Browsing by Author "Farris, Sean P."

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    Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders
    (Springer Nature, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, Yunlong; Medical and Molecular Genetics, School of Medicine
    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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    Allele-specific expression and high-throughput reporter assay reveal functional genetic variants associated with alcohol use disorders.
    (Springer, 2021-04) Rao, Xi; Thapa, Kriti S.; Chen, Andy B.; Lin, Hai; Gao, Hongyu; Reiter, Jill L.; Hargreaves, Katherine A.; Ipe, Joseph; Lai, Dongbing; Xuei, Xiaoling; Wang, Yue; Gu, Hongmei; Kapoor, Manav; Farris, Sean P.; Tischfield, Jay; Foroud, Tatiana; Goate, Alison M.; Skaar, Todd C.; Mayfield, R. Dayne; Edenberg, Howard J.; Liu, Yunlong
    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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    Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism
    (Springer Nature, 2019-02-14) Kapoor, Manav; Wang, Jen-Chyong; Farris, Sean P.; Liu, Yunlong; McClintick, Jeanette; Gupta, Ishaan; Meyers, Jacquelyn L.; Bertelsen, Sarah; Chao, Michael; Nurnberger, John; Tischfield, Jay; Harari, Oscar; Zeran, Li; Hesselbrock, Victor; Bauer, Lance; Raj, Towfique; Porjesz, Bernice; Agrawal, Arpana; Foroud, Tatiana; Edenberg, Howard J.; Mayfield, R. Dayne; Goate, Alison; Medical and Molecular Genetics, School of Medicine
    Alcohol exposure triggers changes in gene expression and biological pathways in human brain. We explored alterations in gene expression in the Pre-Frontal Cortex (PFC) of 65 alcoholics and 73 controls of European descent, and identified 129 genes that showed altered expression (FDR < 0.05) in subjects with alcohol dependence. Differentially expressed genes were enriched for pathways related to interferon signaling and Growth Arrest and DNA Damage-inducible 45 (GADD45) signaling. A coexpression module (thistle2) identified by weighted gene co-expression network analysis (WGCNA) was significantly correlated with alcohol dependence, alcohol consumption, and AUDIT scores. Genes in the thistle2 module were enriched with genes related to calcium signaling pathways and showed significant downregulation of these pathways, as well as enrichment for biological processes related to nicotine response and opioid signaling. A second module (brown4) showed significant upregulation of pathways related to immune signaling. Expression quantitative trait loci (eQTLs) for genes in the brown4 module were also enriched for genetic associations with alcohol dependence and alcohol consumption in large genome-wide studies included in the Psychiatric Genetic Consortium and the UK Biobank's alcohol consumption dataset. By leveraging multi-omics data, this transcriptome analysis has identified genes and biological pathways that could provide insight for identifying therapeutic targets for alcohol dependence.