Search Results (401)

Bacterial stem and root rot (BSRR), caused by Dickeya dadantii, poses a severe threat to global sweetpotato production, yet the genetic architecture underlying resistance remains elusive. To dissect these mechanisms, we conducted a high-resolution genome-wide association study (GWAS) on 135 diverse accessions, integrating two-year field phenotyping with best linear unbiased prediction (BLUP) and 6.8 million single-nucleotide polymorphism (SNP) markers. This approach mapped nine quantitative trait loci (QTLs) exhibiting significant allelic dosage-dependent effects, with the major locus, qBSRR.6.1 was the primary discriminator between resistant and susceptible genotypes. Crucially, transcriptomic profiling within these loci revealed distinct expression patterns: IbTCP5 and IbERF003 (located in qBSRR.5.1 and qBSRR.6.2) were highly expressed in the susceptible cultivar ‘Xinxiang’ but suppressed in the resistant ‘Guangshu87’. Furthermore, BSRR challenge identified IbPUB4, IbKCS5, and IbLig1 as priority candidate genes involved in defense, with expression patterns suggesting roles in ubiquitin-mediated protein turnover, cuticular wax biosynthesis, and DNA repair, respectively. In stark contrast, IbPUB25 was constitutively upregulated in ‘Xinxiang’, potentially acting as a negative regulator of immunity via degradation of target proteins. These findings elucidate the polygenic, dosage-sensitive nature of BSRR resistance and prioritize specific targets for future functional characterization. Pyramiding favorable alleles of positive candidates while silencing potential negative regulators like IbPUB25 offers a promising avenue for developing durable, high-resistance sweetpotato varieties. Full article

Alternaria brown spot, caused by the tangerine pathotype of Alternaria alternata, is a destructive fungal disease affecting citrus production worldwide. Nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes constitute a major class of plant immune receptors; however, their genome-wide characteristics and potential association with Alternaria brown spot resistance loci in citrus remain poorly understood. In this study, we performed a comprehensive genome-wide identification and comparative analysis of NBS-LRR genes across representative citrus species. A total of 417 and 326 NBS-LRR genes were identified in Citrus reticulata and Citrus clementina, respectively, and were classified into NL, CNL, TNL, and RNL subfamilies based on domain architecture. Phylogenetic reconstruction, gene structure analysis, conserved motif composition, chromosomal distribution, synteny relationships, and promoter cis-element profiling collectively revealed considerable structural variation and lineage-specific expansion of the NBS-LRR gene family in citrus genomes. By integrating previously reported quantitative trait locus (QTL) data for Alternaria brown spot, we identified several NBS-LRR genes located within a resistance-associated genomic interval on chromosome 3. Among these, a candidate gene, designated LRR2, exhibited differential transcriptional responses upon pathogen inoculation and displayed distinct sequence variations between citrus genotypes. Structural modeling and molecular docking analyses suggested potential binding interfaces between LRR2 and multiple host-selective toxins, although the biological relevance of these interactions requires further experimental validation. Subcellular localization assays in Nicotiana benthamiana showed that LRR2 is distributed in both the nucleus and cytoplasm. Notably, transient overexpression of LRR2 triggered hypersensitive response-like cell death and H₂O₂ accumulation. Collectively, this study provides a comprehensive overview of the citrus NBS-LRR gene family and presents a multifaceted characterization of a QTL-anchored candidate gene. These findings establish a genomic and molecular framework for further functional investigations of citrus–Alternaria interactions. Full article

Background: Improving grain yield in wheat remains a top priority, requiring integrated breeding and genetic strategies. This complexity poses a major challenge, driven by quantitative polygenic inheritance, environmental influence, and intricate genetic interactions. We investigated genetic factors and their interactions for agronomic and yield traits in two high-yielding winter wheat cultivars adapted to the US Southern Great Plains. Methods: A bi-parental mapping population consisting of 221 F₇ recombinant inbred lines (RIL) derived from ‘TAM 204’ and ‘Iba’ was evaluated for three years in 11 Texas environments. Both parents and RIL population were genotyped on Illumina NovaSeq 6000 and sequences were aligned to IWGSC RefSeq v1.0 using Bowtie2 for SNP calling. For QTL analyses, each trait was analyzed by individual environment, across multiple environments and mega-environments. Results: A total of 86 QTL were mapped for five traits and among them 32 were consistent in more than one environment or analysis. Among consistent QTL, four were pleiotropic to more than one agronomic or yield traits mapped on chromosomes 2B (57.18, 59.47 Mb) and 2D (29.34, 40.64 Mb). The consistent QTL on chromosome 2D (29.34 Mb) was pleiotropic to GYLD, DTH, TW, TKW and explained maximum phenotypic variation for all traits, representing photoperiod gene (Ppd-D1). Another QTL on chromosome 2D (40.64 Mb) was pleiotropic to GYLD and TW and based on the physical position comparisons it likely reflects a unique locus in Iba. The pleiotropic consistent QTL Qgyld.tamu.2B.59 from TAM 204 represents Ppd-B1 gene. Moreover, it is more likely that Qdth.tamu.5B.575 represents the Vrn-B1 gene in Iba. A total of 23 digenic epistatic interactions involved consistent QTL for all traits. Amongst these, epistatic interactions between the consistent QTL on 2B (57.18 Mb) and 2D (29.34 Mb) were observed for GYLD, DTH and TKW. Conclusions: Our findings revealed key allelic diversity and interaction effects in elite wheat cultivars, paving the way for marker development for identified pleiotropic loci and implementation in marker-assisted selection and recombination breeding. Full article

