scholarly journals SAF-A mutants disrupt chromatin structure through dominant negative effects on RNAs associated with chromatin

2021 ◽  
Author(s):  
Heather J. Kolpa ◽  
Kevin M. Creamer ◽  
Lisa L. Hall ◽  
Jeanne B. Lawrence
Keyword(s):  
Rna Binding ◽  
Rna Binding Proteins ◽  
Chromatin Condensation ◽  
Dna Condensation ◽  
Binding Domain ◽  
Dominant Negative ◽  
Negative Effects ◽  
Nuclear Scaffold ◽  
Xist Rna ◽  
The Impact

AbstractHere we provide a brief review of relevant background before presenting results of our investigation into the interplay between scaffold attachment factor A (SAF-A), chromatin-associated RNAs, and DNA condensation. SAF-A, also termed heterogenous nuclear protein U (hnRNP U), is a ubiquitous nuclear scaffold protein that was implicated in XIST RNA localization to the inactive X-chromosome (Xi) but also reported to maintain open DNA packaging in euchromatin. Here we use several means to perturb SAF-A and examine potential impacts on the broad association of RNAs on euchromatin, and on chromatin compaction. SAF-A has an N-terminal DNA binding domain and C-terminal RNA binding domain, and a prominent model has been that the protein provides a single-molecule bridge between XIST RNA and chromatin. Here analysis of the impact of SAF-A on broad RNA-chromatin interactions indicate greater biological complexity. We focus on SAF-A’s role with repeat-rich C0T-1 hnRNA (repeat-rich heterogeneous nuclear RNA), shown recently to comprise mostly intronic sequences of pre-mRNAs and diverse long non-coding RNAs (lncRNAs). Our results show that SAF-A mutants cause dramatic changes to cytological chromatin condensation through dominant negative effects on C0T-1 RNA’s association with euchromatin, and likely other nuclear scaffold factors. In contrast, depletion of SAF-A by RNA interference (RNAi) had no discernible impact on C0T-1 RNA, nor did it cause similarly marked chromatin changes as did three different SAF-A mutations. Overall results support the concept that repeat-rich, chromatin-associated RNAs interact with multiple RNA binding proteins (RBPs) in a complex dynamic meshwork that is integral to larger-scale chromatin architecture and collectively influences cytological-scale DNA condensation.

scholarly journals Current insights into the implications of m6A RNA methylation and autophagy interaction in human diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xuechai Chen ◽  
Jianan Wang ◽  
Muhammad Tahir ◽  
Fangfang Zhang ◽  
Yuanyuan Ran ◽  
...  
Keyword(s):  
Intervertebral Disc Degeneration ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Degradation Process ◽  
Human Diseases ◽  
Rna Modification ◽  
Rna Methylation ◽  
M6a Rna Methylation ◽  
The Impact

AbstractAutophagy is a conserved degradation process crucial to maintaining the primary function of cellular and organismal metabolism. Impaired autophagy could develop numerous diseases, including cancer, cardiomyopathy, neurodegenerative disorders, and aging. N6-methyladenosine (m6A) is the most common RNA modification in eukaryotic cells, and the fate of m6A modified transcripts is controlled by m6A RNA binding proteins. m6A modification influences mRNA alternative splicing, stability, translation, and subcellular localization. Intriguingly, recent studies show that m6A RNA methylation could alter the expression of essential autophagy-related (ATG) genes and influence the autophagy function. Thus, both m6A modification and autophagy could play a crucial role in the onset and progression of various human diseases. In this review, we summarize the latest studies describing the impact of m6A modification in autophagy regulation and discuss the role of m6A modification-autophagy axis in different human diseases, including obesity, heart disease, azoospermatism or oligospermatism, intervertebral disc degeneration, and cancer. The comprehensive understanding of the m6A modification and autophagy interplay may help in interpreting their impact on human diseases and may aid in devising future therapeutic strategies.

scholarly journals Two functionally distinct RNA-binding motifs in the regulatory domain of the protein kinase DAI.

1995 ◽  
Vol 15 (1) ◽  
pp. 358-364 ◽  
Author(s):  
S R Green ◽  
L Manche ◽  
M B Mathews
Keyword(s):  
Amino Acid ◽  
Protein Kinase ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Alpha Helix ◽  
Binding Domain ◽  
Single Amino Acid ◽  
Double Stranded Rna ◽  
C Terminus ◽  
Rna Binding Domain

