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Castillejo-López C, Bárcenas-Walls JR, Cavalli M, Larsson A, Wadelius C. A regulatory element associated to NAFLD in the promoter of DIO1 controls LDL-C, HDL-C and triglycerides in hepatic cells. Lipids Health Dis 2024; 23:48. [PMID: 38365720 PMCID: PMC10870585 DOI: 10.1186/s12944-024-02029-9] [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: 10/13/2023] [Accepted: 01/22/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) have identified genetic variants linked to fat metabolism and related traits, but rarely pinpoint causative variants. This limitation arises from GWAS not considering functional implications of noncoding variants that can affect transcription factor binding and potentially regulate gene expression. The aim of this study is to investigate a candidate noncoding functional variant within a genetic locus flagged by a GWAS SNP associated with non-alcoholic fatty liver disease (NAFLD), a condition characterized by liver fat accumulation in non-alcohol consumers. METHODS CRISPR-Cas9 gene editing in HepG2 cells was used to modify the regulatory element containing the candidate functional variant linked to NAFLD. Global gene expression in mutant cells was assessed through RT-qPCR and targeted transcriptomics. A phenotypic assay measured lipid droplet accumulation in the CRISPR-Cas9 mutants. RESULTS The candidate functional variant, rs2294510, closely linked to the NAFLD-associated GWAS SNP rs11206226, resided in a regulatory element within the DIO1 gene's promoter region. Altering this element resulted in changes in transcription factor binding sites and differential expression of candidate target genes like DIO1, TMEM59, DHCR24, and LDLRAD1, potentially influencing the NAFLD phenotype. Mutant HepG2 cells exhibited increased lipid accumulation, a hallmark of NAFLD, along with reduced LDL-C, HDL-C and elevated triglycerides. CONCLUSIONS This comprehensive approach, that combines genome editing, transcriptomics, and phenotypic assays identified the DIO1 promoter region as a potential enhancer. Its activity could regulate multiple genes involved in the NAFLD phenotype or contribute to defining a polygenic risk score for enhanced risk assessment in NAFLD patients.
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Affiliation(s)
- Casimiro Castillejo-López
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 , Uppsala, Sweden, Box 815, Husargatan 3, BMC
| | - José Ramón Bárcenas-Walls
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 , Uppsala, Sweden, Box 815, Husargatan 3, BMC
| | - Marco Cavalli
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 , Uppsala, Sweden, Box 815, Husargatan 3, BMC
| | - Anders Larsson
- Department of Medical Sciences, Clinical Chemistry, Uppsala University Hospital, 751 85, Uppsala, Sweden
| | - Claes Wadelius
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, 751 08 , Uppsala, Sweden, Box 815, Husargatan 3, BMC.
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Antontseva EV, Degtyareva AO, Korbolina EE, Damarov IS, Merkulova TI. Human-genome single nucleotide polymorphisms affecting transcription factor binding and their role in pathogenesis. Vavilovskii Zhurnal Genet Selektsii 2023; 27:662-675. [PMID: 37965371 PMCID: PMC10641029 DOI: 10.18699/vjgb-23-77] [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: 01/17/2023] [Revised: 03/24/2023] [Accepted: 03/30/2023] [Indexed: 11/16/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) are the most common type of variation in the human genome. The vast majority of SNPs identified in the human genome do not have any effect on the phenotype; however, some can lead to changes in the function of a gene or the level of its expression. Most SNPs associated with certain traits or pathologies are mapped to regulatory regions of the genome and affect gene expression by changing transcription factor binding sites. In recent decades, substantial effort has been invested in searching for such regulatory SNPs (rSNPs) and understanding the mechanisms by which they lead to phenotypic differences, primarily to individual differences in susceptibility to diseases and in sensitivity to drugs. The development of the NGS (next-generation sequencing) technology has contributed not only to the identification of a huge number of SNPs and to the search for their association (genome-wide association studies, GWASs) with certain diseases or phenotypic manifestations, but also to the development of more productive approaches to their functional annotation. It should be noted that the presence of an association does not allow one to identify a functional, truly disease-associated DNA sequence variant among multiple marker SNPs that are detected due to linkage disequilibrium. Moreover, determination of associations of genetic variants with a disease does not provide information about the functionality of these variants, which is necessary to elucidate the molecular mechanisms of the development of pathology and to design effective methods for its treatment and prevention. In this regard, the functional analysis of SNPs annotated in the GWAS catalog, both at the genome-wide level and at the level of individual SNPs, became especially relevant in recent years. A genome-wide search for potential rSNPs is possible without any prior knowledge of their association with a trait. Thus, mapping expression quantitative trait loci (eQTLs) makes it possible to identify an SNP for which - among transcriptomes of homozygotes and heterozygotes for its various alleles - there are differences in the expression level of certain genes, which can be located at various distances from the SNP. To predict rSNPs, approaches based on searches for allele-specific events in RNA-seq, ChIP-seq, DNase-seq, ATAC-seq, MPRA, and other data are also used. Nonetheless, for a more complete functional annotation of such rSNPs, it is necessary to establish their association with a trait, in particular, with a predisposition to a certain pathology or sensitivity to drugs. Thus, approaches to finding SNPs important for the development of a trait can be categorized into two groups: (1) starting from data on an association of SNPs with a certain trait, (2) starting from the determination of allele-specific changes at the molecular level (in a transcriptome or regulome). Only comprehensive use of strategically different approaches can considerably enrich our knowledge about the role of genetic determinants in the molecular mechanisms of trait formation, including predisposition to multifactorial diseases.
