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Results for “expression quantitative trait loci”

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PubMed2026

Multi-Ancestry Genome-Wide Association with Fine-Mapping Identifies Novel Loci for Pigment Dispersion Syndrome and Pigmentary Glaucoma.

PURPOSE: Pigment dispersion syndrome and pigmentary glaucoma are important causes of ocular hypertension and glaucomatous optic neuropathy, yet their genetic determinants remain incompletely defined, particularly across diverse ancestries. This study aimed to use a large multi-ancestry cohort from the All of Us Research Program to investigate the genetic basis of pigment dispersion syndrome and pigmentary glaucoma. DESIGN: Case-control study. PARTICIPANTS: In total, 572 cases and 37 808 controls with array genotyping and 537 cases and 35 493 controls with whole-genome sequencing. METHODS: Using electronic health record phenotyping in the All of Us Research Program, we performed multi-ancestry genome-wide association analyses using both array-based data and whole-genome sequencing-based data, comparing patients with pigment dispersion syndrome or pigmentary glaucoma to those without either condition. We also performed Firth penalized regression and Fisher analyses, and we performed principal component analyses to assess effect sizes across genetic ancestries. We applied statistical fine-mapping, examined for cross-trait overlap, and assessed expression quantitative trait locus associations for lead variants. MAIN OUTCOME MEASURES: P values and odds ratios of lead loci from genome-wide association analyses; size of credible sets determined from fine-mapping; allele frequency of lead variants in cases, controls, and the general population; expression quantitative trait loci effect size and P values linking lead variants to gene expression. RESULTS: We identified 4 loci reaching genome-wide significance across analyses, including signals near EPHA7 (which mediates cell-cell signaling), within TYR (involved in melanin synthesis and replicated from prior studies), within LINC01138, and near OTX2. Statistical fine-mapping refined 3 of these loci to single-variant 95% credible sets and narrowed the TYR locus to small credible sets, prioritizing possible causal variants. Effect estimates were broadly consistent across genetic ancestry clusters. Lead variants showed regulatory evidence in expression quantitative trait locus, including reduced EPHA7 expression. CONCLUSIONS: These findings implicate both melanogenesis and cell-cell adhesion and signaling pathways in pigment dispersion syndrome and pigmentary glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Genome-wide association study↗

PubMed2006

DNA microarray and proteomic strategies for understanding alcohol action.

This article summarizes the proceedings of a symposium presented at the 2005 annual meeting of the Research Society on Alcoholism in Santa Barbara, California. The organizer was James M. Sikela, and he and Michael F. Miles were chairs. The presentations were (1) Genomewide Surveys of Gene Copy Number Variation in Human and Mouse: Implications for the Genetics of Alcohol Action, by James M. Sikela; (2) Regional Differences in the Regulation of Brain Gene Expression: Relevance to the Detection of Genes Associated with Alcohol-Related Traits, by Robert Hitzemann; (3) Identification of Ethanol Quantitative Trait Loci Candidate Genes by Expression Profiling in Inbred Long Sleep/Inbred Short Sleep Congenic Mice, by Robnet T. Kerns; and (4) Quantitative Proteomic Analysis of AC7-Modified Mice, by Kathleen J. Grant.

Alcoholism↗

PubMed2004

Expression profiling of rice segregating for drought tolerance QTLs using a rice genome array.

Plants alter their gene expression patterns in response to drought. Sometimes these transcriptional changes are successful adaptations leading to tolerance, while in other instances the plant ultimately fails to adapt to the stress and is labeled as sensitive to that condition. We measured the expression of approximately half of the genes in rice ( approximately 21,000) in phenotypically divergent accessions and their transgressive segregants to associate stress-regulated gene expression changes with quantitative trait loci (QTLs) for osmotic adjustment (OA, a trait associated with drought tolerance). Among the parental lines, a total of 662 transcripts were differentially expressed. Only 12 genes were induced in the low OA parent, CT9993, at moderate dehydration stress levels while over 200 genes were induced in the high OA parent, IR62266. The high and low OA parents had almost entirely different transcriptional responses to dehydration stress suggesting a complete absence of an appropriate response rather than a slower response in CT9993. Sixty-nine genes were up-regulated in all the high OA lines and nine of those genes were not induced in any of the low OA lines. The annotation of four of those genes, sucrose synthase, a pore protein, a heat shock and an LEA protein, suggests a role in maintaining high OA and membrane stability. Of the 3,954-probe sets that correspond to the QTL intervals, very few had a differential expression pattern between the high OA and low OA lines that suggest a role leading to the phenotypic variation. However, several promising candidates were identified for each of the five QTL including a snRNP auxiliary factor, a LEA protein, a protein phosphatase 2C and a Sar1 homolog.

