Search Results (284)

Plant-parasitic nematodes (PPNs) pose a significant threat to agricultural production and global food security. To mitigate this challenge, quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS) have been extensively employed in crop resistance breeding research. These methods have identified resistance-related genes and genetic markers, offering a solid scientific basis and practical tools for resistance breeding. This review summarizes recent advances in QTL and GWAS applications for enhancing resistance to cyst nematodes (Heterodera glycines, H. filipjevi, and H. avenae), root-knot nematodes (Meloidogyne graminicola and M. incognita), and root-lesion nematodes (Pratylenchus spp.). It also evaluates the commercial deployment of resistance genes, discusses integrated breeding strategies, and highlights future research directions toward developing durable nematode-resistant crops. Full article

Genome-wide association studies (GWAS) have been a successful tool for identifying quantitative trait loci (QTL) for economically important traits in dairy cows. However, the availability of QTLs linked to phenotypic traits is limited in the literature. In this study, we used GWAS, haplotype association, and fine-mapping analyses to identify candidate variants associated with milk production, health, and reproductive traits in 380 Chinese Holstein cattle from Southern China using whole-genome sequence data. GWAS identified 91 genome-wide significant signals that were annotated to 63 genes associated with milk production, health, and reproductive traits in dairy cattle. Haplotype association analysis further revealed that eight GWAS signals within three QTLs were associated with milk production and health traits of cows. Fine-mapping analysis revealed that 3 GWAS signals (6_92530313_G_A, 10_17185230_G_A, and 10_17209112_T_G) were the potential causal variants. Several candidate genes, including ANKS1B, IL17RD, CNOT6L, AOC1, and TLE3, have been confirmed to be associated with milk production, health, and reproductive traits in dairy cows. These findings significantly contribute to unraveling the genetic basis of economically important traits in Holstein cattle. Full article

The field of bacterial systems biology is rapidly advancing beyond static genomic analyses, and moving toward dynamic, integrative approaches that connect genetic variation with cellular function. This review traces the progression from genome-wide association studies (GWAS) to multi-omics frameworks that incorporate transcriptomics, proteomics, and interactome mapping. We emphasize recent breakthroughs in high-resolution transcriptomics, including single-cell, spatial, and epitranscriptomic technologies, which uncover functional heterogeneity and regulatory complexity in bacterial populations. At the same time, innovations in proteomics, such as data-independent acquisition (DIA) and single-bacterium proteomics, provide quantitative insights into protein-level mechanisms. Experimental and AI-assisted strategies for mapping protein–protein interactions help to clarify the architecture of bacterial molecular networks. The integration of these omics layers through quantitative trait locus (QTL) analysis establishes mechanistic links between single-nucleotide polymorphisms and systems-level phenotypes. Despite persistent challenges such as bacterial clonality and genomic plasticity, emerging tools, including deep mutational scanning, microfluidics, high-throughput genome editing, and machine-learning approaches, are enhancing the resolution and scope of bacterial genetics. By synthesizing these advances, we describe a transformative trajectory toward predictive, systems-level models of bacterial life. This perspective opens new opportunities in antimicrobial discovery, microbial engineering, and ecological research. Full article

Stalk lodging constitutes a primary constraint on achieving consistently high yields in maize. Genetic improvement of lodging resistance requires the identification of stable quantitative trait loci (QTL) to facilitate the application of genomics-assisted breeding for improving selection efficiency in breeding programs. In this study, we performed a meta-analysis to identify consensus loci and functionally characterized candidate genes associated with stalk lodging-related traits. Through meta-analysis integrating 889 reported lodging-related QTLs using the IBM2 2008 Neighbors high-density genetic map, we identified 67 meta-QTLs (MQTLs), of which 32 were determined as core MQTLs. Among them, 67% were validated by co-localized marker–trait associations from genome-wide association studies (GWAS). Comparative genomics further revealed 40 evolutionarily conserved orthologs via protein alignment with rice lodging genes, while screening of core MQTL regions detected 802 candidate genes with KEGG enrichment implicating galactose degradation II in cell wall reinforcement, supported by transcriptomic evidence of their roles in lignin biosynthesis pathways modulating mechanical strength. In conclusion, the MQTL identified and validated in our study have significant scope in marker-assisted selection (MAS) breeding and map-based cloning programs for improving maize stalk lodging. Full article

