255 results on '"Chiou, Joshua"'
Search Results
2. The GPCR–Gαs–PKA signaling axis promotes T cell dysfunction and cancer immunotherapy failure
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Wu, Victoria H, Yung, Bryan S, Faraji, Farhoud, Saddawi-Konefka, Robert, Wang, Zhiyong, Wenzel, Alexander T, Song, Miranda J, Pagadala, Meghana S, Clubb, Lauren M, Chiou, Joshua, Sinha, Sanju, Matic, Marin, Raimondi, Francesco, Hoang, Thomas S, Berdeaux, Rebecca, Vignali, Dario AA, Iglesias-Bartolome, Ramiro, Carter, Hannah, Ruppin, Eytan, Mesirov, Jill P, and Gutkind, J Silvio
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Biomedical and Clinical Sciences ,Oncology and Carcinogenesis ,Immunology ,Cancer ,Vaccine Related ,Immunotherapy ,Biotechnology ,Immunization ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Mice ,Animals ,CD8-Positive T-Lymphocytes ,Neoplasms ,Signal Transduction ,Mice ,Transgenic ,Tumor Microenvironment ,Biochemistry and cell biology - Abstract
Immune checkpoint blockade (ICB) targeting PD-1 and CTLA-4 has revolutionized cancer treatment. However, many cancers do not respond to ICB, prompting the search for additional strategies to achieve durable responses. G-protein-coupled receptors (GPCRs) are the most intensively studied drug targets but are underexplored in immuno-oncology. Here, we cross-integrated large singe-cell RNA-sequencing datasets from CD8+ T cells covering 19 distinct cancer types and identified an enrichment of Gαs-coupled GPCRs on exhausted CD8+ T cells. These include EP2, EP4, A2AR, β1AR and β2AR, all of which promote T cell dysfunction. We also developed transgenic mice expressing a chemogenetic CD8-restricted Gαs-DREADD to activate CD8-restricted Gαs signaling and show that a Gαs-PKA signaling axis promotes CD8+ T cell dysfunction and immunotherapy failure. These data indicate that Gαs-GPCRs are druggable immune checkpoints that might be targeted to enhance the response to ICB immunotherapies.
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- 2023
3. Integrating genetics with single-cell multiomic measurements across disease states identifies mechanisms of beta cell dysfunction in type 2 diabetes
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Wang, Gaowei, Chiou, Joshua, Zeng, Chun, Miller, Michael, Matta, Ileana, Han, Jee Yun, Kadakia, Nikita, Okino, Mei-Lin, Beebe, Elisha, Mallick, Medhavi, Camunas-Soler, Joan, dos Santos, Theodore, Dai, Xiao-Qing, Ellis, Cara, Hang, Yan, Kim, Seung K, MacDonald, Patrick E, Kandeel, Fouad R, Preissl, Sebastian, Gaulton, Kyle J, and Sander, Maike
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Biochemistry and Cell Biology ,Genetics ,Biological Sciences ,Obesity ,Machine Learning and Artificial Intelligence ,Human Genome ,Diabetes ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Metabolic and endocrine ,Humans ,Diabetes Mellitus ,Type 2 ,Multiomics ,Insulin-Secreting Cells ,Gene Expression Regulation ,Chromatin ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
Dysfunctional pancreatic islet beta cells are a hallmark of type 2 diabetes (T2D), but a comprehensive understanding of the underlying mechanisms, including gene dysregulation, is lacking. Here we integrate information from measurements of chromatin accessibility, gene expression and function in single beta cells with genetic association data to nominate disease-causal gene regulatory changes in T2D. Using machine learning on chromatin accessibility data from 34 nondiabetic, pre-T2D and T2D donors, we identify two transcriptionally and functionally distinct beta cell subtypes that undergo an abundance shift during T2D progression. Subtype-defining accessible chromatin is enriched for T2D risk variants, suggesting a causal contribution of subtype identity to T2D. Both beta cell subtypes exhibit activation of a stress-response transcriptional program and functional impairment in T2D, which is probably induced by the T2D-associated metabolic environment. Our findings demonstrate the power of multimodal single-cell measurements combined with machine learning for characterizing mechanisms of complex diseases.
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- 2023
4. Nutrient regulation of the islet epigenome controls adaptive insulin secretion
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Wortham, Matthew, Liu, Fenfen, Harrington, Austin R, Fleischman, Johanna Y, Wallace, Martina, Mulas, Francesca, Mallick, Medhavi, Vinckier, Nicholas K, Cross, Benjamin R, Chiou, Joshua, Patel, Nisha A, Sui, Yinghui, McGrail, Carolyn, Jun, Yesl, Wang, Gaowei, Jhala, Ulupi S, Schüle, Roland, Shirihai, Orian S, Huising, Mark O, Gaulton, Kyle J, Metallo, Christian M, and Sander, Maike
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Biochemistry and Cell Biology ,Biological Sciences ,Diabetes ,Autoimmune Disease ,Genetics ,Nutrition ,1.1 Normal biological development and functioning ,Generic health relevance ,Metabolic and endocrine ,Mice ,Humans ,Animals ,Insulin Secretion ,Diabetes Mellitus ,Type 2 ,Histones ,Epigenome ,Islets of Langerhans ,Insulin ,Insulin-Secreting Cells ,Glucose ,Endocrinology ,Epigenetics ,Islet cells ,Metabolism ,Medical and Health Sciences ,Immunology ,Biological sciences ,Biomedical and clinical sciences ,Health sciences - Abstract
Adaptation of the islet β cell insulin-secretory response to changing insulin demand is critical for blood glucose homeostasis, yet the mechanisms underlying this adaptation are unknown. Here, we have shown that nutrient-stimulated histone acetylation plays a key role in adapting insulin secretion through regulation of genes involved in β cell nutrient sensing and metabolism. Nutrient regulation of the epigenome occurred at sites occupied by the chromatin-modifying enzyme lysine-specific demethylase 1 (Lsd1) in islets. β Cell-specific deletion of Lsd1 led to insulin hypersecretion, aberrant expression of nutrient-response genes, and histone hyperacetylation. Islets from mice adapted to chronically increased insulin demand exhibited shared epigenetic and transcriptional changes. Moreover, we found that genetic variants associated with type 2 diabetes were enriched at LSD1-bound sites in human islets, suggesting that interpretation of nutrient signals is genetically determined and clinically relevant. Overall, these studies revealed that adaptive insulin secretion involves Lsd1-mediated coupling of nutrient state to regulation of the islet epigenome.
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- 2023
5. High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease.
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Kim, Hyunkyung, Westerman, Kenneth, Smith, Kirk, Chiou, Joshua, Cole, Joanne, Majarian, Timothy, von Grotthuss, Marcin, Kwak, Soo, Kim, Jaegil, Mercader, Josep, Florez, Jose, Manning, Alisa, Udler, Miriam, and Gaulton, Kyle
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Bayesian non-negative matrix factorisation ,Clustering ,Disease pathways ,GWAS ,Genetics ,NMF ,Polygenic risk scores ,Subtypes ,Type 2 diabetes ,bNMF ,Humans ,Diabetes Mellitus ,Type 2 ,Genome-Wide Association Study ,Genetic Predisposition to Disease ,Bayes Theorem ,Cluster Analysis ,Polymorphism ,Single Nucleotide - Abstract
AIMS/HYPOTHESIS: Type 2 diabetes is highly polygenic and influenced by multiple biological pathways. Rapid expansion in the number of type 2 diabetes loci can be leveraged to identify such pathways. METHODS: We developed a high-throughput pipeline to enable clustering of type 2 diabetes loci based on variant-trait associations. Our pipeline extracted summary statistics from genome-wide association studies (GWAS) for type 2 diabetes and related traits to generate a matrix of 323 variants × 64 trait associations and applied Bayesian non-negative matrix factorisation (bNMF) to identify genetic components of type 2 diabetes. Epigenomic enrichment analysis was performed in 28 cell types and single pancreatic cells. We generated cluster-specific polygenic scores and performed regression analysis in an independent cohort (N=25,419) to assess for clinical relevance. RESULTS: We identified ten clusters of genetic loci, recapturing the five from our prior analysis as well as novel clusters related to beta cell dysfunction, pronounced insulin secretion, and levels of alkaline phosphatase, lipoprotein A and sex hormone-binding globulin. Four clusters related to mechanisms of insulin deficiency, five to insulin resistance and one had an unclear mechanism. The clusters displayed tissue-specific epigenomic enrichment, notably with the two beta cell clusters differentially enriched in functional and stressed pancreatic beta cell states. Additionally, cluster-specific polygenic scores were differentially associated with patient clinical characteristics and outcomes. The pipeline was applied to coronary artery disease and chronic kidney disease, identifying multiple overlapping clusters with type 2 diabetes. CONCLUSIONS/INTERPRETATION: Our approach stratifies type 2 diabetes loci into physiologically interpretable genetic clusters associated with distinct tissues and clinical outcomes. The pipeline allows for efficient updating as additional GWAS become available and can be readily applied to other conditions, facilitating clinical translation of GWAS findings. Software to perform this clustering pipeline is freely available.
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- 2023
6. Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex immune trait variants using single nucleus ATAC-seq in peripheral blood
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Benaglio, Paola, Newsome, Jacklyn, Han, Jee Yun, Chiou, Joshua, Aylward, Anthony, Corban, Sierra, Miller, Michael, Okino, Mei-Lin, Kaur, Jaspreet, Preissl, Sebastian, Gorkin, David U, and Gaulton, Kyle J
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Biological Sciences ,Genetics ,Human Genome ,Biotechnology ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Metabolic and endocrine ,Inflammatory and immune system ,Humans ,Chromatin ,Chromatin Immunoprecipitation Sequencing ,Multifactorial Inheritance ,Leukocytes ,Mononuclear ,Quantitative Trait Loci ,Developmental Biology - Abstract
Gene regulation is highly cell type-specific and understanding the function of non-coding genetic variants associated with complex traits requires molecular phenotyping at cell type resolution. In this study we performed single nucleus ATAC-seq (snATAC-seq) and genotyping in peripheral blood mononuclear cells from 13 individuals. Clustering chromatin accessibility profiles of 96,002 total nuclei identified 17 immune cell types and sub-types. We mapped chromatin accessibility QTLs (caQTLs) in each immune cell type and sub-type using individuals of European ancestry which identified 6,901 caQTLs at FDR < .10 and 4,220 caQTLs at FDR < .05, including those obscured from assays of bulk tissue such as with divergent effects on different cell types. For 3,941 caQTLs we further annotated putative target genes of variant activity using single cell co-accessibility, and caQTL variants were significantly correlated with the accessibility level of linked gene promoters. We fine-mapped loci associated with 16 complex immune traits and identified immune cell caQTLs at 622 candidate causal variants, including those with cell type-specific effects. At the 6q15 locus associated with type 1 diabetes, in line with previous reports, variant rs72928038 was a naïve CD4+ T cell caQTL linked to BACH2 and we validated the allelic effects of this variant on regulatory activity in Jurkat T cells. These results highlight the utility of snATAC-seq for mapping genetic effects on accessible chromatin in specific cell types.
