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Jin W, Xia Y, Nizomov J, Liu Y, Li Z, Lu Q, Chen L. MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants. Bioinformatics 2024; 40:btae578. [PMID: 39325859 PMCID: PMC11464417 DOI: 10.1093/bioinformatics/btae578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 08/29/2024] [Accepted: 09/23/2024] [Indexed: 09/28/2024] Open
Abstract
SUMMARY Massively parallel reporter assay (MPRA) is an important technology for evaluating the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs, and genomic features, totaling 242 818 variants tested more than 30 cell lines and 30 human diseases or traits. MPRAVarDB enables users to query MPRA variants by genomic region, disease and cell line, or any combination of these parameters. Notably, MPRAVarDB offers a suite of pretrained machine-learning models tailored to the specific disease and cell line, facilitating the prediction of regulatory variants. The user-friendly interface allows users to receive query and prediction results with just a few clicks. AVAILABILITY AND IMPLEMENTATION https://mpravardb.rc.ufl.edu.
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Affiliation(s)
- Weijia Jin
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
| | - Yi Xia
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
| | - Javlon Nizomov
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, United States
| | - Zhigang Li
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
| | - Qing Lu
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
| | - Li Chen
- Department of Biostatistics, University of Florida, Gainesville, FL 32603, United States
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2
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Long E, Yin J, Shin JH, Li Y, Li B, Kane A, Patel H, Sun X, Wang C, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi MT, Rothman N, Lan Q, Chang YS, Yu F, Amos CI, Shi J, Lee JG, Kim EY, Choi J. Context-aware single-cell multiomics approach identifies cell-type-specific lung cancer susceptibility genes. Nat Commun 2024; 15:7995. [PMID: 39266564 PMCID: PMC11392933 DOI: 10.1038/s41467-024-52356-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 09/03/2024] [Indexed: 09/14/2024] Open
Abstract
Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.
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Affiliation(s)
- Erping Long
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Ju Hye Shin
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yuyan Li
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bolun Li
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Alexander Kane
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Xinti Sun
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Cong Wang
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Thong Luong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jun Xia
- Department of Biomedical Sciences, Creighton University, Omaha, NE, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Yoon Soo Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Fulong Yu
- Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jin Gu Lee
- Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Eun Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
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Lu F, Wang L, Ma X, Li Y. A Mendelian randomization study of genetic liability to cutaneous melanoma and sunburns. Front Oncol 2024; 14:1393833. [PMID: 39281383 PMCID: PMC11392754 DOI: 10.3389/fonc.2024.1393833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Accepted: 08/12/2024] [Indexed: 09/18/2024] Open
Abstract
Background Some studies have reported that sunburns and cutaneous melanoma (CM) risk is increasing, but a clear causal link has yet to be established. Methods This current study conducted a two-sample Mendelian randomization (MR) approach to clarify the association and causality between sunburn history and CM using large-scale genome-wide association study data. Results The inverse-variance weighted method result showed that sunburn might be associated with the risk of CM increasing (p = 2.21 × 10-23, OR = 1.034, 95% CI= 1.027-1.041), causally. The MR-Egger regression, weighted median method, simple mode method, and weighted mode method results showed similar results. Conclusion This study offers evidence of sunburn history and increased risk of CM, and it shows that there might be common genetic basics regarding sunburns and CM susceptibility in Caucasian, European, or British ethnic groups.
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Affiliation(s)
- Fengmin Lu
- Department of Dermatology, Clinical Medical Research Center of Dermatology and Venereal Disease in Hebei Province, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Ling Wang
- Department of Dermatology, Clinical Medical Research Center of Dermatology and Venereal Disease in Hebei Province, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Xixing Ma
- Department of Dermatology, Clinical Medical Research Center of Dermatology and Venereal Disease in Hebei Province, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yanling Li
- Department of Dermatology, Clinical Medical Research Center of Dermatology and Venereal Disease in Hebei Province, The Second Hospital of Hebei Medical University, Shijiazhuang, China
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Xu L, Liu Y. Identification, Design, and Application of Noncoding Cis-Regulatory Elements. Biomolecules 2024; 14:945. [PMID: 39199333 PMCID: PMC11352686 DOI: 10.3390/biom14080945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 07/25/2024] [Accepted: 07/30/2024] [Indexed: 09/01/2024] Open
Abstract
Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.
