motifbreakR: an R/Bioconductor package for predicting variant effects at transcription factor binding sites

Regulatory non-coding somatic mutations as drivers of neuroblastoma

BACKGROUND

Emerging evidence suggests that non-coding somatic single nucleotide variants (SNVs) in cis-regulatory elements (CREs) contribute to cancer by disrupting gene expression networks. However, the role of non-coding SNVs in cancer, particularly neuroblastoma, remains largely unclear.

METHODS

SNVs effect on CREs activity was evaluated by luciferase assays. Motif analysis and ChIP-qPCR experiments were employed to reveal the transcription factors (TFs) involved in these processes. We exploited CRISPR-Cas9 experiments to elucidate the role of these SNVs on the CREs target genes expression. Cell proliferation and invasion assays were performed to assess their role in neuroblastoma tumorigenesis.

RESULTS

Our findings demonstrate that non-coding SNVs modify the transcriptional activity of two CREs altering the binding of STAT3 and SIN3A. Therefore, these SNVs reduce the expression of CTTNBP2 and MCF2L. We demonstrate that these two genes act as tumor suppressor in neuroblastoma. These pathogenetic SNVs may serve as oncogenic drivers by impairing the transcriptional programs essential for neuronal development and differentiation in which both the investigated TFs and target genes are involved.

CONCLUSION

Overall, the understanding of the functional role of non-coding variants elucidates their impact on tumorigenesis and can uncover new potential targets of cancer therapeutic strategies.

Comparative characterization of human accelerated regions in neurons

Human accelerated regions (HARs) are conserved genomic loci that have experienced rapid nucleotide substitutions following the divergence from chimpanzees1,2. HARs are enriched in candidate regulatory regions near neurodevelopmental genes, suggesting their roles in gene regulation3. However, their target genes and functional contributions to human brain development remain largely uncharacterized. Here we elucidate the cis-regulatory functions of HARs in human and chimpanzee induced pluripotent stem (iPS) cell-induced excitatory neurons. Using genomic4 and chromatin looping information, we prioritized 20 HARs and their chimpanzee orthologues for functional characterization via single-cell CRISPR interference, and demonstrated their species-specific gene regulatory functions. Our findings reveal diverse functional outcomes of HAR-mediated cis-regulation in human neurons, including attenuated NPAS3 expression by altering the binding affinities of multiple transcription factors in HAR202 and maintaining iPS cell pluripotency and neuronal differentiation capacities through the upregulation of PUM2 by 2xHAR.319. Finally, we used prime editing to demonstrate differential enhancer activity caused by several HAR26;2xHAR.178 variants. In particular, we link one variant in HAR26;2xHAR.178 to elevated SOCS2 expression and increased neurite outgrowth in human neurons. Thus, our study sheds new light on the endogenous gene regulatory functions of HARs and their potential contribution to human brain evolution.

Massively parallel assessment of gene regulatory activity at human cortical structure associated variants

Genetic association studies have identified hundreds of largely non-coding loci associated with inter-individual differences in the structure of the human cortex, though the specific genetic variants that impact regulatory activity are unknown. We implemented a Massively Parallel Reporter Assay (MPRA) to measure the regulatory activity of 9,092 cortical structure associated DNA variants in human neural progenitor cells during Wnt stimulation and at baseline. We identified 918 variants with regulatory potential from 150 cortical structure associated loci (76% of loci studied), of which >50% showed allelic effects. Wnt stimulation modified regulatory activity at a subset of loci that functioned as condition-dependent enhancers. Regulatory activity in MPRA was largely induced by Alu elements that were hypothesized to contribute to cortical expansion. The regionally specific impact of genetic variants that disrupt motifs is likely mediated through the levels of transcription factor expression during development, further clarifying the molecular mechanisms altering cortical structure.

Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer

Genome-wide association studies have identified thousands of genetic variants associated with non-small cell lung cancer (NSCLC), however, it is still challenging to determine the causal variants and to improve disease risk prediction. Here, we applied massively parallel reporter assays to perform NSCLC variant-to-function mapping at scale. A total of 1249 candidate variants were evaluated, and 30 potential causal variants within 12 loci were identified. Accordingly, we proposed three genetic architectures underlying NSCLC susceptibility: multiple causal variants in a single haplotype block (e.g. 4q22.1), multiple causal variants in multiple haplotype blocks (e.g. 5p15.33), and a single causal variant (e.g. 20q11.23). We developed a modified polygenic risk score using the potential causal variants from Chinese populations, improving the performance of risk prediction in 450,821 Europeans from the UK Biobank. Our findings not only augment the understanding of the genetic architecture underlying NSCLC susceptibility but also provide strategy to advance NSCLC risk stratification.

Genetic coupling of enhancer activity and connectivity in gene expression control

Gene enhancers often form long-range contacts with promoters, but it remains unclear if the activity of enhancers and their chromosomal contacts are mediated by the same DNA sequences and recruited factors. Here, we study the effects of expression quantitative trait loci (eQTLs) on enhancer activity and promoter contacts in primary monocytes isolated from 34 male individuals. Using eQTL-Capture Hi-C and a Bayesian approach considering both intra- and inter-individual variation, we initially detect 19 eQTLs associated with enhancer-eGene promoter contacts, most of which also associate with enhancer accessibility and activity. Capitalising on these shared effects, we devise a multi-modality Bayesian strategy, identifying 629 "trimodal QTLs" jointly associated with enhancer accessibility, eGene promoter contact, and gene expression. Causal mediation analysis and CRISPR interference reveal causal relationships between these three modalities. Many detected QTLs overlap disease susceptibility loci and influence the predicted binding of myeloid transcription factors, including SPI1, GABPB and STAT3. Additionally, a variant associated with PCK2 promoter contact directly disrupts a CTCF binding motif and impacts promoter insulation from downstream enhancers. Jointly, our findings suggest an inherent genetic coupling of enhancer activity and connectivity in gene expression control relevant to human disease and highlight the regulatory role of genetically determined chromatin boundaries.

Massively parallel reporter assay investigates shared genetic variants of eight psychiatric disorders

A meta-genome-wide association study across eight psychiatric disorders has highlighted the genetic architecture of pleiotropy in major psychiatric disorders. However, mechanisms underlying pleiotropic effects of the associated variants remain to be explored. We conducted a massively parallel reporter assay to decode the regulatory logic of variants with pleiotropic and disorder-specific effects. Pleiotropic variants differ from disorder-specific variants by exhibiting chromatin accessibility that extends across diverse cell types in the neuronal lineage and by altering motifs for transcription factors with higher connectivity in protein-protein interaction networks. We mapped pleiotropic and disorder-specific variants to putative target genes using functional genomics approaches and CRISPR perturbation. In vivo CRISPR perturbation of a pleiotropic and a disorder-specific gene suggests that pleiotropy may involve the regulation of genes expressed broadly across neuronal cell types and with higher network connectivity.

