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Fu T, Amoah K, Chan TW, Bahn JH, Lee JH, Terrazas S, Chong R, Kosuri S, Xiao X. Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes. Nat Commun 2024; 15:3335. [PMID: 38637555 PMCID: PMC11026479 DOI: 10.1038/s41467-024-46795-7] [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: 05/01/2023] [Accepted: 03/06/2024] [Indexed: 04/20/2024] Open
Abstract
Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.
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Affiliation(s)
- Ting Fu
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kofi Amoah
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tracey W Chan
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae Hoon Bahn
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae-Hyung Lee
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Life and Nanopharmaceutical Sciences & Oral Microbiology, School of Dentistry, Kyung Hee University, Seoul, South Korea
| | - Sari Terrazas
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Molecular Biology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sriram Kosuri
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Xinshu Xiao
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Molecular Biology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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2
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Rykova EY, Ershov NI, Degtyareva AO, Bryzgalov LO, Lushnikova EL. The Search for and Functional Analysis of Genetic Variants in microRNA-Binding Sites using Massively Parallel Reporter Assay. Bull Exp Biol Med 2024; 176:595-598. [PMID: 38724816 DOI: 10.1007/s10517-024-06074-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Indexed: 05/18/2024]
Abstract
A large-scale search for the genetic variants with a bias in the representation of alleles in transcriptome data (AE SNPs) and the binding sites in microRNA 3'-UTRs was performed and their functional significance was assessed using massively parallel reporter assay (MPRA). Of the 629,559 associated "SNP-gene" pairs (eQTLs) discovered in the human liver tissue according to the GTEx Analysis V8 data, 4394 polymorphic positions in the 3'-UTRs of the genes, which represent the eQTLs for these genes were selected. The TargetScanHuman 7.0 algorithm and PolymiRTS database were searched for the potential microRNA-binding sites. Of the predicted microRNA sites affected by eQTL-SNPs, we selected 51 sites with the best evidence of functionality according to Ago2-CLIP-seq, CLEAR-CLIP, and eCLIP-seq for RNA-binding proteins. For MPRA, a library of the plasmids carrying the main and alternative alleles for each AE SNP (in total, 102 constructs) was created. Allele-specific expression for 6 SNPs was detected by transfection of the HepG2 cell line with the constructed plasmid library and sequencing of target DNA and RNA sequences using the Illumina (MiSeq) platform.
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Affiliation(s)
- E Yu Rykova
- Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.
| | - N I Ershov
- Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A O Degtyareva
- Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - L O Bryzgalov
- Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E L Lushnikova
- Federal Research Center of Fundamental and Translational Medicine, Novosibirsk, Russia
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Chen AB, Yu X, Thapa KS, Gao H, Reiter JL, Xuei X, Tsai AP, Landreth GE, Lai D, Wang Y, Foroud TM, Tischfield JA, Edenberg HJ, Liu Y. Functional 3'-UTR Variants Identify Regulatory Mechanisms Impacting Alcohol Use Disorder and Related Traits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.31.578270. [PMID: 38370821 PMCID: PMC10871301 DOI: 10.1101/2024.01.31.578270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Although genome-wide association studies (GWAS) have identified loci associated with alcohol consumption and alcohol use disorder (AUD), they do not identify which variants are functional. To approach this, we evaluated the impact of variants in 3' untranslated regions (3'-UTRs) of genes in loci associated with substance use and neurological disorders using a massively parallel reporter assay (MPRA) in neuroblastoma and microglia cells. Functionally impactful variants explained a higher proportion of heritability of alcohol traits than non-functional variants. We identified genes whose 3'UTR activities are associated with AUD and alcohol consumption by combining variant effects from MPRA with GWAS results. We examined their effects by evaluating gene expression after CRISPR inhibition of neuronal cells and stratifying brain tissue samples by MPRA-derived 3'-UTR activity. A pathway analysis of differentially expressed genes identified inflammation response pathways. These analyses suggest that variation in response to inflammation contributes to the propensity to increase alcohol consumption.