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- 2023
7. Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines
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Benaglio, Paola, Zhu, Han, Okino, Mei-Lin, Yan, Jian, Elgamal, Ruth, Nariai, Naoki, Beebe, Elisha, Korgaonkar, Katha, Qiu, Yunjiang, Donovan, Margaret KR, Chiou, Joshua, Wang, Gaowei, Newsome, Jacklyn, Kaur, Jaspreet, Miller, Michael, Preissl, Sebastian, Corban, Sierra, Aylward, Anthony, Taipale, Jussi, Ren, Bing, Frazer, Kelly A, Sander, Maike, and Gaulton, Kyle J
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Biochemistry and Cell Biology ,Genetics ,Biological Sciences ,Diabetes ,Human Genome ,Biotechnology ,Pediatric ,Autoimmune Disease ,Prevention ,2.1 Biological and endogenous factors ,Inflammatory and immune system ,Metabolic and endocrine ,3D chromatin interactions ,CRISPR screen ,accessible chromatin ,beta cell ,functional genomics ,gene expression ,high-throughput reporter assay ,human genetics ,proinflammatory cytokines ,type 1 diabetes - Abstract
We combined functional genomics and human genetics to investigate processes that affect type 1 diabetes (T1D) risk by mediating beta cell survival in response to proinflammatory cytokines. We mapped 38,931 cytokine-responsive candidate cis-regulatory elements (cCREs) in beta cells using ATAC-seq and snATAC-seq and linked them to target genes using co-accessibility and HiChIP. Using a genome-wide CRISPR screen in EndoC-βH1 cells, we identified 867 genes affecting cytokine-induced survival, and genes promoting survival and up-regulated in cytokines were enriched at T1D risk loci. Using SNP-SELEX, we identified 2,229 variants in cytokine-responsive cCREs altering transcription factor (TF) binding, and variants altering binding of TFs regulating stress, inflammation, and apoptosis were enriched for T1D risk. At the 16p13 locus, a fine-mapped T1D variant altering TF binding in a cytokine-induced cCRE interacted with SOCS1, which promoted survival in cytokine exposure. Our findings reveal processes and genes acting in beta cells during inflammation that modulate T1D risk.
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- 2022
8. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
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Mahajan, Anubha, Spracklen, Cassandra N, Zhang, Weihua, Ng, Maggie CY, Petty, Lauren E, Kitajima, Hidetoshi, Yu, Grace Z, Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M, Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R, Rayner, Nigel W, Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H, Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A, Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J, Yao, Jie, Bielak, Lawrence F, Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P, Kals, Mart, Grarup, Niels, Schmidt, Ellen M, Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor JY, Tam, Claudia HT, Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M, Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R, Chen, Guanjie, Jensen, Richard A, Tajuddin, Salman, Kabagambe, Edmond K, An, Ping, Xiang, Anny H, Choi, Hyeok Sun, Cade, Brian E, Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S, Adeyemo, Adebowale, Aguilar-Salinas, Carlos A, Akiyama, Masato, Anand, Sonia S, Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A, Brummett, Chad M, Buchanan, Thomas A, Canouil, Mickaël, Chan, Juliana CN, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, and Cushman, Mary
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Genetics ,Diabetes ,Human Genome ,Metabolic and endocrine ,Diabetes Mellitus ,Type 2 ,Ethnicity ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Polymorphism ,Single Nucleotide ,Risk Factors ,FinnGen ,eMERGE Consortium ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P 50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
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- 2022
9. Plasma proteomic associations with genetics and health in the UK Biobank
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Sun, Benjamin B., Chiou, Joshua, Traylor, Matthew, Benner, Christian, Hsu, Yi-Hsiang, Richardson, Tom G., Surendran, Praveen, Mahajan, Anubha, Robins, Chloe, Vasquez-Grinnell, Steven G., Hou, Liping, Kvikstad, Erika M., Burren, Oliver S., Davitte, Jonathan, Ferber, Kyle L., Gillies, Christopher E., Hedman, Åsa K., Hu, Sile, Lin, Tinchi, Mikkilineni, Rajesh, Pendergrass, Rion K., Pickering, Corran, Prins, Bram, Baird, Denis, Chen, Chia-Yen, Ward, Lucas D., Deaton, Aimee M., Welsh, Samantha, Willis, Carissa M., Lehner, Nick, Arnold, Matthias, Wörheide, Maria A., Suhre, Karsten, Kastenmüller, Gabi, Sethi, Anurag, Cule, Madeleine, Raj, Anil, Burkitt-Gray, Lucy, Melamud, Eugene, Black, Mary Helen, Fauman, Eric B., Howson, Joanna M. M., Kang, Hyun Min, McCarthy, Mark I., Nioi, Paul, Petrovski, Slavé, Scott, Robert A., Smith, Erin N., Szalma, Sándor, Waterworth, Dawn M., Mitnaul, Lyndon J., Szustakowski, Joseph D., Gibson, Bradford W., Miller, Melissa R., and Whelan, Christopher D.
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- 2023
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10. Mutations and variants of ONECUT1 in diabetes
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Philippi, Anne, Heller, Sandra, Costa, Ivan G, Senée, Valérie, Breunig, Markus, Li, Zhijian, Kwon, Gino, Russell, Ronan, Illing, Anett, Lin, Qiong, Hohwieler, Meike, Degavre, Anne, Zalloua, Pierre, Liebau, Stefan, Schuster, Michael, Krumm, Johannes, Zhang, Xi, Geusz, Ryan, Benthuysen, Jacqueline R, Wang, Allen, Chiou, Joshua, Gaulton, Kyle, Neubauer, Heike, Simon, Eric, Klein, Thomas, Wagner, Martin, Nair, Gopika, Besse, Céline, Dandine-Roulland, Claire, Olaso, Robert, Deleuze, Jean-François, Kuster, Bernhard, Hebrok, Matthias, Seufferlein, Thomas, Sander, Maike, Boehm, Bernhard O, Oswald, Franz, Nicolino, Marc, Julier, Cécile, and Kleger, Alexander
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Biomedical and Clinical Sciences ,Regenerative Medicine ,Stem Cell Research - Embryonic - Human ,Genetics ,Clinical Research ,Stem Cell Research - Induced Pluripotent Stem Cell - Human ,Pediatric ,Stem Cell Research - Induced Pluripotent Stem Cell ,Stem Cell Research ,Autoimmune Disease ,Diabetes ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Cell Differentiation ,Congenital Abnormalities ,Diabetes Mellitus ,Type 2 ,Fetal Growth Retardation ,Gallbladder ,Hepatocyte Nuclear Factor 6 ,Homeobox Protein Nkx-2.2 ,Homeodomain Proteins ,Humans ,Infant ,Infant ,Newborn ,Male ,Multifactorial Inheritance ,Organogenesis ,Pancreas ,Pancreatic Diseases ,Pluripotent Stem Cells ,Transcription ,Genetic ,Medical and Health Sciences ,Immunology ,Biomedical and clinical sciences ,Health sciences - Abstract
Genes involved in distinct diabetes types suggest shared disease mechanisms. Here we show that One Cut Homeobox 1 (ONECUT1) mutations cause monogenic recessive syndromic diabetes in two unrelated patients, characterized by intrauterine growth retardation, pancreas hypoplasia and gallbladder agenesis/hypoplasia, and early-onset diabetes in heterozygous relatives. Heterozygous carriers of rare coding variants of ONECUT1 define a distinctive subgroup of diabetic patients with early-onset, nonautoimmune diabetes, who respond well to diabetes treatment. In addition, common regulatory ONECUT1 variants are associated with multifactorial type 2 diabetes. Directed differentiation of human pluripotent stem cells revealed that loss of ONECUT1 impairs pancreatic progenitor formation and a subsequent endocrine program. Loss of ONECUT1 altered transcription factor binding and enhancer activity and NKX2.2/NKX6.1 expression in pancreatic progenitor cells. Collectively, we demonstrate that ONECUT1 controls a transcriptional and epigenetic machinery regulating endocrine development, involved in a spectrum of diabetes, encompassing monogenic (recessive and dominant) as well as multifactorial inheritance. Our findings highlight the broad contribution of ONECUT1 in diabetes pathogenesis, marking an important step toward precision diabetes medicine.
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- 2021
11. A single-cell atlas of chromatin accessibility in the human genome
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Zhang, Kai, Hocker, James D, Miller, Michael, Hou, Xiaomeng, Chiou, Joshua, Poirion, Olivier B, Qiu, Yunjiang, Li, Yang E, Gaulton, Kyle J, Wang, Allen, Preissl, Sebastian, and Ren, Bing
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Human Genome ,Stem Cell Research ,Stem Cell Research - Nonembryonic - Human ,Stem Cell Research - Embryonic - Human ,Genetics ,Underpinning research ,1.1 Normal biological development and functioning ,Generic health relevance ,Adult ,Chromatin ,Cluster Analysis ,Fetus ,Genetic Variation ,Genome ,Human ,Genome-Wide Association Study ,Humans ,Organ Specificity ,Phylogeny ,Regulatory Sequences ,Nucleic Acid ,Risk Factors ,Single-Cell Analysis ,GWAS ,chromatin accessibility ,cis regulatory elements ,enhancers ,epigenome ,noncoding variants ,single cell ATAC-seq ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
Current catalogs of regulatory sequences in the human genome are still incomplete and lack cell type resolution. To profile the activity of gene regulatory elements in diverse cell types and tissues in the human body, we applied single-cell chromatin accessibility assays to 30 adult human tissue types from multiple donors. We integrated these datasets with previous single-cell chromatin accessibility data from 15 fetal tissue types to reveal the status of open chromatin for ∼1.2 million candidate cis-regulatory elements (cCREs) in 222 distinct cell types comprised of >1.3 million nuclei. We used these chromatin accessibility maps to delineate cell-type-specificity of fetal and adult human cCREs and to systematically interpret the noncoding variants associated with complex human traits and diseases. This rich resource provides a foundation for the analysis of gene regulatory programs in human cell types across tissues, life stages, and organ systems.
