An evolutionarily conserved DNA-encoded logic shapes CpG island formation
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PROVIDER: PRJNA293358 | ENA |
REPOSITORIES: ENA
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Project description:DNA methylation is an epigenetic modification of the vertebrate genome that contributes to transcriptional repression, imprinting, and X-chromosome inactivation. While the majority of the genome is blanketed in DNA methylation, regions known as CpG islands (CGIs) remain remarkably refractory to this modification. CpG islands are associated with roughly two thirds of gene promoters, are evolutionarily conserved, and play central roles in gene regulation, yet how they are protected from DNA methylation remains enigmatic. Based on the conserved nature of CpG islands, we have exploited genomic approaches and a transchromosomic model system to ask if DNA sequence is sufficient to specify the hypomethylated state at CpG islands when a human chromosome is newly introduced into mouse. Interestingly, this approach revealed that promoter-associated CGIs remain immensely refractory to DNA methylation regardless of the host species, in fitting with their conservation across vertebrate species and revealing that DNA sequence is a central driver in this outcome. In contrast, the methylation state of distal elements is highly variable between species and is host nucleus dependent. These alterations in methylation state at distal elements are defined by DNA nucleotide frequency and occupancy of DNA binding transcription factors, uncovering a widespread role for these features in defining the how this aspect of the epigenome forms away from gene promoters. These central principles are further supported by transplantation of mouse DNA sequences into the evolutionarily distant zebrafish genome, revealing the existence of a highly conserved and DNA encoded logic that shapes the vertebrate epigenome.
2016-04-18 | GSE72208 | GEO
Project description:Endogenous RNAi pathway evolutionarily shapes the destiny of the antisense lncRNA transcriptome
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| S-EPMC5001583 | biostudies-literature
Project description:Purpose: to characterize the regulatory targets of an AraC-like transcriptional regulator (VC0513) encoded on the Vibrio Seventh Pandemic Island -II (VSP-II) in V. cholerae O1 El Tor N16961 Methods: RNA was isolated from a wild-type N16961 carrying an IPTG-inducible copy of vc0513, vc0515, or an empty vector control Results: vc0513 induction significantly increased expression of other VSP-II encoded genes relative to the empty vector control Conclusions: our study represents the first analysis of a transcriptional regulator encoded on the VSP-II island
2021-05-08 | GSE174028 | GEO
Project description:Increasingly, experimental data on biological systems are obtained from several sources and computational approaches are required to integrate this information and derive models for the function of the system. Here, we demonstrate the power of a logic-based machine learning approach to propose hypotheses for gene function integrating information from two diverse experimental approaches. Specifically, we use inductive logic programming that automatically proposes hypotheses explaining the empirical data with respect to logically encoded background knowledge. We study the capsular polysaccharide biosynthetic pathway of the major human gastrointestinal pathogen Campylobacter jejuni. We consider several key steps in the formation of capsular polysaccharide consisting of 15 genes of which 8 have assigned function, and we explore the extent to which functions can be hypothesised for the remaining 7. Two sources of experimental data provide the information for learning-the results of knockout experiments on the genes involved in capsule formation and the absence/presence of capsule genes in a multitude of strains of different serotypes. The machine learning uses the pathway structure as background knowledge. We propose assignments of specific genes to five previously unassigned reaction steps. For four of these steps, there was an unambiguous optimal assignment of gene to reaction, and to the fifth, there were three candidate genes. Several of these assignments were consistent with additional experimental results. We therefore show that the logic-based methodology provides a robust strategy to integrate results from different experimental approaches and propose hypotheses for the behaviour of a biological system. [Data is also available from http://bugs.sgul.ac.uk/E-BUGS-132]
2012-11-04 | E-BUGS-132 | biostudies-arrayexpress
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2022-12-21 | GSE199805 | GEO
Project description:Pulsed SILAC approaches allow measurement of protein dynamics, including protein translation and degradation. However, its use in quantifying acute changes has been limited due the low labeled peptide stoichiometry. Here, we describe the use of instrument logic to select peaks of interest via targeted mass differences (TMD) for overcoming this limitation. Comparing peptides artificially mixed at low heavy-to-light stoichiometry measured using standard data dependent acquisition with or without TMD revealed 2-3 fold increases in identification without significant loss in quantification precision for both MS2 and MS3 methods. Our benchmarked method approach increases throughput by reducing the necessary machine time. We anticipate that all pulsed SILAC measurements, if combined with TMT or not, would greatly benefit from instrument logic based approaches.
2020-05-29 | PXD018445 | Pride
Project description:Interrogation of gene regulatory circuits in complex organisms requires precise tools for the selection of individual cell types, as well as robust methods for tissue-specific labeling and biochemical profiling of target proteins. By exploiting multiple transgenesis strategies, we have developed a tissue-specific binary in vivo biotinylation system in zebrafish termed "biotagging", a versatile methodology that uses genetically-encoded components to biotinylate target proteins, enabling in-depth genome-wide analyses of their molecular interactions. Using tissue-specific transgenic drivers and individual cell compartment effector lines from our "biotagging" toolkit, we demonstrate the specificity of our approach at the biochemical, cellular and transcriptional levels. By characterizing the in vivo transcriptional landscape of migratory neural crest and myocardial cells in two different cellular compartments (ribosomes and nucleus), we identify a comprehensive network of protein-coding and non-coding RNAs and uncover cis-regulatory modules and regulatory logic conferring cell-specific identity, embedded in the complexity of the non-coding nuclear transcriptomes. Our study demonstrates that "biotagging" eliminates background inherent to complex embryonic environments and allows analyses of molecular interactions in any cellular context at highest resolution.
2017-04-07 | GSE89670 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE39108: UNG shapes the specifity of AID-induced somatic hypermutation in non B cells GSE39114: UNG shapes the specifity of AID-induced somatic hypermutation in B cells Refer to individual Series
2012-07-04 | E-GEOD-39115 | biostudies-arrayexpress
Project description:Transcription must be highly controlled to regulate gene expression and development. However, our understanding of the molecular mechanisms that influence transcription and how these are coordinated in cells to ensure normal gene expression remains rudimentary. Here, we reveal that actively transcribed CpG island-associated gene promoters recruit SET1 chromatin modifying complexes to enable gene expression. Counterintuitively, this effect is independent of SET1 complex histone modifying activity, and instead relies on the capacity of these complexes to interact with the RNA Polymerase II-binding protein, WDR82. Unexpectedly, we discover that SET1 complexes sustain gene transcription by counteracting the activity of the ZC3H4/WDR82 protein complex, which we show can pervasively terminate both genic and extragenic transcription. Therefore, we discover a new gene regulatory mechanism whereby CpG island elements nucleate a protein complex that protects genic transcription from premature termination, effectively distinguishing genic from non-genic transcription to enable gene expression.
2022-12-22 | GSE199804 | GEO