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Affiliation(s)
- Andy B. Chen
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xuhong Yu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Kriti S. Thapa
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Hongyu Gao
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Jill L Reiter
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xiaoling Xuei
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Anatomy and Cell Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Dongbing Lai
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Yue Wang
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Tatiana M. Foroud
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | | | - Howard J. Edenberg
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Yunlong Liu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana
- Center for Medical Genomics, Indiana University School of Medicine, Indianapolis, Indiana
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4
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Gameiro‐Ros I, Popova D, Prytkova I, Pang ZP, Liu Y, Dick D, Bucholz KK, Agrawal A, Porjesz B, Goate AM, Xuei X, Kamarajan C, Tischfield JA, Edenberg HJ, Slesinger PA, Hart RP. 5. Collaborative Study on the Genetics of Alcoholism: Functional genomics. GENES, BRAIN, AND BEHAVIOR 2023; 22:e12855. [PMID: 37533187 PMCID: PMC10550792 DOI: 10.1111/gbb.12855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/17/2023] [Indexed: 08/04/2023]
Abstract
Alcohol Use Disorder is a complex genetic disorder, involving genetic, neural, and environmental factors, and their interactions. The Collaborative Study on the Genetics of Alcoholism (COGA) has been investigating these factors and identified putative alcohol use disorder risk genes through genome-wide association studies. In this review, we describe advances made by COGA in elucidating the functional changes induced by alcohol use disorder risk genes using multimodal approaches with human cell lines and brain tissue. These studies involve investigating gene regulation in lymphoblastoid cells from COGA participants and in post-mortem brain tissues. High throughput reporter assays are being used to identify single nucleotide polymorphisms in which alternate alleles differ in driving gene expression. Specific single nucleotide polymorphisms (both coding or noncoding) have been modeled using induced pluripotent stem cells derived from COGA participants to evaluate the effects of genetic variants on transcriptomics, neuronal excitability, synaptic physiology, and the response to ethanol in human neurons from individuals with and without alcohol use disorder. We provide a perspective on future studies, such as using polygenic risk scores and populations of induced pluripotent stem cell-derived neurons to identify signaling pathways related with responses to alcohol. Starting with genes or loci associated with alcohol use disorder, COGA has demonstrated that integration of multimodal data within COGA participants and functional studies can reveal mechanisms linking genomic variants with alcohol use disorder, and potential targets for future treatments.
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Affiliation(s)
- Isabel Gameiro‐Ros
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Dina Popova
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
| | - Iya Prytkova
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Zhiping P. Pang
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Child Health Institute of New Jersey and Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical SchoolRutgers UniversityNew BrunswickNew JerseyUSA
| | - Yunlong Liu
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Danielle Dick
- Rutgers Addiction Research Center, Robert Wood Johnson Medical SchoolRutgers UniversityPiscatawayNew JerseyUSA
| | - Kathleen K. Bucholz
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Arpana Agrawal
- Department of PsychiatryWashington University School of MedicineSt. LouisMissouriUSA
| | - Bernice Porjesz
- Department of Psychiatry and Behavioral SciencesSUNY Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | - Alison M. Goate
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Xiaoling Xuei
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Chella Kamarajan
- Department of Psychiatry and Behavioral SciencesSUNY Downstate Health Sciences UniversityBrooklynNew YorkUSA
