Multi-sample pooling and illumina genome analyzer sequencing methods to determine gene sequence variation for database development.

作者: Karl V. Voelkerding , Jacob D. Durtschi , David C. Pattison , Rong Mao , Rebecca L. Margraf

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摘要: Determination of sequence variation within a genetic locus to develop clinically relevant databases is critical for molecular assay design and clinical test interpretation, so multisample pooling Illumina genome analyzer (GA) sequencing was investigated using the RET proto-oncogene as model. Samples were Sanger-sequenced exons 10, 11, 13–16. Ten samples with 13 known unique variants (“singleton variants” pool) seven common changes amplified then equimolar-pooled before on single flow cell lane, generating 36 base reads. For comparison, “control” sample run in different lane. After alignment, 24-base quality score-screening threshold 3` read end trimming three bases yielded low background error rates 27% decrease aligned coverage. Sequencing data evaluated an established variant detection method (percent reads), by presented subtractive correction method, SNPSeeker software. In total, 41 (of which 23 singleton variants) detected 10 pool data, included all Sanger-identified variants. The near expected 5% allele frequency (average 5.17%±0.90% well above highest (1.25%). Based rates, coverage, simulated 30, 40, 50 frequencies pools, methods; ≥30 (which demonstrated minimum 1% reads singletons) could be pooled reliably detect GA sequencing.

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