Sequencing and Data Analysis

Here we outline the expected metrics for successful CUT&Tag sequencing, including number of sequencing reads, duplication rates, and data from CUT&Tag control reactions. CUT&Tag sequencing metrics Libraries should be sequenced...

Ideally, you would   troubleshoot low CUT&Tag yields , repeat the experiment, and then proceed to sequencing. This will result in higher quality sequencing data compared to using ultra-low CUT&Tag yields. However, in some cases, r...

High read duplicate rates are common in CUT&Tag due to assay sensitivity and extremely low background. In general, duplication rates are higher for low abundant PTMs (H3K4me3; 50-70%) compared abundant PTMs (H3K27me3 positive control; 10-30...

Libraries should be sequenced to a depth of 5-8 million total reads. For sufficient coverage, each library should generate 3-5 million unique reads (after removing multi-mapping reads, duplicate reads, reads in DAC exclusion list regions).

High background in CUT&Tag data can occur due to a preference of Tn5 for accessible chromatin. The high-salt wash after pAG-Tn5 binding helps reduce signal at open chromatin, but some background may be present in the IgG control and when profil...

Because adapters are added by pAG-Tn5 during tagmentation, adapter dimer formation is NOT possible. Primer dimers may appear at 25-100 bp, but should have minimal enrichment. For more on removing primer dimers, see this article .

CUTANA^TM pAG-Tn5 is highly purified and depleted of contaminating nucleic acids, so residual E. coli DNA cannot be used for sequencing normalization. We do not recommend adding exogenous E. coli Spike-in DNA, as we have not thoroughl...

CUT&RUN and CUT&Tag analysis methods are similar to those used for ChIP-seq datasets, with a few key differences. Briefly, for CUT&RUN and CUT&Tag: Align raw reads to a reference genome using Bowtie2 [1]. The Integrative Genomi...