The RNA-binding domain of the protein kinase DAI, the double-stranded RNA inhibitor of translation, contains two repeats of a motif that is also found in a number of other RNA-binding proteins. This motif consists of 67 amino acid residues and is predicted to contain a positively charged alpha helix at its C terminus. We have analyzed the effects of equivalent single amino acid changes in three conserved residues distributed over each copy of the motif. Mutants in the C-terminal portion of either repeat were severely defective, indicating that both copies of the motif are essential for RNA binding. Changes in the N-terminal and central parts of the motif were more debilitating if they were made in the first motif than in the second, suggesting that the first motif is the more important for RNA binding and that the second motif is structurally more flexible. When the second motif was replaced by a duplicate of the first motif, the ectopic copy retained its greater sensitivity to mutation, implying that the two motifs have distinct functions with respect to the process of RNA binding. Furthermore, the mutations have the same effect on the binding of double-stranded RNA and VA RNA, consistent with the existence of a single RNA-binding domain for both activating and inhibitory RNAs.

scholarly journals Analyzing the Surface Structure of the Binding Domain on DNA and RNA Binding Proteins

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 30042-30049
Author(s):  
Wei Wang ◽  
Keliang Li ◽  
Hehe Lv ◽  
Hongjun Zhang ◽  
Shiguang Zhang ◽  
...  
Keyword(s):  
Surface Structure ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Binding Domain ◽  
Dna And Rna ◽  
Dna And Rna Binding

scholarly journals The 36-kilodalton embryonic-type cytoplasmic polyadenylation element-binding protein in Xenopus laevis is ElrA, a member of the ELAV family of RNA-binding proteins.

1997 ◽  
Vol 17 (11) ◽  
pp. 6402-6409 ◽  
Author(s):  
L Wu ◽  
P J Good ◽  
J D Richter
Keyword(s):  
Xenopus Laevis ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Binding Protein ◽  
Dominant Negative ◽  
Cytoplasmic Polyadenylation ◽  
Element Binding Protein

The translational activation of several maternal mRNAs in Xenopus laevis is dependent on cytoplasmic poly(A) elongation. Messages harboring the UUUUUAU-type cytoplasmic polyadenylation element (CPE) in their 3' untranslated regions (UTRs) undergo polyadenylation and translation during oocyte maturation. This CPE is bound by the protein CPEB, which is essential for polyadenylation. mRNAs that have the poly(U)12-27 embryonic-type CPE (eCPE) in their 3' UTRs undergo polyadenylation and translation during the early cleavage and blastula stages. A 36-kDa eCPE-binding protein in oocytes and embryos has been identified by UV cross-linking. We now report that this 36-kDa protein is ElrA, a member of the ELAV family of RNA-binding proteins. The proteins are identical in size, antibody directed against ElrA immunoprecipitates the 36-kDa protein, and the two proteins have the same RNA binding specificity in vitro. C12 and activin receptor mRNAs, both of which contain eCPEs, are detected in immunoprecipitated ElrA-mRNP complexes from eggs and embryos. In addition, this in vivo interaction requires the eCPE. Although a number of experiments failed to define a role for ElrA in cytoplasmic polyadenylation, the expression of a dominant negative ElrA protein in embryos results in an exogastrulation phenotype. The possible functions of ElrA in gastrulation are discussed.

scholarly journals Inferring Sequence-Structure Preferences of RNA-Binding Proteins with Convolutional Residual Networks

2018 ◽  
Author(s):  
Peter K. Koo ◽  
Praveen Anand ◽  
Steffan B. Paul ◽  
Sean R. Eddy
Keyword(s):  
Rna Structure ◽  
Binding Proteins ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Sequence Data ◽  
Synthetic Data ◽  
Sequence Motifs ◽  
Negative Effects ◽  
Interpretable Model ◽  
Saliency Analysis

AbstractTo infer the sequence and RNA structure specificities of RNA-binding proteins (RBPs) from experiments that enrich for bound sequences, we introduce a convolutional residual network which we call ResidualBind. ResidualBind significantly outperforms previous methods on experimental data from many RBP families. We interrogate ResidualBind to identify what features it has learned from high-affinity sequences with saliency analysis along with 1st-order and 2nd-orderin silicomutagenesis. We show that in addition to sequence motifs, ResidualBind learns a model that includes the number of motifs, their spacing, and both positive and negative effects of RNA structure context. Strikingly, ResidualBind learns RNA structure context, including detailed base-pairing relationships, directly from sequence data, which we confirm on synthetic data. ResidualBind is a powerful, flexible, and interpretable model that can uncovercis-recognition preferences across a broad spectrum of RBPs.

scholarly journals A Deep Learning approach predicts the impact of point mutations in intronic flanking regions on micro-exon splicing definition

2019 ◽  
Author(s):  
Lucas F. DaSilva ◽  
Ana C. Tahira ◽  
Vinicius Mesel ◽  
Sergio Verjovski-Almeida
Keyword(s):  
Rna Binding ◽  
De Novo ◽  
Rna Binding Proteins ◽  
Point Mutations ◽  
Base Point ◽  
Validation Dataset ◽  
Systematic Assessment ◽  
Exon Splicing ◽  
Flanking Sequences ◽  
The Impact