Disasters↗

PubMed2026

Multi-omics Mendelian Randomization Prioritizes Neutrophil Extracellular Trap-related Genes Associated with Atrial Fibrillation Risk.

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 × 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗

PubMed2000

Identification of a murine locus conveying susceptibility to cadmium-induced forelimb malformations.

The heavy metal cadmium (Cd), an environmentally ubiquitous contaminant, is a potent teratogen in mice. When administered parenterally, it induces an array of malformations that vary in scope and severity with the route, dose, time of administration, and the strain of the animal. When administered intraperitoneally on day 9.0 of gestation, 4 mg/kg cadmium chloride produces forelimb defects (predominantly ectrodactyly) in over 80% of fetuses of the C57BL/6 mouse strain, while no limb defects are observed in the identically treated SWV strain. Like other examples of strain-specific teratogenic activity, the underlying nature of the differential susceptibility remains unknown. The present study investigates the segregation of sensitivity to Cd-induced forelimb defects in crosses between C57BL/6 and SWV mice and provides evidence for the involvement of both maternal and fetal factors in the determination of defect expression. In addition, quantitative trait loci (QTL) analysis of the fetal genetic component was performed among 198 backcross progeny, utilizing a genomic linkage map of 149 informative microsatellite markers. One QTL demonstrating significant linkage to expression of the defect, designated Cadfar (cadmium-induced forelimb autopod reduction), was mapped to the distal end of chromosome 6 with a lod score of 3.1.

Abnormalities, Drug-Induced↗

PubMed2026

Colocalization and functional analyses identify GBE1 as a gene linking muscle strength and cardiometabolic fitness.

Handgrip strength is a proxy for muscular fitness, an indicator for general health status, and is associated with cardiometabolic health. The mechanisms connecting handgrip strength to skeletal muscle function are incompletely understood. We applied integrated linkage-disequilibrium-adjusted colocalization analysis of genome-wide association study summary statistics for handgrip strength, combined with expression and splicing quantitative trait loci from skeletal muscle, and identified glycogen branching enzyme 1 (GBE1) as a candidate gene for handgrip strength. CRISPR-interference knockdown of GBE1 in immortalized human skeletal muscle cells (HMCL-7304) demonstrated decreased glycogen content and accumulation of polyglucosan bodies. Knockdown of GBE1 led to increased oxygen consumption rate, oxidative stress, and changes in mitochondrial morphology. Transcriptomic profiling of GBE1 knockdown cells identified upregulation of the human superoxide dismutase 2 and enrichment of pathways related to muscle contraction and oxidative stress responses. These functional genomic analyses prioritize GBE1 as a muscle-relevant candidate gene for handgrip strength and provide mechanistic insights to muscle fitness.NEW & NOTEWORTHY Colocalization of genome-wide association study (GWAS) loci with quantitative trait loci (QTL) in skeletal muscle tissue identified GBE1 as a candidate for handgrip strength. Cellular phenotypes with GBE1 knockdown in immortalized human skeletal muscle cells include decreased glycogen content, accumulation of polyglucosan bodies, changes in mitochondrial function and morphology, and increased expression of reactive oxygen species (ROS) scavengers. Transcriptomic changes suggest a role for GBE1 in muscle contraction and oxidative stress-mediated responses.

Humans↗

PubMed2004

Mapping quantitative trait Loci interactions from the maternal and offspring genomes.

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.

Animals↗

PubMed2024

eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis.

Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.

Humans↗

PubMed2026

A regulatory network underlying idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease in which genetic susceptibility interacts with epithelial, immune, and mesenchymal remodeling. Although the chromosome 11p15.5 locus contains established IPF susceptibility signals near MUC5B and TOLLIP, the broader regulatory architecture of this region remains incompletely resolved. METHODS: We integrated IPF genome-wide association study summary statistics with methylation, expression, and protein quantitative trait loci using summary-data-based Mendelian randomization (SMR). SMR-prioritized candidates were evaluated in independent transcriptomic and methylation cohorts and further contextualized using microRNA, transcription-factor, protein-interaction, machine-learning, single-cell, and spatial transcriptomic analyses. Fibrosis-associated expression patterns were assessed in a bleomycin-induced pulmonary fibrosis rat model. RESULTS: The analyses recovered the established MUC5B and TOLLIP signals and prioritized BRSK2 as a comparatively underexplored candidate supported by eQTL-based SMR and independent molecular evidence. The BRSK2 pQTL association did not pass the HEIDI test and was therefore not interpreted as convergent protein-level genetic evidence. Network analyses linked BRSK2 to cell-cycle, metabolic-stress, and senescence-related programs, while cross-cohort machine learning prioritized FOXA2, CDC25B, and NFE2 as informative network features. Single-cell and spatial analyses localized BRSK2 preferentially to fibroblast and myofibroblast compartments and to regions with greater histological fibrosis severity. In fibrotic rat lungs, BRSK2 expression increased, whereas FOXA2 and CDC25B decreased at the transcript and protein levels. CONCLUSIONS: These findings refine the molecular landscape of the chromosome 11p15.5 IPF susceptibility locus and prioritize BRSK2 as a candidate component of an IPF-associated profibrotic fibroblast state. Its causal contribution, direct regulatory relationships, and therapeutic tractability require targeted mechanistic validation.

