While multiple types of DNA sequence variations exist, single nucleotide polymorphisms (SNPs) are the most frequent form of mutation in many genes. Because of their abundance and stability, SNPs are used in a variety of biologic, genetic, and pharmacologic applications. As SNP technology becomes more widely adopted, the focus has shifted from identifying new SNP markers to characterizing SNPs in sample populations. This change in emphasis has led to the development of novel genotyping strategies aimed to both reduce experimental cost and increase throughput.
In order to benchmark the current state of these SNP technologies, The Science Advisory Board (SAB) assessed researchers’ experimental parameters, sample throughput levels and genotyping methods. In this study, the Board also queried its members about improvements to SNP genotyping that would most benefit researchers as well as the challenges of integrating genotyping and pharmacogenomics into clinical practice. Over 500 scientists participated in this study, and a summary of their best practices and insights is presented in this Study Snapshot.
Current Genotyping Focus
Because SNP genotyping utilizes both the candidate gene approach and association-based fine mapping to identify specific genes, its key applications include genome-wide disease association studies and population genetics. Furthermore, scientists also take advantage of SNPs’ ability to facilitate linkage analyses. Drug research is another common objective of scientists who use SNPs. While greater than 70% of SNP genotyping is done on samples of human origin, one-fifth of samples are murine-based.
Overall, 84% of study participants perform at least some of their genotyping in-house, and 59% of all total genotyping experiments are performed in-house. They named Applied Biosystems as the leading supplier of SNP genotyping instrumentation, followed by Affymetrix. In contrast, researchers who outsource their SNP genotyping are more likely to do so to a core facility or a collaborator’s lab rather than to an off-site service provider. These researchers cite convenient service, the fact that they cannot justify purchase of an instrumentation platform at current throughput levels and the expertise provided by their SNP genotyping provider as the three most common reasons why they outsource. These individuals identified Applied Biosystems as the leading commercial provider of outsourcing services, followed by Illumina.
Genotyping Techniques and Limitations
Of all the SNP genotyping methods available, sequencing still offers researchers the highest degree of specificity and selectivity due to its redundancy. Restriction fragment length polymorphism (RFLP), TaqMan assays and DNA microarrays are also frequently used genotyping methods. The use of DNA microarrays in genotyping has increased since 2002 (the last time this study was conducted), possibly reflecting the widespread adaptation of microarrays across many scientific disciplines. Microarrays are advantageous because they allow a greater deal of multiplexing, so that fewer manual steps are required to genotype a larger number of SNPs.
“Right now, I’m not so sure anyone really knows how to interpret SNP data – we are generating huge amounts of data, and rather a smaller amount of actual knowledge. I know that this is th same situation as faced by the expression microarray profiling field.”
-Postdoctoral Fellow, Europe
Respondents most commonly said that decreased cost per SNP analyzed would be the most valuable future improvement. “Fortunately, detection methods for SNPs are more amenable to automation, especially for large-scale genetic analysis, which may have the added benefit of resulting in lower pricing,” expects Tamara Zemlo, Ph.D., MPH, Executive Director, The Science Advisory Board. Many labs have already incorporated automated workflow solutions-including liquid handling, plate handling and sample preparation-into their genotyping workflow. Overall, 53% of respondents utilize automation—an increase from 39% of study respondents in 2002.
Genotyping and Pharmacogenomics
Pharmacogenomics is the merging of pharmacology and genomics to study how an individual’s genetic inheritance affects the body’s response to drugs. Pharmacogenomic analysis can also identify one’s disease susceptibility genes, possibly generating novel drug targets. Assessing genetically based differences among individuals has the potential to generate radical changes in the healthcare industry’s current approaches to drug discovery, therapies and treatments, and disease prevention strategies.
As scientists further explore the relationship between human genetics and disease, physicians will one day soon be able to prescribe medications based upon their patient’s genetic profile and/or determine a patient’s risk of developing a certain disease. The ability to decipher an individual’s specific genetic make-up in terms of drug response and disease risk will significantly influence the understanding of disease pathogenesis and will allow for physicians to practice personalized medicine. A major tenet of personalized medicine is that drug therapy in genetically similar subpopulations will be more efficacious and less toxic than in the general population.
“SNP genotyping research, particularly epigenetics, has the potential for not only evaluating individual (not just population) disease risk, but also the power to predict responsiveness to therapeutics, and in the case of epigenetic changes, has value for monitoring of individual patients’ treatment responses and the customization of personalized medical treatment plans. Epigenetics may lead to far more accurate assessment of patient prognosis, as well as the design of more effective therapeutics to target particular regulatory gene networks.”
-Principal Investigator, North America
Although most SAB members do not directly work in this area (only 14% cite preclinical pharmacogenomics as their primary research objective), they indicated that SNP genotyping is expected to play a large role in shaping the future of personalized medicine. When asked what they perceived as the greatest challenge to integrating SNP genotyping into clinical practice, many researchers indicated the lack of complete genomic solutions in chronic diseases. Other hurdles identified included the ability to demonstrate clinical utility and access to a dedicated professional team to interpret results.
“After discovery of a novel SNP, it is important to bring affordable technology into publication that allows most medical centers (even in smaller towns) to screen for these SNPs. In the long run, sufficient data on the medical relevance of the SNP will have been gathered and a decision can be made whether it is important to include that specific SNP in an array that may be made available to interested patients.”
-Staff Scientists, North America
Despite these practical obstacles to instituting personalized medicine, SNP genotyping will be indispensable to deciphering the genetic basis of disease, especially for multigenic disorders. Translating this vision to the clinic will require SNP genotyping systems that combine high throughput and accuracy with low cost per SNP analysis. “Scientists should look towards future system offerings that combine efficient miniaturization, a high degree of multiplexing and flexible automation to achieve these goals,” predicts Zemlo.
