scholarly journals Co-expression networks reveal the tissue-specific regulation of transcription and splicing

2016 ◽  
Author(s):  
Ashis Saha ◽  
Yungil Kim ◽  
Ariel D. H. Gewirtz ◽  
Brian Jo ◽  
Chuan Gao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Rna Binding ◽  
Expression Patterns ◽  
Regulation Of Transcription ◽  
Sequencing Data ◽  
Tissue Specific ◽  
Human Transcriptome ◽  
Network Analyses ◽  
Specific Regulation

AbstractGene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of regulatory genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single or small sets of tissues. Here, we have reconstructed networks that capture a much more complete set of regulatory relationships, specifically including regulation of relative isoform abundance and splicing, and tissue-specific connections unique to each of a diverse set of tissues. Using the Genotype-Tissue Expression (GTEx) project v6 RNA-sequencing data across 44 tissues in 449 individuals, we evaluated shared and tissue-specific network relationships. First, we developed a framework called Transcriptome Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the complex interplay between the regulation of splicing and transcription. We built TWNs for sixteen tissues, and found that hubs with isoform node neighbors in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome, and providing a set of candidate shared and tissue-specific regulatory hub genes. Next, we used a Bayesian biclustering model that identifies network edges between genes with co-expression in a single tissue to reconstruct tissue-specific networks (TSNs) for 27 distinct GTEx tissues and for four subsets of related tissues. Using both TWNs and TSNs, we characterized gene co-expression patterns shared across tissues. Finally, we found genetic variants associated with multiple neighboring nodes in our networks, supporting the estimated network structures and identifying 33 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships between genes in the human transcriptome, including tissue-specificity of gene co-expression, regulation of splicing, and the coordinated impact of genetic variation on transcription.

scholarly journals Integrative genomics reveals paths to sex dimorphism in Salix purpurea L

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Brennan Hyden ◽  
Craig H. Carlson ◽  
Fred E. Gouker ◽  
Jeremy Schmutz ◽  
Kerrie Barry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Sex Determination ◽  
Bisulfite Sequencing ◽  
Epigenetic Modification ◽  
Small Rna Sequencing ◽  
Regulation Of Transcription ◽  
Eqtl Analysis ◽  
Sex Dimorphism ◽  
Network Analyses ◽  
Salix Purpurea

AbstractSex dimorphism and gene expression were studied in developing catkins in 159 F2 individuals from the bioenergy crop Salix purpurea, and potential mechanisms and pathways for regulating sex development were explored. Differential expression, eQTL, bisulfite sequencing, and network analysis were used to characterize sex dimorphism, detect candidate master regulator genes, and identify pathways through which the sex determination region (SDR) may mediate sex dimorphism. Eleven genes are presented as candidates for master regulators of sex, supported by gene expression and network analyses. These include genes putatively involved in hormone signaling, epigenetic modification, and regulation of transcription. eQTL analysis revealed a suite of transcription factors and genes involved in secondary metabolism and floral development that were predicted to be under direct control of the sex determination region. Furthermore, data from bisulfite sequencing and small RNA sequencing revealed strong differences in expression between males and females that would implicate both of these processes in sex dimorphism pathways. These data indicate that the mechanism of sex determination in Salix purpurea is likely different from that observed in the related genus Populus. This further demonstrates the dynamic nature of SDRs in plants, which involves a multitude of mechanisms of sex determination and a high rate of turnover.

scholarly journals Compendium of Methods to Uncover RNA-Protein Interactions In Vivo

2021 ◽  
Vol 4 (1) ◽  
pp. 22
Author(s):  
Mrinmoyee Majumder ◽  
Viswanathan Palanisamy
Keyword(s):  
Gene Expression ◽  
Protein Interactions ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Expression Patterns ◽  
Control Of Gene Expression ◽  
Regulatory Pathways ◽  
Advantages And Disadvantages ◽  
Protein Nucleic Acid

Control of gene expression is critical in shaping the pro-and eukaryotic organisms’ genotype and phenotype. The gene expression regulatory pathways solely rely on protein–protein and protein–nucleic acid interactions, which determine the fate of the nucleic acids. RNA–protein interactions play a significant role in co- and post-transcriptional regulation to control gene expression. RNA-binding proteins (RBPs) are a diverse group of macromolecules that bind to RNA and play an essential role in RNA biology by regulating pre-mRNA processing, maturation, nuclear transport, stability, and translation. Hence, the studies aimed at investigating RNA–protein interactions are essential to advance our knowledge in gene expression patterns associated with health and disease. Here we discuss the long-established and current technologies that are widely used to study RNA–protein interactions in vivo. We also present the advantages and disadvantages of each method discussed in the review.

