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PubMed2005

Organization of the sex-ratio meiotic drive region in Drosophila simulans.

Sex-ratio meiotic drive is the preferential transmission of the X chromosome by XY males, which occurs in several Drosophila species and results in female-biased progeny. Although the trait has long been known to exist, its molecular basis remains completely unknown. Here we report a fine-mapping experiment designed to characterize the major drive locus on a sex-ratio X chromosome of Drosophila simulans originating from the Seychelles (XSR6). This primary locus was found to contain two interacting elements at least, both of which are required for drive expression. One of them was genetically tracked to a tandem duplication containing six annotated genes (Trf2, CG32712, CG12125, CG1440, CG12123, org-1), and the other to a candidate region located approximately 110 kb away and spanning seven annotated genes. RT-PCR showed that all but two of these genes were expressed in the testis of both sex-ratio and standard males. In situ hybridization to polytene chromosomes revealed a complete association of the duplication with the sex-ratio trait in random samples of X chromosomes from Madagascar and Reunion.

Animals↗

PubMed1993

The human insulin gene-linked polymorphic region adopts a G-quartet structure in chromatin assembled in vitro.

The insulin gene-linked polymorphic region (ILPR), located 363 bp upstream of the human insulin gene, is composed of tandem repeats of the consensus sequence ACAGGGGT(G/C)(T/C)GGGG. It has previously been shown that an insulin gene fragment containing the ILPR adopts an altered DNA structure in vitro. Furthermore, oligonucleotides containing the consensus repeat sequence exhibit multiple quadriplex DNA structures. The present study was undertaken to determine whether such altered DNA structures existed within the ILPR when the insulin gene was assembled into chromatin in vitro. Chromatin assembly was achieved using histones and an extract from unfertilized eggs from Xenopus laevis. The presence of altered DNA conformations within the 5' region of the human insulin gene was investigated using the structural probe nuclease P1. Nuclease P1 recognized multiple distinct sites in the 5' flanking region of the human insulin gene in naked DNA. Most of these sites disappeared when the recombinant plasmid DNA was treated with histones and unfertilized egg extract. In the assembled DNA, the ILPR appeared as the major site of nuclease P1 hypersensitivity. Fine-mapping of the multiple reactive sites within the ILPR showed a pattern characteristic of G-quartet foldback structures similar to those that have been observed for telomeric DNA.

Animals↗

PubMed2004

MaGIC: a program to generate targeted marker sets for genome-wide association studies.

High-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis of required saturation density. Restricting markers to those within annotated genomic features of interest (e.g., genes or exons) or within feature-rich regions, reduces workload and cost while retaining much information. We have designed a program (MaGIC) that exploits genome assembly data to create lists of markers correlated with other genomic features. Marker lists are generated at a user-defined spacing and can target features with a user-defined density. Maps are in base pairs or linkage disequilibrium units (LDUs) as derived from the International HapMap data, which is useful for association studies and fine-mapping. Markers may be selected on the basis of heterozygosity and source database, and single nucleotide polymorphism (SNP) markers may additionally be selected on the basis of validation status. The import function means the method can be used for any genomic features such as housekeeping genes, long interspersed elements (LINES), or Alu repeats in humans, and is also functional for other species with equivalent data. The program and source code is freely available at http://cogent.iop.kcl.ac.uk/MaGIC.cogx.

Algorithms↗

PubMed2001

Finding genes influencing susceptibility to complex diseases in the post-genome era.

