المؤلفون: Zhang, Martin Jinye, Hou, Kangcheng, Dey, Kushal K, Sakaue, Saori, Jagadeesh, Karthik A, Weinand, Kathryn, Taychameekiatchai, Aris, Rao, Poorvi, Pisco, Angela Oliveira, Zou, James, Wang, Bruce, Gandal, Michael, Raychaudhuri, Soumya, Pasaniuc, Bogdan, Price, Alkes L

المصدر: Nature Genetics. 54(10)

مصطلحات موضوعية: Human Genome, Genetics, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Gene Expression Profiling, Genome-Wide Association Study, Multifactorial Inheritance, RNA-Seq, Single-Cell Analysis, Triglycerides, Biological Sciences, Medical and Health Sciences, Developmental Biology

الوصف: Single-cell RNA sequencing (scRNA-seq) provides unique insights into the pathology and cellular origin of disease. We introduce single-cell disease relevance score (scDRS), an approach that links scRNA-seq with polygenic disease risk at single-cell resolution, independent of annotated cell types. scDRS identifies cells exhibiting excess expression across disease-associated genes implicated by genome-wide association studies (GWASs). We applied scDRS to 74 diseases/traits and 1.3 million single-cell gene-expression profiles across 31 tissues/organs. Cell-type-level results broadly recapitulated known cell-type-disease associations. Individual-cell-level results identified subpopulations of disease-associated cells not captured by existing cell-type labels, including T cell subpopulations associated with inflammatory bowel disease, partially characterized by their effector-like states; neuron subpopulations associated with schizophrenia, partially characterized by their spatial locations; and hepatocyte subpopulations associated with triglyceride levels, partially characterized by their higher ploidy levels. Genes whose expression was correlated with the scDRS score across cells (reflecting coexpression with GWAS disease-associated genes) were strongly enriched for gold-standard drug target and Mendelian disease genes.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/2n72q9f0Test

المؤلفون: Gazal, Steven, Weissbrod, Omer, Hormozdiari, Farhad, Dey, Kushal K, Nasser, Joseph, Jagadeesh, Karthik A, Weiner, Daniel J, Shi, Huwenbo, Fulco, Charles P, O’Connor, Luke J, Pasaniuc, Bogdan, Engreitz, Jesse M, Price, Alkes L

المصدر: Nature Genetics. 54(6)

مصطلحات موضوعية: Biological Sciences, Genetics, Human Genome, Good Health and Well Being, Genome-Wide Association Study, Phenotype, Polymorphism, Single Nucleotide, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology

الوصف: Disease-associated single-nucleotide polymorphisms (SNPs) generally do not implicate target genes, as most disease SNPs are regulatory. Many SNP-to-gene (S2G) linking strategies have been developed to link regulatory SNPs to the genes that they regulate in cis. Here, we developed a heritability-based framework for evaluating and combining different S2G strategies to optimize their informativeness for common disease risk. Our optimal combined S2G strategy (cS2G) included seven constituent S2G strategies and achieved a precision of 0.75 and a recall of 0.33, more than doubling the recall of any individual strategy. We applied cS2G to fine-mapping results for 49 UK Biobank diseases/traits to predict 5,095 causal SNP-gene-disease triplets (with S2G-derived functional interpretation) with high confidence. We further applied cS2G to provide an empirical assessment of disease omnigenicity; we determined that the top 1% of genes explained roughly half of the SNP heritability linked to all genes and that gene-level architectures vary with variant allele frequency.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/0z17597sTest

المؤلفون: Kim, Samuel S., Truong, Buu, Jagadeesh, Karthik, Dey, Kushal K., Shen, Amber Z., Raychaudhuri, Soumya, Kellis, Manolis, Price, Alkes L.

