scholarly journals Identifying functional targets from transcription factor binding data using SNP perturbation

2018 ◽  
Author(s):  
Jing Xiang ◽  
Seyoung Kim
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Graphical Models ◽  
Target Genes ◽  
Expression Data ◽  
Genome Wide ◽  
Binding Data ◽  
A Genome ◽  
Trait Locus ◽  
Locus Mapping

AbstractTranscription factors (TFs) play a key role in transcriptional regulation by binding to DNA to initiate the transcription of target genes. Techniques such as ChIP-seq and DNase-seq provide a genome-wide map of TF binding sites but do not offer direct evidence that those bindings affect gene expression. Thus, these assays are often followed by TF perturbation experiments to determine functional binding that leads to changes in target gene expression. However, such perturbation experiments are costly and time-consuming, and have a well-known limitation that they cannot distinguish between direct and indirect targets. In this study, we propose to use the naturally occurring perturbation of gene expression by genetic variation captured in population SNP and expression data to determine functional targets from TF binding data. We introduce a computational methodology based on probabilistic graphical models for isolating the perturbation effect of each individual SNP, given a large number of SNPs across genomes perturbing the expression of all genes simultaneously. Our computational approach constructs a gene regulatory network over TFs, their functional targets, and further downstream genes, while at the same time identifying the SNPs perturbing this network. Compared to experimental perturbation, our approach has advantages of identifying direct and indirect targets, and leveraging existing data collected for expression quantitative trait locus mapping, a popular approach for studying the genetic architecture of expression. We apply our approach to determine functional targets from the TF binding data for a lymphoblastoid cell line from the ENCODE Project, using SNP and expression data from the HapMap 3 and 1000 Genomes Project samples. Our results show that from TF binding data, functional target genes can be determined by SNP perturbation of various aspects that impact transcriptional regulation, such as TF concentration and TF-DNA binding affinity.

scholarly journals A Genome-Wide Integrative Association Study of DNA Methylation and Gene Expression Data and Later Life Cognitive Functioning in Monozygotic Twins

2020 ◽  
Vol 14 ◽  
Author(s):  
Mette Soerensen ◽  
Dominika Marzena Hozakowska-Roszkowska ◽  
Marianne Nygaard ◽  
Martin J. Larsen ◽  
Veit Schwämmle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cognitive Functioning ◽  
Association Study ◽  
Gene Expression Data ◽  
Monozygotic Twins ◽  
Later Life ◽  
Expression Data ◽  
Genome Wide ◽  
A Genome

scholarly journals Identification of unique venous thromboembolism-susceptibility variants in African-Americans

2017 ◽  
Vol 117 (04) ◽  
pp. 758-768 ◽  
Author(s):  
Sebastian Armasu ◽  
Bryan McCauley ◽  
Iftikhar Kullo ◽  
Hugues Sicotte ◽  
Jyotishman Pathak ◽  
...  
Keyword(s):  
Gene Expression ◽  
Venous Thromboembolism ◽  
African Americans ◽  
Differential Expression ◽  
White Women ◽  
Genome Wide Association Study ◽  
Expression Data ◽  
Significant Differential Expression ◽  
Genome Wide ◽  
A Genome

SummaryTo identify novel single nucleotide polymorphisms (SNPs) associated with venous thromboembolism (VTE) in African-Americans (AAs), we performed a genome-wide association study (GWAS) of VTE in AAs using the Electronic Medical Records and Genomics (eMERGE) Network, comprised of seven sites each with DNA biobanks (total ~39,200 unique DNA samples) with genome-wide SNP data (imputed to 1000 Genomes Project cosmopolitan reference panel) and linked to electronic health records (EHRs). Using a validated EHR-driven phenotype extraction algorithm, we identified VTE cases and controls and tested for an association between each SNP and VTE using unconditional logistic regression, adjusted for age, sex, stroke, site-platform combination and sickle cell risk genotype. Among 393 AA VTE cases and 4,941 AA controls, three intragenic SNPs reached genome-wide significance: LEMD3 rs138916004 (OR=3.2; p=1.3E-08), LY86 rs3804476 (OR=1.8; p=2E-08) and LOC100130298 rs142143628 (OR=4.5; p=4.4E-08); all three SNPs validated using internal cross-validation, parametric bootstrap and meta-analysis methods. LEMD3 rs138916004 and LOC100130298 rs142143628 are only present in Africans (1000G data). LEMD3 showed a significant differential expression in both NCBI Gene Expression Omnibus (GEO) and the Mayo Clinic gene expression data, LOC100130298 showed a significant differential expression only in the GEO expression data, and LY86 showed a significant differential expression only in the Mayo expression data. LEMD3 encodes for an antagonist of TGF-β-induced cell proliferation arrest. LY86 encodes for MD-1 which down-regulates the pro-inflammatory response to lipopolysaccharide; LY86 variation was previously associated with VTE in white women; LOC100130298 is a non-coding RNA gene with unknown regulatory activity in gene expression and epigenetics.Supplementary Material to this article is available online at www.thrombosis-online.com.

