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SMRT Sequencing for Parallel Analysis of Multiple Targets and Accurate SNP Phasing
Xiaoge Guo1, Kevin Lehner2, Karen O'Connell2
1Graduate Program in Molecular Cancer Biology, Duke University, Durham, North Carolina 27710.
G3 (Bethesda, Md.)
|October 27, 2015
Summary
Single-molecule real-time (SMRT) sequencing with barcoding enables simultaneous analysis of multiple genomic targets. This method simplifies mutation and recombination studies by directly identifying linked genetic changes.
Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Single-molecule real-time (SMRT) sequencing offers longer reads than traditional next-generation (next-gen) sequencing.
- Current applications of SMRT sequencing for whole genome or exome analysis are limited.
Purpose of the Study:
- To develop and validate a barcoding-SMRT sequencing approach for simultaneous analysis of multiple genomic targets.
- To assess the utility of this approach for studying genetic changes in model systems and primary tumors.
Main Methods:
- Utilized SMRT sequencing combined with barcoding to analyze genomic targets from multiple sources.
- Applied the method to study strand-exchange intermediates in budding yeast mitotic recombination and forward mutation assays.
- Extended the barcoding-SMRT approach to analyze primary diffuse large B-cell lymphoma tumors and cell lines.
Main Results:
- Successfully analyzed multiple genomic targets simultaneously using the barcoding-SMRT method.
- Detected genetic changes in yeast recombination and mutation assays.
- Results from lymphoma samples showed agreement with previous Illumina exome sequencing data.
- SMRT sequencing inherently provides linkage information between single nucleotide polymorphisms (SNPs).
Conclusions:
- The barcoding-SMRT approach is effective for simultaneous analysis of multiple genomic targets.
- This method offers computational simplicity and eliminates the need for complex statistical analyses for mutation and recombination studies.
- The ability to identify linkage relationships between SNPs is a key advantage over other next-gen sequencing methods.