Three regulatory elements upstream of LMO4 are strongly associated with intermittent fertilization intensity in Chicken

Intermittent fertilization intensity (IFI) is closely related to higher fertilization in chicken hens. Recent studies have identified genes influencing sperm-oocyte interactions and immune regulation that impact the fertilization process in chickens. This research aims to identify key candidate genes and variants regulating IFI through transcriptomic analysis and dual luciferase assays. Our study's transcriptomic analysis of 12 individuals exhibiting extreme IFI revealed several key candidate genes. Validation using quantitative PCR highlighted PRSS12, DNER, WIF1, and NRXN1 as potential contributors to variations in IFI. Notably, we observed significant differences in the expression of LMO4, located 247.2 kb downstream of IFI-associated genomic regions. To explore variants potentially involved in the regulation of LMO4, we conducted short variant annotation and SV-GWAS, but found no significant associations with IFI. Further motif analysis and dual luciferase validation uncovered three regulatory elements within the associated region that exhibited enhanced promoter or enhancer activity following significant SNP mutations. In conclusion, our findings indicate that LMO4, PRSS12, DNER, WIF1, and NRXN1 serve as primary candidate genes for regulating IFI. Additionally, three regulatory elements significantly associated with IFI were identified upstream of LMO4. These variants hold promise for use in selecting low-IFI lines.

Altered chromatin landscape and 3D interactions associated with primary constitutional MLH1 epimutations

BACKGROUND

Lynch syndrome (LS), characterised by an increased risk for cancer, is mainly caused by germline pathogenic variants affecting a mismatch repair gene (MLH1, MSH2, MSH6, PMS2). Occasionally, LS may be caused by constitutional MLH1 epimutation (CME) characterised by soma-wide methylation of one allele of the MLH1 promoter. Most of these are "primary" epimutations, arising de novo without any apparent underlying cis-genetic cause, and are reversible between generations. We aimed to characterise genetic and gene regulatory changes associated with primary CME to elucidate possible underlying molecular mechanisms.

METHODS

Four carriers of a primary CME and three non-methylated relatives carrying the same genetic haplotype were included. Genetic alterations were sought using linked-read WGS in blood DNA. Transcriptome (RNA-seq), chromatin landscape (ATAC-seq, H3K27ac CUT&Tag) and 3D chromatin interactions (UMI-4C) were studied in lymphoblastoid cell lines. The MLH1 promoter SNP (c.-93G > A, rs1800734) was used as a reporter in heterozygotes to assess allele-specific chromatin conformation states.

RESULTS

MLH1 epimutant alleles presented a closed chromatin conformation and decreased levels of H3K27ac, as compared to the unmethylated allele. Moreover, the epimutant MLH1 promoter exhibited differential 3D chromatin contacts, including lost and gained interactions with distal regulatory elements. Of note, rare genetic alterations potentially affecting transcription factor binding sites were found in the promoter-contacting region of CME carriers.

CONCLUSIONS

Primary CMEs present allele-specific differential interaction patterns with neighbouring genes and regulatory elements. The role of the identified cis-regulatory regions in the molecular mechanism underlying the origin and maintenance of CME requires further investigation.

Cell-type-resolved chromatin accessibility in the human intestine identifies complex regulatory programs and clarifies genetic associations in Crohn's disease

Crohn's disease (CD) is a complex inflammatory bowel disease resulting from an interplay of genetic, microbial, and environmental factors. Cell-type-specific contributions to CD etiology and genetic risk are incompletely understood. Here we built a comprehensive atlas of cell-type- resolved chromatin accessibility comprising 557,310 candidate cis-regulatory elements (cCREs) in terminal ileum and ascending colon from patients with active and inactive CD and healthy controls. Using this atlas, we identified cell-type-, anatomic location-, and context-specific cCREs and characterized the regulatory programs underlying inflammatory responses in the intestinal mucosa of CD patients. Genetic variants that disrupt binding motifs of cell-type-specific transcription factors significantly affected chromatin accessibility in specific mucosal cell types. We found that CD heritability is primarily enriched in immune cell types. However, using fine- mapped non-coding CD variants we identified 29 variants located within cCREs several of which were accessible in epithelial and stromal cells implicating cell types from additional lineages in mediating CD risk in some loci. Our atlas provides a comprehensive resource to study gene regulatory effects in CD and health, and highlights the cellular complexity underlying CD risk.

Rare disease genomics and precision medicine

Rare diseases, though individually uncommon, collectively affect millions worldwide. Genomic technologies and big data analytics have revolutionized diagnosing and understanding these conditions. This review explores the role of genomics in rare disease research, the impact of large consortium initiatives, advancements in extensive data analysis, the integration of artificial intelligence (AI) and machine learning (ML), and the therapeutic implications in precision medicine. We also discuss the challenges of data sharing and privacy concerns, emphasizing the need for collaborative efforts and secure data practices to advance rare disease research.

Systematic identification of pathogenic variants of non-small cell lung cancer in the promoters of DNA-damage repair genes

BACKGROUND

Deficiency in DNA-damage repair (DDR) genes, often due to disruptive coding variants, is linked to higher cancer risk. Our previous study has revealed the association between rare loss-of-function variants in DDR genes and the risk of lung cancer. However, it is still challenging to study the predisposing role of rare regulatory variants of these genes.

METHODS

Based on whole-genome sequencing data from 2984 patients with non-small cell lung cancer (NSCLC) and 3020 controls, we performed massively parallel reporter assays on 1818 rare variants located in the promoters of DDR genes. Pathway- or gene-level burden analyses were performed using Firth's logistic regression or generalized linear model.

FINDINGS

We identified 750 rare functional regulatory variants (frVars) that showed allelic differences in transcriptional activity within the promoter regions of DDR genes. Interestingly, the burden of frVars was significantly elevated in cases (odds ratio [OR] = 1.17, p = 0.026), whereas the burden of variants prioritized solely based on bioinformatics annotation was comparable between cases and controls (OR = 1.04, p = 0.549). Among the frVars, 297 were down-regulated transcriptional activity (dr-frVars) and 453 were up-regulated transcriptional activity (ur-frVars); especially, dr-frVars (OR = 1.30, p = 0.008) rather than ur-frVars (OR = 1.06, p = 0.495) were significantly associated with risk of NSCLC. Individuals with NSCLC carried more dr-frVars from Fanconi anemia, homologous recombination, and nucleotide excision repair pathways. In addition, we identified seven genes (i.e., BRCA2, GTF2H1, DDB2, BLM, ALKBH2, APEX1, and RAD51B) with promoter dr-frVars that were associated with lung cancer susceptibility.

INTERPRETATION

Our findings indicate that functional promoter variants in DDR genes, in addition to protein-truncating variants, can be pathogenic and contribute to lung cancer susceptibility.

FUNDING

National Natural Science Foundation of China, Youth Foundation of Jiangsu Province, Research Unit of Prospective Cohort of Cardiovascular Diseases and Cancer of Chinese Academy of Medical Sciences, and Natural Science Foundation of Jiangsu Province.