Idiopathic Pulmonary Fibrosis↗

PubMed2026

Integrative multi-omics reveals a fibroblast-centered, ZFHX3-prioritized regulatory framework linking sick sinus syndrome and atrial fibrillation.

OBJECTIVE: To define shared genetic and multi-scale mechanisms underlying comorbidity between sick sinus syndrome (SSS) and atrial fibrillation (AF). METHODS: We integrated genome-wide association study (GWAS) summary statistics for SSS and AF with Genotype-Tissue Expression (GTEx) expression and splicing quantitative trait loci (eQTL/sQTL), atrial single-cell and spatial transcriptomics, and epigenomics. We identified trait-relevant tissues and pathways, prioritized shared cell types, quantified genome-wide and local genetic sharing, detected joint loci by cross-trait meta-analysis, and linked loci to regulatory programs via colocalization and cell-prioritized co-expression networks. RESULTS: Both traits showed strongest enrichment in cardiac tissue, especially Heart Atrial Appendage. Fibroblasts from the left atrial appendage were consistently prioritized as the key shared cell population. SSS and AF displayed significant positive genome-wide genetic correlation, with multiple locally shared regions, including six major loci. Cross-trait meta-analysis identified eight joint-phenotype SNPs implicating four susceptibility genes. ZFHX3 was the leading tissue-cell-gene candidate, acting as a hub in fibroblast co-expression modules and colocalizing with cardiac regulatory signals. CONCLUSION: Shared liability for SSS and AF is highly tissue- and cell-specific, converging on regulatory networks in atrial appendage fibroblasts, with ZFHX3 serving as a central mechanistic and biomarker node.

Humans↗

PubMed2002

Mapping quantitative trait loci and identification of genes that control fatness in poultry.

Chicken genomics has benefited from the rapid technological advances in the genomics of model organisms and man. A number of resources and approaches are now well established, in the chicken, including genetic markers and maps (both genetic and physical), quantitative trait loci mapping, comparative mapping, expressed sequence tag and bacterial artificial chromosome resources, and physical mapping. In addition, the next phase of gene discovery, functional genomics, is underway. Progress in mapping quantitative trait loci for growth and fatness traits will be discussed, as an application of these new technologies and approaches in the study of avian physiology and genetics.

Adipose Tissue↗

PubMed2005

Expression profiling and QTL analysis: a powerful complementary strategy in drug abuse research.

Alcoholism is a complex disease exhibiting a multifactorial mode of transmission. To simplify the genetic and phenotypic complexity of the alcoholic phenotype, alcohol-preferring (P) and -non-preferring (NP) rats were developed on the basis of alcohol preference and consumption as an animal model of alcoholism. Total gene expression analysis (TOGA) and quantitative trait loci (QTL) analysis were applied to selectively bred, inbred P and NP rats as complementary studies to identify genetic factors that contribute to alcohol preference and consumption. TOGA analysis was utilized to screen for differential expression in several brain regions involved in the mesocorticolimbic dopamine (DA) system. Genes exhibiting differences in expression were then screened for an association to the alcohol preference phenotype, the quantitative trait of a previously identified QTL. By evaluating differences in gene expression for linkage to a quantitative trait, this combined approach was implemented to identify alpha-synuclein, a candidate gene for alcohol preference.

Animals↗

PubMed2026

Morphological, Physiological and Transcriptomic Changes in Response to Water Deficit Stress in Brassica napus L.

