1 resultado para statistical data analysis
em Universita di Parma
Filtro por publicador
- Aberdeen University (1)
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- Archimer: Archive de l'Institut francais de recherche pour l'exploitation de la mer (1)
- Archive of European Integration (10)
- Aston University Research Archive (35)
- Biblioteca de Teses e Dissertações da USP (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (14)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (62)
- Biblioteca Virtual del Sistema Sanitario Público de Andalucía (BV-SSPA), Junta de Andalucía. Consejería de Salud y Bienestar Social, Spain (3)
- Bioline International (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (33)
- Brock University, Canada (4)
- Bulgarian Digital Mathematics Library at IMI-BAS (3)
- CaltechTHESIS (1)
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- CiencIPCA - Instituto Politécnico do Cávado e do Ave, Portugal (1)
- Cochin University of Science & Technology (CUSAT), India (6)
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- Instituto Nacional de Saúde de Portugal (1)
- Instituto Politécnico do Porto, Portugal (23)
- Iowa Publications Online (IPO) - State Library, State of Iowa (Iowa), United States (10)
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- Repositório Científico da Universidade de Évora - Portugal (1)
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- Repositório da Produção Científica e Intelectual da Unicamp (6)
- Repositório da Universidade Federal do Espírito Santo (UFES), Brazil (2)
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- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (102)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (24)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Scielo Saúde Pública - SP (19)
- Scientific Open-access Literature Archive and Repository (2)
- Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom (4)
- Universidad de Alicante (3)
- Universidad del Rosario, Colombia (10)
- Universidad Politécnica de Madrid (6)
- Universidade do Minho (14)
- Universidade dos Açores - Portugal (8)
- Universidade Estadual Paulista "Júlio de Mesquita Filho" (UNESP) (1)
- Universidade Federal do Pará (12)
- Universidade Federal do Rio Grande do Norte (UFRN) (24)
- Universidade Metodista de São Paulo (1)
- Universidade Técnica de Lisboa (2)
- Universita di Parma (1)
- Universitat de Girona, Spain (40)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (7)
- Université de Lausanne, Switzerland (56)
- Université de Montréal, Canada (8)
- University of Michigan (44)
- University of Queensland eSpace - Australia (23)
- University of Southampton, United Kingdom (7)
- University of Washington (1)
Resumo:
Of the ~1.7 million SINE elements in the human genome, only a tiny number are estimated to be active in transcription by RNA polymerase (Pol) III. Tracing the individual loci from which SINE transcripts originate is complicated by their highly repetitive nature. By exploiting RNA-Seq datasets and unique SINE DNA sequences, we devised a bioinformatic pipeline allowing us to identify Pol III-dependent transcripts of individual SINE elements. When applied to ENCODE transcriptomes of seven human cell lines, this search strategy identified ~1300 Alu loci and ~1100 MIR loci corresponding to detectable transcripts, with ~120 and ~60 respectively Alu and MIR loci expressed in at least three cell lines. In vitro transcription of selected SINEs did not reflect their in vivo expression properties, and required the native 5’-flanking region in addition to internal promoter. We also identified a cluster of expressed AluYa5-derived transcription units, juxtaposed to snaR genes on chromosome 19, formed by a promoter-containing left monomer fused to an Alu-unrelated downstream moiety. Autonomous Pol III transcription was also revealed for SINEs nested within Pol II-transcribed genes raising the possibility of an underlying mechanism for Pol II gene regulation by SINE transcriptional units. Moreover the application of our bioinformatic pipeline to both RNA-seq data of cells subjected to an in vitro pro-oncogenic stimulus and of in vivo matched tumor and non-tumor samples allowed us to detect increased Alu RNA expression as well as the source loci of such deregulation. The ability to investigate SINE transcriptomes at single-locus resolution will facilitate both the identification of novel biologically relevant SINE RNAs and the assessment of SINE expression alteration under pathological conditions.