title: Seeking genetic signature of radiosensitivity--a novel method for data analysis in case of small sample sizes.
abstract: BACKGROUND
  The identification of polymorphisms and/or genes responsible for an organism's radiosensitivity increases the knowledge about the cell cycle and the mechanism of the phenomena themselves, possibly providing the researchers with a better understanding of the process of carcinogenesis.
  
  
  OBJECTIVE
  The aim of the study was to develop a data analysis strategy capable of discovering the genetic background of radiosensitivity in the case of small sample size studies.
  
  
  RESULTS
  Among many indirect measures of radiosensitivity known, the level of radiation-induced chromosomal aberrations was used in the study. Mathematical modelling allowed the transformation of the yield-time curve of radiation-induced chromosomal aberrations into the exponential curve with limited number of parameters, while Gaussian mixture models applied to the distributions of these parameters provided the criteria for mouse strain classification. A detailed comparative analysis of genotypes between the obtained subpopulations of mice followed by functional validation provided a set of candidate polymorphisms that might be related to radiosensitivity. Among 1857 candidate relevant SNPs, that cluster in 28 genes, eight SNPs were detected nonsynonymous (nsSNP) on protein function. Two of them, rs48840878 (gene Msh3) and rs5144199 (gene Cc2d2a), were predicted as having increased probability of a deleterious effect. Additionally, rs48840878 is capable of disordering phosphorylation with 14 PKs. In silico analysis of candidate relevant SNP similarity score distribution among 60 CGD mouse strains allowed for the identification of SEA/GnJ and ZALENDE/EiJ mouse strains (95.26% and 86.53% genetic consistency respectively) as the most similar to radiosensitive subpopulation
  
  
  CONCLUSIONS
  A complete step-by-step strategy for seeking the genetic signature of radiosensitivity in the case of small sample size studies conducted on mouse models was proposed. It is shown that the strategy, which is a combination of mathematical modelling, statistical analysis and data mining methodology, allows for the discovery of candidate polymorphisms which might be responsible for radiosensitivity phenomena.
authors: Joanna
authors: J
authors: Zyla
authors: Paul
authors: P
authors: Finnon
authors: Robert
authors: R
authors: Bulman
authors: Simon
authors: S
authors: Bouffler
authors: Christophe
authors: C
authors: Badie
authors: Joanna
authors: J
authors: Polanska
mesh_terms: D000818:Animals; D002869:Chromosome Aberrations; D033481:Chromosomes, Mammalian / Q000235:genetics; D016000:Cluster Analysis; D005260:Female; D005787:Gene Frequency / Q000235:genetics; D056426:Genetic Loci / Q000235:genetics; D007700:Kinetics; D051379:Mice; D008957:Models, Genetic; D016011:Normal Distribution; D010766:Phosphorylation; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011494:Protein Kinases / Q000378:metabolism; D011836:Radiation Tolerance / Q000235:genetics*; D018401:Sample Size; D013223:Statistics as Topic / Q000379:methods*; D013997:Time Factors
chemical_list: D011494:Protein Kinases