Stimulating Wnt signaling reveals context-dependent genetic effects on gene regulation in primary human neural progenitors

Gene regulatory effects have been difficult to detect at many non-coding loci associated with brain-related traits, likely because some genetic variants have distinct functions in specific contexts. To explore context-dependent gene regulation, we measured chromatin accessibility and gene expression after activation of the canonical Wnt pathway in primary human neural progenitors (n = 82 donors). We found that TCF/LEF motifs and brain-structure-associated and neuropsychiatric-disorder-associated variants were enriched within Wnt-responsive regulatory elements. Genetically influenced regulatory elements were enriched in genomic regions under positive selection along the human lineage. Wnt pathway stimulation increased detection of genetically influenced regulatory elements/genes by 66%/53% and enabled identification of 397 regulatory elements primed to regulate gene expression. Stimulation also increased identification of shared genetic effects on molecular and complex brain traits by up to 70%, suggesting that genetic variant function during neurodevelopmental patterning can lead to differences in adult brain and behavioral traits.

Hierarchical annotation of eQTLs by H-eQTL enables identification of genes with cell type-divergent regulation

While context-type-specific regulation of genes is largely determined by cis-regulatory regions, attempts to identify cell type-specific eQTLs are complicated by the nested nature of cell types. We present hierarchical eQTL (H-eQTL), a network-based model for hierarchical annotation of bulk-derived eQTLs to levels of a cell type tree using single-cell chromatin accessibility data and no clustering of cells into discrete cell types. Using our model, we annotate bulk-derived eQTLs from the developing brain with high specificity to levels of a cell type hierarchy, which allows sensitive detection of genes with multiple distinct non-coding elements regulating their expression in different cell types.

Analysis of cis-regulatory changes underlying phenotype divergence shaped by domestication in pigs

Background

Cis-regulatory elements (CREs) are regions of DNA that regulate the expression of nearby genes. Changes in these elements can lead to phenotypic variations and adaptations in different populations. However, the regulatory dynamics underlying the local adaptation of traits remain poorly understood in Chinese and Western pigs. By comparing the chromatin accessibility profiles of skeletal muscle, liver, and fat between these two pig populations, we aimed to identify key regulatory elements that could explain phenotypic differences observed between the two groups.

Results

Our results revealed that the genome-wide chromatin accessibility profiles were largely similar at a qualitative level within tissues. However, we also identified local regions that exhibited quantitative differences, most of which occurred in liver tissue. Interestingly, we found that most of the increased chromatin accessibility in the livers of Chinese pigs was associated with tissue-specific openness. Furthermore, we observed a positive correlation between the ATAC-seq signal at the transcript start site (TSS) and the expression levels of nearby genes. Motif enrichment analysis revealed NR2F1 as a key regulator in Chinese pigs. Differentially expressed genes (DEGs) in Chinese pigs showed enrichment for NR2F1 response targets. One of the genes regulated by NR2F1 in Chinese pigs, NPC1, harbored a high alternative allelic frequency in the intron region.

Conclusion

Overall, our study provides valuable insights into the regulatory dynamics underlying phenotypic variation in pigs. By elucidating the role of CREs in driving phenotypic variation, we can better understand the genetic basis of complex traits and potentially identify targets for genetic improvement in livestock breeding programs.

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Melanoma-specific mutation hotspots in distal, non-coding, promoter-interacting regions implicate novel candidate driver genes

BACKGROUND

To develop targeted treatments, it is crucial to identify the full spectrum of genetic drivers in melanoma, including those in non-coding regions. However, recent efforts to explore non-coding regions have primarily focused on gene-adjacent elements such as promoters and non-coding RNAs, leaving intergenic distal regulatory elements largely unexplored.

METHODS

We used Hi-C chromatin contact data from melanoma cells to map distal, non-coding, promoter-interacting regulatory elements genome-wide in melanoma. Using this "promoter-interaction network", alongside whole-genome sequence and gene expression data from the Pan Cancer Analysis of Whole Genomes, we developed multivariate linear regression models to identify distal somatic mutation hotspots that affect promoter activity.

RESULTS

We identified eight recurrently mutated hotspots that are novel, melanoma-specific, located in promoter-interacting distal regulatory elements, alter transcription factor binding motifs, and affect the expression of genes (e.g., HSPB7, CLDN1, ADCY9 and FDXR) previously implicated as tumour suppressors/oncogenes in various cancers.

CONCLUSIONS

Our study suggests additional non-coding drivers beyond the well-characterised TERT promoter in melanoma, offering new insights into the disruption of complex regulatory networks by non-coding mutations that may contribute to melanoma development. Furthermore, our study provides a framework for integrating multiple levels of biological data to uncover cancer-specific non-coding drivers.

Linking candidate causal autoimmune variants to T cell networks using genetic and epigenetic screens in primary human T cells

Genetic variants associated with autoimmune diseases are highly enriched within putative cis -regulatory regions of CD4 + T cells, suggesting that they alter disease risk via changes in gene regulation. However, very few genetic variants have been shown to affect T cell gene expression or function. We tested >18,000 autoimmune disease-associated variants for allele-specific expression using massively parallel reporter assays in primary human CD4 + T cells. The 545 expression-modulating variants (emVars) identified greatly enrich for likely causal variants. We provide evidence that many emVars are mediated by common upstream regulatory conduits, and that putative target genes of primary T cell emVars are highly enriched within a lymphocyte activation network. Using bulk and single-cell CRISPR-interference screens, we confirm that emVar-containing T cell cis -regulatory elements modulate both known and novel target genes that regulate T cell proliferation, providing plausible mechanisms by which these variants alter autoimmune disease risk.

A compendium of genetic variations associated with promoter usage across 49 human tissues

Promoters play a crucial role in regulating gene transcription. However, our understanding of how genetic variants influence alternative promoter selection is still incomplete. In this study, we implement a framework to identify genetic variants that affect the relative usage of alternative promoters, known as promoter usage quantitative trait loci (puQTLs). By constructing an atlas of human puQTLs across 49 different tissues from 838 individuals, we have identified approximately 76,856 independent loci associated with promoter usage, encompassing 602,009 genetic variants. Our study demonstrates that puQTLs represent a distinct type of molecular quantitative trait loci, effectively uncovering regulatory targets and patterns. Furthermore, puQTLs are regulating in a tissue-specific manner and are enriched with binding sites of epigenetic marks and transcription factors, especially those involved in chromatin architecture formation. Notably, we have also found that puQTLs colocalize with complex traits or diseases and contribute to their heritability. Collectively, our findings underscore the significant role of puQTLs in elucidating the molecular mechanisms underlying tissue development and complex diseases.