Yield losses due to water-deficit (WD) conditions, especially during the reproductive stages of plant development, pose a significant threat to global canola (Brassica napus L.) production. Therefore, it is critical to investigate traits contributing to improved productivity under increased WD conditions. Here we present phenotypic, physiological and transcriptomic changes in response to WD across contrasting canola accessions exhibiting variation in drought resistance-related traits. WD significantly reduced shoot biomass, plant height, harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water-use efficiency and carbon isotope discrimination. WD caused 49 to 100% of the seed yield reduction: the minimum seed yield reduction (49.66%) was observed in a doubled-haploid (DH) line, 06-5101.137, while the maximum yield reduction (94.1 to 100%) occurred in the late-flowering DH lines (06.5101.088 and 06-5101.306). Seed yield showed a positive correlation (r = 0.29 to 0.95) with shoot biomass and harvest index, leaf water content, photosynthetic CO2 assimilation rate, intrinsic water use efficiency and carbon isotope discrimination. However, it showed negative correlations with days to flower, leaf specific weight, root length, root biomass (r = -0.04 to -0.79) across water treatments. The specific leaf transcriptome analysis of the two parental lines of DH population that exhibit variation for effective water use under well-watered and water-deficient conditions revealed different categories of differentially expressed genes (DEGs): WD-responsive DEGs in BC1329 parental line (1116) and BC9102 (1205) with 754 and 853 DEGs unique to BC1329 and BC9102, respectively, WD-responsive DEGs (906), genotype-dependent DEGs (8465) and genotype × treatment interaction DEGs (353). DEG annotations revealed that the WD-treatment-affected genes were involved in stress responses and growth and development. We further located 235 DEGs within the QTL regions underlying agronomic and physiological performance. Our study provides a conceptual framework for the morphological, physiological and molecular determinants involved in water-use efficiency. Seedlings' traits with high heritability values, such as shoot biomass, leaf weight, leaf water content and Δ13C, serve as proxies for trait-based selection for improved seed yield under both water-limited and non-water-limited conditions.

Brassica napus↗

PubMed2026

Cross-tissue multi-omics integration highlights BPHL and mitochondrial targets in Alzheimer's disease.

BACKGROUND: Mitochondrial dysfunction is a hallmark of Alzheimer's disease (AD), yet specific molecular targets remain to be fully characterized. METHODS: A summary-data-based Mendelian randomization (SMR) framework integrated AD genome-wide association study (GWAS) statistics (39,918 cases) with blood DNA methylation quantitative trait loci (mQTL), gene expression (eQTL), and protein (pQTL) data for 1136 mitochondria-related genes. Associations were assessed using Bayesian colocalization and HEIDI testing. Tissue relevance was evaluated in four brain regions (hippocampus, amygdala, cortex, frontal cortex) using GTEx and external transcriptomic datasets. RESULTS: Screening identified eight candidates supported across blood mQTL and eQTL layers. Stepwise central nervous system (CNS) evaluation singled out biphenyl hydrolase-like (BPHL) as the consistent candidate. Higher genetically predicted BPHL expression was associated with reduced AD risk across the hippocampus (OR=0.920, 95% CI 0.873-0.970), amygdala (OR=0.925, 95%CI 0.880-0.973), cortex (OR=0.943, 95% CI 0.908-0.978), and frontal cortex (OR=0.938, 95%CI 0.901-0.976). These findings aligned with protein-protein interactions connecting BPHL to respiratory complexes and lower BPHL expression in independent AD brains. Functional enrichment converged on oxidative phosphorylation pathways. CONCLUSIONS: By integrating multi-omics data with tissue-specific validation, this study nominates BPHL as a consistent protective candidate in the brain. These findings provide genetic support for mitochondrial molecular perturbations in AD, offering insights for future validation.

Alzheimer Disease↗

PubMed2000

A recombination hotspot delimits a wild-species quantitative trait locus for tomato sugar content to 484 bp within an invertase gene.

In nature, genetic variation usually takes the form of a continuous phenotypic range rather than discrete classes. The genetic variation underlying quantitative traits results from the segregation of numerous interacting quantitative trait loci (QTLs), whose expression is modified by the environment. To uncover the molecular basis of this variation, we characterized a QTL (Brix9-2-5) derived from the green-fruited tomato species Lycopersicon pennellii. The wild-species allele increased glucose and fructose contents in cultivated tomato fruits in various genetic backgrounds and environments. Using nearly isogenic lines for the QTL, high-resolution mapping analysis delimited Brix9-2-5 to a single nucleotide polymorphism-defined recombination hotspot of 484 bp spanning an exon and intron of a fruit-specific apoplastic invertase. We suggest that the differences between the Brix9-2-5 alleles of the two species are associated with a polymorphic intronic element that modulates sink strength of tomato fruits. Our results demonstrate a link between naturally occurring DNA variation and a Mendelian determinant of a complex phenotype for a yield-associated trait.