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- 2021
12. An atlas of gene regulatory elements in adult mouse cerebrum
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Li, Yang Eric, Preissl, Sebastian, Hou, Xiaomeng, Zhang, Ziyang, Zhang, Kai, Qiu, Yunjiang, Poirion, Olivier B, Li, Bin, Chiou, Joshua, Liu, Hanqing, Pinto-Duarte, Antonio, Kubo, Naoki, Yang, Xiaoyu, Fang, Rongxin, Wang, Xinxin, Han, Jee Yun, Lucero, Jacinta, Yan, Yiming, Miller, Michael, Kuan, Samantha, Gorkin, David, Gaulton, Kyle J, Shen, Yin, Nunn, Michael, Mukamel, Eran A, Behrens, M Margarita, Ecker, Joseph R, and Ren, Bing
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Human Genome ,Genetics ,Biotechnology ,Brain Disorders ,Stem Cell Research - Nonembryonic - Non-Human ,Stem Cell Research ,Neurosciences ,Underpinning research ,1.1 Normal biological development and functioning ,Neurological ,Animals ,Atlases as Topic ,Cerebrum ,Chromatin ,Chromatin Assembly and Disassembly ,Gene Expression Regulation ,Genetic Predisposition to Disease ,Humans ,Male ,Mice ,Mice ,Inbred C57BL ,Nervous System Diseases ,Neuroglia ,Neurons ,Regulatory Sequences ,Nucleic Acid ,Sequence Analysis ,DNA ,Single-Cell Analysis ,General Science & Technology - Abstract
The mammalian cerebrum performs high-level sensory perception, motor control and cognitive functions through highly specialized cortical and subcortical structures1. Recent surveys of mouse and human brains with single-cell transcriptomics2-6 and high-throughput imaging technologies7,8 have uncovered hundreds of neural cell types distributed in different brain regions, but the transcriptional regulatory programs that are responsible for the unique identity and function of each cell type remain unknown. Here we probe the accessible chromatin in more than 800,000 individual nuclei from 45 regions that span the adult mouse isocortex, olfactory bulb, hippocampus and cerebral nuclei, and use the resulting data to map the state of 491,818 candidate cis-regulatory DNA elements in 160 distinct cell types. We find high specificity of spatial distribution for not only excitatory neurons, but also most classes of inhibitory neurons and a subset of glial cell types. We characterize the gene regulatory sequences associated with the regional specificity within these cell types. We further link a considerable fraction of the cis-regulatory elements to putative target genes expressed in diverse cerebral cell types and predict transcriptional regulators that are involved in a broad spectrum of molecular and cellular pathways in different neuronal and glial cell populations. Our results provide a foundation for comprehensive analysis of gene regulatory programs of the mammalian brain and assist in the interpretation of noncoding risk variants associated with various neurological diseases and traits in humans.
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- 2021
13. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics
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Chiou, Joshua, Geusz, Ryan J, Okino, Mei-Lin, Han, Jee Yun, Miller, Michael, Melton, Rebecca, Beebe, Elisha, Benaglio, Paola, Huang, Serina, Korgaonkar, Katha, Heller, Sandra, Kleger, Alexander, Preissl, Sebastian, Gorkin, David U, Sander, Maike, and Gaulton, Kyle J
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Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Epidemiology ,Health Sciences ,Prevention ,Pediatric ,Human Genome ,Autoimmune Disease ,Diabetes ,2.1 Biological and endogenous factors ,Generic health relevance ,Metabolic and endocrine ,Good Health and Well Being ,Chromatin ,Cystic Fibrosis Transmembrane Conductance Regulator ,Diabetes Mellitus ,Type 1 ,Epigenomics ,Female ,Gene Expression Regulation ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Immunity ,Male ,Pancreatic Ducts ,Single-Cell Analysis ,General Science & Technology - Abstract
Genetic risk variants that have been identified in genome-wide association studies of complex diseases are primarily non-coding1. Translating these risk variants into mechanistic insights requires detailed maps of gene regulation in disease-relevant cell types2. Here we combined two approaches: a genome-wide association study of type 1 diabetes (T1D) using 520,580 samples, and the identification of candidate cis-regulatory elements (cCREs) in pancreas and peripheral blood mononuclear cells using single-nucleus assay for transposase-accessible chromatin with sequencing (snATAC-seq) of 131,554 nuclei. Risk variants for T1D were enriched in cCREs that were active in T cells and other cell types, including acinar and ductal cells of the exocrine pancreas. Risk variants at multiple T1D signals overlapped with exocrine-specific cCREs that were linked to genes with exocrine-specific expression. At the CFTR locus, the T1D risk variant rs7795896 mapped to a ductal-specific cCRE that regulated CFTR; the risk allele reduced transcription factor binding, enhancer activity and CFTR expression in ductal cells. These findings support a role for the exocrine pancreas in the pathogenesis of T1D and highlight the power of large-scale genome-wide association studies and single-cell epigenomics for understanding the cellular origins of complex disease.
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- 2021
14. Cardiac cell type–specific gene regulatory programs and disease risk association
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Hocker, James D, Poirion, Olivier B, Zhu, Fugui, Buchanan, Justin, Zhang, Kai, Chiou, Joshua, Wang, Tsui-Min, Zhang, Qingquan, Hou, Xiaomeng, Li, Yang E, Zhang, Yanxiao, Farah, Elie N, Wang, Allen, McCulloch, Andrew D, Gaulton, Kyle J, Ren, Bing, Chi, Neil C, and Preissl, Sebastian
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Biotechnology ,Cardiovascular ,Genetics ,Human Genome ,Heart Disease ,Aetiology ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Heart ,Humans ,Promoter Regions ,Genetic ,Regulatory Sequences ,Nucleic Acid ,Transcription Factors - Abstract
Misregulated gene expression in human hearts can result in cardiovascular diseases that are leading causes of mortality worldwide. However, the limited information on the genomic location of candidate cis-regulatory elements (cCREs) such as enhancers and promoters in distinct cardiac cell types has restricted the understanding of these diseases. Here, we defined >287,000 cCREs in the four chambers of the human heart at single-cell resolution, which revealed cCREs and candidate transcription factors associated with cardiac cell types in a region-dependent manner and during heart failure. We further found cardiovascular disease-associated genetic variants enriched within these cCREs including 38 candidate causal atrial fibrillation variants localized to cardiomyocyte cCREs. Additional functional studies revealed that two of these variants affect a cCRE controlling KCNH2/HERG expression and action potential repolarization. Overall, this atlas of human cardiac cCREs provides the foundation for illuminating cell type-specific gene regulation in human hearts during health and disease.
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- 2021
15. Glucocorticoid signaling in pancreatic islets modulates gene regulatory programs and genetic risk of type 2 diabetes.
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Aylward, Anthony, Okino, Mei-Lin, Benaglio, Paola, Chiou, Joshua, Beebe, Elisha, Padilla, Jose Andres, Diep, Sharlene, and Gaulton, Kyle J
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Developmental Biology ,Genetics - Abstract
Glucocorticoids are key regulators of glucose homeostasis and pancreatic islet function, but the gene regulatory programs driving responses to glucocorticoid signaling in islets and the contribution of these programs to diabetes risk are unknown. In this study we used ATAC-seq and RNA-seq to map chromatin accessibility and gene expression from eleven primary human islet samples cultured in vitro with the glucocorticoid dexamethasone at multiple doses and durations. We identified thousands of accessible chromatin sites and genes with significant changes in activity in response to glucocorticoids. Chromatin sites up-regulated in glucocorticoid signaling were prominently enriched for glucocorticoid receptor binding sites and up-regulated genes were enriched for ion transport and lipid metabolism, whereas down-regulated chromatin sites and genes were enriched for inflammatory, stress response and proliferative processes. Genetic variants associated with glucose levels and T2D risk were enriched in glucocorticoid-responsive chromatin sites, including fine-mapped variants at 51 known signals. Among fine-mapped variants in glucocorticoid-responsive chromatin, a likely casual variant at the 2p21 locus had glucocorticoid-dependent allelic effects on beta cell enhancer activity and affected SIX2 and SIX3 expression. Our results provide a comprehensive map of islet regulatory programs in response to glucocorticoids through which we uncover a role for islet glucocorticoid signaling in mediating genetic risk of T2D.
