High-Throughput Detection of Exonic Copy-Number Changes Using NimbleGen Oligonucleotide-Based CGH Array Technology

Genomic copy-number variations (CNV) involving large DNA segments are known to causemany genetic disorders. Depending on the changes, they are predicted to lead either to a decreased or an increased gene expression. However, the ability to detect smaller exonic copy-number variants has been explored. Here, we describe a new oligonucleotide-based CGH-array approach (developed in collaboration with NimbeleGene) for high-throughput detection of exonic deletions and duplications and its application to CFTR, sarcoglycans and DMD genes deletion/duplication analyses. In this work we show the successful development of an array-format containing 158 exons that collectively span 8 genes and its clinical application for the rapid screening of deletions and duplications in a diagnostic setting. We have analysed a series of more than 50 DNA samples from patients affected with CF, myopathies or sarcoglycanopathies and characterized copy-number changes that have been validated with other methods. Interestingly, even heterozygous deletions and duplications of only one exon, as well as mosaic deletion were detected by this CGH approach. Our results showed that the resolution is very high as abnormalities of about 1.5 and 2 kb could be detected. Since this approach is completely scalable, this new molecular tool will allow the screening of combinations of genes involved in a particular group of clinically and genetically heterogeneous disorders such as mental retardation, muscular dystrophies and brain malformations.

High-Throughput Approaches for DNA Methylation Profiling

Epigenetics plays a critical role in genome function both in health and disease. Of the many known epigenetic modifications, methylation at CpG dinucleotides is the only known biologically relevant epigenetic modification at the DNA level in humans and vertebrates in general. Knowledge of the methylation status of each of the ~28 million CpG sites (methylome) in the human genome is therefore of great importance for cellular identity, differentiation, development and, if perturbed, for disease aetiology.

I will present data from our efforts using sequencing- and array-based platforms for high-throughput DNA methylation profiling, discuss some of the lessons learnt and give an outlook on how the data may be used in an integrated approach – termed ‘reverse phenotyping’ – to analyse and better understand the (epi)genomics of phenotypic plasticity in health and disease.

Sequence Capture for Medical Sequencing

To identify causative mutations, and to define their role in the outcome of common diseases, we must have the ability to exploit common and rare SNPs and structural variation, across a wide diversity of human populations. Sequencing selected, functionally relevant, regions of the genome in these large population sets will provide us with comprehensive information about the frequency and nature of coding variants, and their connection to the pathogenesis of complex traits. The frequency of such variants is likely to be relatively low, preventing the use of current genome-wide association methods.

Target-specific microarray hybridisation coupled with next generation sequencing technology allows capture and sequencing of both dispersed short genome segments, encompassing individual gene exons, and single long segments, corresponding to entire gene loci, enabling cost-effective and systematic ascertainment of genetic variation. At the Wellcome Trust Sanger Institute we have been working closely with Roche NimbleGen to evaluate and develop this approach.