During the last decade, hundreds of genes that harbor mutations causing simple Mendelian disorders have been identified using a combination of linkage analysis and positional cloning techniques. Traditional approaches to gene mapping have been largely unsuccessful in mapping genes influencing so-called 'complex' genetic diseases, however, because of low power and other factors. Complex genetic diseases do not display simple Mendelian patterns of inheritance, although genes do have an influence and close relatives of probands consequently have an increased risk. These disorders are thought to be due to the combined effects of variation at multiple interacting genes and the environment. Complex diseases have a significant impact on human health because of their high population incidence (unlike simple Mendelian disorders, which tend to be rare). New techniques are being developed aimed specifically at mapping genes conferring susceptibility to complex diseases. A project aimed at mapping genes influencing susceptibility to a complex disease may be undertaken in several stages: establishing a genetic basis for the disease in one or more populations; measuring the distribution of gene effects; studying statistical power using models; carrying out marker-based mapping studies using linkage or association. Quantitative genetic models can be used to estimate the heritability of a complex (polygenic) disease, as well as to predict the distribution of gene effects and to test whether one or more quantitative trait loci (QTLs) exist. Such models can be used to predict the power of different mapping approaches, but are often unrealistic and therefore provide only approximate predictions. Linkage analyses, association studies and family-based association tests are all hindered by low power and other specific problems. Association studies tend to be more powerful but can generate spurious associations due to population admixture. Alternative strategies for association mapping include the use of recent founder populations or unique isolated populations that are genetically homogeneous, and the use of unlinked markers (so-called genomic controls) to assign different regions of the genome of an admixed individual to particular source populations. Linkage disequilibrium observed in a sample of unrelated affected and normal individuals can also be used to fine-map a disease susceptibility locus in a candidate region. New Bayesian strategies make use of an annotated human genome sequence to further refine the position of a candidate disease susceptibility locus.

Genetic Diseases, Inborn↗

PubMed2005

The Autism Genome Project: goals and strategies.

Autism is a complex neurodevelopmental disorder with a broad spectrum of symptoms and varying severity. Currently, no biological diagnosis exists. Although there has been a significant increase in autism genetics research recently, validated susceptibility genes for the most common, sporadic forms of autistic disorder, as well as familial autism, have yet to be identified. The identification of autism-susceptibility genes will not only assist in the identification and/or development of better medications that can help improve the health and neurodevelopment of children with autism, but will also allow for better perinatal diagnosis. The Autism Genome Project (AGP) is a large-scale, collaborative genetics research project initiated by the National Alliance for Autism Research and the National Institutes of Health, and is aimed at sifting through the human genome in search of autism-susceptibility genes. Phase I of the AGP will consist of genome-wide scans utilizing both SNP array and microsatellite technologies. Linkage analysis will subsequently be performed on approximately 1500 pedigrees as will downstream fine-mapping and sequencing of the critical linkage intervals. Ultimately, the vision will be to identify the exact nucleotide variants within genes which give rise to predisposition. The AGP intends to move the field of autism clinical management forward by answering questions about the causal mechanisms underlying the pathophysiology of autism. From this knowledge, therapeutic targets for drug treatments, and ultimately, a newborn screening diagnostic that would allow for early intervention, can begin to be developed.

Autistic Disorder↗

PubMed2001

Mapping by genetic interaction: high-resolution congenic mapping of the type 1 diabetes loci Idd10 and Idd18 in the NOD mouse.

As many of the linked chromosome regions that predispose to type 1 diabetes in the NOD mouse have been dissected, it has become apparent that the initially observed effect is in fact attributable to several loci. One such cluster of loci on distal chromosome 3, originally described as Idd10, is now known to comprise three separate loci, Idd10, Idd17, and Idd18. Although these loci have a significant combined effect on diabetes development, their individual effects are barely detectable when diabetes is used as a read-out, which makes fine-mapping them by use of a conventional congenic approach impractical. In this study, we demonstrate that it is possible to map loci, with modest effects, to regions small enough for systematic gene identification by capitalizing on the fact that the combined loci provide more profound, measurable protection. We have mapped the Idd10 and Idd18 loci to 1.3- and 2.0-cM intervals, respectively, by holding the Idd3 allele constant. In addition, we have excluded Csf1 and Nras as candidates for both loci.

Animals↗

PubMed2002

Challenges and strategies for investigating the genetic complexity of common human diseases.