Genetic architecture of oral glucose-stimulated insulin release provides biological insights into type 2 diabetes aetiology

The genetics of β-cell function (BCF) offer valuable insights into the aetiology of type 2 diabetes (T2D)1,2. Previous studies have expanded the catalogue of BCF genetic associations through candidate gene studies3-7, large-scale genome-wide association studies (GWAS) of fasting BCF8,9 or functional islet studies on T2D risk variants10-14. Nonetheless, GWAS focused on BCF traits derived from oral glucose tolerance test (OGTT) data have been limited in sample size15,16 and have often overlooked the potential for related traits to capture distinct genetic features of insulin-producing β-cells17,18. We reasoned that investigating the genetic basis of multiple BCF estimates could provide a broader understanding of β-cell physiology. Here, we aggregate GWAS data of eight OGTT-based BCF traits from ~26,000 individuals of European descent, identifying 55 independent genetic associations at 44 loci. By examining the effects of BCF genetic signals on related phenotypes, we uncover diverse disease mechanisms whereby genetic regulation of BCF may influence T2D risk. Integrating BCF-GWAS data with pancreatic islet transcriptomic and epigenomic datasets reveals 92 candidate effector genes. Gene silencing in β-cell models highlights ACSL1 and FAM46C as key regulators of insulin secretion. Overall, our findings yield insights into the biology of insulin release and the molecular processes linking BCF to T2D risk, shedding light on the heterogeneity of T2D pathophysiology.

Large-scale multi-omic analysis identifies noncoding somatic driver mutations and nominates ZFP36L2 as a driver gene for pancreatic ductal adenocarcinoma

Identification of somatic driver mutations in the noncoding genome remains challenging. To comprehensively characterize noncoding driver mutations for pancreatic ductal adenocarcinoma (PDAC), we first created genome-scale maps of accessible chromatin regions (ACRs) and histone modification marks (HMMs) in pancreatic cell lines and purified pancreatic acinar and duct cells. Integration with whole-genome mutation calls from 506 PDACs revealed 314 ACRs/HMMs significantly enriched with 3,614 noncoding somatic mutations (NCSMs). Functional assessment using massively parallel reporter assays (MPRA) identified 178 NCSMs impacting reporter activity (19.45% of those tested). Focused luciferase validation confirmed negative effects on gene regulatory activity for NCSMs near CDKN2A and ZFP36L2. For the latter, CRISPR interference (CRISPRi) further identified ZFP36L2 as a target gene (16.0 - 24.0% reduced expression, P = 0.023-0.0047) with disrupted KLF9 binding likely mediating the effect. Our integrative approach provides a catalog of potentially functional noncoding driver mutations and nominates ZFP36L2 as a PDAC driver gene.

Allele-specific transcription factor binding across human brain regions offers mechanistic insight into eQTLs

Transcription factors (TFs) regulate gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because TF occupancy is driven in part by recognition of DNA sequence, genetic variation can influence TF-DNA associations and gene regulation. To identify variants that impact TF binding in human brain tissues, we assessed allele-specific binding (ASB) at heterozygous variants for 94 TFs in nine brain regions from two donors. Leveraging graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signals between alleles at heterozygous variants within each brain region and identified thousands of variants exhibiting ASB for at least one TF. ASB reproducibility was measured by comparisons between independent experiments both within and between donors. We found that rare alleles in the general population more frequently led to reduced TF binding, whereas common alleles had an equal likelihood of increasing or decreasing binding. Further, for ASB variants in predicted binding motifs, the favored allele tended to be the one with the stronger expected motif match, but this concordance was not observed within highly occupied sites. We also found that neuron-specific cis-regulatory elements (cCREs), in contrast with oligodendrocyte-specific cCREs, showed depletion of ASB variants. We identified 2670 ASB variants associated with evidence for allele-specific gene expression in the brain from GTEx data and observed increasing eQTL effect direction concordance as ASB significance increases. These results provide a valuable and unique resource for mechanistic analysis of cis-regulatory variation in human brain tissue.

Deciphering the functional impact of Alzheimer's Disease-associated variants in resting and proinflammatory immune cells

Genome-wide association studies have identified loci associated with Alzheimer's Disease (AD), but identifying the exact causal variants and genes at each locus is challenging due to linkage disequilibrium and their largely non-coding nature. To address this, we performed a massively parallel reporter assay of 3,576 AD-associated variants in THP-1 macrophages in both resting and proinflammatory states and identified 47 expression-modulating variants (emVars). To understand the endogenous chromatin context of emVars, we built an activity-by-contact model using epigenomic maps of macrophage inflammation and inferred condition-specific enhancer-promoter pairs. Intersection of emVars with enhancer-promoter pairs and microglia expression quantitative trait loci allowed us to connect 39 emVars to 76 putative AD risk genes enriched for AD-associated molecular signatures. Overall, systematic characterization of AD-associated variants enhances our understanding of the regulatory mechanisms underlying AD pathogenesis.

Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes

Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

A multi-layered integrative analysis reveals a cholesterol metabolic program in outer radial glia with implications for human brain evolution

The definition of molecular and cellular mechanisms contributing to brain ontogenetic trajectories is essential to investigate the evolution of our species. Yet their functional dissection at an appropriate level of granularity remains challenging. Capitalizing on recent efforts that have extensively profiled neural stem cells from the developing human cortex, we develop an integrative computational framework to perform trajectory inference and gene regulatory network reconstruction, (pseudo)time-informed non-negative matrix factorization for learning the dynamics of gene expression programs, and paleogenomic analysis for a higher-resolution mapping of derived regulatory variants in our species in comparison with our closest relatives. We provide evidence for cell type-specific regulation of gene expression programs during indirect neurogenesis. In particular, our analysis uncovers a key role for a cholesterol program in outer radial glia, regulated by zinc-finger transcription factor KLF6. A cartography of the regulatory landscape impacted by Homo sapiens-derived variants reveals signals of selection clustering around regulatory regions associated with GLI3, a well-known regulator of radial glial cell cycle, and impacting KLF6 regulation. Our study contributes to the evidence of significant changes in metabolic pathways in recent human brain evolution.

Rare variation in non-coding regions with evolutionary signatures contributes to autism spectrum disorder risk

Little is known about the role of non-coding regions in the etiology of autism spectrum disorder (ASD). We examined three classes of non-coding regions: human accelerated regions (HARs), which show signatures of positive selection in humans; experimentally validated neural VISTA enhancers (VEs); and conserved regions predicted to act as neural enhancers (CNEs). Targeted and whole-genome analysis of >16,600 samples and >4,900 ASD probands revealed that likely recessive, rare, inherited variants in HARs, VEs, and CNEs substantially contribute to ASD risk in probands whose parents share ancestry, which enriches for recessive contributions, but modestly contribute, if at all, in simplex family structures. We identified multiple patient variants in HARs near IL1RAPL1 and in VEs near OTX1 and SIM1 and showed that they change enhancer activity. Our results implicate both human-evolved and evolutionarily conserved non-coding regions in ASD risk and suggest potential mechanisms of how regulatory changes can modulate social behavior.

