scholarly journals Validation and characterisation of a wheat GENIE3 network using an independent RNA-Seq dataset

2019 ◽  
Author(s):  
Sophie A. Harrington ◽  
Anna E. Backhaus ◽  
Ajit Singh ◽  
Keywan Hassani-Pak ◽  
Cristobal Uauy

AbstractGene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently, as part of an analysis of the RefSeqv1.0 wheat transcriptome, a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we have used an independent and publicly-available RNA-Seq dataset to validate the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analysed the RNA-Seq data against the RefSeqv1.0 genome and identified a de novo set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the de novo DEGs, more than would be expected for a random transcription factor. Based on high levels of overlap between GENIE3-predicted target genes and the de novo DEGs, we also identified a set of candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and homoeolog expression levels and found that only homoeologous transcription factors are likely to share predicted targets in common. However, homoeologs in dynamic triads, i.e. with higher variation in homoeolog expression levels across tissues, are less likely to share predicted targets than stable triads. This suggests that homoeologs in dynamic triads are more likely to act on distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.

2020 ◽  
Vol 10 (10) ◽  
pp. 3675-3686 ◽  
Author(s):  
Sophie A. Harrington ◽  
Anna E. Backhaus ◽  
Ajit Singh ◽  
Keywan Hassani-Pak ◽  
Cristobal Uauy

Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate gene discovery. However, the extent to which the network predictions are biologically relevant is often unclear. Recently a GENIE3 network which predicted targets of wheat transcription factors was produced. Here we used an independent RNA-Seq dataset to test the predictions of the wheat GENIE3 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-analyzed the RNA-Seq data against the RefSeqv1.0 genome and identified a set of differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-predicted target genes of NAM-A1 overlap significantly with the DEGs, more than would be expected by chance. Based on high levels of overlap between GENIE3-predicted target genes and the DEGs, we identified candidate senescence regulators. We then explored genome-wide trends in the network related to polyploidy and found that only homeologous transcription factors are likely to share predicted targets in common. However, homeologs which vary in expression levels across tissues are less likely to share predicted targets than those that do not, suggesting that they may be more likely to act in distinct pathways. This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions of transcription factor targets, which can be used for candidate gene prediction and for global analyses of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner web application, facilitating its use in future studies.


2019 ◽  
Author(s):  
Haiwei Wang ◽  
Xinrui Wang ◽  
Liangpu Xu ◽  
Hua Cao

Abstract Background: Heart failure is one of leading cause of death worldwide. However, the transcriptional profiling of heart failure is unclear. Moreover, the signaling pathways and transcription factors involving the heart failure developmental progress also are largely unclear.Methods: The transcriptional profiling of heart failure was identified from integrated gene expression datasets. The enriched pathways and transcription factors were analyzed using DAVID and GSEA assay. The transcriptional networks were created by Cytoscape.Results: Compared with the normal heart tissues, we found 90 genes were particularly differentially expressed in heart failing tissues, and those genes were associated with multiple metabolism pathways and insulin signaling pathway. Metabolism and insulin signaling pathway were both inactivated in heart failing tissues. Transcription factors MYC and C/EBPβ were both negatively associated with the expression profiling of heart failing tissues in GSEA assay. Moreover, compared with normal heart tissues, MYC and C/EBPβ were down regulated in heart failing tissues. Furthermore, MYC and C/EBPβ mediated downstream target genes were decreased in heart failing tissues. MYC and C/EBPβ were positively correlated with each other. At last, we constructed the transcription factor MYC and C/EBPβ mediated regulatory networks in heart failing tissues, and identified the MYC and C/EBPβ target genes which had been reported involving the failure developmental progress by literature research. Conclusions: Our results suggested that transcription factor MYC and C/EBPβ played critical roles in heart failure developmental progress. And new heart failure treatments may be developed by targeting MYC and C/EBPβ.


Genes ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1148
Author(s):  
Xin-Wei Zhao ◽  
Hirohisa Kishino

Mammals have variable numbers (1300–2000) of transcription factors (TFs), but the reasons for this large variation are unclear. To investigate general TF patterns, we de novo identified 156,906 TFs from 96 mammalian species. We identified more than 500 human isolated TFs that are rarely reported in human TF-to-TF networks. Mutations in the genes of these TFs were less lethal than those of connected TFs. Consequently, these isolated TFs are more tolerant of changes and have become unique during speciation. They may also serve as a source of variation for TF evolution. Reconciliation of TF-family phylogenetic trees with a mammalian species tree revealed an average of 37.8% TF gains and 15.0% TF losses over 177 million years, which implies that isolated TFs are pervasive in mammals. Compared with non-TF interacting genes, TF-interacting genes have unique TF profiles and have higher expression levels in mice than in humans. Different expression levels of the same TF-interacting gene contribute to species-specific phenotypes. Formation and loss of isolated TFs enabling unique TF profiles may provide variable switches that adjust divergent expression profiles of target genes to generate species-specific phenotypes, thereby making species unique.


