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In this chapter submicroscopic structural variation is described with a particular focus on copy number variation. There is a growing body of evidence to show that copy number variation is a common and important class of genetic variation. Recent technological advances for mapping the extent of copy number variation including microarray based comparative genomic hybridisation are described, together with the results of large scale surveys of copy number variation among healthy individuals. The consequences of such genetic diversity for gene expression are discussed. The important role of copy number variation in susceptibility to a variety of common multifactorial traits is described including infectious and autoimmune disease. Copy number variation is also discussed in relation to evidence for selection in relation to copy number of the gene encoding salivary amylase and a high starch diet, and in relation to drug metabolism with important consequences for pharmacogenomics.

Chromosomal aberrations are a common form of mutation in cancer. Copy number profiling of tumour-derived DNA has proven to be a productive starting point for identifying novel cancer-relevant genes and molecularly-defined tumour subclasses. Generating and interpreting copy number draws on intuitively simple ideas which are complicated when reduced to practice. This chapter presents a range of issues relevant to choosing a profiling platform, designing custom arrays, reducing noise, and identifying artefacts or population polymorphisms which can mimic cancer aberrations. Specific methods and examples highlight the problems of segmentation/change-point determination, multi-sample analysis, hierarchical clustering, and high-resolution mapping of intragenic copy number aberrations.

In this chapter the basis and nature of genomic disorders are described with examples including DiGeorge Syndrome, Williams-Beuren syndrome, Charcot Marie Tooth disease, Prader-Willi, and Angelman syndromes. The mechanisms whereby chromosomal rearrangements may lead to genomic disorders are described, the nature of reciprocal genomic disorders involving deletion or duplication of particular genomic regions and of genomic disorders involving parent of origin effects are also described. Mechanisms leading to genomic disorders through disruption of control of gene expression are also described. Diseases arising from terminal and subtelomeric deletions are highlighted together with the occurrence of inversions in both healthy individuals and those with diseases such as haemophilia A. The application of array comparative genome hybridisation (arrayCGH) techniques to define submicroscopic structural variation responsible for mental retardation is reviewed to illustrate the clinical utility and application of this approach.

Human genetic variation modulates susceptibility to infection with the human immunodeficiency virus (HIV) and progression to acquired immunodeficiency syndrome (AIDS) through diverse mechanisms including viral entry to cells, barriers to infection within cells, cytokines, cell mediated and innate immunity. Diversity in the chemokine coreceptor genes and their natural ligands are discussed including CCR5, CCR2, CXCR2, CCL5, and SDF-1. The impact of copy number variation in the chemokine gene CCL3L1, a natural ligand of CCR5, in susceptibility to HIV-1 and the rate of disease progression is described. The role of TRIM5 in blocking HIV-1 replication soon after viral entry into cells is also described together with the impact of retroviruses during primate evolution. The role of variation in human leucocyte antigens (HLA) and killer immunoglobulin-like receptors (KIRs) is reviewed including evidence for heterozygote advantage and the role of HLA in determining viral set point prior to onset of AIDS.

Copy number variation (CNV) accounts for roughly 12% of the human genome. Beside their inherent role in cancer development, CNVs have been reported to underlie susceptibility to complex diseases. Each variation may range from around 1000 nucleotides to less than 5 megabases. Array comparative genomic hybridization (aCGH) allows the identification of copy number alterations across genomes. The key computational challenge in analyzing CNVs using aCGH data is the detection of segment boundaries of copy number changes and inference of the copy number state for each segment. Markov random fields and, more specifically, conditional random fields provide a unified framework for data preprocessing, segmentation and copy number state decoding.