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Soreq L, Gilboa-Geffen A, Berrih-Aknin S, Lacoste P, Darvasi A, Soreq E, Bergman H, Soreq H. Identifying alternative hyper-splicing signatures in MG-thymoma by exon arrays. PLoS One 2008; 3:e2392. [PMID: 18545673 PMCID: PMC2409220 DOI: 10.1371/journal.pone.0002392] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2008] [Accepted: 03/27/2008] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND The vast majority of human genes (>70%) are alternatively spliced. Although alternative pre-mRNA processing is modified in multiple tumors, alternative hyper-splicing signatures specific to particular tumor types are still lacking. Here, we report the use of Affymetrix Human Exon Arrays to spot hyper-splicing events characteristic of myasthenia gravis (MG)-thymoma, thymic tumors which develop in patients with MG and discriminate them from colon cancer changes. METHODOLOGY/PRINCIPAL FINDINGS We combined GO term to parent threshold-based and threshold-independent ad-hoc functional statistics with in-depth analysis of key modified transcripts to highlight various exon-specific changes. These denote alternative splicing in MG-thymoma tumors compared to healthy human thymus and to in-house and Affymetrix datasets from colon cancer and healthy tissues. By using both global and specific, term-to-parent Gene Ontology (GO) statistical comparisons, our functional integrative ad-hoc method allowed the detection of disease-relevant splicing events. CONCLUSIONS/SIGNIFICANCE Hyper-spliced transcripts spanned several categories, including the tumorogenic ERBB4 tyrosine kinase receptor and the connective tissue growth factor CTGF, as well as the immune function-related histocompatibility gene HLA-DRB1 and interleukin (IL)19, two muscle-specific collagens and one myosin heavy chain gene; intriguingly, a putative new exon was discovered in the MG-involved acetylcholinesterase ACHE gene. Corresponding changes in spliceosome composition were indicated by co-decreases in the splicing factors ASF/SF(2) and SC35. Parallel tumor-associated changes occurred in colon cancer as well, but the majority of the apparent hyper-splicing events were particular to MG-thymoma and could be validated by Fluorescent In-Situ Hybridization (FISH), Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and mass spectrometry (MS) followed by peptide sequencing. Our findings demonstrate a particular alternative hyper-splicing signature for transcripts over-expressed in MG-thymoma, supporting the hypothesis that alternative hyper-splicing contributes to shaping the biological functions of these and other specialized tumors and opening new venues for the development of diagnosis and treatment approaches.
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Affiliation(s)
- Lilach Soreq
- Department of Physiology, The Hebrew University, Hadassah Medical School, Jerusalem, Israel.
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202
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203
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Su WL, Modrek B, GuhaThakurta D, Edwards S, Shah JK, Kulkarni AV, Russell A, Schadt EE, Johnson JM, Castle JC. Exon and junction microarrays detect widespread mouse strain- and sex-bias expression differences. BMC Genomics 2008; 9:273. [PMID: 18533039 PMCID: PMC2432077 DOI: 10.1186/1471-2164-9-273] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2007] [Accepted: 06/04/2008] [Indexed: 12/22/2022] Open
Abstract
Background Studies have shown that genetic and sex differences strongly influence gene expression in mice. Given the diversity and complexity of transcripts produced by alternative splicing, we sought to use microarrays to establish the extent of variation found in mouse strains and genders. Here, we surveyed the effect of strain and sex on liver gene and exon expression using male and female mice from three different inbred strains. Results 71 liver RNA samples from three mouse strains – DBA/2J, C57BL/6J and C3H/HeJ – were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons ("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. Conclusion Exon expression profiling identifies significantly more variation than both 3' gene expression profiling and whole-transcript gene expression profiling. A large percentage of genes that are not differentially expressed at the gene level demonstrate exon expression variation suggesting an influence of strain and sex on alternative splicing and a need to profile expression changes at sub-gene resolution.
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Affiliation(s)
- Wan-Lin Su
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA.