Fusarium ear rot (FER) caused by Fusarium verticillioides is a major constraint on global maize production. The genetic basis of FER resistance is not yet fully understood, and the development of effective breeding strategies for improving FER resistance is still a critical priority. In the present study, a collection of 254 CIMMYT tropical maize lines genotyped with 955,690 high-quality SNPs was used to conduct genome-wide association studies (GWAS), complemented by QTL (quantitative trait locus) mapping in two recombinant inbred line populations. Additionally, genomic prediction (GP) exploring various statistical models and SNP selection schemes was implemented to optimize predictive accuracy for improving FER resistance. The broad-sense heritability estimates of FER resistance were 0.69–0.86 in the CML panel across six environments and 0.39–0.69 in the two RIL populations. At a p-value threshold of 2.61 × 10⁻⁷, GWAS identified 18 SNPs significantly associated with FER resistance across six environments, and in single environment analyses, their phenotypic variance explained (PVE) values ranged from 0.68 to 13.75%, with 13 SNPs exceeding a PVE of 5%. At a p-value threshold of 1 × 10⁻⁵, an additional 37 SNPs were detected, clustering within seven environmentally stable regions identified in at least two environments. Furthermore, 13 haplotype blocks exhibiting significant phenotypic differences were identified within these stable regions, with PVE values ranging from 2.39 to 15.24%, 9 of which exceeded 5%. QTL mapping in the two RIL populations revealed 27 moderate-effect QTLs at a LOD threshold of 2.5, including four detected repeatedly across environments, though only one QTL overlapped with the GWAS-identified region. Moderate genomic prediction accuracies of FER severity were achieved across models, with GBLUP and BayesB outperforming other models, and the prediction accuracies of these two models in the three populations were all around 0.5. Integrating the significant SNP set from genetic mapping results with a 100-SNP background set enhanced the stability of cross-population predictions. These results implied that FER resistance in tropical maize is controlled by multiple genomic regions with small-to-moderate genetic effects, whereas the consistency of genomic regions detected by GWAS and QTL mapping is low. Genomic prediction incorporating regions identified across different genetic backgrounds emerges as a promising tool for accelerating FER resistance breeding. Full article

Mixograph properties represent important quantitative traits that are controlled by multiple genes and influenced by environmental factors. In this study, we conducted quantitative trait locus (QTL) mapping for key Mixograph paraments using a recombinant inbred line (RIL) population derived from a cross between Yangxiaomai and Zhongyou 9507. Based on a high-density genetic map, six stable QTLs were identified on chromosomes 1A, 1B, and 1D across four environments, with individual phenotypic variation explained, ranging from 2.26 to 28.70%. Among these, QTh.ahau-1A, QMt/QPa.ahau-1B, and QTw.ahau-1D.1 are potentially novel loci. Furthermore, four functional Kompetitive Allele-Specific PCR (KASP) markers were developed based on tightly linked SNPs and validated in 110 advanced breeding lines, confirming their significant association with the target traits and utility for marker-assisted selection (MAS). Additionally, six candidate genes were predicted, which encoded proteins such as a hydroxyproline-rich glycoprotein, a CCCH-type zinc finger protein, protease, kinase, a phosphoglucan water dikinase, and a TRP-like family protein. Collectively, these findings provide valuable genetic loci, functional molecular markers, and candidate gene resources for improving wheat processing quality through MAS-based breeding. Full article

