Transcriptome analysis using RNA-Seq fromexperiments with and without biological replicates: areview

Detalhes bibliográficos
Autor(a) principal: Molinari, Mayla Daiane Correa
Data de Publicação: 2021
Outros Autores: Fuganti-Pagliarini, Renata, Angelotti Mendonça, Jéssika, de Amorim Barobosa, Daniel, Rockenbach Marin, Daniel, Mertz-Henning, Liliane, Lima Nepomuceno, Alexandre
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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spelling 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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