There is substantial interest in the identification of genes underlying susceptibility to complex human diseases because of the potential utility of such genes in disease prediction or therapy. Type 1 diabetes is an example of one such disorder and is presumed to arise from the effect of multiple genes and environmental factors. One identified locus has a major effect on type 1 diabetes susceptibility (IDDM1), whereas other loci have significant, yet small, individual effects (IDDM2, IDDM15). It is unclear whether susceptibility for type 1 diabetes arises because of the effects of loci acting independently or whether there are important interactions between loci. Although genetic tools are continuing to be developed to enable examination of candidate regions, the means to identify and narrow "true" susceptibility regions continues to be limited by the lack of statistical power resulting from inadequately sized collections of families. This report provides an evaluation of the approaches for identification of regions harboring type 1 diabetes genes, methods to identify the gene regions that interact to define the risk for type 1 diabetes, and efforts to fine-map the variants responsible.

Chromosome Mapping↗

PubMed2004

A genome-wide scan for childhood obesity-associated traits in French families shows significant linkage on chromosome 6q22.31-q23.2.

We conducted a genome-wide search for childhood obesity-associated traits, including BMI >/==" BORDER="0">95th percentile (PCT95), 97th percentile (PCT97), and 99th percentile (PCT99) as well as age of adiposity rebound (AAR), which corresponds to the beginning of the second rise in childhood adiposity. A set of 431 microsatellite markers was genotyped in 506 subjects from 115 multiplex French Caucasian families, with at least one child with a BMI >/==" BORDER="0">95th percentile. Among these 115 pedigrees, 97 had at least two sibs with a BMI >/==" BORDER="0">95th percentile. Fine-mapping was performed in the seven most positive loci. Nonparametric multipoint analyses revealed six regions of significant or suggestive linkage on chromosomes 2q33.2-q36.3, 6q22.31-q23.2, and 17p13 for PCT95, PCT97, or PCT99 and 15q12-q15.1, 16q22.1-q24.1, and 19p13.3-p13.11 for AAR. The strongest evidence of linkage was detected on chromosome 6q22.31 for PCT97 (maximum likelihood score: 4.06) at the marker D6S287. This logarithm of odds score meets genome-wide significance tested through simulation (empirical genome-wide P = 0.01 [0.0027-0.0254]). Six independent ge-nome scans in adults have reported quantitative trait loci on 6q linked to energy or glucose homeostasis-associated phenotypes. Possible candidate genes in this region include SIM1, MCHR2, and PC-1.

Body Mass Index↗

PubMed2006

Genetic architecture of the APM1 gene and its influence on adiponectin plasma levels and parameters of the metabolic syndrome in 1,727 healthy Caucasians.

The associations of the adiponectin (APM1) gene with parameters of the metabolic syndrome are inconsistent. We performed a systematic investigation based on fine-mapped single nucleotide polymorphisms (SNPs) highlighting the genetic architecture and their role in modulating adiponectin plasma concentrations in a particularly healthy population of 1,727 Caucasians avoiding secondary effects from disease processes. Genotyping 53 SNPs (average spacing of 0.7 kb) in the APM1 gene region in 81 Caucasians revealed a two-block linkage disequilibrium (LD) structure and enabled comprehensive tag SNP selection. We found particularly strong associations with adiponectin concentrations for 11 of the 15 tag SNPs in the 1,727 subjects (five P values <0.0001). Haplotype analysis provided a thorough differentiation of adiponectin concentrations with 9 of 17 haplotypes showing significant associations (three P values <0.0001). No significant association was found for any SNP with the parameters of the metabolic syndrome. We observed a two-block LD structure of APM1 pointing toward at least two independent association signals, one including the promoter SNPs and a second spanning the relevant exons. Our data on a large number of healthy subjects suggest a clear modulation of adiponectin concentrations by variants of APM1, which are not merely a concomitant effect in the course of type 2 diabetes or coronary artery disease.

