Genome-wide algorithm for detecting CNV associations with diseases

SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). The quality of the inferences about copy number can be affected by many factors including batch effects, DNA sample preparation, signal processing, and analytical approach. Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP genotyping data. However, these algorithms lack specificity to detect small CNVs due to the high false positive rate when calling CNVs based on the intensity values. Association tests based on detected CNVs therefore lack power even if the CNVs affecting disease risk are common. In this research, by combining an existing Hidden Markov Model (HMM) and the logistic regression model, a new genome-wide logistic regression algorithm was developed to detect CNV associations with diseases. We showed that the new algorithm is more sensitive and can be more powerful in detecting CNV associations with diseases than an existing popular algorithm, especially when the CNV association signal is weak and a limited number of SNPs are located in the CNV.^

STUDIES OF THE MOLECULAR MECHANISMS OF CHROMOSOME ABERRATION FORMATION (DNA REPAIR, CROSSLINKS, MITOMYCIN C)

The objective of this research has been to study the molecular basis for chromosome aberration formation. Predicated on a variety of data, Mitomycin C (MMC)-induced DNA damage has been postulated to cause the formation of chromatid breaks (and gaps) by preventing the replication of regions of the genome prior to mitosis. The basic protocol for these experiments involved treating synchronized Hela cells in G(,1)-phase with a 1 (mu)g/ml dose of MMC for one hour. After removing the drug, cells were then allowed to progress to mitosis and were harvested for analysis by selective detachment. Utilizing the alkaline elution assay for DNA damage, evidence was obtained to support the conclusion that Hela cells can progress through S-phase into mitosis with intact DNA-DNA interstrand crosslinks. A higher level of crosslinking was observed in those cells remaining in interphase compared to those able to reach mitosis at the time of analysis. Dual radioisotope labeling experiments revealed that, at this dose, these crosslinks were associated to the same extent with both parental and newly replicated DNA. This finding was shown not to be the result of a two-step crosslink formation mechanism in which crosslink levels increase with time after drug treatment. It was also shown not to be an artefact of the double-labeling protocol. Using neutral CsCl density gradient ultracentrifugation of mitotic cells containing BrdU-labeled newly replicated DNA, control cells exhibited one major peak at a heavy/light density. However, MMC-treated cells had this same major peak at the heavy/light density, in addition to another minor peak at a density characteristic for light/light DNA. This was interpreted as indicating either: (1) that some parental DNA had not been replicated in the MMC treated sample or; (2) that a recombination repair mechanism was operational. To distinguish between these two possibilities, flow cytometric DNA fluorescence (i.e., DNA content) measurements of MMC-treated and control cells were made. These studies revealed that the mitotic cells that had been treated with MMC while in G(,1)-phase displayed a 10-20% lower DNA content than untreated control cells when measured under conditions that neutralize chromosome condensation effects (i.e., hypotonic treatment). These measurements were made under conditions in which the binding of the drug, MMC, was shown not to interfere with the stoichiometry of the ethidium bromide-mithramycin stain. At the chromosome level, differential staining techniques were used in an attempt to visualize unreplicated regions of the genome, but staining indicative of large unreplicated regions was not observed. These results are best explained by a recombinogenic mechanism. A model consistent with these results has been proposed.^

Decomposition of $\rm R\times C$ contingency table chi -square: Application to binned DNA fragment size data and population structure analysis

The purpose of this research is to develop a new statistical method to determine the minimum set of rows (R) in a R x C contingency table of discrete data that explains the dependence of observations. The statistical power of the method will be empirically determined by computer simulation to judge its efficiency over the presently existing methods. The method will be applied to data on DNA fragment length variation at six VNTR loci in over 72 populations from five major racial groups of human (total sample size is over 15,000 individuals; each sample having at least 50 individuals). DNA fragment lengths grouped in bins will form the basis of studying inter-population DNA variation within the racial groups are significant, will provide a rigorous re-binning procedure for forensic computation of DNA profile frequencies that takes into account intra-racial DNA variation among populations. ^