Four regions on chromosome A11, D3, D6, and D10 covered by both stable and major effect QTLs are promising for further fine mapping. The genomic regions of the two QTLs detected in three populations and the four major effect QTLs contain 810 genes. Gene functional analysis revealed that the annotated genes are mainly involved in protein binding and metabolic pathways. Fifteen candidate genes in the qFL-D3-2 region are highly expressed in fiber or ovules during fiber initiation, elongation, secondary cell wall thickening, or maturation stages. qRT-PCR revealed that Ghir_D03G005440.1 and Ghir_D03G011310.1 may play a role in promoting fiber initiation, while Ghir_D03G006470.1 may be beneficial for promoting fiber elongation. This study provides more information for revealing the molecular genetic basis underlying cotton fiber quality.

With the rapid emergence and distribution of red crown rot (RCR) across countries, durable sources of resistance against Calonectria ilicicola in soybean [Glycine max (L.) Merrill] is required to control the disease. We employed two RIL populations for the experiment. We identified 15 and 14 QTLs associated with RCR resistance in ZM6 and MN populations, respectively, totaling 29 QTLs. Six and eight QTLs had phenotypic variation above 10% in ZM6 and MN populations, respectively. We identified six (6) “QTL hotspots” for resistance to RCR from the ZM6 and MN RIL populations on chromosomes 1, 7, 10, 11, 13, and 18. Gene annotations, gene ontology enhancement, and RNA sequencing assessment detected 23 genes located within six “QTL Hotspots” as potential candidate genes that could govern RCR resistance in soybeans. Our data will generally assist breeders in rapidly and effectively incorporating RCR resistance into high-yielding accession through marker-assisted selection.

Understanding the genetic basis of salt resistance in crops is crucial for agricultural productivity. This study investigates the phenotypic and genetic basis of salt stress response in rice (Oryza sativa L.), focusing on germination and seedling traits. Under salt stress conditions, significant differences were observed in seed germination and seedling traits between parental LH99 (Indica rice LuHui 99) and SN265 (japonica rice ShenNong 265). Transgressive segregation was evident within the RIL population, indicating complex genetic interactions. Nine QTLs were detected at germination and seedling stages under salt stress, namely qSGE5 and qSGE7 for seed germination energy (SGE); qSGP7 for seed germination percentage (SGP); qSSH7, qSSH9-1, and qSSH9-2 for seeding height (SSH); qSRN6 for root number (SRN); and qSDW6 and qSDW9 for dry weight (SDW). Among them, qSSH9-1 and qSDW9 were localized in the same interval, derived from the salt-resistant parent SN265. PCA revealed distinct trait patterns under salt stress, captured by six PCs explaining 81.12% of the total variance. PC composite scores were used to localize a QTL associated with early salt resistance in rice qESC9, which was located in the same interval as qSSH9-1 and qSDW9, and was subsequently unified under the name qESC9, an important QTL for early-growth salt tolerance in rice. Correlation analysis also confirmed a relationship between alleles of qESC9 and the resistance to salt, underscoring the critical role this locus plays in the determination of overall salt tolerance in rice. Physiological analyses of extreme phenotype lines highlighted the importance of ion exclusion mechanisms in salt-resistant lines, while salt-susceptible lines exhibited elevated oxidative stress and impaired antioxidant defense, contributing to cellular damage. This comprehensive analysis sheds light on the genetic and physiological mechanisms underlying salt stress response in rice, providing valuable insights for breeding programs aimed at enhancing salt resistance in rice.

Improving low nitrogen (LN) tolerance in barley (Hordeum vulgare L.) increases global barley yield and quality. In this study, a recombinant inbred line (RIL) population crossed between “Baudin × CN4079” was used to conduct field experiments on twenty traits of barley yield, agronomy, and nitrogen(N)-related traits under LN and normal nitrogen (NN) treatments for two years. This study identified seventeen QTL, comprising eight QTL expressed under both LN and NN treatments, eight LN-specific QTL, and one NN-specific QTL. The localized C2 cluster contained QTL controlling yield, agronomic, and N-related traits. Of the four novel QTL, the expression of the N-related QTL Qstna.sau-5H and Qnhi.sau-5H was unaffected by N treatment. Qtgw.sau-2H for thousand-grain weight, Qph.sau-3H for plant height, Qsl.sau-7H for spike length, and Qal.sau-7H for awn length were identified to be the four stable expression QTL. Correlation studies revealed a significant negative correlation between grain N content and harvest index (p < 0.01). These results are essential for barley marker-assisted selection (MAS) breeding.

