scholarly journals Comprehensive Characterization of Multitissue Expression Landscape, Co-Expression Networks and Positive Selection in Pikeperch

Cells ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 2289
Author(s):  
Julien Alban Nguinkal ◽  
Marieke Verleih ◽  
Lidia de los Ríos-Pérez ◽  
Ronald Marco Brunner ◽  
Arne Sahm ◽  
...  
Keyword(s):  
Gene Expression ◽  
Positive Selection ◽  
Tissue Specificity ◽  
Fish Family ◽  
Physiological Functions ◽  
Tissue Specific ◽  
Network Analyses ◽  
Network Modules ◽  
Comprehensive Characterization

Promising efforts are ongoing to extend genomics resources for pikeperch (Sander lucioperca), a species of high interest for the sustainable European aquaculture sector. Although previous work, including reference genome assembly, transcriptome sequence, and single-nucleotide polymorphism genotyping, added a great wealth of genomic tools, a comprehensive characterization of gene expression across major tissues in pikeperch still remains an unmet research need. Here, we used deep RNA-Sequencing of ten vital tissues collected in eight animals to build a high-confident and annotated trancriptome atlas, to detect the tissue-specificity of gene expression and co-expression network modules, and to investigate genome-wide selective signatures in the Percidae fish family. Pathway enrichment and protein–protein interaction network analyses were performed to characterize the unique biological functions of tissue-specific genes and co-expression modules. We detected strong functional correlations and similarities of tissues with respect to their expression patterns—but also significant differences in the complexity and composition of their transcriptomes. Moreover, functional analyses revealed that tissue-specific genes essentially play key roles in the specific physiological functions of the respective tissues. Identified network modules were also functionally coherent with tissues’ main physiological functions. Although tissue specificity was not associated with positive selection, several genes under selection were found to be involved in hypoxia, immunity, and gene regulation processes, that are crucial for fish adaption and welfare. Overall, these new resources and insights will not only enhance the understanding of mechanisms of organ biology in pikeperch, but also complement the amount of genomic resources for this commercial species.

scholarly journals Analyzing cancer gene expression data through the lens of normal tissue-specificity

2021 ◽  
Author(s):  
H. Robert Frost
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Tissue Specificity ◽  
Cancer Genomics ◽  
Expression Profiles ◽  
Genetic Alterations ◽  
Cancer Type ◽  
Tissue Specific ◽  
Normal Tissues ◽  
Cancer Types

AbstractThe genetic alterations that underlie cancer development are highly tissue-specific with the majority of driving alterations occurring in only a few cancer types and with alterations common to multiple cancer types often showing a tissue-specific functional impact. This tissue-specificity means that the biology of normal tissues carries important information regarding the pathophysiology of the associated cancers, information that can be leveraged to improve the power and accuracy of cancer genomic analyses. Research exploring the use of normal tissue data for the analysis of cancer genomics has primarily focused on the paired analysis of tumor and adjacent normal samples. Efforts to leverage the general characteristics of normal tissue for cancer analysis has received less attention with most investigations focusing on understanding the tissue-specific factors that lead to individual genomic alterations or dysregulated pathways within a single cancer type. To address this gap and support scenarios where adjacent normal tissue samples are not available, we explored the genome-wide association between the transcriptomes of 21 solid human cancers and their associated normal tissues as profiled in healthy individuals. While the average gene expression profiles of normal and cancerous tissue may appear distinct, with normal tissues more similar to other normal tissues than to the associated cancer types, when transformed into relative expression values, i.e., the ratio of expression in one tissue or cancer relative to the mean in other tissues or cancers, the close association between gene activity in normal tissues and related cancers is revealed. As we demonstrate through an analysis of tumor data from The Cancer Genome Atlas and normal tissue data from the Human Protein Atlas, this association between tissue-specific and cancer-specific expression values can be leveraged to improve the prognostic modeling of cancer, the comparative analysis of different cancer types, and the analysis of cancer and normal tissue pairs.

scholarly journals Comprehensive Characterization of Androgen-Responsive lncRNAs Mediated Regulatory Network in Hormone-Related Cancers

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Dan Wang ◽  
Mingyue Li ◽  
Jing Li ◽  
Xuechao Wan ◽  
Yan Huang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Cancer Progression ◽  
Regulatory Network ◽  
Bioinformatics Analysis ◽  
Mapk Signaling ◽  
Ppi Network ◽  
Network Analyses ◽  
Comprehensive Characterization ◽  
Upstream Regulators

The AR signaling pathway plays an important role in initiation and progression of many hormone-related cancers including prostate, bladder, kidney, lung, and breast cancer. However, the potential roles of androgen-responsive long noncoding RNAs (lncRNAs) in hormone-related cancers remained unclear. In the present study, we identified 469 novel androgen-responsive lncRNAs using microarray data. After validating the accuracy of the array data, we constructed a transcriptional network which contained more than 30 transcriptional factors using ChIP-seq data to explore upstream regulators of androgen-responsive lncRNAs. Next, we conducted bioinformatics analysis to identify lncRNA-miRNA-mRNA regulatory network. To explore the potential roles of androgen-responsive lncRNAs in hormone-related cancers, we performed coexpression network and PPI network analyses using TCGA data. GO and KEGG analyses showed these lncRNAs were mainly involved in regulating signal transduction, transcription, development, cell adhesion, immune response, cell differentiation, and MAPK signaling pathway. We also highlight the prognostic value of HPN-AS1, TPTEP1, and LINC00623 in cancer outcomes. Our results suggest that androgen-responsive lncRNAs played important roles in regulating hormone-related cancer progression and could be novel molecular biomarkers.

scholarly journals Tissue-specificity of gene expression diverges slowly between orthologs, and rapidly between paralogs

