A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences

Detalhes bibliográficos
Autor(a) principal: Carels, Nicolas
Data de Publicação: 2013
Outros Autores: Frias, Diego
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FIOCRUZ (ARCA)
Texto Completo: https://www.arca.fiocruz.br/handle/icict/11675
Resumo: Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genômica Funcional e Bioinformática. Rio de Janeiro, RJ, Brasil.
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spelling Carels, NicolasFrias, Diego2015-09-21T17:25:09Z2015-09-21T17:25:09Z2013CARELS, Nicolas; FRIAS, Diego. A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences. Bioinformatics and Biology Insights, n.7, p.35–54, 2013.1177-9322https://www.arca.fiocruz.br/handle/icict/1167510.4137/BBI.S10053engLibertas AcademicaA Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequencesinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleFundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genômica Funcional e Bioinformática. Rio de Janeiro, RJ, Brasil.Universidade do Estado da Bahia (UNE B). Departamento de Ciências Exatas e da Terr. Salvador, BA, Brasil.Abstract: In this study, we investigated the modalities of coding open reading frame (cORF) classification of expressed sequence tags (EST) by using the universal feature method (UFM). The UFM algorithm is based on the scoring of purine bias (Rrr) and stop codon frequencies. UFM classifies ORFs as coding or non-coding through a score based on 5 factors: (i) stop codon frequency; (ii) the product of the probabilities of purines occurring in the three positions of nucleotide triplets; (iii) the product of the probabilities of Cytosine (C), Guanine (G), and Adenine (A) occurring in the 1st, 2nd, and 3rd positions of triplets, respectively; (iv) the probabilities of a G occurring in the 1st and 2nd positions of triplets; and (v) the probabilities of a T occurring in the 1st and an A in the 2nd position of triplets. Because UFM is based on primary determinants of coding sequences that are conserved throughout the biosphere, it is suitable for cORF classification of any sequence in eukaryote transcriptomes without prior knowledge. Considering the protein sequences of the Protein Data Bank (RCSB PDB or more simply PDB) as a reference, we found that UFM classifies cORFs of $200 bp (if the coding strand is known) and cORFs of $300 bp (if the coding strand is unknown), and releases them in their coding strand and coding frame, which allows their automatic translation into protein sequences with a success rate equal to or higher than 95%. We first established the statistical parameters of UFM using ESTs from Plasmodium falciparum, Arabidopsis thaliana, Oryza sativa, Zea mays, Drosophila melanogaster, Homo sapiens and Chlamydomonas reinhardtii in reference to the protein sequences of PDB. Second, we showed that the success rate of cORF classification using UFM is expected to apply to approximately 95% of higher eukaryote genes that encode for proteins. Third, we used UFM in combination with CAP3 to assemble large EST samples into cORFs that we used to analyze transcriptome phenotypes in rice, maize, and humans. We discuss the error rate and the interference of noisy sequences such as pseudogenes, transposons, and retrotransposons. This method