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204
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Thorsen K, Sørensen KD, Brems-Eskildsen AS, Modin C, Gaustadnes M, Hein AMK, Kruhøffer M, Laurberg S, Borre M, Wang K, Brunak S, Krainer AR, Tørring N, Dyrskjøt L, Andersen CL, Orntoft TF. Alternative splicing in colon, bladder, and prostate cancer identified by exon array analysis. Mol Cell Proteomics 2008; 7:1214-24. [PMID: 18353764 DOI: 10.1074/mcp.m700590-mcp200] [Citation(s) in RCA: 180] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Alternative splicing enhances proteome diversity and modulates cancer-associated proteins. To identify tissue- and tumor-specific alternative splicing, we used the GeneChip Human Exon 1.0 ST Array to measure whole-genome exon expression in 102 normal and cancer tissue samples of different stages from colon, urinary bladder, and prostate. We identified 2069 candidate alternative splicing events between normal tissue samples from colon, bladder, and prostate and selected 15 splicing events for RT-PCR validation, 10 of which were successfully validated by RT-PCR and sequencing. Furthermore 23, 19, and 18 candidate tumor-specific splicing alterations in colon, bladder, and prostate, respectively, were selected for RT-PCR validation on an independent set of 81 normal and tumor tissue samples. In total, seven genes with tumor-specific splice variants were identified (ACTN1, CALD1, COL6A3, LRRFIP2, PIK4CB, TPM1, and VCL). The validated tumor-specific splicing alterations were highly consistent, enabling clear separation of normal and cancer samples and in some cases even of different tumor stages. A subset of the tumor-specific splicing alterations (ACTN1, CALD1, and VCL) was found in all three organs and may represent general cancer-related splicing events. In silico protein predictions suggest that the identified cancer-specific splice variants encode proteins with potentially altered functions, indicating that they may be involved in pathogenesis and hence represent novel therapeutic targets. In conclusion, we identified and validated alternative splicing between normal tissue samples from colon, bladder, and prostate in addition to cancer-specific splicing events in colon, bladder, and prostate cancer that may have diagnostic and prognostic implications.
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Affiliation(s)
- Kasper Thorsen
- Molecular Diagnostic Laboratory, Department of Clinical Biochemistry, Aarhus University Hospital, Skejby, DK-8200 Aarhus N, Denmark
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205
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Differential RNA expression between schizophrenic patients and controls of the dystrobrevin binding protein 1 and neuregulin 1 genes in immortalized lymphocytes. Schizophr Res 2008; 100:281-90. [PMID: 18234478 DOI: 10.1016/j.schres.2007.12.471] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2007] [Revised: 12/10/2007] [Accepted: 12/13/2007] [Indexed: 01/01/2023]
Abstract
The dystrobrevin binding protein 1 (DTNBP1) and neuregulin 1 (NRG1) genes have been related to schizophrenia (SZ) and bipolar disorder (BP) by several whole-genome linkage and associations studies. Few expression studies in post-mortem brains have also reported a lower or a higher expression of DTNBP1 and NRG1, respectively, in SZ. Since the difficulty to access post-mortem brains, we evaluated RNA expression of DTNBP1 and NRG1 in immortalized lymphocytes of SZ patients and unrelated-family controls. An antipsychotic stimulation was also used to challenge the genetic background of the subjects and enhance differential expression. Immortalized lymphocytes of twelve SZ and twelve controls were grown individually in the presence or not of the antipsychotic olanzapine (Zyprexa; EliLilly). RNA was extracted and pooled in four groups of three SZ and four groups of three controls, and used to probe Agilent 18K microchips. Mean gene expression values were contrasted between SZ and control groups using a T-test. For DTNBP1, RNA expression was lower in SZ than in controls before (-28%; p=0.02) and after (-30%; p=0.01) olanzapine stimulation. Similarly, NRG1 GGF2 isoform showed a lower expression in SZ before (-29%; p=0.04) and after (-33%; p=0.02) olanzapine stimulation. In contrast, NRG1 GGF isoform showed no significant difference between SZ and controls (-7%; p=0.61, +3%; p=0.86, respectively), but was slightly repressed by olanzapine in controls (-8%; p=0.008) but not in SZ (+1%; p=0.91). These results are in agreement with those observed in post-mortem brain when the isoforms involved are considered.