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Affiliation(s)
- E V Antontseva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - A O Degtyareva
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - E E Korbolina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - I S Damarov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - T I Merkulova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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3
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Bryzgalov LO, Korbolina EE, Damarov IS, Merkulova TI. The functional insight into the genetics of cardiovascular disease: results from the post-GWAS study. Vavilovskii Zhurnal Genet Selektsii 2022; 26:65-73. [PMID: 35342858 PMCID: PMC8892170 DOI: 10.18699/vjgb-22-10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 11/22/2021] [Accepted: 11/23/2021] [Indexed: 11/19/2022] Open
Abstract
Cardiovascular diseases (CVDs), the leading cause of death worldwide, generally refer to a range of pathological conditions with the involvement of the heart and the blood vessels. A sizable fraction of the susceptibility loci is known, but the underlying mechanisms have been established only for a small proportion. Therefore, there is an increasing need to explore the functional relevance of trait-associated variants and, moreover, to search for novel risk genetic variation. We have reported the bioinformatic approach allowing effective identification of functional non-coding variants by integrated analysis of genome-wide data. Here, the analysis of 1361 previously identified regulatory SNPs (rSNPs) was performed to provide new insights into cardiovascular risk. We found 773,471 coding co-segregating markers for input rSNPs using the 1000 Genomes Project. The intersection of GWAS-derived SNPs with a relevance to cardiovascular traits with these markers was analyzed within a window of 10 Kbp. The effects on the transcription factor (TF) binding sites were explored by DeFine models. Functional pathway enrichment and protein– protein interaction (PPI) network analyses were performed on the targets and the extended genes by STRING and DAVID. Eighteen rSNPs were functionally linked to cardiovascular risk. A significant impact on binding sites of thirteen TFs including those involved in blood cells formation, hematopoiesis, macrophage function, inflammation, and vasoconstriction was found in K562 cells. 21 rSNP gene targets and 5 partners predicted by PPI were enriched for spliceosome and endocytosis KEGG pathways, endosome sorting complex and mRNA splicing REACTOME pathways. Related Gene Ontology terms included mRNA splicing and processing, endosome transport and protein catabolic processes. Together, the findings provide further insight into the biological basis of CVDs and highlight the importance of the precise regulation of splicing and alternative splicing.
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Affiliation(s)
- L. O. Bryzgalov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences
| | - E. E. Korbolina
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences
| | - I. S. Damarov
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences
| | - T. I. Merkulova
- Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State University
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4
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Ignatieva EV, Matrosova EA. Disease-associated genetic variants in the regulatory regions of human genes: mechanisms of action on transcription and genomic resources for dissecting these mechanisms. Vavilovskii Zhurnal Genet Selektsii 2021; 25:18-29. [PMID: 34541447 PMCID: PMC8408020 DOI: 10.18699/vj21.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/18/2021] [Accepted: 01/18/2021] [Indexed: 11/21/2022] Open
Abstract
Whole genome and whole exome sequencing technologies play a very important role in the studies of the genetic aspects of the pathogenesis of various diseases. The ample use of genome-wide and exome-wide association study
methodology (GWAS and EWAS) made it possible to identify a large number of genetic variants associated with diseases.
This information is accumulated in the databases like GWAS central, GWAS catalog, OMIM, ClinVar, etc. Most of the variants identified by the GWAS technique are located in the noncoding regions of the human genome. According to the
ENCODE project, the fraction of regions in the human genome potentially involved in transcriptional control is many times
greater than the fraction of coding regions. Thus, genetic variation in noncoding regions of the genome can increase the
susceptibility to diseases by disrupting various regulatory elements (promoters, enhancers, silencers, insulator regions,
etc.). However, identification of the mechanisms of influence of pathogenic genetic variants on the diseases risk is difficult
due to a wide variety of regulatory elements. The present review focuses on the molecular genetic mechanisms by which
pathogenic genetic variants affect gene expression. At the same time, attention is concentrated on the transcriptional level
of regulation as an initial step in the expression of any gene. A triggering event mediating the effect of a pathogenic genetic
variant on the level of gene expression can be, for example, a change in the functional activity of transcription factor binding sites (TFBSs) or DNA methylation change, which, in turn, affects the functional activity of promoters or enhancers. Dissecting the regulatory roles of polymorphic loci have been impossible without close integration of modern experimental
approaches with computer analysis of a growing wealth of genetic and biological data obtained using omics technologies.
