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      Discovery of CTCF-Sensitive Cis-Spliced Fusion RNAs between Adjacent Genes in Human Prostate Cells

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          Abstract

          Genes or their encoded products are not expected to mingle with each other unless in some disease situations. In cancer, a frequent mechanism that can produce gene fusions is chromosomal rearrangement. However, recent discoveries of RNA trans-splicing and cis-splicing between adjacent genes (cis-SAGe) support for other mechanisms in generating fusion RNAs. In our transcriptome analyses of 28 prostate normal and cancer samples, 30% fusion RNAs on average are the transcripts that contain exons belonging to same-strand neighboring genes. These fusion RNAs may be the products of cis-SAGe, which was previously thought to be rare. To validate this finding and to better understand the phenomenon, we used LNCaP, a prostate cell line as a model, and identified 16 additional cis-SAGe events by silencing transcription factor CTCF and paired-end RNA sequencing. About half of the fusions are expressed at a significant level compared to their parental genes. Silencing one of the in-frame fusions resulted in reduced cell motility. Most out-of-frame fusions are likely to function as non-coding RNAs. The majority of the 16 fusions are also detected in other prostate cell lines, as well as in the 14 clinical prostate normal and cancer pairs. By studying the features associated with these fusions, we developed a set of rules: 1) the parental genes are same-strand-neighboring genes; 2) the distance between the genes is within 30kb; 3) the 5′ genes are actively transcribing; and 4) the chimeras tend to have the second-to-last exon in the 5′ genes joined to the second exon in the 3′ genes. We then randomly selected 20 neighboring genes in the genome, and detected four fusion events using these rules in prostate cancer and non-cancerous cells. These results suggest that splicing between neighboring gene transcripts is a rather frequent phenomenon, and it is not a feature unique to cancer cells.

          Author Summary

          Genes are considered the units of hereditary information; thus, neither genes nor their encoded products are expected to mingle with each other unless in some disease situations. However, the genes are not alone in the genome. Genes have neighbors, some close, some far. With RNA-seq, many fusion RNAs involving neighboring genes are being identified. However, little is done to validate and characterize the fusion RNAs. Using one prostate cell line and a discovery pipeline for cis-splicing between adjacent genes (cis-SAGe), we found 16 new such events. We then developed a set of rules based on the characteristics of these fusion RNAs, and applied them to 20 random neighboring gene pairs. Four turned out to be true. The majority of the fusions are found in cancer cells, as well as in non-cancer cells. These results suggest that the genes are “leaky”, and the fusions are not limited to cancer cells.

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          Most cited references22

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          Transcriptome Sequencing to Detect Gene Fusions in Cancer

          Recurrent gene fusions, typically associated with hematological malignancies and rare bone and soft tissue tumors1, have been recently described in common solid tumors2–9. Here we employ an integrative analysis of high-throughput long and short read transcriptome sequencing of cancer cells to discover novel gene fusions. As a proof of concept we successfully utilized integrative transcriptome sequencing to “re-discover” the BCR-ABL1 10 gene fusion in a chronic myelogenous leukemia cell line and the TMPRSS2-ERG 2,3 gene fusion in a prostate cancer cell line and tissues. Additionally, we nominated, and experimentally validated, novel gene fusions resulting in chimeric transcripts in cancer cell lines and tumors. Taken together, this study establishes a robust pipeline for the discovery of novel gene chimeras using high throughput sequencing, opening up an important class of cancer-related mutations for comprehensive characterization.
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            A slow RNA polymerase II affects alternative splicing in vivo.

            Changes in promoter structure and occupation have been shown to modify the splicing pattern of several genes, evidencing a coupling between transcription and alternative splicing. It has been proposed that the promoter effect involves modulation of RNA pol II elongation rates. The C4 point mutation of the Drosophila pol II largest subunit confers on the enzyme a lower elongation rate. Here we show that expression of a human equivalent to Drosophila's C4 pol II in human cultured cells affects alternative splicing of the fibronectin EDI exon and adenovirus E1a pre-mRNA. Most importantly, resplicing of the Hox gene Ultrabithorax is stimulated in Drosophila embryos mutant for C4, which demonstrates the transcriptional control of alternative splicing on an endogenous gene. These results provide a direct proof for the elongation control of alternative splicing in vivo.
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              Analysis of canonical and non-canonical splice sites in mammalian genomes.

