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Petrizzelli F, Biagini T, Bianco SD, Liorni N, Napoli A, Castellana S, Mazza T. Connecting the dots: A practical evaluation of web-tools for describing protein dynamics as networks. FRONTIERS IN BIOINFORMATICS 2022; 2:1045368. [PMID: 36438625 PMCID: PMC9689706 DOI: 10.3389/fbinf.2022.1045368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 10/05/2022] [Indexed: 01/25/2023] Open
Abstract
Protein Structure Networks (PSNs) are a well-known mathematical model for estimation and analysis of the three-dimensional protein structure. Investigating the topological architecture of PSNs may help identify the crucial amino acid residues for protein stability and protein-protein interactions, as well as deduce any possible mutational effects. But because proteins go through conformational changes to give rise to essential biological functions, this has to be done dynamically over time. The most effective method to describe protein dynamics is molecular dynamics simulation, with the most popular software programs for manipulating simulations to infer interaction networks being RING, MD-TASK, and NAPS. Here, we compare the computational approaches used by these three tools-all of which are accessible as web servers-to understand the pathogenicity of missense mutations and talk about their potential applications as well as their advantages and disadvantages.
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Affiliation(s)
- Francesco Petrizzelli
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tommaso Biagini
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Salvatore Daniele Bianco
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy,Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Niccolò Liorni
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy,Department of Experimental Medicine, Sapienza University of Rome, Rome, Italy
| | - Alessandro Napoli
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Stefano Castellana
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy
| | - Tommaso Mazza
- Bioinformatics Laboratory, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Italy,*Correspondence: Tommaso Mazza,
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2
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Comprehensive characterization of posttranscriptional impairment-related 3'-UTR mutations in 2413 whole genomes of cancer patients. NPJ Genom Med 2022; 7:34. [PMID: 35654793 PMCID: PMC9163142 DOI: 10.1038/s41525-022-00305-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 05/05/2022] [Indexed: 11/09/2022] Open
Abstract
The 3' untranslated region (3'-UTR) is the vital element regulating gene expression, but most studies have focused on variations in RNA-binding proteins (RBPs), miRNAs, alternative polyadenylation (APA) and RNA modifications. To explore the posttranscriptional function of 3'-UTR somatic mutations in tumorigenesis, we collected whole-genome data from 2413 patients across 18 cancer types. Our updated algorithm, PIVar, revealed 25,216 3'-UTR posttranscriptional impairment-related SNVs (3'-UTR piSNVs) spanning 2930 genes; 24 related RBPs were significantly enriched. The somatic 3'-UTR piSNV ratio was markedly increased across all 18 cancer types, which was associated with worse survival for four cancer types. Several cancer-related genes appeared to facilitate tumorigenesis at the protein and posttranscriptional regulation levels, whereas some 3'-UTR piSNV-affected genes functioned mainly via posttranscriptional mechanisms. Moreover, we assessed immune cell and checkpoint characteristics between the high/low 3'-UTR piSNV ratio groups and predicted 80 compounds associated with the 3'-UTR piSNV-affected gene expression signature. In summary, our study revealed the prevalence and clinical relevance of 3'-UTR piSNVs in cancers, and also demonstrates that in addition to affecting miRNAs, 3'-UTR piSNVs perturb RBPs binding, APA and m6A RNA modification, which emphasized the importance of considering 3'-UTR piSNVs in cancer biology.
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3
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Furlan M, Galeota E, Gaudio ND, Dassi E, Caselle M, de Pretis S, Pelizzola M. Genome-wide dynamics of RNA synthesis, processing, and degradation without RNA metabolic labeling. Genome Res 2020; 30:1492-1507. [PMID: 32978246 PMCID: PMC7605262 DOI: 10.1101/gr.260984.120] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 08/21/2020] [Indexed: 12/13/2022]
Abstract
The quantification of the kinetic rates of RNA synthesis, processing, and degradation are largely based on the integrative analysis of total and nascent transcription, the latter being quantified through RNA metabolic labeling. We developed INSPEcT−, a computational method based on the mathematical modeling of premature and mature RNA expression that is able to quantify kinetic rates from steady-state or time course total RNA-seq data without requiring any information on nascent transcripts. Our approach outperforms available solutions, closely recapitulates the kinetic rates obtained through RNA metabolic labeling, improves the ability to detect changes in transcript half-lives, reduces the cost and complexity of the experiments, and can be adopted to study experimental conditions in which nascent transcription cannot be readily profiled. Finally, we applied INSPEcT− to the characterization of post-transcriptional regulation landscapes in dozens of physiological and disease conditions. This approach was included in the INSPEcT Bioconductor package, which can now unveil RNA dynamics from steady-state or time course data, with or without the profiling of nascent RNA.