FC 011KIDNEYNETWORK: USING KIDNEY DERIVED GENE EXPRESSION DATA TO PREDICT AND PRIORITIZE NOVEL GENES INVOLVED IN KIDNEY DISEASE

2021 ◽  
Vol 36 (Supplement_1) ◽  
Author(s):  
Floranne Boulogne ◽  
Laura Claus ◽  
Henry Wiersma ◽  
Roy Oelen ◽  
Floor Schukking ◽  
...  
Keyword(s):  
Gene Expression ◽  
Kidney Disease ◽  
Candidate Gene ◽  
Exome Sequencing ◽  
Rna Sequencing ◽  
Expression Patterns ◽  
Genetic Diagnosis ◽  
Specific Gene ◽  
Sequencing Data ◽  
Exome Sequencing Data

Abstract Background and Aims Genetic testing in patients with suspected hereditary kidney disease does not always reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes that are not known to be involved in kidney disease, which makes it difficult to prioritize and interpret the relevance of these variants. As such, there is a clear need for methods that predict the phenotypic consequences of gene expression in a way that is as unbiased as possible. To help identify candidate genes we have developed KidneyNetwork, in which tissue-specific expression is utilized to predict kidney-specific gene functions. Method We combined gene co-expression in 878 publicly available kidney RNA-sequencing samples with the co-expression of a multi-tissue RNA-sequencing dataset of 31,499 samples to build KidneyNetwork. The expression patterns were used to predict which genes have a kidney-related function, and which (disease) phenotypes might be caused when these genes are mutated. By integrating the information from the HPO database, in which known phenotypic consequences of disease genes are annotated, with the gene co-expression network we obtained prediction scores for each gene per HPO term. As proof of principle, we applied KidneyNetwork to prioritize variants in exome-sequencing data from 13 kidney disease patients without a genetic diagnosis. Results We assessed the prediction performance of KidneyNetwork by comparing it to GeneNetwork, a multi-tissue co-expression network we previously developed. In KidneyNetwork, we observe a significantly improved prediction accuracy of kidney-related HPO-terms, as well as an increase in the total number of significantly predicted kidney-related HPO-terms (figure 1). To examine its clinical utility, we applied KidneyNetwork to 13 patients with a suspected hereditary kidney disease without a genetic diagnosis. Based on the HPO terms “Renal cyst” and “Hepatic cysts”, combined with a list of potentially damaging variants in one of the undiagnosed patients with mild ADPKD/PCLD, we identified ALG6 as a new candidate gene. ALG6 bears a high resemblance to other genes implicated in this phenotype in recent years. Through the 100,000 Genomes Project and collaborators we identified three additional patients with kidney and/or liver cysts carrying a suspected deleterious variant in ALG6. Conclusion We present KidneyNetwork, a kidney specific co-expression network that accurately predicts what genes have kidney-specific functions and may result in kidney disease. Gene-phenotype associations of genes unknown for kidney-related phenotypes can be predicted by KidneyNetwork. We show the added value of KidneyNetwork by applying it to exome sequencing data of kidney disease patients without a molecular diagnosis and consequently we propose ALG6 as a promising candidate gene. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes to better understand kidney physiology and pathophysiology. Acknowledgments This research was made possible through access to the data and findings generated by the 100,000 Genomes Project; http://www.genomicsengland.co.uk.

scholarly journals Global Histone H3 Lysine 4 Trimethylation (H3K4me3) Landscape Changes in Response to TGFβ

2021 ◽  
Vol 14 ◽  
pp. 251686572110517
Author(s):  
Ankit Naik ◽  
Nidhi Dalpatraj ◽  
Noopur Thakur
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Expression Patterns ◽  
Histone H3 ◽  
Epigenetic Mechanism ◽  
Stable Gene ◽  
Regulation Of Transcription ◽  
Functional Categories ◽  
Positive Regulation ◽  
Histone H4 Acetylation