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- 2021
16. Single-cell chromatin accessibility identifies pancreatic islet cell type– and state-specific regulatory programs of diabetes risk
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Chiou, Joshua, Zeng, Chun, Cheng, Zhang, Han, Jee Yun, Schlichting, Michael, Miller, Michael, Mendez, Robert, Huang, Serina, Wang, Jinzhao, Sui, Yinghui, Deogaygay, Allison, Okino, Mei-Lin, Qiu, Yunjiang, Sun, Ying, Kudtarkar, Parul, Fang, Rongxin, Preissl, Sebastian, Sander, Maike, Gorkin, David U, and Gaulton, Kyle J
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Biochemistry and Cell Biology ,Genetics ,Biological Sciences ,Biotechnology ,Stem Cell Research - Embryonic - Non-Human ,Human Genome ,Stem Cell Research ,Diabetes ,1.1 Normal biological development and functioning ,2.1 Biological and endogenous factors ,Metabolic and endocrine ,Blood Glucose ,Cell Differentiation ,Chromatin ,Diabetes Mellitus ,Type 2 ,Epigenomics ,Fasting ,Gene Expression Profiling ,Genome-Wide Association Study ,Glucagon-Secreting Cells ,High-Throughput Nucleotide Sequencing ,Human Embryonic Stem Cells ,Humans ,Insulin-Secreting Cells ,KCNQ1 Potassium Channel ,Multigene Family ,Pancreatic Polypeptide-Secreting Cells ,Polymorphism ,Genetic ,Single-Cell Analysis ,Somatostatin-Secreting Cells ,Transcription Factors ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
Single-nucleus assay for transposase-accessible chromatin using sequencing (snATAC-seq) creates new opportunities to dissect cell type-specific mechanisms of complex diseases. Since pancreatic islets are central to type 2 diabetes (T2D), we profiled 15,298 islet cells by using combinatorial barcoding snATAC-seq and identified 12 clusters, including multiple alpha, beta and delta cell states. We cataloged 228,873 accessible chromatin sites and identified transcription factors underlying lineage- and state-specific regulation. We observed state-specific enrichment of fasting glucose and T2D genome-wide association studies for beta cells and enrichment for other endocrine cell types. At T2D signals localized to islet-accessible chromatin, we prioritized variants with predicted regulatory function and co-accessibility with target genes. A causal T2D variant rs231361 at the KCNQ1 locus had predicted effects on a beta cell enhancer co-accessible with INS and genome editing in embryonic stem cell-derived beta cells affected INS levels. Together our findings demonstrate the power of single-cell epigenomics for interpreting complex disease genetics.
- Published
- 2021
17. Systematic analysis of binding of transcription factors to noncoding variants
- Author
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Yan, Jian, Qiu, Yunjiang, Ribeiro dos Santos, André M, Yin, Yimeng, Li, Yang E, Vinckier, Nick, Nariai, Naoki, Benaglio, Paola, Raman, Anugraha, Li, Xiaoyu, Fan, Shicai, Chiou, Joshua, Chen, Fulin, Frazer, Kelly A, Gaulton, Kyle J, Sander, Maike, Taipale, Jussi, and Ren, Bing
- Subjects
Biological Sciences ,Bioinformatics and Computational Biology ,Genetics ,Human Genome ,Generic health relevance ,Binding Sites ,Disease ,Genome ,Human ,Humans ,Ligands ,Polymorphism ,Single Nucleotide ,Protein Binding ,SELEX Aptamer Technique ,Support Vector Machine ,Transcription Factors ,General Science & Technology - Abstract
Many sequence variants have been linked to complex human traits and diseases1, but deciphering their biological functions remains challenging, as most of them reside in noncoding DNA. Here we have systematically assessed the binding of 270 human transcription factors to 95,886 noncoding variants in the human genome using an ultra-high-throughput multiplex protein-DNA binding assay, termed single-nucleotide polymorphism evaluation by systematic evolution of ligands by exponential enrichment (SNP-SELEX). The resulting 828 million measurements of transcription factor-DNA interactions enable estimation of the relative affinity of these transcription factors to each variant in vitro and evaluation of the current methods to predict the effects of noncoding variants on transcription factor binding. We show that the position weight matrices of most transcription factors lack sufficient predictive power, whereas the support vector machine combined with the gapped k-mer representation show much improved performance, when assessed on results from independent SNP-SELEX experiments involving a new set of 61,020 sequence variants. We report highly predictive models for 94 human transcription factors and demonstrate their utility in genome-wide association studies and understanding of the molecular pathways involved in diverse human traits and diseases.
- Published
- 2021
18. Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics.
- Author
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Muus, Christoph, Luecken, Malte, Eraslan, Gökcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik, Duong, Elizabeth, Fiskin, Evgenij, Torlai Triglia, Elena, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam, Chung, Hattie, Montoro, Daniel, Adams, Taylor, Aliee, Hananeh, Allon, Samuel, Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Bécavin, Christophe, Benhar, Inbal, Bergenstråhle, Joseph, Bergenstråhle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh, Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas, Cuoco, Michael, Cuomo, Anna, Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David, Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin, Habermann, Arun, Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros, Kuo, Christin, Larsson, Ludvig, Leney-Greene, Michael, Lim, Kyungtae, Litviňuková, Monika, Ludwig, Leif, Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph, Mbano, Ian, McAdams, Alexi, Nabhan, Ahmad, Nyquist, Sarah, Penland, Lolita, Poirion, Olivier, Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas, Shea, Conor, Shi, Xingyi, Sinha, Rahul, Sit, Rene, Slowikowski, Kamil, Slyper, Michal, Smith, Neal, Sountoulidis, Alex, Strunz, Maximilian, and Sullivan, Travis
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Adult ,Aged ,Aged ,80 and over ,Alveolar Epithelial Cells ,Angiotensin-Converting Enzyme 2 ,COVID-19 ,Cathepsin L ,Datasets as Topic ,Demography ,Female ,Gene Expression Profiling ,Host-Pathogen Interactions ,Humans ,Lung ,Male ,Middle Aged ,Organ Specificity ,Respiratory System ,SARS-CoV-2 ,Sequence Analysis ,RNA ,Serine Endopeptidases ,Single-Cell Analysis ,Virus Internalization - Abstract
Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.
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- 2021
19. Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development.
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Geusz, Ryan J, Wang, Allen, Chiou, Joshua, Lancman, Joseph J, Wetton, Nichole, Kefalopoulou, Samy, Wang, Jinzhao, Qiu, Yunjiang, Yan, Jian, Aylward, Anthony, Ren, Bing, Dong, P Duc Si, Gaulton, Kyle J, and Sander, Maike
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GWAS ,Type 2 diabetes ,Zebrafish ,chromatin ,developmental biology ,genetics ,genomics ,hESC ,human ,pancreas ,zebrafish ,Cancer ,Stem Cell Research ,Regenerative Medicine ,Rare Diseases ,Digestive Diseases ,Stem Cell Research - Embryonic - Human ,Diabetes ,Pancreatic Cancer ,Genetics ,Metabolic and endocrine ,Biochemistry and Cell Biology - Abstract
Genetic variants associated with type 2 diabetes (T2D) risk affect gene regulation in metabolically relevant tissues, such as pancreatic islets. Here, we investigated contributions of regulatory programs active during pancreatic development to T2D risk. Generation of chromatin maps from developmental precursors throughout pancreatic differentiation of human embryonic stem cells (hESCs) identifies enrichment of T2D variants in pancreatic progenitor-specific stretch enhancers that are not active in islets. Genes associated with progenitor-specific stretch enhancers are predicted to regulate developmental processes, most notably tissue morphogenesis. Through gene editing in hESCs, we demonstrate that progenitor-specific enhancers harboring T2D-associated variants regulate cell polarity genes LAMA1 and CRB2. Knockdown of lama1 or crb2 in zebrafish embryos causes a defect in pancreas morphogenesis and impairs islet cell development. Together, our findings reveal that a subset of T2D risk variants specifically affects pancreatic developmental programs, suggesting that dysregulation of developmental processes can predispose to T2D.
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- 2021
20. Author Correction: An atlas of dynamic chromatin landscapes in mouse fetal development
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Gorkin, David U, Barozzi, Iros, Zhao, Yuan, Zhang, Yanxiao, Huang, Hui, Lee, Ah Young, Li, Bin, Chiou, Joshua, Wildberg, Andre, Ding, Bo, Zhang, Bo, Wang, Mengchi, Strattan, J Seth, Davidson, Jean M, Qiu, Yunjiang, Afzal, Veena, Akiyama, Jennifer A, Plajzer-Frick, Ingrid, Novak, Catherine S, Kato, Momoe, Garvin, Tyler H, Pham, Quan T, Harrington, Anne N, Mannion, Brandon J, Lee, Elizabeth A, Fukuda-Yuzawa, Yoko, He, Yupeng, Preissl, Sebastian, Chee, Sora, Han, Jee Yun, Williams, Brian A, Trout, Diane, Amrhein, Henry, Yang, Hongbo, Cherry, J Michael, Wang, Wei, Gaulton, Kyle, Ecker, Joseph R, Shen, Yin, Dickel, Diane E, Visel, Axel, Pennacchio, Len A, and Ren, Bing
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Reproductive Medicine ,Biomedical and Clinical Sciences ,Pediatric ,General Science & Technology - Abstract
A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03089-4.
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- 2021
21. Sequence logic at enhancers governs a dual mechanism of endodermal organ fate induction by FOXA pioneer factors
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Geusz, Ryan J, Wang, Allen, Lam, Dieter K, Vinckier, Nicholas K, Alysandratos, Konstantinos-Dionysios, Roberts, David A, Wang, Jinzhao, Kefalopoulou, Samy, Ramirez, Araceli, Qiu, Yunjiang, Chiou, Joshua, Gaulton, Kyle J, Ren, Bing, Kotton, Darrell N, and Sander, Maike
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Biochemistry and Cell Biology ,Biological Sciences ,Pancreatic Cancer ,Cancer ,Digestive Diseases ,Stem Cell Research ,Rare Diseases ,Genetics ,Binding Sites ,Cell Differentiation ,Embryonic Stem Cells ,Endoderm ,Enhancer Elements ,Genetic ,Gene Expression Regulation ,Developmental ,Hepatocyte Nuclear Factor 3-alpha ,Hepatocyte Nuclear Factor 3-beta ,Homeodomain Proteins ,Humans ,Liver ,Lung ,Nucleotide Motifs ,Organ Specificity ,Organogenesis ,Pancreas ,Trans-Activators - Abstract
FOXA pioneer transcription factors (TFs) associate with primed enhancers in endodermal organ precursors. Using a human stem cell model of pancreas differentiation, we here discover that only a subset of pancreatic enhancers is FOXA-primed, whereas the majority is unprimed and engages FOXA upon lineage induction. Primed enhancers are enriched for signal-dependent TF motifs and harbor abundant and strong FOXA motifs. Unprimed enhancers harbor fewer, more degenerate FOXA motifs, and FOXA recruitment to unprimed but not primed enhancers requires pancreatic TFs. Strengthening FOXA motifs at an unprimed enhancer near NKX6.1 renders FOXA recruitment pancreatic TF-independent, induces priming, and broadens the NKX6.1 expression domain. We make analogous observations about FOXA binding during hepatic and lung development. Our findings suggest a dual role for FOXA in endodermal organ development: first, FOXA facilitates signal-dependent lineage initiation via enhancer priming, and second, FOXA enforces organ cell type-specific gene expression via indirect recruitment by lineage-specific TFs.