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Affiliation(s)
- Lingna Xu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China;
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China;
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan 528226, China
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5
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Long E, Patel H, Golden A, Antony M, Yin J, Funderburk K, Feng J, Song L, Hoskins JW, Amundadottir LT, Hung RJ, Amos CI, Shi J, Rothman N, Lan Q, Choi J. High-throughput characterization of functional variants highlights heterogeneity and polygenicity underlying lung cancer susceptibility. Am J Hum Genet 2024; 111:1405-1419. [PMID: 38906146 PMCID: PMC11267514 DOI: 10.1016/j.ajhg.2024.05.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 05/23/2024] [Accepted: 05/23/2024] [Indexed: 06/23/2024] Open
Abstract
Genome-wide association studies (GWASs) have identified numerous lung cancer risk-associated loci. However, decoding molecular mechanisms of these associations is challenging since most of these genetic variants are non-protein-coding with unknown function. Here, we implemented massively parallel reporter assays (MPRAs) to simultaneously measure the allelic transcriptional activity of risk-associated variants. We tested 2,245 variants at 42 loci from 3 recent GWASs in East Asian and European populations in the context of two major lung cancer histological types and exposure to benzo(a)pyrene. This MPRA approach identified one or more variants (median 11 variants) with significant effects on transcriptional activity at 88% of GWAS loci. Multimodal integration of lung-specific epigenomic data demonstrated that 63% of the loci harbored multiple potentially functional variants in linkage disequilibrium. While 22% of the significant variants showed allelic effects in both A549 (adenocarcinoma) and H520 (squamous cell carcinoma) cell lines, a subset of the functional variants displayed a significant cell-type interaction. Transcription factor analyses nominated potential regulators of the functional variants, including those with cell-type-specific expression and those predicted to bind multiple potentially functional variants across the GWAS loci. Linking functional variants to target genes based on four complementary approaches identified candidate susceptibility genes, including those affecting lung cancer cell growth. CRISPR interference of the top functional variant at 20q13.33 validated variant-to-gene connections, including RTEL1, SOX18, and ARFRP1. Our data provide a comprehensive functional analysis of lung cancer GWAS loci and help elucidate the molecular basis of heterogeneity and polygenicity underlying lung cancer susceptibility.
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Affiliation(s)
- Erping Long
- State Key Laboratory of Respiratory Health and Multimorbidity, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Alyxandra Golden
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Michelle Antony
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Karen Funderburk
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - James Feng
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Lei Song
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jason W Hoskins
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Laufey T Amundadottir
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
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6
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Coetzee SG, Hazelett DJ. MotifbreakR v2: extended capability and database integration. ARXIV 2024:arXiv:2407.03441v1. [PMID: 39010878 PMCID: PMC11247919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
MotifbreakR is a software tool that scans genetic variants against position weight matrices of transcription factors (TF) to determine the potential for the disruption of TF binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to operate across a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single nucleotide variants (common and rare SNVs) on potential TF binding sites, in motifbreakR v2, we have updated the functionality. New features include the ability to query other types of more complex genetic variants, such as short insertions and deletions (indels). This function allows modeling a more extensive array of variants that may have more significant effects on TF binding. Additionally, while TF binding is based partly on sequence preference, predictions of TF binding based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR implements querying the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we have implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.
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Affiliation(s)
- Simon G Coetzee
- Department of Computational Biomedicine at Cedars-Sinai Medical Center
| | - Dennis J Hazelett
- Department of Computational Biomedicine at Cedars-Sinai Medical Center
- Cancer Prevention and Control - Samuel Oschin Cancer Center, Cedars-Sinai
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7
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Jin W, Xia Y, Thela SR, Liu Y, Chen L. In silico generation and augmentation of regulatory variants from massively parallel reporter assay using conditional variational autoencoder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.25.600715. [PMID: 38979263 PMCID: PMC11230389 DOI: 10.1101/2024.06.25.600715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Predicting the functional consequences of genetic variants in non-coding regions is a challenging problem. Massively parallel reporter assays (MPRAs), which are an in vitro high-throughput method, can simultaneously test thousands of variants by evaluating the existence of allele specific regulatory activity. Nevertheless, the identified labelled variants by MPRAs, which shows differential allelic regulatory effects on the gene expression are usually limited to the scale of hundreds, limiting their potential to be used as the training set for achieving a robust genome-wide prediction. To address the limitation, we propose a deep generative model, MpraVAE, to in silico generate and augment the training sample size of labelled variants. By benchmarking on several MPRA datasets, we demonstrate that MpraVAE significantly improves the prediction performance for MPRA regulatory variants compared to the baseline method, conventional data augmentation approaches as well as existing variant scoring methods. Taking autoimmune diseases as one example, we apply MpraVAE to perform a genome-wide prediction of regulatory variants and find that predicted regulatory variants are more enriched than background variants in enhancers, active histone marks, open chromatin regions in immune-related cell types, and chromatin states associated with promoter, enhancer activity and binding sites of cMyC and Pol II that regulate gene expression. Importantly, predicted regulatory variants are found to link immune-related genes by leveraging chromatin loop and accessible chromatin, demonstrating the importance of MpraVAE in genetic and gene discovery for complex traits.
