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Results for “quantitative trait locus”

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PubMed2026

Integration of Genome-Wide Association Studies With Single-Cell and Bulk Expression Quantitative Trait Locus to Identify Stroke Susceptibility Genes.

BACKGROUND: Previous studies have integrated genome-wide association studies with expression quantitative trait locus (eQTL) data from bulk tissues to identify stroke susceptibility genes. However, eQTL data exhibit high cell-type specificity, and genetic variants may have distinct effects across stroke subtypes. METHODS: We applied the summary-data-based Mendelian randomization (MR) method to integrate eQTL data from 7 brain cell types with genome-wide association studies data for 5 stroke phenotypes (stroke, ischemic stroke, cardioembolic stroke, large artery stroke, and small vessel stroke). Results were compared with summary-data-based MR using eQTL data from 49 tissues in the Genotype-Tissue Expression project. Robustness of significant single-cell summary-data-based MR associations was assessed via MR and colocalization analyses. Further evaluations included single-cell RNA-seq differential expression, protein-protein interaction, druggability, and phenome-wide association studies. RESULTS: Single-cell summary-data-based MR identified many novel significant genes not detected using bulk tissue eQTL data. Validated associations revealed 2 stroke risk genes (LRCH1, ICA1L), 3 stroke protective genes (AHI1, LYRM9, CENPQ), 2 large artery stroke risk genes (LIPA, ELL), and 1 ischemic stroke protective gene (CENPQ). Single-cell RNA-seq showed significantly increased LIPA expression in mouse stroke samples compared with controls. Protein-protein interaction and druggability analyses, along with phenome-wide association studies, prioritized LIPA and LRCH1 as potential therapeutic targets for stroke while indicating possible adverse effects. CONCLUSIONS: Integrating single-cell eQTL with stroke-subtype genome-wide association studies uncovers novel cell-type-specific causal genes and highlights promising therapeutic targets, advancing understanding of stroke pathogenesis.

Genome-Wide Association Study↗

PubMed2026

Quantitative trait locus qLDC5 regulates primary root branching in an auxin-dependent manner.

L-type lateral root (LLR) density determines root system architecture, affecting nutrient acquisition in rice (Oryza sativa L.), particularly under low-phosphorus conditions. Previous studies identified genotypic differences in LLR density and a quantitative trait locus (QTL) enhancing LLR density on crown roots (qLDC5). We showed that LLR densities on crown and primary roots were closely correlated and confirmed higher LLR density on primary roots in qLDC5 donor DJ123 compared with the African variety NERICA4 using X-ray micro-computed tomography. We confirmed the qLDC5 effect in a field experiment for LLR density on primary roots. LLR densities on primary and crown roots, therefore, appear under similar genetic control. Developmental analyses revealed that DJ123 and NDJ188-a derivative line harboring qLDC5-initiate more lateral root primordia than NERICA4, with a higher proportion progressing to elongation, but that exogenous auxin application reversed this ranking. Within qLDC5, auxin biosynthesis gene OsYUCCA2 and auxin response factor OsARF15 were up-regulated in DJ123. Transcriptome analysis revealed an indirect auxin-mediated regulatory network underlying LLR variation. Differentially expressed genes in DJ123 and NDJ188 were enriched for ent-kaurene and gibberellin metabolism, including the robust induction of OsGA2ox5. These findings suggest qLDC5 increases lateral root density by coordinating gibberellin, auxin, and terpene pathways.

Oryza↗

PubMed2026

Single-cell expression quantitative trait locus Mendelian randomization reveals immune cell-specific causal regulatory networks and actionable targets in polycystic ovary syndrome.