Understanding the genetic architecture of complex traits is crucial for crop improvement and molecular breeding. We developed a mutagenized soybean population using carbon ion beam irradiation and conducted genome-wide association studies (GWAS) to identify variants controlling key agronomic traits. Whole-genome resequencing of 199 M4 lines revealed 1.48 million SNPs, predominantly C→T transitions, with population structure analysis identifying three distinct genetic groups. GWAS across five traits revealed striking differences in genetic architecture: the podding habit showed extreme polygenic control with 87,029 significant associations of small effect, while pubescence color exhibited oligogenic inheritance with only 122 variants. Hundred-seed weight displayed moderate complexity (4637 associations) with the largest effect sizes (−3.74 to 5.03) and major QTLs on chromosomes 4, 7, and 15–20. Growth habit involved 12,136 SNPs, including a strong chromosome 3 association (−log₁₀(p-value) > 50). Flower color showed 2662 associations clustered on chromosome 15. Functional analysis of 18,542 candidate genes revealed trait-specific pathway enrichments: flavonoid biosynthesis for flower color, phloem transport for seed weight, auxin signaling for growth habit, and amino acid transport for podding habit. This study demonstrates how mutagenesis-induced variation, combined with association mapping, reveals evolutionary constraints that shape genetic architectures, providing insights for genetics-assisted breeding strategies. Full article

Background/Objectives: Global maize production is considerably affected by drought aggravated by climate change. No genome-wide association study (GWAS) or candidate gene analysis has been performed using chlorophyll fluorescence (ChlF) and hyperspectral (HS) indices measured in young plants challenged by a water deficit. Our objective was to conduct a GWAS of nine ChlF and HS indices measured in a diversity panel of drought-stressed young plants grown in a controlled environment using a maize single nucleotide polymorphism (SNP) 50k chip. Methods: A total of 165 inbred lines were genotyped using the Infinium Maize50K SNP array and association mapping was carried out using a mixed linear model. Results: The GWAS detected 37 respective SNP markers significantly associated with the maximum quantum yield of the primary photochemistry of a dark-adapted leaf (Phi_Po), the probability that a trapped exciton moves an electron into the electron transport chain further than QA (Psi_o), the normalized difference vegetation index (NDVI), the Zarco–Tejada and Miller Index (ZMI), greenness, modified chlorophyll absorption in reflectance (MCARI), modified chlorophyll absorption in reflectance 1 (MCARI1), and Gitelson and Merzlyak indices 1 and 2 (GM1 and GM2). Conclusions: Our results contribute to a better understanding of the genetic dissection of the ChlF and HS indices, which is directly or indirectly related to physiological processes in maize, supporting the use of HS imaging in the context of maize breeding. Full article

As the fourth-largest global food crop, the quality and functional characteristics of processed potato products are closely linked to endogenous sugar metabolism in tubers, with the trehalose–sucrose metabolism playing a key role in processing adaptability. This study analyzed 333 accessions from a tetraploid potato natural population. The trehalose and sucrose content of potato tubers at harvest was quantified using the high-performance liquid chromatography (HPLC) method. Combined with whole-genome resequencing, a genome-wide association study (GWAS) was conducted to map regulatory loci and identify candidate genes. The results showed that relative trehalose content in tubers was 20.38–24.78, while relative sucrose content was 10.32–19.50. Frequency histograms for both sugars exhibited normal distributions characteristic of quantitative traits, and a positive correlation was observed between them. GWAS for trehalose identified 111 significant SNP loci, mainly on chromosomes 10 and 12, leading to the identification of 88 candidate genes. Kyoto encyclopedia of genes and genomes analysis (KEGG) revealed that trehalose-related genes were primarily involved in pathways such as ABC transporters, tricarboxylic acid (TCA) cycle, and cysteine and methionine metabolism. Candidate genes potentially regulating tuber trehalose content included GH10, GH28, GH127, UXS, UGT, PMEI, and MYB108. For sucrose, GWAS identified 279 significant SNP loci, mainly on chromosomes 5, 6, and 12, resulting in 111 candidate genes. KEGG enrichment analysis showed that sucrose-related genes were enriched in pathways including starch and sucrose metabolism, cyanoamino acid metabolism, and phenylpropanoid biosynthesis. Candidate genes potentially regulating tuber sucrose content included GH17, GH31,GH47, GH9A4, SPP1, BGLU12, GSA1, TPS8, cwINV4, HXK, UST, MYB5, MYB14, and WRKY11. Therefore, this study provides marker loci for trehalose and sucrose metabolism research, aiming to clarify their regulatory mechanisms and support potato variety improvement and superior germplasm development. Full article

