A flexible approach for highly multiplexed candidate gene targeted resequencing

• Published in: PloS one 2011-06, Vol.6 (6), p.e21088-e21088
• Main Authors: Natsoulis, Georges, Bell, John M, Xu, Hua, Buenrostro, Jason D, Ordonez, Heather, Grimes, Susan, Newburger, Daniel, Jensen, Michael, Zahn, Jacob M, Zhang, Nancy, Ji, Hanlee P
• Format: Article
• Language: English
• Subjects: Analysis; Assaying; Bioinformatics; Biology; Chemotherapy; Colorectal cancer; Computational Biology - methods; Computer Science; Cost analysis; Deoxyribonucleic acid; Diagnostic systems; DNA; DNA polymerase; DNA sequencing; Downloading; Enzymes; Exons; Exons - genetics; Flexibility; Gene sequencing; Genes; Genome, Human - genetics; Genomes; Genomics; Humans; Medicine; Metastasis; Multiplex Polymerase Chain Reaction; Multiplexing; Mutation; Oligonucleotides; Polymerase Chain Reaction; Population studies; Researchers; Sequence Analysis, DNA - methods; Studies
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0021088

We have developed an integrated strategy for targeted resequencing and analysis of gene subsets from the human exome for variants. Our capture technology is geared towards resequencing gene subsets substantially larger than can be done efficiently with simplex or multiplex PCR but smaller in scale than exome sequencing. We describe all the steps from the initial capture assay to single nucleotide variant (SNV) discovery. The capture methodology uses in-solution 80-mer oligonucleotides. To provide optimal flexibility in choosing human gene targets, we designed an in silico set of oligonucleotides, the Human OligoExome, that covers the gene exons annotated by the Consensus Coding Sequencing Project (CCDS). This resource is openly available as an Internet accessible database where one can download capture oligonucleotides sequences for any CCDS gene and design custom capture assays. Using this resource, we demonstrated the flexibility of this assay by custom designing capture assays ranging from 10 to over 100 gene targets with total capture sizes from over 100 Kilobases to nearly one Megabase. We established a method to reduce capture variability and incorporated indexing schemes to increase sample throughput. Our approach has multiple applications that include but are not limited to population targeted resequencing studies of specific gene subsets, validation of variants discovered in whole genome sequencing surveys and possible diagnostic analysis of disease gene subsets. We also present a cost analysis demonstrating its cost-effectiveness for large population studies.