In recent years, next-generation sequencing approaches have generated unprecedented advances. With over 2,000 genes linked to at least one disease-relevant mutation, DNA sequencing has assumed increasingly important clinical relevance.
Nevertheless, multiple considerations still make it impractical to routinely sequence large numbers of eukaryotic genomes. Enrichment for specific regions of interest often becomes necessary, and targeted resequencing, which examines a limited number of genes within large populations, is emerging as a key approach, instrumental in our ability to unveil clinically and biologically relevant sequence variants.
Hanlee P. Ji, Ph.D., assistant professor in the department of medicine at Stanford University, and colleagues have developed several different approaches that allow targeted resequencing of genomic DNA and are useful for many applications such as the validation of mutations from cancer genomes, a topic that is still filled with challenges, partly due to the genetic heterogeneity found in clinical samples.
“This is one application for which targeted resequencing will be necessary and is unlikely to go away anytime soon,” explains Dr. Ji.
Another application is in clinical diagnosis, when multiple mutations in several genes are often linked to the same malignant tumor, but interpreting the clinical relevance of individual mutations is often a difficult task.
“I think what is practically going to happen is that gene subsets that have immediate clinical relevance and are clinically actionable will be quickly disseminated as diagnostic tests, and we already have started seeing that.”
Dr. Ji and colleagues recently published a targeted resequencing strategy that uses in-solution 80-mer oligonucleotides for capture and allows the analysis of gene subsets from the human exome. “This first-generation targeting technology is public and openly available for users.”
The Human OligoExome application is available at oligoexome.stanford.edu. Users can download the capture oligonucleotides to create their own assays independently of working with commercial sources.
“I think this is the first time that something like this has become available, on such a scale, for targeted resequencing,” explains Dr. Ji. The authors demonstrated the general robustness of this particular technology and revealed that it can resequence, with high sensitivity, genomic regions up to 1 megabase in size, when as little as tens of nanograms of target DNA is available.
While targeted resequencing provides a revolutionary approach to survey genetic variants, it also presents specific limitations for clinical diagnostics. “One challenge is that the existing targeted methods, which still require a large amount of sample and are expensive, are very cumbersome for molecular diagnostics,” says Patrice Milos, Ph.D., svp and CSO at Helicos BioSciences.
Dr. Milos and colleagues recently developed an approach that allows any gene to be captured and sequenced directly from genomic DNA, eliminating the need for DNA amplification and for other enzymatic steps prior to sequencing.
DNA isolated from a clinical sample of interest is initially sheared and then introduced into the custom flow cell for sequencing, and all these sample-prep steps can be performed within two hours. “In addition, what is being sequenced is the patient's natural DNA, as opposed to DNA obtained by methodologies that involve amplification and other enzymatic steps.”
This method involves very small sample amounts, and Dr. Milos illustrated its accuracy and low cost in a recently published study that examined mutations in the BRCA1 gene. An important advantage that this approach presents over Sanger sequencing and enzymatic amplification techniques is the quantitative nature of the sequencing, which enables it to identify not only substitution mutations but also large insertions, deletions, and rearrangements.
“The field of human genetics is highly dynamic. Every few years, there is a major technological change, and it is important to adapt to these new technologies and devise novel approaches to analyze the data that is coming out,” says Chun Li, Ph.D., an investigator at the Center for Human Genetics Research at Vanderbilt University.
While genome-wide association studies have seen unprecedented advances, these approaches still face several challenges. One of them is the difficulty inherent in sequencing the genome of every participating individual. This is particularly cumbersome in the case of rare disease alleles and uncommon genetic variants for which resequencing is currently the only feasible strategy to reliably identify them and interrogate their clinical relevance.
“Once we are able to perform sequencing at the highest resolution, one of the greatest challenges is how to analyze the data,” reveals Dr. Li, who, together with colleagues, developed SampleSeq, a probability-based algorithm that allows investigators to select and optimize samples for targeted resequencing.
The authors revealed that in groups of unrelated study participants, SampleSeq enriches the yield of rare or uncommon disease alleles and helps select participants with a balanced representation of all chromosomal regions when multiple regions of interest have to be sequenced. In addition, SampleSeq can estimate the sample size that is necessary to detect a rare allele and can thus guide resequencing efforts.