The review provides a brief description of a number of the most well-known public genomic information resources containing data obtained using omics technologies, including (1) resources that accumulate data on the chromatin states and the
regions of transcription factor binding derived from ChIP-seq experiments; (2) resources containing data on genomic loci,
for which allele-specific transcription factor binding was revealed based on ChIP-seq technology; (3) resources containing
in silico predicted data on the potential impact of genetic variants on the transcription factor binding sites
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Affiliation(s)
- E V Ignatieva
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
| | - E A Matrosova
- Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia Novosibirsk State University, Novosibirsk, Russia
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5
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Abstract
Diploidy has profound implications for population genetics and susceptibility to genetic diseases. Although two copies are present for most genes in the human genome, they are not necessarily both active or active at the same level in a given individual. Genomic imprinting, resulting in exclusive or biased expression in favor of the allele of paternal or maternal origin, is now believed to affect hundreds of human genes. A far greater number of genes display unequal expression of gene copies due to cis-acting genetic variants that perturb gene expression. The availability of data generated by RNA sequencing applied to large numbers of individuals and tissue types has generated unprecedented opportunities to assess the contribution of genetic variation to allelic imbalance in gene expression. Here we review the insights gained through the analysis of these data about the extent of the genetic contribution to allelic expression imbalance, the tools and statistical models for gene expression imbalance, and what the results obtained reveal about the contribution of genetic variants that alter gene expression to complex human diseases and phenotypes.
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Affiliation(s)
- Siobhan Cleary
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway H91 H3CY, Ireland;
| | - Cathal Seoighe
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland, Galway H91 H3CY, Ireland;
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6
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Korbolina EE, Bryzgalov LO, Ustrokhanova DZ, Postovalov SN, Poverin DV, Damarov IS, Merkulova TI. A Panel of rSNPs Demonstrating Allelic Asymmetry in Both ChIP-seq and RNA-seq Data and the Search for Their Phenotypic Outcomes through Analysis of DEGs. Int J Mol Sci 2021; 22:ijms22147240. [PMID: 34298860 PMCID: PMC8303726 DOI: 10.3390/ijms22147240] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 06/24/2021] [Accepted: 06/30/2021] [Indexed: 12/12/2022] Open
Abstract
Currently, the detection of the allele asymmetry of gene expression from RNA-seq data or the transcription factor binding from ChIP-seq data is one of the approaches used to identify the functional genetic variants that can affect gene expression (regulatory SNPs or rSNPs). In this study, we searched for rSNPs using the data for human pulmonary arterial endothelial cells (PAECs) available from the Sequence Read Archive (SRA). Allele-asymmetric binding and expression events are analyzed in paired ChIP-seq data for H3K4me3 mark and RNA-seq data obtained for 19 individuals. Two statistical approaches, weighted z-scores and predicted probabilities, were used to improve the efficiency of finding rSNPs. In total, we identified 14,266 rSNPs associated with both allele-specific binding and expression. Among them, 645 rSNPs were associated with GWAS phenotypes; 4746 rSNPs were reported as eQTLs by GTEx, and 11,536 rSNPs were located in 374 candidate transcription factor binding motifs. Additionally, we searched for the rSNPs associated with gene expression using an SRA RNA-seq dataset for 281 clinically annotated human postmortem brain samples and detected eQTLs for 2505 rSNPs. Based on these results, we conducted Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and constructed the protein-protein interaction networks to represent the top-ranked biological processes with a possible contribution to the phenotypic outcome.
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Affiliation(s)
- Elena E. Korbolina
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 LavrentyevaProspekt, 630090 Novosibirsk, Russia; (L.O.B.); (I.S.D.); (T.I.M.)
- Correspondence:
| | - Leonid O. Bryzgalov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 LavrentyevaProspekt, 630090 Novosibirsk, Russia; (L.O.B.); (I.S.D.); (T.I.M.)
- VECTOR-BEST, PO BOX 492, 630117 Novosibirsk, Russia
| | - Diana Z. Ustrokhanova
- Department of Information Biology, The Novosibirsk State University, 1 Pirogovast, 630090 Novosibirsk, Russia;
| | - Sergey N. Postovalov
- Department of Theoretical and Applied Informatics, The Novosibirsk State Technical University, 630073 Novosibirsk, Russia; (S.N.P.); (D.V.P.)
| | - Dmitry V. Poverin
- Department of Theoretical and Applied Informatics, The Novosibirsk State Technical University, 630073 Novosibirsk, Russia; (S.N.P.); (D.V.P.)
| | - Igor S. Damarov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 LavrentyevaProspekt, 630090 Novosibirsk, Russia; (L.O.B.); (I.S.D.); (T.I.M.)
| | - Tatiana I. Merkulova
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 LavrentyevaProspekt, 630090 Novosibirsk, Russia; (L.O.B.); (I.S.D.); (T.I.M.)
- Department of Information Biology, The Novosibirsk State University, 1 Pirogovast, 630090 Novosibirsk, Russia;
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7
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Degtyareva AO, Antontseva EV, Merkulova TI. Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases. Int J Mol Sci 2021; 22:6454. [PMID: 34208629 PMCID: PMC8235176 DOI: 10.3390/ijms22126454] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 06/15/2021] [Accepted: 06/15/2021] [Indexed: 12/19/2022] Open
Abstract
The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.
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Affiliation(s)
- Arina O. Degtyareva
- Department of Molecular Genetic, Institute of Cytology and Genetics, 630090 Novosibirsk, Russia; (A.O.D.); (E.V.A.)
| | - Elena V. Antontseva
- Department of Molecular Genetic, Institute of Cytology and Genetics, 630090 Novosibirsk, Russia; (A.O.D.); (E.V.A.)
| | - Tatiana I. Merkulova
- Department of Molecular Genetic, Institute of Cytology and Genetics, 630090 Novosibirsk, Russia; (A.O.D.); (E.V.A.)