Alleles↗

PubMed2006

Fine mapping reveals sex bias in quantitative trait loci affecting growth, skeletal size and obesity-related traits on mouse chromosomes 2 and 11.

Previous speed congenic analysis has suggested that the expression of growth and obesity quantitative trait loci (QTL) on distal mouse chromosomes (MMU) 2 and 11, segregating between the CAST/EiJ (CAST) and C57BL/6J-hg/hg (HG) strains, is dependent on sex. To confirm, fine map, and further evaluate QTL x sex interactions, we constructed congenic by recipient F2 crosses for the HG.CAST-(D2Mit329-D2Mit457)N(6) (HG2D) and HG.CAST-(D11Mit260-D11Mit255)N(6) (HG11) congenic strains. Over 700 F2 mice were densely genotyped and phenotyped for a panel of 40 body and organ weight, skeletal length, and obesity-related traits at 9 weeks of age. Linkage analysis revealed 20 QTL affecting a representative subset of phenotypes in HG2DF2 and HG11F2 mice. The effect of sex was quantified by comparing two linear models: the first model included sex as an additive covariate and the second incorporated sex as an additive and an interactive covariate. Of the 20 QTL, 8 were sex biased, sex specific, or sex antagonistic. Most traits were regulated by single QTL; however, two closely linked loci were identified for five traits in HG2DF2 mice. Additionally, the confidence intervals for most QTL were significantly reduced relative to the original mapping results, setting the stage for quantitative trait gene (QTG) discovery. These results highlight the importance of assessing the contribution of sex in complex trait analyses.

Animals↗

PubMed2025

Multi-omics analysis of ubiquitin E2 genes in Setaria: evidence for the roles of E2 genes in various aspects of plant development, stress tolerance, and domestication.

Ubiquitin E2 enzymes (E2s) are critical mediators in the ubiquitination cascade, a post-translational modification process that regulates protein stability, activity, localization, and degradation. Here, we analyzed the E2 gene family in foxtail millet (Setaria italica), integrating comparative genomics, transcriptomics, and functional studies. A total of 52 E2 genes were identified and classified into four subfamilies (UBC, UEV, SCE, and RCE) based on phylogenetic analysis across 49 species. Notably, foxtail millet exhibited significant gene expansion. Tissue-specific expression profiling revealed distinct roles of E2 genes in growth and development. Haplotype and quantitative trait loci analyses demonstrated that several E2 genes, including SiUBC39, are associated with key agronomic traits, such as plant height, flowering time, and stress tolerance. Using CRISPR/Cas9, we validated the functional role of SiUBC39, finding that its disruption led to phenotypes resembling wild species (Setaria viridis), such as early flowering and reduced plant height and grain yield. IP-MS and transcriptome analysis revealed SiUBC39's involvement in growth and development regulation, drought stress response, and immune response. SiPIP2;1 and SiEhd2 were identified as interactors of SiUBC39, explaining its roles in blast resistance and flowering time control. Furthermore, domestication analysis identified an A/G mutation in the SiUBC39 promoter TATA box, distinguishing domesticated and wild haplotypes and highlighting its role in domestication selection. This study underscores the essential roles of E2 genes in regulating crop agronomic traits and stress responses, providing valuable insights for genetic improvement in foxtail millet and other cereals.

Setaria Plant↗

PubMed2005

The landscape of genetic complexity across 5,700 gene expression traits in yeast.

Many studies have identified quantitative trait loci (QTLs) that contribute to continuous variation in heritable traits of interest. However, general principles regarding the distribution of QTL numbers, effect sizes, and combined effects of multiple QTLs remain to be elucidated. Here, we characterize complex genetics underlying inheritance of thousands of transcript levels in a cross between two strains of Saccharomyces cerevisiae. Most detected QTLs have weak effects, with a median variance explained of 27% for highly heritable transcripts. Despite the high statistical power of the study, no QTLs were detected for 40% of highly heritable transcripts, indicating extensive genetic complexity. Modeling of QTL detection showed that only 3% of highly heritable transcripts are consistent with single-locus inheritance, 17-18% are consistent with control by one or two loci, and half require more than five loci under additive models. Strikingly, analysis of parent and progeny trait distributions showed that a majority of transcripts exhibit transgressive segregation. Sixteen percent of highly heritable transcripts exhibit evidence of interacting loci. Our results will aid design of future QTL mapping studies and may shed light on the evolution of quantitative traits.

Computer Simulation↗