Abstract
Complementary techniques that deepen information content and minimize reagent costs are required to realize the full potential of massively parallel sequencing. Here, we describe a resequencing approach that directs focus to genomic regions of high interest by combining hybridization-based purification of multi-megabase regions with sequencing on the Illumina Genome Analyzer (GA). The capture matrix is created by a microarray on which probes can be programmed as desired to target any non-repeat portion of the genome, while the method requires only a basic familiarity with microarray hybridization. We present a detailed protocol suitable for 1–2 μg of input genomic DNA and highlight key design tips in which high specificity (>65% of reads stem from enriched exons) and high sensitivity (98% targeted base pair coverage) can be achieved. We have successfully applied this to the enrichment of coding regions, in both human and mouse, ranging from 0.5 to 4 Mb in length. From genomic DNA library production to base-called sequences, this procedure takes approximately 9–10 d inclusive of array captures and one Illumina flow cell run.
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Acknowledgements
We are thankful to Danea Rebolini, Laura Cardone and Melissa Kramer for sequencing and informatic support. We also thank Mona Spector for helpful discussions. This work was supported by an NIH postdoctoral training grant (E.H.) and by kind gifts from the Stanley Foundation and Kathryn W. Davis (G.J.H.). G.J.H. is an investigator of the Howard Hughes Medical Institute.
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We declare the following conflicts of interest. Arindam Bhattacharjee, D. Benjamin Gordon, and Leonardo Brizuela are employees of Agilent, Inc. Agilent supplies arrays that can be used for the hybrid selection procedures described in this manuscript.
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Hodges, E., Rooks, M., Xuan, Z. et al. Hybrid selection of discrete genomic intervals on custom-designed microarrays for massively parallel sequencing. Nat Protoc 4, 960–974 (2009). https://doi.org/10.1038/nprot.2009.68
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DOI: https://doi.org/10.1038/nprot.2009.68
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