Dr. Salehi and others from the University of California, Irvine recently published a paper describing a novel quality filtering and base pruning pipeline designed to detect sequence variants in a complex population with high sequence similarity, Complex Heterogeneous Overlapped Paired-End Reads (CHOPER). In this study they used All-Codon-Scanning (ACS) mutagenesis, which creates a defined gene library where each individual codon within a specific target region is changed into all possible codons with only a single codon change per mutagenesis product, to create a complex, heterogeneous population of cancer rescue mutations in the p53 protein.
ACS libraries were prepared and the rescue mutations were amplified using PCR. The NEXTflex ChIP-Seq Kit and NEXTflex ChIP-Seq Barcodes were used to prepare Illumina compatible libraries which were sequenced on a HiSeq instrument. CHOPER was used to detect biologically important low-frequency variants within genetically heterogeneous populations which can be difficult to identify due to intrinsic NGS sequencing error rates.
Relative to error filtering based on Phred quality scores, CHOPER improved accuracy by about 13% while discarding only half as many bases. These results are a step toward extending the power of NGS to the analysis of genetically heterogeneous populations.
Salehi, F., et al. (2015) CHOPER Filters Enable Rare Mutation Detection in Complex Mutagenesis Populations by Next-Generation Sequencing. PLoS ONE. Doi: 10.1371/journal.pone.0116877.