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

Detalhes bibliográficos
Autor(a) principal: ALVARENGA, S. M.
Data de Publicação: 2010
Outros Autores: CAIXETA, E. T., HUFNAGEL, B., THIEBAUT, F., ZAMBOLIM, E. M., ZAMBOLIM, L., SAKIYAMA, N. S.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/880494
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. K
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spelling In silico identification of coffee genome expressed sequences potentially associated with resistance to diseases.ESTsData miningCoffeaGenomicsBioinformaticsSequences 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. KSAMUEL MAZZINGHY ALVARENGA, Universidade Federal de Viçosa; EVELINE TEIXEIRA CAIXETA, SAPC; BÁRBARA HUFNAGEL, Universidade Federal de Viçosa; FLÁVIA THIEBAUT, Universidade Federal de Viçosa; EUNIZE MACIEL ZAMBOLIM, Universidade Federal de Viçosa; LAÉRCIO ZAMBOLIM, Universidade Federal de Viçosa; NEY SUSSUMU SAKIYAMA, Universidade Federal de Viçosa.ALVARENGA, S. M.CAIXETA, E. T.HUFNAGEL, B.THIEBAUT, F.ZAMBOLIM, E. M.ZAMBOLIM, L.SAKIYAMA, N. S.2011-04-10T11:11:11Z2011-04-10T11:11:11Z2011-03-1120102011-07-07T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article795-806GENETICS AND MOLECULAR BIOLOGY, v. 33, n.4, p. 795-806. 2010.http://www.alice.cnptia.embrapa.br/alice/handle/doc/880494enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-08-15T22:34:33Zoai:www.alice.cnptia.embrapa.br:doc/880494Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-08-15T22:34:33falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-08-15T22:34:33Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)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, S. M.
ESTs
Data mining
Coffea
Genomics
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, S. M.
author_facet ALVARENGA, S. M.
CAIXETA, E. T.
HUFNAGEL, B.
THIEBAUT, F.
ZAMBOLIM, E. M.
ZAMBOLIM, L.
SAKIYAMA, N. S.
author_role author
author2 CAIXETA, E. T.
HUFNAGEL, B.
THIEBAUT, F.
ZAMBOLIM, E. M.
ZAMBOLIM, L.
SAKIYAMA, N. S.
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv SAMUEL MAZZINGHY ALVARENGA, Universidade Federal de Viçosa; EVELINE TEIXEIRA CAIXETA, SAPC; BÁRBARA HUFNAGEL, Universidade Federal de Viçosa; FLÁVIA THIEBAUT, Universidade Federal de Viçosa; EUNIZE MACIEL ZAMBOLIM, Universidade Federal de Viçosa; LAÉRCIO ZAMBOLIM, Universidade Federal de Viçosa; NEY SUSSUMU SAKIYAMA, Universidade Federal de Viçosa.
dc.contributor.author.fl_str_mv ALVARENGA, S. M.
CAIXETA, E. T.
HUFNAGEL, B.
THIEBAUT, F.
ZAMBOLIM, E. M.
ZAMBOLIM, L.
SAKIYAMA, N. S.
dc.subject.por.fl_str_mv ESTs
Data mining
Coffea
Genomics
Bioinformatics
topic ESTs
Data mining
Coffea
Genomics
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. K
publishDate 2010
dc.date.none.fl_str_mv 2010
2011-04-10T11:11:11Z
2011-04-10T11:11:11Z
2011-03-11
2011-07-07T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv GENETICS AND MOLECULAR BIOLOGY, v. 33, n.4, p. 795-806. 2010.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/880494
identifier_str_mv GENETICS AND MOLECULAR BIOLOGY, v. 33, n.4, p. 795-806. 2010.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/880494
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.format.none.fl_str_mv 795-806
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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