TGFβ expression acts as a biomarker of poor prognosis in prostate cancer. It plays a dual functional role in prostate cancer. In the early stages of the tumor, it acts as a tumor suppressor while at the later stages of tumor development, it promotes metastasis. The molecular mechanisms of action of TGFβ are largely understood through the canonical and non-canonical signal transduction pathways. Our understanding of the mechanisms that establish transient TGFβ stimulation into stable gene expression patterns remains incomplete. Epigenetic marks like histone H3 modifications are directly linked with gene expression and they play an important role in tumorigenesis. In this report, we performed chromatin immunoprecipitation-sequencing (ChIP-Seq) to identify the genome-wide regions that undergo changes in histone H3 Lysine 4 trimethylation (H3K4me3) occupancy in response to TGFβ stimulation. We also show that TGFβ stimulation can induce acute epigenetic changes through the modulation of H3K4me3 signals at genes belonging to special functional categories in prostate cancer. TGFβ induces the H3K4me3 on its own ligands like TGFβ, GDF1, INHBB, GDF3, GDF6, BMP5 suggesting a positive feedback loop. The majority of genes were found to be involved in the positive regulation of transcription from the RNA polymerase II promoter in response to TGFβ. Other functional categories were intracellular protein transport, brain development, EMT, angiogenesis, antigen processing, antigen presentation via MHC class II, lipid transport, embryo development, histone H4 acetylation, positive regulation of cell cycle arrest, and genes involved in mitotic G2 DNA damage checkpoints. Our results link TGFβ stimulation to acute changes in gene expression through an epigenetic mechanism. These findings have broader implications on epigenetic bases of acute gene expression changes caused by growth factor stimulation.

scholarly journals A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

2019 ◽  
Author(s):  
Tom G Richardson ◽  
Gibran Hemani ◽  
Tom R Gaunt ◽  
Caroline L Relton ◽  
George Davey Smith
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Drug Repositioning ◽  
Association Studies ◽  
Thyroid Tissue ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide

AbstractBackgroundDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. By applying the principles of Mendelian randomization, we have undertaken a systematic analysis to evaluate transcriptome-wide associations between gene expression across 48 different tissue types and 395 complex traits.ResultsOverall, we identified 100,025 gene-trait associations based on conventional genome-wide corrections (P < 5 × 10−08) that also provided evidence of genetic colocalization. These results indicated that genetic variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. We identified many examples of tissue-specific effects, such as genetically-predicted TPO, NR3C2 and SPATA13 expression only associating with thyroid disease in thyroid tissue. Additionally, FBN2 expression was associated with both cardiovascular and lung function traits, but only when analysed in heart and lung tissue respectively.We also demonstrate that conducting phenome-wide evaluations of our results can help flag adverse on-target side effects for therapeutic intervention, as well as propose drug repositioning opportunities. Moreover, we find that exploring the tissue-dependency of associations identified by genome-wide association studies (GWAS) can help elucidate the causal genes and tissues responsible for effects, as well as uncover putative novel associations.ConclusionsThe atlas of tissue-dependent associations we have constructed should prove extremely valuable to future studies investigating the genetic determinants of complex disease. The follow-up analyses we have performed in this study are merely a guide for future research. Conducting similar evaluations can be undertaken systematically at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

scholarly journals An integrative multi-omics approach in Sjögren’s Syndrome identifies novel genetic drivers with regulatory function and disease-specificity

2020 ◽  
Author(s):  
María Teruel ◽  
Guillermo Barturen ◽  
Manuel Martínez-Bueno ◽  
Miguel Barroso ◽  
Olivia Castelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Sjögren’S Syndrome ◽  
Genetic Variants ◽  
Sjögren's Syndrome ◽  
Expression Patterns ◽  
Sjogren’S Syndrome ◽  
Sjogren's Syndrome ◽  
Regulatory Function ◽  
Sjögren‘S Syndrome