Implications of noncoding regulatory functions in the development of insulinomas

Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

Physiological variability in pancreatic cell type gene regulation and the impact on diabetes risk is poorly understood. In this study we mapped gene regulation in pancreatic cell types using single cell multiomic (joint RNA-seq and ATAC-seq) profiling in 28 non-diabetic donors in combination with single cell data from 35 non-diabetic donors in the Human Pancreas Analysis Program. We identified widespread associations with age, sex, BMI, and HbA1c, where gene regulatory responses were highly cell type- and phenotype-specific. In beta cells, donor age associated with hypoxia, apoptosis, unfolded protein response, and external signal-dependent transcriptional regulators, while HbA1c associated with inflammatory responses and gender with chromatin organization. We identified 10.8K loci where genetic variants were QTLs for cis regulatory element (cRE) accessibility, including 20% with lineage- or cell type-specific effects which disrupted distinct transcription factor motifs. Type 2 diabetes and glycemic trait associated variants were enriched in both phenotype- and QTL-associated beta cell cREs, whereas type 1 diabetes showed limited enrichment. Variants at 226 diabetes and glycemic trait loci were QTLs in beta and other cell types, including 40 that were statistically colocalized, and annotating target genes of colocalized QTLs revealed genes with putatively novel roles in disease. Our findings reveal diverse responses of pancreatic cell types to phenotype and genotype in physiology, and identify pathways, networks, and genes through which physiology impacts diabetes risk.

Parallel Evolution at the Regulatory Base-Pair Level Contributes to Mammalian Interspecific Differences in Polygenic Traits

Parallel evolution occurs when distinct lineages with similar ancestral states converge on a new phenotype. Parallel evolution has been well documented at the organ, gene pathway, and amino acid sequence level but in theory, it can also occur at individual nucleotides within noncoding regions. To examine the role of parallel evolution in shaping the biology of mammalian complex traits, we used data on single-nucleotide polymorphisms (SNPs) influencing human intraspecific variation to predict trait values in other species for 11 complex traits. We found that the alleles at SNP positions associated with human intraspecific height and red blood cell (RBC) count variation are associated with interspecific variation in the corresponding traits across mammals. These associations hold for deeper branches of mammalian evolution as well as between strains of collaborative cross mice. While variation in RBC count between primates uses both ancient and more recently evolved genomic regions, we found that only primate-specific elements were correlated with primate body size. We show that the SNP positions driving these signals are flanked by conserved sequences, maintain synteny with target genes, and overlap transcription factor binding sites. This work highlights the potential of conserved but tunable regulatory elements to be reused in parallel to facilitate evolutionary adaptation in mammals.

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer

Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

Dynamic stress- and inflammatory-based regulation of psychiatric risk loci in human neurons

The prenatal environment can alter neurodevelopmental and clinical trajectories, markedly increasing risk for psychiatric disorders in childhood and adolescence. To understand if and how fetal exposures to stress and inflammation exacerbate manifestation of genetic risk for complex brain disorders, we report a large-scale context-dependent massively parallel reporter assay (MPRA) in human neurons designed to catalogue genotype x environment (GxE) interactions. Across 240 genome-wide association study (GWAS) loci linked to ten brain traits/disorders, the impact of hydrocortisone, interleukin 6, and interferon alpha on transcriptional activity is empirically evaluated in human induced pluripotent stem cell (hiPSC)-derived glutamatergic neurons. Of ~3,500 candidate regulatory risk elements (CREs), 11% of variants are active at baseline, whereas cue-specific CRE regulatory activity range from a high of 23% (hydrocortisone) to a low of 6% (IL-6). Cue-specific regulatory activity is driven, at least in part, by differences in transcription factor binding activity, the gene targets of which show unique enrichments for brain disorders as well as co-morbid metabolic and immune syndromes. The dynamic nature of genetic regulation informs the influence of environmental factors, reveals a mechanism underlying pleiotropy and variable penetrance, and identifies specific risk variants that confer greater disorder susceptibility after exposure to stress or inflammation. Understanding neurodevelopmental GxE interactions will inform mental health trajectories and uncover novel targets for therapeutic intervention.

MotifbreakR v2: extended capability and database integration

MotifbreakR is a software tool that scans genetic variants against position weight matrices of transcription factors (TF) to determine the potential for the disruption of TF binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to operate across a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single nucleotide variants (common and rare SNVs) on potential TF binding sites, in motifbreakR v2, we have updated the functionality. New features include the ability to query other types of more complex genetic variants, such as short insertions and deletions (indels). This function allows modeling a more extensive array of variants that may have more significant effects on TF binding. Additionally, while TF binding is based partly on sequence preference, predictions of TF binding based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR implements querying the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we have implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.

Single-nucleus multi-omics of Parkinson's disease reveals a glutamatergic neuronal subtype susceptible to gene dysregulation via alteration of transcriptional networks

The genetic architecture of Parkinson's disease (PD) is complex and multiple brain cell subtypes are involved in the neuropathological progression of the disease. Here we aimed to advance our understanding of PD genetic complexity at a cell subtype precision level. Using parallel single-nucleus (sn)RNA-seq and snATAC-seq analyses we simultaneously profiled the transcriptomic and chromatin accessibility landscapes in temporal cortex tissues from 12 PD compared to 12 control subjects at a granular single cell resolution. An integrative bioinformatic pipeline was developed and applied for the analyses of these snMulti-omics datasets. The results identified a subpopulation of cortical glutamatergic excitatory neurons with remarkably altered gene expression in PD, including differentially-expressed genes within PD risk loci identified in genome-wide association studies (GWAS). This was the only neuronal subtype showing significant and robust overexpression of SNCA. Further characterization of this neuronal-subpopulation showed upregulation of specific pathways related to axon guidance, neurite outgrowth and post-synaptic structure, and downregulated pathways involved in presynaptic organization and calcium response. Additionally, we characterized the roles of three molecular mechanisms in governing PD-associated cell subtype-specific dysregulation of gene expression: (1) changes in cis-regulatory element accessibility to transcriptional machinery; (2) changes in the abundance of master transcriptional regulators, including YY1, SP3, and KLF16; (3) candidate regulatory variants in high linkage disequilibrium with PD-GWAS genomic variants impacting transcription factor binding affinities. To our knowledge, this study is the first and the most comprehensive interrogation of the multi-omics landscape of PD at a cell-subtype resolution. Our findings provide new insights into a precise glutamatergic neuronal cell subtype, causal genes, and non-coding regulatory variants underlying the neuropathological progression of PD, paving the way for the development of cell- and gene-targeted therapeutics to halt disease progression as well as genetic biomarkers for early preclinical diagnosis.

Identification of functional enhancer variants associated with type I diabetes in CD4+ T cells

Type I diabetes is an autoimmune disease mediated by T-cell destruction of β cells in pancreatic islets. Currently, there is no known cure, and treatment consists of daily insulin injections. Genome-wide association studies and twin studies have indicated a strong genetic heritability for type I diabetes and implicated several genes. As most strongly associated variants are noncoding, there is still a lack of identification of functional and, therefore, likely causal variants. Given that many of these genetic variants reside in enhancer elements, we have tested 121 CD4+ T-cell enhancer variants associated with T1D. We found four to be functional through massively parallel reporter assays. Three of the enhancer variants weaken activity, while the fourth strengthens activity. We link these to their cognate genes using 3D genome architecture or eQTL data and validate them using CRISPR editing. Validated target genes include CLEC16A and SOCS1. While these genes have been previously implicated in type 1 diabetes and other autoimmune diseases, we show that enhancers controlling their expression harbor functional variants. These variants, therefore, may act as causal type 1 diabetic variants.