              A set of 43 337 splice junction pairs was extracted from mammalian GenBank annotated genes. Expressed sequence tag (EST) sequences support 22 489 of them. Of these, 98.71% contain canonical dinucleotides GT and AG for donor and acceptor sites, respectively; 0.56% hold non-canonical GC-AG splice site pairs; and the remaining 0.73% occurs in a lot of small groups (with a maximum size of 0.05%). Studying these groups we observe that many of them contain splicing dinucleotides shifted from the annotated splice junction by one position. After close examination of such cases we present a new classification consisting of only eight observed types of splice site pairs (out of 256 a priori possible combinations). EST alignments allow us to verify the exonic part of the splice sites, but many non-canonical cases may be due to intron sequencing errors. This idea is given substantial support when we compare the sequences of human genes having non-canonical splice sites deposited in GenBank by high throughput genome sequencing projects (HTG). A high proportion (156 out of 171) of the human non-canonical and EST-supported splice site sequences had a clear match in the human HTG. They can be classified after corrections as: 79 GC-AG pairs (of which one was an error that corrected to GC-AG), 61 errors that were corrected to GT-AG canonical pairs, six AT-AC pairs (of which two were errors that corrected to AT-AC), one case was produced from non-existent intron, seven cases were found in HTG that were deposited to GenBank and finally there were only two cases left of supported non-canonical splice sites. If we assume that approximately the same situation is true for the whole set of annotated mammalian non-canonical splice sites, then the 99.24% of splice site pairs should be GT-AG, 0.69% GC-AG, 0.05% AT-AC and finally only 0.02% could consist of other types of non-canonical splice sites. We analyze several characteristics of EST-verified splice sites and build weight matrices for the major groups, which can be incorporated into gene prediction programs. We also present a set of EST-verified canonical splice sites larger by two orders of magnitude than the current one (22 199 entries versus approximately 600) and finally, a set of 290 EST-supported non-canonical splice sites. Both sets should be significant for future investigations of the splicing mechanism.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS Genet
                PLoS Genet
                plos
                plosgen
                PLoS Genetics
                Public Library of Science (San Francisco, CA USA )
                1553-7390
                1553-7404
                6 February 2015
                February 2015
                : 11
                : 2
                : e1005001
                Affiliations
                [1 ]Department of Pathology, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
                [2 ]Pharmacy Department of Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, China
                [3 ]Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, Virginia, United States of America
                Stanford Medical School, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Conceived and designed the experiments: HL FQ. Performed the experiments: FQ MB ZS YS. Analyzed the data: HL FQ MB ZS LF RS MA. Contributed reagents/materials/analysis tools: RS. Wrote the paper: HL FQ.

                Article
                PGENETICS-D-14-03081
                10.1371/journal.pgen.1005001
                4450057
                25658338
                edc2a823-da57-42ac-881b-ba1cb41ac21c
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 17 November 2014
                : 13 January 2015
                Page count
                Figures: 6, Tables: 1, Pages: 19
                Funding
                This work is supported by NIH grant CA190713, www.cancer.gov. HL is an American Cancer Society Research Scholar RSG-14-065-01-RMC, www.acs.org, and a St. Baldrick V Scholar, http://www.stbaldricks.org. FQ is supported by the Farrow Fellowship and by the NCI Cancer Center Support Grant P30 CA44579, www.cancer.gov. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All fusion RNAs and primer sequences are listed in the table and supplementary table. The Raw and processed RNA-sequencing data from this study have been submitted to the NCBI Gene Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE63487.

                Genetics
                Genetics

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