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1.
Nat Commun. 2018 Sep 19;9(1):3810. doi: 10.1038/s41467-018-06184-3.

Roquin targets mRNAs in a 3'-UTR-specific manner by different modes of regulation.

Author information

1
Institute for Immunology at the Biomedical Center, Ludwig-Maximilians-Universität München, 82152, Planegg-Martinsried, Germany.
2
Computational and Systems Biology, Biozentrum, University of Basel, 4056, Basel, Switzerland.
3
Research Unit Molecular Immune Regulation, Helmholtz Zentrum München, 81377, München, Germany.
4
Institute of Structural Biology, Helmholtz Zentrum München, 85764, Neuherberg, Germany.
5
Center for Integrated Protein Science Munich at Biomolecular NMR Spectroscopy, Department Chemie, Technische Universität München, 85748, Garching, Germany.
6
Young Investigators Group Bioinformatics and Transcriptomics, Department Molecular Systems Biology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany.
7
Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center of Bioinformatics, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.
8
Division of Biophysics, Institute of Experimental Physics, Faculty of Physics, University of Warsaw, 02-089, Warsaw, Poland.
9
Immunology Unit, Department of Experimental and Health Sciences, Pompeu Fabra University, 08003, Barcelona, Spain.
10
Centre of New Technologies, University of Warsaw, 02-097, Warsaw, Poland.
11
Institute of Biochemistry, Hannover Medical School, 30623, Hannover, Germany.
12
Bioinformatics Unit, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology-IZI, Leipzig, Germany.
13
Computational and Systems Biology, Biozentrum, University of Basel, 4056, Basel, Switzerland. mihaela.zavolan@unibas.ch.
14
Institute for Immunology at the Biomedical Center, Ludwig-Maximilians-Universität München, 82152, Planegg-Martinsried, Germany. vigo.heissmeyer@med.uni-muenchen.de.
15
Research Unit Molecular Immune Regulation, Helmholtz Zentrum München, 81377, München, Germany. vigo.heissmeyer@med.uni-muenchen.de.

Abstract

The RNA-binding proteins Roquin-1 and Roquin-2 redundantly control gene expression and cell-fate decisions. Here, we show that Roquin not only interacts with stem-loop structures, but also with a linear sequence element present in about half of its targets. Comprehensive analysis of a minimal response element of the Nfkbid 3'-UTR shows that six stem-loop structures cooperate to exert robust and profound post-transcriptional regulation. Only binding of multiple Roquin proteins to several stem-loops exerts full repression, which redundantly involved deadenylation and decapping, but also translational inhibition. Globally, most Roquin targets are regulated by mRNA decay, whereas a small subset, including the Nfat5 mRNA, with more binding sites in their 3'-UTRs, are also subject to translational inhibition. These findings provide insights into how the robustness and magnitude of Roquin-mediated regulation is encoded in complex cis-elements.

PMID:
30232334
PMCID:
PMC6145892
DOI:
10.1038/s41467-018-06184-3
[Indexed for MEDLINE]
Free PMC Article
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2.
Nat Commun. 2018 Jan 19;9(1):299. doi: 10.1038/s41467-017-02582-1.

Binding of NUFIP2 to Roquin promotes recognition and regulation of ICOS mRNA.

Author information

1
Institute for Immunology at the Biomedical Center, Ludwig-Maximilians-Universität München, Grosshaderner Strasse 9, 82152, Planegg-Martinsried, Germany.
2
Research Unit Molecular Immune Regulation, Helmholtz Zentrum München, Marchioninistrasse 25, 81377, München, Germany.
3
Group Intracellular Transport and RNA Biology, Institute of Structural Biology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany.
4
Center for Integrated Protein Science at the Department of Biology, Ludwig-Maximilians-Universität München, Grosshaderner Strasse 2, 82152, Planegg-Martinsried, Germany.
5
Young Investigators Group Bioinformatics and Transcriptomics, Department Molecular Systems Biology, Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, 04318, Leipzig, Germany.
6
Bioinformatics Group, Department of Computer Science; and Interdisciplinary Center of Bioinformatics, Leipzig University, Härtelstraße 16-18, 04107, Leipzig, Germany.
7
Division of Cell Biology, La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA.
8
The Functional Genomics Center, La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA.
9
Department of Health Sciences, Universita' del Piemonte Orientale, via Solaroli 17, 28100, Novara, Italy.
10
CBG Department of Clinical Genetics, Erasmus MC, Wytemaweg 80, 3015 CN, Rotterdam, Netherlands.
11
Monoclonal Antibody Core Facility and Research Group, Institute for Diabetes and Obesity, Helmholtz Zentrum München, Marchioninistrasse 25, 81377, München, Germany.
12
Bioinformatic Unit, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology- IZI, 04103, Leipzig, Germany.
13
Division of Cell Biology, La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA. soniasharma@lji.org.
14
The Functional Genomics Center, La Jolla Institute for Allergy and Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA. soniasharma@lji.org.
15
Group Intracellular Transport and RNA Biology, Institute of Structural Biology, Helmholtz Zentrum München, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany. dierk.niessing@uni-ulm.de.
16
Department of Cell Biology at the Biomedical Center, Ludwig-Maximilians-Universität München, Grosshaderner Strasse 9, 82152, Planegg-Martinsried, Germany. dierk.niessing@uni-ulm.de.
17
Institute of Pharmaceutical Biotechnology, Ulm University, James Franck Ring N27, 89081, Ulm, Germany. dierk.niessing@uni-ulm.de.
18
Institute for Immunology at the Biomedical Center, Ludwig-Maximilians-Universität München, Grosshaderner Strasse 9, 82152, Planegg-Martinsried, Germany. vigo.heissmeyer@med.uni-muenchen.de.
19
Research Unit Molecular Immune Regulation, Helmholtz Zentrum München, Marchioninistrasse 25, 81377, München, Germany. vigo.heissmeyer@med.uni-muenchen.de.