Integrative multi-omics analyses to identify the genetic and functional mechanisms underlying ovarian cancer risk regions

To identify credible causal risk variants (CCVs) associated with different histotypes of epithelial ovarian cancer (EOC), we performed genome-wide association analysis for 470,825 genotyped and 10,163,797 imputed SNPs in 25,981 EOC cases and 105,724 controls of European origin. We identified five histotype-specific EOC risk regions (p value <5 × 10-8) and confirmed previously reported associations for 27 risk regions. Conditional analyses identified an additional 11 signals independent of the primary signal at six risk regions (p value <10-5). Fine mapping identified 4,008 CCVs in these regions, of which 1,452 CCVs were located in ovarian cancer-related chromatin marks with significant enrichment in active enhancers, active promoters, and active regions for CCVs from each EOC histotype. Transcriptome-wide association and colocalization analyses across histotypes using tissue-specific and cross-tissue datasets identified 86 candidate susceptibility genes in known EOC risk regions and 32 genes in 23 additional genomic regions that may represent novel EOC risk loci (false discovery rate <0.05). Finally, by integrating genome-wide HiChIP interactome analysis with transcriptome-wide association study (TWAS), variant effect predictor, transcription factor ChIP-seq, and motifbreakR data, we identified candidate gene-CCV interactions at each locus. This included risk loci where TWAS identified one or more candidate susceptibility genes (e.g., HOXD-AS2, HOXD8, and HOXD3 at 2q31) and other loci where no candidate gene was identified (e.g., MYC and PVT1 at 8q24) by TWAS. In summary, this study describes a functional framework and provides a greater understanding of the biological significance of risk alleles and candidate gene targets at EOC susceptibility loci identified by a genome-wide association study.

An endothelial regulatory module links blood pressure regulation with elite athletic performance

The control of transcription is crucial for homeostasis in mammals. A previous selective sweep analysis of horse racing performance revealed a 19.6 kb candidate regulatory region 50 kb downstream of the Endothelin3 (EDN3) gene. Here, the region was narrowed to a 5.5 kb span of 14 SNVs, with elite and sub-elite haplotypes analyzed for association to racing performance, blood pressure and plasma levels of EDN3 in Coldblooded trotters and Standardbreds. Comparative analysis of human HiCap data identified the span as an enhancer cluster active in endothelial cells, interacting with genes relevant to blood pressure regulation. Coldblooded trotters with the sub-elite haplotype had significantly higher blood pressure compared to horses with the elite performing haplotype during exercise. Alleles within the elite haplotype were part of the standing variation in pre-domestication horses, and have risen in frequency during the era of breed development and selection. These results advance our understanding of the molecular genetics of athletic performance and vascular traits in both horses and humans.

Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro

BACKGROUND

CALCRL (calcitonin receptor-like) protein is an important mediator of the endothelial fluid shear stress response, which is associated with the genetic risk of coronary artery disease. In this study, we functionally characterized the noncoding regulatory elements carrying coronary artery disease that risks single-nucleotide polymorphisms and studied their role in the regulation of CALCRL expression in endothelial cells.

METHODS

To functionally characterize the coronary artery disease single-nucleotide polymorphisms harbored around the gene CALCRL, we applied an integrative approach encompassing statistical, transcriptional (RNA-seq), and epigenetic (ATAC-seq [transposase-accessible chromatin with sequencing], chromatin immunoprecipitation assay-quantitative polymerase chain reaction, and electromobility shift assay) analyses, alongside luciferase reporter assays, and targeted gene and enhancer perturbations (siRNA and clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9) in human aortic endothelial cells.

RESULTS

We demonstrate that the regulatory element harboring rs880890 exhibits high enhancer activity and shows significant allelic bias. The A allele was favored over the G allele, particularly under shear stress conditions, mediated through alterations in the HSF1 (heat shock factor 1) motif and binding. CRISPR deletion of rs880890 enhancer resulted in downregulation of CALCRL expression, whereas HSF1 knockdown resulted in a significant decrease in rs880890-enhancer activity and CALCRL expression. A significant decrease in HSF1 binding to the enhancer region in endothelial cells was observed under disturbed flow compared with unidirectional flow. CALCRL knockdown and variant perturbation experiments indicated the role of CALCRL in mediating eNOS (endothelial nitric oxide synthase), APLN (apelin), angiopoietin, prostaglandins, and EDN1 (endothelin-1) signaling pathways leading to a decrease in cell proliferation, tube formation, and NO production.

CONCLUSIONS

Overall, our results demonstrate the existence of an endothelial-specific HSF (heat shock factor)-regulated transcriptional enhancer that mediates CALCRL expression. A better understanding of CALCRL gene regulation and the role of single-nucleotide polymorphisms in the modulation of CALCRL expression could provide important steps toward understanding the genetic regulation of shear stress signaling responses.

Massively parallel characterization of regulatory elements in the developing human cortex

Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

Deconvolution of polygenic risk score in single cells unravels cellular and molecular heterogeneity of complex human diseases

Polygenic risk scores (PRSs) are commonly used for predicting an individual's genetic risk of complex diseases. Yet, their implication for disease pathogenesis remains largely limited. Here, we introduce scPRS, a geometric deep learning model that constructs single-cell-resolved PRS leveraging reference single-cell chromatin accessibility profiling data to enhance biological discovery as well as disease prediction. Real-world applications across multiple complex diseases, including type 2 diabetes (T2D), hypertrophic cardiomyopathy (HCM), and Alzheimer's disease (AD), showcase the superior prediction power of scPRS compared to traditional PRS methods. Importantly, scPRS not only predicts disease risk but also uncovers disease-relevant cells, such as hormone-high alpha and beta cells for T2D, cardiomyocytes and pericytes for HCM, and astrocytes, microglia and oligodendrocyte progenitor cells for AD. Facilitated by a layered multi-omic analysis, scPRS further identifies cell-type-specific genetic underpinnings, linking disease-associated genetic variants to gene regulation within corresponding cell types. We substantiate the disease relevance of scPRS-prioritized HCM genes and demonstrate that the suppression of these genes in HCM cardiomyocytes is rescued by Mavacamten treatment. Additionally, we establish a novel microglia-specific regulatory relationship between the AD risk variant rs7922621 and its target genes ANXA11 and TSPAN14. We further illustrate the detrimental effects of suppressing these two genes on microglia phagocytosis. Our work provides a multi-tasking, interpretable framework for precise disease prediction and systematic investigation of the genetic, cellular, and molecular basis of complex diseases, laying the methodological foundation for single-cell genetics.