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
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8
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Xu S, Feng W, Lu Z, Yu CY, Shao W, Nakshatri H, Reiter JL, Gao H, Chu X, Wang Y, Liu Y. regSNPs-ASB: A Computational Framework for Identifying Allele-Specific Transcription Factor Binding From ATAC-seq Data. Front Bioeng Biotechnol 2020; 8:886. [PMID: 32850739 PMCID: PMC7405637 DOI: 10.3389/fbioe.2020.00886] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 07/09/2020] [Indexed: 12/21/2022] Open
Abstract
Expression quantitative trait loci (eQTL) analysis is useful for identifying genetic variants correlated with gene expression, however, it cannot distinguish between causal and nearby non-functional variants. Because the majority of disease-associated SNPs are located in regulatory regions, they can impact allele-specific binding (ASB) of transcription factors and result in differential expression of the target gene alleles. In this study, our aim was to identify functional single-nucleotide polymorphisms (SNPs) that alter transcriptional regulation and thus, potentially impact cellular function. Here, we present regSNPs-ASB, a generalized linear model-based approach to identify regulatory SNPs that are located in transcription factor binding sites. The input for this model includes ATAC-seq (assay for transposase-accessible chromatin with high-throughput sequencing) raw read counts from heterozygous loci, where differential transposase-cleavage patterns between two alleles indicate preferential transcription factor binding to one of the alleles. Using regSNPs-ASB, we identified 53 regulatory SNPs in human MCF-7 breast cancer cells and 125 regulatory SNPs in human mesenchymal stem cells (MSC). By integrating the regSNPs-ASB output with RNA-seq experimental data and publicly available chromatin interaction data from MCF-7 cells, we found that these 53 regulatory SNPs were associated with 74 potential target genes and that 32 (43%) of these genes showed significant allele-specific expression. By comparing all of the MCF-7 and MSC regulatory SNPs to the eQTLs in the Genome-Tissue Expression (GTEx) Project database, we found that 30% (16/53) of the regulatory SNPs in MCF-7 and 43% (52/122) of the regulatory SNPs in MSC were also in eQTL regions. The enrichment of regulatory SNPs in eQTLs indicated that many of them are likely responsible for allelic differences in gene expression (chi-square test, p-value < 0.01). In summary, we conclude that regSNPs-ASB is a useful tool for identifying causal variants from ATAC-seq data. This new computational tool will enable efficient prioritization of genetic variants identified as eQTL for further studies to validate their causal regulatory function. Ultimately, identifying causal genetic variants will further our understanding of the underlying molecular mechanisms of disease and the eventual development of potential therapeutic targets.
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Affiliation(s)
- Siwen Xu
- Institute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, China.,Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Weixing Feng
- Institute of Intelligent System and Bioinformatics, College of Automation, Harbin Engineering University, Harbin, China
| | - Zixiao Lu
- Regenstrief Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Christina Y Yu
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, United States.,Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States
| | - Wei Shao
- Regenstrief Institute, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Harikrishna Nakshatri
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Jill L Reiter
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Hongyu Gao
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Xiaona Chu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yue Wang
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
| | - Yunlong Liu
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, United States.,Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States
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9
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Pan G, Cavalli M, Carlsson B, Skrtic S, Kumar C, Wadelius C. rs953413 Regulates Polyunsaturated Fatty Acid Metabolism by Modulating ELOVL2 Expression. iScience 2020; 23:100808. [PMID: 31928966 PMCID: PMC7033636 DOI: 10.1016/j.isci.2019.100808] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 11/26/2019] [Accepted: 12/23/2019] [Indexed: 12/11/2022] Open
Abstract
Long-chain polyunsaturated fatty acids (LC-PUFAs) influence human health in several areas, including cardiovascular disease, diabetes, fatty liver disease, and cancer. ELOVL2 encodes one of the key enzymes in the in vivo synthesis of LC-PUFAs from their precursors. Variants near ELOVL2 have repeatedly been associated with levels of LC-PUFA-derived metabolites in genome-wide association studies (GWAS), but the mechanisms behind these observations remain poorly defined. In this study, we found that rs953413, located in the first intron of ELOVL2, lies within a functional FOXA and HNF4α cooperative binding site. The G allele of rs953413 increases binding of FOXA1/FOXA2 and HNF4α to an evolutionarily conserved enhancer element, conferring allele-specific upregulation of the rs953413-associated gene ELOVL2. The expression of ELOVL2 was significantly downregulated by both FOXA1 and HNF4α knockdown and CRISPR/Cas9-mediated direct mutation to the enhancer element. Our results suggest that rs953413 regulates LC-PUFAs metabolism by altering ELOVL2 expression through FOXA1/FOXA2 and HNF4α cooperation. rs953413 resides in an evolutionarily conserved enhancer region rs953413 mediates the cooperative binding of FOXA and HNF4α to the enhancer region The rs953413 locus plays a key role in regulating ELOVL2 expression rs953413 is implicated in PUFA metabolism by regulating ELOVL2 expression
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Affiliation(s)
- Gang Pan
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Marco Cavalli
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Björn Carlsson
- Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Stanko Skrtic
- Pharmaceutical Technology & Development, AstraZeneca AB, Gothenburg, Sweden; Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Chanchal Kumar
- Translational Science & Experimental Medicine, Research and Early Development, Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden; Karolinska Institutet/AstraZeneca Integrated CardioMetabolic Center (KI/AZ ICMC), Department of Medicine, Novum, Huddinge, Sweden