2021 ◽  
Author(s):  
Xin-Wei Zhao ◽  
Jiaqi Wu ◽  
Hirohisa Kishino

As one of the most successful categories of organisms, mammals occupy a variety of niches on earth as a result of macroevolution. Transcription factors (TFs), the basic regulators of gene expression, may also evolve during mammalian phenotypic diversification and macroevolution. To examine the relationship between TFs and mammalian macroevolution, we analyzed 140,821 de novo-identified TFs and their birth and death histories from 96 mammalian species. Gene tree vs. species tree reconciliation revealed that mammals experienced an upsurge in TF losses around 100 million years ago and also near the K–Pg boundary, thus implying a relationship with the divergence of placental animals. From approximately 100 million years ago to the present, losses dominated TF events without a significant change in TF gains. To quantify the effects of this TF pruning on mammalian macroevolution, we analyzed rates of molecular evolution and expression profiles of regulated target genes. Surprisingly, TF loss decelerated, rather than accelerated, molecular evolutionary rates of their target genes, suggesting increased functional constraints. Furthermore, an association study revealed that massive TF losses are significantly positively correlated with solitary behavior, nocturnality, reproductive-seasonality and insectivory life history traits, possibly through rewiring of regulatory networks.


2019 ◽  
Author(s):  
Xi Chen

AbstractBICORN is an R package developed to integrate prior transcription factor binding information and gene expression data for cis-regulatory module (CRM) inference. BICORN searches for a list of candidate CRMs from binary bindings on potential target genes. Applying Gibbs sampling, BICORN samples CRMs for each gene using the fitting performance of transcription factor activities and regulation strengths of TFs in each CRM on gene expression. Consequently, sparse regulatory networks are inferred as functional CRMs regulating target genes. The BICORN package is implemented in R and is available at https://cran.r-project.org/web/packages/BICORN/index.html.


2013 ◽  
Vol 41 (6) ◽  
pp. 1696-1700 ◽  
Author(s):  
Gordon Chua

Mapping transcriptional-regulatory networks requires the identification of target genes, binding specificities and signalling pathways of transcription factors. However, the characterization of each transcription factor sufficiently for deciphering such networks remains laborious. The recent availability of overexpression and deletion strains for almost all of the transcription factor genes in the fission yeast Schizosaccharomyces pombe provides a valuable resource to better investigate transcription factors using systematic genetics. In the present paper, I review and discuss the utility of these strain collections combined with transcriptome profiling and genome-wide chromatin immunoprecipitation to identify the target genes of transcription factors.


2020 ◽  
Vol 22 (Supplement_3) ◽  
pp. iii311-iii312
Author(s):  
Bernhard Englinger ◽  
Johannes Gojo ◽  
Li Jiang ◽  
Jens M Hübner ◽  
McKenzie L Shaw ◽  
...  

Abstract Ependymoma represents a heterogeneous disease affecting the entire neuraxis. Extensive molecular profiling efforts have identified molecular ependymoma subgroups based on DNA methylation. However, the intratumoral heterogeneity and developmental origins of these groups are only partially understood, and effective treatments are still lacking for about 50% of patients with high-risk tumors. We interrogated the cellular architecture of ependymoma using single cell/nucleus RNA-sequencing to analyze 24 tumor specimens across major molecular subgroups and anatomic locations. We additionally analyzed ten patient-derived ependymoma cell models and two patient-derived xenografts (PDXs). Interestingly, we identified an analogous cellular hierarchy across all ependymoma groups, originating from undifferentiated neural stem cell-like populations towards different degrees of impaired differentiation states comprising neuronal precursor-like, astro-glial-like, and ependymal-like tumor cells. While prognostically favorable ependymoma groups predominantly harbored differentiated cell populations, aggressive groups were enriched for undifferentiated subpopulations. Projection of transcriptomic signatures onto an independent bulk RNA-seq cohort stratified patient survival even within known molecular groups, thus refining the prognostic power of DNA methylation-based profiling. Furthermore, we identified novel potentially druggable targets including IGF- and FGF-signaling within poorly prognostic transcriptional programs. Ependymoma-derived cell models/PDXs widely recapitulated the transcriptional programs identified within fresh tumors and are leveraged to validate identified target genes in functional follow-up analyses. Taken together, our analyses reveal a developmental hierarchy and transcriptomic context underlying the biologically and clinically distinct behavior of ependymoma groups. The newly characterized cellular states and underlying regulatory networks could serve as basis for future therapeutic target identification and reveal biomarkers for clinical trials.


2021 ◽  
Vol 22 (15) ◽  
pp. 8193
Author(s):  
Daniel Pérez-Cremades ◽  
Ana B. Paes ◽  
Xavier Vidal-Gómez ◽  
Ana Mompeón ◽  
Carlos Hermenegildo ◽  
...  