| | | | - Jay A. Tischfield
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Department of GeneticsRutgers UniversityPiscatawayNew JerseyUSA
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular BiologyIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana UniversityIndianapolisIndianaUSA
| | - Paul A. Slesinger
- Nash Family Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Ronald P. Hart
- Human Genetics Institute of New JerseyRutgers UniversityPiscatawayNew JerseyUSA
- Department of Cell Biology and NeuroscienceRutgers UniversityPiscatawayNew JerseyUSA
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5
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SNPs in 3'UTR miRNA Target Sequences Associated with Individual Drug Susceptibility. Int J Mol Sci 2022; 23:ijms232213725. [PMID: 36430200 PMCID: PMC9692299 DOI: 10.3390/ijms232213725] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 11/04/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022] Open
Abstract
The complementary interaction of microRNAs (miRNAs) with their binding sites in the 3'untranslated regions (3'UTRs) of target gene mRNAs represses translation, playing a leading role in gene expression control. MiRNA recognition elements (MREs) in the 3'UTRs of genes often contain single nucleotide polymorphisms (SNPs), which can change the binding affinity for target miRNAs leading to dysregulated gene expression. Accumulated data suggest that these SNPs can be associated with various human pathologies (cancer, diabetes, neuropsychiatric disorders, and cardiovascular diseases) by disturbing the interaction of miRNAs with their MREs located in mRNA 3'UTRs. Numerous data show the role of SNPs in 3'UTR MREs in individual drug susceptibility and drug resistance mechanisms. In this review, we brief the data on such SNPs focusing on the most rigorously proven cases. Some SNPs belong to conventional genes from the drug-metabolizing system (in particular, the genes coding for cytochromes P450 (CYP 450), phase II enzymes (SULT1A1 and UGT1A), and ABCB3 transporter and their expression regulators (PXR and GATA4)). Other examples of SNPs are related to the genes involved in DNA repair, RNA editing, and specific drug metabolisms. We discuss the gene-by-gene studies and genome-wide approaches utilized or potentially utilizable to detect the MRE SNPs associated with individual response to drugs.
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Powell NR, Zhao H, Ipe J, Liu Y, Skaar TC. Mapping the miRNA-mRNA Interactome in Human Hepatocytes and Identification of Functional mirSNPs in Pharmacogenes. Clin Pharmacol Ther 2021; 110:1106-1118. [PMID: 34314509 PMCID: PMC9007393 DOI: 10.1002/cpt.2379] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 07/21/2021] [Indexed: 12/21/2022]
Abstract
MiRNAs regulate the expression of hepatic genes involved in pharmacokinetics and pharmacodynamics. Genetic variants affecting miRNA binding (mirSNPs) have been associated with altered drug response, but previously used methods to identify miRNA binding sites and functional mirSNPs in pharmacogenes are indirect and limited by low throughput. We utilized the high-throughput chimeric-eCLIP assay to directly map thousands of miRNA-mRNA interactions and define the miRNA binding sites in primary hepatocytes. We then used the high-throughput PASSPORT-seq assay to functionally test 262 potential mirSNPs with coordinates overlapping the identified miRNA binding sites. Using chimeric-eCLIP, we identified a network of 448 miRNAs that collectively target 11,263 unique genes in primary hepatocytes pooled from 100 donors. Our data provide an extensive map of miRNA binding of each gene, including pharmacogenes, expressed in primary hepatocytes. For example, we identified the hsa-mir-27b-DPYD interaction at a previously validated binding site. A second example is our identification of 19 unique miRNAs that bind to CYP2B6 across 20 putative binding sites on the transcript. Using PASSPORT-seq, we then identified 24 mirSNPs that functionally impacted reporter mRNA levels. To our knowledge, this is the most comprehensive identification of miRNA binding sites in pharmacogenes. Combining chimeric-eCLIP with PASSPORT-seq successfully identified functional mirSNPs in pharmacogenes that may affect transcript levels through altered miRNA binding. These results provide additional insights into potential mechanisms contributing to interindividual variability in drug response.