AbstractWhile mammalian exons are on average 140-nt-long, thousands of human genes harbor micro-exons (≤ 39 nt). Large numbers of micro-exons have their splicing altered in diseases such as autism and cancer, and yet there is no systematic assessment of the impact of point mutations in intronic flanking-sequences on the splicing of a neighboring micro-exon. Here, we constructed a model using the Convolutional Neural Network (CNN) to predict the impact of point mutations in intronic-flanking-sequences on the splicing of a neighboring micro-exon. The prediction model was based on both the sequence contents and conservation among species of the two 100-nt intronic regions (5’ and 3’) that flank all human micro-exons and a set with the same number of randomly selected long exons. After training our CNN model, the micro-exon splicing event prediction accuracy, using an independent validation dataset, was 0.71 with an area under the ROC curve of 0.76, showing that our model had identified sequence patterns that have been conserved in evolution in the introns that flank micro-exons. Next, we introduced in silico point mutations at each of the 200 nucleotides in the introns that flank a micro-exon and used the trained CNN algorithm to predict splicing for every mutated intronic sequence version. This analysis identified thousands of point mutations in the flanking introns that significantly decreased the power of the CNN model to correctly predict a neighboring micro-exon splicing event, thus pointing to predictive bases in intronic regions important for micro-exon splicing signaling. We found these predictive bases to locate within conserved RNA-binding-motifs for RNA-binding-proteins (RBPs) known to relate to micro-exon splicing. Experimental data of minigene splicing reporter changes upon intron-base point-mutation confirmed the effect predicted by the CNN model for some of the micro-exon splicing events. The model can be used for validating novel micro-exons de novo assembled from RNA-seq data, and for an unbiased screening of introns, identifying genomic bases that have high micro-exon-splicing predictive power, possibly revealing critical point mutations that would be related in a yet unknown manner to a given disease.

scholarly journals The Impact of Pro-Inflammatory Cytokines on Alternative Splicing Patterns in Human Islets

2021 ◽  
Author(s):  
Wenting Wu ◽  
Farooq Syed ◽  
Edward Simpson ◽  
Chih-Chun Lee ◽  
Jing Liu ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Mhc Class Ii ◽  
Single Molecule ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Ex Vivo ◽  
Class Ii ◽  
Human Islets ◽  
Β Cell ◽  
The Impact

Alternative splicing (AS) within the β cell has been proposed as one potential pathway that may exacerbate autoimmunity and unveil novel immunogenic epitopes in type 1 diabetes (T1D). We employed a computational strategy to prioritize pathogenic splicing events in human islets treated with IL-1β + IFN-γ as an <i>ex vivo</i> model of T1D and coupled this analysis with a k-mer based approach to predict RNA binding proteins involved in AS. In total, 969 AS events were identified in cytokine-treated islets, with the majority (44.8%) involving a skipped exon. ExonImpact identified 129 events predicted to impact protein structure. AS occurred with high frequency in MHC Class II-related mRNAs, and targeted qPCR validated reduced inclusion of Exon5 in the MHC Class II gene HLA-DMB. Single-molecule RNA FISH confirmed increased HLA-DMB splicing in pancreatic sections from human donors with established T1D and autoantibody positivity. Serine and Arginine Rich Splicing Factor 2 was implicated in 37.2% of potentially pathogenic events, including Exon5 exclusion in HLA-DMB. Together, these data suggest that dynamic control of AS plays a role in the β cell response to inflammatory signals during T1D evolution.

scholarly journals The Impact of Pro-Inflammatory Cytokines on Alternative Splicing Patterns in Human Islets

2021 ◽  
Author(s):  
Wenting Wu ◽  
Farooq Syed ◽  
Edward Simpson ◽  
Chih-Chun Lee ◽  
Jing Liu ◽  
...  
Keyword(s):  
Alternative Splicing ◽  
Mhc Class Ii ◽  
Single Molecule ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Ex Vivo ◽  
Class Ii ◽  
Human Islets ◽  
Β Cell ◽  
The Impact