scholarly journals Genome-Wide Analysis of Glucocorticoid-Responsive Transcripts in the Hypothalamic Paraventricular Region of Male Rats

Endocrinology ◽  
2018 ◽  
Vol 160 (1) ◽  
pp. 38-54 ◽  
Author(s):  
Keiichi Itoi ◽  
Ikuko Motoike ◽  
Ying Liu ◽  
Sam Clokie ◽  
Yasumasa Iwasaki ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Receptor Gene ◽  
Male Rats ◽  
Regulatory Mechanisms ◽  
High Dose ◽  
Sequencing Analysis ◽  
Reverse Transcription Pcr ◽  
Genome Wide ◽  
A Genome

Abstract Glucocorticoids (GCs) are essential for stress adaptation, acting centrally and in the periphery. Corticotropin-releasing factor (CRF), a major regulator of adrenal GC synthesis, is produced in the paraventricular nucleus of the hypothalamus (PVH), which contains multiple neuroendocrine and preautonomic neurons. GCs may be involved in diverse regulatory mechanisms in the PVH, but the target genes of GCs are largely unexplored except for the CRF gene (Crh), a well-known target for GC negative feedback. Using a genome-wide RNA-sequencing analysis, we identified transcripts that changed in response to either high-dose corticosterone (Cort) exposure for 12 days (12-day high Cort), corticoid deprivation for 7 days (7-day ADX), or acute Cort administration. Among others, canonical GC target genes were upregulated prominently by 12-day high Cort. Crh was upregulated or downregulated most prominently by either 7-day ADX or 12-day high Cort, emphasizing the recognized feedback effects of GC on the hypothalamic-pituitary-adrenal (HPA) axis. Concomitant changes in vasopressin and apelin receptor gene expression are likely to contribute to HPA repression. In keeping with the pleotropic cellular actions of GCs, 7-day ADX downregulated numerous genes of a broad functional spectrum. The transcriptome response signature differed markedly between acute Cort injection and 12-day high Cort. Remarkably, six immediate early genes were upregulated 1 hour after Cort injection, which was confirmed by quantitative reverse transcription PCR and semiquantitative in situ hybridization. This study may provide a useful database for studying the regulatory mechanisms of GC-dependent gene expression and repression in the PVH.

scholarly journals A compendium of uniformly processed human gene expression and splicing quantitative trait loci

2021 ◽  
Vol 53 (9) ◽  
pp. 1290-1299
Author(s):  
Nurlan Kerimov ◽  
James D. Hayhurst ◽  
Kateryna Peikova ◽  
Jonathan R. Manning ◽  
Peter Walter ◽  
...  
Keyword(s):  
Gene Expression ◽  
Quantitative Trait ◽  
Target Genes ◽  
Genome Wide Association Study ◽  
Cell Types ◽  
Summary Statistics ◽  
Genome Wide ◽  
Cell Type Specific ◽  
Trait Locus ◽  
Complex Human Traits

AbstractMany gene expression quantitative trait locus (eQTL) studies have published their summary statistics, which can be used to gain insight into complex human traits by downstream analyses, such as fine mapping and co-localization. However, technical differences between these datasets are a barrier to their widespread use. Consequently, target genes for most genome-wide association study (GWAS) signals have still not been identified. In the present study, we present the eQTL Catalogue (https://www.ebi.ac.uk/eqtl), a resource of quality-controlled, uniformly re-computed gene expression and splicing QTLs from 21 studies. We find that, for matching cell types and tissues, the eQTL effect sizes are highly reproducible between studies. Although most QTLs were shared between most bulk tissues, we identified a greater diversity of cell-type-specific QTLs from purified cell types, a subset of which also manifested as new disease co-localizations. Our summary statistics are freely available to enable the systematic interpretation of human GWAS associations across many cell types and tissues.

scholarly journals DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Ieva Rauluseviciute ◽  
Finn Drabløs ◽  
Morten Beck Rye
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Dna Methylation ◽  
Epigenetic Regulation ◽  
Normal Tissue ◽  
Expression Profiles ◽  
Expression Data ◽  
Dna Hypermethylation ◽  
Genome Wide ◽  
A Genome