- Published
- 2021
22. Single-cell multiomic profiling of human lungs reveals cell-type-specific and age-dynamic control of SARS-CoV2 host genes.
- Author
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Wang, Allen, Chiou, Joshua, Poirion, Olivier B, Buchanan, Justin, Valdez, Michael J, Verheyden, Jamie M, Hou, Xiaomeng, Kudtarkar, Parul, Narendra, Sharvari, Newsome, Jacklyn M, Guo, Minzhe, Faddah, Dina A, Zhang, Kai, Young, Randee E, Barr, Justinn, Sajti, Eniko, Misra, Ravi, Huyck, Heidie, Rogers, Lisa, Poole, Cory, Whitsett, Jeffery A, Pryhuber, Gloria, Xu, Yan, Gaulton, Kyle J, Preissl, Sebastian, Sun, Xin, and NHLBI LungMap Consortium
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NHLBI LungMap Consortium ,Lung ,Humans ,Membrane Transport Proteins ,Receptors ,Virus ,Chromosome Mapping ,Gene Expression Profiling ,Age Factors ,Adult ,Child ,Preschool ,Infant ,Newborn ,Virus Internalization ,Genetic Variation ,Pandemics ,Single-Cell Analysis ,Alveolar Epithelial Cells ,Host Microbial Interactions ,COVID-19 ,Angiotensin-Converting Enzyme 2 ,SARS-CoV-2 ,cis-regulatory elements ,developmental biology ,gene regulation ,genetics ,genomics ,human ,human sequence variants ,lung ,single cell RNA/ATAC-seq ,Receptors ,Virus ,Child ,Preschool ,Infant ,Newborn ,Biochemistry and Cell Biology - Abstract
Respiratory failure associated with COVID-19 has placed focus on the lungs. Here, we present single-nucleus accessible chromatin profiles of 90,980 nuclei and matched single-nucleus transcriptomes of 46,500 nuclei in non-diseased lungs from donors of ~30 weeks gestation,~3 years and ~30 years. We mapped candidate cis-regulatory elements (cCREs) and linked them to putative target genes. We identified distal cCREs with age-increased activity linked to SARS-CoV-2 host entry gene TMPRSS2 in alveolar type 2 cells, which had immune regulatory signatures and harbored variants associated with respiratory traits. At the 3p21.31 COVID-19 risk locus, a candidate variant overlapped a distal cCRE linked to SLC6A20, a gene expressed in alveolar cells and with known functional association with the SARS-CoV-2 receptor ACE2. Our findings provide insight into regulatory logic underlying genes implicated in COVID-19 in individual lung cell types across age. More broadly, these datasets will facilitate interpretation of risk loci for lung diseases.
- Published
- 2020
23. Author Correction: An atlas of dynamic chromatin landscapes in mouse fetal development
- Author
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Gorkin, David U, Barozzi, Iros, Zhao, Yuan, Zhang, Yanxiao, Huang, Hui, Lee, Ah Young, Li, Bin, Chiou, Joshua, Wildberg, Andre, Ding, Bo, Zhang, Bo, Wang, Mengchi, Strattan, J Seth, Davidson, Jean M, Qiu, Yunjiang, Afzal, Veena, Akiyama, Jennifer A, Plajzer-Frick, Ingrid, Novak, Catherine S, Kato, Momoe, Garvin, Tyler H, Pham, Quan T, Harrington, Anne N, Mannion, Brandon J, Lee, Elizabeth A, Fukuda-Yuzawa, Yoko, He, Yupeng, Preissl, Sebastian, Chee, Sora, Han, Jee Yun, Williams, Brian A, Trout, Diane, Amrhein, Henry, Yang, Hongbo, Cherry, J Michael, Wang, Wei, Gaulton, Kyle, Ecker, Joseph R, Shen, Yin, Dickel, Diane E, Visel, Axel, Pennacchio, Len A, and Ren, Bing
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Reproductive Medicine ,Biomedical and Clinical Sciences ,General Science & Technology - Abstract
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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- 2020
24. An atlas of dynamic chromatin landscapes in mouse fetal development
- Author
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Gorkin, David U, Barozzi, Iros, Zhao, Yuan, Zhang, Yanxiao, Huang, Hui, Lee, Ah Young, Li, Bin, Chiou, Joshua, Wildberg, Andre, Ding, Bo, Zhang, Bo, Wang, Mengchi, Strattan, J Seth, Davidson, Jean M, Qiu, Yunjiang, Afzal, Veena, Akiyama, Jennifer A, Plajzer-Frick, Ingrid, Novak, Catherine S, Kato, Momoe, Garvin, Tyler H, Pham, Quan T, Harrington, Anne N, Mannion, Brandon J, Lee, Elizabeth A, Fukuda-Yuzawa, Yoko, He, Yupeng, Preissl, Sebastian, Chee, Sora, Han, Jee Yun, Williams, Brian A, Trout, Diane, Amrhein, Henry, Yang, Hongbo, Cherry, J Michael, Wang, Wei, Gaulton, Kyle, Ecker, Joseph R, Shen, Yin, Dickel, Diane E, Visel, Axel, Pennacchio, Len A, and Ren, Bing
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Biological Sciences ,Bioinformatics and Computational Biology ,Biomedical and Clinical Sciences ,Genetics ,Biotechnology ,Human Genome ,Pediatric ,1.1 Normal biological development and functioning ,2.1 Biological and endogenous factors ,Generic health relevance ,Animals ,Chromatin ,Chromatin Immunoprecipitation Sequencing ,Datasets as Topic ,Disease ,Enhancer Elements ,Genetic ,Female ,Fetal Development ,Gene Expression Regulation ,Developmental ,Genetic Variation ,Histones ,Humans ,Male ,Mice ,Mice ,Inbred C57BL ,Molecular Sequence Annotation ,Organ Specificity ,Regulatory Sequences ,Nucleic Acid ,Reproducibility of Results ,Transposases ,General Science & Technology - Abstract
The Encyclopedia of DNA Elements (ENCODE) project has established a genomic resource for mammalian development, profiling a diverse panel of mouse tissues at 8 developmental stages from 10.5 days after conception until birth, including transcriptomes, methylomes and chromatin states. Here we systematically examined the state and accessibility of chromatin in the developing mouse fetus. In total we performed 1,128 chromatin immunoprecipitation with sequencing (ChIP-seq) assays for histone modifications and 132 assay for transposase-accessible chromatin using sequencing (ATAC-seq) assays for chromatin accessibility across 72 distinct tissue-stages. We used integrative analysis to develop a unified set of chromatin state annotations, infer the identities of dynamic enhancers and key transcriptional regulators, and characterize the relationship between chromatin state and accessibility during developmental gene regulation. We also leveraged these data to link enhancers to putative target genes and demonstrate tissue-specific enrichments of sequence variants associated with disease in humans. The mouse ENCODE data sets provide a compendium of resources for biomedical researchers and achieve, to our knowledge, the most comprehensive view of chromatin dynamics during mammalian fetal development to date.
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- 2020
25. Common DNA sequence variation influences 3-dimensional conformation of the human genome
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Gorkin, David U, Qiu, Yunjiang, Hu, Ming, Fletez-Brant, Kipper, Liu, Tristin, Schmitt, Anthony D, Noor, Amina, Chiou, Joshua, Gaulton, Kyle J, Sebat, Jonathan, Li, Yun, Hansen, Kasper D, and Ren, Bing
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Cancer ,Human Genome ,Stem Cell Research ,Genetics ,1.1 Normal biological development and functioning ,Underpinning research ,Generic health relevance ,Base Sequence ,Epigenome ,Genetic Variation ,Genome ,Human ,Humans ,Nucleic Acid Conformation ,Quantitative Trait Loci ,Transcriptome ,Environmental Sciences ,Biological Sciences ,Information and Computing Sciences ,Bioinformatics - Abstract
BACKGROUND:The 3-dimensional (3D) conformation of chromatin inside the nucleus is integral to a variety of nuclear processes including transcriptional regulation, DNA replication, and DNA damage repair. Aberrations in 3D chromatin conformation have been implicated in developmental abnormalities and cancer. Despite the importance of 3D chromatin conformation to cellular function and human health, little is known about how 3D chromatin conformation varies in the human population, or whether DNA sequence variation between individuals influences 3D chromatin conformation. RESULTS:To address these questions, we perform Hi-C on lymphoblastoid cell lines from 20 individuals. We identify thousands of regions across the genome where 3D chromatin conformation varies between individuals and find that this variation is often accompanied by variation in gene expression, histone modifications, and transcription factor binding. Moreover, we find that DNA sequence variation influences several features of 3D chromatin conformation including loop strength, contact insulation, contact directionality, and density of local cis contacts. We map hundreds of quantitative trait loci associated with 3D chromatin features and find evidence that some of these same variants are associated at modest levels with other molecular phenotypes as well as complex disease risk. CONCLUSION:Our results demonstrate that common DNA sequence variants can influence 3D chromatin conformation, pointing to a more pervasive role for 3D chromatin conformation in human phenotypic variation than previously recognized.
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- 2019
26. A Network of microRNAs Acts to Promote Cell Cycle Exit and Differentiation of Human Pancreatic Endocrine Cells
- Author
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Jin, Wen, Mulas, Francesca, Gaertner, Bjoern, Sui, Yinghui, Wang, Jinzhao, Matta, Ileana, Zeng, Chun, Vinckier, Nicholas, Wang, Allen, Nguyen-Ngoc, Kim-Vy, Chiou, Joshua, Kaestner, Klaus H, Frazer, Kelly A, Carrano, Andrea C, Shih, Hung-Ping, and Sander, Maike
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Biological Sciences ,Bioinformatics and Computational Biology ,Medicinal and Biomolecular Chemistry ,Chemical Sciences ,Stem Cell Research ,Genetics ,Stem Cell Research - Embryonic - Human ,Diabetes ,Biotechnology ,1.1 Normal biological development and functioning ,2.1 Biological and endogenous factors ,Generic health relevance ,Endocrinology ,Molecular Mechanism of Gene Regulation ,Molecular Network ,Stem Cells Research - Abstract
Pancreatic endocrine cell differentiation is orchestrated by the action of transcription factors that operate in a gene regulatory network to activate endocrine lineage genes and repress lineage-inappropriate genes. MicroRNAs (miRNAs) are important modulators of gene expression, yet their role in endocrine cell differentiation has not been systematically explored. Here we characterize miRNA-regulatory networks active in human endocrine cell differentiation by combining small RNA sequencing, miRNA over-expression, and network modeling approaches. Our analysis identified Let-7g, Let-7a, miR-200a, miR-127, and miR-375 as endocrine-enriched miRNAs that drive endocrine cell differentiation-associated gene expression changes. These miRNAs are predicted to target different transcription factors, which converge on genes involved in cell cycle regulation. When expressed in human embryonic stem cell-derived pancreatic progenitors, these miRNAs induce cell cycle exit and promote endocrine cell differentiation. Our study delineates the role of miRNAs in human endocrine cell differentiation and identifies miRNAs that could facilitate endocrine cell reprogramming.