Abstract

The ubiquitously expressed RNA-binding proteins Roquin-1 and Roquin-2 are essential for appropriate immune cell function and postnatal survival of mice. Roquin proteins repress target mRNAs by recognizing secondary structures in their 3'-UTRs and by inducing mRNA decay. However, it is unknown if other cellular proteins contribute to target control. To identify cofactors of Roquin, we used RNA interference to screen ~1500 genes involved in RNA-binding or mRNA degradation, and identified NUFIP2 as a cofactor of Roquin-induced mRNA decay. NUFIP2 binds directly and with high affinity to Roquin, which stabilizes NUFIP2 in cells. Post-transcriptional repression of human ICOS by endogenous Roquin proteins requires two neighboring non-canonical stem-loops in the ICOS 3'-UTR. This unconventional cis-element as well as another tandem loop known to confer Roquin-mediated regulation of the Ox40 3'-UTR, are bound cooperatively by Roquin and NUFIP2. NUFIP2 therefore emerges as a cofactor that contributes to mRNA target recognition by Roquin.

PMID:
29352114
PMCID:
PMC5775257
DOI:
10.1038/s41467-017-02582-1
[Indexed for MEDLINE]
Free PMC Article
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Publication type, MeSH terms, Substances, Grant support

3.
Sci Rep. 2017 Aug 11;7(1):7976. doi: 10.1038/s41598-017-08348-5.

STAT3-induced long noncoding RNAs in multiple myeloma cells display different properties in cancer.

Binder S1,2,3, Hösler N4,5,6, Riedel D4,5, Zipfel I4,5, Buschmann T5,7, Kämpf C5,8,9,6, Reiche K5,7,8, Burger R10, Gramatzki M10, Hackermüller J5,8,11, Stadler PF5,9,6,12,13,14,15,16,17, Horn F4,5,7,6.

Author information

1
Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany. stefanie.binder@medizin.uni-leipzig.de.
2
Fraunhofer Institute for Cell Therapy and Immunology, Department of Diagnostics, Leipzig, Germany. stefanie.binder@medizin.uni-leipzig.de.
3
LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany. stefanie.binder@medizin.uni-leipzig.de.
4
Institute of Clinical Immunology, Faculty of Medicine, University of Leipzig, Leipzig, Germany.
5
Fraunhofer Institute for Cell Therapy and Immunology, Department of Diagnostics, Leipzig, Germany.
6
LIFE - Leipzig Research Center for Civilization Diseases, University of Leipzig, Leipzig, Germany.
7
The RIBOLUTION Consortium, Leipzig, Germany.
8
Young Investigators Group Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany.
9
Bioinformatics Group, Department of Computer Science, University of Leipzig, Leipzig, Germany.
10
Division of Stem Cell Transplantation and Immunotherapy, Department of Internal Medicine 2, Christian-Albrechts-University, Kiel, Germany.
11
Department of Computer Science, University of Leipzig, Leipzig, Germany.
12
Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.
13
German Centre for Integrative Biodiversity Research - iDiv, Halle-Jena-Leipzig, Germany.
14
Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany.
15
Department of Theoretical Chemistry, University of Vienna, Vienna, Austria.
16
Center for RNA in Technology and Health, University of Copenhagen, Copenhagen, Denmark.
17
Santa Fe Institute, Santa Fe, USA.

