Andolfo, Giuseppe (2014) Exploration of the Effector Triggered Immunity (ETI) in S. lycopersicum using genomic approaches. [Tesi di dottorato]

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Exploration of the Effector Triggered Immunity (ETI) in S. lycopersicum using genomic approaches
Autori:
AutoreEmail
Andolfo, Giuseppegiuseppeandolfo@hotmail.com
Data: 8 Maggio 2014
Numero di pagine: 122
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Agraria
Scuola di dottorato: Scienze agrarie e agro-alimentari
Dottorato: Agrobiologia e agrochimica
Ciclo di dottorato: 26
Coordinatore del Corso di dottorato:
nomeemail
Carputo, Domenicocarputo@unina.it
Tutor:
nomeemail
Ercolano, Maria Raffaella[non definito]
Data: 8 Maggio 2014
Numero di pagine: 122
Parole chiave: Duplication events; evolution history; orthology; arrangement of R loci; physical map; predicted proteins; genomic approach; Fol, ToMV; incompatible interaction; gene enrichment analysis; transcript mapping; RenSeq; NB-LRR; cDNA; gene model; disease resistance; paralogous; plant breeding; Solanum lycopersicum; Solanum pimpinellifolium; Arabidopsis thaliana.
Settori scientifico-disciplinari del MIUR: Area 07 - Scienze agrarie e veterinarie > AGR/07 - Genetica agraria
Aree tematiche (7° programma Quadro): BIOTECNOLOGIE, PRODOTTI ALIMENTARI E AGRICOLTURA > Scienze della vita, biotecnologia e biochimica per prodotti e processi non-alimentari sostenibili
Depositato il: 08 Apr 2014 09:07
Ultima modifica: 15 Lug 2015 01:01
URI: http://www.fedoa.unina.it/id/eprint/9699

Abstract

In order to investigate the genome-wide spatial arrangement of R loci, a complete catalogue of tomato (Solanum lycopersicum) and potato (Solanum tuberosum) nucleotide-binding site (NBS) NBS, receptor-like protein (RLP) and receptor-like kinase (RLK) gene repertories was generated. Candidate pathogen recognition genes were characterized with respect to structural diversity, phylogenetic relationships and chromosomal distribution. NBS genes frequently occur in clusters of related gene copies that also include RLP or RLK genes. This scenario is compatible with the existence of selective pressures optimizing coordinated transcription. A number of duplication events associated with lineage-specific evolution were discovered. These findings suggest that different evolutionary mechanisms shaped pathogen recognition gene cluster architecture to expand and to modulate the defense repertoire. Analysis of pathogen recognition gene clusters associated with documented resistance function allowed the identification of adaptive divergence events and the reconstruction of the evolution history of these loci. Most candidate pathogen recognition gene orthologues were distributed at less than perfectly matching positions, suggesting an ongoing lineage-specific rearrangement. Taken together, these findings have implications for improved understanding of the mechanisms of molecular adaptive selection at Solanum R loci. An updated Solanaceae RenSeq bait library to reannotate the full NB-LRR gene complement in tomato (Solanum lycopersicum) Heinz 1706 and to identify novel sequences that were not picked up by the semi-automated gene prediction software. Using 250-bp MiSeq reads after resistance gene enrichment sequencing (RenSeq) on genomic DNA of Heinz 1706, we identified 105 novel NB-LRR sequences. Reannotation included the splitting of gene models, combination of partial genes to a longer sequence and closing of assembly gaps. Within the draft S. pimpinellifolium LA1589 genome, RenSeq enabled the annotation of 355 NB-LRR genes. Phylogenetic analyses show a high conservation of all NB-LRR classes between Heinz 1706, LA1589 and the potato clone DM, suggesting that all sub-families were already present in the last common ancestor. A phylogenetic comparison to the Arabidopsis thaliana NB-LRR complement verifies the high conservation of the more ancient CCRPW8-type NB-LRRs. Use of RenSeq on cDNA from uninfected and late blight-infected tomato leaves allows the avoidance of sequence analysis of non-expressed paralogues. cDNA RenSeq enables for the first time next-generation sequencing approaches targeted to this very low-expressed gene family without the need for normalization. Moreover in this thesis, we show that information on the tomato genome can be used predictively to link resistance function with specific sequences. An integrated genomic approach for identifying new resistance (R) gene candidates was developed. An R gene functional map was created by co-localization of candidate pathogen recognition genes and anchoring molecular markers associated with resistance phenotypes. In-depth characterization of the identified pathogen recognition genes was performed. Such methodology can help to better direct positional cloning, reducing the amount of effort required to identify a functional gene. The resulting candidate loci selected are available for exploiting their specific function. Finally, in order to identify a set of genes of interest in tomato plants infected with F. oxysporum f. sp. lycopersici (Fol) and Tomato Mosaic Virus (ToMV) a transcriptional analysis was performed. Differentially expressed tomato genes upon inoculation with Fol and ToMV were identified at 2 days post-inoculation. A large overlap was found in differentially expressed genes throughout the two incompatible interactions. However, GO enrichment analysis evidenced specific categories in both interactions. Response to ToMV seems more multifaceted, since more than 70 specific categories were enriched versus the 30 detected in Fol interaction. In particular, virus stimulated the production of an invertase enzyme that is able to redirect the flux of carbohydrates, whereas Fol induced homeostatic responses that prevent the attempt of fungus to kill cells. Genomic mapping of transcripts suggested that specific genomic regions are involved in pathogen resistance response. Coordinated R gene machinery could have an important role in prompt the response, since the 60% of pathogen receptor genes were differentially expressed during both interactions. Assessment of gene expression patterns could help for tracing a genomic model of R gene mediated resistance response.

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