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Affiliation(s)
- Mattia Furlan
- Center for Genomic Science, Fondazione Istituto Italiano di Tecnologia, 20139 Milan, Italy.,Physics Department and INFN, University of Turin, 10125 Turin, Italy
| | - Eugenia Galeota
- Center for Genomic Science, Fondazione Istituto Italiano di Tecnologia, 20139 Milan, Italy
| | - Nunzio Del Gaudio
- Center for Genomic Science, Fondazione Istituto Italiano di Tecnologia, 20139 Milan, Italy
| | - Erik Dassi
- Centre for Integrative Biology, University of Trento, 38123 Trento, Italy
| | - Michele Caselle
- Physics Department and INFN, University of Turin, 10125 Turin, Italy
| | - Stefano de Pretis
- Center for Genomic Science, Fondazione Istituto Italiano di Tecnologia, 20139 Milan, Italy
| | - Mattia Pelizzola
- Center for Genomic Science, Fondazione Istituto Italiano di Tecnologia, 20139 Milan, Italy
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4
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Teng H, Wei W, Li Q, Xue M, Shi X, Li X, Mao F, Sun Z. Prevalence and architecture of posttranscriptionally impaired synonymous mutations in 8,320 genomes across 22 cancer types. Nucleic Acids Res 2020; 48:1192-1205. [PMID: 31950163 PMCID: PMC7026592 DOI: 10.1093/nar/gkaa019] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2019] [Accepted: 01/07/2020] [Indexed: 02/06/2023] Open
Abstract
Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.
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Affiliation(s)
- Huajing Teng
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Wenqing Wei
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qinglan Li
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Meiying Xue
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaohui Shi
- Sino-Danish college, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xianfeng Li
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China.,Key laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Radiation Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Fengbiao Mao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhongsheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
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5
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Marchese D, Botta-Orfila T, Cirillo D, Rodriguez JA, Livi CM, Fernández-Santiago R, Ezquerra M, Martí MJ, Bechara E, Tartaglia GG. Discovering the 3' UTR-mediated regulation of alpha-synuclein. Nucleic Acids Res 2018; 45:12888-12903. [PMID: 29149290 PMCID: PMC5728410 DOI: 10.1093/nar/gkx1048] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 10/20/2017] [Indexed: 12/24/2022] Open
Abstract
Recent evidence indicates a link between Parkinson's Disease (PD) and the expression of a-synuclein (SNCA) isoforms with different 3′ untranslated regions (3′UTRs). Yet, the post-transcriptional mechanisms regulating SNCA expression are unknown. Using a large-scale in vitro /in silico screening we identified RNA-binding proteins (RBPs) that interact with SNCA 3′ UTRs. We identified two RBPs, ELAVL1 and TIAR, that bind with high affinity to the most abundant and translationally active 3′ UTR isoform (575 nt). Knockdown and overexpression experiments indicate that both ELAVL1 and TIAR positively regulate endogenous SNCA in vivo. The mechanism of regulation implies mRNA stabilization as well as enhancement of translation in the case of TIAR. We observed significant alteration of both TIAR and ELAVL1 expression in motor cortex of post-mortem brain donors and primary cultured fibroblast from patients affected by PD and Multiple System Atrophy (MSA). Moreover, trans expression quantitative trait loci (trans-eQTLs) analysis revealed that a group of single nucleotide polymorphisms (SNPs) in TIAR genomic locus influences SNCA expression in two different brain areas, nucleus accumbens and hippocampus. Our study sheds light on the 3′ UTR-mediated regulation of SNCA and its link with PD pathogenesis, thus opening up new avenues for investigation of post-transcriptional mechanisms in neurodegeneration.