Abstract

Interleukin-6 (IL-6)-activated Signal Transducer and Activator of Transcription 3 (STAT3) facilitates survival in the multiple myeloma cell line INA-6 and therefore represents an oncogenic key player. However, the biological mechanisms are still not fully understood. In previous studies we identified microRNA-21 as a STAT3 target gene with strong anti-apoptotic potential, suggesting that noncoding RNAs have an impact on the pathogenesis of human multiple myeloma. Here, we describe five long noncoding RNAs (lncRNAs) induced by IL-6-activated STAT3, which we named STAiRs. While STAiRs 1, 2 and 6 remain unprocessed in the nucleus and show myeloma-specific expression, STAiRs 15 and 18 are spliced and broadly expressed. Especially STAiR2 and STAiR18 are promising candidates. STAiR2 originates from the first intron of a tumor suppressor gene. Our data support a mutually exclusive expression of either STAiR2 or the functional tumor suppressor in INA-6 cells and thus a contribution of STAiR2 to tumorigenesis. Furthermore, STAiR18 was shown to be overexpressed in every tested tumor entity, indicating its global role in tumor pathogenesis. Taken together, our study reveals a number of STAT3-induced lncRNAs suggesting that the interplay between the coding and noncoding worlds represents a fundamental principle of STAT3-driven cancer development in multiple myeloma and beyond.

4.
Toxicol Sci. 2017 Jun 1;157(2):291-304. doi: 10.1093/toxsci/kfx045.

The Transcriptome of the Zebrafish Embryo After Chemical Exposure: A Meta-Analysis.

Author information

1
Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research - UFZ, Permoserstraβe 15, Leipig, Germany.
2
Institute for Environmental Research, RWTH Aachen, Worringerweg 1, Aachen, Germany.
3
Young Investigators Group Bioinformatics and Transcriptomics, Department Molecular Systems Biology, Helmholtz Centre for Environmental Research - UFZ, Permoserstraβe 15, Leipig, Germany.
4
Bioinformatics Unit, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology, Perlickstraβe 1, Leipzig, Germany.
5
Department Bioanalytical Ecotoxicology, Helmholtz Centre for Environmental Research - UFZ, Permoserstraße 15, Leipig, Germany.

Abstract

Numerous studies have been published in the past years investigating the transcriptome of the zebrafish embryo (ZFE) upon being subjected to chemical stress. Aiming at a more mechanistic understanding of the results of such studies, knowledge about commonalities of transcript regulation in response to chemical stress is needed. Thus, our goal in this study was to identify and interpret genes and gene sets constituting a general response to chemical exposure. Therefore, we aggregated and reanalyzed published toxicogenomics data obtained with the ZFE. We found that overlap of differentially transcribed genes in response to chemical stress across independent studies is generally low and the most commonly differentially transcribed genes appear in less than 50% of all treatments across studies. However, effect size analysis revealed several genes showing a common trend of differential expression, among which genes related to calcium homeostasis emerged as key, especially in exposure settings up to 24 h post-fertilization. Additionally, we found that these and other downregulated genes are often linked to anatomical regions developing during the respective exposure period. Genes showing a trend of increased expression were, among others, linked to signaling pathways (e.g., Wnt, Fgf) as well as lysosomal structures and apoptosis. The findings of this study help to increase the understanding of chemical stress responses in the developing zebrafish embryo and provide a starting point to improve experimental designs for this model system. In future, improved time- and concentration-resolved experiments should offer better understanding of stress response patterns and access to mechanistic information.

KEYWORDS:

meta-analysis; microarray; stress response; toxicogenomics; transcriptome; zebrafish embryo

PMID:
28329862
PMCID:
PMC5443304
DOI:
10.1093/toxsci/kfx045
[Indexed for MEDLINE]
Free PMC Article
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5.
Hum Mol Genet. 2015 Aug 15;24(16):4746-63. doi: 10.1093/hmg/ddv194. Epub 2015 May 27.

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci†.

Author information

1
Institute for Medical Informatics, Statistics and Epidemiology, LIFE - Leipzig Research Center for Civilization Diseases, Cognitive Genetics, Department of Cell Therapy.
2
Department for Computer Science, Analysis Strategies Group, Department of Diagnostics, Young Investigators Group Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany and.
3
Institute of Laboratory Medicine, Ludwig-Maximilians-University, Munich, Germany.
4
Institute for Medical Informatics, Statistics and Epidemiology, LIFE - Leipzig Research Center for Civilization Diseases.
5
LIFE - Leipzig Research Center for Civilization Diseases, Department of Internal Medicine/Cardiology, Heart Center.
6
Interdisciplinary Center for Clinical Research, Faculty of Medicine and .
7
LIFE - Leipzig Research Center for Civilization Diseases, Institute of Laboratory Medicine, University of Leipzig, Leipzig, Germany.
8
Department for Computer Science, RNomics Group, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology- IZI, Leipzig, Germany, Young Investigators Group Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany and.
9
Institute for Medical Informatics, Statistics and Epidemiology, LIFE - Leipzig Research Center for Civilization Diseases, markus.scholz@imise.uni-leipzig.de.

