scholarly journals From “Simple” DNA-Protein Interactions to the Macromolecular Machines of Gene Expression

Author(s):  
Peter H. von Hippel
2014 ◽  
Vol 46 (13) ◽  
pp. 441-447 ◽  
Author(s):  
Hector Guillen-Ahlers ◽  
Michael R. Shortreed ◽  
Lloyd M. Smith ◽  
Michael Olivier

DNA-protein interactions are central to gene expression and chromatin regulation and have become one of the main focus areas of the ENCODE consortium. Advances in mass spectrometry and associated technologies have facilitated studies of these interactions, revealing many novel DNA-interacting proteins and histone posttranslational modifications. Proteins interacting at a single locus or at multiple loci have been targeted in these recent studies, each requiring a separate analytical strategy for isolation and analysis of DNA-protein interactions. The enrichment of target chromatin fractions occurs via a number of methods including immunoprecipitation, affinity purification, and hybridization, with the shared goal of using proteomics approaches as the final readout. The result of this is a number of exciting new tools, with distinct strengths and limitations that can enable highly robust and novel chromatin studies when applied appropriately. The present review compares and contrasts these methods to help the reader distinguish the advantages of each approach.


2021 ◽  
Author(s):  
Seth W Cheetham ◽  
Yohaann M.A Jafrani ◽  
Stacey B Andersen ◽  
Natasha Jansz ◽  
Adam D Ewing ◽  
...  

DNA-protein interactions and cytosine methylation control eukaryotic gene expression. Here, we present an approach to simultaneously detect cytosine methylation and DNA-protein interactions from single molecules, through selective sequencing of adenine-labelled DNA. Applying this approach to LaminB1-associated heterochromatin domains, we identify strict CpG methylation maintenance at transcriptional start sites amid a generalised relaxation of methylation, potentially to prevent ectopic aberrant heterochromatic gene expression.


2013 ◽  
Vol 54 ◽  
pp. 79-90 ◽  
Author(s):  
Saba Valadkhan ◽  
Lalith S. Gunawardane

Eukaryotic cells contain small, highly abundant, nuclear-localized non-coding RNAs [snRNAs (small nuclear RNAs)] which play important roles in splicing of introns from primary genomic transcripts. Through a combination of RNA–RNA and RNA–protein interactions, two of the snRNPs, U1 and U2, recognize the splice sites and the branch site of introns. A complex remodelling of RNA–RNA and protein-based interactions follows, resulting in the assembly of catalytically competent spliceosomes, in which the snRNAs and their bound proteins play central roles. This process involves formation of extensive base-pairing interactions between U2 and U6, U6 and the 5′ splice site, and U5 and the exonic sequences immediately adjacent to the 5′ and 3′ splice sites. Thus RNA–RNA interactions involving U2, U5 and U6 help position the reacting groups of the first and second steps of splicing. In addition, U6 is also thought to participate in formation of the spliceosomal active site. Furthermore, emerging evidence suggests additional roles for snRNAs in regulation of various aspects of RNA biogenesis, from transcription to polyadenylation and RNA stability. These snRNP-mediated regulatory roles probably serve to ensure the co-ordination of the different processes involved in biogenesis of RNAs and point to the central importance of snRNAs in eukaryotic gene expression.


Author(s):  
Hana Pivoňková ◽  
Kateřina Němcová ◽  
Petra Horáková ◽  
Luděk Havran ◽  
Hana Macíčková-Cahová ◽  
...  

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
He-Gang Chen ◽  
Xiong-Hui Zhou

Drug repurposing/repositioning, which aims to find novel indications for existing drugs, contributes to reducing the time and cost for drug development. For the recent decade, gene expression profiles of drug stimulating samples have been successfully used in drug repurposing. However, most of the existing methods neglect the gene modules and the interactions among the modules, although the cross-talks among pathways are common in drug response. It is essential to develop a method that utilizes the cross-talks information to predict the reliable candidate associations. In this study, we developed MNBDR (Module Network Based Drug Repositioning), a novel method that based on module network to screen drugs. It integrated protein–protein interactions and gene expression profile of human, to predict drug candidates for diseases. Specifically, the MNBDR mined dense modules through protein–protein interaction (PPI) network and constructed a module network to reveal cross-talks among modules. Then, together with the module network, based on existing gene expression data set of drug stimulation samples and disease samples, we used random walk algorithms to capture essential modules in disease development and proposed a new indicator to screen potential drugs for a given disease. Results showed MNBDR could provide better performance than popular methods. Moreover, functional analysis of the essential modules in the network indicated our method could reveal biological mechanism in drug response.


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