Telomemore enables single-cell analysis of cell cycle and chromatin condensation

Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/533267v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@eec414org.highwire.dtl.DTLVardef@18b31d7org.highwire.dtl.DTLVardef@1753decorg.highwire.dtl.DTLVardef@346c5f_HPS_FORMAT_FIGEXP M_FIG C_FIG ABSTRACTSingle-cell RNA-seq methods can be used to delineate cell types and states at unprecedented resolution but do little to explain why certain genes are expressed. Single-cell ATAC-seq and multiome (ATAC+RNA) have emerged to give a complementary view of the cell state. It is however unclear what additional information can be extracted from ATAC-seq data besides transcription factor binding sites. Here we show that ATAC-seq telomere-like reads, mostly originating from the subtelomere, cannot be used to infer telomere length, but can be used as a biomarker for chromatin condensation. Using long-read sequencing, we further show that modern hyperactive Tn5 does not duplicate 9bp of its target sequence, contrary to common belief. We provide a new tool, Telomemore, which can quantify non-aligning subtelomeric reads. By analyzing several public datasets, and generating new multiome fibroblast and B cell atlases, we show how this new readout can aid single-cell data interpretation. We show how drivers of condensation processes can be inferred, and how it complements common RNA-seq-based cell cycle inference, which fails for monocytes. Telomemore-based analysis of the condensation state is thus a valuable complement to the single-cell analysis toolbox.