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Open Access Highly Accessed Research article

Sequence mining and transcript profiling to explore cyst nematode parasitism

Axel A Elling123, Makedonka Mitreva4, Xiaowu Gai5, John Martin4, Justin Recknor67, Eric L Davis8, Richard S Hussey9, Dan Nettleton6, James P McCarter104 and Thomas J Baum12*

Author Affiliations

1 Interdepartmental Genetics Program, Iowa State University, Ames, IA 50011, USA

2 Department of Plant Pathology, Iowa State University, Ames, IA 50011, USA

3 Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520, USA

4 Genome Sequencing Center, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA

5 Center for Biomedical Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA

6 Department of Statistics, Iowa State University, Ames, IA 50011, USA

7 Eli Lilly and Company, Lilly Research Laboratories, Greenfield, IN 46140, USA

8 Department of Plant Pathology, North Carolina State University, Raleigh, NC 27695, USA

9 Department of Plant Pathology, University of Georgia, Athens, GA 30602, USA

10 Divergence Inc., St. Louis, MO 63141, USA

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BMC Genomics 2009, 10:58  doi:10.1186/1471-2164-10-58

Published: 30 January 2009

Abstract

Background

Cyst nematodes are devastating plant parasites that become sedentary within plant roots and induce the transformation of normal plant cells into elaborate feeding cells with the help of secreted effectors, the parasitism proteins. These proteins are the translation products of parasitism genes and are secreted molecular tools that allow cyst nematodes to infect plants.

Results

We present here the expression patterns of all previously described parasitism genes of the soybean cyst nematode, Heterodera glycines, in all major life stages except the adult male. These insights were gained by analyzing our gene expression dataset from experiments using the Affymetrix Soybean Genome Array GeneChip, which contains probeset sequences for 6,860 genes derived from preparasitic and parasitic H. glycines life stages. Targeting the identification of additional H. glycines parasitism-associated genes, we isolated 633 genes encoding secretory proteins using algorithms to predict secretory signal peptides. Furthermore, because some of the known H. glycines parasitism proteins have strongest similarity to proteins of plants and microbes, we searched for predicted protein sequences that showed their highest similarities to plant or microbial proteins and identified 156 H. glycines genes, some of which also contained a signal peptide. Analyses of the expression profiles of these genes allowed the formulation of hypotheses about potential roles in parasitism. This is the first study combining sequence analyses of a substantial EST dataset with microarray expression data of all major life stages (except adult males) for the identification and characterization of putative parasitism-associated proteins in any parasitic nematode.

Conclusion

We have established an expression atlas for all known H. glycines parasitism genes. Furthermore, in an effort to identify additional H. glycines genes with putative functions in parasitism, we have reduced the currently known 6,860 H. glycines genes to a pool of 788 most promising candidate genes (including known parasitism genes) and documented their expression profiles. Using our approach to pre-select genes likely involved in parasitism now allows detailed functional analyses in a manner not feasible for larger numbers of genes. The generation of the candidate pool described here is an important enabling advance because it will significantly facilitate the unraveling of fascinating plant-animal interactions and deliver knowledge that can be transferred to other pathogen-host systems. Ultimately, the exploration of true parasitism genes verified from the gene pool delineated here will identify weaknesses in the nematode life cycle that can be exploited by novel anti-nematode efforts.