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Affiliation(s)
- Weijia Jin
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603, USA
| | - Yi Xia
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603, USA
| | - Sai Ritesh Thela
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603, USA
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Li Chen
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603, USA
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8
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Siraj L, Castro RI, Dewey H, Kales S, Nguyen TTL, Kanai M, Berenzy D, Mouri K, Wang QS, McCaw ZR, Gosai SJ, Aguet F, Cui R, Vockley CM, Lareau CA, Okada Y, Gusev A, Jones TR, Lander ES, Sabeti PC, Finucane HK, Reilly SK, Ulirsch JC, Tewhey R. Functional dissection of complex and molecular trait variants at single nucleotide resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.05.592437. [PMID: 38766054 PMCID: PMC11100724 DOI: 10.1101/2024.05.05.592437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.
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Affiliation(s)
- Layla Siraj
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Biophysics, Harvard Graduate School of Arts and Sciences, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology MD/PhD Program, Harvard Medical School, Boston, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | | | | | | | | | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Qingbo S. Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | | | - Sager J. Gosai
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - François Aguet
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Ran Cui
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Caleb A. Lareau
- Program in Computational and Systems Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Alexander Gusev
- Harvard Medical School and Dana-Farber Cancer Institute, Boston, MA, USA
| | - Thouis R. Jones
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric S. Lander
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Pardis C. Sabeti
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Hilary K. Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Jacob C. Ulirsch
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
- Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
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9
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Bhattarai KR, Mobley RJ, Barnett KR, Ferguson DC, Hansen BS, Diedrich JD, Bergeron BP, Yoshimura S, Yang W, Crews KR, Manring CS, Jabbour E, Paietta E, Litzow MR, Kornblau SM, Stock W, Inaba H, Jeha S, Pui CH, Cheng C, Pruett-Miller SM, Relling MV, Yang JJ, Evans WE, Savic D. Investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment. Nat Commun 2024; 15:3681. [PMID: 38693155 PMCID: PMC11063049 DOI: 10.1038/s41467-024-48124-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 04/18/2024] [Indexed: 05/03/2024] Open
Abstract
Defining genetic factors impacting chemotherapy failure can help to better predict response and identify drug resistance mechanisms. However, there is limited understanding of the contribution of inherited noncoding genetic variation on inter-individual differences in chemotherapy response in childhood acute lymphoblastic leukemia (ALL). Here we map inherited noncoding variants associated with treatment outcome and/or chemotherapeutic drug resistance to ALL cis-regulatory elements and investigate their gene regulatory potential and target gene connectivity using massively parallel reporter assays and three-dimensional chromatin looping assays, respectively. We identify 54 variants with transcriptional effects and high-confidence gene connectivity. Additionally, functional interrogation of the top variant, rs1247117, reveals changes in chromatin accessibility, PU.1 binding affinity and gene expression, and deletion of the genomic interval containing rs1247117 sensitizes cells to vincristine. Together, these data demonstrate that noncoding regulatory variants associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to antileukemic agents.
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Affiliation(s)
- Kashi Raj Bhattarai
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Robert J Mobley
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kelly R Barnett
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel C Ferguson
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Baranda S Hansen
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jonathan D Diedrich
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Brennan P Bergeron
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Satoshi Yoshimura
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Advanced Pediatric Medicine, Tohoku University School of Medicine, Tokyo, Japan
| | - Wenjian Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Kristine R Crews
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Christopher S Manring
- Alliance Hematologic Malignancy Biorepository; Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH, 43210, USA
| | - Elias Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Mark R Litzow
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN, 55905, USA
| | - Steven M Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Wendy Stock
- Comprehensive Cancer Center, University of Chicago Medicine, Chicago, IL, USA
| | - Hiroto Inaba
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Sima Jeha
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Ching-Hon Pui
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Cheng Cheng
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Shondra M Pruett-Miller
- Center for Advanced Genome Engineering, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Mary V Relling
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Jun J Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA
| | - William E Evans
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
| | - Daniel Savic
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA.