2016 ◽  
Author(s):  
Nadezda Kryuchkova-Mostacci ◽  
Marc Robinson-Rechavi
Keyword(s):  
Gene Expression ◽  
Tissue Specificity ◽  
Pearson Correlation ◽  
Expression Patterns ◽  
Divergence Time ◽  
Gene Copy ◽  
Strong Increase ◽  
Small Scale ◽  
Ontology Term ◽  
Tissue Specific

AbstractThe ortholog conjecture implies that functional similarity between orthologous genes is higher than between paralogs. It has been supported using levels of expression and Gene Ontology term analysis, although the evidence was rather weak and there were also conflicting reports. In this study on 12 species we provide strong evidence of high conservation in tissue-specificity between orthologs, in contrast to low conservation between within-species paralogs. This allows us to shed a new light on the evolution of gene expression patterns. While there have been several studies of the correlation of expression between species, little is known about the evolution of tissue-specificity itself. Ortholog tissue-specificity is strongly conserved between all tetrapod species, with the lowest Pearson correlation between mouse and frog at r = 0.66. Tissue-specificity correlation decreases strongly with divergence time. Paralogs in human show much lower conservation, even for recent Primate-specific paralogs. When both paralogs from ancient whole genome duplication tissue-specific paralogs are tissue-specific, it is often to different tissues, while other tissue-specific paralogs are mostly specific to the same tissue. The same patterns are observed using human or mouse as focal species, and are robust to choices of datasets and of thresholds. Our results support the following model of evolution: in the absence of duplication, tissue-specificity evolves slowly, and tissue-specific genes do not change their main tissue of expression; after small-scale duplication the less expressed paralog loses the ancestral specificity, leading to an immediate difference between paralogs; over time, both paralogs become more broadly expressed, but remain poorly correlated. Finally, there is a small number of paralog pairs which stay tissue-specific with the same main tissue of expression, for at least 300 million years.Author summaryFrom specific examples, it has been assumed by comparative biologists that the same gene in different species has the same function, whereas duplication of a gene inside one species to create several copies allows them to acquire different functions. Yet this model was little tested until recently, and then has proven harder than expected to confirm. One of the problems is defining “function” in a way which can be easily studied. We introduce a new way of considering function: how specific is the activity (“expression”) of a gene? Genes which are specific to certain tissues have functions related to these tissues, whereas genes which are broadly active over many or all tissues have more general functions for the organism. We find that this “tissue-specificity” evolves very slowly in the absence of duplication, while immediately after duplication the new gene copy differs. This shows that indeed duplication leads to a strong increase in the evolution of new functions.

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 Drosophila female reproductive tract gene expression reveals coordinated mating responses and rapidly evolving tissue-specific genes

2021 ◽  
Author(s):  
Caitlin E McDonough-Goldstein ◽  
Kirill Borziak ◽  
Scott Pitnick ◽  
Steve Dorus
Keyword(s):  
Gene Expression ◽  
Reproductive Tract ◽  
Expression Profiles ◽  
Female Reproductive Tract ◽  
Tissue Specific ◽  
Accelerated Evolution ◽  
Before And After ◽  
Complex Coordination ◽  
Extracellular Environment

Abstract Sexual reproduction in internally fertilizing species requires complex coordination between female and male reproductive systems and among the diverse tissues of the female reproductive tract (FRT). Here, we report a comprehensive, tissue-specific investigation of Drosophila melanogaster FRT gene expression before and after mating. We identified expression profiles that distinguished each tissue, including major differences between tissues with glandular or primarily non-glandular epithelium. All tissues were enriched for distinct sets of genes possessing secretion signals and exhibiting accelerated evolution, as might be expected for genes participating in molecular interactions between the sexes within the FRT extracellular environment. Despite robust transcriptional differences between tissues, post-mating responses were dominated by coordinated transient changes indicative of an integrated systems-level functional response. This comprehensive characterization of gene expression throughout the FRT identifies putative female contributions to post-copulatory events critical to reproduction and potentially reproductive isolation, as well as the putative targets of sexual selection and conflict.

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 Atlas of tissue-specific and tissue-preferential gene expression in ecologically and economically significant conifer Pinus sylvestris

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11781
Author(s):  
Sandra Cervantes ◽  
Jaana Vuosku ◽  
Tanja Pyhäjärvi
Keyword(s):  
Gene Expression ◽  
Pinus Sylvestris ◽  
Tissue Specificity ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Biological Databases ◽  
Ploidy Levels ◽  
Tissue Specific ◽  
Genomic Resources ◽  
Wide Range

Despite their ecological and economical importance, conifers genomic resources are limited, mainly due to the large size and complexity of their genomes. Additionally, the available genomic resources lack complete structural and functional annotation. Transcriptomic resources have been commonly used to compensate for these deficiencies, though for most conifer species they are limited to a small number of tissues, or capture only a fraction of the genes present in the genome. Here we provide an atlas of gene expression patterns for conifer Pinus sylvestris across five tissues: embryo, megagametophyte, needle, phloem and vegetative bud. We used a wide range of tissues and focused our analyses on the expression profiles of genes at tissue level. We provide comprehensive information of the per-tissue normalized expression level, indication of tissue preferential upregulation and tissue-specificity of expression. We identified a total of 48,001 tissue preferentially upregulated and tissue specifically expressed genes, of which 28% have annotation in the Swiss-Prot database. Even though most of the putative genes identified do not have functional information in current biological databases, the tissue-specific patterns discovered provide valuable information about their potential functions for further studies, as for example in the areas of plant physiology, population genetics and genomics in general. As we provide information on tissue specificity at both diploid and haploid life stages, our data will also contribute to the understanding of evolutionary rates of different tissue types and ploidy levels.

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