Fusarium ear rot (FER), caused by Fusarium verticillioides, is a devastating disease that substantially reduces maize yield and compromises kernel quality. To investigate the genetic and molecular basis of resistance, an F₂ population derived from a cross between the resistant inbred line 3IBZ2 and the susceptible inbred line KW5G321 was analysed. By integrating bulked segregant analysis sequencing (BSA-Seq) with RNA sequencing (RNA-Seq), a major quantitative trait locus (QTL), designated qFER4, was identified on chromosome 4. Genetic analysis further demonstrated that qFER4 confers resistance through partial dominance. Transcriptome profiling of the resistant line revealed 7684 and 7906 differentially expressed genes (DEGs) at 36 and 72 h post inoculation (hpi), respectively. These DEGs were significantly enriched in defence-related biological processes and pathways, including phenylpropanoid biosynthesis, jasmonic acid signalling, MAPK cascades, and plant-pathogen interactions. By combining QTL mapping with transcriptome analyses, four candidate genes within the qFER4 interval were screened. Sequence analysis identified extensive structural variations in the promoter and coding regions of Zm00001d053393, including a premature stop codon predicted to lead to a gain-of-function mutation. In contrast, the other three genes exhibited only minor promoter polymorphisms with identical coding sequences between the parental lines. Overall, this study identifies a novel major-effect QTL and candidate gene associated with FER resistance, providing a foundation for gene function and a valuable genetic resource for breeding FER-resistant maize varieties. Full article

Soybean (Glycine max L. Merr.) is a globally significant oilseed crop. The number of four-seeded pods in the lower part (FSPL) serves as a critical yield component under high-density planting. To date, numerous crop-specific traits have been investigated in multiple breeding studies of soybean; however, little attention has been paid to studies on FSPL. Hence, in this study, we investigated the genetic basis of FSPL using a recombinant inbred line population (RIL3613) across four environments. The segregated genetic mapping population was cultivated during the field experiments, and the collected phenotypic dataset of FSPL exhibited quantitative genetics and high broad-sense heritability (0.724), indicating stable genetic control. Further, we performed quantitative trait locus (QTL) mapping using raw means in each environment and identified 10 QTL, explaining phenotypic variations (PVE) ranging from 0.10% to 2.94%. Among the identified environmentally stable QTL, qFSPL-15-1 was consistently detected across all environments. Two candidate genes [Glyma.15G034100 (encoding lysophosphatidic acid acyltransferase 2) and Glyma.15G034200 (encoding an RNA-binding protein)] were predicted within the flanking genomic interval. The allele frequencies of haplotype combinations of Hap1: Pro2 + CDS1 for Glyma.15G034100 and Hap3: Pro3 + CDS1 for Glyma.15G034200 in wild soybeans (26.6–30.0%) were larger than improved cultivars (52.6–53.4%). We believe that our current findings elucidate the molecular mechanisms regulating lower-pod formation and provide precise genetic targets for marker-assisted selection in high-yield soybean breeding. Full article

Low-temperature stress during germination is a major constraint for lettuce establishment in temperate and early-season production systems, causing delayed emergence, poor stand uniformity, and reduced yield. Cold germination represents an adaptive trait that enables seeds to initiate growth under suboptimal temperatures, but its genetic basis in lettuce remains poorly understood. Here, we investigated genetic architecture underlying cold germination using a biparental recombinant inbred line population derived from a cross between Lactuca sativa cv. Salinas and Lactuca serriola (wild lettuce). Phenotypic evaluations revealed substantial variation in germination performance at low temperatures, with cultivated lettuce exhibiting superior cold germination compared with the wild parent. Estimates of heritability indicated that genetic factors accounted for a large proportion of the observed phenotypic variation, demonstrating strong potential for selection. Quantitative trait locus (QTL) analysis identified two genomic regions significantly associated with cold germination ability, together explaining a substantial fraction of phenotypic variance (35%). These regions contained candidate genes involved in hormone signaling, membrane stability, and stress-responsive transcriptional regulation, including components of abscisic acid (ABA), gibberellic acid (GA), and ethylene pathways known to modulate germination under adverse conditions. Together, these results indicate that cold germination is a genetically complex trait that has likely been shaped through domestication and breeding. By elucidating the genetic basis of cold germination in lettuce, this study provides valuable targets for marker-assisted breeding aimed at improving seedling establishment and extending lettuce production into cooler environments. Full article