Abstract

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

PMID:
26019233
PMCID:
PMC4512630
DOI:
10.1093/hmg/ddv194
[Indexed for MEDLINE]
Free PMC Article
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6.
RNA. 2015 May;21(5):801-12. doi: 10.1261/rna.046342.114. Epub 2015 Mar 23.

Comparison of splice sites reveals that long noncoding RNAs are evolutionarily well conserved.

Author information

1
Bioinformatics Group, Department of Computer Science, University of Leipzig, D-04107 Leipzig, Germany Interdisciplinary Center for Bioinformatics, University of Leipzig, D-04107 Leipzig, Germany.
2
Bioinformatics Group, Department of Computer Science, University of Freiburg, D-79110 Freiburg, Germany MML, Munich Leukemia Laboratory GmbH, D-81377 München, Germany.
3
Interdisciplinary Center for Bioinformatics, University of Leipzig, D-04107 Leipzig, Germany ecSeq Bioinformatics, D-04275 Leipzig, Germany.
4
Young Investigators Group Bioinformatics and Transcriptomics, Department of Proteomics, Helmholtz Centre for Environmental Research-UFZ, D-04318 Leipzig, Germany Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology-IZI, D-04103 Leipzig, Germany.
5
Bioinformatics Group, Department of Computer Science, University of Leipzig, D-04107 Leipzig, Germany Interdisciplinary Center for Bioinformatics, University of Leipzig, D-04107 Leipzig, Germany Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology-IZI, D-04103 Leipzig, Germany Max Planck Institute for Mathematics in the Sciences, D-04103 Leipzig, Germany Department of Theoretical Chemistry, University of Vienna, A-1090 Wien, Austria Center for non-coding RNA in Technology and Health, University of Copenhagen, DK-1870 Frederiksberg C, Denmark Santa Fe Institute, Santa Fe, New Mexico 87501, USA.

Abstract

Large-scale RNA sequencing has revealed a large number of long mRNA-like transcripts (lncRNAs) that do not code for proteins. The evolutionary history of these lncRNAs has been notoriously hard to study systematically due to their low level of sequence conservation that precludes comprehensive homology-based surveys and makes them nearly impossible to align. An increasing number of special cases, however, has been shown to be at least as old as the vertebrate lineage. Here we use the conservation of splice sites to trace the evolution of lncRNAs. We show that >85% of the human GENCODE lncRNAs were already present at the divergence of placental mammals and many hundreds of these RNAs date back even further. Nevertheless, we observe a fast turnover of intron/exon structures. We conclude that lncRNA genes are evolutionary ancient components of vertebrate genomes that show an unexpected and unprecedented evolutionary plasticity. We offer a public web service (http://splicemap.bioinf.uni-leipzig.de) that allows to retrieve sets of orthologous splice sites and to produce overview maps of evolutionarily conserved splice sites for visualization and further analysis. An electronic supplement containing the ncRNA data sets used in this study is available at http://www.bioinf.uni-leipzig.de/publications/supplements/12-001.

KEYWORDS:

conservation; evolution; evolutionary plasticity; lncRNA; long noncoding RNAs; multiple sequence alignments; splice sites

PMID:
25802408
PMCID:
PMC4408788
DOI:
10.1261/rna.046342.114
[Indexed for MEDLINE]
Free PMC Article
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7.
PLoS One. 2014 Sep 29;9(9):e106076. doi: 10.1371/journal.pone.0106076. eCollection 2014.

Long non-coding RNAs differentially expressed between normal versus primary breast tumor tissues disclose converse changes to breast cancer-related protein-coding genes.

Author information

1
Young Investigators Group Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany, and Department for Computer Science, University of Leipzig, Leipzig, Germany; RNomics Group, Department Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany.
2
RNomics Group, Department Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany; LIFE Interdisciplinary Research Cluster, University of Leipzig, Leipzig, Germany.
3
Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway; K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
4
K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
5
K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Oncology, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
6
Department of Breast and Endocrine Surgery, Oslo University Hospital, Ullevål, Norway.
7
Clinical Molecular Biology (EpiGen), Akershus University Hospital, Lørenskog, Norway; K.G. Jebsen Center for Breast Cancer Research, Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
8
RNomics Group, Department Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany; Institute for Clinical Immunology, University of Leipzig, Leipzig, Germany.
9
Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Pediatric Research, Women and Children's Division, Oslo University Hospital Rikshospitalet, Oslo, Norway.