ObjectiveTo systematically investigate whether the pathogenesis of polycystic ovary syndrome (PCOS) is causally related to dysregulated gene expression in specific immune cell subsets, and to evaluate the potential of these causal genes as actionable drug targets.MethodsThis study employed a two-sample Mendelian randomization (MR) framework using publicly available genome-wide association study (GWAS) summary statistics. The participant data included 797 PCOS cases and 140,558 controls (no direct patient recruitment was involved). Instrumental variables were derived from high-resolution immune cell-specific single-cell expression quantitative trait locus (sc-eQTL) data (OneK1K project) across 14 immune cell types. Primary analyses utilized the inverse-variance weighted (IVW) method. Shared causal variants were validated using Bayesian colocalization. Phenome-wide association analysis (PheWAS), external transcriptomic dataset validation (GSE8157), and DrugBank database screening were conducted for pleiotropy assessment and drug repositioning.ResultsMR analysis revealed genome-wide significant causal associations for GLIPR1 in non-classical monocytes (Mono NC) and XBP1 in CD4+ effector memory T cells (CD4 ET) with PCOS risk. Higher GLIPR1 expression was associated with a decreased PCOS risk (OR = 0.669, P = 4.34×10-6), whereas higher XBP1 expression was associated with an increased risk (OR = 1.406, P = 9.53×10-8). Colocalization analysis confirmed that GLIPR1 shares a causal variant with PCOS (PP.H4 = 96.73%). PheWAS and external validation confirmed the safety profile and significant upregulation (P = 0.03) of GLIPR1. Drug repositioning identified SOT-107, a Phase III protein therapy drug, as a potential interacting agent for GLIPR1.ConclusionsThis sc-eQTL MR study reveals immune cell-specific causal regulatory networks in PCOS. GLIPR1 in non-classical monocytes represents a high-confidence protective target, while XBP1 provides suggestive evidence for immune-mediated pathogenesis. The candidate drug SOT-107 highlights theoretical repositioning opportunities, though rigorous preclinical validation remains required.

Female↗

PubMed2025

From aerial drone to quantitative trait locus: leveraging next-generation phenotyping to reveal the genetics of color and height in field-grown Lactuca sativa.

In recent years, accurate and low-cost variant calling has enabled the genotyping of large diversity panels for genome-wide association studies. As a result, phenotyping rather than genotyping is now the rate-limiting step, especially in field experiments. This has created a strong need for high-throughput, accurate, and low-cost in-field phenotyping. Here, we present a genome-wide association study (GWAS) study on 194 field-grown accessions of lettuce (Lactuca sativa). These accessions were non-destructively phenotyped at two time points 15 days apart using a drone equipped with an RGB and multispectral (MSP) camera. Our high-throughput phenotyping approach integrates an RGB- and MSP camera to measure the color and height of lettuce in this large-scale field experiment. We used the mean and other summary statistics, such as median, quantiles, skewness, kurtosis, minimum, and maximum to quantify different aspects of color and height variation in lettuce from the drone images. Using these summary statistics as traits for GWAS, we confirm several previously described genetic associations, now under field conditions, and identify additional novel associations for color and height traits in lettuce.

Lactuca↗

PubMed2026

Exploring genomic regions regulating the liver transcriptome and energy homeostasis in pigs.