Twin births in dairy cattle present challenges for producers, resulting in increased prevalence of health issues for both cows and calves, thereby impacting profitability. Genome-wide association study (GWAS) analyses of the twinning rate in Holstein cattle have reported the most significant genomic association with twinning rate in a region containing two strong candidate genes: follicle-stimulating hormone receptor (FSHR) and luteinizing hormone/chorionic gonadotropin receptor (LHCGR). Coding-sequence variants of these genes were not associated with the twinning rate, suggesting that one of the two genes is differentially expressed in association with the twinning rate. Granulosa cells were collected from 38 Holstein cows that were selected to provide similar representation of genotypes for the twinning rate quantitative trait locus (QTL). RNA was extracted from granulosa cells and gene expression was assessed by quantitative PCR with data analyzed by the ΔΔCT method. Association of gene expression with QTL genotype was tested by the Kruskal–Wallis test with the QTL genotype based on the SNP most significantly associated with twinning rate. QTL genotype was significantly associated (p = 1.88 × 10⁻⁸) with the expression of FSHR but was not associated with LHCGR expression (p = 0.18). The increased FSHR expression was associated with an increasing copy number of the G allele and thus an increased twinning rate. Full article

Given that nitrogen (N) is a major limiting factor for global crop production, improving low-nitrogen (LN) tolerance in barley is essential for sustaining yields worldwide. Building on our laboratory’s previous quantitative trait locus (QTL) mapping, which identified three LN-specific QTL clusters on chromosomes 2H and 5H, this study investigated the potential of gene pyramiding to improve LN tolerance. We generated two recombinant inbred line populations (C79 and F79) containing these QTLs and evaluated them for thirty-six traits related to yield, agronomy, and N, phosphorus (P), and potassium (K) uptake and utilization. The results confirmed that LN stress significantly reduced most yield, agronomic, and NPK-related traits. Under LN conditions, grain yield and accumulations of N, P, and K in the C79 population increased with the number of QTL clusters harbored by the lines. More compellingly, in the F79 population under LN stress, lines containing all three QTL clusters exhibited superior performance for critical yield components such as grain yield, spike number, grain number, and nutrient efficiency indices. Furthermore, in both populations, lines with the full QTL complement demonstrated higher values for harvest index, grain number, and K harvest index under LN stress than under normal-N conditions. In conclusion, this study is the first to link LN-QTL pyramiding with P and K use efficiency and demonstrates that pyramiding breeding can produce high-yielding barley varieties with enhanced LN tolerance and nutrient absorption capacity. Full article

Stem lodging critically limits wheat yield stability, with its resistance heavily influenced by internode mechanical strength, a trait whose genetic architecture remains poorly resolved. This study aimed to dissect the genetic basis of stem strength in the first three basal internodes of wheat. Using a panel of 224 cultivars, we measured internode strength across two environments and performed a genome-wide association study with 269,708 SNPs, employing the FarmCPU model. Three stable quantitative trait loci (QTL) associated with internode stem strength were identified: QI1SS.sau.5A, QI2SS.sau.2D, and QI2SS.sau.6B across a diverse wheat panel, with allele-dependent effects observed among accessions. Among them, QI2SS.sau.2D consistently enhanced stem strength across all three internodes, explaining up to 10.8% of phenotypic variance, without adverse effects on plant height or thousand-grain weight. In contrast, the other two QTL were associated with trade-offs, such as reduced plant height or grain weight. These results reveal a polygenic and partially internode-shared genetic regulation of stem strength. The locus QI2SS.sau.2D is highlighted as a particularly promising, penalty-free target for marker-assisted selection to improve lodging resistance while maintaining agronomic performance, including plant height and thousand-grain weight. Full article

Salinity–alkalinity stress is one of the major abiotic stresses that limit rice production in the world. The salinity–alkalinity tolerance of rice at the germination stage has a direct effect on the survival and final yield of seedlings in direct sowing. However, there are few reports of quantitative trait locus (QTL) mapping and mapping-based cloning of alkaline tolerance at the bud burst stage. Here, new alkaline tolerance loci were constructed for F_2:3 and BC₃F₄ by using IR36 and Long-Dao124 (LD124) rice varieties with significant differences in alkaline tolerance. Through linkage analysis and a fine-mapping strategy, qAT3 was identified as the major QTL for alkaline tolerance at the bud burst stage, which could explain 14.79% of the phenotypic variation on average. Then the interval was fine-mapped to 110.265 kb, and the candidate gene LOC_Os03g03150 was predicted by quantitative real-time polymerase chain reaction (qRT-PCR) analysis and sequencing analysis. This provides a key theory for the molecular breeding of alkali-tolerant genes and the study of the molecular mechanism of alkali tolerance in LD124. Full article