| | - Claes Wadelius
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
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10
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Zhou B, Ho SS, Greer SU, Spies N, Bell JM, Zhang X, Zhu X, Arthur JG, Byeon S, Pattni R, Saha I, Huang Y, Song G, Perrin D, Wong WH, Ji HP, Abyzov A, Urban AE. Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2. Nucleic Acids Res 2019; 47:3846-3861. [PMID: 30864654 PMCID: PMC6486628 DOI: 10.1093/nar/gkz169] [Citation(s) in RCA: 170] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 02/19/2019] [Accepted: 03/01/2019] [Indexed: 12/19/2022] Open
Abstract
HepG2 is one of the most widely used human cancer cell lines in biomedical research and one of the main cell lines of ENCODE. Although the functional genomic and epigenomic characteristics of HepG2 are extensively studied, its genome sequence has never been comprehensively analyzed and higher order genomic structural features are largely unknown. The high degree of aneuploidy in HepG2 renders traditional genome variant analysis methods challenging and partially ineffective. Correct and complete interpretation of the extensive functional genomics data from HepG2 requires an understanding of the cell line’s genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of genome characteristics in HepG2: copy numbers of chromosomal segments at high resolution, SNVs and Indels (corrected for aneuploidy), regions with loss of heterozygosity, phased haplotypes extending to entire chromosome arms, retrotransposon insertions and structural variants (SVs) including complex and somatic genomic rearrangements. A large number of SVs were phased, sequence assembled and experimentally validated. We re-analyzed published HepG2 datasets for allele-specific expression and DNA methylation and assembled an allele-specific CRISPR/Cas9 targeting map. We demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.
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Affiliation(s)
- Bo Zhou
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Steve S Ho
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Stephanie U Greer
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Noah Spies
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA.,Genome-scale Measurements Group, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA
| | - John M Bell
- Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, USA
| | - Xianglong Zhang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Xiaowei Zhu
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Joseph G Arthur
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Seunggyu Byeon
- School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
| | - Reenal Pattni
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Ishan Saha
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yiling Huang
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Giltae Song
- School of Computer Science and Engineering, College of Engineering, Pusan National University, Busan 46241, South Korea
| | - Dimitri Perrin
- Science and Engineering Faculty, Queensland University of Technology, Brisbane, QLD 4001, Australia
| | - Wing H Wong
- Department of Statistics, Stanford University, Stanford, CA 94305, USA.,Department of Biomedical Data Science, Bio-X Program, Stanford University, Stanford, CA 94305, USA
| | - Hanlee P Ji
- Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.,Stanford Genome Technology Center, Stanford University, Palo Alto, CA 94304, USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Alexander E Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA.,Tashia and John Morgridge Faculty Scholar, Stanford Child Health Research Institute, Stanford, CA 94305, USA
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11
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Castillejo-Lopez C, Pjanic M, Pirona AC, Hetty S, Wabitsch M, Wadelius C, Quertermous T, Arner E, Ingelsson E. Detailed Functional Characterization of a Waist-Hip Ratio Locus in 7p15.2 Defines an Enhancer Controlling Adipocyte Differentiation. iScience 2019; 20:42-59. [PMID: 31557715 PMCID: PMC6817687 DOI: 10.1016/j.isci.2019.09.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 07/10/2019] [Accepted: 09/05/2019] [Indexed: 12/22/2022] Open
Abstract
We combined CAGE sequencing in human adipocytes during differentiation with data from genome-wide association studies to identify an enhancer in the SNX10 locus on chromosome 7, presumably involved in body fat distribution. Using reporter assays and CRISPR-Cas9 gene editing in human cell lines, we characterized the role of the enhancer in adipogenesis. The enhancer was active during adipogenesis and responded strongly to insulin and isoprenaline. The allele associated with increased waist-hip ratio in human genetic studies was associated with higher enhancer activity. Mutations of the enhancer resulted in less adipocyte differentiation. RNA sequencing of cells with disrupted enhancer showed reduced expression of established adipocyte markers, such as ADIPOQ and LPL, and identified CHI3L1 on chromosome 1 as a potential gene involved in adipocyte differentiation. In conclusion, we identified and characterized an enhancer in the SNX10 locus and outlined its plausible mechanisms of action and downstream targets. An enhancer active during adipogenesis is located in an obesity GWAS locus The enhancer responded strongly to insulin and isoprenaline Mutation of the enhancer by CRISPR-Cas9 decreased adipocyte differentiation Knockout of CHI3L1 decreased adipocyte differentiation
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Affiliation(s)
- Casimiro Castillejo-Lopez
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Milos Pjanic
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Anna Chiara Pirona
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Susanne Hetty
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Martin Wabitsch
- Department of Pediatrics and Adolescent Medicine, Division of Pediatric Endocrinology and Diabetes, University of Ulm, Ulm, Germany
| | - Claes Wadelius
- Department of Immunology, Genetics and Pathology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Thomas Quertermous
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA
| | - Erik Arner
- Laboratory for Applied Regulatory Genomics Network Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045 Japan
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA; Stanford Diabetes Research Center, Stanford University, Stanford, CA 94305, USA.
