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The use of hybridization capture has enabled a massive upscaling in sample sizes for ancient DNA studies, allowing the analysis of hundreds of skeletal remains or sediments in single studies. Nevertheless, demands in throughput continue to grow, and hybridization capture has become a limiting step in sample preparation due to the large consumption of reagents, consumables and time. Here, we explored the possibility of improving the economics of sample preparation via multiplex capture, that is, the hybridization capture of pools of double‐indexed ancient DNA libraries. We demonstrate that this strategy is feasible, at least for small genomic targets such as mitochondrial DNA, if the annealing temperature is increased and PCR cycles are limited in post‐capture amplification to avoid index swapping by jumping PCR, which manifests as cross‐contamination in resulting sequence data. We also show that the reamplification of double‐indexed libraries to PCR plateau before or after hybridization capture can sporadically lead to small, but detectable cross‐contamination even if libraries are amplified in separate reactions. We provide protocols for both manual capture and automated capture in 384‐well format that are compatible with single‐ and multiplex capture and effectively suppress cross‐contamination and artefact formation. Last, we provide a simple computational method for quantifying cross‐contamination due to index swapping in double‐indexed libraries, which we recommend using for routine quality checks in studies that are sensitive to cross‐contamination. [ABSTRACT FROM AUTHOR]

Abstract Background Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps. Results Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping. Conclusions Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing.

Background: Here we present an in-depth characterization of the mechanism of sequencer-induced sample contamination due to the phenomenon of index swapping that impacts Illumina sequencers employing patterned flow cells with Exclusion Amplification (ExAmp) chemistry (HiSeqX, HiSeq4000, and NovaSeq). We also present a remediation method that minimizes the impact of such swaps. Results: Leveraging data collected over a two-year period, we demonstrate the widespread prevalence of index swapping in patterned flow cell data. We calculate mean swap rates across multiple sample preparation methods and sequencer models, demonstrating that different library methods can have vastly different swapping rates and that even non-ExAmp chemistry instruments display trace levels of index swapping. We provide methods for eliminating sample data cross contamination by utilizing non-redundant dual indexing for complete filtering of index swapped reads, and share the sequences for 96 non-combinatorial dual indexes we have validated across various library preparation methods and sequencer models. Finally, using computational methods we provide a greater insight into the mechanism of index swapping. Conclusions: Index swapping in pooled libraries is a prevalent phenomenon that we observe at a rate of 0.2 to 6% in all sequencing runs on HiSeqX, HiSeq 4000/3000, and NovaSeq. Utilizing non-redundant dual indexing allows for the removal (flagging/filtering) of these swapped reads and eliminates swapping induced sample contamination, which is critical for sensitive applications such as RNA-seq, single cell, blood biopsy using circulating tumor DNA, or clinical sequencing. [ABSTRACT FROM AUTHOR]