In pigs, energy homeostasis has an impact on meat quality and health. In a Duroc pig population, 30 quantitative trait locus (QTL) regions associated with fatty acid (FA) composition in adipose tissue, plasma, liver and muscle were previously identified. Mapping of expression quantitative trait locus (eQTL) regions will provide a molecular hypothesis for genotype-phenotype interactions and may allow the identification of shared causal variants, key to increasing our understanding of the genetic regulation of FA composition and energy homeostasis. However, gene expression is impacted by environmental factors, while individual-level allelic imbalance (AI) can be more reliable and can be surveyed via allelic-specific expression (ASE) analysis. Furthermore, treatment of ASE as a quantitative trait allows the identification of allele-specific expression quantitative trait loci (aseQTLs), which are variants whose heterozygosity is linked to the AI of a nearby single-nucleotide polymorphism (SNP), pointing to regulatory elements. In this study, liver was selected as a key metabolic hub with an important role in the regulation of energy homeostasis, and 310 liver RNA sequencing samples were analysed using a combination of (1) eQTL mapping, (2) ASE analysis, and (3) aseQTL mapping methods. A total of 2 188 eQTL regions were identified, mostly cis-eQTL regions (73.17%). ASE analysis reported 1 964 ASE SNPs, associated with 633 genes. Finally, aseQTL mapping reported 64 172 aseQTL, associated with the AI of 31 genes. Colocalisation analysis combined with ASE analysis showed that the expression of FADS1 and FADS2 genes is associated with the polyunsaturated FA composition in several tissues, where microRNA regulation may be present. Finally, in the DGAT2 gene, annotated in a QTL region associated with multiple FAs in adipose tissue, ASE revealed allelic imbalance in the 3' untranslated region (UTR) of this gene. Allelic differential expression can be caused by a 13-bp insertion affecting messenger RNA stability, previously described, exemplifying how allelic imbalance is caused by a post-transcriptional regulatory mechanism undetectable by eQTL mapping. Furthermore, aseQTLs were associated with this gene, linked to a previously identified copy number variant not yet associated with DGAT2 expression. These results demonstrate how ASE analysis and aseQTL mapping can complement eQTL mapping, as they resolved a complex region affected by allelic heterogeneity, a main confounding effect of QTL mapping. In conclusion, the combination of eQTL mapping, ASE analysis and aseQTL mapping allowed the characterisation of the regulation of liver gene expression, improving our understanding of the genetic determinism of energy homeostasis.

Allele-specific expression↗

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↗

PubMed2025

Ectopic Gene Conversion Causing Quantitative Trait Variation.

Why is there so much non-neutral genetic variation segregating in natural populations? We dissect function and evolution of a near-cryptic quantitative trait locus (QTL) for defense metabolites in Arabidopsis using the CRISPR/Cas9 system and nucleotide polymorphism patterns. The QTL is explained by genetic variation in a family of 4 tightly linked indole-glucosinolate O-methyltransferase genes. Some of this variation appears to be maintained by balancing selection, some appears to be generated by non-reciprocal transfer of sequence, also known as ectopic gene conversion (EGC), between functionally diverged gene copies. Here, we elucidate how EGC, as an inevitable consequence of gene duplication, could be a general mechanism for generating genetic variation for fitness traits.

Quantitative Trait Loci↗

PubMed2025

Integrative omics of the genetic basis for wheat WUE and drought resilience reveal the function of TaMYB7-A1.

Improving wheat drought resilience and water use efficiency (WUE) is critical for sustaining productivity under increasing water scarcity. Here, we integrate genome-wide association study (GWAS), expression quantitative trait locus (eQTL) mapping, population-transcriptome analysis, and summary-data-based mendelian randomization (SMR), followed by functional validation using indexed EMS mutants and transgenic lines, to systematically identify key WUE regulators. GWAS across water conditions in 228 accessions identifies 73 quantitative trait loci (QTLs) for WUE-traits. Transcriptome profiling of 110 diverse accessions reveals 28 drought-responsive modules. eQTL mapping uncovers 146,966 regulatory variants, including condition-specific hotspots associated with key drought-related pathways. Integrative analysis underscores 85 high-confidence candidate genes, notably TaMYB7-A1. Overexpression of TaMYB7-A1 enhances photosynthesis, WUE, root development, and grain yield under drought condition by activating TaPIP2;2-B1 (water transport), TaRD20-D1 (stomatal regulation), and TaABCB4-B1 (root growth), reflecting reduced water loss and improved physiological resilience. Our study presents a comprehensive regulatory map and robust targets for wheat drought adaptation and resilient cultivar breeding.

Triticum↗

PubMed2026

Integrating Genetics and Environment to Find Causal Mechanisms for Multiple Sclerosis.

