scholarly journals The N.C.Yeastract and CommunityYeastract databases to study gene and genomic transcription regulation in non-conventional yeasts

2021 ◽  
Vol 21 (6) ◽  
Author(s):  
Cláudia P Godinho ◽  
Margarida Palma ◽  
Jorge Oliveira ◽  
Marta N Mota ◽  
Miguel Antunes ◽  
...  
Keyword(s):  
Binding Sites ◽  
Regulatory Networks ◽  
Target Genes ◽  
Kluyveromyces Lactis ◽  
Weak Acid ◽  
Zygosaccharomyces Bailii ◽  
Spoilage Yeast ◽  
Yeast Community ◽  
Acid Tolerant ◽  
Yeast Yarrowia Lipolytica

ABSTRACT Responding to the recent interest of the yeast research community in non-Saccharomyces cerevisiae species of biotechnological relevance, the N.C.Yeastract (http://yeastract-plus.org/ncyeastract/) was associated to YEASTRACT + (http://yeastract-plus.org/). The YEASTRACT + portal is a curated repository of known regulatory associations between transcription factors (TFs) and target genes in yeasts. N.C.Yeastract gathers all published regulatory associations and TF-binding sites for Komagataellaphaffii (formerly Pichia pastoris), the oleaginous yeast Yarrowia lipolytica, the lactose fermenting species Kluyveromyces lactis and Kluyveromyces marxianus, and the remarkably weak acid-tolerant food spoilage yeast Zygosaccharomyces bailii. The objective of this review paper is to advertise the update of the existing information since the release of N.C.Yeastract in 2019, and to raise awareness in the community about its potential to help the day-to-day work on these species, exploring all the information available in the global YEASTRACT + portal. Using simple and widely used examples, a guided exploitation is offered for several tools: (i) inference of orthologous genes; (ii) search for putative TF binding sites and (iii) inter-species comparison of transcription regulatory networks and prediction of TF-regulated networks based on documented regulatory associations available in YEASTRACT + for well-studied species. The usage potentialities of the new CommunityYeastract platform by the yeast community are also discussed.

scholarly journals The PARP Inhibitor Olaparib Modulates the Transcriptional Regulatory Networks of Long Non-Coding RNAs during Vasculogenic Mimicry

Cells ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2690
Author(s):  
Mónica Fernández-Cortés ◽  
Eduardo Andrés-León ◽  
Francisco Javier Oliver
Keyword(s):  
Transcription Factors ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Target Genes ◽  
Parp Inhibitor ◽  
Vasculogenic Mimicry ◽  
Transcriptome Profiling ◽  
Key Species ◽  
Non Coding Rnas ◽  
The Impact

In highly metastatic tumors, vasculogenic mimicry (VM) involves the acquisition by tumor cells of endothelial-like traits. Poly-(ADP-ribose) polymerase (PARP) inhibitors are currently used against tumors displaying BRCA1/2-dependent deficient homologous recombination, and they may have antimetastatic activity. Long non-coding RNAs (lncRNAs) are emerging as key species-specific regulators of cellular and disease processes. To evaluate the impact of olaparib treatment in the context of non-coding RNA, we have analyzed the expression of lncRNA after performing unbiased whole-transcriptome profiling of human uveal melanoma cells cultured to form VM. RNAseq revealed that the non-coding transcriptomic landscape differed between olaparib-treated and non-treated cells: olaparib significantly modulated the expression of 20 lncRNAs, 11 lncRNAs being upregulated, and 9 downregulated. We subjected the data to different bioinformatics tools and analysis in public databases. We found that copy-number variation alterations in some olaparib-modulated lncRNAs had a statistically significant correlation with alterations in some key tumor suppressor genes. Furthermore, the lncRNAs that were modulated by olaparib appeared to be regulated by common transcription factors: ETS1 had high-score binding sites in the promoters of all olaparib upregulated lncRNAs, while MZF1, RHOXF1 and NR2C2 had high-score binding sites in the promoters of all olaparib downregulated lncRNAs. Finally, we predicted that olaparib-modulated lncRNAs could further regulate several transcription factors and their subsequent target genes in melanoma, suggesting that olaparib may trigger a major shift in gene expression mediated by the regulation lncRNA. Globally, olaparib changed the lncRNA expression landscape during VM affecting angiogenesis-related genes.

