Dataset DOI: 10.5061/dryad.zw3r228fj

Data archive for

NAD⁺ prevents septic shock-induced death by non-canonical inflammasome blockade and IL-10 cytokine production in macrophages. Jasper Iske, Rachid El Fatimy, Yeqi Nian, Amina Ghouzlani, Siawosh K. Eskandari, Hector Rodriguez Cetina Biefer, Anju Vasudevan and Abdallah Elkhal.

Description of the data

This dataset contains bulk RNA sequencing (RNA-seq) data from murine bone marrow-derived macrophages (BMDMs) in three experimental groups:

• CTRL (control group): naive BMDMs that were differentiated without further treatment or stimulation.
• NAD (NAD⁺ group): BMDMs treated with NAD⁺, then primed with Pam3CSK4 and stimulated with lipopolysaccharide (LPS) plus cholera toxin B (CTB) to activate the non-canonical inflammasome.
• PBS (PBS group): BMDMs treated with PBS (vehicle), then primed and stimulated in the same way as the NAD group.

The dataset includes the raw sequencing reads, the reads aligned to the mouse reference genome, the reference files, and the downstream analysis results: quality control, mapping statistics, gene expression quantification, differential expression analysis, clustering, functional enrichment (GO, KEGG, Reactome) and protein–protein interaction networks. The main finding is that NAD⁺-treated and PBS-treated BMDMs have distinct transcriptional signatures, with significant downregulation of the interferon pathway in the NAD group.

Group labels CTRL, NAD and PBS are used consistently in all file names, column headers and figure legends. One RNA-seq library was sequenced per group.

Files and variables

The dataset consists of six files. File names are listed exactly as they appear in the Dryad submission.

File: rawdata.zip

Description: Raw paired-end sequencing reads for each group (CTRL, NAD, PBS) as delivered by Novogene, in gzip-compressed FASTQ format. Files are named by group, with the suffixes _1 and _2 for read 1 and read 2 of each pair. An MD5 checksum file for verifying file integrity may also be included. FASTQ files can be opened with standard bioinformatics tools such as FastQC, seqtk or any aligner (e.g., STAR, HISAT2).

File: bam.zip

Description: Clean reads for each group (CTRL, NAD, PBS) aligned to the mouse reference genome mm10 with STAR, in BAM format (binary sequence alignment/map). Files are named by group (e.g., CTRL.bam). BAM files can be viewed and processed with SAMtools, IGV (Integrative Genomics Viewer) or R/Bioconductor packages such as Rsamtools.

File: ref.zip

Description: The mouse (Mus musculus) mm10 reference files used for alignment and gene annotation: the genome sequence (FASTA format) and the gene annotation (GTF/GFF format). These files are needed to reproduce the alignment and the gene-level quantification. They can be opened with any text editor or with standard genomics tools (e.g., SAMtools, bedtools).

File: Gene_Description.xlsx

Description: Excel workbook with descriptions of the genes reported in the analysis. It can be opened with Microsoft Excel, LibreOffice Calc or any other spreadsheet software.

File: X202SC19041039-Z01-F001_Mus_musculus_mm10_MED_result.zip

Description: The complete bioinformatic analysis report from Novogene (project ID X202SC19041039). Each numbered subfolder contains a *.README.txt file from Novogene explaining that analysis step in detail. Figures are provided as PDF and PNG files, and some also as EPS. Tables are tab-separated text files (.tsv) with a header row. Single-column gene lists are plain text files (.txt) with one Ensembl gene ID per line. Sequence files are in FASTA format (.fa). All text files use UTF-8 encoding. Tables can be opened with any text editor, spreadsheet software, or R/Python (e.g., read.delim() in R, pandas.read_csv(sep="\t") in Python).

Comparisons are named <group1>vs<group2> (NADvsCTRL, PBSvsCTRL, PBSvsNAD). In each comparison, a positive log2 fold change means higher expression in group1 than in group2.

Gene identifiers are Ensembl mouse gene IDs (e.g., ENSMUSG00000000001). Genomic coordinates refer to mm10.

1.QC – sequencing quality control

• datatable.tsv: quality summary per sample. Variables:
  • Sample name: group (CTRL, NAD, PBS)
  • Raw reads: number of raw reads
  • Clean reads: number of reads remaining after filtering
  • Raw bases / Clean bases: number of sequenced bases before/after filtering, in gigabases (G)
  • Error rate(%): average base-calling error rate, in percent
  • Q20(%) / Q30(%): percentage of bases with Phred quality score > 20 / > 30
  • GC content(%): percentage of G and C bases among all bases
• ErrorRate/<group>.Error.pdf|png: error rate distribution along the read positions.
• GC/<group>.GC.pdf|png: base composition (A, T, G, C) along the read positions.
• ReadsClassification/<group>.pie3d.pdf|png: pie chart showing the proportions of clean reads and of reads removed by each filter.
• QC.README.txt: detailed explanation of this folder.