المصدر: Nature Communications ; volume 15, issue 1 ; ISSN 2041-1723

مصطلحات موضوعية: General Physics and Astronomy, General Biochemistry, Genetics and Molecular Biology, General Chemistry, Multidisciplinary

الوصف: Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

الإتاحة: https://doi.org/10.1038/s41467-024-44742-0Test
https://www.nature.com/articles/s41467-024-44742-0.pdfTest
https://www.nature.com/articles/s41467-024-44742-0Test

المؤلفون: Muus, Christoph, Luecken, Malte D., Eraslan, Gokcen, Sikkema, Lisa, Waghray, Avinash, Heimberg, Graham, Kobayashi, Yoshihiko, Vaishnav, Eeshit Dhaval, Subramanian, Ayshwarya, Smillie, Christopher, Jagadeesh, Karthik A., Duong, Elizabeth Thu, Fiskin, Evgenij, Triglia, Elena Torlai, Ansari, Meshal, Cai, Peiwen, Lin, Brian, Buchanan, Justin, Chen, Sijia, Shu, Jian, Haber, Adam L., Chung, Hattie, Montoro, Daniel T., Adams, Taylor, Aliee, Hananeh, Allon, Samuel J., Andrusivova, Zaneta, Angelidis, Ilias, Ashenberg, Orr, Bassler, Kevin, Becavin, Christophe, Benhar, Inbal, Bergenstrahle, Joseph, Bergenstrahle, Ludvig, Bolt, Liam, Braun, Emelie, Bui, Linh T., Callori, Steven, Chaffin, Mark, Chichelnitskiy, Evgeny, Chiou, Joshua, Conlon, Thomas M., Cuoco, Michael S., Cuomo, Anna S. E., Deprez, Marie, Duclos, Grant, Fine, Denise, Fischer, David S., Ghazanfar, Shila, Gillich, Astrid, Giotti, Bruno, Gould, Joshua, Guo, Minzhe, Gutierrez, Austin J., Habermann, Arun C., Harvey, Tyler, He, Peng, Hou, Xiaomeng, Hu, Lijuan, Hu, Yan, Jaiswal, Alok, Ji, Lu, Jiang, Peiyong, Kapellos, Theodoros S., Kuo, Christin S., Larsson, Ludvig, Leney-Greene, Michael A., Lim, Kyungtae, Litvinukova, Monika, Ludwig, Leif S., Lukassen, Soeren, Luo, Wendy, Maatz, Henrike, Madissoon, Elo, Mamanova, Lira, Manakongtreecheep, Kasidet, Leroy, Sylvie, Mayr, Christoph H., Mbano, Ian M., McAdams, Alexi M., Nabhan, Ahmad N., Nyquist, Sarah K., Penland, Lolita, Poirion, Olivier B., Poli, Sergio, Qi, CanCan, Queen, Rachel, Reichart, Daniel, Rosas, Ivan, Schupp, Jonas C., Shea, Conor, Shi, Xingyi, Sinha, Rahul, Sit, Rene, Slowikowski, Kamil, Slyper, Michal, Smith, Neal P., Sountoulidis, Alex, Strunz, Maximilian, Sullivan, Travis B., Sun, Dawei, Talavera-Lopez, Carlos, Tan, Peng, Tantivit, Jessica, Travaglini, Kyle J., Tucker, Nathan R., Vernon, Katherine A., Wadsworth, Marc H., Waldman, Julia, Wang, Xiuting, Xu, Ke, Yan, Wenjun, Zhao, William, Ziegler, Carly G. K.

المصدر: Nature Medicine. 27(3):546-559

الوصف: 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. An integrated analysis of over 100 single-cell and single-nucleus transcriptomics studies illustrates severe acute respiratory syndrome coronavirus 2 viral entry gene coexpression patterns across different human tissues, and shows association of age, smoking status and sex with viral entry gene expression in respiratory cell populations.

وصف الملف: print

الوصول الحر: https://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-192186Test
https://doi.org/10.1038/s41591-020-01227-zTest

المؤلفون: Birgmeier, Johannes, Haeussler, Maximilian, Deisseroth, Cole A, Steinberg, Ethan H, Jagadeesh, Karthik A, Ratner, Alexander J, Guturu, Harendra, Wenger, Aaron M, Diekhans, Mark E, Stenson, Peter D, Cooper, David N, Ré, Christopher, Beggs, Alan H, Bernstein, Jonathan A, Bejerano, Gill

المصدر: Science Translational Medicine. 12(544)

مصطلحات موضوعية: Biomedical and Clinical Sciences, Clinical Sciences, Rare Diseases, Genetics, Detection, screening and diagnosis, 4.1 Discovery and preclinical testing of markers and technologies, Child, Exome, Genotype, Humans, Phenotype, Probability, Retrospective Studies, Biological Sciences, Medical and Health Sciences, Medical biotechnology, Biomedical engineering