Evolution of miRNA binding sites and regulatory networks in cichlids

2021 ◽  
Author(s):  
Tarang K Mehta ◽  
Luca Penso-Dolfin ◽  
Will K Nash ◽  
Sushmita Roy ◽  
Federica Di Palma ◽  
...  
Keyword(s):  
Binding Site ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Target Genes ◽  
Phenotypic Diversity ◽  
Regulatory Regions ◽  
Adaptive Trait ◽  
Regulatory Variants ◽  
Key Driver ◽  
Species Specific

The divergence of regulatory regions and gene regulatory network (GRN) rewiring is a key driver of cichlid phenotypic diversity. However, the contribution of miRNA binding site turnover has yet to be linked to GRN evolution across cichlids. Here, we extend our previous studies by analysing the selective constraints driving evolution of miRNA and transcription factor (TF) binding sites of target genes, to infer instances of cichlid GRN rewiring associated with regulatory binding site turnover. Comparative analyses identified increased species-specific networks that are functionally associated to traits of cichlid phenotypic diversity. The evolutionary rewiring is associated with differential models of miRNA snd TF binding site turnover, driven by a high proportion of fast-evolving polymorphic sites in adaptive trait genes compared to subsets of random genes. Positive selection acting upon discrete mutations in these regulatory regions is likely to be an important mechanism in rewiring GRNs in rapidly radiating cichlids. Regulatory variants of functionally associated miRNA and TF binding sites of visual opsin genes differentially segregate according to phylogeny and ecology of Lake Malawi species, identifying both rewired e.g. clade-specific and conserved network motifs of adaptive trait associated GRNs. Our approach revealed several novel candidate regulators, regulatory regions and three-node motifs across cichlid genomes with previously reported associations to known adaptive evolutionary traits.

scholarly journals YEASTRACT+: a portal for cross-species comparative genomics of transcription regulation in yeasts

2019 ◽  
Vol 48 (D1) ◽  
pp. D642-D649 ◽  
Author(s):  
Pedro T Monteiro ◽  
Jorge Oliveira ◽  
Pedro Pais ◽  
Miguel Antunes ◽  
Margarida Palma ◽  
...  
Keyword(s):  
Transcription Regulation ◽  
Binding Sites ◽  
Target Genes ◽  
Yeast Species ◽  
Kluyveromyces Lactis ◽  
Pathogenic Yeast ◽  
Genomic Expression ◽  
Network Analyses ◽  
Dna Binding Sites ◽  
Health Relevance

Abstract The YEASTRACT+ information system (http://YEASTRACT-PLUS.org/) is a wide-scope tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in yeasts of biotechnological or human health relevance. YEASTRACT+ is a new portal that integrates the previously existing YEASTRACT (http://www.yeastract.com/) and PathoYeastract (http://pathoyeastract.org/) databases and introduces the NCYeastract (Non-Conventional Yeastract) database (http://ncyeastract.org/), focused on the so-called non-conventional yeasts. The information in the YEASTRACT database, focused on Saccharomyces cerevisiae, was updated. PathoYeastract was extended to include two additional pathogenic yeast species: Candida parapsilosis and Candida tropicalis. Furthermore, the NCYeastract database was created, including five biotechnologically relevant yeast species: Zygosaccharomyces baillii, Kluyveromyces lactis, Kluyveromyces marxianus, Yarrowia lipolytica and Komagataella phaffii. The YEASTRACT+ portal gathers 289 706 unique documented regulatory associations between transcription factors (TF) and target genes and 420 DNA binding sites, considering 247 TFs from 10 yeast species. YEASTRACT+ continues to make available tools for the prediction of the TFs involved in the regulation of gene/genomic expression. In this release, these tools were upgraded to enable predictions based on orthologous regulatory associations described for other yeast species, including two new tools for cross-species transcription regulation comparison, based on multi-species promoter and TF regulatory network analyses.

scholarly journals Extreme resistance to weak-acid preservatives in the spoilage yeast Zygosaccharomyces bailii

2013 ◽  
Vol 166 (1) ◽  
pp. 126-134 ◽  
Author(s):  
Malcolm Stratford ◽  
Hazel Steels ◽  
Gerhard Nebe-von-Caron ◽  
Michaela Novodvorska ◽  
Kimran Hayer ◽  
...  
Keyword(s):  
Weak Acid ◽  
Extreme Resistance ◽  
Zygosaccharomyces Bailii ◽  
Spoilage Yeast

scholarly journals Filtering of Data-Driven Gene Regulatory Networks Using Drosophila melanogaster as a Case Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Yesid Cuesta-Astroz ◽  
Guilherme Gischkow Rucatti ◽  
Leandro Murgas ◽  
Carol D. SanMartín ◽  
Mario Sanhueza ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Drosophila Melanogaster ◽  
Gene Regulatory Networks ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Whole Genomes ◽  
Gene Regulatory

