Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Revista de Ciências Agrárias (Belém. Online) |
Texto Completo: | https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319 |
Resumo: | The discovery of nucleic acids opened new frontiers of knowledge, enabling researchers to access an enormous amount of data, through large-scale sequencing methodologies and bioinformatics tools. Amongst these new possibilities, RNA-Seq has been used to identify and quantify RNA molecules. To obtain more accurate biological responses from RNA-Seq data some questions should be considered such as experimental design, type of synthesized library, size of the fragments generated, number of biological replicates, depth, and coverage of the sequencing, species genome availability, and, the choice of software to properly perform the computational analyzes. Accurate bioinformatics analyzes allow the selection of genes with a lower error rate, increasing the validation assertiveness via RT-qPCR and thus, reducing costs. The objective of this review was to present the analysis stages of RNA-Seq data, from experimental design to system biology, considering relevant points, as well as to pointed out some software currently available to carry these analyzes out. Besides, with this review, we aimed to help the academic community to understand all steps and biases involved in RNA-Seq data analysis, from experiments with or without biological replicates. |
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Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areviewTranscriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areviewsequencingbioinformaticspipelineRNAAnálises transcricionaisbioinformáticagenética vegetalRNA-seq com e sem replicatas sequenciadassequenciamentobioinformáticapipelineRNAThe discovery of nucleic acids opened new frontiers of knowledge, enabling researchers to access an enormous amount of data, through large-scale sequencing methodologies and bioinformatics tools. Amongst these new possibilities, RNA-Seq has been used to identify and quantify RNA molecules. To obtain more accurate biological responses from RNA-Seq data some questions should be considered such as experimental design, type of synthesized library, size of the fragments generated, number of biological replicates, depth, and coverage of the sequencing, species genome availability, and, the choice of software to properly perform the computational analyzes. Accurate bioinformatics analyzes allow the selection of genes with a lower error rate, increasing the validation assertiveness via RT-qPCR and thus, reducing costs. The objective of this review was to present the analysis stages of RNA-Seq data, from experimental design to system biology, considering relevant points, as well as to pointed out some software currently available to carry these analyzes out. Besides, with this review, we aimed to help the academic community to understand all steps and biases involved in RNA-Seq data analysis, from experiments with or without biological replicates.A descoberta de ácidos nucléicos abriu novas fronteiras de conhecimento, permitindo que os pesquisadores acessassem uma enorme quantidade de dados, através de metodologias de sequenciamento em larga escala e ferramentas de bioinformática. Entre essas novas possibilidades, o RNA-Seq (sequenciamento de RNA) tem sido usado para identificar e quantificar moléculas de RNA. Para obter respostas biológicas mais precisas a partir dos dados de RNA-Seq, algumas questões devem ser consideradas, como o desenho experimental, o tipo de biblioteca sintetizada, o tamanho dos fragmentos gerados, o número de repetições biológicas, a profundidade e cobertura do sequenciamento, a disponibilidade do genoma da espécie e, a escolha dos softwares para executar adequadamente as análises computacionais. Análises bioinformáticas precisas permitem a seleção de genes com menor taxa de erro, aumentando a assertividade da validação via RT-qPCR e, assim, reduzindo custos. O objetivo desta revisão foi apresentar as etapas de análise de dados de RNA-Seq, desde o projeto experimental até a biologia do sistema, considerando pontos relevantes, bem como apontar alguns softwares atualmente disponíveis para realizar essas análises. Além disso, com esta revisão, objetivamos ajudar a comunidade acadêmica a compreender todas as etapas e vieses envolvidos na análise de dados de RNA-Seq, a partir de experimentos com ou sem réplicas biológicas.Universidade Federal Rural da Amazônia/UFRA2021-01-19info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontextoapplication/pdfhttps://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319Amazonian Journal of Agricultural Sciences Journal of Agricultural and Environmental Sciences; Vol 64 (2021): RCA AJAESRevista de Ciências Agrárias Amazonian Journal of Agricultural and Environmental Sciences; v. 64 (2021): RCA AJAES2177-87601517-591Xreponame:Revista de Ciências Agrárias (Belém. Online)instname:Universidade Federal Rural da Amazônia (UFRA)instacron:UFRAporhttps://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319/1612Copyright (c) 2021 Mayla Daiane Correa Molinari, Renata Fuganti-Pagliarini, Jéssika Angelotti Mendonça, Daniel de Amorim Barobosa, Daniel Rockenbach Marin, Liliane Mertz-Henning, Alexandre Lima Nepomucenohttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessMolinari, Mayla Daiane CorreaFuganti-Pagliarini, RenataAngelotti Mendonça, Jéssika de Amorim Barobosa, DanielRockenbach Marin, DanielMertz-Henning, LilianeLima Nepomuceno, Alexandre 2021-10-14T21:43:27Zoai:ojs.www.periodicos.ufra.edu.br:article/3319Revistahttps://ajaes.ufra.edu.br/index.php/ajaes/PUBhttps://ajaes.ufra.edu.br/index.php/ajaes/oaiallan.lobato@ufra.edu.br || ajaes.suporte@gmail.com2177-87601517-591Xopendoar:2021-10-14T21:43:27Revista de Ciências Agrárias (Belém. Online) - Universidade Federal Rural da Amazônia (UFRA)false |
