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Computational Biology in the Effector Group

Genome diagram
Sequencing, and analysis of sequences, is of increasing importance to plant pathology

Computational biology in the Effector Group encompasses identification and classification of effectors themselves, and the interactions of effectors with their hosts.

Sequencing is of increasing importance and accessibility to plant pathology in general. The recent availability of genomes for important plant pathogens (for example, Phytophthora spp.[1], [2]) and their hosts (for example, potato [3]) has enabled the identification of hundreds of effector proteins [4], and their counterpart R-genes, by sequence mining and comparative genomic approaches [5-7]. Having many effector protein sequences enables the identification of functional domains, and classification into groups[4,8,9]. Bioinformaticians in the Effector Group have made significant contributions to the identification and classification of effectors[1,4],[10,11], and have developed user-friendly pipelines for their rapid identification using Galaxy and other open-source tools.

Genome Diagram Understanding the dynamics of effector production is key to understanding the infection process, and Effector Group computational biologists have extensive experience in transcriptomic and regulatory analysis[12-15]. As pathogens act to modify their hosts’ behaviour using effectors, a systems-level appreciation of these interactions is necessary[16],[17]. This can best be achieved through computational and modelling approaches, another area of expertise within the group[18,19],[20].

References

1. Haas BJ, Kamoun S, Zody MC, Jiang RHY, Handsaker RE, et al. (2009) Genome sequence and analysis of the Irish potato famine pathogen Phytophthora infestans. Nature 461: 393–398. doi:10.1038/nature08358
2. Baxter L, Tripathy S, Ishaque N, Boot N, Cabral A, et al. (2010) Signatures of Adaptation to Obligate Biotrophy in the Hyaloperonospora arabidopsidis Genome. Science 330: 1549–1551. doi:10.1126/science.1195203
3. Potato Genome Sequencing Consortium, Xu X, Pan S, Cheng S, Zhang B, et al. (2011) Genome sequence and analysis of the tuber crop potato. Nature 475: 189–195. doi:10.1038/nature10158
4. Whisson SC, Boevink PC, Moleleki L, Avrova AO, Morales JG, et al. (2007) A translocation signal for delivery of oomycete effector proteins into host plant cells. Nature 450: 115–118. doi:10.1038/nature06203
5. Pritchard L, Liu H, Booth C, Douglas E, François P, et al. (2009) Microarray comparative genomic hybridisation analysis incorporating genomic organisation, and application to enterobacterial plant pathogens. PLoS Comp Biol 5: e1000473. doi:10.1371/journal.pcbi.1000473
6. Toth IK, Pritchard L, Birch PRJ (2006) Comparative genomics reveals what makes an enterobacterial plant pathogen. Annu Rev Phytopathol 44: 305–336. doi:10.1146/annurev.phyto.44.070505.143444
7. Pritchard L, White JA, Birch PRJ, Toth IK (2006) GenomeDiagram: a python package for the visualization of large-scale genomic data. Bioinformatics 22: 616–617. doi:10.1093/bioinformatics/btk021
8. Reynolds C, Damerell D, Jones S (2009) ProtorP: a protein-protein interaction analysis server. Bioinformatics 25: 413–414. doi:10.1093/bioinformatics/btn584
9. Murakami Y, Spriggs RV, Nakamura H, Jones S (2010) PiRaNhA: a server for the computational prediction of RNA-binding residues in protein sequences. Nucleic Acids Res 38: W412–W416. doi:10.1093/nar/gkq474
10. Kikuchi T, Cotton JA, Dalzell JJ, Hasegawa K, Kanzaki N, et al. (2011) Genomic Insights into the Origin of Parasitism in the Emerging Plant Pathogen Bursaphelenchus xylophilus. PLoS Pathog 7: e1002219. doi:10.1371/journal.ppat.1002219
11. Jones JT, Kumar A, Pylypenko LA, Thirugnanasambandam A, Castelli L, et al. (2009) Identification and functional characterization of effectors in expressed sequence tags from various life cycle stages of the potato cyst nematode Globodera pallida. Mol Plant Pathol 10: 815–828. doi:10.1111/j.1364-3703.2009.00585.x
12. Lin K, Husmeier D, Dondelinger F, Mayer CD, Liu H, et al. (n.d.) Reverse Engineering Gene Regulatory Networks Related to Quorum Sensing in the Plant Pathogen Pectobacterium atrosepticum. Methods in Molecular Biology: Computational Biology.Vol. 673. pp. 253–281. doi.org/10.1007/978-1-60761-842-3_17.
13. Liu H, Coulthurst SJ, Pritchard L, Hedley PE, Ravensdale M, et al. (2008) Quorum sensing coordinates brute force and stealth modes of infection in the plant pathogen Pectobacterium atrosepticum. PLoS Pathog 4: e1000093. doi:10.1371/journal.ppat.1000093
14. Cock PJA, Whitworth DE (2007) Evolution of prokaryotic two-component system signaling pathways: gene fusions and fissions. Mol Biol Evol 24: 2355–2357. doi:10.1093/molbev/msm170
15. Whitworth DE, Cock PJA (2009) Evolution of prokaryotic two-component systems: insights from comparative genomics. Amino Acids 37: 459–466. doi:10.1007/s00726-009-0259-2
16. Pritchard L, Birch P (2011) A systems biology perspective on plant–microbe interactions: Biochemical and structural targets of pathogen effectors. Plant Science 180: 584–603. doi:10.1016/j.plantsci.2010.12.008
17. Flower K, Hellen E, Newport MJ, Jones S, Sinclair AJ (2010) Evaluation of a Prediction Protocol to Identify Potential Targets of Epigenetic Reprogramming by the Cancer Associated Epstein Barr Virus. PLoS ONE 5: e9443. doi:10.1371/journal.pone.0009443.g007
18. Pritchard L, Kell DB (2002) Schemes of flux control in a model of Saccharomyces cerevisiae glycolysis. Eur J Biochem 269: 3894–3904.
19. Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, et al. (2009) Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics 25: 1422–1423. doi:10.1093/bioinformatics/btp163
20. Spriggs RV, Jones S (2009) RNA-binding residues in sequence space: Conservation and interaction patterns. Computational Biology and Chemistry 33: 397–403. doi:10.1016/j.compbiolchem.2009.07.01

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The James Hutton Research Institute is the result of the merger in April 2011 of MLURI and SCRI. This merger formed a new powerhouse for research into food, land use, and climate change.