الوصف: The diagnosis of Mendelian disorders requires labor-intensive literature research. Trained clinicians can spend hours looking for the right publication(s) supporting a single gene that best explains a patient's disease. AMELIE (Automatic Mendelian Literature Evaluation) greatly accelerates this process. AMELIE parses all 29 million PubMed abstracts and downloads and further parses hundreds of thousands of full-text articles in search of information supporting the causality and associated phenotypes of most published genetic variants. AMELIE then prioritizes patient candidate variants for their likelihood of explaining any patient's given set of phenotypes. Diagnosis of singleton patients (without relatives' exomes) is the most time-consuming scenario, and AMELIE ranked the causative gene at the very top for 66% of 215 diagnosed singleton Mendelian patients from the Deciphering Developmental Disorders project. Evaluating only the top 11 AMELIE-scored genes of 127 (median) candidate genes per patient resulted in a rapid diagnosis in more than 90% of cases. AMELIE-based evaluation of all cases was 3 to 19 times more efficient than hand-curated database-based approaches. We replicated these results on a retrospective cohort of clinical cases from Stanford Children's Health and the Manton Center for Orphan Disease Research. An analysis web portal with our most recent update, programmatic interface, and code is available at AMELIE.stanford.edu.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/4hv9h8vvTest

المؤلفون: Birgmeier, Johannes, Deisseroth, Cole A, Hayward, Laura E, Galhardo, Luisa MT, Tierno, Andrew P, Jagadeesh, Karthik A, Stenson, Peter D, Cooper, David N, Bernstein, Jonathan A, Haeussler, Maximilian, Bejerano, Gill

المصدر: Genetics in Medicine. 22(2)

مصطلحات موضوعية: Biological Sciences, Bioinformatics and Computational Biology, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Data Management, Databases, Factual, Databases, Genetic, Electronic Data Processing, Genomics, Humans, Information Storage and Retrieval, Natural Language Processing, PubMed, Publications, automatic variant retrieval, machine learning, natural language processing, full-text extraction, variants database, Clinical Sciences, Genetics & Heredity

الوصف: PurposeBoth monogenic pathogenic variant cataloging and clinical patient diagnosis start with variant-level evidence retrieval followed by expert evidence integration in search of diagnostic variants and genes. Here, we try to accelerate pathogenic variant evidence retrieval by an automatic approach.MethodsAutomatic VAriant evidence DAtabase (AVADA) is a novel machine learning tool that uses natural language processing to automatically identify pathogenic genetic variant evidence in full-text primary literature about monogenic disease and convert it to genomic coordinates.ResultsAVADA automatically retrieved almost 60% of likely disease-causing variants deposited in the Human Gene Mutation Database (HGMD), a 4.4-fold improvement over the current best open source automated variant extractor. AVADA contains over 60,000 likely disease-causing variants that are in HGMD but not in ClinVar. AVADA also highlights the challenges of automated variant mapping and pathogenicity curation. However, when combined with manual validation, on 245 diagnosed patients, AVADA provides valuable evidence for an additional 18 diagnostic variants, on top of ClinVar's 21, versus only 2 using the best current automated approach.ConclusionAVADA advances automated retrieval of pathogenic monogenic variant evidence from full-text literature. Far from perfect, but much faster than PubMed/Google Scholar search, careful curation of AVADA-retrieved evidence can aid both database curation and patient diagnosis.

وصف الملف: application/pdf

الوصول الحر: https://escholarship.org/uc/item/03x3x405Test

المؤلفون: Yuan, Feng, Gasser, Grace N., Lemire, Evan, Montoro, Daniel T., Jagadeesh, Karthik, Zhang, Yan, Duan, Yifan, Levlev, Vitaly, Wells, Kristen L., Rotti, Pavana G., Shahin, Weam, Winter, Michael, Rosen, Bradley H., Evans, Idil, Cai, Qian, Yu, Miao, Walsh, Susan A., Acevedo, Michael R., Pandya, Darpan N., Akurathi, Vamsidhar, Dick, David W., Wadas, Thaddeus J., Joo, Nam Soo, Wine, Jeffrey J., Birket, Susan, Fernandez, Courtney M., Leung, Hui Min, Tearney, Guillermo J., Verkman, Alan S., Haggie, Peter M., Scott, Kathleen, Bartels, Douglas, Meyerholz, David K., Rowe, Steven M., Liu, Xiaoming, Yan, Ziying, Haber, Adam L., Sun, Xingshen, Engelhardt, John F.