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Affiliation(s)
- Domenica Marchese
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Teresa Botta-Orfila
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Davide Cirillo
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Barcelona Supercomputing Center (BSC), Torre Girona c/Jordi Girona, 29, 08034 Barcelona, Spain
| | - Juan Antonio Rodriguez
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Centro Nacional de Análisis Genómico, c/BaldiriReixac, 4, 08028 Barcelona, Spain
| | - Carmen Maria Livi
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,IFOM, the FIRC Institute of Molecular Oncology, Via Adamello 16, 20139 Milan, Italy
| | - Rubén Fernández-Santiago
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Institut de Neurociències Hospital Clínic, CIBERNED, Barcelona, Spain
| | - Mario Ezquerra
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Institut de Neurociències Hospital Clínic, CIBERNED, Barcelona, Spain
| | - Maria J Martí
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Parkinson's Disease and Movement Disorders Unit, Institut de Neurociències Hospital Clínic, CIBERNED, Barcelona, Spain
| | - Elias Bechara
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Gian Gaetano Tartaglia
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Dr. Aiguader 88, 08003 Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Institucio Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
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6
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Associating transcription factors and conserved RNA structures with gene regulation in the human brain. Sci Rep 2017; 7:5776. [PMID: 28720872 PMCID: PMC5516038 DOI: 10.1038/s41598-017-06200-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 06/20/2017] [Indexed: 02/06/2023] Open
Abstract
Anatomical subdivisions of the human brain can be associated with different neuronal functions. This functional diversification is reflected by differences in gene expression. By analyzing post-mortem gene expression data from the Allen Brain Atlas, we investigated the impact of transcription factors (TF) and RNA secondary structures on the regulation of gene expression in the human brain. First, we modeled the expression of a gene as a linear combination of the expression of TFs. We devised an approach to select robust TF-gene interactions and to determine localized contributions to gene expression of TFs. Among the TFs with the most localized contributions, we identified EZH2 in the cerebellum, NR3C1 in the cerebral cortex and SRF in the basal forebrain. Our results suggest that EZH2 is involved in regulating ZIC2 and SHANK1 which have been linked to neurological diseases such as autism spectrum disorder. Second, we associated enriched regulatory elements inside differentially expressed mRNAs with RNA secondary structure motifs. We found a group of purine-uracil repeat RNA secondary structure motifs plus other motifs in neuron related genes such as ACSL4 and ERLIN2.
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7
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Bisio A, Latorre E, Andreotti V, Bressac-de Paillerets B, Harland M, Scarra GB, Ghiorzo P, Spitale RC, Provenzani A, Inga A. The 5'-untranslated region of p16INK4a melanoma tumor suppressor acts as a cellular IRES, controlling mRNA translation under hypoxia through YBX1 binding. Oncotarget 2016; 6:39980-94. [PMID: 26498684 PMCID: PMC4741874 DOI: 10.18632/oncotarget.5387] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2015] [Accepted: 10/05/2015] [Indexed: 12/20/2022] Open
Abstract
CDKN2A/p16INK4a is an essential tumor suppressor gene that controls cell cycle progression and replicative senescence. It is also the main melanoma susceptibility gene. Here we report that p16INK4a 5'UTR mRNA acts as a cellular Internal Ribosome Entry Site (IRES). The potential for p16INK4a 5'UTR to drive cap-independent translation was evaluated by dual-luciferase assays using bicistronic and monocistronic vectors. Results of reporters' relative activities coupled to control analyses for actual bicistronic mRNA transcription, indicated that the wild type p16INK4a 5'UTR could stimulate cap-independent translation. Notably, hypoxic stress and the treatment with mTOR inhibitors enhanced the translation-stimulating property of p16INK4a 5'UTR. RNA immunoprecipitation performed in melanoma-derived SK-Mel-28 and in a patient-derived lymphoblastoid cell line indicated that YBX1 can bind the wild type p16INK4a mRNA increasing its translation efficiency, particularly during hypoxic stress. Modulation of YBX1 expression further supported its involvement in cap-independent translation of the wild type p16INK4a but not a c.-42T>A variant. RNA SHAPE assays revealed local flexibility changes for the c.-42T>A variant at the predicted YBX1 binding site region. Our results indicate that p16INK4a 5'UTR contains a cellular IRES that can enhance mRNA translation efficiency, in part through YBX1.
