--------------------------------------------- # Comparison of type 1 conventional dendritic cells pre-cDC1 and CD8+ cDC1 and dendritic cells from bendamustine- or cyclophosphamide-treated mice Preferred citation (DataCite format): Molina, Megan S; Katsanis, Emmanuel (2021). Comparison of type 1 conventional dendritic cells pre-cDC1 and CD8+ cDC1 and dendritic cells from bendamustine- or cyclophosphamide-treated mice. University of Arizona Research Data Repository. Dataset. https://doi.org/10.25422/azu.data.14241902 Corresponding Author: Megan S Molina, University of Arizona, meganm4@email.arizona.edu License: CC BY 4.0 DOI: https://doi.org/10.25422/azu.data.14241902 --------------------------------------------- ## Summary Dendritic cells (DCs) harvested from murine spleens to evaluate the effect of treatment with two chemotherapeutic agents: bendamustine and cyclophosphamide. Previous work found that bendamustine treatment results in accumulation of the type 1 conventional DC precursor (pre-cDC1). Pre-cDC1 are an understudied population of murine DCs. This 2x2 study compared the transcriptional profile of bendamustine versus cyclophosphamide and pre-cDC1 versus the mature CD8+ cDC1. * * * _For inquiries regarding the contents of this dataset, please contact the Corresponding Author listed in the README.txt file. Administrative inquiries (e.g., removal requests, trouble downloading, etc.) can be directed to data- management@arizona.edu_ --------------------------------------------- ## Files and Folders #### Cell Preparation Protocols.zip: Methodology for the preparation of cell samples for RNAsequencing analysis #### Expression Counts.zip: The raw expression counts for each sample #### Comparisons.zip: Fold change comparisons between each of the four sample groups #### Figures.zip: Figures visualizing data comparisons #### Ingenuity Pathway Analyses.zip: Pathway analyses and upstream regulators For the canonical pathways the columns are - Pathway name - -log p-value: the higher the number the more significant the p-value, a 0.05 p-value corresponds to a 1.3 -log p-value so anything above this value can be considered "significant" - Ratio: the percentage of the genes in the pathway that overlap with the DE gene list - z-scores: greater than the pathway is considered "activated", less than -2 is considered "deactivated", between -2 and 2 means that the pathway was not definitively "activated" or "deactivated", #NUM! or blank indicates that there isn't enough known about the pathway's "normal" expression to give a z-score, so you can have a pathway with a significant gene enrichment, but no expression value. - the list of genes from the DEG list that correspond to that particular pathway. For the upstream analysis, it is an IPA tool that tries to predict regulators that are controlling the expression of the experimental group. The columns are - The name of the regulator - Indicator if a regulator is one of the genes in the DE list, if there's a value in this column, it is the log2foldchange from the differential expression result. Predicted activation here is also determined using a +/-2 z-score. --------------------------------------------- ## Materials & Methods RNA Samples were assessed for quality with an Advanced Analytics Fragment Analyzer (High Sensitivity RNA Analysis Kit – Catalog # DNF-491 / User Guide DNF-491-2014AUG13) and quantity with a Qubit RNA quantification kit (Qubit® RNA HS Assay Kit – Catalog # Q32852). Given satisfactory quality and quantity, samples were used for library builds with the Swift RNA Library Kit – (Catalog # R1024 / Swift Protocol version 3.0) and Swift Dual Combinatorial Indexing Kit – (Catalog # X8096). Upon library build completion, samples had quality and average fragment size assessed with the Advanced Analytics Fragment Analyzer with the High Sensitivity NGS Analysis Kit – (Catalog # DNF-486 / User Guide DNF-486-2014MAR10). Quantity was assessed with an Illumina Universal Adaptor-specific qPCR kit, the Kapa Library Quantification kit for Illumina NGS – (Catalog # KK4824 / KAPA Library Quantification Technical Guide - AUG2014). After final library QC was completed, samples were equimolar-pooled and clustered for sequencing on the NextSeq500 machine. The sequencing run was performed using Illumina NextSeq500 run chemistry (NextSeq 500/550 High Output v2 kit 150 cycles – Catalog FC-404-2002), and data were sent to UAGC Biocomputing Group for further analysis. Paired-end reads were demultiplexed using Illumina’s BaseSpace service. Reads were trimmed using Trimmomatic version 0.32 (USADelLab, Aachen, Germany). Fastq files were aligned to the GRCm38 version of the mouse reference genome using STAR version 2.5.2b (Dobin et al). Gene level quantification was performed using htseq-count version 0.6.1 (Anders et al). DESeq2 was used to conduct differential expression analysis with genes having an adjusted p-value (padj) < 0.05 being considered significant (Love et al). Pathway enrichment was performed on the significant DEGs using QIAGEN’s IPA software tool.