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12
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Integrating genome-wide association study with regulatory SNP annotation information identified candidate genes and pathways for schizophrenia. Aging (Albany NY) 2019; 11:3704-3715. [PMID: 31175266 PMCID: PMC6594824 DOI: 10.18632/aging.102008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 05/29/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Schizophrenia is a complex mental disorder. The genetic mechanism of schizophrenia remains elusive now. METHODS We conducted a large-scale integrative analysis of two genome-wide association studies of schizophrenia with functional annotation datasets of regulatory single-nucleotide polymorphism (rSNP). The significant SNPs identified by the two genome-wide association studies were first annotated to obtain schizophrenia associated rSNPs and their target genes and proteins, respectively. We then compared the integrative analysis results to identify the common rSNPs and their target regulatory genes and proteins, shared by the two genome-wide association studies of schizophrenia. Finally, DAVID tool was used to conduct gene ontology and pathway enrichment analysis of the identified targets genes and proteins. RESULTS We detected 53 schizophrenia-associated target genes for rSNP, such as FOS (P value = 2.18×10-20), ATXN1 (P value = 5.22×10-21) and HLA-DQA1 (P value = 1.98×10-10). Pathway enrichment analysis identified 24 pathways for transcription factors binding regions, chromatin interacting regions, long non-coding RNAs, topologically associated domains, circular RNAs and post-translational modifications, such as hsa05034:Alcoholism (P value = 2.57×10-7) and hsa04612:Antigen processing and presentation (P value = 6.82×10-8). CONCLUSION We detected multiple candidate genes, gene ontology terms and pathways for schizophrenia, supporting the functional importance of rSNPs, and providing novel clues for understanding the genetic architecture of schizophrenia.
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13
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Cavalli M, Baltzer N, Umer HM, Grau J, Lemnian I, Pan G, Wallerman O, Spalinskas R, Sahlén P, Grosse I, Komorowski J, Wadelius C. Allele specific chromatin signals, 3D interactions, and motif predictions for immune and B cell related diseases. Sci Rep 2019; 9:2695. [PMID: 30804403 PMCID: PMC6389883 DOI: 10.1038/s41598-019-39633-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Accepted: 01/24/2019] [Indexed: 12/20/2022] Open
Abstract
Several Genome Wide Association Studies (GWAS) have reported variants associated to immune diseases. However, the identified variants are rarely the drivers of the associations and the molecular mechanisms behind the genetic contributions remain poorly understood. ChIP-seq data for TFs and histone modifications provide snapshots of protein-DNA interactions allowing the identification of heterozygous SNPs showing significant allele specific signals (AS-SNPs). AS-SNPs can change a TF binding site resulting in altered gene regulation and are primary candidates to explain associations observed in GWAS and expression studies. We identified 17,293 unique AS-SNPs across 7 lymphoblastoid cell lines. In this set of cell lines we interrogated 85% of common genetic variants in the population for potential regulatory effect and we identified 237 AS-SNPs associated to immune GWAS traits and 714 to gene expression in B cells. To elucidate possible regulatory mechanisms we integrated long-range 3D interactions data to identify putative target genes and motif predictions to identify TFs whose binding may be affected by AS-SNPs yielding a collection of 173 AS-SNPs associated to gene expression and 60 to B cell related traits. We present a systems strategy to find functional gene regulatory variants, the TFs that bind differentially between alleles and novel strategies to detect the regulated genes.
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Affiliation(s)
- Marco Cavalli
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Nicholas Baltzer
- Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden
| | - Husen M Umer
- Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden
| | - Jan Grau
- Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Ioana Lemnian
- Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany
| | - Gang Pan
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ola Wallerman
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Rapolas Spalinskas
- Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Pelin Sahlén
- Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Ivo Grosse
- Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.,German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
| | - Jan Komorowski
- Department of Cell and Molecular Biology, Computational Biology and Bioinformatics, Uppsala University, Uppsala, Sweden.,Institute of Computer Science, Polish Academy of Sciences, Warszawa, Poland
| | - Claes Wadelius
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.
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14
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Joshi HJ, Hansen L, Narimatsu Y, Freeze HH, Henrissat B, Bennett E, Wandall HH, Clausen H, Schjoldager KT. Glycosyltransferase genes that cause monogenic congenital disorders of glycosylation are distinct from glycosyltransferase genes associated with complex diseases. Glycobiology 2018; 28:284-294. [PMID: 29579191 DOI: 10.1093/glycob/cwy015] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Indexed: 12/12/2022] Open
Abstract
Glycosylation of proteins, lipids and proteoglycans in human cells involves at least 167 identified glycosyltransferases (GTfs), and these orchestrate the biosynthesis of diverse types of glycoconjugates and glycan structures. Mutations in this part of the genome-the GTf-genome-cause more than 58 rare, monogenic congenital disorders of glycosylation (CDGs). They are also statistically associated with a large number of complex phenotypes, diseases or predispositions to complex diseases based on Genome-Wide Association Studies (GWAS). CDGs are extremely rare and often with severe medical consequences. In contrast, GWAS are likely to identify more common genetic variations and generally involve less severe and distinct traits. We recently confirmed that structural defects in GTf genes are extremely rare, which seemed at odds with the large number of GWAS pointing to GTf-genes. To resolve this issue, we surveyed the GTf-genome for reported CDGs and GWAS candidates; we found little overlap between the two groups of genes. Moreover, GTf-genes implicated by CDG or GWAS appear to constitute different classes with respect to their: (i) predicted roles in glycosylation pathways; (ii) potential for partial redundancy by closely homologous genes; and (iii) transcriptional regulation as evaluated by RNAseq data. Our analysis suggest that more complex traits are caused by dysregulation rather than structural deficiency of GTfs, which suggests that some glycosylation reactions may be predicted to be under tight regulation for fine-tuning of important biological functions.