As the laying cycle is prolonged, the egg albumen quality exhibits a declining trend. A Haugh unit (HU) is a standard measure of the albumen quality, which reflects viscosity and freshness. During the late laying period, the HU not only decreased significantly, but also exhibited greater variability among individuals. The magnum, as the primary site of albumen synthesis, plays a central role in this process; however, the mechanisms by which it regulates the albumen quality remain unclear. To address this, we obtained genomic and transcriptomic data from 254 individuals, along with single-cell RNA sequencing (scRNA-seq) data of the magnum tissue. Genome-wide association studies (GWAS) across five laying stages (66, 72, 80, 90, and 100 weeks of age) identified 77 HU-associated single-nucleotide polymorphisms (SNPs). Expression quantitative trait locus (eQTL) mapping linked these variants to the expression of 12 genes in magnum tissue. In addition, transcriptomic analysis using linear regression and random forest models identified 259 genes that significantly correlated with the HU. Single-cell RNA sequencing further revealed two key cell types, plasma cells and a subset of epithelial cells, marked by ADAMTSL1 and OVAL, which are functionally relevant to the HU. Through integrated Transcriptome-Wide Association Study (TWAS) and Summary-data-based Mendelian Randomization (SMR) analyses, we identified four robust regulators of the albumen quality: CISD1, NQO2, SLC22A23, and CMTM6. These genes are functionally involved in mitochondrial function, antioxidant defense, and membrane transport. Overall, our findings uncovered the genetic and cellular mechanisms underlying age-related decline in the albumen quality and identified potential targets for improving the egg quality in aging flocks. Full article

Aflatoxin contamination, primarily caused by Aspergillus flavus, poses a significant threat to peanut (Arachis hypogaea L.) production, food safety, and global trade. Despite extensive efforts, breeding for durable resistance remains difficult due to the polygenic and environmentally sensitive nature of resistance. Although germplasm such as J11 have shown partial resistance, none of the identified lines demonstrated stable or comprehensive protection across diverse environments. Resistance involves physical barriers, biochemical defenses, and suppression of toxin biosynthesis. However, these traits typically exhibit modest effects and are strongly influenced by genotype–environment interactions. A paradigm shift is underway with increasing focus on host susceptibility (S) genes, native peanut genes exploited by A. flavus to facilitate colonization or toxin production. Recent studies have identified promising S gene candidates such as AhS5H1/2, which suppress salicylic acid-mediated defense, and ABR1, a negative regulator of ABA signaling. Disrupting such genes through gene editing holds potential for broad-spectrum resistance. To advance resistance breeding, an integrated pipeline is essential. This includes phenotyping diverse germplasm under stress conditions, mapping resistance loci using QTL and GWAS, and applying multi-omics platforms to identify candidate genes. Functional validation using CRISPR/Cas9, Cas12a, base editors, and prime editing allows precise gene targeting. Validated genes can be introgressed into elite lines through breeding by marker-assisted and genomic selection, accelerating the breeding of aflatoxin-resistant peanut varieties. This review highlights recent advances in peanut aflatoxin resistance research, emphasizing susceptibility gene targeting and genome editing. Integrating conventional breeding with multi-omics and precision biotechnology offers a promising path toward developing aflatoxin-free peanut cultivars. Full article

