Australasian Plant Pathology

, Volume 41, Issue 2, pp 113–124 | Cite as

A Bioinformatics Framework for plant pathologists to deliver global food security outcomes

Keynote address from the 18th Australasian Plant Pathology Society Conference 2011
  • Matthew I. BellgardEmail author
  • Stanley E. Bellgard


Bioinformatics applies information technologies to the allied fields of agriculture, horticulture, forestry, biotechnology, microbiology, plant physiology and molecular biology. Bioinformatics devises strategies for data management, analysis and integration tools that enable rapid scientific discovery and informed decision making. In plant pathology, the ‘contemporary’ application stage of bioinformatics is typically after a pathogen has been identified as a causative agent for a given plant host and subjected to biotechnological studies. In contrast, this paper contends that a broader bioinformatics framework should also integrate data/reports and interpretations/treatments as soon as potential pathogen incursions are encountered on a farm or forestry plot: capturing in real-time, elements of the incursion, sampling/survey, diagnostics, remedial treatments and field/laboratory work leading to the development of new cultivars or multiple disease resistance. Data currently captured/generated are managed in disparate formats: field/laboratory books, spreadsheets maintained independently by growers, extension officers and scientists, located in geographically disperse locations (e.g. farms, offices, institutions, archival repositories). Bioinformatics solutions provide the opportunity for a more coordinated electronic basis to manage/integrate this information. In this paper, a Bioinformatics Framework is proposed that enables improved cross-border, trans-discipline collaborative efforts that will enable more informed decision making by relevant stakeholders. In this way a shared biosecurity infrastructure can be developed that caters for sustainable global food and fibre production in the context of global climatic changes and increased opportunities for accidental disease incursions through the global plant trade.


Bioinformatics Plant pathology Global food safety Disease incursion 



MIB: acknowledges BioPlatforms Australia Pty Ltd for travel and bioinformatics infrastructure support funded through the Australian Federally funded National Collaborative Research Infrastructure Strategy. Insightful suggestions regarding remote sensing in assessing crop performance from Professor Mike Bevan at the John Innes Centre, UK. The Australasian Plant Pathology Society especially Professor Mark Sutherland for the invitation to give a Key Note address at the 18th Biennial Australasian Plant Pathology Society Conference, 26–29 April, 2011.

SEB: acknowledges Landcare Research Capability Fund CF 1011-94-01 for research and travel support.