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206
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McKee AE, Neretti N, Carvalho LE, Meyer CA, Fox EA, Brodsky AS, Silver PA. Exon expression profiling reveals stimulus-mediated exon use in neural cells. Genome Biol 2008; 8:R159. [PMID: 17683528 PMCID: PMC2374990 DOI: 10.1186/gb-2007-8-8-r159] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2007] [Revised: 06/12/2007] [Accepted: 08/02/2007] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Neuronal cells respond to changes in intracellular calcium ([Ca2+]i) by affecting both the abundance and architecture of specific mRNAs. Although calcium-induced transcription and transcript variation have both been recognized as important sources of gene regulation, the interplay between these two phenomena has not been evaluated on a genome-wide scale. RESULTS Here, we show that exon-centric microarrays can be used to resolve the [Ca2+]i-modulated gene expression response into transcript-level and exon-level regulation. Global assessments of affected transcripts reveal modulation within distinct functional gene categories. We find that transcripts containing calcium-modulated exons exhibit enrichment for calcium ion binding, calmodulin binding, plasma membrane associated, and metabolic proteins. Additionally, we uncover instances of regulated exon use in potassium channels, neuroendocrine secretory proteins and metabolic enzymes, and demonstrate that regulated changes in exon expression give rise to distinct transcript variants. CONCLUSION Our findings connect extracellular stimuli to specific exon behavior, and suggest that changes in transcript and exon abundance are reflective of a coordinated gene expression response to elevated [Ca2+]i. The technology we describe here lends itself readily to the resolution of stimulus-induced gene expression at both the transcript and exon levels.
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Affiliation(s)
- Adrienne E McKee
- Department of Systems Biology, 200 Longwood Avenue, Harvard Medical School, Boston, Massachusetts 02115, USA.
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207
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Abstract
Alternative mRNA splicing is a rich source of transcript diversity in eukaryotic cells with broad roles in development and disease. Systems-wide experimental methods have started to define how global splicing regulation shapes complex biological properties and pathways. Here, we review these approaches, describe recent insights they have yielded, and discuss avenues of future investigation.
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Affiliation(s)
- Michael J Moore
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
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208
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Hung LH, Heiner M, Hui J, Schreiner S, Benes V, Bindereif A. Diverse roles of hnRNP L in mammalian mRNA processing: a combined microarray and RNAi analysis. RNA (NEW YORK, N.Y.) 2008; 14:284-96. [PMID: 18073345 PMCID: PMC2212255 DOI: 10.1261/rna.725208] [Citation(s) in RCA: 118] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Alternative mRNA splicing patterns are determined by the combinatorial control of regulator proteins and their target RNA sequences. We have recently characterized human hnRNP L as a global regulator of alternative splicing, binding to diverse C/A-rich elements. To systematically identify hnRNP L target genes on a genome-wide level, we have combined splice-sensitive microarray analysis and an RNAi-knockdown approach. As a result, we describe 11 target genes of hnRNP L that were validated by RT-PCR and that represent several new modes of hnRNP L-dependent splicing regulation, involving both activator and repressor functions: first, intron retention; second, inclusion or skipping of cassette-type exons; third, suppression of multiple exons; and fourth, alternative poly(A) site selection. In sum, this approach revealed a surprising diversity of splicing-regulatory processes as well as poly(A) site selection in which hnRNP L is involved.
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Affiliation(s)
- Lee-Hsueh Hung
- Institute of Biochemistry, Justus-Liebig-University of Giessen, D-35392 Giessen, Germany
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209
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Kwan T, Benovoy D, Dias C, Gurd S, Provencher C, Beaulieu P, Hudson TJ, Sladek R, Majewski J. Genome-wide analysis of transcript isoform variation in humans. Nat Genet 2008; 40:225-31. [PMID: 18193047 DOI: 10.1038/ng.2007.57] [Citation(s) in RCA: 264] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2007] [Accepted: 10/31/2007] [Indexed: 12/22/2022]
Abstract
We have performed a genome-wide analysis of common genetic variation controlling differential expression of transcript isoforms in the CEU HapMap population using a comprehensive exon tiling microarray covering 17,897 genes. We detected 324 genes with significant associations between flanking SNPs and transcript levels. Of these, 39% reflected changes in whole gene expression and 55% reflected transcript isoform changes such as splicing variants (exon skipping, alternative splice site use, intron retention), differential 5' UTR (initiation of transcription) use, and differential 3' UTR (alternative polyadenylation) use. These results demonstrate that the regulatory effects of genetic variation in a normal human population are far more complex than previously observed. This extra layer of molecular diversity may account for natural phenotypic variation and disease susceptibility.