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Affiliation(s)
- Alessandra Bisio
- Laboratory of Transcriptional Networks, Centre for Integrative Biology, CIBIO, University of Trento, Trento, Italy
| | - Elisa Latorre
- Laboratory of Genomic Screening, Centre for Integrative Biology, CIBIO, University of Trento, Trento, Italy
| | - Virginia Andreotti
- Laboratory of Genetics of Rare Hereditary Cancers, DiMI, University of Genoa, Italy and IRCCS AOU San Martino-IST, Genoa, Italy
| | | | - Mark Harland
- Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Giovanna Bianchi Scarra
- Laboratory of Genetics of Rare Hereditary Cancers, DiMI, University of Genoa, Italy and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Paola Ghiorzo
- Laboratory of Genetics of Rare Hereditary Cancers, DiMI, University of Genoa, Italy and IRCCS AOU San Martino-IST, Genoa, Italy
| | - Robert C Spitale
- Department of Pharmaceutical Sciences, University of California, Irvine, CA, USA
| | - Alessandro Provenzani
- Laboratory of Genomic Screening, Centre for Integrative Biology, CIBIO, University of Trento, Trento, Italy
| | - Alberto Inga
- Laboratory of Transcriptional Networks, Centre for Integrative Biology, CIBIO, University of Trento, Trento, Italy
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8
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Mao F, Xiao L, Li X, Liang J, Teng H, Cai W, Sun ZS. RBP-Var: a database of functional variants involved in regulation mediated by RNA-binding proteins. Nucleic Acids Res 2016; 44:D154-63. [PMID: 26635394 PMCID: PMC4702914 DOI: 10.1093/nar/gkv1308] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 11/01/2015] [Accepted: 11/09/2015] [Indexed: 12/31/2022] Open
Abstract
Transcription factors bind to the genome by forming specific contacts with the primary DNA sequence; however, RNA-binding proteins (RBPs) have greater scope to achieve binding specificity through the RNA secondary structure. It has been revealed that single nucleotide variants (SNVs) that alter RNA structure, also known as RiboSNitches, exhibit 3-fold greater local structure changes than replicates of the same DNA sequence, demonstrated by the fact that depletion of RiboSNitches could result in the alteration of specific RNA shapes at thousands of sites, including 3' UTRs, binding sites of microRNAs and RBPs. However, the network between SNVs and post-transcriptional regulation remains unclear. Here, we developed RBP-Var, a database freely available at http://www.rbp-var.biols.ac.cn/, which provides annotation of functional variants involved in post-transcriptional interaction and regulation. RBP-Var provides an easy-to-use web interface that allows users to rapidly find whether SNVs of interest can transform the secondary structure of RNA and identify RBPs whose binding may be subsequently disrupted. RBP-Var integrates DNA and RNA biology to understand how various genetic variants and post-transcriptional mechanisms cooperate to orchestrate gene expression. In summary, RBP-Var is useful in selecting candidate SNVs for further functional studies and exploring causal SNVs underlying human diseases.
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Affiliation(s)
- Fengbiao Mao
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Sciences, Beijing 100049, China
| | - Luoyuan Xiao
- Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
| | - Xianfeng Li
- State Key Laboratory of Medical Genetics, Central South University, Changsha, Hunan, 410078, China
| | - Jialong Liang
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huajing Teng
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Wanshi Cai
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhong Sheng Sun
- Beijing Institutes of Life Science, Chinese Academy of Sciences, Beijing 100101, China Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou 325035, China
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9
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Hecker N, Christensen-Dalsgaard M, Seemann SE, Havgaard JH, Stadler PF, Hofacker IL, Nielsen H, Gorodkin J. Optimizing RNA structures by sequence extensions using RNAcop. Nucleic Acids Res 2015; 43:8135-45. [PMID: 26283181 PMCID: PMC4787817 DOI: 10.1093/nar/gkv813] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2015] [Revised: 07/28/2015] [Accepted: 07/30/2015] [Indexed: 12/26/2022] Open
Abstract
A key aspect of RNA secondary structure prediction is the identification of novel functional elements. This is a challenging task because these elements typically are embedded in longer transcripts where the borders between the element and flanking regions have to be defined. The flanking sequences impact the folding of the functional elements both at the level of computational analyses and when the element is extracted as a transcript for experimental analysis. Here, we analyze how different flanking region lengths impact folding into a constrained structure by computing probabilities of folding for different sizes of flanking regions. Our method, RNAcop (RNA context optimization by probability), is tested on known and de novo predicted structures. In vitro experiments support the computational analysis and suggest that for a number of structures, choosing proper lengths of flanking regions is critical. RNAcop is available as web server and stand-alone software via http://rth.dk/resources/rnacop.