Genome-wide association studies (GWAS) have identified hundreds of risk loci for multiple sclerosis (MS), but we have limited knowledge of the mechanisms through which genetic variants mediate risk. Similarly, epidemiological studies implicate numerous environmental risk factors in MS risk, but these cannot identify specific causal mechanisms. We review our current knowledge of genetic mechanisms in MS, including the critical role of expression quantitative trait locus (eQTL) mapping in translating genetic risk loci into causal mechanisms. Molecular and functional context has emerged as an important missing component of these studies, and we discuss how environmental risk factors can be modelled in a quantitative genetic context to identify disease mechanisms. In parallel, we highlight recent advances in which quantitative genetic methods establish a causal role for low vitamin D and obesity in MS, and to dissect the mechanisms through which these operate. As genetic, transcriptional, and epigenetic studies continue to expand, further mechanistic insights for MS are likely to come from the integration of genetic and environmental data.

Humans↗

PubMed2025

Association of AGER genetic variants with chronic obstructive pulmonary disease susceptibility in Southern Chinese Han populations.

OBJECTIVE: Chronic obstructive pulmonary disease (COPD) remains a leading cause of disability and mortality among elderly populations. Studies indicate that AGER plays a critical regulatory role in the pathogenesis of respiratory disorders. However, the genetic variations in AGER to COPD susceptibility remain incompletely understood. This study employs a case-control design to investigate associations between AGER genetic variants and COPD risk in the Southern Chinese Han population. METHODS: This study enrolled 270 COPD patients and 271 healthy controls. AGER single-nucleotide polymorphisms (SNPs) were analysed using the MassARRAY iPLEX platform. Logistic regression models evaluated associations between AGER polymorphisms and COPD susceptibility, with false discovery rate (FDR) correction applied to mitigate multiple testing errors. SNP-SNP interactions were investigated through multifactor dimensionality reduction (MDR) analysis. Expression quantitative trait locus (eQTL) data from the GTEx database were further analysed to assess regulatory relationships between SNPs and AGER gene expression levels. RESULTS: This study showed that rs3134941 (G allele, OR = 0.21, 95% CI = 0.10-0.41, p (FDR) = 0.001) and rs3131300 (G allele, OR = 0.32, 95% CI = 0.20-0.49, p (FDR) = 0.0001) were significantly associated with a reduced susceptibility to COPD. MDR indicated that rs3131300 was the optimal predictive model for COPD risk. Additionally, initial mechanistic investigations utilizing the GTEx database identify rs3134941 (C > G) and rs3131300 (A > G) as significant expression quantitative trait loci for AGER mRNA in cell-cultured fibroblasts and whole blood. CONCLUSION: Our study demonstrated that AGER genetic variants might play a protective role in the progression of COPD.

Aged↗

PubMed2026

Genome-wide association study combined with multi-assay phenotyping identifies a novel anthracnose resistance locus in apple.

BACKGROUND: Apple anthracnose, a disease complex that includes Glomerella leaf spot (GLS) and bitter rot caused by Colletotrichum species, is a major disease affecting apple production worldwide. In this study, we combined multi-year field evaluations with controlled inoculation assays to identify genomic regions associated with anthracnose resistance in apple. RESULTS: A total of 440 apple genotypes, including 411 F₁ progenies derived from six parental crosses and 29 cultivars, were evaluated under natural orchard conditions and through artificial fruit and leaf inoculation assays using wound and non-wound methods. Disease severity varied substantially between years, particularly under contrasting environmental conditions, indicating strong genotype-by-environment interactions. Genome-wide association analysis (GWAS) using field-derived disease severity scores from 2019 identified a significant quantitative trait locus (QTL) on chromosome 15 (~ 31.8 Mb) associated with reduced anthracnose severity. This locus was distinct from the previously reported Rgls/MdTNL1 region on chromosome 15 (~ 2-5 Mb), suggesting the presence of a novel resistance-associated locus. In contrast, no genome-wide significant associations were detected from artificial inoculation datasets. CONCLUSIONS: These findings demonstrate the importance of field-based, multi-environment phenotyping for detecting field-relevant resistance loci and improving understanding of the genetic architecture underlying anthracnose resistance in apple.