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Affiliation(s)
- Tony Kwan
- Department of Human Genetics, McGill University, 740 Dr. Penfield, Room 7210, Montréal, Québec H3A 1A4, Canada
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210
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Larsson O, Nadon R. Gene Expression – Time to Change Point of View? Biotechnol Genet Eng Rev 2008; 25:77-92. [DOI: 10.5661/bger-25-77] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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211
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Kwan T, Benovoy D, Dias C, Gurd S, Serre D, Zuzan H, Clark TA, Schweitzer A, Staples MK, Wang H, Blume JE, Hudson TJ, Sladek R, Majewski J. Heritability of alternative splicing in the human genome. Genome Res 2007; 17:1210-8. [PMID: 17671095 PMCID: PMC1933514 DOI: 10.1101/gr.6281007] [Citation(s) in RCA: 92] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Alternative pre-mRNA splicing increases proteomic diversity and provides a potential mechanism underlying both phenotypic diversity and susceptibility to genetic disorders in human populations. To investigate the variation in splicing among humans on a genome-wide scale, we use a comprehensive exon-targeted microarray to examine alternative splicing in lymphoblastoid cell lines (LCLs) derived from the CEPH HapMap population. We show the identification of transcripts containing sequence verified exon skipping, intron retention, and cryptic splice site usage that are specific between individuals. A number of novel alternative splicing events with no previous annotations in either the RefSeq and EST databases were identified, indicating that we are able to discover de novo splicing events. Using family-based linkage analysis, we demonstrate Mendelian inheritance and segregation of specific splice isoforms with regulatory haplotypes for three genes: OAS1, CAST, and CRTAP. Allelic association was further used to identify individual SNPs or regulatory haplotype blocks linked to the alternative splicing event, taking advantage of the high-resolution genotype information from the CEPH HapMap population. In one candidate, we identified a regulatory polymorphism that disrupts a 5' splice site of an exon in the CAST gene, resulting in its exclusion in the mutant allele. This report illustrates that our approach can detect both annotated and novel alternatively spliced variants, and that such variation among individuals is heritable and genetically controlled.
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Affiliation(s)
- Tony Kwan
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | - David Benovoy
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | - Christel Dias
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
| | - Scott Gurd
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | - David Serre
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | - Harry Zuzan
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | | | | | | | - Hui Wang
- Affymetrix Inc., Santa Clara, California 95051, USA
| | | | - Thomas J. Hudson
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
- Ontario Institute for Cancer Research, Toronto, Ontario M5G IL7, Canada
| | - Rob Sladek
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
| | - Jacek Majewski
- Department of Human Genetics, McGill University, Montréal, Québec, H3A 1A4, Canada
- McGill University and Génome Québec Innovation Centre, Montréal, Québec, H3A 1A4, Canada
- Corresponding author.E-mail ; fax (514) 398-1790
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212
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Ben-Dov C, Hartmann B, Lundgren J, Valcárcel J. Genome-wide analysis of alternative pre-mRNA splicing. J Biol Chem 2007; 283:1229-33. [PMID: 18024428 DOI: 10.1074/jbc.r700033200] [Citation(s) in RCA: 110] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
Alternative splicing of mRNA precursors allows the synthesis of multiple mRNAs from a single primary transcript, significantly expanding the information content and regulatory possibilities of higher eukaryotic genomes. High-throughput enabling technologies, particularly large-scale sequencing and splicing-sensitive microarrays, are providing unprecedented opportunities to address key questions in this field. The picture emerging from these pioneering studies is that alternative splicing affects most human genes and a significant fraction of the genes in other multicellular organisms, with the potential to greatly influence the evolution of complex genomes. A combinatorial code of regulatory signals and factors can deploy physiologically coherent programs of alternative splicing that are distinct from those regulated at other steps of gene expression. Pre-mRNA splicing and its regulation play important roles in human pathologies, and genome-wide analyses in this area are paving the way for improved diagnostic tools and for the identification of novel and more specific pharmaceutical targets.