Abstract Background Prostate cancer (PCa) has the highest incidence rates of cancers in men in western countries. Unlike several other types of cancer, PCa has few genetic drivers, which has led researchers to look for additional epigenetic and transcriptomic contributors to PCa development and progression. Especially datasets on DNA methylation, the most commonly studied epigenetic marker, have recently been measured and analysed in several PCa patient cohorts. DNA methylation is most commonly associated with downregulation of gene expression. However, positive associations of DNA methylation to gene expression have also been reported, suggesting a more diverse mechanism of epigenetic regulation. Such additional complexity could have important implications for understanding prostate cancer development but has not been studied at a genome-wide scale. Results In this study, we have compared three sets of genome-wide single-site DNA methylation data from 870 PCa and normal tissue samples with multi-cohort gene expression data from 1117 samples, including 532 samples where DNA methylation and gene expression have been measured on the exact same samples. Genes were classified according to their corresponding methylation and expression profiles. A large group of hypermethylated genes was robustly associated with increased gene expression (UPUP group) in all three methylation datasets. These genes demonstrated distinct patterns of correlation between DNA methylation and gene expression compared to the genes showing the canonical negative association between methylation and expression (UPDOWN group). This indicates a more diversified role of DNA methylation in regulating gene expression than previously appreciated. Moreover, UPUP and UPDOWN genes were associated with different compartments — UPUP genes were related to the structures in nucleus, while UPDOWN genes were linked to extracellular features. Conclusion We identified a robust association between hypermethylation and upregulation of gene expression when comparing samples from prostate cancer and normal tissue. These results challenge the classical view where DNA methylation is always associated with suppression of gene expression, which underlines the importance of considering corresponding expression data when assessing the downstream regulatory effect of DNA methylation.

scholarly journals Novel Mechanism of Positive versus Negative Regulation by Thyroid Hormone Receptor β1 (TRβ1) Identified by Genome-wide Profiling of Binding Sites in Mouse Liver

2013 ◽  
Vol 289 (3) ◽  
pp. 1313-1328 ◽  
Author(s):  
Preeti Ramadoss ◽  
Brian J. Abraham ◽  
Linus Tsai ◽  
Yiming Zhou ◽  
Ricardo H. Costa-e-Sousa ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Thyroid Hormone ◽  
Binding Sites ◽  
Hormone Receptor ◽  
Target Genes ◽  
Thyroid Hormone Receptor ◽  
Negative Regulation ◽  
Genome Wide

Triiodothyronine (T3) regulates key metabolic processes in the liver through the thyroid hormone receptor, TRβ1. However, the number of known target genes directly regulated by TRβ1 is limited, and the mechanisms by which positive and especially negative transcriptional regulation occur are not well understood. To characterize the TRβ1 cistrome in vivo, we expressed a biotinylated TRβ1 in hypo- and hyperthyroid mouse livers, used ChIP-seq to identify genomic TRβ1 targets, and correlated these data with gene expression changes. As with other nuclear receptors, the majority of TRβ1 binding sites were not in proximal promoters but in the gene body of known genes. Remarkably, T3 can dictate changes in TRβ1 binding, with strong correlation to T3-induced gene expression changes, suggesting that differential TRβ1 binding regulates transcriptional outcome. Additionally, DR-4 and DR-0 motifs were significantly enriched at binding sites where T3 induced an increase or decrease in TRβ1 binding, respectively, leading to either positive or negative regulation by T3. Taken together, the results of this study provide new insights into the mechanisms of transcriptional regulation by TRβ1 in vivo.

scholarly journals Genome-Wide Phylogenetic Analysis, Expression Pattern, and Transcriptional Regulatory Network of the Pig C/EBP Gene Family

2021 ◽  
Vol 17 ◽  
pp. 117693432110413
Author(s):  
Chaoxin Zhang ◽  
Tao Wang ◽  
Tongyan Cui ◽  
Shengwei Liu ◽  
Bing Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Phylogenetic Analysis ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Genome Wide ◽  
A Genome

The CCAAT/enhancer binding protein (C/EBP) transcription factors (TFs) regulate many important biological processes, such as energy metabolism, inflammation, cell proliferation etc. A genome-wide gene identification revealed the presence of a total of 99 C/EBP genes in pig and 19 eukaryote genomes. Phylogenetic analysis showed that all C/EBP TFs were classified into 6 subgroups named C/EBPα, C/EBPβ, C/EBPδ, C/EBPε, C/EBPγ, and C/EBPζ. Gene expression analysis showed that the C/EBPα, C/EBPβ, C/EBPδ, C/EBPγ, and C/EBPζ genes were expressed ubiquitously with inconsistent expression patterns in various pig tissues. Moreover, a pig C/EBP regulatory network was constructed, including C/EBP genes, TFs and miRNAs. A total of 27 feed-forward loop (FFL) motifs were detected in the pig C/EBP regulatory network. Based on the RNA-seq data, gene expression patterns related to FFL sub-network were analyzed in 27 adult pig tissues. Certain FFL motifs may be tissue specific. Functional enrichment analysis indicated that C/EBP and its target genes are involved in many important biological pathways. These results provide valuable information that clarifies the evolutionary relationships of the C/EBP family and contributes to the understanding of the biological function of C/EBP genes.

