Next month in San Diego, CHI will present “Now Generation Sequencing” in which discussions about targeted resequencing will be front and center. This mixture of molecular biology and sophisticated computer analysis hones in on genomic regions of interest, interrogating multiple genetic sites. Enabling the detection of rare mutations and hard-to-reach corners of the genome, it takes advantage of low sample-input requirements. Moreover, these strategies allow areas of interest to be identified through genome-wide association studies while sequencing genes and candidate regions.
Using next-generation sequencing for clinical diagnostic purposes offers unique challenges due to the complexity of the technology and data analysis issues. Presentations at “Now Generation Sequencing” will discuss how to streamline technical processes and bioinformatics analyses to rapidly move this technology into the clinic.
The identification of the genes for extremely rare disorders was extremely difficult until the development of targeted approaches for sequencing partial components of the entire genome. Classic human gene mapping studies required large pedigrees of many affected families in which the association between the disease and the candidate gene could be narrowed down through its linkage with such markers as single nucleotide polymorphisms and microsatellites.
Today the availability of powerful computer analysis combined with automated sequencing technology has allowed a brute-force approach to identification of the genetic region of interest. The large size of the entire human genome, however, requires a method of selective sequencing. Since the exome or coding regions comprise only 30 megabases, or 1% of the total human genetic makeup, a second-generation approach targeting this select class would make the task manageable and more cost-friendly.
Sarah Ng, a graduate student in genome sciences at the University of Washington, has been involved in a project to demonstrate proof of principle for targeted capture and massive parallel sequencing, using the Freeman-Sheldon Syndrome as a model. Success in the endeavor spurred the team on to nail down the location of the Miller Syndrome, a previously unmapped disorder.
“For the first time, we have pursued candidate gene identification through exome sequencing of a small number of unrelated affected individuals,” says Ng.
The team’s approach requires the enrichment of exomes by hybridization of DNA from shotgun libraries to microarrays with synthesized DNA probes complementary to the human exome sequence. In this project, four libraries, each consisting of broken-up genomic DNA fragments from a subject with the condition, were hybridized to two custom 244 K Agilent microarrays, and the captured exomic DNA from the affected individuals was entirely sequenced on the Illumina Genome Analyzer platform.
This data revealed a large number of variants in each individual, which could be subjected to additional filtering techniques to identify the sequences responsible for the disease. The candidate gene, which codes for an enzyme in pyrimidine biosynthesis, is referred to as DHODH. Mutations in this gene were then identified in a number of unrelated Miller Syndrome families.
Prior to the work of the University of Washington team, it was unclear whether Miller Syndrome was dominant or recessive since large pedigrees had never been observed. This unknown, combined with the decreased reproductive ability of individuals with this condition, greatly restricted the options available for its analysis.
“We have demonstrated the power, efficiency, and cost-effectiveness of this strategy,” says Ng. “This approach is likely to become a standard tool for the discovery of genes underlying rare monogenic disorders.”
Therapy for genetically based diseases invariably requires a solid understanding of the molecular basis of the condition—phenylketonuria being a classic example. This knowledge can now be put to use, although the rareness of the condition may stand in the way of efforts to develop a workable treatment.
febit biomed is using its HybSelect™ automated technology to investigate new cancer markers as well as other issues pertaining to the isolation of disease-related genes.
febit’s targeted resequencing technology is a microarray-based sequence capture strategy in which the entire genome is scaled down to manageable portions that can be used in focused investigations. It consists of three steps—hybridization of a genomic library to a Geniom biochip, washing and elution, and finally sequencing and analysis. Working with 10% of the genome (300 million bases) the company scales down further to focus on clinically relevant regions. “Currently our main interest is in the area of oncogenes and oncology,” says Peer Stähler, CSO.
febit uses barcoding for the indexing of samples. This is accomplished by adding identifying base sequences onto the PCR primers, which allows samples to be identified and followed, making automation of sequencing possible.
“We are currently conducting a large-scale analysis of cancer-related genes,” explains Stähler. “This includes the breast cancer genes BRCA-1 and -2. We can analyze more than 60 samples in one run.”