Seed oil represents a key trait in soybeans, which holds substantial economic significance, contributing to roughly 60% of global oilseed production. This research employed genome-wide association mapping to identify genetic loci associated with oil content in soybean seeds. A panel comprising 341 soybean accessions, primarily sourced from Northeast China, was assessed for seed oil content at Heilongjiang Province in three replications over two growing seasons (2021 and 2023) and underwent genotyping via whole-genome resequencing, resulting in 1,048,576 high-quality SNP markers. Phenotypic analysis indicated notable variation in oil content, ranging from 11.00% to 21.77%, with an average increase of 1.73% to 2.28% across all growing regions between 2021 and 2023. A genome-wide association study (GWAS) analysis revealed 119 significant single-nucleotide polymorphism (SNP) loci associated with oil content, with a prominent cluster of 77 SNPs located on chromosome 8. Candidate gene analysis identified four key genes potentially implicated in oil content regulation, selected based on proximity to significant SNPs (≤10 kb) and functional annotation related to lipid metabolism and signal transduction. Notably, Glyma.08G123500, encoding a receptor-like kinase involved in signal transduction, contained multiple significant SNPs with PROVEAN scores ranging from deleterious (−1.633) to neutral (0.933), indicating complex functional impacts on protein function. Additional candidate genes include Glyma.08G110000 (hydroxycinnamoyl-CoA transferase), Glyma.08G117400 (PPR repeat protein), and Glyma.08G117600 (WD40 repeat protein), each showing distinct expression patterns and functional roles. Some SNP clusters were associated with increased oil content, while others correlated with decreased oil content, indicating complex genetic regulation of this trait. The findings provide molecular markers with potential for marker-assisted selection (MAS) in breeding programs aimed at increasing soybean oil content and enhancing our understanding of the genetic architecture governing this critical agricultural trait. Full article

Vegetable oils are essential for human nutrition and industrial applications. With growing global demand, increasing oil content in oilseed crops has become a top priority. This review synthesizes recent progress in understanding the genetic, environmental, and molecular mechanisms regulating oil content, and presents biotechnological strategies to enhance oil accumulation in major oilseed crops. Oil biosynthesis is governed by intricate genetic–environmental interactions. Environmental factors and agronomic practices significantly impact oil accumulation dynamics. Quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) have identified key loci and candidate genes involved in lipid biosynthesis pathways. Transcription factors and epigenetic regulators further fine-tune oil accumulation. Biotechnological approaches, including marker-assisted selection (MAS) and CRISPR/Cas9-mediated genome editing, have successfully generated high-oil-content variants. Future research should integrate multi-omics data, leverage AI-based predictive breeding, and apply precision genome editing to optimize oil yield while maintaining seed quality. This review provides critical references for the genetic improvement and breeding of high- and ultra-high-oil-content varieties in oilseed crops. Full article

Enhancing quality traits is a primary objective in silage maize breeding programs. The use of genome-wide association studies (GWAS) for quality traits, in combination with the integration of genetic resources, presents an opportunity to identify crucial genomic regions and candidate genes influencing silage maize quality. In this study, a GWAS was conducted on 580 inbred lines of silage maize, and a meta-analysis was performed on 477 quantitative trait loci (QTLs) from 34 studies. The analysis identified 27 significant single nucleotide polymorphisms (SNPs) and 87 consensus QTLs (cQTLs), with 7 cQTLs associated with multiple quality traits. By integrating the SNPs identified through association mapping, one SNP was found to overlap with the cQTL interval related to crude protein, neutral detergent fiber, and starch content. Furthermore, enrichment analysis predicted 300 and 5669 candidate genes through GWAS and meta-analysis, respectively, highlighting pathways such as cellular metabolism, the biosynthesis of secondary metabolites, ribosome function, carbon metabolism, protein processing in the endoplasmic reticulum, and amino acid biosynthesis. The examination of 13 candidate genes from three co-located regions revealed Zm00001d050977 as a cytochrome P450 family gene, while the other 2 genes primarily encode proteins involved in stress responses and other biological pathways. In conclusion, this research presents a methodology combining GWAS and meta-analysis to identify genomic regions and potential genes influencing quality traits in silage maize. These findings serve as a foundation for the identification of significant QTLs and candidate genes crucial for improving silage maize quality. Full article

