Search Results (33)

Obesity is a highly complex, multifactorial disease influenced by dynamic interactions among genetic, epigenetic, environmental, and behavioral determinants that explicitly position genetics as the core. While advances in multi-omic integration have revolutionized our understanding of adiposity pathways, translation into personalized clinical nutrition remains a critical challenge. This review systematically consolidates emerging insights into the molecular and nutrigenomic architecture of obesity by integrating data from large-scale GWAS, functional epigenomics, nutrigenetic interactions, and microbiome-mediated metabolic programming. The primary aim is to systematically organize and synthesize recent genetic and genomic findings in obesity, while also highlighting how these discoveries can be contextualized within precision nutrition frameworks. A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science up to July 2024 using MeSH terms, nutrigenomic-specific queries, and multi-omics filters. Eligible studies were classified into five domains: monogenic obesity, polygenic GWAS findings, epigenomic regulation, nutrigenomic signatures, and gut microbiome contributions. Over 127 candidate genes and 253 QTLs have been implicated in obesity susceptibility. Monogenic variants (e.g., LEP, LEPR, MC4R, POMC, PCSK1) explain rare, early-onset phenotypes, while FTO (polygenic) and MC4R (monogenic mutations as well as common polygenic variants) represent major loci across populations. Epigenetic mechanisms, dietary composition, physical activity, and microbial diversity significantly recalibrate obesity trajectories. Integration of genomics, functional epigenomics, precision nutrigenomics, and microbiome science presents transformative opportunities for personalized obesity interventions. However, translation into evidence-based clinical nutrition remains limited, emphasizing the need for functional validation, cross-ancestry mapping, and AI-driven precision frameworks. Specifically, this review systematically identifies and integrates evidence from genomics, epigenomics, nutrigenomics, and microbiome studies published between 2000 and 2024, applying structured inclusion/exclusion criteria and narrative synthesis to highlight translational pathways for precision nutrition. Full article

Plant height is a key agronomic trait influencing both seed production and yield in hybrid rice. In the elite japonica hybrid ‘Shenyou 26’, optimal plant height differences between the restorer line (‘Shenhui 26’) and the male sterile line (‘Shen 9A’) are critical for efficient pollination. In this study, we dissected the genetic basis of plant height variation using a doubled haploid (DH) population derived from ‘Shenyou 26’. Multi-environment phenotyping and QTL mapping identified seven QTLs associated with plant height, among which qPH1.1 and qPH9.1 were validated. qPH1.1 co-localized with the semi-dwarf gene SD1, and ‘Shen 9A’ carries a rare SD1-EQH allele that potentially confers reduced height relative to the SD1-EQ allele in ‘Shenhui 26’. qPH9.1 also contributed significantly to plant height variation, with the Shenhui26 allele increasing plant height in backcross validation. These findings indicate that plant height variation in ‘Shenyou 26’ is controlled by multiple loci, including SD1 allelic variants and other complementary QTLs, providing valuable resources for fine-tuning plant architecture in rice breeding. Full article

Potato (Solanum tuberosum L.) is a globally important food crop, but its tetrasomic inheritance and diploid self-incompatibility have limited the discovery of potato genes and progress in breeding. Here, we developed an F₂ segregating population consisting of 174 lines by crossing a self-compatible genome-homozygous diploid line (Y8, female parent) with a heterozygous diploid line (IVP101, male parent), followed by selfing. Using whole-genome resequencing, we constructed a high-density genetic map containing 4464 recombinant bin markers with an average physical distance of 165.51 Kb. Phenotypic evaluation of 8 traits related to yield, tuber shape, and tuber eye number across three environments revealed significant parental differences and wide phenotypic variation within the F₂ population. QTL (Quantitative trait loci) mapping using this genetic map and multi-environment phenotypic data identified 89 QTLs, including 7 previously reported QTLs/genes. In addition, 10 QTLs were stably detected across multiple seasons (stable QTLs). Further genetic effect analysis showed that favorable alleles of these stable QTLs significantly enhanced phenotypic values. Notably, two pleiotropic QTLs were identified on chromosomes 5 and 12; the major-effect QTL on chromosome 12 (qTY-12-6, qTS-12-3, and qTE-12-4) exhibited high phenotypic variance explained (PVE). Its favorable allele from Y8 significantly increased mean tuber weight, tuber number per plant, and promoted rounder tuber shape while reducing eye number, simultaneously improving yield and quality. Collectively, this study provides a reference for genetic mapping using homozygous and heterozygous diploid parents, and the identified QTLs offer valuable genetic resources for potato breeding and molecular mechanism research, enhancing our understanding of the genetic regulation of yield, tuber shape, and eye number in potato. 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

