Index switching causes “spreading-of-signal” among multiplexed samples in Illumina HiSeq 4000 DNA sequencing

Abstract

Illumina-based next generation sequencing (NGS) has accelerated biomedical discovery through its ability to generate thousands of gigabases of sequencing output per run at a fraction of the time and cost of conventional technologies. The process typically involves four basic steps: library preparation, cluster generation, sequencing, and data analysis. In 2015, a new chemistry of cluster generation was introduced in the newer Illumina machines (HiSeq 3000/4000/X Ten) called exclusion amplification (ExAmp), which was a fundamental shift from the earlier method of random cluster generation by bridge amplification on a non-patterned flow cell. The ExAmp chemistry, in conjunction with patterned flow cells containing nanowells at fixed locations, increases cluster density on the flow cell, thereby reducing the cost per run. It also increases sequence read quality, especially for longer read lengths (up to 150 base pairs). This advance has been widely adopted for genome sequencing because greater sequencing depth can be achieved for lower cost without compromising the quality of longer reads. We show that this promising chemistry is problematic, however, when multiplexing samples. We discovered that up to 5-10% of sequencing reads (or signals) are incorrectly assigned from a given sample to other samples in a multiplexed pool. We provide evidence that this "spreading-of-signals" arises from low levels of free index primers present in the pool. These index primers can prime pooled library fragments at random via complementary 3' ends, and get extended by DNA polymerase, creating a new library molecule with a new index before binding to the patterned flow cell to generate a cluster for sequencing. This causes the resulting read from that cluster to be assigned to a different sample, causing the spread of signals within multiplexed samples. We show that low levels of free index primers persist after the most common library purification procedure recommended by Illumina, and that the amount of signal spreading among samples is proportional to the level of free index primer present in the library pool. This artifact causes homogenization and misclassification of cells in single cell RNA-seq experiments. Therefore, all data generated in this way must now be carefully re-examined to ensure that "spreading-ofsignals" has not compromised data analysis and conclusions. Re-sequencing samples using an older technology that uses conventional bridge amplification for cluster generation, or improved library cleanup strategies to remove free index primers, can minimize or eliminate this signal spreading artifact.

A novel post hoc method for detecting index switching finds no evidence for increased switching on the Illumina HiSeq X

“…Previous work has suggested that index switching is occurring for 1-10% of reads depending on 131 factors during library preparation and sequencing (Sinha et al 2017). This low level means that, 132 for our dataset, at a single locus, an allele acquired because of index switching is likely to only 133 have one read, given moderate overall read depth.…”

“…With the central role that sequencing 34 plays, it is alarming that a recent preprint suggests increased index switching on the new HiSeq 35 4000 and HiSeq X machines (Sinha et al 2017). 36…”

“…As the output of a single sequencing lane has increased, multiplexing has 43 become increasingly common. This is especially true in molecular ecology, where researchers 44 often aim to maximize sample size by using low coverage whole genome data (Buerkle and 45 (Sinha et al 2017). They dual indexed (i.e.…”

Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data

“…It is likely that capture or sequencing failed for these wells, so they were not used for variance estimation. In addition, we examined the effect of index switching (Sinha et al 2017) in each data set generated on the HiSeq 4000 and found it to be negligible (Supplemental Material, Section 3; Supplemental Fig. 13).…”

Analysis of single-cell genome sequences of bacteria and archaea

“…Multiplexing samples, specifically biased MDA'd samples, for sequencing on the Illumina platform, however, can cause significant 'bleed over' between poolmates. For example, Sinha et al [34] showed that 5-10% of reads can be assigned to the wrong sample based on low levels of index-free primers present in the multiplexed pool, when using the HiSeq platform. More stringent library cleanup procedures, the use of dual indexes [35] and quality filtering [36] are all methods that can reduce this effect.…”