المساهمون: Medicine, School of Medicine

المصدر: PMC

مصطلحات موضوعية: Mechanisms of disease, Stem-cell differentiation, Sequence annotation, Genetic engineering, Next-generation sequencing

الوصف: Speciation leads to adaptive changes in organ cellular physiology and creates challenges for studying rare cell-type functions that diverge between humans and mice. Rare cystic fibrosis transmembrane conductance regulator (CFTR)-rich pulmonary ionocytes exist throughout the cartilaginous airways of humans1,2, but limited presence and divergent biology in the proximal trachea of mice has prevented the use of traditional transgenic models to elucidate ionocyte functions in the airway. Here we describe the creation and use of conditional genetic ferret models to dissect pulmonary ionocyte biology and function by enabling ionocyte lineage tracing (FOXI1-CreERT2::ROSA-TG), ionocyte ablation (FOXI1-KO) and ionocyte-specific deletion of CFTR (FOXI1-CreERT2::CFTRL/L). By comparing these models with cystic fibrosis ferrets3,4, we demonstrate that ionocytes control airway surface liquid absorption, secretion, pH and mucus viscosity-leading to reduced airway surface liquid volume and impaired mucociliary clearance in cystic fibrosis, FOXI1-KO and FOXI1-CreERT2::CFTRL/L ferrets. These processes are regulated by CFTR-dependent ionocyte transport of Cl- and HCO3-. Single-cell transcriptomics and in vivo lineage tracing revealed three subtypes of pulmonary ionocytes and a FOXI1-lineage common rare cell progenitor for ionocytes, tuft cells and neuroendocrine cells during airway development. Thus, rare pulmonary ionocytes perform critical CFTR-dependent functions in the proximal airway that are hallmark features of cystic fibrosis airway disease. These studies provide a road map for using conditional genetics in the first non-rodent mammal to address gene function, cell biology and disease processes that have greater evolutionary conservation between humans and ferrets.

وصف الملف: application/pdf

العلاقة: Nature; Yuan F, Gasser GN, Lemire E, et al. Transgenic ferret models define pulmonary ionocyte diversity and function. Nature. 2023;621(7980):857-867. doi:10.1038/s41586-023-06549-9; https://hdl.handle.net/1805/39186Test

الإتاحة: https://doi.org/10.1038/s41586-023-06549-9Test
https://hdl.handle.net/1805/39186Test

المؤلفون: Sakaue, Saori, Weinand, Kathryn, Isaac, Shakson, Dey, Kushal K., Jagadeesh, Karthik, Kanai, Masahiro, Watts, Gerald F. M., Zhu, Zhu, Albrecht, Jennifer, Anolik, Jennifer H., Apruzzese, William, Banda, Nirmal, Barnas, Jennifer L., Bathon, Joan M., Ben-Artzi, Ami, Boyce, Brendan F., Boyle, David L., Bridges, S. Louis, Bykerk, Vivian P., Campbell, Debbie, Carr, Hayley L., Ceponis, Arnold, Chicoine, Adam, Cordle, Andrew, Curtis, Michelle, Deane, Kevin D., DiCarlo, Edward, Dunn, Patrick, Filer, Andrew, Firestein, Gary S., Forbess, Lindsy, Geraldino-Pardilla, Laura, Goodman, Susan M., Gravallese, Ellen M., Gregersen, Peter K., Guthridge, Joel M., Gutierrez-Arcelus, Maria, Gurajala, Siddarth, Michael Holers, V., Horowitz, Diane, Hughes, Laura B., Ishigaki, Kazuyoshi, Ivashkiv, Lionel B., James, Judith A., Jonsson, Anna Helena, Kang, Joyce B., Keras, Gregory, Korsunsky, Ilya, Lakhanpal, Amit, Lederer, James A., Li, Zhihan J., Li, Yuhong, Liao, Katherine P., Mandelin, Arthur M., Mantel, Ian, Maybury, Mark, Mears, Joseph, Meednu, Nida, Millard, Nghia, Moreland, Larry W., Nathan, Aparna, Nerviani, Alessandra, Orange, Dana E., Perlman, Harris, Pitzalis, Costantino, Rangel-Moreno, Javier, Rao, Deepak A., Raza, Karim, Reshef, Yakir, Ritchlin, Christopher, Rivellese, Felice, Robinson, William H., Rumker, Laurie, Sahbudin, Ilfita, Seifert, Jennifer A., Slowikowski, Kamil, Smith, Melanie H., Tabechian, Darren, Scheel-Toellner, Dagmar, Utz, Paul J., Weisenfeld, Dana, Weisman, Michael H., Xiao, Qian, Zhang, Fan, Brenner, Michael B., McDavid, Andrew, Donlin, Laura T., Wei, Kevin, Price, Alkes L., Raychaudhuri, Soumya