Wheat stripe rust (Puccinia striiformis f. sp. tritici, Pst) resistance and agronomic traits are crucial determinants of wheat yield. Elucidating the quantitative trait loci (QTLs) associated with these essential traits can furnish valuable genetic resources for improving both the yield potential and disease resistance in wheat. Lantian 31 is an excellent Chinese winter wheat cultivar; multi-environment phenotyping across three ecological regions (2022–2024) confirmed stable adult-plant resistance (IT 1–2; DS < 30%) against predominant Chinese Pst races (CYR31–CYR34), alongside superior thousand-kernel weight (TKW) and kernel morphology. Here, we dissected the genetic architecture of these traits using a total of 234 recombinant inbred lines (RILs) derived from a cross between Lantian 31 and the susceptible cultivar Avocet S (AvS). Genotyping with a 15K SNP array, complemented by 660K SNP-derived KASP and SSR markers, identified four stable QTLs for stripe rust resistance (QYrlt.swust-1B, -1D, -2D, -6B) and eight QTLs governing plant height (PH), spike length (SL), and kernel traits. Notably, QYrlt.swust-1B (1BL; 29.9% phenotypic variance) likely represents the pleiotropic Yr29/Lr46 locus, while QYrlt.swust-1D (1DL; 22.9% variance) is the first reported APR locus on chromosome 1DL. A pleiotropic cluster on 1B (670.4–689.9 Mb) concurrently enhanced the TKW and the kernel width and area, demonstrating Lantian 31’s dual utility as a resistance and yield donor. The integrated genotyping pipeline—combining 15K SNP discovery, 660K SNP fine-mapping, and KASP validation—precisely delimited QYrlt.swust-1B to a 1.5 Mb interval, offering a cost-effective model for QTL resolution in common wheat. This work provides breeder-friendly markers and a genetic roadmap for pyramiding durable resistance and yield traits in wheat breeding programs. Full article

Rice tillering is an important trait that is genetically and environmentally co-regulated. Nitorgen is one of the key nutrients affecting tillering, and straw return further affects tiller development by altering soil heterogeneity. In order to analyze the genetic regulation mechanism of rice tillering and its interactions with the environment, 124 recombinant inbred line (RIL) populations derived from two superior Peijiu lines, 9311 and PA64s, were used as materials in this study, and the dynamic tillering phenotypes were measured under three treatments (no nitrogen application, nitrogen application, and nitrogen + straw return) for two consecutive years. Using an existing genetic map, we conducted single-environment, multi-environment, and meta-QTL analyses to systematically identify tiller-related genetic loci and their environmental interactions. The main findings were as follows: (1) A total of 57 QTLs were identified in the single-environment QTL analysis, of which 44 were unreported new QTLs. Four QTLs showed temporal pleiotropy, ten QTLs contributed more than 10% to the phenotypes under the no-N treatment, and five QTLs contributed more than 10% under the straw return treatment. Among them, the phenotypic contribution of mks1-355 (qD1tn1-3) and mks1-352 (qD2TN1-2) both exceeded 40%. (2) Multi-environmental QTL analysis detected 15 QTLs. Of these, qmD1TN1 (mks1-356) showed no environmental interaction effect, while qmD1TN12 (mks12-267), qmD2TN1 (mks1-334), qmD2TN3-1 (mks3-105), and qmD5TN6 (mks6-71) exhibited antagonistic pleiotropy, suggesting that these QTL need to be considered for environmental specificity in breeding. (3) Meta-QTL analysis localized 52 MQTLs, of which MQTL3.1 and MQTL6.8 contained 82 and 59 candidate genes, respectively, and no reported tiller-related genes were found. (4) mks1-355 (qD1tn1-3), mks1-352 (qD2TN1-2), and mks1-356 (qmD1TN1) may be located in the same genetic locus, and their phenotypic contributions were more than 40%. These QTLs were detected stably for two consecutive years, and they may be the main effector QTLs in tillering that are less affected by the environment. Further analysis revealed that these QTLs corresponded to MQTL1.6, which contains 56 candidate genes. Of these, the expression level of OsSPL2 gene in the parental line 9311 was significantly higher than that of PA64s, and there were polymorphic differences in the coding region. It was hypothesized that OsSPL2 was the main effector gene of this QTL. This study provides important genetic resources for mining candidate genes related to tillering and nitrogen efficiency in rice and lays a theoretical foundation for directional breeding and molecular marker development in specific environments. Full article

