scholarly journals Understanding Tissue-specific Gene Regulation

2017 ◽  
Author(s):  
Abhijeet R. Sonawane ◽  
John Platig ◽  
Maud Fagny ◽  
Cho-Yi Chen ◽  
Joseph N. Paulson ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcriptional Control ◽  
Tissue Specificity ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Tissue Specific ◽  
Network Nodes ◽  
Transcription Factor Expression

Although all human tissues carry out common processes, tissues are distinguished by gene expres-sion patterns, implying that distinct regulatory programs control tissue-specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have higher tissue-specificity than network nodes (genes) and that regulating nodes (transcription factors) are less likely to be expressed in a tissue-specific manner as compared to their targets (genes). Gene set enrichment analysis of network targeting also indicates that regulation of tissue-specific function is largely independent of transcription factor expression. In addition, tissue-specific genes are not highly targeted in their corresponding tissue-network. However, they do assume bottleneck positions due to variability in transcription factor targeting and the influence of non-canonical regulatory interactions. These results suggest that tissue-specificity is driven by context-dependent regulatory paths, providing transcriptional control of tissue-specific processes.

scholarly journals Identification of key tissue-specific, biological processes by integrating enhancer information in maize gene regulatory networks

2020 ◽  
Author(s):  
Maud Fagny ◽  
Marieke Lydia Kuijjer ◽  
Maike Stam ◽  
Johann Joets ◽  
Olivier Turc ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Binding Sites ◽  
Regulatory Network ◽  
Tissue Specificity ◽  
Target Genes ◽  
Specific Gene ◽  
Tissue Specific ◽  
Genome Wide ◽  
Gene Regulatory

AbstractEnhancers are important regulators of gene expression during numerous crucial processes including tissue differentiation across development. In plants, their recent molecular characterization revealed their capacity to activate the expression of several target genes through the binding of transcription factors. Nevertheless, identifying these target genes at a genome-wide level remains a challenge, in particular in species with large genomes, where enhancers and target genes can be hundreds of kilobases away. Therefore, the contribution of enhancers to regulatory network is still poorly understood in plants. In this study, we investigate the enhancer-driven regulatory network of two maize tissues at different stages: leaves at seedling stage and husks (bracts) at flowering. Using a systems biology approach, we integrate genomic, epigenomic and transcriptomic data to model the regulatory relationship between transcription factors and their potential target genes. We identify regulatory modules specific to husk and V2-IST, and show that they are involved in distinct functions related to the biology of each tissue. We evidence enhancers exhibiting binding sites for two distinct transcription factor families (DOF and AP2/ERF) that drive the tissue-specificity of gene expression in seedling immature leaf and husk. Analysis of the corresponding enhancer sequences reveals that two different transposable element families (TIR transposon Mutator and MITE Pif/Harbinger) have shaped the regulatory network in each tissue, and that MITEs have provided new transcription factor binding sites that are involved in husk tissue-specificity.SignificanceEnhancers play a major role in regulating tissue-specific gene expression in higher eukaryotes, including angiosperms. While molecular characterization of enhancers has improved over the past years, identifying their target genes at the genome-wide scale remains challenging. Here, we integrate genomic, epigenomic and transcriptomic data to decipher the tissue-specific gene regulatory network controlled by enhancers at two different stages of maize leaf development. Using a systems biology approach, we identify transcription factor families regulating gene tissue-specific expression in husk and seedling leaves, and characterize the enhancers likely to be involved. We show that a large part of maize enhancers is derived from transposable elements, which can provide novel transcription factor binding sites crucial to the regulation of tissue-specific biological functions.

scholarly journals TS-GOEA: a web tool for tissue-specific gene set enrichment analysis based on gene ontology

2019 ◽  
Vol 20 (S18) ◽  
Author(s):  
Jiajie Peng ◽  
Guilin Lu ◽  
Hansheng Xue ◽  
Tao Wang ◽  
Xuequn Shang
Keyword(s):  
Gene Ontology ◽  
Enrichment Analysis ◽  
Experimental Results ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Web Tool ◽  
Tissue Specific ◽  
Analysis Tools ◽  
Go Enrichment ◽  
Go Enrichment Analysis