Malus↗

PubMed2026

Overlapping genetic etiology of pediatric and adult germ cell tumors.

BACKGROUND: Germ cell tumors are heterogeneous neoplasms arising from primordial germ cells. Although genome-wide association studies have identified numerous susceptibility loci for adult testicular germ cell tumors, the heritable basis of pediatric testicular germ cell tumors and germ cell tumors that arise outside the testes remain poorly understood. METHODS: We conducted a multi-ancestry genome-wide association study of pediatric germ cell tumors, including 1927 cases from the Germ Cell Tumor Epidemiology Study and 10 601 controls. Cases were diagnosed with testicular (n = 678), ovarian (n = 441), intracranial (n = 435), and extragonadal (n = 373) germ cell tumor between the ages of 0 and 19 years. RESULTS: We identified 4 loci reaching genome-wide significance, including variants near BAK1 (chr 6: rs3831846), SPRY4 (chr 5: rs12515244), DMRT1 (chromosome [chr] 9: rs10815910), and DEPTOR (chr 8: rs13277786). Additional genome-wide statistically significant associations were identified in subgroup analyses, including 6 loci for intracranial germ cell tumors (rs2758612 [PMF1/BGLAP], rs9854760 [PLCL2], rs6851498 [KIT], rs11816992 on chromosome 10, rs3830273 [TFAM], and rs13054014 [LZTR1]), 1 locus for testicular germ cell tumor (rs1907702 [KITLG]), and 1 locus for males (rs4610628 [MAD1L1]). After Bonferroni correction, 18 of 78 previously reported testicular germ cell tumor loci were significantly associated with germ cell tumor overall or in at least 1 subgroup with a particularly strong correlation between testicular germ cell tumor and intracranial germ cell tumor effect estimates (rho = 0.63, P = 5.5 × 10-10). Expression quantitative trait locus (QTL) analyses identified candidate genes in the regions identified on chromosome 6 (BAK1, LINC003366, and ITPR3) and chromosome 8 (DEPTOR and RP11-760H22.2). CONCLUSIONS: Our data support a role for germline genetic variation in the development of germ cell tumors in locations outside the testes and highlight shared genetic architecture across age group and tumor location.

Humans↗

PubMed2026

Quantitative trait loci mapping of gene expression and chromatin accessibility in primary fibroblasts reveals shared allelic effects between Latin American and European ancestries.

BACKGROUND: Quantitative Trait Locus (QTL) analysis of molecular data has identified genetic variants associated with traits such as gene expression, and colocalization of these functional QTL with GWAS risk loci has offered insights into the genetic basis of human disease. We employed gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) obtained from human primary fibroblasts to investigate quantitative trait loci (QTLs) in cohorts ascertained for bipolar disorder of European (n = 150) and Latin American (n = 96) ancestries. RESULTS: Leveraging data from three countries of origin (The Netherlands, Colombia, Costa Rica) within our cohort, we characterized differences among individuals at the SNP, gene, and accessible-chromatin levels to compute ancestry-specific expression (e)QTLs and chromatin-accessibility (ca)QTLs. Across ancestries, we observed R2 ≥ 0.93 for eQTL effect sizes and R2 ≥ 0.95 for caQTLs, indicating a high degree of concordance. Integrating chromatin data with expression and genotype information enabled precise fine-mapping of eQTLs, yielding 203 genes with high-confidence (posterior probability > 90%) candidate regulatory pathways. In downstream analyses, transcriptome-wide (TWAS) and chromatin-wide (CWAS) association studies with brain- and skin-related GWAS identified 36 TWAS-significant genes and 77 CWAS-significant open chromatin regions. CONCLUSIONS: These findings underscore the shared genetic regulatory mechanisms across European and Latin American ancestries, while demonstrating that ancestry-specific reference panels enhance the accuracy of TWAS and CWAS in diverse populations. More broadly, this study highlights the value of paired multi-omic datasets from diverse cohorts for interpreting disease-associated genetic variation.