Gene Regulatory Networks (GRNs) allow the study of regulation of gene expression of whole genomes. Among the most relevant advantages of using networks to depict this key process, there is the visual representation of large amounts of information and the application of graph theory to generate new knowledge. Nonetheless, despite the many uses of GRNs, it is still difficult and expensive to assign Transcription Factors (TFs) to the regulation of specific genes. ChIP-Seq allows the determination of TF Binding Sites (TFBSs) over whole genomes, but it is still an expensive technique that can only be applied one TF at a time and requires replicates to reduce its noise. Once TFBSs are determined, the assignment of each TF and its binding sites to the regulation of specific genes is not trivial, and it is often performed by carrying out site-specific experiments that are unfeasible to perform in all possible binding sites. Here, we addressed these relevant issues with a two-step methodology using Drosophila melanogaster as a case study. First, our protocol starts by gathering all transcription factor binding sites (TFBSs) determined with ChIP-Seq experiments available at ENCODE and FlyBase. Then each TFBS is used to assign TFs to the regulation of likely target genes based on the TFBS proximity to the transcription start site of all genes. In the final step, to try to select the most likely regulatory TF from those previously assigned to each gene, we employ GENIE3, a random forest-based method, and more than 9,000 RNA-seq experiments from D. melanogaster. Following, we employed known TF protein-protein interactions to estimate the feasibility of regulatory events in our filtered networks. Finally, we show how known interactions between co-regulatory TFs of each gene increase after the second step of our approach, and thus, the consistency of the TF-gene assignment. Also, we employed our methodology to create a network centered on the Drosophila melanogaster gene Hr96 to demonstrate the role of this transcription factor on mitochondrial gene regulation.

scholarly journals Regulatory Targets of the Response Regulator RR_1586 from Clostridioides difficile Identified Using a Bacterial One-Hybrid Screen

2018 ◽  
Vol 200 (23) ◽  
Author(s):  
Skyler D. Hebdon ◽  
Smita K. Menon ◽  
George B. Richter-Addo ◽  
Elizabeth A. Karr ◽  
Ann H. West
Keyword(s):  
Dna Binding ◽  
Binding Sites ◽  
Regulatory Networks ◽  
Target Genes ◽  
Response Regulator ◽  
Self Regulation ◽  
Transport Systems ◽  
Content Type ◽  
Clostridioides Difficile ◽  
Two Component

ABSTRACT The Clostridioides difficile R20291 genome encodes 57 response regulator proteins that, as part of two-component signaling pathways, regulate adaptation to environmental conditions. Genomic and transcriptomic studies in C. difficile have been limited, due to technical challenges, to the analysis of either high-throughput screens or high-priority targets, such as primary regulators of toxins or spore biology. We present the use of several technically accessible and generally applicable techniques to elucidate the putative regulatory targets of a response regulator, RR_1586, involved in sporulation of the hypervirulent C. difficile strain R20291. A DNA-binding specificity motif for RR_1586 was determined using a bacterial one-hybrid assay originally developed for Drosophila transcription factors. Comparative bioinformatics approaches identified and in vitro experiments confirmed RR_1586 binding sites upstream of putative target genes, including those that encode phosphate ion transporters, spermidine/putrescine biosynthesis and transport pathways, ABC type transport systems, known regulators of sporulation, and genes encoding spore structural proteins. Representative examples of these regulatory interactions have been tested and confirmed in Escherichia coli-based reporter assays. Finally, evidence of possible regulatory mechanisms is also presented. A working model includes self-regulation by RR_1586 and phosphorylation-dependent and -independent DNA binding at low- and high-fidelity binding sites, respectively. Broad application of this and similar approaches is anticipated to be an important catalyst for the study of gene regulation by two-component systems from pathogenic or technically challenging bacteria. IMPORTANCE Clostridioides difficile spores survive under harsh conditions and can germinate into actively dividing cells capable of causing disease. An understanding of the regulatory networks controlling sporulation and germination in C. difficile could be exploited for therapeutic advantage. However, such studies are hindered by the challenges of working with an anaerobic pathogen recalcitrant to genetic manipulation. Although two-component response regulators can be identified from genetic sequences, identification of their downstream regulatory networks requires further development. This work integrates experimental and bioinformatic approaches, which provide practical advantages over traditional transcriptomic analyses, to identify the putative regulon of the C. difficile response regulator RR_1586 by first screening for protein-DNA interactions in E. coli and then predicting regulatory outputs in C. difficile.

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