# Sequencing FAQ for the Illumina 5 Base WGS and Enrichment kits **Which instruments are supported for sequencing of this library type?** * **NovaSeq 6000:** S4 standard or Xp loading * **NovaSeq X**: 1.5B, 10B, 25B * **NextSeq 1000/2000:** XLEAP P3 onboard denature and dilute **What is the recommended sequencing read lengths and override cycles?** * 2x 151 with dual, 10 bp indexes * Override cycles are U7N1Y143;I10;I10;U7N1Y143 * **IMPORTANT**: omitting the override cycles will lead to higher-than-normal false positive rate (typically around 3.5-4%). This is because indexes and UMI anchors are not methylated. **What are the recommended loading concentrations?** The following loading concentrations apply to WGS libraries as well as Enriched libraries. These are general starting guidelines and loading concentrations may need to be adjusted/optimized for optimal performance. * **NovaSeq 6000, S4 standard** = 0.5 nM (starting concentration), 100 pM (final concentration) * **NovaSeq 6000, S4 Xp** = 0.25 nM (starting concentration), 50 pM (final concentration) * **NovaSeq X, 1.5B** = 130 pM * **NovaSeq X, 10B** = 130 pM * **NovaSeq X, 25B** = 150 pM * **NextSeq 1000/2000, XLEAP P3, onboard** = 750 pM. Note: NextSeq 1000/2000 output is insufficient for WGS libraries and is intended for Enrichment libraries **Can samples from gDNA and cfDNA be pooled together for sequencing even though the fragment sizes differ?** * This is not recommended to ensure optimal sequencer performance. **Is it recommended to add PhiX to the sequencing run? If yes, how much?** * Yes, 1% for all sequencing runs. **Can a 2% PhiX spike-in be used instead of the recommended 1%?** * Yes, if preferred. More reads will go to PhiX at 2% compared to 1%. **What sequencing depth/number of reads per sample is recommended? What is the recommended samples per run?** **For WGS (see** [**datasheet**](https://www.illumina.com/content/dam/illumina/gcs/assembled-assets/marketing-literature/illumina-5-base-dna-prep-data-sheet-m-gl-03689/illumina-5-base-dna-prep-data-sheet-m-gl-03689.pdf)**):** * **NovaSeq 6000, S4 (standard or XP)** = 18 libraries per flow cell * **NovaSeq X,** **1.5B** = 3 libraries max * **NovaSeq X, 10B** = 18 libraries max * **NovaSeq X, 25B** = 48 libraries max, either single pool across all lanes, or 6 libraries per lane **For Enrichment** * **For gDNA enrichment**: target 25 reads (clusters) per bp of target panel * **For cfDNA enrichment:** target 200 reads (clusters) per bp of target panel **What sequencing coverage depth does Illumina recommend for various applications?** * Illumina recommends 35X coverage for optimal performance of methylation calling + variant calling. If interested in methylation calling only, can consider 30X or even lower. * For other applications, see the below for suggested starting coverage depth recommendations, some optimization may be required (information from the [datasheet](https://www.illumina.com/content/dam/illumina/gcs/assembled-assets/marketing-literature/illumina-5-base-dna-prep-data-sheet-m-gl-03689/illumina-5-base-dna-prep-data-sheet-m-gl-03689.pdf)): ![](https://761066130-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGM9W2DuBTgEXv1ClCm8H%2Fuploads%2Fgit-blob-cb1372a03559c770d009623d620d21524c7c0af9%2Fimage1.png?alt=media) **If sequencing a pool of samples, is it better to make one pool and split it across all lanes, or sequence specific (and different) samples per lane?** * Both options are valid if aiming for the same number of reads per sample. * However, if performing **unequal pooling** (some samples loaded at higher volume/concentrations than others), then the recommendation is to **split up pooling events into smaller pools split across the flow cell** (not recommended to do a single pool per flow cell in this scenario). If performing unequal pooling and a single sample is pooled significantly higher than the others, resulting in the majority of the clusters in all lanes, it can cause data processing issues downstream. **Is it better to run eight libraries per flow cell and run three flow cells, or make one pool of 24 libraries, and sequence it three times?** * It is better to make a pool of the 24 libraries and sequence it three times. This allows for rebalancing after the first run, though it is important ensure there is sufficient library in for re-pool, if needed. **Do the 5-Base runs have a different base profile compared to standard whole genome or enrichment runs?** * Generally, no. In human genomes, most methylation is observed in the CpG context only. There are \~28 million cytosines in the CpG context in the human genome (\~3.3 billion bases). Thus only \~1% of the genome is available to be converted from 5mC>T. This will not be noticeable when reviewing run performance metrics. \ \ \
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