Abstract Background The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. Since the beginning of GO project, various tools have been developed to perform GO enrichment analysis experiments. GO enrichment analysis has become a commonly used method of gene function analysis. Existing GO enrichment analysis tools do not consider tissue-specific information, although this information is very important to current research. Results In this paper, we built an easy-to-use web tool called TS−GOEA that allows users to easily perform experiments based on tissue-specific GO enrichment analysis. TS−GOEA uses strict threshold statistical method for GO enrichment analysis, and provides statistical tests to improve the reliability of the analysis results. Meanwhile, TS−GOEA provides tools to compare different experimental results, which is convenient for users to compare the experimental results. To evaluate its performance, we tested the genes associated with platelet disease with TS−GOEA. Conclusions TS−GOEA is an effective GO analysis tool with unique features. The experimental results show that our method has better performance and provides a useful supplement for the existing GO enrichment analysis tools. TS−GOEA is available at http://120.77.47.2:5678.

scholarly journals Mechanisms of tissue-specific genetic regulation revealed by latent factors across eQTLs

2019 ◽  
Author(s):  
Yuan He ◽  
Surya B. Chhetri ◽  
Marios Arvanitis ◽  
Kaushik Srinivasan ◽  
François Aguet ◽  
...  
Keyword(s):  
Matrix Factorization ◽  
Tissue Specificity ◽  
Genetic Regulation ◽  
Regulation Of Gene Expression ◽  
Genetic Effect ◽  
Cell Types ◽  
Tissue Expression ◽  
Specific Gene ◽  
Disease Etiology ◽  
Tissue Specific

AbstractBackgroundGenetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), varies across tissues in complex patterns ranging from highly tissue-specific effects to effects shared across many or all tissues. Improved characterization of these patterns may allow us to better understand the biological mechanisms that underlie tissue-specific gene regulation and disease etiology.ResultsWe develop a constrained matrix factorization model to learn patterns of tissue sharing and tissue specificity of eQTLs across 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors include patterns reflecting tissues with known biological similarity or shared cell types, in addition to a dense factor representing a universal genetic effect across all tissues. To explore the regulatory mechanisms that generate tissue-specific patterns of expression, we evaluate chromatin state enrichment and identify specific transcription factors with binding sites enriched for eQTLs from each factor.ConclusionsOur results demonstrate that matrix factorization can be applied to learn the tissue specificity pattern of eQTLs and that it exhibits better biological interpretability than heuristic methods. We present a framework to characterize the tissue specificity of eQTLs, and we identify examples of tissue-specific eQTLs that may be driven by tissue-specific transcription factor (TF) binding, with relevance to interpretation of disease association.

scholarly journals A hypothesis-driven approach to assessing significance of differences in RNA expression levels among specific groups of genes

2017 ◽  
Author(s):  
Mingze He ◽  
Peng Liu ◽  
Carolyn J. Lawrence-Dill
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Heat Shock ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Simple Method ◽  
Expression Levels ◽  
Gene Set

AbstractGenome-wide molecular gene expression studies generally compare expression values for each gene across multiple conditions followed by cluster and gene set enrichment analysis to determine whether differentially expressed genes are enriched in specific biochemical pathways, cellular components, biological processes, and/or molecular functions, etc. This approach to analyzing differences in gene expression enables discovery of gene function, but is not useful to determine whether pre-defined groups of genes share or diverge in their expression patterns in response to treatments nor to assess the correctness of pre-defined gene set groupings. Here we present a simple method that changes the dimension of comparison by treating genes as variable traits to directly assess significance of differences in expression levels among pre-defined gene groups. Because expression distributions are typically skewed (thus unfit for direct assessment using Gaussian statistical methods) our method involves transforming expression data to approximate a normal distribution followed by dividing the genes into groups, then applying Gaussian parametric methods to assess significance of observed differences. This method enables the assessment of differences in gene expression distributions within and across samples, enabling hypothesis-based comparison among groups of genes. We demonstrate this method by assessing the significance of specific gene groups’ differential response to heat stress conditions in maize.AbbreviationsGO– gene ontology HSP – heat shock proteinKEGG– Kyoto Encyclopedia of Genes and GenomesHSF TF– heat shock factor transcription factorHSBP– heat shock binding proteinRNA– ribonucleic acidTE– transposable elementTF– transcription factorTPM– transcripts per kilobase millions

scholarly journals Transcriptomic Analysis and Specific Expression of Transcription Factor Genes in the Root and Sporophyll of Dryopteris fragrans (L.) Schott

2020 ◽  
Vol 21 (19) ◽  
pp. 7296
Author(s):  
Lingling Chen ◽  
Dongrui Zhang ◽  
Chunhua Song ◽  
Hemeng Wang ◽  
Xun Tang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Glandular Trichomes ◽  
Transcriptomic Analysis ◽  
Specific Gene ◽  
Specific Expression ◽  
Tissue Specific ◽  
Transcription Factor Genes ◽  
Dryopteris Fragrans ◽  
Different Tissues