dc.title.none.fl_str_mv |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
title |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
spellingShingle |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview Molinari, Mayla Daiane Correa sequencing bioinformatics pipeline RNA Análises transcricionais bioinformática genética vegetal RNA-seq com e sem replicatas sequenciadas sequenciamento bioinformática pipeline RNA |
title_short |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
title_full |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
title_fullStr |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
title_full_unstemmed |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
title_sort |
Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview |
author |
Molinari, Mayla Daiane Correa |
author_facet |
Molinari, Mayla Daiane Correa Fuganti-Pagliarini, Renata Angelotti Mendonça, Jéssika de Amorim Barobosa, Daniel Rockenbach Marin, Daniel Mertz-Henning, Liliane Lima Nepomuceno, Alexandre |
author_role |
author |
author2 |
Fuganti-Pagliarini, Renata Angelotti Mendonça, Jéssika de Amorim Barobosa, Daniel Rockenbach Marin, Daniel Mertz-Henning, Liliane Lima Nepomuceno, Alexandre |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Molinari, Mayla Daiane Correa Fuganti-Pagliarini, Renata Angelotti Mendonça, Jéssika de Amorim Barobosa, Daniel Rockenbach Marin, Daniel Mertz-Henning, Liliane Lima Nepomuceno, Alexandre |
dc.subject.por.fl_str_mv |
sequencing bioinformatics pipeline RNA Análises transcricionais bioinformática genética vegetal RNA-seq com e sem replicatas sequenciadas sequenciamento bioinformática pipeline RNA |
topic |
sequencing bioinformatics pipeline RNA Análises transcricionais bioinformática genética vegetal RNA-seq com e sem replicatas sequenciadas sequenciamento bioinformática pipeline RNA |
description |
The discovery of nucleic acids opened new frontiers of knowledge, enabling researchers to access an enormous amount of data, through large-scale sequencing methodologies and bioinformatics tools. Amongst these new possibilities, RNA-Seq has been used to identify and quantify RNA molecules. To obtain more accurate biological responses from RNA-Seq data some questions should be considered such as experimental design, type of synthesized library, size of the fragments generated, number of biological replicates, depth, and coverage of the sequencing, species genome availability, and, the choice of software to properly perform the computational analyzes. Accurate bioinformatics analyzes allow the selection of genes with a lower error rate, increasing the validation assertiveness via RT-qPCR and thus, reducing costs. The objective of this review was to present the analysis stages of RNA-Seq data, from experimental design to system biology, considering relevant points, as well as to pointed out some software currently available to carry these analyzes out. Besides, with this review, we aimed to help the academic community to understand all steps and biases involved in RNA-Seq data analysis, from experiments with or without biological replicates. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-01-19 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion texto |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319 |
url |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://ajaes.ufra.edu.br/index.php/ajaes/article/view/3319/1612 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal Rural da Amazônia/UFRA |
publisher.none.fl_str_mv |
Universidade Federal Rural da Amazônia/UFRA |
dc.source.none.fl_str_mv |
Amazonian Journal of Agricultural Sciences Journal of Agricultural and Environmental Sciences; Vol 64 (2021): RCA AJAES Revista de Ciências Agrárias Amazonian Journal of Agricultural and Environmental Sciences; v. 64 (2021): RCA AJAES 2177-8760 1517-591X reponame:Revista de Ciências Agrárias (Belém. Online) instname:Universidade Federal Rural da Amazônia (UFRA) instacron:UFRA |
instname_str |
Universidade Federal Rural da Amazônia (UFRA) |
instacron_str |
UFRA |
institution |
UFRA |
reponame_str |
Revista de Ciências Agrárias (Belém. Online) |
collection |
Revista de Ciências Agrárias (Belém. Online) |
repository.name.fl_str_mv |
Revista de Ciências Agrárias (Belém. Online) - Universidade Federal Rural da Amazônia (UFRA) |
repository.mail.fl_str_mv |
allan.lobato@ufra.edu.br || ajaes.suporte@gmail.com |
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1797231630329315328 |