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Affiliation(s)
- Nikolai Hecker
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Mikkel Christensen-Dalsgaard
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Cellular and Molecular Medicine, Panum Institute, University of Copenhagen, Bledgamsvej 3, 2200 Copenhagen N, Denmark
| | - Stefan E Seemann
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Jakob H Havgaard
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
| | - Peter F Stadler
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Bioinformatics Group, Department of Computer Science & IZBI-Interdisciplinary Center for Bioinformatics & LIFE-Leipzig Research Center for Civilization Diseases, University Leipzig, Härtelstraße 16-18, 04107 Leipzig, Germany Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090 Wien, Austria Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103 Leipzig, Germany Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA
| | - Ivo L Hofacker
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Institute for Theoretical Chemistry, University of Vienna, Währingerstraße 17, 1090 Wien, Austria
| | - Henrik Nielsen
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Cellular and Molecular Medicine, Panum Institute, University of Copenhagen, Bledgamsvej 3, 2200 Copenhagen N, Denmark
| | - Jan Gorodkin
- Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark Department of Veterinary Clinical and Animal Science, University of Copenhagen, Grønnegårdsvej 3, 1870 Frederiksberg C, Denmark
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10
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Blin K, Dieterich C, Wurmus R, Rajewsky N, Landthaler M, Akalin A. DoRiNA 2.0--upgrading the doRiNA database of RNA interactions in post-transcriptional regulation. Nucleic Acids Res 2014; 43:D160-7. [PMID: 25416797 PMCID: PMC4383974 DOI: 10.1093/nar/gku1180] [Citation(s) in RCA: 102] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
The expression of almost all genes in animals is subject to post-transcriptional regulation by RNA binding proteins (RBPs) and microRNAs (miRNAs). The interactions between both RBPs and miRNAs with mRNA can be mapped on a whole-transcriptome level using experimental and computational techniques established in the past years. The combined action of RBPs and miRNAs is thought to form a post-transcriptional regulatory code. Here we present doRiNA 2.0, available at http://dorina.mdc-berlin.de. In this highly improved new version, we have completely reworked the user interface and expanded the database to improve the usability of the website. Taking into account user feedback over the past years, the input forms for both the simple and the combinatorial search function have been streamlined and combined into a single web page that will also display the search results. Especially, custom uploads is one of the key new features in doRiNA 2.0. To enable the inclusion of doRiNA into third-party analysis pipelines, all operations are accessible via a REST API. Alternatively, local installations can be queried using a Python API. Both the web application and the APIs are available under an OSI-approved Open Source license that allows research and commercial access and re-use.
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Affiliation(s)
- Kai Blin
- Computational RNA Biology Group, Max Planck Institute for Biology of Ageing, 50931 Cologne, Germany
| | - Christoph Dieterich
- Computational RNA Biology Group, Max Planck Institute for Biology of Ageing, 50931 Cologne, Germany
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11
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Dassi E, Quattrone A. Fingerprints of a message: integrating positional information on the transcriptome. Front Cell Dev Biol 2014; 2:39. [PMID: 25364746 PMCID: PMC4207014 DOI: 10.3389/fcell.2014.00039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 07/30/2014] [Indexed: 12/24/2022] Open
Abstract
The recent explosion of high-throughput sequencing methods applied to RNA molecules is allowing us to go beyond the description of sequence variants and their relative abundances, as measured by RNA-seq. We can now probe for RNA engagement in polysomes, for ribosomes, RNA binding proteins and microRNAs binding sites, for RNA secondary structure and for RNA methylation. These descriptors produce a steadily growing multidimensional array of positional information on RNA sequences, whose effective integration only would bring to decipher the regulatory interplay occurring between proteins, RNAs and their modifications on the transcriptome. This interplay ultimately dictates the degree of mRNA availability to translation, and thus the occurrence of cell phenotypes. However, several issues in data presentation are slowing down effective integration. A standardization effort for new dataset types produced should be urgently undertaken to solve these issues. Providing uniformed experimental details along with datasets processed to be directly usable and employing shared formats would greatly simplify integration efforts, strengthening hypotheses stemming from correlative observations and eventually bringing to mechanistic understanding.
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Affiliation(s)
- Erik Dassi
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento Trento, Italy
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento Trento, Italy
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Müller S, Rycak L, Afonso-Grunz F, Winter P, Zawada AM, Damrath E, Scheider J, Schmäh J, Koch I, Kahl G, Rotter B. APADB: a database for alternative polyadenylation and microRNA regulation events. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau076. [PMID: 25052703 PMCID: PMC4105710 DOI: 10.1093/database/bau076] [Citation(s) in RCA: 68] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3′ untranslated region (3′UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3′UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3′ end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3′ end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3′UTR lengths, especially for chicken, and APADB provides necessary information to close this gap. Database URL:http://tools.genxpro.net/apadb/
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Affiliation(s)
- Sören Müller
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, GermanyPlant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Lukas Rycak
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Fabian Afonso-Grunz
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, GermanyPlant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Peter Winter
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Adam M Zawada
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Ewa Damrath
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Jessica Scheider