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Affiliation(s)
- Claudia Ben-Dov
- Centre de Regulació Genòmica, Dr. Aiguader 88, 08003 Barcelona, Spain
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213
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Levy A, Sela N, Ast G. TranspoGene and microTranspoGene: transposed elements influence on the transcriptome of seven vertebrates and invertebrates. Nucleic Acids Res 2007; 36:D47-52. [PMID: 17986453 PMCID: PMC2238949 DOI: 10.1093/nar/gkm949] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
Transposed elements (TEs) are mobile genetic sequences. During the evolution of eukaryotes TEs were inserted into active protein-coding genes, affecting gene structure, expression and splicing patterns, and protein sequences. Genomic insertions of TEs also led to creation and expression of new functional non-coding RNAs such as microRNAs. We have constructed the TranspoGene database, which covers TEs located inside protein-coding genes of seven species: human, mouse, chicken, zebrafish, fruit fly, nematode and sea squirt. TEs were classified according to location within the gene: proximal promoter TEs, exonized TEs (insertion within an intron that led to exon creation), exonic TEs (insertion into an existing exon) or intronic TEs. TranspoGene contains information regarding specific type and family of the TEs, genomic and mRNA location, sequence, supporting transcript accession and alignment to the TE consensus sequence. The database also contains host gene specific data: gene name, genomic location, Swiss-Prot and RefSeq accessions, diseases associated with the gene and splicing pattern. In addition, we created microTranspoGene: a database of human, mouse, zebrafish and nematode TE-derived microRNAs. The TranspoGene and microTranspoGene databases can be used by researchers interested in the effect of TE insertion on the eukaryotic transcriptome. Publicly available query interfaces to TranspoGene and microTranspoGene are available at http://transpogene.tau.ac.il/ and http://microtranspogene.tau.ac.il, respectively. The entire database can be downloaded as flat files.
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Affiliation(s)
- Asaf Levy
- Department of Molecular Genetics and Biochemistry, Tel-Aviv University Medical School, Tel Aviv 69978, Israel
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214
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Yates T, Okoniewski MJ, Miller CJ. X:Map: annotation and visualization of genome structure for Affymetrix exon array analysis. Nucleic Acids Res 2007; 36:D780-6. [PMID: 17932061 PMCID: PMC2238884 DOI: 10.1093/nar/gkm779] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Affymetrix exon arrays aim to target every known and predicted exon in the human, mouse or rat genomes, and have reporters that extend beyond protein coding regions to other areas of the transcribed genome. This combination of increased coverage and precision is important because a substantial proportion of protein coding genes are predicted to be alternatively spliced, and because many non-coding genes are known also to be of biological significance. In order to fully exploit these arrays, it is necessary to associate each reporter on the array with the features of the genome it is targeting, and to relate these to gene and genome structure. X:Map is a genome annotation database that provides this information. Data can be browsed using a novel Google-maps based interface, and analysed and further visualized through an associated BioConductor package. The database can be found at http://xmap.picr.man.ac.uk.
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Affiliation(s)
- Tim Yates
- Cancer Research UK, Bioinformatics Group, Paterson Institute for Cancer Research, The University of Manchester, Christie Hospital Site, Wilmslow Road, Withington, Manchester, M20 4BX, UK
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215
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Mitchell ME, Sander TL, Klinkner DB, Tomita-Mitchell A. The Molecular Basis of Congenital Heart Disease. Semin Thorac Cardiovasc Surg 2007; 19:228-37. [DOI: 10.1053/j.semtcvs.2007.07.013] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/26/2007] [Indexed: 12/31/2022]
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216
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Schutte M, Elstrodt F, Bralten LBC, Nagel JHA, Duijm E, Hollestelle A, Vuerhard MJ, Wasielewski M, Peeters JK, van der Spek P, Sillevis Smitt PA, French PJ. Exon expression arrays as a tool to identify new cancer genes. PLoS One 2007; 3:e3007. [PMID: 18688287 PMCID: PMC2500185 DOI: 10.1371/journal.pone.0003007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2008] [Accepted: 07/31/2008] [Indexed: 12/12/2022] Open
Abstract
Background Identification of genes that are causally implicated in oncogenesis is a major goal in cancer research. An estimated 10–20% of cancer-related gene mutations result in skipping of one or more exons in the encoded transcripts. Here we report on a strategy to screen in a global fashion for such exon-skipping events using PAttern based Correlation (PAC). The PAC algorithm has been used previously to identify differentially expressed splice variants between two predefined subgroups. As genetic changes in cancer are sample specific, we tested the ability of PAC to identify aberrantly expressed exons in single samples. Principal Findings As a proof-of-principle, we tested the PAC strategy on human cancer samples of which the complete coding sequence of eight cancer genes had been screened for mutations. PAC detected all seven exon-skipping mutants among 12 cancer cell lines. PAC also identified exon-skipping mutants in clinical cancer specimens although detection was compromised due to heterogeneous (wild-type) transcript expression. PAC reduced the number of candidate genes/exons for subsequent mutational analysis by two to three orders of magnitude and had a substantial true positive rate. Importantly, of 112 randomly selected outlier exons, sequence analysis identified two novel exon skipping events, two novel base changes and 21 previously reported base changes (SNPs). Conclusions The ability of PAC to enrich for mutated transcripts and to identify known and novel genetic changes confirms its suitability as a strategy to identify candidate cancer genes.