Background: Dryopteris fragrans, which is densely covered with glandular trichomes, is considered to be one of the ferns with the most medicinal potential. The transcriptomes from selected tissues of D. fragrans were collected and analyzed for functional and comparative genomic studies. The aim of this study was to determine the transcriptomic characteristics of wild D. fragrans sporangium in tissues from the SR (root), SL (sporophyll), and TRL (sporophyll with glandular trichomes removed). Results: Cluster analysis identified genes that were highly expressed in an organ-specific manner according to read mapping, feature counting, and normalization. The functional map identified gene clusters that can uniquely describe the function of each tissue. We identified a group of three tissue-specific transcription factors targeting the SL, SR, and TRL. In addition, highly expressed transcription factors (TFs) were found in each tissue-specific gene cluster, where ERF and bHLH transcription factors were the two types showing the most distinct expression patterns between the three different tissues. The specific expression of transcription factor genes varied between the different types of tissues. The numbers of transcription factors specifically expressed in the roots and sporophylls were 60 and 30, respectively, while only seven were found for the sporophylls with glandular trichomes removed. The expression of genes known to be associated with the development of glandular trichomes in flowering plants, including MIXTA, ATML1, and MYB106, were also validated and are discussed. In particular, a unigene encoding MIXTA was identified and exhibited the highest expression level in SL in D. fragrans. Conclusions: This study is the first report of global transcriptomic analysis in different tissues of D. fragrans, and the first to discuss these findings in the context of the development of homologous glandular trichomes. These results set the stage for further research on the development, stress resistance, and secondary metabolism of D. fragrans glandular trichomes.

scholarly journals A Comparative Study of Mouse Hepatic and Intestinal Gene Expression Profiles under PPARαKnockout by Gene Set Enrichment Analysis

PPAR Research ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Kan He ◽  
Qishan Wang ◽  
Yumei Yang ◽  
Minghui Wang ◽  
Yuchun Pan
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Enrichment Analysis ◽  
Small Cell ◽  
Gene Set Enrichment Analysis ◽  
Small Cell Lung ◽  
Gene Set Enrichment ◽  
Tissue Specific

Gene expression profiling of PPARαhas been used in several studies, but fewer studies went further to identify the tissue-specific pathways or genes involved in PPARαactivation in genome-wide. Here, we employed and applied gene set enrichment analysis to two microarray datasets both PPARαrelated respectively in mouse liver and intestine. We suggested that the regulatory mechanism of PPARαactivation by WY14643 in mouse small intestine is more complicated than in liver due to more involved pathways. Several pathways were cancer-related such as pancreatic cancer and small cell lung cancer, which indicated that PPARαmay have an important role in prevention of cancer development. 12 PPARαdependent pathways and 4 PPARαindependent pathways were identified highly common in both liver and intestine of mice. Most of them were metabolism related, such as fatty acid metabolism, tryptophan metabolism, pyruvate metabolism with regard to PPARαregulation but gluconeogenesis and propanoate metabolism independent of PPARαregulation. Keratan sulfate biosynthesis, the pathway of regulation of actin cytoskeleton, the pathways associated with prostate cancer and small cell lung cancer were not identified as hepatic PPARαindependent but as WY14643 dependent ones in intestinal study. We also provided some novel hepatic tissue-specific marker genes.

scholarly journals Tissue-specific transcription factor target identification in the Caenorhabditis elegans epidermis using targeted DamID

2020 ◽  
Author(s):  
Dimitris Katsanos ◽  
Michalis Barkoulas
Keyword(s):  
Transcription Factor ◽  
Cell Differentiation ◽  
Single Molecule ◽  
Regulatory Networks ◽  
Specific Binding ◽  
Wnt Signalling ◽  
Specific Gene ◽  
List Type ◽  
Tissue Specific ◽  
Transcription Factor Target

SummaryTranscription factors are key orchestrators of development in multicellular animals and display complex patterns of expression, as well as tissue-specific binding to targets. However, our ability to map transcription factor-target interactions in specific tissues of intact animals remains limited. We introduce here targeted DamID (TaDa) as a method to identify transcription factor targets with tissue-specific resolution in C. elegans. We focus on the epidermis as a paradigm and demonstrate that TaDa circumvents problems with Dam-associated toxicity and allows reproducible identification of putative targets. Using a combination of TaDa and single-molecule FISH (smFISH), we refine the positions of LIN-22 and NHR-25 within the epidermal gene network. We reveal direct links between these two factors and the cell differentiation programme, as well as the Wnt signalling pathway. Our results illustrate how TaDa and smFISH can be used to dissect the architecture of tissue-specific gene regulatory networks.HighlightsTaDa circumvents Dam-associated toxicity by keeping levels of Dam expression low.TaDa allows the recovery of tissue-specific methylation profiles representing TF binding.Methylation signal is enriched in regulatory regions of the genome.LIN-22 and NHR-25 targets reveal a link to cell differentiation and Wnt signalling.