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Juliane Schmäh
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Ina Koch
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Günter Kahl
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
| | - Björn Rotter
- Plant Molecular Biology, Molecular BioSciences, University of Frankfurt am Main, Marie-Curie-Street 9, D-60439 Frankfurt, Germany, GenXPro GmbH, Frankfurt Innovation Center Biotechnology, Altenhöferallee 3, D-60438 Frankfurt, Germany, Molecular Bioinformatics Group, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt "Macromolecular Complexes", Institute of Computer Science, Robert-Mayer-Strasse 11-15, D-60325 Frankfurt am Main, Germany, Department of Internal Medicine IV; Saarland University Medical Center, Kirrberger Strasse, D-66421 Homburg/Saar, Germany, Experimental Neurology, Department of Neurology, Goethe University Medical School, Heinrich, Hoffmann Strasse 7, D-60528 Frankfurt am Main, Germany, Institute for Ecology, Evolution and Diversity, Aquatic Ecotoxicology, University of Frankfurt am Main, Max-von-Laue-Str. 13, D-60438 Frankfurt, Germany and Department of Pediatrics, University Hospital Schleswig-Holstein, Schwanenweg 20, D-24105 Kiel, Germany
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13
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Biswas A, Brown CM. Scan for Motifs: a webserver for the analysis of post-transcriptional regulatory elements in the 3' untranslated regions (3' UTRs) of mRNAs. BMC Bioinformatics 2014; 15:174. [PMID: 24909639 PMCID: PMC4067372 DOI: 10.1186/1471-2105-15-174] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Accepted: 05/16/2014] [Indexed: 11/21/2022] Open
Abstract
Background Gene expression in vertebrate cells may be controlled post-transcriptionally through regulatory elements in mRNAs. These are usually located in the untranslated regions (UTRs) of mRNA sequences, particularly the 3′UTRs. Results Scan for Motifs (SFM) simplifies the process of identifying a wide range of regulatory elements on alignments of vertebrate 3′UTRs. SFM includes identification of both RNA Binding Protein (RBP) sites and targets of miRNAs. In addition to searching pre-computed alignments, the tool provides users the flexibility to search their own sequences or alignments. The regulatory elements may be filtered by expected value cutoffs and are cross-referenced back to their respective sources and literature. The output is an interactive graphical representation, highlighting potential regulatory elements and overlaps between them. The output also provides simple statistics and links to related resources for complementary analyses. The overall process is intuitive and fast. As SFM is a free web-application, the user does not need to install any software or databases. Conclusions Visualisation of the binding sites of different classes of effectors that bind to 3′UTRs will facilitate the study of regulatory elements in 3′ UTRs.
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Affiliation(s)
| | - Chris M Brown
- Department of Biochemistry, Genetics Otago, University of Otago, Dunedin, New Zealand.
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14
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Livi CM, Blanzieri E. Protein-specific prediction of mRNA binding using RNA sequences, binding motifs and predicted secondary structures. BMC Bioinformatics 2014; 15:123. [PMID: 24780077 PMCID: PMC4098778 DOI: 10.1186/1471-2105-15-123] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Accepted: 04/16/2014] [Indexed: 12/14/2022] Open
Abstract
Background RNA-binding proteins interact with specific RNA molecules to regulate important cellular processes. It is therefore necessary to identify the RNA interaction partners in order to understand the precise functions of such proteins. Protein-RNA interactions are typically characterized using in vivo and in vitro experiments but these may not detect all binding partners. Therefore, computational methods that capture the protein-dependent nature of such binding interactions could help to predict potential binding partners in silico. Results We have developed three methods to predict whether an RNA can interact with a particular RNA-binding protein using support vector machines and different features based on the sequence (the Oli method), the motif score (the OliMo method) and the secondary structure (the OliMoSS method). We applied these approaches to different experimentally-derived datasets and compared the predictions with RNAcontext and RPISeq. Oli outperformed OliMoSS and RPISeq, confirming our protein-specific predictions and suggesting that tetranucleotide frequencies are appropriate discriminative features. Oli and RNAcontext were the most competitive methods in terms of the area under curve. A precision-recall curve analysis achieved higher precision values for Oli. On a second experimental dataset including real negative binding information, Oli outperformed RNAcontext with a precision of 0.73 vs. 0.59. Conclusions Our experiments showed that features based on primary sequence information are sufficiently discriminating to predict specific RNA-protein interactions. Sequence motifs and secondary structure information were not necessary to improve these predictions. Finally we confirmed that protein-specific experimental data concerning RNA-protein interactions are valuable sources of information that can be used for the efficient training of models for in silico predictions. The scripts are available upon request to the corresponding author.
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Affiliation(s)
- Carmen M Livi
- Department of Information Engineering and Computer Science, University of Trento, Via Sommarive 5, Trento, Italy.
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15
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Cirillo D, Marchese D, Agostini F, Livi CM, Botta-Orfila T, Tartaglia GG. Constitutive patterns of gene expression regulated by RNA-binding proteins. Genome Biol 2014; 15:R13. [PMID: 24401680 PMCID: PMC4054784 DOI: 10.1186/gb-2014-15-1-r13] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2013] [Accepted: 01/02/2014] [Indexed: 02/04/2023] Open
Abstract
Background RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but the partners of many RNA-binding proteins are still uncharacterized. Results We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively and negatively correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein–RNA interactions, with positively correlated patterns related to cell cycle control and negatively correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein–RNA interactions and expression networks, we developed the catRAPID express web server. Conclusions Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid future experimental studies.
