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Título: | High-throughput genomic sequencing of cassava bacterial blight strains identifies conserved effectors to target for durable resistance. |
Autor(es): | Bart, Rebecca Cohn, Megan Kassen, Andrew McCallumb, Emily J. Shybut, Mikel Petriello, Annalise Krasileva, Ksenia Dahlbeck, Douglas Medina, Cesar Alicai, Titus Kumar, Lava Moreira, Leandro Marcio Neto, Júlio Rodrigues Verdier, Valerie Santana, María Angélica Kositcharoenkul, Nuttima Vanderschuren, Hervé Gruissem, Wilhelm Bernal, Adriana Staskawicz, Brian J. |
Palavras-chave: | Innate immunity Type three effectors Next-generation sequencing |
Data do documento: | 2012 |
Referência: | BART, R. et al. High-throughput genomic sequencing of cassava bacterial blight strains identifies conserved effectors to target for durable resistance. Proceedings of the National Academy of Sciences of the United States of America, v. 109, p. E1972-E1979, 2012. Disponível em: <http://www.pnas.org/content/109/28/E1972.long>. Acesso em: 19 fev. 2017. |
Resumo: | Cassava bacterial blight (CBB), incited by Xanthomonas axonopodis pv. manihotis (Xam), is the most important bacterial disease of cassava, a staple food source for millions of people in developing countries. Here we present a widely applicable strategy for elucidating the virulence components of a pathogen population. We report Illumina-based draft genomes for 65 Xam strains and deduce the phylogenetic relatedness of Xam across the areas where cassava is grown. Using an extensive database of effector proteins from animal and plant pathogens, we identify the effector repertoire for each sequenced strain and use a comparative sequence analysis to deduce the least polymorphic of the conserved effectors. These highly conserved effectors have been maintained over 11 countries, three continents, and 70 y of evolution and as such represent ideal targets for developing resistance strategies. |
URI: | http://www.repositorio.ufop.br/handle/123456789/7959 |
Link para o artigo: | http://www.pnas.org/content/109/28/E1972.long |
DOI: | https://doi.org/10.1073/pnas.1208003109 |
ISSN: | 1091-6490 |
Aparece nas coleções: | DECBI - Artigos publicados em periódicos |
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Arquivo | Descrição | Tamanho | Formato | |
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ARTIGO_HighThroughputGenomic.pdf Restricted Access | 2,97 MB | Adobe PDF | Visualizar/Abrir |
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