الوصف: AbstractTranslating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. We developed a new non-parametric statistical method, SCENT (Single-Cell ENhancer Target gene mapping) which models association between enhancer chromatin accessibility and gene expression in single-cell multimodal RNA-seq and ATAC-seq data. We applied SCENT to 9 multimodal datasets including > 120,000 single cells and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in eQTLs and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases. In addition, we were able to link somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining non-coding variant function. ; Accepted Manuscript

وصف الملف: application/vnd.openxmlformats-officedocument.wordprocessingml.document

العلاقة: Nature Genetics; Nat Genet; Sakaue, Saori, Kathryn Weinand, Shakson Isaac, Kushal K. Dey, Karthik Jagadeesh, Masahiro Kanai, Gerald F. M. Watts et al. "Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles." Nat Genet 56, no. 4 (2024): 615-626. DOI:10.1038/s41588-024-01682-1; https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37379190Test

الإتاحة: https://doi.org/10.1038/s41588-024-01682-1Test
https://nrs.harvard.edu/URN-3:HUL.INSTREPOS:37379190Test

المؤلفون: Zhou, Wei, Bi, Wenjian, Zhao, Zhangchen, Dey, Kushal K., Jagadeesh, Karthik A., Karczewski, Konrad J., Daly, Mark J., Neale, Benjamin M., Lee, Seunggeun

المساهمون: National Research Foundation of Korea, U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute, Foundation for the National Institutes of Health

المصدر: Nature Genetics ; volume 54, issue 11, page 1755-1755 ; ISSN 1061-4036 1546-1718

مصطلحات موضوعية: Genetics

الإتاحة: https://doi.org/10.1038/s41588-022-01220-xTest
https://www.nature.com/articles/s41588-022-01220-x.pdfTest
https://www.nature.com/articles/s41588-022-01220-xTest

المؤلفون: Zhou, Wei, Bi, Wenjian, Zhao, Zhangchen, Dey, Kushal K., Jagadeesh, Karthik A., Karczewski, Konrad J., Daly, Mark J., Neale, Benjamin M., Lee, Seunggeun

المساهمون: National Research Foundation of Korea, U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute, Foundation for the National Institutes of Health

المصدر: Nature Genetics ; volume 54, issue 10, page 1466-1469 ; ISSN 1061-4036 1546-1718

مصطلحات موضوعية: Genetics

الوصف: Several biobanks, including UK Biobank (UKBB), are generating large-scale sequencing data. An existing method, SAIGE-GENE, performs well when testing variants with minor allele frequency (MAF) ≤ 1%, but inflation is observed in variance component set-based tests when restricting to variants with MAF ≤ 0.1% or 0.01%. Here, we propose SAIGE-GENE+ with greatly improved type I error control and computational efficiency to facilitate rare variant tests in large-scale data. We further show that incorporating multiple MAF cutoffs and functional annotations can improve power and thus uncover new gene–phenotype associations. In the analysis of UKBB whole exome sequencing data for 30 quantitative and 141 binary traits, SAIGE-GENE+ identified 551 gene–phenotype associations.

الإتاحة: https://doi.org/10.1038/s41588-022-01178-wTest
https://www.nature.com/articles/s41588-022-01178-w.pdfTest
https://www.nature.com/articles/s41588-022-01178-wTest