decoding a substantial set of samples in parallel by massive sequencing解码一个实质性的样本集由大规模并行测序.pdfVIP

decoding a substantial set of samples in parallel by massive sequencing解码一个实质性的样本集由大规模并行测序.pdf

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decoding a substantial set of samples in parallel by massive sequencing解码一个实质性的样本集由大规模并行测序

Decoding a Substantial Set of Samples in Parallel by Massive Sequencing ˚ Marten Neiman, Sverker Lundin, Peter Savolainen, Afshin Ahmadian* Science for Life Laboratory, Department of Gene Technology, School of Biotechnology, Royal Institute of Technology (KTH), Solna, Sweden Abstract There has been a dramatic increase of throughput of sequenced bases in the last years but sequencing a multitude of samples in parallel has not yet developed equally. Here we present a novel strategy where the combination of two tags is used to link sequencing reads back to their origins from a pool of samples. By incorporating the tags in two steps sample- handling complexity is lowered by nearly 100 times compared to conventional indexing protocols. In addition, the method described here enables accurate identification and typing of thousands of samples in parallel. In this study the system was designed to test 4992 samples using only 122 tags. To prove the concept of the two-tagging method, the highly polymorphic 2nd exon of DLA-DRB1 in dogs and wolves was sequenced using the 454 GS FLX Titanium Chemistry. By requiring a minimum sequence depth of 20 reads per sample, 94% of the successfully amplified samples were genotyped. In addition, the method allowed digital detection of chimeric fragments. These results demonstrate that it is possible to sequence thousands of samples in parallel without complex pooling patterns or primer combinations. Furthermore, the method is highly scalable as only a limited number of additional tags leads to substantial increase of the sample size. Citation: Neiman M, Lundin S, Savolainen P, Ahmadian A (2011) Decoding a Substantial Set of Samples in Parallel by Massive Sequencing. PLoS ONE 6(3): e17785. doi:10.1371/journal.pone.0017785 Editor: Mikael And

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