  1. Adams I, Glover R, Monger WA, Mumford R, Jackeviciene E, Navalinskiene M, Samuitiene M, Boonham N (2009) Next generation sequencing and metagenomic analysis: a universal diagnostic tool in plant virology. Mol Plant Pathol 10(4):537–545PubMedCrossRefGoogle Scholar
  2. Agrios G (2004) Plant pathology, 5th edn. Elsevier Academic, The NetherlandsGoogle Scholar
  3. Alfano JR (2009) Roadmap for future research on plant pathogen effectors. Mol Plant Pathol 10(6):805–813PubMedCrossRefGoogle Scholar
  4. Alkan C, Sajjadian S, Eichler E (2011) Limitations of next-generation genome sequence assembly. Nat Meth 8(1):61–65CrossRefGoogle Scholar
  5. Barga R, Howe B, Beck D, Bowers S, Dobyns W, Haynes W, Higdon R, Howard C, Roth C, Stewart E, Welch D, Kolker E (2011) Bioinformatics and data-intensive scientific discovery in the beginning of the 21st century. OMICS 15(4):199–201PubMedCrossRefGoogle Scholar
  6. Barrero RA, Albertyn Z, Zhang B, Keeble-Gagnère G, Moolhuijzen P, Ikeo K, Tateno Y, Gojobori T, Guerrero FD, Lew-Tabor A, Bellgard MI (2011) Evolutionary conserved microRNAs are ubiquitously expressed compared to tick-specific miRNAs in the cattle tick rhipicephalus (boophilus) microplus. BMC Genom 12:328CrossRefGoogle Scholar
  7. Bellgard MI (2005) Bioinformatics from comparative genomic analysis through to integrated systems. In: Ruvinsky A, Marshall-Graves J (eds) Mammalian genomics, CABI Pub., pp 393–409Google Scholar
  8. Bellgard MI, Gojobori T (1999) Inferring the direction of evolutionary changes of genomic base composition. Trends Genet 15(7):254–256PubMedCrossRefGoogle Scholar
  9. Bellgard SE, Williams SE (2011) Response of mycorrhizal diversity to current climatic changes. Diversity 3:8–90CrossRefGoogle Scholar
  10. Bellgard MI, Hunter A, Kenworthy W (2003) Microarray analysis using bioinformatics analysis audit trails (BAATs). C R Biol 326(10–11):1083–1087PubMedCrossRefGoogle Scholar
  11. Bellgard M, Ye J, Gojobori T, Appels R (2004) The bioinformatics challenges in comparative analysis of cereal genomes-an overview. Funct Integr Genomics 4(1):1–11PubMedCrossRefGoogle Scholar
  12. Bellgard MI, Wanchanthuek P, La T, Ryan K, Moolhuijzen P, Albertyn Z, Shaban B, Motro Y, Dunn DS, Schibeci D, Hunter A, Barrero R, Phillips ND, Hampson DJ (2009) Genome sequence of the pathogenic intestinal spirochete brachyspira hyodysenteriae reveals adaptations to its lifestyle in the porcine large intestine. PLoS One 4(3):e4641, Epub Mar 5. PubMed PMID: 19262690PubMedCrossRefGoogle Scholar
  13. Benslimane D, Dustdar S, Sheth A (2008) Services mashups: the new generation of web applications. IEEE Internet Comput 12(5):13–15CrossRefGoogle Scholar
  14. Binslev L, Oliver RP, Johansen B (2002) In situ PCR for detection and identification of fungal species. Mycol Res 106(3):277–279CrossRefGoogle Scholar
  15. Brasier CM (2008) The biosecurity threat to the UK and global environment from international trade in plants. Plant Pathol 57(5):792–808CrossRefGoogle Scholar
  16. Breen J, Wicker T, Kong X, Zhang J, Ma W, Paux E, Feuillet C, Appels R, Bellgard MA (2010) Highly conserved gene island of three genes on chromosome 3B of hexaploid wheat: diverse gene function and genomic structure maintained in a tightly linked block. BMC Plant Biol 27(10):98CrossRefGoogle Scholar
  17. Chakraborty S, Luck J, Holloway G, Freeman A, Norton R, Garrett KA, Percy K, Hopkins A, Davis C, Karnosky D (2008) Impacts of global change on diseases of agricultural crops and forest trees. CAB Reviews: Perspectives in Agriculture, Veterinary Science, Nutrition and Natural Resources No. 054Google Scholar
  18. Chen J, Lan P, Tarr A, Yan YM, Francki M, Appels R, Ma W (2007) Matrix-assisted laser desorption/ionization time-of-flight based wheat gliadin protein peaks are useful molecular markers for wheat genetic study. Rapid Comm Mass Spectrom 21(17):2913–2917CrossRefGoogle Scholar
  19. Dunham MJ, Lewis EJ (2010) Yeast evolution and ecology meets genomics. EMBO Rep 12:8–10PubMedCrossRefGoogle Scholar