Flag leaf angle (FLA) in rice (Oryza sativa L.) is one of the important traits affecting F₁ seed production by mechanization. Here, we report the map-based cloning and functional characterization of the FLA1 (FLAG-LEAF-ANGLE 1) gene, which resides at a major-effect quantitative trait locus (QTL). Through cell morphological observations and exogenous hormone treatment assays, we demonstrate that gibberellin (GA) modulates rice FLA by altering both the number of cell layers and cell length. Combining genetic and molecular biological analyses with genetic complementation and gene overexpression assays, we elucidated and validated the biological function of FLA1. In addition, we found that FLA1 is constitutively expressed and encodes a protein localized to both the cell membrane and nucleus. Via RT-qPCR assays, we further demonstrated that the FLA1^fla-R allele from the rice accession fla-R enhances GA biosynthesis by upregulating the expression of CLA1 and GA20ox2. Furthermore, yeast two-hybrid assays revealed that auxin-repressed protein 1 (ARP1) interacts with FLA1, suggesting a potential role of this interaction in the modulation of rice FLA. Collectively, our results demonstrate that optimizing rice FLA via molecular manipulation of FLA1 can resolve the problem of flag leaf shearing during F₁ hybrid rice seed production without compromising F₁ hybrid seed yield, thereby facilitating mechanized F₁ hybrid rice seed production. Full article

Genome-wide association studies (GWAS) have transformed the study of chronic kidney disease (CKD) by identifying hundreds of genetic loci associated with multiple aspects of kidney function, including albuminuria and CKD risk factors, in diverse populations. A major challenge is translating statistically significant signals into causal genes and mechanisms, as most CKD-associated variants lie in non-coding regulatory regions and often act in a cell type- and context-specific manner. In this review, we provide an overview of the current strategies for moving from GWAS signals toward the identification of causal genes for CKD. We discuss advances in four areas: statistical and functional fine-mapping, molecular quantitative trait locus (QTL) mapping, colocalization, and transcriptome-wide associations, highlighting the advantages and disadvantages of each. We further examined how emerging kidney-specific single-cell, single-nucleus, and spatial transcriptomic atlases have enabled the mapping of genetic risk to specific renal cell types and microanatomical niches. By combining these approaches with chromatin interaction data, multi-omics analytics, and clustered regularly interspaced short palindromic repeats (CRISPR)-based studies, the process of generating causal relationships and mechanistic understanding has been further refined. Importantly, this review provides a unifying framework that synthesizes cross-sectional and longitudinal GWAS with kidney-specific functional genomics to distinguish genetic determinants of CKD susceptibility from modifiers of disease progression, thereby highlighting how regulatory variation and disease trajectories inform precision nephrology. As a result, we can provide insights into the role of genetically informed gene prioritization for experimentation, therapeutic target discovery, and the development of a framework for precision nephrology. Together, these advancements highlight how human genetics, in conjunction with functional genomics and experimental biology, can link an association signal to a clinically relevant interpretation of CKD. Full article

Wheat (Triticum aestivum L.) is one of the most important staple crops in the world. Iron (Fe) plays a vital role in the growth and development of wheat as an essential nutrient. Meanwhile, Fe is closely associated with human health, as Fe deficiency anemia can cause fatigue, weakness, heart problems, and so on. In this study, quantitative trait loci (QTLs) for grain Fe content (GFeC) were detected in two populations: a recombinant inbred line (RIL) population with 175 lines derived from a cross between Avocet and Huites (AH population) genotyped with diversity array technology (DArT) and a natural population of 243 varieties (CH population) genotyped by using the 660K single-nucleotide polymorphism (SNP). Three stable QTLs (QGFe.haust-AH-5B, QGFe.haust-AH-6A, and QGFe.haust-AH-7A.2) were identified through QTL mapping with phenotypic variations of 11.55–13.63%, 3.58–9.89%, and 4.81–11.12% in the AH population in four environments. Genetic effects of QGFe.haust-AH-5B, QGFe.haust-AH-6A, and QGFe.haust-AH-7A.2 were shown to significantly increase GFeC by 8.11%, 14.05%, and 5.25%, respectively. One hundred and thirty-three significant SNPs were identified (p < 0.001) through a genome-wide association study (GWAS) for GFeC on chromosomes 1B, 2B, 3A, 3B, 5D, and 7A with phenotypic variations of 5.26–9.88% in the CH population. A novel locus was co-located within the physical interval 689.86 Mb-690.01 Mb in five environments through QTL mapping and GWAS, with one high-confidence gene, TraesCS7A02G499500, which was temporarily designated as TaqFe-7A, involved in GFeC regulation. A Kompetitive allele-specific PCR, KAFe-7A-2, was developed, which was validated in 181 natural populations. Genetic effect analysis revealed that favorable haplotype AA significantly increased GFeC by 4.64% compared to an unfavorable haplotype (p < 0.05). Therefore, this study provides the theoretical basis for cloning the GFeC gene and nutritional fortification breeding. Full article