Variant-to-function analysis of the childhood obesity chr12q13 locus implicates rs7132908 as a causal variant within the 3' UTR of FAIM2

The ch12q13 locus is among the most significant childhood obesity loci identified in genome-wide association studies. This locus resides in a non-coding region within FAIM2; thus, the underlying causal variant(s) presumably influence disease susceptibility via cis-regulation. We implicated rs7132908 as a putative causal variant by leveraging our in-house 3D genomic data and public domain datasets. Using a luciferase reporter assay, we observed allele-specific cis-regulatory activity of the immediate region harboring rs7132908. We generated isogenic human embryonic stem cell lines homozygous for either rs7132908 allele to assess changes in gene expression and chromatin accessibility throughout a differentiation to hypothalamic neurons, a key cell type known to regulate feeding behavior. The rs7132908 obesity risk allele influenced expression of FAIM2 and other genes and decreased the proportion of neurons produced by differentiation. We have functionally validated rs7132908 as a causal obesity variant that temporally regulates nearby effector genes and influences neurodevelopment and survival.

NetREm: Network Regression Embeddings reveal cell-type transcription factor coordination for gene regulation

Transcription factor (TF) coordination plays a key role in target gene (TG) regulation via protein-protein interactions (PPIs) and DNA co-binding to regulatory elements. Single-cell technologies facilitate gene expression measurement for individual cells and cell-type identification, yet the connection between TF coordination and TG regulation of various cell types remains unclear. To address this, we have developed a novel computational approach, Network Regression Embeddings (NetREm), to reveal cell-type TF-TF coordination activities for TG regulation. NetREm leverages network-constrained regularization using prior knowledge of direct and/or indirect PPIs among TFs to analyze single-cell gene expression data. We test NetREm by simulation data and benchmark its performance in 4 real-world applications that have gold standard TF-TG networks available: mouse (mESCs) and simulated human (hESCs) embryonic stem (ESCs), human hematopoietic stem (HSCs), and mouse dendritic (mDCs) cells. Further, we use NetREm to prioritize valid novel TF-TF coordination links in human Peripheral Blood Mononuclear cell (PBMC) sub-types. We apply NetREm to analyze various cell types in both central (CNS) and peripheral (PNS) nerve system (NS) (e.g. neuronal, glial, Schwann cells (SCs)) as well as in Alzheimers disease (AD). Our findings uncover cell-type coordinating TFs and identify new TF-TG candidate links. We validate our top predictions using Cut&Run and knockout loss-of-function expression data in rat/mouse models and compare results with additional functional genomic data, including expression quantitative trait loci (eQTL) and Genome-Wide Association Studies (GWAS) to link genetic variants (single nucleotide polymorphisms (SNPs)) to TF coordination.

Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions

Here, in a multi-ancestry genome-wide association study meta-analysis of kidney cancer (29,020 cases and 835,670 controls), we identified 63 susceptibility regions (50 novel) containing 108 independent risk loci. In analyses stratified by subtype, 52 regions (78 loci) were associated with clear cell renal cell carcinoma (RCC) and 6 regions (7 loci) with papillary RCC. Notably, we report a variant common in African ancestry individuals ( rs7629500 ) in the 3' untranslated region of VHL, nearly tripling clear cell RCC risk (odds ratio 2.72, 95% confidence interval 2.23-3.30). In cis-expression quantitative trait locus analyses, 48 variants from 34 regions point toward 83 candidate genes. Enrichment of hypoxia-inducible factor-binding sites underscores the importance of hypoxia-related mechanisms in kidney cancer. Our results advance understanding of the genetic architecture of kidney cancer, provide clues for functional investigation and enable generation of a validated polygenic risk score with an estimated area under the curve of 0.65 (0.74 including risk factors) among European ancestry individuals.

Characterization of cell cycle, inflammation, and oxidative stress signaling role in non-communicable diseases: Insights into genetic variants, microRNAs and pathways

Non-Communicable Diseases (NCDs) significantly impact global health, contributing to over 70% of premature deaths, as reported by the World Health Organization (WHO). These diseases have complex and multifactorial origins, involving genetic, epigenetic, environmental and lifestyle factors. While Genome-Wide Association Study (GWAS) is widely recognized as a valuable tool for identifying variants associated with complex phenotypes; the multifactorial nature of NCDs necessitates a more comprehensive exploration, encompassing not only the genetic but also the epigenetic aspect. For this purpose, we employed a bioinformatics-multiomics approach to examine the genetic and epigenetic characteristics of NCDs (i.e. colorectal cancer, coronary atherosclerosis, squamous cell lung cancer, psoriasis, type 2 diabetes, and multiple sclerosis), aiming to identify novel biomarkers for diagnosis and prognosis. Leveraging GWAS summary statistics, we pinpointed Single Nucleotide Polymorphisms (SNPs) independently associated with each NCD. Subsequently, we identified genes linked to cell cycle, inflammation and oxidative stress mechanisms, revealing shared genes across multiple diseases, suggesting common functional pathways. From an epigenetic perspective, we identified microRNAs (miRNAs) with regulatory functions targeting these genes of interest. Our findings underscore critical genetic pathways implicated in these diseases. In colorectal cancer, the dysregulation of the "Cytokine Signaling in Immune System" pathway, involving LAMA5 and SMAD7, regulated by Hsa-miR-21-5p, Hsa-miR-103a-3p, and Hsa-miR-195-5p, emerged as pivotal. In coronary atherosclerosis, the pathway associated with "binding of TCF/LEF:CTNNB1 to target gene promoters" displayed noteworthy implications, with the MYC factor controlled by Hsa-miR-16-5p as a potential regulatory factor. Squamous cell lung carcinoma analysis revealed significant pathways such as "PTK6 promotes HIF1A stabilization," regulated by Hsa-let-7b-5p. In psoriasis, the "Endosomal/Vacuolar pathway," involving HLA-C and Hsa-miR-148a-3p and Hsa-miR-148b-3p, was identified as crucial. Type 2 Diabetes implicated the "Regulation of TP53 Expression" pathway, controlled by Hsa-miR-106a-5p and Hsa-miR-106b-5p. In conclusion, our study elucidates the genetic framework and molecular mechanisms underlying NCDs, offering crucial insights into potential genetic/epigenetic biomarkers for diagnosis and prognosis. The specificity of pathways and related miRNAs in different pathologies highlights promising candidates for further clinical validation, with the potential to advance personalized treatments and alleviate the global burden of NCDs.

Genetic variation is a key determinant of chromatin accessibility and drives differences in the regulatory landscape of C57BL/6J and 129S1/SvImJ mice

Most common genetic variants associated with disease are located in non-coding regions of the genome. One mechanism by which they function is through altering transcription factor (TF) binding. In this study, we explore how genetic variation is connected to differences in the regulatory landscape of livers from C57BL/6J and 129S1/SvImJ mice fed either chow or a high-fat diet. To identify sites where regulatory variation affects TF binding and nearby gene expression, we employed an integrative analysis of H3K27ac ChIP-seq (active enhancers), ATAC-seq (chromatin accessibility) and RNA-seq (gene expression). We show that, across all these assays, the genetically driven (i.e. strain-specific) differences in the regulatory landscape are more pronounced than those modified by diet. Most notably, our analysis revealed that differentially accessible regions (DARs, N = 29635, FDR < 0.01 and fold change > 50%) are almost always strain-specific and enriched with genetic variation. Moreover, proximal DARs are highly correlated with differentially expressed genes. We also show that TF binding is affected by genetic variation, which we validate experimentally using ChIP-seq for TCF7L2 and CTCF. This study provides detailed insights into how non-coding genetic variation alters the gene regulatory landscape, and demonstrates how this can be used to study the regulatory variation influencing TF binding.