The Multi-Parent Advanced Generation Inter-Cross (MAGIC) population is a powerful tool for dissecting the genetic architecture controlling natural variation in complex traits. In this work, the natural variation available in Arabidopsis thaliana MAGIC lines was evaluated by mapping quantitative trait loci (QTLs) for primary root length (PRL), lateral root number (LRN), lateral root length (LRL), adventitious root number (ARN), and adventitious root length (ARL). We analyzed the differences in the root structure of 139 MAGIC lines by measuring PRL, LRN, LRL, ARN, and ARL. Through QTL mapping, we identified new potential genes that may be responsible for these traits. Furthermore, we detected single-nucleotide polymorphisms (SNPs) in the coding regions of candidate genes in the founder accessions and the recombinant inbred lines (RILs). We identified a significant region on chromosome 1 associated with AR formation. This region encompasses 316 genes, many of which are involved in auxin and gibberellin signaling and homeostasis. We discovered SNPs in the coding regions of these candidate genes in the founder accessions that may contribute to natural variation in AR characteristics. Additionally, we found a novel gene that encodes a protein from the hydroxyproline-rich glycoprotein family, which exhibits differential SNPs in accessions with contrasting AR formation. This study provides genetic insights into the natural variation in AR numbers using MAGIC lines linked to hormone-related genes. Full article

Background/Objectives: Diabetic kidney disease (DKD) is a common diabetic complication, driven by a multifactorial pathogenesis that includes various genetic components. However, the precise causative genes and their underlying biological pathways remain poorly understood. Methods: We performed a cross-tissue transcriptome-wide association study (TWAS) of DKD using expression quantitative trait loci (eQTL) data from 49 tissues in the Genotype—Tissue Expression (GTEx) version 8 (v8) resource. Five complementary analytical frameworks—sparse canonical correlation analysis (sCCA), functional summary-based imputation (FUSION), fine-mapping of causal gene sets (FOCUS), summary-data-based Mendelian randomization (SMR), and multi-marker analysis of genomic annotation (MAGMA)—were integrated to nominate candidate genes. Causal inference was refined using Mendelian randomization (MR), and biological significance was evaluated through pathway enrichment, protein interaction networks, and druggability profiling. Results: We identified 23 candidate genes associated with DKD risk, of which 13 were supported by MR analysis. Among these, 10 represent previously unreported susceptibility genes. Notably, four genes—HLA-DRB1, HLA-DRB5, NOTCH4, and CYP21A2—encode potentially druggable proteins, with HLA-DRB5 and CYP21A2 both qualifying as novel susceptibility genes and therapeutic targets. These genes converge on immune modulation, steroid biosynthesis, DNA repair, and transcriptional regulation—processes central to DKD pathogenesis. Conclusions: Our study represents the first systematic cross-tissue TWAS of DKD, revealing a prioritized set of genetically and functionally supported susceptibility genes. The identification of druggable targets among these genes provides critical insight into the mechanistic underpinnings of DKD and highlights their potential for future therapeutic development. These findings enhance our understanding of DKD pathophysiology and offer a foundation for precision medicine strategies in nephrology. Full article

Rice is a major crop for half of the world’s population, and nitrogen (N) fertilizers play a crucial role in its production. However, imbalanced N fertilizer uses and traditional fertilization practices have led to low nitrogen use efficiency (NUE), increased N footprints, and reduced rice yields and farmers’ income. There are limited studies where the integration of both agronomic and molecular advancements to enhance NUE is discussed, particularly in developing countries. This review highlights novel agronomic and molecular strategies to enhance NUE, rice yields, and profitability, while minimizing environmental impact. The agronomic strategies include the 4R Nutrient Stewardship framework, enhanced efficiency nitrogen fertilizers (EENFs), nano-fertilizers, biochar-based fertilizers, biological N fixation, and sensor-based fertilizer management in major rice-growing countries. The molecular mechanisms focus on N uptake, assimilation, and utilization, highlighting the role of hormones, key genes, transcription factors (TFs), and regulatory pathways. Moreover, we examine promising rice genotypes and cultivars with improved NUE and grain yield. Additionally, this paper offers deep insights into recent advancements in molecular genetics, such as multi-omics approaches (transcriptomics, metabolomics, and metagenomics), the Genome-Wide Association Study (GWAS), Quantitative Traits Loci mapping (QTLs), Single Nucleotide Polymorphisms (SNPs) analysis, and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR-Cas9)-mediated genome editing, which serve as valuable tools for developing rice cultivars with enhanced NUE and grain yield. Full article