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- 2019
27. Illuminating the Onco-GPCRome: Novel G protein–coupled receptor-driven oncocrine networks and targets for cancer immunotherapy
- Author
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Wu, Victoria, Yeerna, Huwate, Nohata, Nijiro, Chiou, Joshua, Harismendy, Olivier, Raimondi, Francesco, Inoue, Asuka, Russell, Robert B, Tamayo, Pablo, and Gutkind, J Silvio
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Biochemistry and Cell Biology ,Biomedical and Clinical Sciences ,Biological Sciences ,Immunology ,Oncology and Carcinogenesis ,Cancer ,2.1 Biological and endogenous factors ,Good Health and Well Being ,Animals ,DNA Copy Number Variations ,Humans ,Immunotherapy ,Mutation ,Neoplasms ,Receptors ,G-Protein-Coupled ,Signal Transduction ,G protein-coupled receptor ,G protein ,signal transduction ,cancer ,immunotherapy ,drug repurposing ,oncocrine signaling ,precision therapies ,G protein–coupled receptor ,Chemical Sciences ,Medical and Health Sciences ,Biochemistry & Molecular Biology ,Biological sciences ,Biomedical and clinical sciences ,Chemical sciences - Abstract
G protein-coupled receptors (GPCRs) are the largest gene family of cell membrane-associated molecules mediating signal transmission, and their involvement in key physiological functions is well-established. The ability of GPCRs to regulate a vast array of fundamental biological processes, such as cardiovascular functions, immune responses, hormone and enzyme release from endocrine and exocrine glands, neurotransmission, and sensory perception (e.g. vision, odor, and taste), is largely due to the diversity of these receptors and the layers of their downstream signaling circuits. Dysregulated expression and aberrant functions of GPCRs have been linked to some of the most prevalent human diseases, which renders GPCRs one of the top targets for pharmaceutical drug development. However, the study of the role of GPCRs in tumor biology has only just begun to make headway. Recent studies have shown that GPCRs can contribute to the many facets of tumorigenesis, including proliferation, survival, angiogenesis, invasion, metastasis, therapy resistance, and immune evasion. Indeed, GPCRs are widely dysregulated in cancer and yet are underexploited in oncology. We present here a comprehensive analysis of GPCR gene expression, copy number variation, and mutational signatures in 33 cancer types. We also highlight the emerging role of GPCRs as part of oncocrine networks promoting tumor growth, dissemination, and immune evasion, and we stress the potential benefits of targeting GPCRs and their signaling circuits in the new era of precision medicine and cancer immunotherapies.
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- 2019
28. Pancreatic islet chromatin accessibility and conformation reveals distal enhancer networks of type 2 diabetes risk.
- Author
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Greenwald, William W, Chiou, Joshua, Yan, Jian, Qiu, Yunjiang, Dai, Ning, Wang, Allen, Nariai, Naoki, Aylward, Anthony, Han, Jee Yun, Kadakia, Nikita, Regue, Laura, Okino, Mei-Lin, Drees, Frauke, Kramer, Dana, Vinckier, Nicholas, Minichiello, Liliana, Gorkin, David, Avruch, Joseph, Frazer, Kelly A, Sander, Maike, Ren, Bing, and Gaulton, Kyle J
- Subjects
Islets of Langerhans ,Cell Nucleus ,Chromatin ,Animals ,Mice ,Inbred C57BL ,Mice ,Knockout ,Humans ,Mice ,Diabetes Mellitus ,Type 2 ,Genetic Predisposition to Disease ,Insulin ,Glucose ,RNA-Binding Proteins ,Gene Expression Profiling ,Chromatin Assembly and Disassembly ,Molecular Conformation ,Quantitative Trait Loci ,Adult ,Middle Aged ,Female ,Male ,Gene Regulatory Networks ,Enhancer Elements ,Genetic ,Genetics ,Diabetes ,Biotechnology ,Human Genome ,2.1 Biological and endogenous factors ,Metabolic and endocrine - Abstract
Genetic variants affecting pancreatic islet enhancers are central to T2D risk, but the gene targets of islet enhancer activity are largely unknown. We generate a high-resolution map of islet chromatin loops using Hi-C assays in three islet samples and use loops to annotate target genes of islet enhancers defined using ATAC-seq and published ChIP-seq data. We identify candidate target genes for thousands of islet enhancers, and find that enhancer looping is correlated with islet-specific gene expression. We fine-map T2D risk variants affecting islet enhancers, and find that candidate target genes of these variants defined using chromatin looping and eQTL mapping are enriched in protein transport and secretion pathways. At IGF2BP2, a fine-mapped T2D variant reduces islet enhancer activity and IGF2BP2 expression, and conditional inactivation of IGF2BP2 in mouse islets impairs glucose-stimulated insulin secretion. Our findings provide a resource for studying islet enhancer function and identifying genes involved in T2D risk.
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- 2019
29. The long noncoding RNA ROCKI regulates inflammatory gene expression
- Author
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Zhang, Qiong, Chao, Ti‐Chun, Patil, Veena S, Qin, Yue, Tiwari, Shashi Kant, Chiou, Joshua, Dobin, Alexander, Tsai, Chih‐Ming, Li, Zhonghan, Dang, Jason, Gupta, Shagun, Urdahl, Kevin, Nizet, Victor, Gingeras, Thomas R, Gaulton, Kyle J, and Rana, Tariq M
- Subjects
Biological Sciences ,Biomedical and Clinical Sciences ,Genetics ,Emerging Infectious Diseases ,Biotechnology ,Human Genome ,Biodefense ,Infectious Diseases ,2.1 Biological and endogenous factors ,1.1 Normal biological development and functioning ,Inflammatory and immune system ,Good Health and Well Being ,Cells ,Cultured ,Cytokines ,DNA-(Apurinic or Apyrimidinic Site) Lyase ,Gene Expression Regulation ,Genome ,Human ,Histone Deacetylase 1 ,Humans ,Immunity ,Innate ,Inflammation ,Macrophages ,Myristoylated Alanine-Rich C Kinase Substrate ,Promoter Regions ,Genetic ,RNA ,Long Noncoding ,Streptococcal Infections ,Streptococcus agalactiae ,Toll-Like Receptors ,cytokine production ,host-pathogen interactions ,innate immune system ,lncRNA ,TLRs ,host–pathogen interactions ,Information and Computing Sciences ,Medical and Health Sciences ,Developmental Biology ,Biological sciences ,Biomedical and clinical sciences - Abstract
Long noncoding RNAs (lncRNAs) can regulate target gene expression by acting in cis (locally) or in trans (non-locally). Here, we performed genome-wide expression analysis of Toll-like receptor (TLR)-stimulated human macrophages to identify pairs of cis-acting lncRNAs and protein-coding genes involved in innate immunity. A total of 229 gene pairs were identified, many of which were commonly regulated by signaling through multiple TLRs and were involved in the cytokine responses to infection by group B Streptococcus We focused on elucidating the function of one lncRNA, named lnc-MARCKS or ROCKI (Regulator of Cytokines and Inflammation), which was induced by multiple TLR stimuli and acted as a master regulator of inflammatory responses. ROCKI interacted with APEX1 (apurinic/apyrimidinic endodeoxyribonuclease 1) to form a ribonucleoprotein complex at the MARCKS promoter. In turn, ROCKI-APEX1 recruited the histone deacetylase HDAC1, which removed the H3K27ac modification from the promoter, thus reducing MARCKS transcription and subsequent Ca2+ signaling and inflammatory gene expression. Finally, genetic variants affecting ROCKI expression were linked to a reduced risk of certain inflammatory and infectious disease in humans, including inflammatory bowel disease and tuberculosis. Collectively, these data highlight the importance of cis-acting lncRNAs in TLR signaling, innate immunity, and pathophysiological inflammation.
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- 2019
30. Genetic Discovery and Risk Prediction for Type 1 Diabetes in Individuals Without High-Risk HLA-DR3/DR4 Haplotypes.
- Author
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McGrail, Carolyn, Chiou, Joshua, Elgamal, Ruth, Luckett, Amber M., Oram, Richard A., Benaglio, Paola, and Gaulton, Kyle J.
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GENETIC risk score , *TYPE 1 diabetes , *TYPE 2 diabetes , *DISEASE risk factors , *ANTIGEN presentation - Abstract
OBJECTIVE: More than 10% of patients with type 1 diabetes (T1D) do not have high-risk HLA-DR3 or -DR4 haplotypes with distinct clinical features, such as later onset and reduced insulin dependence. We aimed to identify genetic drivers of T1D in the absence of DR3/DR4 and improve prediction of T1D risk in these individuals. RESEARCH DESIGN AND METHODS: We performed T1D association and fine-mapping analyses in 12,316 non-DR3/DR4 samples. Next, we performed heterogeneity tests to examine differences in T1D risk variants in individuals without versus those with DR3/DR4 haplotypes. We further assessed genome-wide differences in gene regulatory element and biological pathway enrichments between the non-DR3/DR4 and DR3/DR4 cohorts. Finally, we developed a genetic risk score (GRS) to predict T1D in individuals without DR3/DR4 and comparedwith an existing T1DGRS. RESULTS: k variants in non-DR3/DR4 samples were identified. Risk variants at the MHC and multiple other loci genome wide had heterogeneity in effects on T1D dependent on DR3/DR4 status, and non-DR3/DR4 T1D had evidence for a greater polygenic burden. T1D-associated variants in non-DR3/DR4 were more enriched for regulatory elements and pathways involved in antigen presentation, innate immunity, and β-cells and depleted in T cells compared with DR3/DR4. A non-DR3/DR4 GRS outperformed an existing risk score GRS2 in discriminating non-DR3/DR4 T1D from no diabetes (area under the curve 0.867; P = 7.48 × 10-32) and type 2 diabetes (0.907; P = 4.94 × 10-44). CONCLUSIONS: In total, we identified heterogeneity in T1D genetic risk dependent on high-risk HLA-DR3/DR4 haplotype, which uncovers disease mechanisms and enables more accurate prediction of T1D across the HLA background. [ABSTRACT FROM AUTHOR]
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- 2025
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31. Integrative analysis of the genome, transcriptome, and proteome identifies causal mechanisms of complex traits.