Soybean (Glycine max) peptide lunasin exhibits significant cancer-preventive, antioxidant, and hypocholesterolemic effects. This study aimed to identify quantitative trait nucleotides (QTNs) associated with lunasin content and to annotate the candidate genes in the soybean genome. The mapping panel of 144 accessions was gathered from the USDA Soybean Germplasm Collection, encompassing diverse geographical origins and genetic backgrounds, and was genotyped using SoySNP50K iSelect Beadchips. The lunasin content in soybean seeds was measured using the enzyme-linked immunosorbent assay (ELISA) method, with lipid-adjusted soybean flour prepared from seeds obtained from the Germplasm Resource Information Network (GRIN) of USDA-ARS in 2003 and from North Carolina in 2021, respectively. QTNs significantly related to lunasin content in soybean seeds were detected on 15 chromosomes, with LOD scores greater than 3.0, explaining various phenotypic variations identified using the R package mrMLM (v4.0). Significant QTNs on chromosomes 3, 13, 16, 18, and 20 were consistently identified across multiple models as being significantly associated with soybean lunasin content, based on assessment data from two years. Twenty-nine candidate genes were found, with 12 identified in seeds from 2003 and 17 from 2021. Our study is an important effort to understand the genetic basis and functional genes for lunasin production in soybean seeds. Full article

Growth traits are the most important economic traits in red tilapia (Oreochromis spp.) production, and are the main targets for its genetic improvement. Increasing salinity levels in the environment are affecting the growth, development, and molecular processes of aquatic animals. Red tilapia tolerates saline water to some degree. However, few credible genetic markers or potential genes are available for choosing fast-growth traits in salt-tolerant red tilapia. This work used genome-wide association study (GWAS) and RNA-sequencing (RNA-seq) to discover genes related to four growth traits in red tilapia cultured in saline water. Through genotyping, it was determined that 22 chromosomes have 12,776,921 high-quality single-nucleotide polymorphisms (SNPs). One significant SNP and eight suggestive SNPs were obtained, explaining 0.0019% to 0.3873% of phenotypic variance. A significant SNP peak associated with red tilapia growth traits was located on chr7 (chr7-47464467), and plxnb2 was identified as the candidate gene in this region. A total of 501 differentially expressed genes (DEGs) were found in the muscle of fast-growing individuals compared to those of slow-growing ones, according to a transcriptome analysis. Combining the findings of the GWAS and RNA-seq analysis, 11 candidate genes were identified, namely galnt9, esrrg, map7, mtfr2, kcnj8, fhit, dnm1, cald1, plxnb2, nuak1, and bpgm. These genes were involved in ‘other types of O-glycan biosynthesis’, ‘glycine, serine and threonine metabolism’, ‘glycolysis/gluconeogenesis’, ‘mucin-type O-glycan biosynthesis’ and ‘purine metabolism signaling’ pathways. We have developed molecular markers to genetically breed red tilapia that grow quickly in salty water. Our study lays the foundation for the future marker-assisted selection of growth traits in salt-tolerant red tilapia. Full article

The coronavirus disease 2019 (COVID-19) pandemic has led to substantial health and financial burdens worldwide, and vaccines provide hope for reducing the burden of this pandemic. However, vaccinated people remain at risk for SARS-CoV-2 infection. Genome-wide association studies (GWASs) may identify potential genetic factors involved in the development of COVID-19 breakthrough infections (BIs); however, very few or no GWASs have been conducted for COVID-19 BI thus far. We conducted a GWAS and detailed bioinformatics analysis on COVID-19 BIs in a European population via the UK Biobank (UKBB). We conducted a series of analyses at different levels, including SNP-based, gene-based, pathway, and transcriptome-wide association analyses, to investigate genetic factors associated with COVID-19 BIs and hospitalized infections. The polygenic risk score (PRS) and Hoeffding’s test were performed to reveal the genetic relationships between BIs and other medical conditions. Two independent loci (LD-clumped at r² = 0.01) reached genome-wide significance (p < 5 × 10⁻⁸), including rs36170929, which mapped to LOC102725191/VWDE, and rs28645263, which mapped to RETREG1. A pathway enrichment analysis highlighted pathways such as viral myocarditis, Rho-selective guanine exchange factor AKAP13 signaling, and lipid metabolism. The PRS analyses revealed significant genetic overlap between COVID-19 BIs and heart failure and between HbA1c and type 1 diabetes. Genetic dependence was also observed between COVID-19 BIs and asthma, lung abnormalities, schizophrenia, and type 1 diabetes on the basis of Hoeffding’s test. This GWAS revealed two significant loci that may be associated with COVID-19 BIs and a number of genes and pathways that may be involved in BIs. Genetic overlap with other diseases was identified. Further studies are warranted to replicate these findings and elucidate the mechanisms involved. Full article