Adiponectin↗

PubMed2004

Assessment of positional candidate genes myf5 and igf1 for growth on bovine chromosome 5 in commercial lines of Bos taurus.

Quantitative trait loci for growth traits in beef cattle have been previously reported and fine-mapped in three chromosomal regions of 0 to 30 cM, 55 to 70 cM, and 70 to 80 cM of bovine chromosome 5. In this study, we further examined the association between gene-specific single nucleotide polymorphisms (SNP) of two positional candidate genes, bovine myogenic factor 5 (myf5) and insulin-like growth factor-1 (igf1), in the QTL regions and the birth weight (BWT), preweaning average daily gain (PWADG), and average daily gain on feed (ADGF) in commercial lines of Bos taurus. The QTL regions for the growth traits identified using a haplotype association analysis, which included the gene-specific SNP markers for both genes in this study, were in agreement with previous studies. The gene-specific SNP marker association analysis indicated that the SNP in myf5 had a significant additive effect on PWADG in the M1 line of Beefbooster Inc. (P < 0.10), and a significant additive effect (P < 0.05) and a significant dominance effect (P < 0.10) on ADGF in the M3 line of Beefbooster Inc. When the data from the two commercial lines were pooled, the SNP in myf5 showed a significant association with PWADG (P < 0.10) and with ADGF (P < 0.05). The association between the SNP and BWT, however, did not reach a significance level in the M1 line, the M3 line, or across the lines. For igf1, no significant association between the SNP and the growth traits was detected in either the M1 line or the M3 line, whereas there was only a significant dominance effect (P < 0.10) on BWT detected for the SNP in igfl when the data from the two commercial lines were pooled. These results suggest that myf5 is a strong candidate gene that influences PWADG and ADGF in beef cattle. The SNP of igf1 may not be a causative or close to the causative mutation that affects the three growth traits in the populations of beef cattle examined in this study. Other SNP of igf1 and myf5 or other genes in their respective chromosomal regions, however, should also be studied.

Alleles↗

PubMed2004

Identification and fine mapping of quantitative trait loci for backfat on bovine chromosomes 2, 5, 6, 19, 21, and 23 in a commercial line of Bos taurus.

Backfat thickness is one of the major quantitative traits that affects carcass quality in beef cattle. In this study, we identified and fine-mapped QTL for backfat EBV on bovine chromosomes 2, 5, 6, 19, 21, and 23 using an identical-by-descent haplotype-sharing analysis in a commercial line of Bos taurus. Eleven haplotypes were found to have significant associations with backfat EBV at the comparison-wise P-value threshold, and one at the chromosome-wise P-value threshold on bovine chromosomes 5, 6, 19, 21, and 23. On average, the 12 significant haplotypes had an effect of 0.62 SD on backfat EBV, ranging from 0.38 SD to 1.33 SD. The 12 significant haplotypes spanned nine chromosomal regions, one on chromosome 5 (65.4 to 70.0 cM), three on 6 (8.2 to 11.8 cM, 63.6 to 68.1 cM, and 81.5 to 83.0 cM), three on 19 (4.8 to 15.9 cM, 39.4 to 46.5 cM, and 65.7 to 99.5 cM), one on 21 (46.1 to 53.1 cM), and one on 23 (45.1 to 50.9 cM). Among the nine chromosomal regions, six were new QTL regions and three showed remarkable agreement with QTL regions that were previously reported. Eight of the nine QTL regions were localized to less than or close to 10 cM in genetic distance. The results provide a useful reference for further positional candidate gene research and marker-assisted selection for backfat.

Adipose Tissue↗

PubMed2002

Interval and composite interval mapping of somatic cell score, yield, and components of milk in dairy cattle.