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN, 38163, USA.
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10
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Nizomov J, Jin W, Xia Y, Liu Y, Li Z, Chen L. MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587790. [PMID: 38617248 PMCID: PMC11014600 DOI: 10.1101/2024.04.02.587790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits. MPRAVarDB empowers the query of MPRA variants by genomic region, disease and cell line or by any combination of these query terms. Notably, MPRAVarDB offers a suite of pretrained machine learning models tailored to the specific disease and cell line, facilitating the genome-wide prediction of regulatory variants. MPRAVarDB is friendly to use, and users only need a few clicks to receive query and prediction results.
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Affiliation(s)
- Javlon Nizomov
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Weijia Jin
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Yi Xia
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Zhigang Li
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Li Chen
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
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11
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Shook MS, Lu X, Chen X, Parameswaran S, Edsall L, Trimarchi MP, Ernst K, Granitto M, Forney C, Donmez OA, Diouf AA, VonHandorf A, Rothenberg ME, Weirauch MT, Kottyan LC. Systematic identification of genotype-dependent enhancer variants in eosinophilic esophagitis. Am J Hum Genet 2024; 111:280-294. [PMID: 38183988 PMCID: PMC10870143 DOI: 10.1016/j.ajhg.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 12/01/2023] [Accepted: 12/05/2023] [Indexed: 01/08/2024] Open
Abstract
Eosinophilic esophagitis (EoE) is a rare atopic disorder associated with esophageal dysfunction, including difficulty swallowing, food impaction, and inflammation, that develops in a small subset of people with food allergies. Genome-wide association studies (GWASs) have identified 9 independent EoE risk loci reaching genome-wide significance (p < 5 × 10-8) and 27 additional loci of suggestive significance (5 × 10-8 < p < 1 × 10-5). In the current study, we perform linkage disequilibrium (LD) expansion of these loci to nominate a set of 531 variants that are potentially causal. To systematically interrogate the gene regulatory activity of these variants, we designed a massively parallel reporter assay (MPRA) containing the alleles of each variant within their genomic sequence context cloned into a GFP reporter library. Analysis of reporter gene expression in TE-7, HaCaT, and Jurkat cells revealed cell-type-specific gene regulation. We identify 32 allelic enhancer variants, representing 6 genome-wide significant EoE loci and 7 suggestive EoE loci, that regulate reporter gene expression in a genotype-dependent manner in at least one cellular context. By annotating these variants with expression quantitative trait loci (eQTL) and chromatin looping data in related tissues and cell types, we identify putative target genes affected by genetic variation in individuals with EoE. Transcription factor enrichment analyses reveal possible roles for cell-type-specific regulators, including GATA3. Our approach reduces the large set of EoE-associated variants to a set of 32 with allelic regulatory activity, providing functional insights into the effects of genetic variation in this disease.
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Affiliation(s)
- Molly S Shook
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Xiaoming Lu
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Xiaoting Chen
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Sreeja Parameswaran
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Lee Edsall
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Michael P Trimarchi
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Kevin Ernst
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Marissa Granitto
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Carmy Forney
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Omer A Donmez
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Arame A Diouf
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Andrew VonHandorf
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Marc E Rothenberg
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Matthew T Weirauch
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA; Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
| | - Leah C Kottyan
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45229, USA; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA.
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12
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Long E, Yin J, Shin JH, Li Y, Kane A, Patel H, Luong T, Xia J, Han Y, Byun J, Zhang T, Zhao W, Landi MT, Rothman N, Lan Q, Chang YS, Yu F, Amos C, Shi J, Lee JG, Kim EY, Choi J. Context-aware single-cell multiome approach identified cell-type specific lung cancer susceptibility genes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.25.559336. [PMID: 37808664 PMCID: PMC10557605 DOI: 10.1101/2023.09.25.559336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, the genetic mechanisms and target genes underlying these loci are largely unknown, as most risk-associated-variants might regulate gene expression in a context-specific manner. Here, we generated a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Accessible chromatin peak detection identified cell-type-specific candidate cis-regulatory elements (cCREs) from each lung cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs prioritized the variants for 68% of the GWAS loci, a subset of which was also supported by transcription factor abundance and footprinting. cCRE colocalization and single-cell based trait relevance score nominated epithelial and immune cells as the main cell groups contributing to lung cancer susceptibility. Notably, cCREs of rare proliferating epithelial cell types, such as AT2-proliferating (0.13%) and basal cells (1.8%), overlapped with CCVs, including those in TERT. A multi-level cCRE-gene linking system identified candidate susceptibility genes from 57% of lung cancer loci, including those not detected in tissue- or cell-line-based approaches. cCRE-gene linkage uncovered that adjacent genes expressed in different cell types are correlated with distinct subsets of coinherited CCVs, including JAML and MPZL3 at the 11q23.3 locus. Our data revealed the cell types and contexts where the lung cancer susceptibility genes are functional.
