How Should DNA Sample Collections Be Managed?
What are the sources of DNA that can be sampled for studying human genetic variation?
Peripheral blood is the most common source of DNA for studying human genetic variation. Standard protocols allow 10,000-50,000 assays to be performed on the DNA from a single 10 mL blood sample. The number of assays can be increased to 500,000 by using techniques like nested PCR. Other tissues like buccal cells and hair follicles can also be used but provide less DNA than blood. Transformed cell lines from blood provide an unlimited supply of DNA but are more expensive to establish and maintain.
What are the different classes of DNA markers that can be used to characterize genetic variation?
Various classes of DNA polymorphisms arising from mutations can be used as markers to characterize genetic variation. These include RFLPs detected by Southern blotting, VNTRs with varying numbers of tandem repeats, and microsatellites/STRs which are highly abundant and informative but have higher mutation rates. PCR-based biallelic markers with low mutation rates are also useful. Mitochondrial, Y-linked, X-linked and autosomal markers illuminate different genetic processes and provide different views of variation. Both gene regions and anonymous segments are studied to assess variation patterns.
Should there be a core set of DNA markers scored for all samples in the repository?
Designating a common core set of markers to be genotyped for all samples is not recommended, as the types of markers will depend on the specific research questions. The emerging DNA chip technology will allow efficient high-throughput screening of many markers, making it likely different studies will use a common large set of markers. Investigator-initiated efforts screening genome variation will naturally result in comprehensive genotyping better than mandating a defined core set.
What are the options for research material management of the DNA samples?
Fully decentralized, centralized, and regional center models exist for managing specimen collections. A single repository risks perception of exclusivity but is efficient. Fully decentralized repositories maximize autonomy but are inefficient. Establishing a few regional centers balances efficiencies and drawbacks. International cooperation will be key for success. Samples collected should be converted to purified DNA for flexible future use.
What are key considerations for effective data management?
A mechanism for allocating and reviewing sample requests is needed. Procedures for updating multiple synchronized database copies at regional centers are required. Quality control via standardized protocols and proficiency testing should be enforced. Public data networks facilitate information exchange but may require additional privacy protections if data is identifiable. The sensitive nature of genetic data means security risks must be addressed if data is linkable to individuals.
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