Background/Aims: Estrogen has been reported to have beneficial effects on vascular biology through direct actions on endothelium. Together with transcription factors, miRNAs are the major drivers of gene expression and signaling networks. The objective of this study was to identify a comprehensive regulatory network (miRNA-transcription factor-downstream genes) that controls the transcriptomic changes observed in endothelial cells exposed to estradiol. Methods: miRNA/mRNA interactions were assembled using our previous microarray data of human umbilical vein endothelial cells (HUVEC) treated with 17β-estradiol (E2) (1 nmol/L, 24 h). miRNA–mRNA pairings and their associated canonical pathways were determined using Ingenuity Pathway Analysis software. Transcription factors were identified among the miRNA-regulated genes. Transcription factor downstream target genes were predicted by consensus transcription factor binding sites in the promoter region of E2-regulated genes by using JASPAR and TRANSFAC tools in Enrichr software. Results: miRNA–target pairings were filtered by using differentially expressed miRNAs and mRNAs characterized by a regulatory relationship according to miRNA target prediction databases. The analysis identified 588 miRNA–target interactions between 102 miRNAs and 588 targets. Specifically, 63 upregulated miRNAs interacted with 295 downregulated targets, while 39 downregulated miRNAs were paired with 293 upregulated mRNA targets. Functional characterization of miRNA/mRNA association analysis highlighted hypoxia signaling, integrin, ephrin receptor signaling and regulation of actin-based motility by Rho among the canonical pathways regulated by E2 in HUVEC. Transcription factors and downstream genes analysis revealed eight networks, including those mediated by JUN and REPIN1, which are associated with cadherin binding and cell adhesion molecule binding pathways. Conclusion: This study identifies regulatory networks obtained by integrative microarray analysis and provides additional insights into the way estradiol could regulate endothelial function in human endothelial cells.


Blood ◽  
2005 ◽  
Vol 106 (6) ◽  
pp. 1938-1947 ◽  
Author(s):  
Tomohiko Tamura ◽  
Pratima Thotakura ◽  
Tetsuya S. Tanaka ◽  
Minoru S. H. Ko ◽  
Keiko Ozato

Abstract Interferon regulatory factor-8 (IRF-8)/interferon consensus sequence–binding protein (ICSBP) is a transcription factor that controls myeloid-cell development. Microarray gene expression analysis of Irf-8-/- myeloid progenitor cells expressing an IRF-8/estrogen receptor chimera (which differentiate into macrophages after addition of estradiol) was used to identify 69 genes altered by IRF-8 during early differentiation (62 up-regulated and 7 down-regulated). Among them, 4 lysosomal/endosomal enzyme-related genes (cystatin C, cathepsin C, lysozyme, and prosaposin) did not require de novo protein synthesis for induction, suggesting that they were direct targets of IRF-8. We developed a reporter assay system employing a self-inactivating retrovirus and analyzed the cystatin C and cathepsin C promoters. We found that a unique cis element mediates IRF-8–induced activation of both promoters. Similar elements were also found in other IRF-8 target genes with a consensus sequence (GAAANN[N]GGAA) comprising a core IRF-binding motif and an Ets-binding motif; this sequence is similar but distinct from the previously reported Ets/IRF composite element. Chromatin immunoprecipitation assays demonstrated that IRF-8 and the PU.1 Ets transcription factor bind to this element in vivo. Collectively, these data indicate that IRF-8 stimulates transcription of target genes through a novel cis element to specify macrophage differentiation.


2019 ◽  
Vol 28 (14) ◽  
pp. 2319-2329 ◽  
Author(s):  
Kohei Hamanaka ◽  
Atsushi Takata ◽  
Yuri Uchiyama ◽  
Satoko Miyatake ◽  
Noriko Miyake ◽  
...  

AbstractDisorders of sex development (DSDs) are defined as congenital conditions in which chromosomal, gonadal or anatomical sex is atypical. In many DSD cases, genetic causes remain to be elucidated. Here, we performed a case–control exome sequencing study comparing gene-based burdens of rare damaging variants between 26 DSD cases and 2625 controls. We found exome-wide significant enrichment of rare heterozygous truncating variants in the MYRF gene encoding myelin regulatory factor, a transcription factor essential for oligodendrocyte development. All three variants occurred de novo. We identified an additional 46,XY DSD case of a de novo damaging missense variant in an independent cohort. The clinical symptoms included hypoplasia of Müllerian derivatives and ovaries in 46,XX DSD patients, defective development of Sertoli and Leydig cells in 46,XY DSD patients and congenital diaphragmatic hernia in one 46,XY DSD patient. As all of these cells and tissues are or partly consist of coelomic epithelium (CE)-derived cells (CEDC) and CEDC developed from CE via proliferaiton and migration, MYRF might be related to these processes. Consistent with this hypothesis, single-cell RNA sequencing of foetal gonads revealed high expression of MYRF in CE and CEDC. Reanalysis of public chromatin immunoprecipitation sequencing data for rat Myrf showed that genes regulating proliferation and migration were enriched among putative target genes of Myrf. These results suggested that MYRF is a novel causative gene of 46,XY and 46,XX DSD and MYRF is a transcription factor regulating CD and/or CEDC proliferation and migration, which is essential for development of multiple organs.


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