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1.
PLoS One ; 10(6): e0130328, 2015.
Artigo em Inglês | MEDLINE | ID: mdl-26091106

RESUMO

The Asian citrus psyllid (ACP) Diaphorina citri Kuwayama (Hemiptera: Psyllidae) is the insect vector of the fastidious bacterium Candidatus Liberibacter asiaticus (CLas), the causal agent of citrus greening disease, or Huanglongbing (HLB). The widespread invasiveness of the psyllid vector and HLB in citrus trees worldwide has underscored the need for non-traditional approaches to manage the disease. One tenable solution is through the deployment of RNA interference technology to silence protein-protein interactions essential for ACP-mediated CLas invasion and transmission. To identify psyllid interactor-bacterial effector combinations associated with psyllid-CLas interactions, cDNA libraries were constructed from CLas-infected and CLas-free ACP adults and nymphs, and analyzed for differential expression. Library assemblies comprised 24,039,255 reads and yielded 45,976 consensus contigs. They were annotated (UniProt), classified using Gene Ontology, and subjected to in silico expression analyses using the Transcriptome Computational Workbench (TCW) (http://www.sohomoptera.org/ACPPoP/). Functional-biological pathway interpretations were carried out using the Kyoto Encyclopedia of Genes and Genomes databases. Differentially expressed contigs in adults and/or nymphs represented genes and/or metabolic/pathogenesis pathways involved in adhesion, biofilm formation, development-related, immunity, nutrition, stress, and virulence. Notably, contigs involved in gene silencing and transposon-related responses were documented in a psyllid for the first time. This is the first comparative transcriptomic analysis of ACP adults and nymphs infected and uninfected with CLas. The results provide key initial insights into host-parasite interactions involving CLas effectors that contribute to invasion-virulence, and to host nutritional exploitation and immune-related responses that appear to be essential for successful ACP-mediated circulative, propagative CLas transmission.


Assuntos
Hemípteros/microbiologia , Insetos Vetores/microbiologia , Doenças das Plantas/microbiologia , Rhizobiaceae/fisiologia , Fenômenos Fisiológicos da Nutrição Animal/imunologia , Animais , Citrus/microbiologia , Citrus/parasitologia , Mapeamento de Sequências Contíguas , Elementos de DNA Transponíveis , Regulação da Expressão Gênica no Desenvolvimento/imunologia , Ontologia Genética , Genes de Insetos , Hemípteros/crescimento & desenvolvimento , Hemípteros/imunologia , Interações Hospedeiro-Patógeno , Imunidade Inata , Insetos Vetores/fisiologia , Anotação de Sequência Molecular , Ninfa/microbiologia , Ninfa/fisiologia , Transdução de Sinais , Transcriptoma
2.
Pathogens ; 3(4): 875-907, 2014 Nov 03.
Artigo em Inglês | MEDLINE | ID: mdl-25436509

RESUMO

The potato psyllid (PoP) Bactericera cockerelli (Sulc) and Asian citrus psyllid (ACP) Diaphorina citri Kuwayama are the insect vectors of the fastidious plant pathogen, Candidatus Liberibacter solanacearum (CLso) and Ca. L. asiaticus (CLas), respectively. CLso causes Zebra chip disease of potato and vein-greening in solanaceous species, whereas, CLas causes citrus greening disease. The reliance on insecticides for vector management to reduce pathogen transmission has increased interest in alternative approaches, including RNA interference to abate expression of genes essential for psyllid-mediated Ca. Liberibacter transmission. To identify genes with significantly altered expression at different life stages and conditions of CLso/CLas infection, cDNA libraries were constructed for CLso-infected and -uninfected PoP adults and nymphal instars. Illumina sequencing produced 199,081,451 reads that were assembled into 82,224 unique transcripts. PoP and the analogous transcripts from ACP adult and nymphs reported elsewhere were annotated, organized into functional gene groups using the Gene Ontology classification system, and analyzed for differential in silico expression. Expression profiles revealed vector life stage differences and differential gene expression associated with Liberibacter infection of the psyllid host, including invasion, immune system modulation, nutrition, and development.

3.
BMC Plant Biol ; 14: 46, 2014 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-24521476

RESUMO

BACKGROUND: The rhizome, the original stem of land plants, enables species to invade new territory and is a critical component of perenniality, especially in grasses. Red rice (Oryza longistaminata) is a perennial wild rice species with many valuable traits that could be used to improve cultivated rice cultivars, including rhizomatousness, disease resistance and drought tolerance. Despite these features, little is known about the molecular mechanisms that contribute to rhizome growth, development and function in this plant. RESULTS: We used an integrated approach to compare the transcriptome, proteome and metabolome of the rhizome to other tissues of red rice. 116 Gb of transcriptome sequence was obtained from various tissues and used to identify rhizome-specific and preferentially expressed genes, including transcription factors and hormone metabolism and stress response-related genes. Proteomics and metabolomics approaches identified 41 proteins and more than 100 primary metabolites and plant hormones with rhizome preferential accumulation. Of particular interest was the identification of a large number of gene transcripts from Magnaportha oryzae, the fungus that causes rice blast disease in cultivated rice, even though the red rice plants showed no sign of disease. CONCLUSIONS: A significant set of genes, proteins and metabolites appear to be specifically or preferentially expressed in the rhizome of O. longistaminata. The presence of M. oryzae gene transcripts at a high level in apparently healthy plants suggests that red rice is resistant to this pathogen, and may be able to provide genes to cultivated rice that will enable resistance to rice blast disease.


Assuntos
Oryza/metabolismo , Rizoma/metabolismo , Resistência à Doença/genética , Perfilação da Expressão Gênica , Regulação da Expressão Gênica de Plantas , Oryza/genética , Oryza/fisiologia , Rizoma/genética , Rizoma/fisiologia , Transcriptoma/genética
4.
PLoS One ; 8(7): e69401, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23874959

RESUMO

BACKGROUND: The analysis of transcriptome data involves many steps and various programs, along with organization of large amounts of data and results. Without a methodical approach for storage, analysis and query, the resulting ad hoc analysis can lead to human error, loss of data and results, inefficient use of time, and lack of verifiability, repeatability, and extensibility. METHODOLOGY: The Transcriptome Computational Workbench (TCW) provides Java graphical interfaces for methodical analysis for both single and comparative transcriptome data without the use of a reference genome (e.g. for non-model organisms). The singleTCW interface steps the user through importing transcript sequences (e.g. Illumina) or assembling long sequences (e.g. Sanger, 454, transcripts), annotating the sequences, and performing differential expression analysis using published statistical programs in R. The data, metadata, and results are stored in a MySQL database. The multiTCW interface builds a comparison database by importing sequence and annotation from one or more single TCW databases, executes the ESTscan program to translate the sequences into proteins, and then incorporates one or more clusterings, where the clustering options are to execute the orthoMCL program, compute transitive closure, or import clusters. Both singleTCW and multiTCW allow extensive query and display of the results, where singleTCW displays the alignment of annotation hits to transcript sequences, and multiTCW displays multiple transcript alignments with MUSCLE or pairwise alignments. The query programs can be executed on the desktop for fastest analysis, or from the web for sharing the results. CONCLUSION: It is now affordable to buy a multi-processor machine, and easy to install Java and MySQL. By simply downloading the TCW, the user can interactively analyze, query and view their data. The TCW allows in-depth data mining of the results, which can lead to a better understanding of the transcriptome. TCW is freely available from www.agcol.arizona.edu/software/tcw.


Assuntos
Biologia Computacional , Transcriptoma
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