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16
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Panni S, Rombo SE. Searching for repetitions in biological networks: methods, resources and tools. Brief Bioinform 2013; 16:118-36. [PMID: 24300112 DOI: 10.1093/bib/bbt084] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
We present here a compact overview of the data, models and methods proposed for the analysis of biological networks based on the search for significant repetitions. In particular, we concentrate on three problems widely studied in the literature: 'network alignment', 'network querying' and 'network motif extraction'. We provide (i) details of the experimental techniques used to obtain the main types of interaction data, (ii) descriptions of the models and approaches introduced to solve such problems and (iii) pointers to both the available databases and software tools. The intent is to lay out a useful roadmap for identifying suitable strategies to analyse cellular data, possibly based on the joint use of different interaction data types or analysis techniques.
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Tebaldi T, Dassi E, Kostoska G, Viero G, Quattrone A. tRanslatome: an R/Bioconductor package to portray translational control. ACTA ACUST UNITED AC 2013; 30:289-91. [PMID: 24222209 PMCID: PMC3892686 DOI: 10.1093/bioinformatics/btt634] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Summary: High-throughput technologies have led to an explosion of genomic data available for automated analysis. The consequent possibility to simultaneously sample multiple layers of variation along the gene expression flow requires computational methods integrating raw information from different ‘-omics’. It has been recently demonstrated that translational control is a widespread phenomenon, with profound and still underestimated regulation capabilities. Although detecting changes in the levels of total messenger RNAs (mRNAs; the transcriptome), of polysomally loaded mRNAs (the translatome) and of proteins (the proteome) is experimentally feasible in a high-throughput way, the integration of these levels is still far from being robustly approached. Here we introduce tRanslatome, a new R/Bioconductor package, which is a complete platform for the simultaneous pairwise analysis of transcriptome, translatome and proteome data. The package includes most of the available statistical methods developed for the analysis of high-throughput data, allowing the parallel comparison of differentially expressed genes and the corresponding differentially enriched biological themes. Notably, it also enables the prediction of translational regulatory elements on mRNA sequences. The utility of this tool is demonstrated with two case studies. Availability and implementation: tRanslatome is available in Bioconductor. Contact: t.tebaldi@unitn.it Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Toma Tebaldi
- Laboratory of Translational Genomics - Centre for Integrative Biology, University of Trento, Via delle Regole 101, 38123 Mattarello (TN) and Institute of Biophysics CNR - Via alla Cascata 56/C, 38123 Povo (TN), Italy
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Kropivšek K, Pickford J, Carter DA. Postnatal dynamics of Zeb2 expression in rat brain: analysis of novel 3' UTR sequence reveals a miR-9 interacting site. J Mol Neurosci 2013; 52:138-47. [PMID: 24458742 DOI: 10.1007/s12031-013-0146-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2013] [Accepted: 10/09/2013] [Indexed: 12/17/2022]
Abstract
ZEB2 is a transcription factor with established roles in neurogenesis but no defined function in postnatal brain despite extensive neuronal expression in telencephalic structures. Multiple, incompletely annotated transcripts derive from the Zeb2 locus; the purpose of the present study was to structurally characterize rat brain Zeb2 transcripts with respect to 3' untranslated (UTR) sequence in order to understand Zeb2 transcript regulation including possible interactions with regulatory molecules such as neuronal miRNAs. We cloned a 5054-nucleotide Zeb2 3' UTR that is included in the most abundant Zeb2 transcript in neonatal rat brain. Unique features of the distal 3' UTR region included a number of brain-specific miRNA target sites; a highly conserved miR-9 target site at 3' UTR position 4097 was selected for functional verification in transfection experiments. Parallel analysis of Zeb2 transcript, ZEB2 protein and miR-9 levels across postnatal brain cortical development revealed a significant accumulation of ZEB2 protein levels only between postnatal days P2 and P5 that was associated with an acute loss of postnatal miR-9 expression in cortex. These studies demonstrate novel features of Zeb2 gene expression in postnatal rat brain and highlight the importance of full transcript annotation for identifying the complement of potential transcript-interacting regulators.
