In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases

Detalhes bibliográficos
Autor(a) principal: Alvarenga,Samuel Mazzinghy
Data de Publicação: 2010
Outros Autores: Caixeta,Eveline Teixeira, Hufnagel,Bárbara, Thiebaut,Flávia, Maciel-Zambolim,Eunize, Zambolimand,Laércio, Sakiyama,Ney Sussumu
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Genetics and Molecular Biology
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031
Resumo: Sequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and plant defense responses to diseases. The 140 EST-contigs identified through the keyword NBS-LRR were classified according to function. This classification allowed association of the predicted products of EST-contigs with biological processes, including host defense and apoptosis, and with molecular functions such as nucleotide binding and signal transducer activity. Fisher's exact test was used to examine the significance of differences in contig expression between libraries representing the responses to biotic stress challenges and other libraries from the BCGP. This analysis revealed seven contigs highly similar to catalase, chitinase, protein with a BURP domain and unknown proteins. The involvement of these coffee proteins in plant responses to disease is discussed.
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spelling In silico identification of coffee genome expressed sequences potentially associated with resistance to diseasesCoffeadata miningESTsgenomicsin silicobioinformaticsSequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and plant defense responses to diseases. The 140 EST-contigs identified through the keyword NBS-LRR were classified according to function. This classification allowed association of the predicted products of EST-contigs with biological processes, including host defense and apoptosis, and with molecular functions such as nucleotide binding and signal transducer activity. Fisher's exact test was used to examine the significance of differences in contig expression between libraries representing the responses to biotic stress challenges and other libraries from the BCGP. This analysis revealed seven contigs highly similar to catalase, chitinase, protein with a BURP domain and unknown proteins. The involvement of these coffee proteins in plant responses to disease is discussed.Sociedade Brasileira de Genética2010-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031Genetics and Molecular Biology v.33 n.4 2010reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/S1415-47572010000400031info:eu-repo/semantics/openAccessAlvarenga,Samuel MazzinghyCaixeta,Eveline TeixeiraHufnagel,BárbaraThiebaut,FláviaMaciel-Zambolim,EunizeZambolimand,LaércioSakiyama,Ney Sussumueng2011-01-06T00:00:00Zoai:scielo:S1415-47572010000400031Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2011-01-06T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false
dc.title.none.fl_str_mv In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
title In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
spellingShingle In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
Alvarenga,Samuel Mazzinghy
Coffea
data mining
ESTs
genomics
in silico
bioinformatics
title_short In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
title_full In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
title_fullStr In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
title_full_unstemmed In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
title_sort In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases
author Alvarenga,Samuel Mazzinghy
author_facet Alvarenga,Samuel Mazzinghy
Caixeta,Eveline Teixeira
Hufnagel,Bárbara
Thiebaut,Flávia
Maciel-Zambolim,Eunize
Zambolimand,Laércio
Sakiyama,Ney Sussumu
author_role author
author2 Caixeta,Eveline Teixeira
Hufnagel,Bárbara
Thiebaut,Flávia
Maciel-Zambolim,Eunize
Zambolimand,Laércio
Sakiyama,Ney Sussumu
author2_role author
author
author
author
author
author
dc.contributor.author.fl_str_mv Alvarenga,Samuel Mazzinghy
Caixeta,Eveline Teixeira
Hufnagel,Bárbara
Thiebaut,Flávia
Maciel-Zambolim,Eunize
Zambolimand,Laércio
Sakiyama,Ney Sussumu
dc.subject.por.fl_str_mv Coffea
data mining
ESTs
genomics
in silico
bioinformatics
topic Coffea
data mining
ESTs
genomics
in silico
bioinformatics
description Sequences potentially associated with coffee resistance to diseases were identified by in silico analyses using the database of the Brazilian Coffee Genome Project (BCGP). Keywords corresponding to plant resistance mechanisms to pathogens identified in the literature were used as baits for data mining. Expressed sequence tags (ESTs) related to each of these keywords were identified with tools available in the BCGP bioinformatics platform. A total of 11,300 ESTs were mined. These ESTs were clustered and formed 979 EST-contigs with similarities to chitinases, kinases, cytochrome P450 and nucleotide binding site-leucine rich repeat (NBS-LRR) proteins, as well as with proteins related to disease resistance, pathogenesis, hypersensitivity response (HR) and plant defense responses to diseases. The 140 EST-contigs identified through the keyword NBS-LRR were classified according to function. This classification allowed association of the predicted products of EST-contigs with biological processes, including host defense and apoptosis, and with molecular functions such as nucleotide binding and signal transducer activity. Fisher's exact test was used to examine the significance of differences in contig expression between libraries representing the responses to biotic stress challenges and other libraries from the BCGP. This analysis revealed seven contigs highly similar to catalase, chitinase, protein with a BURP domain and unknown proteins. The involvement of these coffee proteins in plant responses to disease is discussed.
publishDate 2010
dc.date.none.fl_str_mv 2010-01-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572010000400031
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S1415-47572010000400031
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Genética
publisher.none.fl_str_mv Sociedade Brasileira de Genética
dc.source.none.fl_str_mv Genetics and Molecular Biology v.33 n.4 2010
reponame:Genetics and Molecular Biology
instname:Sociedade Brasileira de Genética (SBG)
instacron:SBG
instname_str Sociedade Brasileira de Genética (SBG)
instacron_str SBG
institution SBG
reponame_str Genetics and Molecular Biology
collection Genetics and Molecular Biology
repository.name.fl_str_mv Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)
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