Abstract

Breast cancer, the second leading cause of cancer death in women, is a highly heterogeneous disease, characterized by distinct genomic and transcriptomic profiles. Transcriptome analyses prevalently assessed protein-coding genes; however, the majority of the mammalian genome is expressed in numerous non-coding transcripts. Emerging evidence supports that many of these non-coding RNAs are specifically expressed during development, tumorigenesis, and metastasis. The focus of this study was to investigate the expression features and molecular characteristics of long non-coding RNAs (lncRNAs) in breast cancer. We investigated 26 breast tumor and 5 normal tissue samples utilizing a custom expression microarray enclosing probes for mRNAs as well as novel and previously identified lncRNAs. We identified more than 19,000 unique regions significantly differentially expressed between normal versus breast tumor tissue, half of these regions were non-coding without any evidence for functional open reading frames or sequence similarity to known proteins. The identified non-coding regions were primarily located in introns (53%) or in the intergenic space (33%), frequently orientated in antisense-direction of protein-coding genes (14%), and commonly distributed at promoter-, transcription factor binding-, or enhancer-sites. Analyzing the most diverse mRNA breast cancer subtypes Basal-like versus Luminal A and B resulted in 3,025 significantly differentially expressed unique loci, including 682 (23%) for non-coding transcripts. A notable number of differentially expressed protein-coding genes displayed non-synonymous expression changes compared to their nearest differentially expressed lncRNA, including an antisense lncRNA strongly anticorrelated to the mRNA coding for histone deacetylase 3 (HDAC3), which was investigated in more detail. Previously identified chromatin-associated lncRNAs (CARs) were predominantly downregulated in breast tumor samples, including CARs located in the protein-coding genes for CALD1, FTX, and HNRNPH1. In conclusion, a number of differentially expressed lncRNAs have been identified with relation to cancer-related protein-coding genes.

PMID:
25264628
PMCID:
PMC4180073
DOI:
10.1371/journal.pone.0106076
[Indexed for MEDLINE]
Free PMC Article
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8.
J Biotechnol. 2014 Nov 10;189:154-6. doi: 10.1016/j.jbiotec.2014.09.012. Epub 2014 Sep 28.

CEM-designer: design of custom expression microarrays in the post-ENCODE Era.

Author information

1
Bioinformatics Group, Department for Computer Science, University of Leipzig, Leipzig, Germany; RNomics Group, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany.
2
Bioinformatics Group, Department for Computer Science, University of Leipzig, Leipzig, Germany.
3
Young Investigators Group, Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; Bioinformatics Group, Department for Computer Science, University of Leipzig, Leipzig, Germany; RNomics Group, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany. Electronic address: joerg.hackermueller@ufz.de.
4
Young Investigators Group, Bioinformatics and Transcriptomics, Department Proteomics, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany; Bioinformatics Group, Department for Computer Science, University of Leipzig, Leipzig, Germany; RNomics Group, Department of Diagnostics, Fraunhofer Institute for Cell Therapy and Immunology - IZI, Leipzig, Germany. Electronic address: kristin.reiche@ufz.de.

Abstract

Microarrays are widely used in gene expression studies, and custom expression microarrays are popular to monitor expression changes of a customer-defined set of genes. However, the complexity of transcriptomes uncovered recently make custom expression microarray design a non-trivial task. Pervasive transcription and alternative processing of transcripts generate a wealth of interweaved transcripts that requires well-considered probe design strategies and is largely neglected in existing approaches. We developed the web server CEM-Designer that facilitates microarray platform independent design of custom expression microarrays for complex transcriptomes. CEM-Designer covers (i) the collection and generation of a set of unique target sequences from different sources and (ii) the selection of a set of sensitive and specific probes that optimally represents the target sequences. Probe design itself is left to third party software to ensure that probes meet provider-specific constraints. CEM-Designer is available at http://designpipeline.bioinf.uni-leipzig.de.

KEYWORDS:

Custom expression microarray; Microarray design; Non-coding RNA; Pervasive transcription; Transcriptomics

PMID:
25262644
DOI:
10.1016/j.jbiotec.2014.09.012
[Indexed for MEDLINE]
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9.
Genome Biol. 2014 Mar 4;15(3):R48. doi: 10.1186/gb-2014-15-3-r48.

Cell cycle, oncogenic and tumor suppressor pathways regulate numerous long and macro non-protein-coding RNAs.

Abstract

BACKGROUND:

The genome is pervasively transcribed but most transcripts do not code for proteins, constituting non-protein-coding RNAs. Despite increasing numbers of functional reports of individual long non-coding RNAs (lncRNAs), assessing the extent of functionality among the non-coding transcriptional output of mammalian cells remains intricate. In the protein-coding world, transcripts differentially expressed in the context of processes essential for the survival of multicellular organisms have been instrumental in the discovery of functionally relevant proteins and their deregulation is frequently associated with diseases. We therefore systematically identified lncRNAs expressed differentially in response to oncologically relevant processes and cell-cycle, p53 and STAT3 pathways, using tiling arrays.

RESULTS:

We found that up to 80% of the pathway-triggered transcriptional responses are non-coding. Among these we identified very large macroRNAs with pathway-specific expression patterns and demonstrated that these are likely continuous transcripts. MacroRNAs contain elements conserved in mammals and sauropsids, which in part exhibit conserved RNA secondary structure. Comparing evolutionary rates of a macroRNA to adjacent protein-coding genes suggests a local action of the transcript. Finally, in different grades of astrocytoma, a tumor disease unrelated to the initially used cell lines, macroRNAs are differentially expressed.