Humans↗

PubMed2025

Candidate genes at the Rmi1 locus for resistance to Meloidogyne incognita in soybean.

The RKN resistance locus Rmi1 was fine-mapped to two genes on chromosome 10, a glycosyl hydrolase family 9 β-1,4-endoglucanase gene and a type I pectin methylesterase gene. Root-knot nematodes (Meloidogyne spp.) are a serious threat to soybean production in the southeast USA, with yield losses of more than $165 million in 2023. Development and deployment of resistant soybean cultivars is the most effective strategy for managing these nematode pests; however, the identity of the resistance genes and underlying mechanism of resistance remains obscure. An additive resistance gene, Resistance to M. incognita-1 (Rmi1), to the predominant species, was first identified in soybean cultivar Forrest but never mapped to a genomic region. Multiple mapping studies have identified a major quantitative trait locus (QTL) with additive action on chromosome 10. In this study, a population consisting of 170 F2:3 families derived from a cross of Bossier (susceptible) × Forrest (resistant) was initially used to confirm that Rmi1 is in the chromosome 10 QTL. Subsequently, 884 F5:6 recombinant inbred lines (RILs) derived from the same cross were used to fine-map the Rmi1 causal gene(s) to two genes - a β-1,4-endoglucanase (Glyma.10G017000, EG) and a pectin methylesterase/methylesterase inhibitor (Glyma.10G017100, PME1). Both gene candidates have the potential to play a role in the resistance response to M. incognita. Both gene promoters harbor SNPs and indels and the encoded proteins exhibit amino acid polymorphisms, including a premature stop in PME1 of resistant soybeans. Additionally, both genes show a higher expression level in susceptible roots compared to resistant roots in the absence of infection. This suggests that Rmi1 may confer one or more pre-existing differences related to cell wall modification in soybean roots, ultimately leading to a decrease in susceptibility.

Tylenchoidea↗

PubMed2025

Naturally occurring variation in a cytochrome P450 modifies thiabendazole responses independently of beta-tubulin.

Widespread anthelmintic resistance has complicated the management of parasitic nematodes. Resistance to the benzimidazole (BZ) drug class is nearly ubiquitous in many species and is associated with mutations in beta-tubulin genes. However, mutations in beta-tubulin alone do not fully explain all BZ resistance. We performed a genome-wide association study using a genetically diverse panel of Caenorhabditis elegans strains to identify loci that contribute to resistance to the BZ drug thiabendazole (TBZ). We identified a quantitative trait locus (QTL) on chromosome V independent of all beta-tubulin genes and overlapping with two promising candidate genes, the cytochrome P450 gene cyp-35D1 and the nuclear hormone receptor nhr-176. Both genes were previously demonstrated to play a role in TBZ metabolism. NHR-176 binds TBZ and induces the expression of CYP-35D1, which metabolizes TBZ. We generated single gene deletions of cyp-35D1 and nhr-176 and found that both genes play a role in TBZ response. A predicted high-impact lysine-to-glutamate substitution at position 267 (K267E) in CYP-35D1 was identified in a sensitive strain, and reciprocal allele replacement strains in different genetic backgrounds were used to show that the lysine allele conferred increased TBZ resistance. Using competitive fitness assays, we found that neither allele was deleterious, but the lysine allele was selected in the presence of TBZ. Additionally, we found that the lysine allele significantly increased the rate of TBZ metabolism compared to the glutamate allele. Moreover, yeast expression assays showed that the lysine version of CYP-35D1 had twice the enzymatic activity of the glutamate allele. To connect our results to parasitic nematodes, we analyzed four Haemonchus contortus cytochrome P450 orthologs but did not find variation at the 267 position in fenbendazole-resistant populations. Overall, we confirmed that variation in this cytochrome P450 gene is the first locus independent of beta-tubulin to play a role in BZ resistance.