ABSTRACTPrimary Sjögren’s syndrome (SS) is a systemic autoimmune disease characterized by lymphocytic infiltration and damage of exocrine salivary and lacrimal glands. The etiology of SS is complex with environmental triggers and genetic factors involved. By conducting an integrated multi-omics study we identified vast coordinated hypomethylation and overexpression effects, that also exhibit increased variability, in many already known IFN-regulated genes. We report a novel epigenetic signature characterized by increased DNA methylation levels in a large number of novel genes enriched in pathways such as collagen metabolism and extracellular matrix organization. We identified new genetic variants associated with SS that mediate their risk by altering DNA methylation or gene expression patterns, as well as disease-interacting genetic variants that exhibit regulatory function only in the SS population. Our study sheds new light on the interaction between genetics, DNA methylation, gene expression and SS, and contributes to elucidate the genetic architecture of gene regulation in an autoimmune population.

scholarly journals Development of cDNA normalization system and preliminary transcription analysis of KCS genes in apple tissues

2011 ◽  
Vol 59 (3) ◽  
pp. 9-12 ◽  
Author(s):  
Zsolt Albert ◽  
Cs. Deák ◽  
A. Miskó ◽  
M. Tóth ◽  
I. Papp
Keyword(s):  
Gene Expression ◽  
Expression System ◽  
Expression Patterns ◽  
Housekeeping Genes ◽  
Apple Fruit ◽  
Rt Pcr ◽  
Specific Primers ◽  
Specific Expression ◽  
Transcription Analysis ◽  
Tissue Specific

Wax production is an important aspect of apple (Malus domestica Borkh.) fruit development from both theoretical and practical point of views. The complex molecular mechanism that controls wax biosynthesis is still widely unknown but many studies focused on this topic. We aimed to develop further the experimental framework of these efforts with a description of an improved reference genes expression system. Results in the literature show that similarities exist among the expression of some housekeeping genes of different plant species. Based on these considerations and on gene expression data from Arabidopsis thaliana, some genes in apple were assigned for analysis. EST sequences of apple were used to design specific primers for RT-PCR experiments. Isolation of intact RNA from different apple tissues and performing RT-PCR reaction were also key point in obtaining expression patterns. To monitor DNA contamination of the RNA samples, specific primers were used that amplify intron-containing sequences from the cDNA. We found that actin primers can be used for the detection of intron containing genomic DNA, and tubulin primers are good internal controls in RT-PCR experiments. We were able to make a difference between tissue-specific and tissue-independent gene-expression, furthermore we found tissue specific differences between the expression patterns of candidate genes, that are potentially involved in wax-biosynthesis. Our results show that KCS1 and KCS4 are overexpressed in the skin tissue, this could mean that these genes have skin-specific expression in apple fruit.

scholarly journals GSDMA drives the most replicated association with asthma in naïve CD4+ T cells

2019 ◽  
Author(s):  
Anne-Marie Madore ◽  
Lucile Pain ◽  
Anne-Marie Boucher-Lafleur ◽  
Jolyane Meloche ◽  
Andréanne Morin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
T Cells ◽  
Genetic Variants ◽  
Immune Cell ◽  
Cell Types ◽  
Sequencing Data ◽  
Opposite Pattern ◽  
Genetic Mechanisms ◽  
New Gene

AbstractBackgroundThe 17q12-21 locus is the most replicated association with asthma. However, no study had described the genetic mechanisms underlying this association considering all genes of the locus in immune cell samples isolated from asthmatic and non-asthmatic individuals.ObjectiveThis study takes benefit of samples from naïve CD4+ T cells and eosinophils isolated from the same 200 individuals to describe specific interactions between genetic variants, gene expression and DNA methylation levels for the 17q12-21 asthma locus.Methods and ResultsAfter isolation of naïve CD4+ T cells and eosinophils from blood samples, next generation sequencing was used to measure DNA methylation levels and gene expression counts. Genetic interactions were then evaluated considering genetic variants from imputed genotype data. In naïve CD4+ T cells but not eosinophils, 20 SNPs in the fourth and fifth haplotype blocks modulated both GSDMA expression and methylation levels, showing an opposite pattern of allele frequencies and expression counts in asthmatics compared to controls. Moreover, negative correlations have been measured between methylation levels of CpG sites located within the 1.5 kb region from the transcription start site of GSDMA and its expression counts.ConclusionAvailability of sequencing data from two key cell types isolated from asthmatic and non-asthmatic individuals allowed identifying a new gene in naïve CD4+ T cells that drives the association with the 17q12-21 locus, leading to a better understanding of the genetic mechanisms taking place in it.

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