wp4: predicting risk via analysis of phytophthora genome evolution

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Work package 4 Predicting risk via analysis of Phytophthora genome evolution Paul Sharp, Leighton Pritchard, David Cooke, Sarah Green

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Page 1: WP4: Predicting risk via analysis of Phytophthora genome evolution

Work package 4

Predicting risk via analysis of Phytophthora genome evolution

Paul Sharp, Leighton Pritchard, David Cooke, Sarah Green

Page 2: WP4: Predicting risk via analysis of Phytophthora genome evolution

02/05/232

Phytophthora genome evolution

- Understanding UK Phytophthora diversity- Understanding origins of emerging Phytophthoras- Understanding genome evolution in Phytophthora

Adaptation to new hosts? Adaptation to woody hosts?

Hybridization? Horizontal gene transfer?

Page 3: WP4: Predicting risk via analysis of Phytophthora genome evolution

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Proposed approach (P. Sharp)

1. Look at the Phytophthora phylogeny

2. Classify species according to pathogenicity, woody-or-not host (and any other interesting phenotype?)

3. Categorise those species with, and those without genome data

4. Then identify three species that can be contrasted with existing genomes

Not easy because so many unknowns, particularly for newly described species

Which Phytophthoras to target sequence ?

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Clade 1 (P. andina, P. infestans, P. parasitica, P. cactorum)

Clade 2 (P. capsici, P. plurivora, P. multivora)

Clade 3 (P. pluvialis, P. taxon totara)

Clade 4 (P. palmivora)

Clade 5 (P. agathidicida)

Clade 6 (P. pinifolia)

Clade 7 (P. alni, P. sojae, P. pisi, P. rubi, P. fragariae, P. cambivora, P. cinnamomi)

Clade 8 (P. ramorum, P. lateralis, P. cryptogea, P. syringae, P. austrocedri)

Clade 9 0

Clade 10 (P. kernoviae)

Phytophthora genomes by clade

Page 5: WP4: Predicting risk via analysis of Phytophthora genome evolution

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Infect woody parts of trees;P. cactorum, P. plurivora, P. multivora, P. agathidicida, P. alni, P. cambivora, P. cinnamomi, P. ramorum, P. lateralis, P. austrocedri, P. kernoviae

Infect foliage of trees; P. pluvialis, P. taxon totara, P. palmivora, P. pinifolia, P. syringae

Infect herbaceous (non-woody) plants; P. andina, P. infestans, P. parasitica, P. capsici, P. sojae, P. pisi, P. rubi, P. fragariae, P. cryptogea

Phytophthora genomes by infection phenotype

Page 6: WP4: Predicting risk via analysis of Phytophthora genome evolution

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Narrow vs broad host range ? ie P. infestans vs P. cinnamomi

Aerial vs root infecting ?ie P. ramorum vs P. austrocedri

Strong vs weak pathogens ?ie all current genomes vs ?

Phytophthora genomes by other phenotype ?

So look for weak pathogen (as regarded to date) to contrast with already sequenced, economically important pathogens of woody hosts

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Clade 7 has for example P. alni, P. cinnamomi and P. cambivora already sequenced

P. europaea as a contrast ?

Proposed genomes to target sequence

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Clade 8c has P. ramorum and P. lateralis already sequenced

P. foliorum as a contrast ?

Proposed genomes to target sequence

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Clade 2 has P. multivora and P. plurivora already sequenced

P. multivesiculata as a contrast ?

Proposed genomes to target sequence

Page 10: WP4: Predicting risk via analysis of Phytophthora genome evolution

02/05/2310

OR novel clade 8d has P. austrocedri and P. syringae (genomes in progress)

P. obscura as a contrast ? (very closely related to P. austrocedri)

Proposed genomes to target sequence