Modelling of Genetic Interactions in GWAS Reveals More Complex Relations between Genotype and Phenotype

Joanna Zyla, Christophe Badie, Ghazi Alsbeih, Joanna Polanska

Abstract

The aim of this work is to present the complete methodology useful in GWAS analysis with small sample size, where comprehension of interaction between the genotype and phenotype is a main issue. By including all possible models of interaction into the process of model building, we were able to significantly increase the number of candidate polymorphisms and decrease the false discovery ratio.

References

  1. Bergoni, J. and Tribondeau, L. (1906). De quelques rsultats de la radiotherapie et essai de fixation d'une technique rationnelle. Comptes-Rendus des Sances de l'Acadmie des Sciences, 43:983-985.
  2. Burnet, N., Elliott, R., Dunning, A., and West, C. (2006). Radiosensitivity, radiogenomics and rapper. Clinical Oncology, 18(7):525-528.
  3. Bush, W. and Moore, J. (2012). Chapter 11: Genome-wide association studies. PLOS Comput Biol., 8(12).
  4. Chung, S., Low, S., Zembutsu, H., Takahashi, A., ans M. Sasa, M. K., and Nakamura, Y. (2013). A genome-wide association study of chemotherapyinduced alopecia in breast cancer patients. Breast Cancer Res., 15(5):R81.
  5. Finnon, P., Robertson, N., Dziwura, D., Raffy, C., Zhang, W., Ainsbury, L., Kaprio, J., Badie, C., and Bouffler, S. (2008). Evidence for significant heritability of apoptotic and cell cycle responses to ionising radiation. Hum Genet., 123(5):485-493.
  6. Hindorff, L., Sethupathy, P., Junkins, H., Ramos, E., Mehta, J., Collins, F., and Manolio, T. (2009). Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. PNAS, 106(23):9362-9367.
  7. Kamboh, M., Demirci, F., Wang, X., Minster, R., Carrasquillo, M., Pankratz, V., Younkin, S., Saykin, A., Jun, G., Baldwin, C., Logue, M., Buros, J., Farrer, L., Pericak-Vance, M., Haines, J., Sweet, R., Ganguli, M., Feingold, E., Dekosky, S., Lopez, O., and Barmada, M. (2012). Genome-wide association study of alzheimer's disease. Transl Psychiatry., 15:2:e117.
  8. Klein, R., Zeiss, C., Chew, E., Tsai, J., Sackler, R., Haynes, C., Henning, A., SanGiovanni, J., Mane, S., Mayne, S., Bracken, M., Ferris, F., Ott, J., Barnstable, C., and Hoh, J. (2005). Complement factor h polymorphism in age-related macular degeneration. Science, 308(5720):385-389.
  9. Lewis, C. (2002). Genetic association studies: design, analysis and interpretation. Brief Bioinform., 3(2):146- 153.
  10. Lin, A., Wang, R., Ahn, S., Park, C., and Smith, D. (2005). A genome-wide map of human genetic interactions inferred from radiation hybrid genotypes. Genome Res, 20(8):1122-1132.
  11. Lin, W. and Lee, W. (2012). Improving power of genomewide association studies with weighted false discovery rate control and prioritized subset analysis. PLOS One., 7(4).
  12. NCI (2012). Radiation Therapy and You. National Institute of Health publiaction No. 12-7157.
  13. Niu, N., Qin, Y., Fridley, B., Hou, J., Kalari, K., Zhu, M., Wu, T., Jenkins, G., Batzler, A., and Wang, L. (2010). Radiation pharmacogenomics: a genome-wide association approach to identify radiation response biomarkers using human lymphoblastoid cell lines. Genome Res, 20(11):1482-1492.
  14. O'Donovan, M., Freemantle, M., Hull, G., Bell, D., Arlett, C., and Cole, J. (1995). Extended-term cultures of human t-lymphocytes: a practical alternative to primary human lymphocytes for use in genotoxicity testing. Mutagenesis., 10(3):189-201.
  15. Pahl, R. and Schafer, H. (2010). Permory: an ld-exploiting permutation test algorithm for powerful genome-wide association testing. Bioinformatics, 26(17):2093- 2100.
  16. Ramensky, V., Bork, P., and Sunyaev, S. (2002). Human nonsynonymous snps: server and survey. Nucleic Acids Research, 30(17):3894-3900.
  17. Roberts, S., Spreadborough, A., Bulman, B., Barber, J., Evans, D., and Scott, D. (1999). Heritability of cellular radiosensitivity: a marker of low-penetrance predisposition genes in breast cancer? American Journal of Human Genetics, 65(3):784-794.
  18. Strachan, T. and Read, A. (1999). Human Molecular Genetics. Wiley-Liss, New York, 2nd edition.
  19. Taneja, N., Davis, M., Choy, J., Beckett, M., Singh, R., Kron, S., and Weichselbaum, R. (2004). Histone h2ax phosphorylation as a predictor of radiosensitivity and target for radiotherapy. J Biol Chem., 279(3):2273- 2280.
  20. UNSCEAR (2010). Sources and effects of ionizing radiation. United Nations Publication, New York.
  21. Wrixon, A., Barraclough, I., Clark, M., Ford, J., DiesnerKuepfer, A., and Blann, B. (2004). Radiation, People and the Enviroment. International Atomic Energy Agency, Austria.
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Paper Citation


in Harvard Style

Zyla J., Badie C., Alsbeih G. and Polanska J. (2014). Modelling of Genetic Interactions in GWAS Reveals More Complex Relations between Genotype and Phenotype . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014) ISBN 978-989-758-012-3, pages 204-208. DOI: 10.5220/0004807402040208


in Bibtex Style

@conference{bioinformatics14,
author={Joanna Zyla and Christophe Badie and Ghazi Alsbeih and Joanna Polanska},
title={Modelling of Genetic Interactions in GWAS Reveals More Complex Relations between Genotype and Phenotype},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014)},
year={2014},
pages={204-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004807402040208},
isbn={978-989-758-012-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2014)
TI - Modelling of Genetic Interactions in GWAS Reveals More Complex Relations between Genotype and Phenotype
SN - 978-989-758-012-3
AU - Zyla J.
AU - Badie C.
AU - Alsbeih G.
AU - Polanska J.
PY - 2014
SP - 204
EP - 208
DO - 10.5220/0004807402040208