is suitable for rapid cORF extraction from transcriptome data and allows correct description of the genome phenotypes of plant genomes without prior knowledge. Additional care is necessary when addressing the human transcriptome due to the interference caused by large amounts of noisy sequences. UFM can be regarded as a low complexity tool for prior knowledge extraction concerning the coding fraction of the transcriptome of any eukaryote. Due to its low level of complexity, UFM is also very robust to variations of codon usage.GenomicsRNYESTORFCDSUFMClassificationTranscriptomaGenômicainfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txttext/plain1914https://www.arca.fiocruz.br/bitstream/icict/11675/1/license.txt7d48279ffeed55da8dfe2f8e81f3b81fMD51ORIGINALnicolas_farrelefrias_IOC_2013.pdfapplication/pdf2293297https://www.arca.fiocruz.br/bitstream/icict/11675/2/nicolas_farrelefrias_IOC_2013.pdf22a26c143725fc8272d56eab95256053MD52TEXTnicolas_farrelefrias_IOC_2013.pdf.txtnicolas_farrelefrias_IOC_2013.pdf.txtExtracted texttext/plain76113https://www.arca.fiocruz.br/bitstream/icict/11675/3/nicolas_farrelefrias_IOC_2013.pdf.txtfd124a54685e2a0e4ca292aa5a379f96MD53icict/116752022-06-24 12:17:44.072oai:www.arca.fiocruz.br:icict/11675TElDRU7Dh0EgREUgRElTVFJJQlVJw4fDg08gTsODTy1FWENMVVNJVkEKCkFvIGNvbmNvcmRhciBlIGFjZWl0YXIgZXN0YSBsaWNlbsOnYSB2b2PDqiAoYXV0b3Igb3UgZGV0ZW50b3IgZG9zIGRpcmVpdG9zIGF1dG9yYWlzKToKCmEpIERlY2xhcmEgcXVlIGNvbmhlY2UgYSBwb2zDrXRpY2EgZGUgY29weXJpZ2h0IGRhIGVkaXRvcmEgZG8gc2V1IGRvY3VtZW50by4KCmIpIERlY2xhcmEgcXVlIGNvbmhlY2UgZSBhY2VpdGEgYXMgRGlyZXRyaXplcyBwYXJhIG8gUmVwb3NpdMOzcmlvIEluc3RpdHVjaW9uYWwgZGEgRnVuZGHDp8OjbyBPc3dhbGRvIENydXogKEZJT0NSVVopLgoKYykgQ29uY2VkZSDDoCBGSU9DUlVaIG8gZGlyZWl0byBuw6NvLWV4Y2x1c2l2byBkZSBhcnF1aXZhciwgcmVwcm9kdXppciwgY29udmVydGVyIChjb21vIGRlZmluaWRvIGEgc2VndWlyKSwgY29tdW5pY2FyCiAKZS9vdSBkaXN0cmlidWlyIG5vIFJlcG9zaXTDs3JpbyBkYSBGSU9DUlVaLCBvIGRvY3VtZW50byBlbnRyZWd1ZSAoaW5jbHVpbmRvIG8gcmVzdW1vL2Fic3RyYWN0KSBlbSBmb3JtYXRvIGRpZ2l0YWwgb3UgCgpwb3IgcXVhbHF1ZXIgb3V0cm8gbWVpby4KCmQpIERlY2xhcmEgcXVlIGF1dG9yaXphIGEgRklPQ1JVWiBhIGFycXVpdmFyIG1haXMgZGUgdW1hIGPDs3BpYSBkZXN0ZSBkb2N1bWVudG8gZSBjb252ZXJ0w6otbG8sIHNlbSBhbHRlcmFyIG8gc2V1IGNvbnRlw7pkbywgCgpwYXJhIHF1YWxxdWVyIGZvcm1hdG8gZGUgYXJxdWl2bywgbWVpbyBvdSBzdXBvcnRlLCBwYXJhIGVmZWl0b3MgZGUgc2VndXJhbsOnYSwgcHJlc2VydmHDp8OjbyAoYmFja3VwKSBlIGFjZXNzby4KCmUpIERlY2xhcmEgcXVlIG8gZG9jdW1lbnRvIHN1Ym1ldGlkbyDDqSBvIHNldSB0cmFiYWxobyBvcmlnaW5hbCwgZSBxdWUgZGV0w6ltIG8gZGlyZWl0byBkZSBjb25jZWRlciBhIHRlcmNlaXJvcyBvcyBkaXJlaXRvcyAKCmNvbnRpZG9zIG5lc3RhIGxpY2Vuw6dhLiBEZWNsYXJhIHRhbWLDqW0gcXVlIGEgZW50cmVnYSBkbyBkb2N1bWVudG8gbsOjbyBpbmZyaW5nZSBvcyBkaXJlaXRvcyBkZSBxdWFscXVlciBvdXRyYSBwZXNzb2Egb3UgZW50aWRhZGUuCgpmKSBEZWNsYXJhIHF1ZSwgbm8gY2FzbyBkbyBkb2N1bWVudG8gc3VibWV0aWRvIGNvbnRlciBtYXRlcmlhbCBkbyBxdWFsIG7Do28gZGV0w6ltIG9zIGRpcmVpdG9zIGRlIGF1dG9yLCBvYnRldmUgYSBhdXRvcml6YcOnw6NvIAoKaXJyZXN0cml0YSBkbyByZXNwZWN0aXZvIGRldGVudG9yIGRlc3NlcyBkaXJlaXRvcywgcGFyYSBjZWRlciBhIEZJT0NSVVogb3MgZGlyZWl0b3MgcmVxdWVyaWRvcyBwb3IgZXN0YSBMaWNlbsOnYSBlIGF1dG9yaXphciBhIAoKdXRpbGl6w6EtbG9zIGxlZ2FsbWVudGUuIERlY2xhcmEgdGFtYsOpbSBxdWUgZXNzZSBtYXRlcmlhbCBjdWpvcyBkaXJlaXRvcyBzw6NvIGRlIHRlcmNlaXJvcyBlc3TDoSBjbGFyYW1lbnRlIGlkZW50aWZpY2FkbyBlIHJlY29uaGVjaWRvIAoKbm8gdGV4dG8gb3UgY29udGXDumRvIGRvIGRvY3VtZW50byBlbnRyZWd1ZS4KCmcpIFNFIE8gRE9DVU1FTlRPIEVOVFJFR1VFIMOJIEJBU0VBRE8gRU0gVFJBQkFMSE8gRklOQU5DSUFETyBPVSBBUE9JQURPIFBPUiBPVVRSQSBJTlNUSVRVScOHw4NPIFFVRSBOw4NPIEEgRklPQ1JVWiwgREVDTEFSQSBRVUUgQ1VNUFJJVSAKClFVQUlTUVVFUiBPQlJJR0HDh8OVRVMgRVhJR0lEQVMgUEVMTyBSRVNQRUNUSVZPIENPTlRSQVRPIE9VIEFDT1JETy4gQSBGSU9DUlVaIGlkZW50aWZpY2Fyw6EgY2xhcmFtZW50ZSBvKHMpIG5vbWUocykgZG8ocykgYXV0b3IoZXMpIGRvcyAKCmRpcmVpdG9zIGRvIGRvY3VtZW50byBlbnRyZWd1ZSBlIG7Do28gZmFyw6EgcXVhbHF1ZXIgYWx0ZXJhw6fDo28sIHBhcmEgYWzDqW0gZG8gcHJldmlzdG8gbmEgYWzDrW5lYSBjKS4KRepositório