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Affiliation(s)
- Klara Kropivšek
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, CF10 3AX, UK
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19
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Affinity analysis of differentially expressed genes in hepatocytes expressing HCV core genotype 1b or 3a. Biosystems 2013; 114:64-8. [PMID: 23743338 DOI: 10.1016/j.biosystems.2013.05.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Revised: 05/20/2013] [Accepted: 05/22/2013] [Indexed: 01/22/2023]
Abstract
Chronic hepatitis C patients display many genotype-specific clinical features of HCV infection. The core proteins encoded by different genotypes dysregulate numerous sets of distinct host genes. In this study we tested the hypothesis that HCV core proteins 1b and 3a would actually act on a limited number of independent cellular players, as well as on several functionally linked gene products. Structural and functional tests identified a core set of host genes dysregulated by HCV core genotypes 1b and 3a. The core proteins of HCV genotypes 1b and 3a target specifically limited sets of functionally related gene products, which may be responsible for the variations in the clinical spectra associated with HCV infection.
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Dassi E, Zuccotti P, Leo S, Provenzani A, Assfalg M, D’Onofrio M, Riva P, Quattrone A. Hyper conserved elements in vertebrate mRNA 3'-UTRs reveal a translational network of RNA-binding proteins controlled by HuR. Nucleic Acids Res 2013; 41:3201-16. [PMID: 23376935 PMCID: PMC3597683 DOI: 10.1093/nar/gkt017] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2012] [Revised: 12/20/2012] [Accepted: 12/26/2012] [Indexed: 02/06/2023] Open
Abstract
Little is known regarding the post-transcriptional networks that control gene expression in eukaryotes. Additionally, we still need to understand how these networks evolve, and the relative role played in them by their sequence-dependent regulatory factors, non-coding RNAs (ncRNAs) and RNA-binding proteins (RBPs). Here, we used an approach that relied on both phylogenetic sequence sharing and conservation in the whole mapped 3'-untranslated regions (3'-UTRs) of vertebrate species to gain knowledge on core post-transcriptional networks. The identified human hyper conserved elements (HCEs) were predicted to be preferred binding sites for RBPs and not for ncRNAs, namely microRNAs and long ncRNAs. We found that the HCE map identified a well-known network that post-transcriptionally regulates histone mRNAs. We were then able to discover and experimentally confirm a translational network composed of RNA Recognition Motif (RRM)-type RBP mRNAs that are positively controlled by HuR, another RRM-type RBP. HuR shows a preference for these RBP mRNAs bound in stem-loop motifs, confirming its role as a 'regulator of regulators'. Analysis of the transcriptome-wide HCE distribution revealed a profile of prevalently small clusters separated by unconserved intercluster RNA stretches, which predicts the formation of discrete small ribonucleoprotein complexes in the 3'-UTRs.
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Affiliation(s)
- Erik Dassi
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Paola Zuccotti
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Sara Leo
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Alessandro Provenzani
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Michael Assfalg
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Mariapina D’Onofrio
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Paola Riva
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
| | - Alessandro Quattrone
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy, Department of Medical Biotechnology and Translational Medicine, University of Milan, Milan, via Viotti, 3/5 20133 Milano, Italy, Laboratory of Genomic Screening, Centre for Integrative Biology, University of Trento, Trento, via delle Regole, 101 38123 Mattarello (TN) Italy and Department of Biotechnology, University of Verona, Province of Verona, Ca' Vignal 1, Strada Le Grazie 15 37134 Verona, Italy
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Dassi E, Quattrone A. Tuning the engine: an introduction to resources on post-transcriptional regulation of gene expression. RNA Biol 2012; 9:1224-32. [PMID: 22995832 DOI: 10.4161/rna.22035] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
In the last years post-transcriptional regulation (PTR) of gene expression has been increasingly recognized to be a powerful and general determinant of the quantitative changes in proteomes, and therefore a driving force for cell phenotypes. By means of networks of trans-factors on one hand, and cis-elements found primarily in untranslated regions (UTRs) of mRNA on the other hand, mRNA availability to translation and translation rates are tightly controlled and can be rapidly tuned according to the changing state of the cell. A number of dedicated resources and tools, including databases and predictive algorithms, have been proposed as bioinformatics aids for the study of this fundamental layer of gene expression regulation. Their use, however, is rendered difficult by heterogeneity and fragmentation. This review aims to locate these resources in their proper space, classifying them according to their goals, limitations and integration capabilities and, in the end, to provide the user with an initial toolbox for the bioinformatic analysis of post-transcriptional regulation of gene expression. The accompanying website, available at www.ptrguide.org, lists all resources, provides summary and features for each one and will be regularly updated in the future.
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Affiliation(s)
- Erik Dassi
- Laboratory of Translational Genomics, Centre for Integrative Biology, University of Trento, Trento, Italy
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