Fusarium head blight (FHB), caused by Fusarium graminearum, is a globally significant disease that severely impacts the yield and quality of wheat. Breeding resistant wheat varieties using resistance genes is the most cost-effective strategy for managing FHB, but few markers are available for marker-assisted selection (MAS) of resistance. In this study, we evaluated the resistance of a recombinant inbred line (RIL) population to FHB through single-floret inoculation in four field environments over two years. Combined with quantitative trait loci (QTL) detection through high-density genetic mapping based on wheat 50 K SNP arrays, we identified a total of 21 QTLs influencing FHB resistance. It is worth noting that QFhba-5D.2-1 was detected in two field environments as well as in the multi-environment trial (MET) analysis, explaining phenotypic variation ranging from 1.98% to 18.55%. We also pinpointed thirteen resistance genes within the QTL intervals on chromosomes 4A, 5D, 6B, and 7A associated with FHB defense mechanisms. Furthermore, we developed two Kompetitive Allele-Specific PCR (KASP) markers for the QFhba-5D.2-1 and QFhba-7A regions to validate their specificity within the RIL population. Subsequently, we validated the polymorphism of these two markers in 305 wheat germplasms and analyzed their effect on thousand kernel weight (TKW) and spike length (SL). These markers will accelerate the development of FHB-resistant wheat varieties through MAS, significantly reducing yield losses and strengthening food security. Full article

Background/Objectives: Cowpea is an important legume crop in sub-Saharan Africa (SSA) and beyond. However, access to phosphorus (P), a critical element for plant growth and development, is a significant constraint in SSA. Thus, it is essential to have high P-use efficiency varieties to achieve increased yields in environments where little-to- no phosphate fertilizers are applied. Methods: In this study, crop phenology, yield, and grain P efficiency traits were assessed in two recombinant inbred line (RIL) populations across ten environments under high- and low-P soil conditions to identify traits’ response to different soil P levels and associated quantitative trait loci (QTLs). Single-environment (SEA) and multi-environment (MEA) QTL analyses were conducted for days to flowering (DTF), days to maturity (DTM), biomass yield (BYLD), grain yield (GYLD), grain P-use efficiency (gPUE) and grain P-uptake efficiency (gPUpE). Results: Phenotypic data indicated significant variation among the RILs, and inadequate soil P had a negative impact on flowering, maturity, and yield traits. A total of 40 QTLs were identified by SEA, with most explaining greater than 10% of the phenotypic variance, indicating that many major-effect QTLs contributed to the genetic component of these traits. Similarly, MEA identified 23 QTLs associated with DTF, DTM, GYLD, and gPUpE under high- and low-P environments. Thirty percent (12/40) of the QTLs identified by SEA were also found by MEA, and some of those were identified in more than one P environment, highlighting their potential in breeding programs targeting PUE. QTLs on chromosomes Vu03 and Vu08 exhibited consistent effects under both high- and low-P conditions. In addition, candidate genes underlying the QTL regions were identified. Conclusions: This study lays the foundation for molecular breeding for PUE and contributes to understanding the genetic basis of cowpea response in different soil P conditions. Some of the identified genomic loci, many being novel QTLs, could be deployed in marker-aided selection and fine mapping of candidate genes. Full article

Background: Patients with inflammatory bowel disease (IBD) have an increased risk of developing immune-mediated diseases. However, the genetic basis of IBD is complex, and an integrated approach should be used to elucidate the complex genetic relationship between IBD and immune-mediated diseases. Methods: The genetic relationship between IBD and 16 immune-mediated diseases was examined using linkage disequilibrium score regression. GWAS data were synthesized from two IBD databases using the METAL, and multi-trait analysis of genome-wide association studies was performed to enhance statistical robustness and identify novel genetic associations. Independent risk loci were meticulously examined using conditional and joint genome-wide multi-trait analysis, multi-marker analysis of genomic annotation, and functional mapping and annotation of significant genetic loci, integrating the information of quantitative trait loci and different methodologies to identify risk-related genes and proteins. Results: The results revealed four immune-mediated diseases (AS, psoriasis, iridocyclitis, and PsA) with a significant relationship with IBD. The multi-trait analysis revealed 909 gene loci of statistical significance. Of these loci, 28 genetic variants were closely related to IBD, and 7 single-nucleotide polymorphisms represented novel independent risk loci. In addition, 14 genes and 514 proteins were found to be associated with susceptibility to immune-mediated diseases. Notably, IL1RL1 emerged as a key player, present within pleiotropic genes across multiple protein databases, highlighting its potential as a therapeutic target. Conclusions: This study suggests that the common polygenic determinants between IBD and immune-mediated diseases are widely distributed across the genome. The findings not only support a shared genetic relationship between IBD and immune-mediated diseases but also provide novel therapeutic targets for these diseases. Full article

