DNA Copy Number Profiling in Normal and Tumor Genomes

Abstract

For a biological sample, the DNA copy number of a genomic region is defined as the number of copies of the DNA in that region within the genome of the sample, relative to either a single control sample or a pool of population reference samples. Within the last decade, significant advances in microarray technology have enabled the genome-wide fine-scale measurement of DNA copy number in a highthroughput manner [5, 35, 39, 40, 47]. This enables systematic studies which can lead to a better understanding of the role of DNA copy number changes in human disease and in phenotypic variation in the human population. These high-throughput experiments produce large amounts of data that are rich in structure, motivating the development of new statistical methods for their analysis. This chapter reviews the computational and statistical problems that arise in DNA copy number data and surveys recent advances in their treatment. First, we review some terms and general concepts relating to DNA copy number. A copy number variant (CNV) is defined as a genomic region where the DNA copy number differs between two or more individuals from a population. CNVs that have so far been catalogued are by convention larger than 1 kilobase, although technologies based on high-throughput sequencing [45] and denser arrays [19] can detect shorter CNVs. Within the last five years, many studies [9, 10, 21, 30, 41] have shown that CNVs are a common type of genetic variation in the human population, with the fraction of the genome covered by CNVs estimated to be between 2% [10] and 15% [13]. Like single nucleotide polymorphisms (SNPs), variants in copy number segregate in a Mendelian fashion and contribute to phenotypic variation. Considering that they cover significantly more genomic territory in terms of base pairs and that they are more likely than SNPs to have a deleterious effect, CNVs are now routinely used alongside SNPs in genetic association studies.