CONCLUSIONS:

It has been shown previously that the majority of expressed non-ribosomal transcripts are non-coding. We now conclude that differential expression triggered by signaling pathways gives rise to a similar abundance of non-coding content. It is thus unlikely that the prevalence of non-coding transcripts in the cell is a trivial consequence of leaky or random transcription events.

PMID:
24594072
PMCID:
PMC4054595
DOI:
10.1186/gb-2014-15-3-r48
[Indexed for MEDLINE]
Free PMC Article
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10.
Bioinformatics. 2012 Jun 1;28(11):1471-9. doi: 10.1093/bioinformatics/bts142. Epub 2012 Apr 6.

Detection of differentially expressed segments in tiling array data.

Author information

1
Bioinformatics Group, Department of Computer Science and Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany.

Abstract

MOTIVATION:

Tiling arrays have been a mainstay of unbiased genome-wide transcriptomics over the last decade. Currently available approaches to identify expressed or differentially expressed segments in tiling array data are limited in the recovery of the underlying gene structures and require several parameters that are intensity-related or partly dataset-specific.

RESULTS:

We have developed TileShuffle, a statistical approach that identifies transcribed and differentially expressed segments as significant differences from the background distribution while considering sequence-specific affinity biases and cross-hybridization. It avoids dataset-specific parameters in order to provide better comparability of different tiling array datasets, based on different technologies or array designs. TileShuffle detects highly and differentially expressed segments in biological data with significantly lower false discovery rates under equal sensitivities than commonly used methods. Also, it is clearly superior in the recovery of exon-intron structures. It further provides window z-scores as a normalized and robust measure for visual inspection.

AVAILABILITY:

The R package including documentation and examples is freely available at http://www.bioinf.uni-leipzig.de/Software/TileShuffle/

PMID:
22492638
DOI:
10.1093/bioinformatics/bts142
[Indexed for MEDLINE]
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11.
Methods Mol Biol. 2011;719:299-330. doi: 10.1007/978-1-61779-027-0_14.

Bioinformatics for RNomics.

Author information

1
Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany.

Abstract

Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.

PMID:
21370090
DOI:
10.1007/978-1-61779-027-0_14
[Indexed for MEDLINE]
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12.
Virology. 2011 Mar 30;412(1):75-82. doi: 10.1016/j.virol.2010.12.059. Epub 2011 Jan 22.

Deletion analysis of the 3' long terminal repeat sequence of plant retrotransposon Tto1 identifies 125 base pairs redundancy as sufficient for first strand transfer.

Author information

1
Department of Biochemistry and Cell Biology, Max F. Perutz Laboratories, University of Vienna, Dr. Bohr-Gasse 9, Vienna, Austria.

Abstract

Retroviruses and many retrotransposons are flanked by sequence repeats called long terminal repeats (LTRs). These sequences contain a promoter region, which is active in the 5' LTR, and transcription termination signals, which are active in the LTR copy present at the 3' end. A section in the middle of the LTR, called Redundancy region, occurs at both ends of the mRNA. Here we show that in the copia type retrotransposon Tto1, the promoter and terminator functions of the LTR can be supplied by heterologous sequences, thereby converting the LTR into a significantly shorter sub-terminal repeat. An engineered Tto1 element with 125 instead of the usual 574 base pairs repeated in the 5' and 3' region can still promote strand transfer during cDNA synthesis, defining a minimal Redundancy region for this element. Based on this finding, we propose a model for first strand transfer of Tto1.

PMID:
21262516
PMCID:
PMC3061985
DOI:
10.1016/j.virol.2010.12.059
[Indexed for MEDLINE]
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13.
Nature. 2010 Mar 11;464(7286):250-5. doi: 10.1038/nature08756. Epub 2010 Feb 17.

The primary transcriptome of the major human pathogen Helicobacter pylori.

Author information

1
Max Planck Institute for Infection Biology, RNA Biology Group, D-10117 Berlin, Germany.

Abstract

Genome sequencing of Helicobacter pylori has revealed the potential proteins and genetic diversity of this prevalent human pathogen, yet little is known about its transcriptional organization and noncoding RNA output. Massively parallel cDNA sequencing (RNA-seq) has been revolutionizing global transcriptomic analysis. Here, using a novel differential approach (dRNA-seq) selective for the 5' end of primary transcripts, we present a genome-wide map of H. pylori transcriptional start sites and operons. We discovered hundreds of transcriptional start sites within operons, and opposite to annotated genes, indicating that complexity of gene expression from the small H. pylori genome is increased by uncoupling of polycistrons and by genome-wide antisense transcription. We also discovered an unexpected number of approximately 60 small RNAs including the epsilon-subdivision counterpart of the regulatory 6S RNA and associated RNA products, and potential regulators of cis- and trans-encoded target messenger RNAs. Our approach establishes a paradigm for mapping and annotating the primary transcriptomes of many living species.

