Integrated detection and population-genetic analysis of SNPs and copy number variation

Genetic mapping in human disease

Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead.

Ultraconserved elements: analyses of dosage sensitivity, motifs and boundaries

Ultraconserved elements (UCEs) are sequences that are identical between reference genomes of distantly related species. As they are under negative selection and enriched near or in specific classes of genes, one explanation for their ultraconservation may be their involvement in important functions. Indeed, many UCEs can drive tissue-specific gene expression. We have demonstrated that nonexonic UCEs are depleted among segmental duplications (SDs) and copy number variants (CNVs) and proposed that their ultraconservation may reflect a mechanism of copy counting via comparison. Here, we report that nonexonic UCEs are also depleted among 10 of 11 recent genomewide data sets of human CNVs, including 3 obtained with strategies permitting greater precision in determining the extents of CNVs. We further present observations suggesting that nonexonic UCEs per se may contribute to this depletion and that their apparent dosage sensitivity was in effect when they became fixed in the last common ancestor of mammals, birds, and reptiles, consistent with dosage sensitivity contributing to ultraconservation. Finally, in searching for the mechanism(s) underlying the function of nonexonic UCEs, we have found that they are enriched in TAATTA, which is also the recognition sequence for the homeodomain DNA-binding module, and bounded by a change in A + T frequency.

Autoimmune diseases: insights from genome-wide association studies

Autoimmune diseases occur when an individual's own immune system attacks and destroys his or her healthy cells and tissues. Although it is clear that environmental stimuli can predispose someone to develop autoimmune diseases, twin- and family-based studies have shown that genetic factors also play an important role in modifying disease risk. Because many of these diseases are relatively common (prevalence in European-derived populations: 0.01-1%) and exhibit a complex mode of inheritance, many DNA sequence variants with modest effect on disease risk contribute to the genetic burden. Recently, the completion of the HapMap project, together with the development of new genotyping technologies, has given human geneticists the tools necessary to comprehensively, and in an unbiased manner, search our genome for DNA polymorphisms associated with many autoimmune diseases. Here we review recent progress made in the identification of genetic risk factors for celiac disease, Crohn's disease, multiple sclerosis, rheumatoid arthritis, systemic lupus erythematosus and type-1 diabetes using genome-wide association studies (GWAS). Strikingly, GWAS have increased the number of genetic risk variants associated with these autoimmune diseases from 15 before 2006 to 68 now. We summarize what this new genetic landscape teaches us in terms of the pathogenesis of these diseases, and highlight some of the outstanding challenges ahead. Finally, we open a discussion on ways to best maximize the impact of these genetic discoveries where it matters the most, that is for autoimmune disease patients.

Integrated genotype calling and association analysis of SNPs, common copy number polymorphisms and rare CNVs

Accurate and complete measurement of single nucleotide (SNP) and copy number (CNV) variants, both common and rare, will be required to understand the role of genetic variation in disease. We present Birdsuite, a four-stage analytical framework instantiated in software for deriving integrated and mutually consistent copy number and SNP genotypes. The method sequentially assigns copy number across regions of common copy number polymorphisms (CNPs), calls genotypes of SNPs, identifies rare CNVs via a hidden Markov model (HMM), and generates an integrated sequence and copy number genotype at every locus (for example, including genotypes such as A-null, AAB and BBB in addition to AA, AB and BB calls). Such genotypes more accurately depict the underlying sequence of each individual, reducing the rate of apparent mendelian inconsistencies. The Birdsuite software is applied here to data from the Affymetrix SNP 6.0 array. Additionally, we describe a method, implemented in PLINK, to utilize these combined SNP and CNV genotypes for association testing with a phenotype.

Rare chromosomal deletions and duplications increase risk of schizophrenia

Schizophrenia is a severe mental disorder marked by hallucinations, delusions, cognitive deficits and apathy, with a heritability estimated at 73-90% (ref. 1). Inheritance patterns are complex, and the number and type of genetic variants involved are not understood. Copy number variants (CNVs) have been identified in individual patients with schizophrenia and also in neurodevelopmental disorders, but large-scale genome-wide surveys have not been performed. Here we report a genome-wide survey of rare CNVs in 3,391 patients with schizophrenia and 3,181 ancestrally matched controls, using high-density microarrays. For CNVs that were observed in less than 1% of the sample and were more than 100 kilobases in length, the total burden is increased 1.15-fold in patients with schizophrenia in comparison with controls. This effect was more pronounced for rarer, single-occurrence CNVs and for those that involved genes as opposed to those that did not. As expected, deletions were found within the region critical for velo-cardio-facial syndrome, which includes psychotic symptoms in 30% of patients. Associations with schizophrenia were also found for large deletions on chromosome 15q13.3 and 1q21.1. These associations have not previously been reported, and they remained significant after genome-wide correction. Our results provide strong support for a model of schizophrenia pathogenesis that includes the effects of multiple rare structural variants, both genome-wide and at specific loci.