  20. Eckert JD, Sobral BW (2003) A life scientist’s gateway to distributed data management and computing: the PathPort/ToolBus framework. Omics 7:79–88CrossRefGoogle Scholar
  21. FAO (2009) Climate change and food security in the pacific–policy brief. Food and Agriculture Organisation of the United Nations, RomeGoogle Scholar
  22. Fletcher J, Bender C, Budowle B, Cobb WT, Gold SE, Ishimaru CA, Luster D, Melcher U, Murch R, Scherm H, Seem RC, Sherwood JL, Sobral BW, Tolin SA (2006) Plant pathogen forensics: capabilities, needs and recommendations. Microbiol Mol Biol Rev 70(2):450–471PubMedCrossRefGoogle Scholar
  23. Frank J, Menz M (2007) Multi-temporal wheat disease detection by multi-spectral remote sensing. Precis Agric 8:11–172Google Scholar
  24. Frow E, Ingram D, Powell W, Steer D, Vogel J, Yearly S (2009) The politics of plants. Food Sec 1:17–23CrossRefGoogle Scholar
  25. Fry WE, Goodwin SB, Dyer AT, Matuszak JM, Drenth A, Tooley PW, Sujkowski LS, Koh YJ, Cohen BA, Spielman LJ, Deahl KL, Inglis DA, Sandlan KP (1993) Historical and recent migrations of phytophthora infestans: chronology, pathways and implications. Plant Dis 77(7):653–661CrossRefGoogle Scholar
  26. Goble C, Stevens R (2008) State of the national in the data integration for bioinformatics. J Biomed Informat 41:687–693CrossRefGoogle Scholar
  27. Harman HM, Waipara NW, Winks CJ, Smith LA, Peterson PG, Jones A, Stanley J (2007) Distribution of bridal creeper rust (Puccinia myrsiphylli) in New Zealand. NZ J Pl Prot 60:320Google Scholar
  28. Kruger H, Stenekes N, Clarke R, Carr A (2010) Biosecurity engagement guidelines: practical advice for involving communities. Commonwealth of Australia, CanberraGoogle Scholar
  29. Lanoiselet V, Cother E, Ash G (2002) CLIMEX and DYMEX simulations of the potential occurrence of rice blast disease in south-eastern Australia. Australas Plant Pathol 31(1):1–7CrossRefGoogle Scholar
  30. Lazo GR, Chao S, Hummell DD, Edwards H, Crossman CC, Lui N, Matthews DE, Carrollo VL, Hane DL, You FM, Butler GE, Miller RE, Close TJ, Peng JH, Lapitan NLV, Gustafson JP, Qi LL, Echalier B, Gill BS, Dilbirligi M, Randhawa HS, Gill KS, Greene RA, Sorrells ME, Akhunov ED, Dvořák J, Linkiewicz AM, Dubkovsky J, Hossain KG, Kalavacharla V, Kianian SF, Mahmoud AA, Miftahudin, Ma X-F, Conley EJ, Anderson JA, Pathan MS, Nguyen HT, McGuire PE, Qualset CO, Anderson OD (2004) Development of an Expressed Sequence Tag (EST) for wheat (Triticum aestivum L.): EST generation, unigene analysis, probe selection and bioinformatics for a 16,000-locus bin-delineated map. Genetics 168:585–593PubMedCrossRefGoogle Scholar
  31. Lew A, Kurscheid S, Barrero R, Gondro C, Mollhuijzen P, Rodriguez Valle M, Morgan J, Covacin C, Bellgard M (2011) Gene expression evidence for off target effects caused by RNA interference-mediated gene silencing of Ubiquitin-63E in the cattle tick rhipicephalus microplus. Int J Parasitol 41(9):1001–1014Google Scholar
  32. Maffei HM, Arena JV (1993) Forest insect and disease risk and occurrence maps in GIS: application to integrated resource analysis. Gen tech rep NE. USDA Forest Service, NFES, NewtonGoogle Scholar
  33. Moolhuijzen P, Cakir M, Hunter A, Schibeci D, Macgregor A, Smith C, Francki M, Jones MG, Appels R, Bellgard M (2006) LegumeDB1 bioinformatics resource: comparative genomic analysis and novel cross-genera marker identification in lupin and pasture legume species. Genome 49(6):689–699, Erratum in: Genome 49(9): 1206–1207PubMedCrossRefGoogle Scholar
  34. Moolhuijzen PM, Lew-Tabor AE, Wlodek BM, Agüero FG, Comerci DJ, Ugalde RA, Sanchez DO, Appels R, Bellgard M (2009) Genomic analysis of campylobacter fetus subspecies: identification of candidate virulence determinants and diagnostic assay targets. BMC Microbiol 8(9):86, PubMed PMID: 19422718CrossRefGoogle Scholar
  35. Moolhuijzen P, Kulski JK, Dunn DS, Schibeci D, Barrero R, Gojobori T, Bellgard M (2010) The transcript repeat element: the human Alu sequence as a component of gene networks influencing cancer. Funct Integr Genomics 10(3):307–319CrossRefGoogle Scholar