Peanut stem rot, also known as white mold, poses a significant threat to peanut production. It is typically managed using fungicides and moderately resistant cultivars. Cultivars with higher resistance can reduce fungicide dependency and increase sustainability. This study explores the potential of wild peanut species in stem rot resistance breeding programs by enhancing genetic diversity in cultivated peanut. Through greenhouse and field evaluations, 13 allotetraploid hybrids with Arachis stenosperma as one of the parents showed superior resistance compared to other wild genotypes. The genomic regions that confer the stem rot resistance were further identified by genotyping and phenotyping an F2 population derived from the allotetraploid ValSten1 (A. valida × A. stenosperma)4× and A. hypogaea cv. TifGP-2. A linkage map was constructed from 1926 SNP markers. QTL analysis revealed both beneficial and deleterious loci, with two resistance-associated QTLs derived from A. stenosperma and four susceptibility loci, two from A. stenosperma and two from A. valida. This is the first study that evaluated peanut-compatible wild-derived allotetraploids for stem rot resistance and that identified wild-derived QTLs for resistance to this pathogen. The allotetraploid hybrid ValSten1, that has A. stenosperma as one of the parents, offers a resource for resistance breeding. Markers associated with resistance QTLs can facilitate introgression from ValSten1 into cultivated peanut varieties in future breeding efforts, potentially reducing reliance on chemical control measures.

Bakanae disease is mainly caused by Fusarium fujikuroi and is a significant fungal disease with a number of disastrous consequences. It causes great losses in rice production. However, few studies have focused on the details of bakanae disease resistance in rice. Here, we summarize and discuss the progress of bakanae disease resistance in rice. Besides rice germplasm screening and resistance-related gene/quantitative trait locus (QTL) exploration, the route of pathogen invasion in rice plants was determined. We further discussed the regulation of phytohormone-related genes and changes in endogenous phytohormones in rice plants that are induced by the pathogen. To achieve better control of bakanae disease, the use of natural fungicides was assessed in this review. During rice—F. fujikuroi interactions, the infection processes and spatial distribution of F. fujikuroi in infected seedlings and adult plants exhibit different trends. Fungal growth normally occurs both in resistant and susceptible cultivars, with less abundance in the former. Generally, bakanae disease is seed-borne, and seed disinfection using effective fungicides should always be the first and main option to better control the disease. Besides the friendly and effective measure of using natural fungicides, breeding and utilization of resistant rice cultivars is also an effective control method. To some extent, rice cultivars with low grain quality, indica subspecies, and some dwarf or semi-dwarf rice germplasms are more resistant to bakanae disease. Although no highly resistant germplasms were obtained, 37 QTLs were located, with almost half of the QTLs being located on chromosome 1. Using omics methods, WRKYs and MAPKs were usually found to be regulated during rice—F. fujikuroi interactions. The regulation of certain phytohormone-related genes and changes in some endogenous phytohormones induced by the pathogen were clear, i.e., it downregulated gibberellin-related genes and repressed endogenous gibberellins in resistant genotypes, but the opposite results were noted in susceptible rice genotypes. Overall, exploring resistant germplasms or resistance-related genes/QTLs for the breeding of rice with bakanae disease resistance, expanding research on the complex mechanism of rice—F. fujikuroi interactions, and using cost-effective and eco-friendly innovative control methods against the disease are necessary for present and future bakanae disease management.

The development and deployment of diverse resistance sources in novel wheat cultivars underpin the durable control of stripe rust. The objectives of this study were to identify quantitative trait loci (QTL) associated with stripe rust resistance in the Chinese wheat breeding line YN1813 and to provide wheat breeders with original genes with potentially durable resistance. A total of 306 F7:8 recombinant inbred lines (RIL), derived from a cross between YN1813 (infection type 0–3 and disease severity 1–36%) and the moderately susceptible landrace Chinese Spring (IT 7–9 and DS 41–65%), were assessed for stripe rust disease severity in the field at Qingshui in Gansu and Pixian in Sichuan in 2020 and 2021 following inoculation with a mixture of the currently predominant Pst races. The parents and RIL were genotyped using the Wheat 55K single-nucleotide polymorphism (SNP) array. The total length of the constructed genetic linkage map was 3896.30 cm, with an average interval of 1.30 cm between adjacent markers. Two major QTL were identified on chromosome 7B and 7D across all tested environments. QYr.hau-7B was mapped to a 2.26 cm interval between the SNP markers AX-110908486–AX-89658728–AX-109489314 on chromosome 7B, explaining 0.9% to 16.9% of the phenotypic variation. QYr.hau-7D was positioned in a 0.67 cm interval flanked by the SNP markers AX-111654594 and AX-89378255, explaining 0.4% to 21.4% of the phenotypic variation. The QTL on 7D likely correspond to the previously known gene Yr18, whereas QYr.hau-7B was presumed to be a novel gene adjacent to YrZH84 or the core part of YrZH84. SNP markers closely linked with QYr.hau-7B were converted to allele-specific quantitative PCR-based genotyping assay (AQP) markers and validated in a panel of 712 wheat accessions. The group possessing a positive allele (TT) of AQP_AX-89658728 significantly (p < 0.05) decreased the IT by 45.8% and the DS by 63.2%. QYr.hau-7B and its markers could be useful in breeding programs to improve the level and durability of stripe rust resistance.