PMID:
20164839
DOI:
10.1038/nature08756
[Indexed for MEDLINE]
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14.
J Bioinform Comput Biol. 2008 Dec;6(6):1157-75.

Duplicated RNA genes in teleost fish genomes.

Author information

1
Bioinformatics Group, Department of Computer Science, Interdisciplinary Center for Bioinformatics, University of Leipzig, Leipzig, Germany. dominic@bioinf.uni-leipzig.de

Abstract

Teleost fishes share a duplication of their entire genomes. We report here on a computational survey of structured non-coding RNAs (ncRNAs) in teleost genomes, focusing on the fate of fish-specific duplicates. As in other metazoan groups, we find evidence of a large number (11,543) of structured RNAs, most of which (~86%) are clade-specific or evolve so fast that their tetrapod homologs cannot be detected. In surprising contrast to protein-coding genes, the fish-specific genome duplication did not lead to a large number of paralogous ncRNAs: only 188 candidates, mostly microRNAs, appear in a larger copy number in teleosts than in tetrapods, suggesting that large-scale gene duplications do not play a major role in the expansion of the vertebrate ncRNA inventory.

PMID:
19090022
[Indexed for MEDLINE]
15.
Bioinformatics. 2009 Feb 1;25(3):291-4. doi: 10.1093/bioinformatics/btn628. Epub 2008 Dec 4.

Structural profiles of human miRNA families from pairwise clustering.

Author information

1
Division of Genetics and Bioinformatics, IBHV, University of Copenhagen, Frederiksberg C, Denmark.

Abstract

MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures.

AVAILABILITY:

http://genome.ku.dk/resources/mirclust

PMID:
19059941
DOI:
10.1093/bioinformatics/btn628
[Indexed for MEDLINE]
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16.
Genomics. 2008 Jul;92(1):65-74. doi: 10.1016/j.ygeno.2008.04.003. Epub 2008 Jun 3.

NcDNAlign: plausible multiple alignments of non-protein-coding genomic sequences.

Author information

1
Bioinformatics Group, Department of Computer Science, University of Leipzig, Härtelstrasse 16-18, D-04107 Leipzig, Germany.

Abstract

Genome-wide multiple sequence alignments (MSAs) are a necessary prerequisite for an increasingly diverse collection of comparative genomic approaches. Here we present a versatile method that generates high-quality MSAs for non-protein-coding sequences. The NcDNAlign pipeline combines pairwise BLAST alignments to create initial MSAs, which are then locally improved and trimmed. The program is optimized for speed and hence is particulary well-suited to pilot studies. We demonstrate the practical use of NcDNAlign in three case studies: the search for ncRNAs in gammaproteobacteria and the analysis of conserved noncoding DNA in nematodes and teleost fish, in the latter case focusing on the fate of duplicated ultra-conserved regions. Compared to the currently widely used genome-wide alignment program TBA, our program results in a 20- to 30-fold reduction of CPU time necessary to generate gammaproteobacterial alignments. A showcase application of bacterial ncRNA prediction based on alignments of both algorithms results in similar sensitivity, false discovery rates, and up to 100 putatively novel ncRNA structures. Similar findings hold for our application of NcDNAlign to the identification of ultra-conserved regions in nematodes and teleosts. Both approaches yield conserved sequences of unknown function, result in novel evolutionary insights into conservation patterns among these genomes, and manifest the benefits of an efficient and reliable genome-wide alignment package. The software is available under the GNU Public License at http://www.bioinf.uni-leipzig.de/Software/NcDNAlign/.

PMID:
18511233
DOI:
10.1016/j.ygeno.2008.04.003
[Indexed for MEDLINE]
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17.
BMC Genomics. 2007 Nov 8;8:406.

Computational RNomics of drosophilids.

Author information

1
Bioinformatics Group, Department of Computer Science, University of Leipzig, Härtelstrasse 16-18, Leipzig, Germany. dominic@bioinf.uni-leipzig.de

Abstract

BACKGROUND:

Recent experimental and computational studies have provided overwhelming evidence for a plethora of diverse transcripts that are unrelated to protein-coding genes. One subclass consists of those RNAs that require distinctive secondary structure motifs to exert their biological function and hence exhibit distinctive patterns of sequence conservation characteristic for positive selection on RNA secondary structure. The deep-sequencing of 12 drosophilid species coordinated by the NHGRI provides an ideal data set of comparative computational approaches to determine those genomic loci that code for evolutionarily conserved RNA motifs. This class of loci includes the majority of the known small ncRNAs as well as structured RNA motifs in mRNAs. We report here on a genome-wide survey using RNAz.