Alternative splicing (AS) within the β cell has been proposed as one potential pathway that may exacerbate autoimmunity and unveil novel immunogenic epitopes in type 1 diabetes (T1D). We employed a computational strategy to prioritize pathogenic splicing events in human islets treated with IL-1β + IFN-γ as an <i>ex vivo</i> model of T1D and coupled this analysis with a k-mer based approach to predict RNA binding proteins involved in AS. In total, 969 AS events were identified in cytokine-treated islets, with the majority (44.8%) involving a skipped exon. ExonImpact identified 129 events predicted to impact protein structure. AS occurred with high frequency in MHC Class II-related mRNAs, and targeted qPCR validated reduced inclusion of Exon5 in the MHC Class II gene HLA-DMB. Single-molecule RNA FISH confirmed increased HLA-DMB splicing in pancreatic sections from human donors with established T1D and autoantibody positivity. Serine and Arginine Rich Splicing Factor 2 was implicated in 37.2% of potentially pathogenic events, including Exon5 exclusion in HLA-DMB. Together, these data suggest that dynamic control of AS plays a role in the β cell response to inflammatory signals during T1D evolution.

scholarly journals Protein methyltransferase 7 deficiency in Leishmania major increases neutrophil associated pathology in murine model

2021 ◽  
Vol 15 (3) ◽  
pp. e0009230
Author(s):  
Juliana Alcoforado Diniz ◽  
Mariana M. Chaves ◽  
Slavica Vaselek ◽  
Rubens D. Miserani Magalhães ◽  
Rafael Ricci-Azevedo ◽  
...  
Keyword(s):  
Transcriptional Control ◽  
Leishmania Major ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Binding Capacity ◽  
Sand Fly ◽  
Parasite Development ◽  
Post Translational Modification ◽  
Phlebotomus Duboscqi ◽  
The Impact

Leishmania major is the main causative agent of cutaneous leishmaniasis in the Old World. In Leishmania parasites, the lack of transcriptional control is mostly compensated by post-transcriptional mechanisms. Methylation of arginine is a conserved post-translational modification executed by Protein Arginine Methyltransferase (PRMTs). The genome from L. major encodes five PRMT homologs, including the cytosolic protein associated with several RNA-binding proteins, LmjPRMT7. It has been previously reported that LmjPRMT7 could impact parasite infectivity. In addition, a more recent work has clearly shown the importance of LmjPRMT7 in RNA-binding capacity and protein stability of methylation targets, demonstrating the role of this enzyme as an important epigenetic regulator of mRNA metabolism. In this study, we unveil the impact of PRMT7-mediated methylation on parasite development and virulence. Our data reveals that higher levels of LmjPRMT7 can impair parasite pathogenicity, and that deletion of this enzyme rescues the pathogenic phenotype of an attenuated strain of L. major. Interestingly, lesion formation caused by LmjPRMT7 knockout parasites is associated with an exacerbated inflammatory reaction in the tissue correlated with an excessive neutrophil recruitment. Moreover, the absence of LmjPRMT7 also impairs parasite development within the sand fly vector Phlebotomus duboscqi. Finally, a transcriptome analysis shed light onto possible genes affected by depletion of this enzyme. Taken together, this study highlights how post-transcriptional regulation can affect different aspects of the parasite biology.

scholarly journals Positional motif analysis reveals the extent of specificity of protein-RNA interactions observed by CLIP

2021 ◽  
Author(s):  
Klara Kuret ◽  
Aram Gustav Amalietti ◽  
Jernej Ule
Keyword(s):  
Rna Binding ◽  
Rna Binding Proteins ◽  
Data Interpretation ◽  
Low Complexity ◽  
Motif Analysis ◽  
Link Type ◽  
Motif Enrichment ◽  
The Impact

AbstractBackgroundCrosslinking and immunoprecipitation (CLIP) is a method used to identify in vivo RNA– protein binding sites on a transcriptome-wide scale. With the increasing amounts of available data for RNA-binding proteins (RBPs), it is important to understand to what degree the enriched motifs specify the RNA binding profiles of RBPs in cells.ResultsWe develop positionally-enriched k-mer analysis (PEKA), a computational tool for efficient analysis of enriched motifs from individual CLIP datasets, which minimises the impact of technical and regional genomic biases by internal data normalisation. We cross-validate PEKA with mCross, and show that background correction by size-matched input doesn’t generally improve the specificity of detected motifs. We identify motif classes with common enrichment patterns across eCLIP datasets and across RNA regions, while also observing variations in the specificity and the extent of motif enrichment across eCLIP datasets, between variant CLIP protocols, and between CLIP and in vitro binding data. Thereby we gain insights into the contributions of technical and regional genomic biases to the enriched motifs, and find how motif enrichment features relate to the domain composition and low-complexity regions (LCRs) of the studied proteins.ConclusionsOur study provides insights into the overall contributions of regional binding preferences, protein domains and LCRs to the specificity of protein-RNA interactions, and shows the value of cross-motif and cross-RBP comparison for data interpretation. Our results are presented for exploratory analysis via an online platform in an RBP-centric and motif-centric manner (https://imaps.goodwright.com/apps/peka/). PEKA is available from https://github.com/ulelab/peka.

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