Fig. 2: BC Detection by qPCR and next generation sequencing methods.

a qPCR-based BC identification and quantification is achieved by subjecting sample gDNA to 2 rounds of PCR using pre-amplification primers (red, round 1) and BC-specific primers (black, round 2). b Heatmap showing hamming distance between all barcodes in the Met1 BC Pool. c Heatmap of qPCR cycle threshold (CT) values after testing each indicated barcode oligonucleotide primer against every Met1 BC population and the Met1-BC pool. d Multiplexing of gDNA samples for NGS is achieved in 3 steps. 1: Barcode regions in each gDNA sample are PCR-amplified using primers to universal barcode flanking sequences. To the resulting amplicons from each sample, one of 20 available unique 8-bp indexes is added downstream (3' end) of the barcode region via PCR. 2: Up to 20 different indexed amplicons (various colors) are pooled to generate a single barcode-index library. 3: Amplicons in each barcode-index library are ligated to Illumina adaptors. A universal P5 adaptor (green) is ligated upstream (5' end) and one of 24 available P7 adaptors (e.g., TruSeq1, blue and Truseq2, orange) is ligated downstream (3' end) of the barcode region. e Sequencing read counts from 2 HMLER-HR BC test samples. Each library corresponds to a single Illumina adaptor, and the expected barcode pair for each library is indicated. For each library, the average false-positive read count (±S.E.M.) per BC is shown for BCs in the HMLER-HR BC Pool (black) and for BCs not represented in the HMLER-HR BC Pool (red). All BCs that yielded a read count are represented. f Example of thresholding method for identifying BCs from experimental samples by NGS. Graph shows read counts for each barcode from an HMLER-HR BC Pool tumor. The only false positive read corresponds to BC43, which was used to set the false-positive threshold (red line). Barcodes with read counts below the threshold were discarded as sequencer noise. Source data are provided as a Source Data file.