Single-marker, interval-mapping (IM) and composite interval mapping (CIM) were used to detect quantitative trait loci (QTL) controlling milk, fat and protein yields, and somatic cell score (SCS). A granddaughter design was used to combine molecular genetic information with predicted transmitting abilities (PTA) and estimated daughter yield deviations (DYD) from eight Dairy Bull DNA Repository Holstein families. Models that included and excluded weights accounting for the uncertainty of the response variable were evaluated in each trait, family and phenotype (DYD and PTA) combination. The genotypic information consisted of 174 microsatellite markers along 29 Bos taurus autosomes. The average number of informative markers per autosome was three and the number of informative sons per family and marker varied between 21 and 173. Within-family results from the least squares single-marker analyses were used in expectation-maximization likelihood IM and CIM implemented with QTL Cartographer. Different CIM model specifications, offering complementary control on the background QTL outside the interval under study, were evaluated. Permutation techniques were used to calculate the genome-wide threshold test statistic values based on 1,000 samples. Results from the DYD and PTA analyses were highly consistent across traits and families. The minor differences in the estimates from the models that accounted for or ignored the uncertainty of the DYD (variance) and PTA (inverse of reliability) may be associated to the elevated and consistent precision of the DYD and PTA among sons. The CIM model best supported by the data had 10 markers controlling for background effects. On autosome (BTA) three, a QTL at 32 cM influencing protein yield was located in family five and a QTL at 74 cM for fat yield was located in family eight. Two map positions associated with SCS were detected on BTA 21, one at 33 cM in family one and the other at 84 cM in family three. A QTL for protein yield was detected between 26 and 36 cM on BTA six, family six, and a QTL for milk yield was detected at 116 cM on BTA seven in family three. The IM and CIM approaches detected a QTL at 3 cM on BTA 14 influencing fat yield in family four. Two map positions on BTA 29 were associated with significant variation of milk (0 cM) and fat yield (14 cM) in family seven. These results suggest the presence of one QTL with pleiotropic effects on multiple traits or multiple QTL within the marker interval. Findings from this study could be used in subsequent fine-mapping work and applied to marker-assisted selection of dairy production and health traits.

Animals↗

PubMed2026

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm.

BACKGROUND: Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. METHODS: We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. RESULTS: We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. CONCLUSION: This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

MAGMA↗

PubMed2005

Functional role of C-terminal sequence elements in the transporter associated with antigen processing.

TAP delivers antigenic peptides into the endoplasmic reticulum (ER) that are subsequently bound by MHC class I molecules. TAP consists of two subunits (TAP1 and TAP2), each with a transmembrane (TMD) and a nucleotide-binding (NBD) domain. The two TAP-NBDs have distinct biochemical properties and control different steps during the peptide translocation process. We noted previously that the nonhomologous C-terminal tails of rat TAP1 and TAP2 determine the distinct functions of TAP-NBD1 and -NBD2. To identify the sequence elements responsible for the asymmetrical NBD function, we constructed chimeric rat TAP variants in which we systematically exchanged sequence regions of different length between the two TAP-NBDs. Our fine-mapping studies demonstrate that a nonhomologous region containing the alpha6/beta10-loop in conjunction with the downstream switch region is directly responsible for the functional separation of the TAP-NBDs. The alpha6/beta10-loop determines the nonsynonymous nucleotide binding of NBD1 and NBD2, whereas the switch region seems to play a critical role in regulating the functional cross-talk between the structural domains of TAP. Based on our findings, we postulate that these two sequence elements build a minimal functional unit that controls the asymmetry of the two TAP-NBDs.

ATP-Binding Cassette Transporters↗

PubMed2026

FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g. electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (Fine-mapping of causal Genes for Phenome-wide Transcriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., binary, count or continuous) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes BCAS3, LRRC37A, NOS2P3, ARL17B and UBB on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT's power to disentangle complex gene-phenotype relationships in large-scale phenome-wide studies, uncovering shared biological mechanisms across diverse human traits and advancing translational and comorbidity research.

Bayesian fine mapping↗

PubMed2026

Developmental patterning of adipose tissue by abd-A and Abd-B homeotic genes in Drosophila melanogaster.

