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New insights into Phakopsora pachyrhizi infection based on transcriptome analysis in planta
Asian soybean rust (ASR) is one of the most destructive diseases affecting soybeans. The causative agent of ASR, the fungus Phakopsora pachyrhizi, presents characteristics that make it difficult to study in vitro, limiting our knowledge of plant-pathogen dynamics. Therefore, this work used leaf lesi...
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Published in: | Genetics and molecular biology 2018-07, Vol.41 (3), p.671-691 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Asian soybean rust (ASR) is one of the most destructive diseases affecting soybeans. The causative agent of ASR, the fungus Phakopsora pachyrhizi, presents characteristics that make it difficult to study in vitro, limiting our knowledge of plant-pathogen dynamics. Therefore, this work used leaf lesion laser microdissection associated with deep sequencing to determine the pathogen transcriptome during compatible and incompatible interactions with soybean. The 36,350 generated unisequences provided an overview of the main genes and biological pathways that were active in the fungus during the infection cycle. We also identified the most expressed transcripts, including sequences similar to other fungal virulence and signaling proteins. Enriched P. pachyrhizi transcripts in the resistant (PI561356) soybean genotype were related to extracellular matrix organization and metabolic signaling pathways and, among infection structures, in amino acid metabolism and intracellular transport. Unisequences were further grouped into gene families along predicted sequences from 15 other fungi and oomycetes, including rust fungi, allowing the identification of conserved multigenic families, as well as being specific to P. pachyrhizi. The results revealed important biological processes observed in P. pachyrhizi, contributing with information related to fungal biology and, consequently, a better understanding of ASR. |
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ISSN: | 1415-4757 1678-4685 1678-4685 |
DOI: | 10.1590/1678-4685-gmb-2017-0161 |