RESULTS:

We obtain 16 000 high quality predictions among which we recover the majority of the known ncRNAs. Taking a pessimistically estimated false discovery rate of 40% into account, this implies that at least some ten thousand loci in the Drosophila genome show the hallmarks of stabilizing selection action of RNA structure, and hence are most likely functional at the RNA level. A subset of RNAz predictions overlapping with TRF1 and BRF binding sites [Isogai et al., EMBO J. 26: 79-89 (2007)], which are plausible candidates of Pol III transcripts, have been studied in more detail. Among these sequences we identify several "clusters" of ncRNA candidates with striking structural similarities.

CONCLUSION:

The statistical evaluation of the RNAz predictions in comparison with a similar analysis of vertebrate genomes [Washietl et al., Nat. Biotech. 23: 1383-1390 (2005)] shows that qualitatively similar fractions of structured RNAs are found in introns, UTRs, and intergenic regions. The intergenic RNA structures, however, are concentrated much more closely around known protein-coding loci, suggesting that flies have significantly smaller complement of independent structured ncRNAs compared to mammals.

PMID:
17996037
PMCID:
PMC2216035
DOI:
10.1186/1471-2164-8-406
[Indexed for MEDLINE]
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18.
Genome Res. 2007 Jun;17(6):852-64.

Structured RNAs in the ENCODE selected regions of the human genome.

Author information

1
Institute for Theoretical Chemistry, University of Vienna, A-1090 Wien, Austria. wash@tbi.univie.ac.at

Abstract

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

PMID:
17568003
PMCID:
PMC1891344
DOI:
10.1101/gr.5650707
[Indexed for MEDLINE]
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19.
Algorithms Mol Biol. 2007 May 31;2:6.

RNAstrand: reading direction of structured RNAs in multiple sequence alignments.

Author information

1
Bioinformatics Group, Dept. of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Germany. kristin@bioinf.uni-leipzig.de

Abstract

MOTIVATION:

Genome-wide screens for structured ncRNA genes in mammals, urochordates, and nematodes have predicted thousands of putative ncRNA genes and other structured RNA motifs. A prerequisite for their functional annotation is to determine the reading direction with high precision.

RESULTS:

While folding energies of an RNA and its reverse complement are similar, the differences are sufficient at least in conjunction with substitution patterns to discriminate between structured RNAs and their complements. We present here a support vector machine that reliably classifies the reading direction of a structured RNA from a multiple sequence alignment and provides a considerable improvement in classification accuracy over previous approaches.

SOFTWARE:

RNAstrand is freely available as a stand-alone tool from http://www.bioinf.uni-leipzig.de/Software/RNAstrand and is also included in the latest release of RNAz, a part of the Vienna RNA Package.

20.
PLoS Comput Biol. 2007 Apr 13;3(4):e65. Epub 2007 Feb 22.

Inferring noncoding RNA families and classes by means of genome-scale structure-based clustering.

Author information

1
Bioinformatics Group, Institute of Computer Science, University of Freiburg, Freiburg, Germany.

Abstract

The RFAM database defines families of ncRNAs by means of sequence similarities that are sufficient to establish homology. In some cases, such as microRNAs and box H/ACA snoRNAs, functional commonalities define classes of RNAs that are characterized by structural similarities, and typically consist of multiple RNA families. Recent advances in high-throughput transcriptomics and comparative genomics have produced very large sets of putative noncoding RNAs and regulatory RNA signals. For many of them, evidence for stabilizing selection acting on their secondary structures has been derived, and at least approximate models of their structures have been computed. The overwhelming majority of these hypothetical RNAs cannot be assigned to established families or classes. We present here a structure-based clustering approach that is capable of extracting putative RNA classes from genome-wide surveys for structured RNAs. The LocARNA (local alignment of RNA) tool implements a novel variant of the Sankoff algorithm that is sufficiently fast to deal with several thousand candidate sequences. The method is also robust against false positive predictions, i.e., a contamination of the input data with unstructured or nonconserved sequences. We have successfully tested the LocARNA-based clustering approach on the sequences of the RFAM-seed alignments. Furthermore, we have applied it to a previously published set of 3,332 predicted structured elements in the Ciona intestinalis genome (Missal K, Rose D, Stadler PF (2005) Noncoding RNAs in Ciona intestinalis. Bioinformatics 21 (Supplement 2): i77-i78). In addition to recovering, e.g., tRNAs as a structure-based class, the method identifies several RNA families, including microRNA and snoRNA candidates, and suggests several novel classes of ncRNAs for which to date no representative has been experimentally characterized.

PMID:
17432929
PMCID:
PMC1851984
DOI:
10.1371/journal.pcbi.0030065
[Indexed for MEDLINE]
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