InstitucionalPUBhttps://www.arca.fiocruz.br/oai/requestrepositorio.arca@fiocruz.bropendoar:21352022-06-24T15:17:44Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)false
dc.title.pt_BR.fl_str_mv A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
title A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
spellingShingle A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
Carels, Nicolas
Genomics
RNY
EST
ORF
CDS
UFM
Classification
Transcriptoma
Genômica
title_short A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
title_full A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
title_fullStr A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
title_full_unstemmed A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
title_sort A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences
author Carels, Nicolas
author_facet Carels, Nicolas
Frias, Diego
author_role author
author2 Frias, Diego
author2_role author
dc.contributor.author.fl_str_mv Carels, Nicolas
Frias, Diego
dc.subject.en.pt_BR.fl_str_mv Genomics
RNY
EST
ORF
CDS
UFM
Classification
topic Genomics
RNY
EST
ORF
CDS
UFM
Classification
Transcriptoma
Genômica
dc.subject.decs.pt_BR.fl_str_mv Transcriptoma
Genômica
description Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Genômica Funcional e Bioinformática. Rio de Janeiro, RJ, Brasil.
publishDate 2013
dc.date.issued.fl_str_mv 2013
dc.date.accessioned.fl_str_mv 2015-09-21T17:25:09Z
dc.date.available.fl_str_mv 2015-09-21T17:25:09Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.citation.fl_str_mv CARELS, Nicolas; FRIAS, Diego. A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences. Bioinformatics and Biology Insights, n.7, p.35–54, 2013.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/11675
dc.identifier.issn.pt_BR.fl_str_mv 1177-9322
dc.identifier.doi.pt_BR.fl_str_mv 10.4137/BBI.S10053
identifier_str_mv CARELS, Nicolas; FRIAS, Diego. A Statistical Method without Training Step for the Classification of Coding Frame in Transcriptome Sequences. Bioinformatics and Biology Insights, n.7, p.35–54, 2013.
1177-9322
10.4137/BBI.S10053
url https://www.arca.fiocruz.br/handle/icict/11675
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Libertas Academica
publisher.none.fl_str_mv Libertas Academica
dc.source.none.fl_str_mv reponame:Repositório Institucional da FIOCRUZ (ARCA)
instname:Fundação Oswaldo Cruz (FIOCRUZ)
instacron:FIOCRUZ
instname_str Fundação Oswaldo Cruz (FIOCRUZ)
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reponame_str Repositório Institucional da FIOCRUZ (ARCA)
collection Repositório Institucional da FIOCRUZ (ARCA)
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repository.name.fl_str_mv Repositório Institucional da FIOCRUZ (ARCA) - Fundação Oswaldo Cruz (FIOCRUZ)
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