Overlapping binding sites underlie TF genomic occupancy

Sequence-specific DNA binding by transcription factors (TFs) is a crucial step in gene regulation. However, current high-throughput in vitro approaches cannot reliably detect lower affinity TF-DNA interactions, which play key roles in gene regulation. Here, we developed PADIT-seq ( p rotein a ffinity to D NA by in vitro transcription and RNA seq uencing) to assay TF binding preferences to all 10-bp DNA sequences at far greater sensitivity than prior approaches. The expanded catalogs of low affinity DNA binding sites for the human TFs HOXD13 and EGR1 revealed that nucleotides flanking high affinity DNA binding sites create overlapping lower affinity sites that together modulate TF genomic occupancy in vivo . Formation of such extended recognition sequences stems from an inherent property of TF binding sites to interweave each other and expands the genomic sequence space for identifying noncoding variants that directly alter TF binding.

One-Sentence Summary

Overlapping DNA binding sites underlie TF genomic occupancy through their inherent propensity to interweave each other.

Enhancer mutations modulate the severity of chemotherapy-induced myelosuppression

Non-small cell lung cancer is often diagnosed at advanced stages, and many patients are still treated with classical chemotherapy. The unselective nature of chemotherapy often results in severe myelosuppression. Previous studies showed that protein-coding mutations could not fully explain the predisposition to myelosuppression. Here, we investigate the possible role of enhancer mutations in myelosuppression susceptibility. We produced transcriptome and promoter-interaction maps (using HiCap) of three blood stem-like cell lines treated with carboplatin or gemcitabine. Taking advantage of publicly available enhancer datasets, we validated HiCap results in silico and in living cells using epigenetic CRISPR technology. We also developed a network approach for interactome analysis and detection of differentially interacting genes. Differential interaction analysis provided additional information on relevant genes and pathways for myelosuppression compared with differential gene expression analysis at the bulk level. Moreover, we showed that enhancers of differentially interacting genes are highly enriched for variants associated with differing levels of myelosuppression. Altogether, our work represents a prominent example of integrative transcriptome and gene regulatory datasets analysis for the functional annotation of noncoding mutations.

Identification of somatic mutation-driven enhancers and their clinical utility in breast cancer

Somatic mutations contribute to cancer development by altering the activity of enhancers. In the study, a total of 135 mutation-driven enhancers, which displayed significant chromatin accessibility changes, were identified as candidate risk factors for breast cancer (BRCA). Furthermore, we identified four mutation-driven enhancers as independent prognostic factors for BRCA subtypes. In Her2 subtype, enhancer G > C mutation was associated with poorer prognosis through influencing its potential target genes FBXW9, TRIR, and WDR83. We identified aminoglutethimide and quinpirole as candidate drugs targeting the mutated enhancer. In normal subtype, enhancer G > A mutation was associated with poorer prognosis through influencing its target genes ALOX15B, LINC00324, and MPDU1. We identified eight candidate drugs such as erastin, colforsin, and STOCK1N-35874 targeting the mutated enhancer. Our findings suggest that somatic mutations contribute to breast cancer subtype progression by altering enhancer activity, which could be potential candidates for cancer therapy.

Parkinson's disease risk enhancers in microglia

Genome-wide association studies have identified thousands of single nucleotide polymorphisms that associate with increased risk for Parkinson's disease (PD), but the functions of most of them are unknown. Using assay for transposase-accessible chromatin (ATAC) and H3K27ac chromatin immunoprecipitation (ChIP) sequencing data, we identified 73 regulatory elements in microglia that overlap PD risk SNPs. To determine the target genes of a "risk enhancer" within intron two of SNCA, we used CRISPR-Cas9 to delete the open chromatin region where two PD risk SNPs reside. The loss of the enhancer led to reduced expression of multiple genes including SNCA and the adjacent gene MMRN1. It also led to expression changes of genes involved in glucose metabolism, a process that is known to be altered in PD patients. Our work expands the role of SNCA in PD and provides a connection between PD-associated genetic variants and underlying biology that points to a risk mechanism in microglia.

Integrative functional genomic analyses identify genetic variants influencing skin pigmentation in Africans

Skin color is highly variable in Africans, yet little is known about the underlying molecular mechanism. Here we applied massively parallel reporter assays to screen 1,157 candidate variants influencing skin pigmentation in Africans and identified 165 single-nucleotide polymorphisms showing differential regulatory activities between alleles. We combine Hi-C, genome editing and melanin assays to identify regulatory elements for MFSD12, HMG20B, OCA2, MITF, LEF1, TRPS1, BLOC1S6 and CYB561A3 that impact melanin levels in vitro and modulate human skin color. We found that independent mutations in an OCA2 enhancer contribute to the evolution of human skin color diversity and detect signals of local adaptation at enhancers of MITF, LEF1 and TRPS1, which may contribute to the light skin color of Khoesan-speaking populations from Southern Africa. Additionally, we identified CYB561A3 as a novel pigmentation regulator that impacts genes involved in oxidative phosphorylation and melanogenesis. These results provide insights into the mechanisms underlying human skin color diversity and adaptive evolution.

Comparative analysis of models in predicting the effects of SNPs on TF-DNA binding using large-scale in vitro and in vivo data

Non-coding variants associated with complex traits can alter the motifs of transcription factor (TF)-deoxyribonucleic acid binding. Although many computational models have been developed to predict the effects of non-coding variants on TF binding, their predictive power lacks systematic evaluation. Here we have evaluated 14 different models built on position weight matrices (PWMs), support vector machines, ordinary least squares and deep neural networks (DNNs), using large-scale in vitro (i.e. SNP-SELEX) and in vivo (i.e. allele-specific binding, ASB) TF binding data. Our results show that the accuracy of each model in predicting SNP effects in vitro significantly exceeds that achieved in vivo. For in vitro variant impact prediction, kmer/gkm-based machine learning methods (deltaSVM_HT-SELEX, QBiC-Pred) trained on in vitro datasets exhibit the best performance. For in vivo ASB variant prediction, DNN-based multitask models (DeepSEA, Sei, Enformer) trained on the ChIP-seq dataset exhibit relatively superior performance. Among the PWM-based methods, tRap demonstrates better performance in both in vitro and in vivo evaluations. In addition, we find that TF classes such as basic leucine zipper factors could be predicted more accurately, whereas those such as C2H2 zinc finger factors are predicted less accurately, aligning with the evolutionary conservation of these TF classes. We also underscore the significance of non-sequence factors such as cis-regulatory element type, TF expression, interactions and post-translational modifications in influencing the in vivo predictive performance of TFs. Our research provides valuable insights into selecting prioritization methods for non-coding variants and further optimizing such models.