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Okamoto, Jeffrey, primary, Yin, Xianyong, additional, Ryan, Brady, additional, Chiou, Joshua, additional, Luca, Francesca, additional, Pique-Regi, Roger, additional, Im, Hae Kyung, additional, Morrison, Jean, additional, Burant, Charles, additional, Fauman, Eric, additional, Laakso, Markku, additional, Boehnke, Michael, additional, and Wen, Xiaoquan, additional
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- 2024
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32. Protein chainmail variants in dsDNA viruses
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Zhou, Z Hong and Chiou, Joshua
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Biochemistry and Cell Biology ,Biological Sciences ,structural biology ,microbiology ,protein chainmail ,HK97 ,BPP-1 ,P22 ,lambda ,Herpesvirus ,RRV ,HK97-like fold ,virus ,cryoEM ,X-ray crystallography ,Zoology ,Medical physiology - Abstract
First discovered in bacteriophage HK97, biological chainmail is a highly stable system formed by concatenated protein rings. Each subunit of the ring contains the HK97-like fold, which is characterized by its submarine-like shape with a 5-stranded β sheet in the axial (A) domain, spine helix in the peripheral (P) domain, and an extended (E) loop. HK97 capsid consists of covalently-linked copies of just one HK97-like fold protein and represents the most effective strategy to form highly stable chainmail needed for dsDNA genome encapsidation. Recently, near-atomic resolution structures enabled by cryo electron microscopy (cryoEM) have revealed a range of other, more complex variants of this strategy for constructing dsDNA viruses. The first strategy, exemplified by P22-like phages, is the attachment of an insertional (I) domain to the core 5-stranded β sheet of the HK97-like fold. The atomic models of the Bordetella phage BPP-1 showcases an alternative topology of the classic HK97 topology of the HK97-like fold, as well as the second strategy for constructing stable capsids, where an auxiliary jellyroll protein dimer serves to cement the non-covalent chainmail formed by capsid protein subunits. The third strategy, found in lambda-like phages, uses auxiliary protein trimers to stabilize the underlying non-covalent chainmail near the 3-fold axis. Herpesviruses represent highly complex viruses that use a combination of these strategies, resulting in four-level hierarchical organization including a non-covalent chainmail formed by the HK97-like fold domain found in the floor region. A thorough understanding of these structures should help unlock the enigma of the emergence and evolution of dsDNA viruses and inform bioengineering efforts based on these viruses.
- Published
- 2015
33. Genetic discovery and risk prediction for type 1 diabetes in individuals without high-risk HLA-DR3/DR4 haplotypes
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McGrail, Carolyn, primary, Chiou, Joshua, additional, Elgamal, Ruth, additional, Luckett, Amber, additional, Oram, Richard, additional, Benaglio, Paola, additional, and Gaulton, Kyle, additional
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- 2023
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34. Understanding pancreatic mechanisms of diabetes risk with genetic association and single cell epigenome data
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Chiou, Joshua
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Genetics ,Diabetes ,Epigenomics ,Genome-wide association study ,Pancreas ,Single cell genomics - Abstract
Although genome-wide association studies (GWAS) have demonstrated the importance of the pancreas in diabetes risk, mechanistic insight remains challenging in part due to the non-coding nature of risk variants and the lack of cell type-resolved regulatory annotations. Beta cells within pancreatic islets are central to both forms of diabetes and are destroyed by autoimmune mechanisms in T1D or dysfunctional due to insulin resistance in T2D. However, the relevance of beta cell states or other pancreatic cell types to diabetes is relatively unknown. Here I present two studies, both of which use single cell chromatin accessibility to annotate cell type-specific genetic risk mechanisms of diabetes. In the first study, I use snATAC-seq of pancreatic islets to show that endocrine cell types are heterogenous at the gene regulation level, and beta cell states are differently enriched for T2D risk. I highlight a causal T2D variant (rs231361) at the KCNQ1 locus that was predicted to have state-specific effects on regulatory function, was located in a beta cell enhancer co-accessible with INS, and affected expression levels of INS in embryonic stem cell-derived beta cells. In the second study, I generate the largest-to-date GWAS of T1D in 520k samples to enable comprehensive fine mapping of T1D risk signals. I show that pancreatic exocrine cells are causal contributors of T1D through integration of fine mapping with a snATAC-seq reference map of pancreatic and immune cell types. I highlight a likely-causal T1D risk variant (rs7795896) at the CFTR locus that mapped within a ductal-specific enhancer co-accessible with the CFTR promoter, had allele-specific effects on enhancer activity and transcription factor binding in ductal cell models, and was associated with decreased CFTR expression in ductal cells. These two studies highlight the power of integrating comprehensive GWAS fine mapping with single cell epigenomics to understand how pancreatic cell types contribute to diabetes risk.
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- 2021
35. The influence of HLA genetic variation on plasma protein expression
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Krishna, Chirag, primary, Chiou, Joshua, additional, Lee, Isac, additional, Kim, Hye In, additional, Atalar Aksit, Melis, additional, Sakaue, Saori, additional, Von Schack, David, additional, Raychaudhuri, Soumya, additional, Ziemek, Daniel, additional, and Hu, Xinli, additional
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- 2023
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36. Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes
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Wang, Gaowei, primary, Chiou, Joshua, additional, Zeng, Chun, additional, Miller, Michael, additional, Matta, Ileana, additional, Han, Jee Yun, additional, Kadakia, Nikita, additional, Okino, Mei-Lin, additional, Beebe, Elisha, additional, Mallick, Medhavi, additional, Camunas-Soler, Joan, additional, Santos, Theodore dos, additional, Dai, Xiao-Qing, additional, Ellis, Cara, additional, Hang, Yan, additional, Kim, Seung K., additional, MacDonald, Patrick E., additional, Kandeel, Fouad R., additional, Preissl, Sebastian, additional, Gaulton, Kyle J, additional, and Sander, Maike, additional
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- 2023
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37. High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease
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Kim, Hyunkyung, primary, Westerman, Kenneth E., additional, Smith, Kirk, additional, Chiou, Joshua, additional, Cole, Joanne B., additional, Majarian, Timothy, additional, von Grotthuss, Marcin, additional, Kwak, Soo Heon, additional, Kim, Jaegil, additional, Mercader, Josep M., additional, Florez, Jose C., additional, Gaulton, Kyle, additional, Manning, Alisa K., additional, and Udler, Miriam S., additional
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- 2022
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38. 1267-P: Fine-Mapping Type 1 Diabetes Risk at the MHC Locus
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MCGRAIL, CAROLYN, primary, CHIOU, JOSHUA, additional, BENAGLIO, PAOLA, additional, and GAULTON, KYLE J., additional
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- 2022
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39. 295-OR: Identification of Type 1 Diabetes Genes and Regulatory Processes Mediating Pancreatic Beta-Cell Survival in Response to Proinflammatory Cytokines
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BENAGLIO, PAOLA, primary, ZHU, HAN, additional, OKINO, MEI-LIN, additional, YAN, JIAN, additional, ELGAMAL, RUTH, additional, NARIAI, NAOKI, additional, BEEBE, ELISHA, additional, KORGAONKAR, KATHA, additional, QIU, YUNJIANG, additional, DONOVAN, MARGARET, additional, CHIOU, JOSHUA, additional, NEWSOME ASHMUS, JACKLYN M., additional, KAUR, JASPREET, additional, CORBAN, SIERRA, additional, REN, BING, additional, FRAZER, KELLY, additional, SANDER, MAIKE, additional, and GAULTON, KYLE J., additional
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- 2022
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40. Type 2 diabetes genetic loci informed by multi-trait associations point to disease mechanisms and subtypes: A soft clustering analysis
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Udler, Miriam S., Kim, Jaegil, von Grotthuss, Marcin, Bonàs-Guarch, Sílvia, Cole, Joanne B., Chiou, Joshua, Boehnke, Michael, Laakso, Markku, Atzmon, Gil, Glaser, Benjamin, Mercader, Josep M., Gaulton, Kyle, Flannick, Jason, Getz, Gad, and Florez, Jose C.