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Affiliation(s)
- Hiren J Joshi
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Lars Hansen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Yoshiki Narimatsu
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Hudson H Freeze
- Human Genetics Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Bernard Henrissat
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark.,Architecture et Fonction des Macromolécules Biologiques, Centre National de la Recherche Scientifique (CNRS), Aix-Marseille University, F-13288 Marseille, France
| | - Eric Bennett
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Hans H Wandall
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Henrik Clausen
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
| | - Katrine T Schjoldager
- Copenhagen Center for Glycomics, Departments of Cellular and Molecular Medicine and School of Dentistry, Faculty of Health Sciences, University of Copenhagen, Blegdamsvej 3, DK-2200 Copenhagen N, Denmark
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15
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Bryzgalov LO, Korbolina EE, Brusentsov II, Leberfarb EY, Bondar NP, Merkulova TI. Novel functional variants at the GWAS-implicated loci might confer risk to major depressive disorder, bipolar affective disorder and schizophrenia. BMC Neurosci 2018; 19:22. [PMID: 29745862 PMCID: PMC5998904 DOI: 10.1186/s12868-018-0414-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND A challenge of understanding the mechanisms underlying cognition including neurodevelopmental and neuropsychiatric disorders is mainly given by the potential severity of cognitive disorders for the quality of life and their prevalence. However, the field has been focused predominantly on protein coding variation until recently. Given the importance of tightly controlled gene expression for normal brain function, the goal of the study was to assess the functional variation including non-coding variation in human genome that is likely to play an important role in cognitive functions. To this end, we organized and utilized available genome-wide datasets from genomic, transcriptomic and association studies into a comprehensive data corpus. We focused on genomic regions that are enriched in regulatory activity-overlapping transcriptional factor binding regions and repurpose our data collection especially for identification of the regulatory SNPs (rSNPs) that showed associations both with allele-specific binding and allele-specific expression. We matched these rSNPs to the nearby and distant targeted genes and then selected the variants that could implicate the etiology of cognitive disorders according to Genome-Wide Association Studies (GWAS). Next, we use DeSeq 2.0 package to test the differences in the expression of the certain targeted genes between the controls and the patients that were diagnosed bipolar affective disorder and schizophrenia. Finally, we assess the potential biological role for identified drivers of cognition using DAVID and GeneMANIA. RESULTS As a result, we selected fourteen regulatory SNPs locating within the loci, implicated from GWAS for cognitive disorders with six of the variants unreported previously. Grouping of the targeted genes according to biological functions revealed the involvement of processes such as 'posttranscriptional regulation of gene expression', 'neuron differentiation', 'neuron projection development', 'regulation of cell cycle process' and 'protein catabolic processes'. We identified four rSNP-targeted genes that showed differential expression between patient and control groups depending on brain region: NRAS-in schizophrenia cohort, CDC25B, DDX21 and NUCKS1-in bipolar disorder cohort. CONCLUSIONS Overall, our findings are likely to provide the keys for unraveling the mechanisms that underlie cognitive functions including major depressive disorder, bipolar disorder and schizophrenia etiopathogenesis.
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Affiliation(s)
- Leonid O. Bryzgalov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
| | - Elena E. Korbolina
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
- The Novosibirsk State University, 1 Pirogova st., Novosibirsk, Russian Federation 630090
| | - Ilja I. Brusentsov
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
| | - Elena Y. Leberfarb
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
| | - Natalia P. Bondar
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
- The Novosibirsk State University, 1 Pirogova st., Novosibirsk, Russian Federation 630090
| | - Tatiana I. Merkulova
- The Federal Research Center Institute of Cytology and Genetics, The Siberian Branch of the Russian Academy of Science, 10 Lavrentyeva Prospekt, Novosibirsk, Russian Federation 630090
- The Novosibirsk State University, 1 Pirogova st., Novosibirsk, Russian Federation 630090
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16
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Liu Y, Walavalkar NM, Dozmorov MG, Rich SS, Civelek M, Guertin MJ. Identification of breast cancer associated variants that modulate transcription factor binding. PLoS Genet 2017; 13:e1006761. [PMID: 28957321 PMCID: PMC5619690 DOI: 10.1371/journal.pgen.1006761] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 04/12/2017] [Indexed: 01/11/2023] Open
Abstract
Genome-wide association studies (GWAS) have discovered thousands loci associated with disease risk and quantitative traits, yet most of the variants responsible for risk remain uncharacterized. The majority of GWAS-identified loci are enriched for non-coding single-nucleotide polymorphisms (SNPs) and defining the molecular mechanism of risk is challenging. Many non-coding causal SNPs are hypothesized to alter transcription factor (TF) binding sites as the mechanism by which they affect organismal phenotypes. We employed an integrative genomics approach to identify candidate TF binding motifs that confer breast cancer-specific phenotypes identified by GWAS. We performed de novo motif analysis of regulatory elements, analyzed evolutionary conservation of identified motifs, and assayed TF footprinting data to identify sequence elements that recruit TFs and maintain chromatin landscape in breast cancer-relevant tissue and cell lines. We identified candidate causal SNPs that are predicted to alter TF binding within breast cancer-relevant regulatory regions that are in strong linkage disequilibrium with significantly associated GWAS SNPs. We confirm that the TFs bind with predicted allele-specific preferences using CTCF ChIP-seq data. We used The Cancer Genome Atlas breast cancer patient data to identify ANKLE1 and ZNF404 as the target genes of candidate TF binding site SNPs in the 19p13.11 and 19q13.31 GWAS-identified loci. These SNPs are associated with the expression of ZNF404 and ANKLE1 in breast tissue. This integrative analysis pipeline is a general framework to identify candidate causal variants within regulatory regions and TF binding sites that confer phenotypic variation and disease risk.