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Affiliation(s)
- Mieke Schutte
- Department of Medical Oncology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
- * E-mail: (MS); (PF)
| | - Fons Elstrodt
- Department of Medical Oncology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Linda B. C. Bralten
- Department of Neurology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jord H. A. Nagel
- Department of Medical Oncology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Elza Duijm
- Department of Neurology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Antoinette Hollestelle
- Department of Medical Oncology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maartje J. Vuerhard
- Department of Neurology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Marijke Wasielewski
- Department of Medical Oncology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Justine K. Peeters
- Department of Bioinformatics, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter van der Spek
- Department of Bioinformatics, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Peter A. Sillevis Smitt
- Department of Neurology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Pim J. French
- Department of Neurology, Josephine Nefkens Institute, Erasmus University Medical Center, Rotterdam, The Netherlands
- * E-mail: (MS); (PF)
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217
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Artamonova II, Gelfand MS. Comparative Genomics and Evolution of Alternative Splicing: The Pessimists' Science. Chem Rev 2007; 107:3407-30. [PMID: 17645315 DOI: 10.1021/cr068304c] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Irena I Artamonova
- Group of Bioinformatics, Vavilov Institute of General Genetics, RAS, Gubkina 3, Moscow 119991, Russia
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Das D, Clark TA, Schweitzer A, Yamamoto M, Marr H, Arribere J, Minovitsky S, Poliakov A, Dubchak I, Blume JE, Conboy JG. A correlation with exon expression approach to identify cis-regulatory elements for tissue-specific alternative splicing. Nucleic Acids Res 2007; 35:4845-57. [PMID: 17626050 PMCID: PMC1950531 DOI: 10.1093/nar/gkm485] [Citation(s) in RCA: 70] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2007] [Revised: 06/04/2007] [Accepted: 06/05/2007] [Indexed: 12/22/2022] Open
Abstract
Correlation of motif occurrences with gene expression intensity is an effective strategy for elucidating transcriptional cis-regulatory logic. Here we demonstrate that this approach can also identify cis-regulatory elements for alternative pre-mRNA splicing. Using data from a human exon microarray, we identified 56 cassette exons that exhibited higher transcript-normalized expression in muscle than in other normal adult tissues. Intron sequences flanking these exons were then analyzed to identify candidate regulatory motifs for muscle-specific alternative splicing. Correlation of motif parameters with gene-normalized exon expression levels was examined using linear regression and linear splines on RNA words and degenerate weight matrices, respectively. Our unbiased analysis uncovered multiple candidate regulatory motifs for muscle-specific splicing, many of which are phylogenetically conserved among vertebrate genomes. The most prominent downstream motifs were binding sites for Fox1- and CELF-related splicing factors, and a branchpoint-like element acuaac; pyrimidine-rich elements resembling PTB-binding sites were most significant in upstream introns. Intriguingly, our systematic study indicates a paucity of novel muscle-specific elements that are dominant in short proximal intronic regions. We propose that Fox and CELF proteins play major roles in enforcing the muscle-specific alternative splicing program, facilitating expression of unique isoforms of cytoskeletal proteins critical to muscle cell function.
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Affiliation(s)
- Debopriya Das
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Tyson A. Clark
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Anthony Schweitzer
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Miki Yamamoto
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Henry Marr
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Josh Arribere
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Simon Minovitsky
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Alexander Poliakov
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Inna Dubchak
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - John E. Blume
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - John G. Conboy
- Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, Affymetrix, Inc., Santa Clara, CA, 95051 and Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
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