- Subjects
Type 2 diabetes -- Care and treatment -- Genetic aspects -- Development and progression ,Patient care -- Management ,Treatment outcome -- Analysis ,Biological markers -- Usage ,Diabetics -- Care and treatment ,Company business management ,Biological sciences - Abstract
Background Type 2 diabetes (T2D) is a heterogeneous disease for which (1) disease-causing pathways are incompletely understood and (2) subclassification may improve patient management. Unlike other biomarkers, germline genetic markers do not change with disease progression or treatment. In this paper, we test whether a germline genetic approach informed by physiology can be used to deconstruct T2D heterogeneity. First, we aimed to categorize genetic loci into groups representing likely disease mechanistic pathways. Second, we asked whether the novel clusters of genetic loci we identified have any broad clinical consequence, as assessed in four separate subsets of individuals with T2D. Methods and findings In an effort to identify mechanistic pathways driven by established T2D genetic loci, we applied Bayesian nonnegative matrix factorization (bNMF) clustering to genome-wide association study (GWAS) results for 94 independent T2D genetic variants and 47 diabetes-related traits. We identified five robust clusters of T2D loci and traits, each with distinct tissue-specific enhancer enrichment based on analysis of epigenomic data from 28 cell types. Two clusters contained variant-trait associations indicative of reduced beta cell function, differing from each other by high versus low proinsulin levels. The three other clusters displayed features of insulin resistance: obesity mediated (high body mass index [BMI] and waist circumference [WC]), 'lipodystrophy-like' fat distribution (low BMI, adiponectin, and high-density lipoprotein [HDL] cholesterol, and high triglycerides), and disrupted liver lipid metabolism (low triglycerides). Increased cluster genetic risk scores were associated with distinct clinical outcomes, including increased blood pressure, coronary artery disease (CAD), and stroke. We evaluated the potential for clinical impact of these clusters in four studies containing individuals with T2D (Metabolic Syndrome in Men Study [METSIM], N = 487; Ashkenazi, N = 509; Partners Biobank, N = 2,065; UK Biobank [UKBB], N = 14,813). Individuals with T2D in the top genetic risk score decile for each cluster reproducibly exhibited the predicted cluster-associated phenotypes, with approximately 30% of all individuals assigned to just one cluster top decile. Limitations of this study include that the genetic variants used in the cluster analysis were restricted to those associated with T2D in populations of European ancestry. Conclusion Our approach identifies salient T2D genetically anchored and physiologically informed pathways, and supports the use of genetics to deconstruct T2D heterogeneity. Classification of patients by these genetic pathways may offer a step toward genetically informed T2D patient management., Author(s): Miriam S. Udler 1,2,3,4, Jaegil Kim 3, Marcin von Grotthuss 3, Sílvia Bonàs-Guarch 5, Joanne B. Cole 2,3, Joshua Chiou 6, Christopher D. Anderson on behalf of METASTROKE and [...]
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- 2018
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41. Type 1 diabetes risk genes mediate pancreatic beta cell survival in response to proinflammatory cytokines
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Benaglio, Paola, primary, Zhu, Han, additional, Okino, Mei-Lin, additional, Yan, Jian, additional, Elgamal, Ruth, additional, Nariai, Naoki, additional, Beebe, Elisha, additional, Korgaonkar, Katha, additional, Qiu, Yunjiang, additional, Donovan, Margaret, additional, Chiou, Joshua, additional, Newsome, Jacklyn, additional, Kaur, Jaspreet, additional, Corban, Sierra, additional, Aylward, Anthony, additional, Taipale, Jussi, additional, Ren, Bing, additional, Frazer, Kelly A, additional, Sander, Maike, additional, and Gaulton, Kyle J, additional
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- 2021
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42. Interpreting type 1 diabetes risk with genetics and single-cell epigenomics
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Chiou, Joshua, primary, Geusz, Ryan J, additional, Okino, Mei-Lin, additional, Han, Jee Yun, additional, Miller, Michael, additional, Melton, Rebecca, additional, Beebe, Elisha, additional, Benaglio, Paola, additional, Huang, Serina, additional, Korgaonkar, Katha, additional, Heller, Sandra, additional, Kleger, Alexander, additional, Preissl, Sebastian, additional, Gorkin, David U, additional, Sander, Maike, additional, and Gaulton, Kyle J, additional
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- 2021
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43. Systematic Analysis of Transcription Factors Binding to Noncoding Variants
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Yan, Jian, Qiu, Yunjiang, Ribeiro dos Santos, André M, Yin, Yimeng, Li, Yang E., Vinckier, Nick, Nariai, Naoki, Benaglio, Paola, Raman, Anugraha, Li, Xiaoyu, Fan, Shicai, Chiou, Joshua, Chen, Fulin, Frazer, Kelly A., Gaulton, Kyle J., Sander, Maike, Taipale, Jussi, and Ren, Bing
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Binding Sites ,Support Vector Machine ,Genome, Human ,SELEX Aptamer Technique ,Humans ,Disease ,Ligands ,Polymorphism, Single Nucleotide ,Article ,Protein Binding ,Transcription Factors - Abstract
A large number of sequence variants have been linked to complex human traits and diseases(1), but deciphering their biological functions is still challenging since most of them reside in the noncoding DNA. To fill this gap, we have systematically assessed the binding of 270 human transcription factors (TF) to 95,886 noncoding variants in the human genome using an ultra-high-throughput multiplex protein-DNA binding assay, termed SNP evaluation by Systematic Evolution of Ligands by EXponential enrichment (SNP-SELEX). The resulting 828 million measurements of TF-DNA interactions enable estimation of the relative affinity of these TFs to each variant in vitro and allow for evaluation of the current methods to predict the impact of noncoding variants on TF binding. We show that the Position Weight Matrices (PWMs) of most TFs lack sufficient predictive power, while the Support Vector Machine (SVM) combined with the gapped k-mer representation show much improved performance, when assessed on results from independent SNP-SELEX experiments involving a new set of 61,020 sequence variants. We report highly predictive models for 94 human TFs and demonstrate their utility in genome-wide association studies (GWAS) and understanding of the molecular pathways involved in diverse human traits and diseases.
- Published
- 2021
44. Single Nucleus Multiomic Profiling Reveals Age-Dynamic Regulation of Host Genes Associated with SARS-CoV-2 Infection
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Wang, Allen, Chiou, Joshua, Poirion, Olivier B, Buchanan, Justin, Valdez, Michael J, Verheyden, Jamie M, Hou, Xiaomeng, Guo, Minzhe, Newsome, Jacklyn M, Kudtarkar, Parul, Faddah, Dina A, Zhang, Kai, Young, Randee E, Barr, Justinn, Misra, Ravi, Huyck, Heidie, Rogers, Lisa, Poole, Cory, Whitsett, Jeffery A., Pryhuber, Gloria, Xu, Yan, Gaulton, Kyle J, Preissl, Sebastian, and Sun, Xin
- Subjects
0303 health sciences ,Biology ,TMPRSS2 ,stat ,Chromatin ,03 medical and health sciences ,0302 clinical medicine ,medicine.anatomical_structure ,030228 respiratory system ,Respiratory failure ,Immunology ,medicine ,Respiratory system ,Gene ,Nucleus ,030304 developmental biology ,Epigenomics - Abstract
SUMMARYRespiratory failure is the leading cause of COVID-19 death and disproportionately impacts adults more than children. Here, we present a large-scale snATAC-seq dataset (90,980 nuclei) of the human lung, generated in parallel with snRNA-seq (46,500 nuclei), from healthy donors of ~30 weeks, ~3 years and ~30 years of age. Focusing on genes implicated in SARS-CoV-2 cell entry, we observed an increase in the proportion of alveolar epithelial cells expressingACE2andTMPRSS2in adult compared to young lungs. Consistent with expression dynamics, 10 chromatin peaks linked toTMPRSS2exhibited significantly increased activity with age and harbored IRF and STAT binding sites. Furthermore, we identified 14 common sequence variants in age-increasing peaks with predicted regulatory function, including several associated with respiratory traits andTMPRSS2expression. Our findings reveal a plausible contributor to why children are more resistant to COVID-19 and provide an epigenomic basis for transferring this resistance to older populations.
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- 2020
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45. A cell atlas of chromatin accessibility across 25 adult human tissues
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Zhang, Kai, primary, Hocker, James D., additional, Miller, Michael, additional, Hou, Xiaomeng, additional, Chiou, Joshua, additional, Poirion, Olivier B., additional, Qiu, Yunjiang, additional, Li, Yang E., additional, Gaulton, Kyle J., additional, Wang, Allen, additional, Preissl, Sebastian, additional, and Ren, Bing, additional
- Published
- 2021
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46. Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development
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Geusz, Ryan J, primary, Wang, Allen, additional, Chiou, Joshua, additional, Lancman, Joseph J, additional, Wetton, Nichole, additional, Kefalopoulou, Samy, additional, Wang, Jinzhao, additional, Qiu, Yunjiang, additional, Yan, Jian, additional, Aylward, Anthony, additional, Ren, Bing, additional, Dong, P Duc Si, additional, Gaulton, Kyle J, additional, and Sander, Maike, additional
- Published
- 2021
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47. Author response: Pancreatic progenitor epigenome maps prioritize type 2 diabetes risk genes with roles in development
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Geusz, Ryan J, primary, Wang, Allen, additional, Chiou, Joshua, additional, Lancman, Joseph J, additional, Wetton, Nichole, additional, Kefalopoulou, Samy, additional, Wang, Jinzhao, additional, Qiu, Yunjiang, additional, Yan, Jian, additional, Aylward, Anthony, additional, Ren, Bing, additional, Dong, P Duc Si, additional, Gaulton, Kyle J, additional, and Sander, Maike, additional
- Published
- 2021
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48. Large-scale genetic association and single cell accessible chromatin mapping defines cell type-specific mechanisms of type 1 diabetes risk
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Chiou, Joshua, primary, Geusz, Ryan J, additional, Okino, Mei-Lin, additional, Han, Jee Yun, additional, Miller, Michael, additional, Benaglio, Paola, additional, Huang, Serina, additional, Korgaonkar, Katha, additional, Heller, Sandra, additional, Kleger, Alexander, additional, Preissl, Sebastian, additional, Gorkin, David U, additional, Sander, Maike, additional, and Gaulton, Kyle J, additional
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- 2021
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49. Mapping genetic effects on cell type-specific chromatin accessibility and annotating complex trait variants using single nucleus ATAC-seq
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Benaglio, Paola, primary, Newsome, Jacklyn, additional, Han, Jee Yun, additional, Chiou, Joshua, additional, Aylward, Anthony, additional, Corban, Sierra, additional, Okino, Mei-Lin, additional, Kaur, Jaspreet, additional, Gorkin, David U, additional, and Gaulton, Kyle J, additional
- Published
- 2020
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50. Cardiac Cell Type-Specific Gene Regulatory Programs and Disease Risk Association
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Hocker, James D., primary, Poirion, Olivier B., additional, Zhu, Fugui, additional, Buchanan, Justin, additional, Zhang, Kai, additional, Chiou, Joshua, additional, Wang, Tsui-Min, additional, Hou, Xiaomeng, additional, Li, Yang E., additional, Zhang, Yanxiao, additional, Farah, Elie N., additional, Wang, Allen, additional, McCulloch, Andrew D., additional, Gaulton, Kyle J., additional, Ren, Bing, additional, Chi, Neil C., additional, and Preissl, Sebastian, additional
- Published
- 2020
- Full Text
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