Coronary artery disease (CAD) is a common comorbidity of type 2 diabetes mellitus (T2DM). However, the pathophysiology connecting these two phenotypes remains to be further understood. Combined analysis in multi-ethnic populations can help contribute to deepening our understanding of biological mechanisms caused by shared genetic loci. We applied genetic correlation analysis and then performed conditional and joint association analyses in Chinese, Japanese, and European populations to identify the genetic variants jointly associated with CAD and T2DM. Next, the associations between genes and the two traits were also explored. Finally, fine-mapping and functional enrichment analysis were employed to identify the potential causal variants and pathways. Genetic correlation results indicated significant genetic overlap between CAD and T2DM in the three populations. Over 10,000 shared signals were identified, and 587 were shared by East Asian and European populations. Fifty-six novel shared genes were found to have significant effects on both CAD and T2DM. Most loci were fine-mapped to plausible causal variant sets. Several similarities and differences of the involved genes in GO terms and KEGG pathways were revealed across East Asian and European populations. These findings highlight the importance of immunoregulation, neuroregulation, heart development, and the regulation of glucose metabolism in shared etiological mechanisms between CAD and T2DM. Full article

Plants can express different phenotypic responses following polyploidization, but ploidy-dependent phenotypic variation has so far not been assigned to specific genetic factors. To map such effects, segregating populations at different ploidy levels are required. The availability of an efficient haploid inducer line in Arabidopsis thaliana allows for the rapid development of large populations of segregating haploid offspring. Because Arabidopsis haploids can be self-fertilised to give rise to homozygous doubled haploids, the same genotypes can be phenotyped at both the haploid and diploid ploidy level. Here, we compared the phenotypes of recombinant haploid and diploid offspring derived from a cross between two late flowering accessions to map genotype × ploidy (G × P) interactions. Ploidy-specific quantitative trait loci (QTLs) were detected at both ploidy levels. This implies that mapping power will increase when phenotypic measurements of monoploids are included in QTL analyses. A multi-trait analysis further revealed pleiotropic effects for a number of the ploidy-specific QTLs as well as opposite effects at different ploidy levels for general QTLs. Taken together, we provide evidence of genetic variation between different Arabidopsis accessions being causal for dissimilarities in phenotypic responses to altered ploidy levels, revealing a G × P effect. Additionally, by investigating a population derived from late flowering accessions, we revealed a major vernalisation-specific QTL for variation in flowering time, countering the historical bias of research in early flowering accessions. Full article

Assessing interspecific adaptive genetic variation across environmental gradients offers insight into the scale of habitat-dependent heritable heterotic effects, which may ultimately enable pre-breeding for abiotic stress tolerance and novel climates. However, environmentally dependent allelic effects are often bypassed by intra-specific single-locality genome-wide associations studies (GWAS). Therefore, in order to bridge this gap, this study aimed at coupling an advanced panel of drought/heat susceptible common bean (Phaseolus vulgaris L.) × tolerant tepary bean (P. acutifolius A. Gray) interspecific lines with last-generation multi-environment GWAS algorithms to identify novel sources of heat and drought tolerance to the humid and dry subregions of the Caribbean coast of Colombia, where the common bean typically exhibits maladaptation to extreme weather. A total of 87 advanced lines with interspecific ancestries were genotyped by sequencing (GBS), leading to the discovery of 15,645 single-nucleotide polymorphism (SNP) markers. Five yield traits were recorded for each genotype and inputted in modern GWAS algorithms (i.e., FarmCPU and BLINK) to identify the putative associated loci across four localities in coastal Colombia. Best-fit models revealed 47 significant quantitative trait nucleotides (QTNs) distributed in all 11 common bean chromosomes. A total of 90 flanking candidate genes were identified using 1-kb genomic windows centered in each associated SNP marker. Pathway-enriched analyses were done using the mapped output of the GWAS for each yield trait. Some genes were directly linked to the drought tolerance response; morphological, physiological, and metabolic regulation; signal transduction; and fatty acid and phospholipid metabolism. We conclude that habitat-dependent interspecific polygenic effects are likely sufficient to boost common bean adaptation to the severe climate in coastal Colombia via introgression breeding. Environmental-dependent polygenic adaptation may be due to contrasting levels of selection and the deleterious load across localities. This work offers putative associated loci for marker-assisted and genomic selection targeting the common bean’s neo-tropical lowland adaptation to drought and heat. Full article