  36. Nelson MN, Phan HT, Ellwood SR, Moolhuijzen PM, Hane J, Williams A, O'Lone CE, Fosu-Nyarko J, Scobie M, Cakir M, Jones MG, Bellgard M, Ksiazkiewicz M, Wolko B, Barker SJ, Oliver RP, Cowling WA (2006) The first gene-based map of lupinus angustifolius L.-location of domestication genes and conserved synteny with Medicago truncatula. Theor Appl Genet 113(2):225–238PubMedCrossRefGoogle Scholar
  37. Nelson MN, Moolhuijzen PM, Boersma JG, Chudy M, Lesniewska K, Bellgard M, Oliver RP, Swiecicki W, Wolko B, Cowling WA, Ellwood SR (2010) Aligning a new reference genetic map of lupinus angustifolius with the genome sequence of the model legume, lotus japonicus. DNA Res 17(2):73–83PubMedCrossRefGoogle Scholar
  38. Nilsson H (1995) Remote sensing and image analysis in plant pathology. Annu Rev Phytopathology 33:489–528CrossRefGoogle Scholar
  39. Nutter FW (2004) Post-introduction mapping of new and emerging agricultural pathogens in real-time using GPS and GIS technologies. Phytopathology Suppl 94:S130Google Scholar
  40. Patton MQ (1990) Qualitative evaluation and research methods, 2nd edn. Sage, Newbury ParkGoogle Scholar
  41. Pinstrup-Andersen P (2009) Food security: definition and measurement. Food Sec 1:5–7CrossRefGoogle Scholar
  42. Rhee SY, Dickerson J, Xu D (2006) Bioinformatics and its applications in plant biology. Annu Rev Plant Biol 57:335–360PubMedCrossRefGoogle Scholar
  43. Rizzo DM, Garbellotto M, Hansen EM (2005) Phytopthora ramorum: integrative research and management of an emerging pathogen in California and Oregon. Annu Rev Phytopathology 43(13):1–13Google Scholar
  44. Roessner U, Nahid A, Hunter A, Bellgard M (2011) Metabolomics—the combination of analytical chemistry, biology and informatics. In: Moo-Young M (ed-in-chief), Comprehensive Biotechnology (2nd ed), Vol 1, Academic Press, Burlington 447–459Google Scholar
  45. Schatz MC, Delcher AL, Salzberg SL (2010) Assembly of large genomes using second-generation sequencing. Genome Res 20:1165–1173PubMedCrossRefGoogle Scholar
  46. Spielmeyer W, Singh RP, McFadden H, Wellings CR, Huerta-Espino J, Kong X, Appels R, Lagudah ES (2008) Fine scale genetic and physical mapping using interstitial deletion mutants of Lr34/Yr18: a disease resistance locus effective against multiple pathogens in wheat. Theor Appl Genet 116(4):481–490PubMedCrossRefGoogle Scholar
  47. Sutherst RW, Matwald GF (1985) A computerised system for matching climates to in ecology. Agr Ecosyst Env 13:281–299CrossRefGoogle Scholar
  48. Taylor CF et al (2008) Promoting coherent minimum reporting guidelines for biological and biomedical investigations: the MIBBI project. Nat Biotechnol 26(8):889–889PubMedCrossRefGoogle Scholar
  49. Wang B, Dale ML, Kochman JK (1999) Studies on a pathogenicity assay for screening cotton germplasms for resistance to Fusarium oxysporum f.sp. vasinfectum in the glasshouse. Aust J Exp Agric 39:967–974CrossRefGoogle Scholar
  50. Wang LH, Zhao XL, He ZH, Ma W, Appels R, Peña RJ, Xia XC (2009) Characterization of low-molecular-weight glutenin subunit Glu-B3 genes and development of STS markers in common wheat (Triticum aestivum L.). Theor Appl Genet 118(3):525–539, Epub 2008 Nov 7PubMedCrossRefGoogle Scholar
  51. Whisson SC et al (2007) A translocation signal for delivery of oomycete effector proteins into host plant cells. Nature 450:115–118PubMedCrossRefGoogle Scholar
  52. White TJ, Bruns T, Lee S, Taylor J (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innes MA, Gelfand DH, Sninsky JJ, White TJ (eds) PCR protocols a guide to methods and applications. Academic, California, pp 315–322Google Scholar
  53. Wooley JC, Godzik A, Friedberg I (2010) A primer on metagenomics. PLoS Comput Biol 6(2):e1000667. doi: 10.1371/journal.pcbi.1000667 PubMedCrossRefGoogle Scholar

Copyright information

© Australasian Plant Pathology Society Inc. 2011

Authors and Affiliations

  1. 1.Centre for Comparative GenomicsMurdoch UniversityMurdochAustralia
  2. 2.Landcare ResearchAucklandNew Zealand

Personalised recommendations