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Affiliation(s)
- Erping Long
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
- Current affiliation: Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinhu Yin
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ju Hye Shin
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Yuyan Li
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Alexander Kane
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Harsh Patel
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Thong Luong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jun Xia
- Department of Biomedical Sciences, Creighton University, Omaha, NE, USA
| | - Younghun Han
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jinyoung Byun
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Tongwu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wei Zhao
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Maria Teresa Landi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Yoon Soo Chang
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Fulong Yu
- Guangzhou National Laboratory, Guangzhou International Bio Island, Guangzhou, China
| | - Christopher Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jin Gu Lee
- Department of Thoracic and Cardiovascular Surgery, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Eun Young Kim
- Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jiyeon Choi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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13
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Bhattarai KR, Mobley RJ, Barnett KR, Ferguson DC, Hansen BS, Diedrich JD, Bergeron BP, Yang W, Crews KR, Manring CS, Jabbour E, Paietta E, Litzow MR, Kornblau SM, Stock W, Inaba H, Jeha S, Pui CH, Cheng C, Pruett-Miller SM, Relling MV, Yang JJ, Evans WE, Savic D. Functional investigation of inherited noncoding genetic variation impacting the pharmacogenomics of childhood acute lymphoblastic leukemia treatment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.10.23285762. [PMID: 36798219 PMCID: PMC9934807 DOI: 10.1101/2023.02.10.23285762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
Although acute lymphoblastic leukemia (ALL) is the most common childhood cancer, there is limited understanding of the contribution of inherited genetic variation on inter-individual differences in chemotherapy response. Defining genetic factors impacting therapy failure can help better predict response and identify drug resistance mechanisms. We therefore mapped inherited noncoding variants associated with chemotherapeutic drug resistance and/or treatment outcome to ALL cis-regulatory elements and investigated their gene regulatory potential and genomic connectivity using massively parallel reporter assays and promoter capture Hi-C, respectively. We identified 53 variants with reproducible allele-specific effects on transcription and high-confidence gene targets. Subsequent functional interrogation of the top variant (rs1247117) determined that it disrupted a PU.1 consensus motif and PU.1 binding affinity. Importantly, deletion of the genomic interval containing rs1247117 sensitized ALL cells to vincristine. Together, these data demonstrate that noncoding regulatory variation associated with diverse pharmacological traits harbor significant effects on allele-specific transcriptional activity and impact sensitivity to chemotherapeutic agents in ALL.
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Affiliation(s)
- Kashi Raj Bhattarai
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Robert J. Mobley
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Kelly R. Barnett
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Daniel C. Ferguson
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Baranda S. Hansen
- Center for Advanced Genome Engineering, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Jonathan D. Diedrich
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Brennan P. Bergeron
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Wenjian Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Kristine R. Crews
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Christopher S. Manring
- Alliance Hematologic Malignancy Biorepository; Clara D. Bloomfield Center for Leukemia Outcomes Research, Columbus, OH 43210, USA
| | - Elias Jabbour
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Mark R. Litzow
- Division of Hematology, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Steven M. Kornblau
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Wendy Stock
- Comprehensive Cancer Center, University of Chicago Medicine, Chicago, IL
| | - Hiroto Inaba
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN
| | - Sima Jeha
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN
| | - Ching-Hon Pui
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN
| | - Cheng Cheng
- Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, TN
| | - Shondra M. Pruett-Miller
- Center for Advanced Genome Engineering, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
- Department of Cell and Molecular Biology, St. Jude Children’s Research Hospital, Memphis, TN 38105, USA
| | - Mary V. Relling
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Jun J. Yang
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN
| | - William E. Evans
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
| | - Daniel Savic
- Hematological Malignancies Program, St. Jude Children's Research Hospital, Memphis, TN
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, TN
- Graduate School of Biomedical Sciences, St. Jude Children's Research Hospital, Memphis, TN
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, TN
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