Additional file 2 of Protocol variations in run-on transcription dataset preparation produce detectable signatures in sequencing libraries
Creators: name: Hunter, Samuel
name: Sigauke, Rutendo F.
name: Stanley, Jacob T.
name: Allen, Mary A.
name: Dowell, Robin D.
Publisher: name: figshare
Year: 2022
Subjects: subject: Biochemistry
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: Immunology
subject: FOS: Clinical medicine
subject: 19999 Mathematical Sciences not elsewhere classified
subject: FOS: Mathematics
subject: Plant Biology
subject: Computational Biology

description: Additional file 2 Supplemental Figure 2 Metagenes of public GRO-RPR and in house libraries. Supplemental Figure 3 Read distribution of all libraries. Supplemental Figure 4 Discrete wavelet transform PCA results for 294 highly transcribed genes, demonstrates 39.8% of genes separate on PC1. Supplemental Figure 5 DWT PCA Results of detail coefficients at UBB Locus. PCA results for UBB locus, as in Figure 2F, but results are colored by library preparation method. At this locus, the results cluster less distinctly by library preparation method, compared to the enrichment protocol. Supplemental Figure 6 Schematic for the Support Vector Machine (SVM) leave one out cross validation (LOOCV) analysis. Eighteen nascent RNA sequencing samples were used as input. Given a gene, each of the samples was selected as a test sample and the other samples as training set, the SVM classification was evaluated. Based on this criteria, a majority of the genes (&gt;75%) accurately classified the protocol for the n=18 samples. Supplemental Figure 7 Support vector machine results for 294 highly transcribed genes as well as a larger 669 set. Supplemental Figure 8 Scatterplot matrix of elongation region TPM for highly transcribed genes. Supplemental Figure 9 Heatmap showing the ratio of reads in pause regions between pairs of libraries. Supplemental Figure 11 Heatmap showing the ratio of reads in pause regions in publicly available data. Supplemental Figure 10 Metagenes for PRO-LIG libaries with varied biotin-NTP/NTP ratio. Supplemental Figure 12 Metagenes and pause index comparison in publicly available K562 data. Supplemental Figure 13 Short reads obtained from different run-on ratios and size selection criteria. Supplemental Figure 14 Ratio of small reads near TSS versus all short reads. Supplemental Figure 15 Scatterplot matrix of counts within the pause region of the most highly transcribed genes. Supplemental Figure 16 Pause index and rank correlation of GRO-CIRC and PRO-LIG libraries. Supplemental Figure 17 Comparison of signal in FANTOM enhancer annotations. Supplemental Figure 18 Upset plots of Tfit and dREG called regions across library preparations. Supplemental Figure 19 Example of an enhancer that is differentially recovered by different protocols. Supplemental Figure 20 Metagene summary of enhancers differentially detected between GRO-LIG and GRO-CIRC libraries. Supplemental Figure 21 GSEA enrichment plots for GRO-LIG, PRO-LIG and GRO-CIRC libraries. Supplemental Figure 22 Overlap of GSEA specified p53 genes in GRO-LIG and PRO-LIG libraries. Supplemental Figure 23 TFEA results for PRO-LIG libraries. Supplemental Figure 24 Example p53 responsive enhancer that is captured disparately across protocols. Supplemental Figure 25 Rank differential of GRO-LIG and PRO-LIG identified p53 responsive enhancers.