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Affiliation(s)
- Nicholas R. Powell
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis, Indiana, USA
| | - Harrison Zhao
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis, Indiana, USA
| | - Joseph Ipe
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis, Indiana, USA
| | - Yunlong Liu
- Indiana University School of Medicine, Department of Medical and Molecular Genetics, Indianapolis, Indiana, USA
| | - Todd C. Skaar
- Indiana University School of Medicine, Department of Medicine, Division of Clinical Pharmacology, Indianapolis, Indiana, USA
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7
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Rao X, Thapa KS, Chen AB, Lin H, Gao H, Reiter JL, Hargreaves KA, Ipe J, Lai D, Xuei X, Wang Y, Gu H, Kapoor M, Farris SP, Tischfield J, Foroud T, Goate AM, Skaar TC, Mayfield RD, Edenberg HJ, Liu Y. Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders. Mol Psychiatry 2021; 26:1142-1151. [PMID: 31477794 PMCID: PMC7050407 DOI: 10.1038/s41380-019-0508-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 07/09/2019] [Accepted: 07/24/2019] [Indexed: 11/15/2022]
Abstract
Genome-wide association studies (GWAS) of complex traits, such as alcohol use disorders (AUD), usually identify variants in non-coding regions and cannot by themselves distinguish whether the associated variants are functional or in linkage disequilibrium with the functional variants. Transcriptome studies can identify genes whose expression differs between alcoholics and controls. To test which variants associated with AUD may cause expression differences, we integrated data from deep RNA-seq and GWAS of four postmortem brain regions from 30 subjects with AUD and 30 controls to analyze allele-specific expression (ASE). We identified 88 genes with differential ASE in subjects with AUD compared to controls. Next, to test one potential mechanism contributing to the differential ASE, we analyzed single nucleotide polymorphisms (SNPs) in the 3' untranslated regions (3'UTR) of these genes. Of the 88 genes with differential ASE, 61 genes contained 437 SNPs in the 3'UTR with at least one heterozygote among the subjects studied. Using a modified PASSPORT-seq (parallel assessment of polymorphisms in miRNA target-sites by sequencing) assay, we identified 25 SNPs that affected RNA levels in a consistent manner in two neuroblastoma cell lines, SH-SY5Y and SK-N-BE(2). Many of these SNPs are in binding sites of miRNAs and RNA-binding proteins, indicating that these SNPs are likely causal variants of AUD-associated differential ASE. In sum, we demonstrate that a combination of computational and experimental approaches provides a powerful strategy to uncover functionally relevant variants associated with the risk for AUD.
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Affiliation(s)
- Xi Rao
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kriti S Thapa
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andy B Chen
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hai Lin
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hongyu Gao
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jill L Reiter
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Katherine A Hargreaves
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joseph Ipe
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Dongbing Lai
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xiaoling Xuei
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yue Wang
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hongmei Gu
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Manav Kapoor
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sean P Farris
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA
| | - Jay Tischfield
- Department of Genetics, Rutgers University, Piscataway, NJ, USA
| | - Tatiana Foroud
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - R Dayne Mayfield
- Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA
| | - Howard J Edenberg
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yunlong Liu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
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Thapa KS, Chen AB, Lai D, Xuei X, Wetherill L, Tischfield JA, Liu Y, Edenberg HJ. Identification of Functional Genetic Variants Associated With Alcohol Dependence and Related Phenotypes Using a High-Throughput Assay. Alcohol Clin Exp Res 2020; 44:2494-2518. [PMID: 33119910 PMCID: PMC7725989 DOI: 10.1111/acer.14492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 10/20/2020] [Indexed: 01/22/2023]
Abstract
BACKGROUND Genome-wide association studies (GWAS) of alcohol dependence (AD) and related phenotypes have identified multiple loci, but the functional variants underlying the loci have in most cases not been identified. Noncoding variants can influence phenotype by affecting gene expression; for example, variants in the 3' untranslated regions (3'UTR) can affect gene expression posttranscriptionally. METHODS We adapted a high-throughput assay known as PASSPORT-seq (parallel assessment of polymorphisms in miRNA target sites by sequencing) to identify among variants associated with AD and related phenotypes those that cause differential expression in neuronal cell lines. Based upon meta-analyses of alcohol-related traits in African American and European Americans in the Collaborative Study on the Genetics of Alcoholism, we tested 296 single nucleotide polymorphisms (SNPs with meta-analysis p values ≤ 0.001) that were located in 3'UTRs. RESULTS We identified 60 SNPs that affected gene expression (false discovery rate [FDR] < 0.05) in SH-SY5Y cells and 92 that affected expression in SK-N-BE(2) cells. Among these, 30 SNPs altered RNA levels in the same direction in both cell lines. Many of these SNPs reside in the binding sites of miRNAs and RNA-binding proteins and are expression quantitative trait loci of genes including KIF6,FRMD4A,CADM2,ADD2,PLK2, and GAS7. CONCLUSION The SNPs identified in the PASSPORT-seq assay are functional variants that might affect the risk for AD and related phenotypes. Our study provides insights into gene regulation in AD and demonstrates the value of PASSPORT-seq as a tool to screen genetic variants in GWAS loci for one potential mechanism of action.