The Bithorax Complex (BX-C) homeobox proteins specify segmental identities along the anterior-posterior axis during Drosophila embryogenesis. Differential expression of the BX-C genes abd-A and Abd-B distinguishes abdominal from thoracic adipocytes, yet the mechanism regulating this heterogeneity remains poorly understood. Here, we identify cis-regulatory elements (CREs) and transcription factors that direct abdominal-specific expression of abd-A and Abd-B in the larval fat body. Fine-mapping analyses identified a 627-bp CRE within the Abd-B locus and a ~6-kb CRE within the abd-A locus sufficient to drive heterogeneous expression. Yeast one-hybrid screening combined with functional analyses identified Lola, Lolal, and Combgap as key repressors of Abd-B, whereas Piragua (Prg) and Seven up (Svp) function as transcriptional activators, indicating that adipocyte heterogeneity in postembryonic adipose tissue is actively regulated. In turn, lola and prg are repressed by Abd-B, whereas lolal and svp are activated, forming a feedback circuit further modulated by Wnt signaling, which promotes lola and lolal expression while repressing svp. CUT&RUN analyses suggest that these interactions are direct, with dTCF/Pan and Abd-B occupancy detected at target loci. Together, our findings define a transcriptional circuit that regulates Abd-B gene transcription to pattern adipose tissue and may establish the developmental basis of fat depot specialization.

Abd-B↗

PubMed2026

Multimodal atlas of human atherosclerosis links granular vascular cell states to coronary artery disease risk.

Advances in single-cell and spatial assays have revolutionized the scale and resolution of molecular tissue profiling. Here we present MetaPlaq, a multimodal atlas of human atherosclerotic arterial beds comprising over a million cells across single-cell transcriptomics, epigenomics and high-resolution spatial expression assays. We map granular cell states and disease-relevant transcriptional programs within the native tissue context of coronary arteries. Furthermore, we map cardiovascular GWAS signals to smooth muscle cells (SMCs) and endothelial cells (ECs) and uncover the cis-regulatory architecture governing their phenotypic transitions. Our comprehensive epigenomic reference allowed us to build cell-specific enhancer-gene link maps and multimodal gene regulatory networks (GRNs) underlying disease-relevant states such as osteogenic SMCs and ECs undergoing mesenchymal transition. We also integrate SMC and EC disease-associated gene sets with GRNs to nominate key transcription factors such as PRRX1, BNC2 and ELK3 regulating atherosclerosis-relevant transcriptional programs. Finally, we layer single-cell and spatial modalities to fine-map GWAS variants with improved cell and anatomical context. We highlight candidate cell-specific regulatory mechanisms at less characterized CAD loci, including FGD5 and MCF2L in ECs. Together, this atlas represents an important step towards fully interpreting genetic risk loci and informing new therapeutic strategies for cardiovascular disease.

Journal Article↗

PubMed2026

Integrating multi-ancestry common and rare variant mapping accelerates therapeutic target discovery.

Integrating human genetics into therapeutic discovery accelerates drug development. However, ancestral biases in historical cohorts have left critical functional variation largely uncharted. Here, we leverage the diverse NIH All of Us Research Program to conduct comprehensive common- and rare-variant association analyses for 624 quantitative traits across 369,655 ancestrally diverse individuals. We identified 6,181 genome-wide significant locus-trait associations (526 novel) and 416 gene-trait associations (105 novel) via rare-variant burden testing. By integrating fine-mapping with computational variant-effect predictors, we systematically prioritized rare, likely causal variants driving these signals. Jointly modeling common and rare variation with protein-class annotations significantly improved the identification of known drug targets compared to common-variant analysis alone. Notably, we identified NRG4 as a high-confidence candidate therapeutic target for preserving kidney function. Our findings demonstrate that characterization of rare and common variation across diverse populations enhances causal gene discovery and identifies novel, actionable therapeutic targets.

Journal Article↗