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Affiliation(s)
- Yunxian Liu
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Ninad M. Walavalkar
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Mikhail G. Dozmorov
- Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, United States of America
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
| | - Mete Civelek
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
- Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, United Statess of America
| | - Michael J. Guertin
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, Virginia, United States of America
- Center for Public Health Genomics, University of Virginia, Charlottesville, Virginia, United States of America
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17
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Cavalli M, Pan G, Nord H, Wallén Arzt E, Wallerman O, Wadelius C. Genetic prevention of hepatitis C virus-induced liver fibrosis by allele-specific downregulation of MERTK. Hepatol Res 2017; 47:826-830. [PMID: 27577861 DOI: 10.1111/hepr.12810] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 08/24/2016] [Accepted: 08/28/2016] [Indexed: 01/02/2023]
Abstract
AIM Infection by hepatitis C virus (HCV) can result in the development of liver fibrosis and may eventually progress into cirrhosis and hepatocellular carcinoma. However, the molecular mechanisms for this process are not fully known. Several genome-wide association studies have been carried out to pinpoint causative variants in HCV-infected patient cohorts, but these variants are usually not the functional ones. The aim of this study was to identify the regulatory single nucleotide polymorphism associated with the risk of HCV-induced liver fibrosis and elucidate its molecular mechanism. METHODS We utilized a bioinformatics approach to identify a non-coding regulatory variant, located in an intron of the MERTK gene, based on differential transcription factor binding between the alleles. We validated the results using expression reporter assays and electrophoresis mobility shift assays. RESULTS Chromatin immunoprecipitation sequencing indicated that transcription factor(s) bind stronger to the A allele of rs6726639. Electrophoresis mobility shift assays supported these findings and suggested that the transcription factor is interferon regulatory factor 1 (IRF1). Luciferase report assays showed lower enhancer activity from the A allele and that IRF1 may act as a repressor. CONCLUSIONS Treatment of hepatitis C with interferon-α results in increased IRF1 levels and our data suggest that this leads to an allele-specific downregulation of MERTK mediated by an allelic effect on the regulatory element containing the functional rs6726639. This variant also shows the hallmarks for being the driver of the genome-wide association studies for reduced risk of liver fibrosis and non-alcoholic fatty liver disease at MERTK.
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Affiliation(s)
- Marco Cavalli
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Gang Pan
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Helena Nord
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Emelie Wallén Arzt
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden.,Department of Biosciences and Nutrition, Center for Biosciences, Karolinska Institute, Huddinge, Sweden
| | - Ola Wallerman
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Claes Wadelius
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
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18
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Do C, Shearer A, Suzuki M, Terry MB, Gelernter J, Greally JM, Tycko B. Genetic-epigenetic interactions in cis: a major focus in the post-GWAS era. Genome Biol 2017. [PMID: 28629478 PMCID: PMC5477265 DOI: 10.1186/s13059-017-1250-y] [Citation(s) in RCA: 94] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Studies on genetic-epigenetic interactions, including the mapping of methylation quantitative trait loci (mQTLs) and haplotype-dependent allele-specific DNA methylation (hap-ASM), have become a major focus in the post-genome-wide-association-study (GWAS) era. Such maps can nominate regulatory sequence variants that underlie GWAS signals for common diseases, ranging from neuropsychiatric disorders to cancers. Conversely, mQTLs need to be filtered out when searching for non-genetic effects in epigenome-wide association studies (EWAS). Sequence variants in CCCTC-binding factor (CTCF) and transcription factor binding sites have been mechanistically linked to mQTLs and hap-ASM. Identifying these sites can point to disease-associated transcriptional pathways, with implications for targeted treatment and prevention.
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Affiliation(s)
- Catherine Do
- Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Alyssa Shearer
- Institute for Cancer Genetics and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Masako Suzuki
- Center for Epigenomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Mary Beth Terry
- Department of Epidemiology, Columbia University Mailman School of Public Health, and Herbert Irving Comprehensive Cancer Center, Columbia University, New York, NY, 10032, USA
| | - Joel Gelernter
- Departments of Psychiatry, Genetics, and Neurobiology, Yale University School of Medicine, New Haven, CT, 06520, USA
| | - John M Greally
- Center for Epigenomics, Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Benjamin Tycko
- Institute for Cancer Genetics, Herbert Irving Comprehensive Cancer Center, Taub Institute for Research on Alzheimer's disease and the Aging Brain, New York, NY, 10032, USA. .,Department of Pathology and Cell Biology, Columbia University, New York, NY, 10032, USA.
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