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Affiliation(s)
- Kriti S. Thapa
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Andy B Chen
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Dongbing Lai
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Xiaoling Xuei
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Leah Wetherill
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Jay A. Tischfield
- Department of Genetics, Rutgers University, Piscataway, NJ, 99999, USA
| | - Yunlong Liu
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
| | - Howard J. Edenberg
- Department of Biochemistry & Molecular Biology, Indiana University School of Medicine, Indianapolis, Indiana
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana
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9
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Helmy M, Hatlen A, Marco A. The Impact of Population Variation in the Analysis of microRNA Target Sites. Noncoding RNA 2019; 5:E42. [PMID: 31234531 PMCID: PMC6630466 DOI: 10.3390/ncrna5020042] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 06/11/2019] [Accepted: 06/20/2019] [Indexed: 02/07/2023] Open
Abstract
The impact of population variation in the analysis of regulatory interactions is an underdeveloped area. MicroRNA target recognition occurs via pairwise complementarity. Consequently, a number of computational prediction tools have been developed to identify potential target sites that can be further validated experimentally. However, as microRNA target predictions are done mostly considering a reference genome sequence, target sites showing variation among populations are neglected. Here, we studied the variation at microRNA target sites in human populations and quantified their impact in microRNA target prediction. We found that African populations carry a significant number of potential microRNA target sites that are not detectable in the current human reference genome sequence. Some of these targets are conserved in primates and only lost in Out-of-Africa populations. Indeed, we identified experimentally validated microRNA/transcript interactions that are not detected in standard microRNA target prediction programs, yet they have segregating target alleles abundant in non-European populations. In conclusion, we show that ignoring population diversity may leave out regulatory elements essential to understand disease and gene expression, particularly neglecting populations of African origin.
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Affiliation(s)
- Mohab Helmy
- School of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK.
| | - Andrea Hatlen
- School of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK.
| | - Antonio Marco
- School of Biological Sciences, University of Essex, Colchester CO4 3SQ, UK.
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10
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Lauschke VM, Ingelman-Sundberg M. Prediction of drug response and adverse drug reactions: From twin studies to Next Generation Sequencing. Eur J Pharm Sci 2019; 130:65-77. [PMID: 30684656 DOI: 10.1016/j.ejps.2019.01.024] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Revised: 01/21/2019] [Accepted: 01/22/2019] [Indexed: 01/12/2023]
Abstract
Understanding and predicting inter-individual differences related to the success of drug therapy is of tremendous importance, both during drug development and for clinical applications. Importantly, while seminal twin studies indicate that the majority of inter-individual differences in drug disposition are driven by hereditary factors, common genetic polymorphisms explain only less than half of this genetically encoded variability. Recent progress in Next Generation Sequencing (NGS) technologies has for the first time allowed to comprehensively map the genetic landscape of human pharmacogenes. Importantly, these projects have unveiled vast numbers of rare genetic variants, which are estimated to contribute substantially to the missing heritability of drug metabolism phenotypes. However, functional interpretation of these rare variants remains challenging and constitutes one of the important frontiers of contemporary pharmacogenomics. Furthermore, NGS technologies face challenges in the interrogation of genes residing in complex genomic regions, such as CYP2D6 and HLA genes. We here provide an update of the implementation of pharmacogenomic variations in the clinical setting and present emerging strategies that facilitate the translation of NGS data into clinically useful information. Importantly, we anticipate that these developments will soon result in a paradigm shift of pre-emptive genotyping away from the interrogation to candidate variants and towards the comprehensive profiling of an individuals genotype, thus allowing for a true individualization of patient drug treatment regimens.
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Affiliation(s)
- Volker M Lauschke
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, SE-171 77 Stockholm, Sweden
| | - Magnus Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics, Karolinska Institutet, SE-171 77 Stockholm, Sweden.
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