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Sample selection algorithm to improve quality of genotyping from plasma-derived DNA: To separate the wheat from the chaff.
Hum. Mutat. 28, 1141-1149 (2007)
Plasma and serum samples were often the only biological material collected for earlier epidemiological studies. These studies have a huge informative content, especially due to their long follow-up and would be an invaluable treasure for genetic investigations. However, often no banked DNA is available. To use the small amounts of DNA present in plasma, in a first step, we applied magnetic bead technology to extract this DNA, followed by a whole-genome amplification (WGA) using phi29-polymerase. We assembled 88 sample pairs, each consisting of WGA plasma DNA and the corresponding whole-blood DNA. We genotyped nine highly polymorphic short tandem repeats (STRs) and 23 SNPs in both DNA sources. The average within-pair discordance was 3.8% for SNPs and 15.9% for STR genotypes, respectively. We developed an algorithm based on one-half of the sample pairs and validated on the other one-half to identify the samples with high WGA plasma DNA quality to assure low genotyping error and to exclude plasma DNA samples with insufficient quality: excluding samples showing homozygosity at five or more of the nine STR loci yielded exclusion of 22.7% of all samples and decreased average discordance for STR and SNP markers to 3.92% and 0.63%, respectively. For SNPs, this is very close to the error observed for genomic DNA in many laboratories. Our workflow and sample selection algorithm offers new opportunities to recover reliable DNA from stored plasma material. This algorithm is superior to testing the amount of input DNA.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
whole genome amplification; plasma; DNA purification; quality control
Language
english
Publication Year
2007
HGF-reported in Year
2007
ISSN (print) / ISBN
1059-7794
e-ISSN
1098-1004
Journal
Human Mutation
Quellenangaben
Volume: 28,
Issue: 11,
Pages: 1141-1149
Publisher
Wiley
Reviewing status
Peer reviewed
Institute(s)
Institute of Epidemiology (EPI)
POF-Topic(s)
30503 - Chronic Diseases of the Lung and Allergies
Research field(s)
Genetics and Epidemiology
PSP Element(s)
G-503900-001
PubMed ID
17614297
WOS ID
000250610200012
Scopus ID
35649010955
Erfassungsdatum
2007-12-31