scholarly journals DNA Microarray-Based Global Gene Expression Profiling in Human Amniotic Epithelial Cells Predicts the Potential of Microalgae-Derived Squalene for the Nervous System and Metabolic Health

Biomedicines ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 48
Author(s):  
Farhana Ferdousi ◽  
Kinji Furuya ◽  
Kazunori Sasaki ◽  
Yun-Wen Zheng ◽  
Tatsuya Oda ◽  
...  
Keyword(s):  
Nervous System ◽  
Epithelial Cells ◽  
Dna Microarray ◽  
Enrichment Analysis ◽  
Nervous System Development ◽  
Gene Set Enrichment Analysis ◽  
Potential Health ◽  
Tissue Specific ◽  
Amniotic Epithelial Cells ◽  
Human Amniotic Epithelial Cells

In recent years, perinatal stem cells, such as human amniotic epithelial cells (hAECs), have attracted increasing interest as a novel tool of stem cell-based high-throughput drug screening. In the present study, we investigated the bioactivities of squalene (SQ) derived from ethanol extract (99.5%) of a microalgae Aurantiochytrium Sp. (EEA-SQ) in hAECs using whole-genome DNA microarray analysis. Tissue enrichment analysis showed that the brain was the most significantly enriched tissue by the differentially expressed genes (DEGs) between EEA-SQ-treated and control hAECs. Further gene set enrichment analysis and tissue-specific functional analysis revealed biological functions related to nervous system development, neurogenesis, and neurotransmitter modulation. Several adipose tissue-specific genes and functions were also enriched. Gene-disease association analysis showed nervous system-, metabolic-, and immune-related diseases were enriched. Altogether, our study suggests the potential health benefits of microalgae-derived SQ and we would further encourage investigation in EEA-SQ and its derivatives as potential therapeutics for nervous system- and metabolism-related diseases.

scholarly journals Transcriptional profiling identifies an androgen receptor activity-low, stemness program associated with enzalutamide resistance

2020 ◽  
Vol 117 (22) ◽  
pp. 12315-12323 ◽  
Author(s):  
Joshi J. Alumkal ◽  
Duanchen Sun ◽  
Eric Lu ◽  
Tomasz M. Beer ◽  
George V. Thomas ◽  
...  
Keyword(s):  
Androgen Receptor ◽  
De Novo ◽  
Statistical Significance ◽  
Specific Antigen ◽  
Enrichment Analysis ◽  
Progression Free Survival ◽  
Gene Set Enrichment Analysis ◽  
Specific Gene ◽  
Castration Resistant Prostate Cancer ◽  
Gene Alterations

The androgen receptor (AR) antagonist enzalutamide is one of the principal treatments for men with castration-resistant prostate cancer (CRPC). However, not all patients respond, and resistance mechanisms are largely unknown. We hypothesized that genomic and transcriptional features from metastatic CRPC biopsies prior to treatment would be predictive of de novo treatment resistance. To this end, we conducted a phase II trial of enzalutamide treatment (160 mg/d) in 36 men with metastatic CRPC. Thirty-four patients were evaluable for the primary end point of a prostate-specific antigen (PSA)50 response (PSA decline ≥50% at 12 wk vs. baseline). Nine patients were classified as nonresponders (PSA decline <50%), and 25 patients were classified as responders (PSA decline ≥50%). Failure to achieve a PSA50 was associated with shorter progression-free survival, time on treatment, and overall survival, demonstrating PSA50’s utility. Targeted DNA-sequencing was performed on 26 of 36 biopsies, and RNA-sequencing was performed on 25 of 36 biopsies that contained sufficient material. Using computational methods, we measured AR transcriptional function and performed gene set enrichment analysis (GSEA) to identify pathways whose activity state correlated with de novo resistance.TP53gene alterations were more common in nonresponders, although this did not reach statistical significance (P= 0.055).ARgene alterations and AR expression were similar between groups. Importantly, however, transcriptional measurements demonstrated that specific gene sets—including those linked to low AR transcriptional activity and a stemness program—were activated in nonresponders. Our results suggest that patients whose tumors harbor this program should be considered for clinical trials testing rational agents to overcome de novo enzalutamide resistance.

Sign in / Sign up

Export Citation Format

Share Document