Animals↗

PubMed2026

Genetic evidence and cross-species functional characterization implicate CNN2 in age-related macular degeneration susceptibility.

Age-related macular degeneration (AMD) is a leading cause of irreversible visual impairment in the aging population globally. Although genome-wide association studies (GWAS) have identified many AMD susceptibility loci, the genes and mechanisms underlying many of these associations remain unresolved. Here, we integrated expression quantitative trait locus (eQTL) data with AMD GWAS to prioritize nine putative genes. Through in vivo screening in zebrafish, we demonstrated that the downregulation of cnn2 and sarm1 expression led to ocular structural abnormalities and visual functional impairment. Subsequent mouse model studies confirmed that Cnn2 deficiency affected photoreceptor structure and function, impaired contrast sensitivity, and caused abnormalities in cone cell immunostaining. Given that CNN2 is predominantly expressed in endothelial cells, we propose that endothelial dysfunction may cascade to impair photoreceptor function. Collectively, through in silico prioritization and cross-species functional characterization, we identify CNN2 as a candidate susceptibility gene in AMD pathogenesis, providing vital underlying mechanistic insights.

Animals↗

PubMed2025

Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.

Exotic Gossypium accessions still harbor QTL‑validated alleles that, combined with CRISPR pyramiding and genomic selection, can break the entrenched fiber length-strength trade‑off. Cotton's four independent domestications twice in diploids and twice in allotetraploids offer a natural experiment in fiber improvement. Synthesizing three decades of data, we chart how polyploidy, selection and modern breeding have repeatedly reshaped the Gossypium genome. More than 15,000 quantitative trait locus (QTL) and genome wide association mapping studies (GWAS) hits converge on a handful of chromosomal "hotspots"; new MAGIC, NAM, NIL and long-read resources now narrow these peaks to < 200 kb, resolving causal genes such as GhHOX3, GhZF14 and GhMYB7. Multi-omics evidence links auxin, ethylene, gibberellin, brassinosteroid and strigolactone signaling to HDZIP IV, MYB, bHLH/HLH and ERF networks that drive fiber initiation, extreme cell elongation and cellulose deposition. Population genomics shows that ~ 40% of favorable fiber alleles are fixed in elite Gossypium hirsutum, yet wild diploids and landraces still harbor variants that could break the length strength trade-off. We propose a three-step roadmap genomic selection, CRISPR gene pyramiding and accelerated introgression to expand cotton's genetic base and deliver fibers suited to sustainable textile demands.

Gossypium↗

PubMed2025

Saturating the eQTL map in Drosophila: Genome-wide patterns of cis and trans regulation of transcriptional variation in outbred populations.

Most genetic polymorphisms associated with complex traits are found in non-coding regions of the genome. Characterizing their effect presents a formidable challenge, and expression quantitative trait locus (eQTLs) mapping has been a key approach to do so. As comprehensive eQTL maps are available only for a few species, here we developed the Drosophila outbred synthetic population (Dros-OSP) and used it to characterize the landscape of transcriptional regulation in Drosophila melanogaster. We collected head and body transcriptomes and genomes from 1,286 outbred flies and mapped local and distant eQTLs for 98% of the genes. We characterized the network organization of the transcriptome across tissues and described the properties of local and distal eQTLs in terms of genetic diversity, heritability, connectivity, and pleiotropy. These results provide new insights into the genetic basis of transcriptional regulation in the fruit fly and offer a new mapping resource that will expand the possibilities currently available for the Drosophila community.

Animals↗