scholarly journals A genome-wide linkage study of GAW15 gene expression data

2007 ◽  
Vol 1 (Suppl 1) ◽  
pp. S87 ◽  
Author(s):  
Donghui Kan ◽  
Richard Cooper ◽  
Xiaofeng Zhu
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Linkage Study ◽  
Expression Data ◽  
Genome Wide ◽  
A Genome

Functional and Molecular Impact Of Dp1-Dependent Alternate Splicing In Multiple Myeloma

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 1845-1845
Author(s):  
Mariateresa Fulciniti ◽  
Manoj Bashin ◽  
Mehmet Kemal Samur ◽  
Rajya Bandi ◽  
Parantu K Shah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Clinical Outcome ◽  
Binding Sites ◽  
Rna Splicing ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Expression Data ◽  
Alternate Splicing ◽  
Genome Wide

Abstract Transcription factors (TFs) are important oncogenic regulator and are altered during tumor initiation and progression. Our oncogenomic analysis of gene expression data from large clinically-annotated patient samples identified TF Dp1 as one of the most important gene affecting both overall and event-free survival in multiple myeloma (MM). Elevated Dp1 expression was predictive of adverse clinical outcome, independent of Dp1 protein partners, E2Fs and RB, suggesting direct impact of Dp1 and providing the rationale to further evaluate its specific role in MM. We have observed high level of Dp1 expression and activity in MM cells which was further induced after interaction with bone marrow stromal cells (BMSC). Moreover, Dp1 knock-down using specific sh-RNA decreased MM cell growth in 5 MM cell lines with different genetic background, with a concomitant G1 arrest and late induction of apoptosis. These data suggest a role for Dp1 in MM cell proliferation and survival and established a rationale to identify its molecular impact. We have further characterized Dp1 activity using chromatin immunoprecipitation with Dp1 or E2F1 specific antibody followed by genome wide sequencing (ChIP-Seq) to identify Dp1-binding regions in MM. We have identified 2783 exclusive Dp1 binding regions in two MM cell lines. Examination of Dp1 and E2F1 binding revealed that Dp1 co-occupies 65% of the binding sites with E2F1. The DAVID gene set enrichment analysis showed that identified genes were related to cell cycle, as well as to transcriptional and translational processes. To assess the functional consequences of Dp1 DNA binding, the ChIP-Seq data were supplemented with gene expression profile of MM1S cells following shRNA-mediated Dp1 and E2F knock-downs. Integrated analysis incorporating ChIP-seq and expression data identified Dp1 response program in MM. 805 (46%) of 1752 differentially expressed genes also have binding sites for Dp1 and likely are direct transcriptional targets of Dp1 in MM. Enrichment analysis of direct targets revealed that the most strongly enriched pathways for both Dp1 and E2F1 genes combined were related to the cell cycle, especially DNA replication, repair, and metabolism. Interestingly, pathway analysis identified ‘‘regulation of RNA metabolic processes’’ (40 target genes), ‘‘RNA processing’’ (93 target genes) ‘‘RNA splicing’’ (95 genes), and ‘‘RNA binding’’ (53 genes) as statistically significant RNA-related categories enriched among Dp1 target genes, suggests role of Dp1 in RNA splicing. Based on our previous data showing that dysregulated alternate splicing (AS) has significant impact on overall clinical outcome MM, we evaluated the expression of Dp1-modulated splicing factors in our clinically annotated cohort of MM patients and 5 normal PCs. We identified 23 SFs upregulated in MM compared to normal plasma cells. Importantly, the increased expression of 12 of these SFs was linked with poor prognosis in this cohort of myeloma patients. Our data show for the first time that SFs are upregulated in myeloma and link to clinical outcome. To evaluate the impact of Dp1 on alternate splicing (AS), we performed genome-wide analysis of alternate splicing in total RNA from Dp1 silenced MM1S cells using Human Exon1 ST arrays. Splicing profiles showed that Dp1 knock down causes widespread changes in AS. We have identified 3683 genes whose one exon has splicing index more than 1.5 in in shDP1 compared to control pLKO.1-transduced MM1S cells, suggesting impact of Dp1 silencing on alternate splicing. We are now evaluating impact of a peptide able to disrupt Dp1-E2F1 binding with consequent effect on MM cell growth and alternate splicing. In conclusion, our investigation showed that the Dp1/E2F1 signaling pathway plays significant role in myeloma and can directly activate transcription of specific SFs with effect on alternate splicing and potential functional, clinical and therapeutic implications in myeloma. Disclosures: No relevant conflicts of interest to declare.

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