2.Mapping – alignment to the reference genome

• MapStat.tsv: mapping statistics. Each row is a metric and each column a group (CTRL, NAD, PBS). Metrics:
  • Total reads: number of clean reads
  • Total mapped reads: number of reads aligned to the genome
  • Uniquely mapped reads: number of reads aligned to a single position
  • Multiple mapped reads: number of reads aligned to multiple positions
  • Total, uniquely and multiple mapping rate: the corresponding numbers as percentages of total reads
• Distribution/<group>.density.pdf|png: distribution of mapped reads across the chromosomes.
• Mapregion/<group>.MR.pdf|png: proportion of reads mapped to exons, introns and intergenic regions.
• Mapping.README.txt: detailed explanation of this folder.

3.Quantification – gene expression

• Count/readcount.tsv: raw read counts per gene. Columns: geneID (Ensembl gene ID) and one column per group (CTRL, NAD, PBS) with integer read counts.
• Count/fpkm_sample.tsv and Count/fpkm_group.tsv: expression per gene in FPKM, per sample and per group. Because there is one sample per group, both files contain the same values (column order differs).
• Count/readcount_genename.tsv and Count/fpkm_genename.tsv: the same read counts and FPKM values with gene annotation added. Annotation columns:
  • Gene_name: gene symbol
  • Chrom: chromosome
  • Strand: + or −
  • Start / End: gene start and end coordinates (bp, mm10)
  • GeneLength: gene length in bp
  • Gene_type: gene biotype (e.g., protein_coding, lincRNA)
  • Description: gene description
• Distribution/fpkm_interval.tsv: number (and percentage) of genes per group in each FPKM interval (0–1, 1–3, 3–15, 15–60, >60).
• Distribution/boxplot|density|violin.pdf|png: FPKM distribution per group.
• Correlation/cor_pearson.tsv: pairwise squared Pearson correlation coefficients (R²) of gene expression between groups.
• Correlation/cor_pearson.pdf|png: heatmap of the correlation coefficients.
• Correlation/<group1>_vs_<group2>.scatter.pdf|png: pairwise scatter plots of expression.
• Correlation/PCA2D.pdf|png and PCA3D.pdf|png: principal component analysis of the groups.
• Quantification.README.txt: detailed explanation of this folder.

4.DiffExprAnalysis – differential expression

• DEGlist/<comparison>_DEG.tsv: differential expression results for all expressed genes.
• DEGlist/<comparison>_DEG_all.tsv: all significant differentially expressed genes (DEGs).
• DEGlist/<comparison>_DEG_up.tsv: significant DEGs upregulated in group1.
• DEGlist/<comparison>_DEG_down.tsv: significant DEGs downregulated in group1.
• Number of significant DEGs (up/down/total): NADvsCTRL 789/712/1501, PBSvsCTRL 1047/951/1998, PBSvsNAD 41/3/44.
• Variables in all DEGlist files:
  • Gene_ID: Ensembl gene ID
  • <group1>, : normalized read counts of each group
  • log2FoldChange: log2 of the expression ratio group1/group2
  • pvalue: p-value of the edgeR test
  • padj: Benjamini–Hochberg adjusted p-value
  • GeneName, Chrom, Strand, Start, End, GeneLength, GeneType, GeneDescription: gene annotation, as in 3.Quantification
  • <group>_readcount: raw read count of each group
  • <group>_fpkm: FPKM of each group
• DEGseq/<comparison>_DEG_all|up|down.fa: nucleotide sequences of the corresponding DEGs in FASTA format. Headers are Ensembl gene IDs.
• Volcano/<comparison>.volcano.pdf|png: volcano plots of log2 fold change against −log10(padj).
• Annotation/<comparison>/<comparison>.diffTF.tsv: DEGs that are annotated as transcription factors. Columns: Gene_ID, Gene_Symbol, normalized counts of both groups, log2FoldChange, Description, then transcription factor annotation (DBD_Classification, Reviewer, Judgement, Taxa, Reviewer_Commments, PubMed_ID, Function, Species, Evidence_Strength, PubMed_Comments). Missing values are "N.A." or empty.
• Annotation/<comparison>/<comparison>.diffCosmic.tsv: DEGs listed in the COSMIC Cancer Gene Census. Columns: Gene_ID, Gene_Symbol, normalized counts of both groups, log2FoldChange, Description, then COSMIC annotation (Chr_Band, Tumour_Types(Somatic), Tumour_Types(Germline), Cancer_Syndrome, Molecular_Genetics, Mutation_Types, Translocation_Partner, Synonyms). Missing values are "N.A.".
• No annotation files are provided for PBSvsNAD, because none of the 44 DEGs in that comparison are annotated transcription factors or COSMIC genes.
• Cluster/Union_for_cluster.tsv: FPKM values (columns PBS, NAD, CTRL) of the union of all DEGs, used for clustering.
• Cluster/heatCluster.pdf|png and heatCluster.detail.pdf: heatmap of hierarchical clustering of the DEGs.
• Cluster/hclust/, Cluster/kmeans/ and Cluster/som/: gene clusters from hierarchical clustering, k-means clustering and self-organizing maps (SOM). Each subcluster_<n>.tsv (SOM: subcluster_<row>_<column>.tsv) lists the genes of one cluster. These files have no header row. Column 1 is the Ensembl gene ID, and columns 2–4 are relative expression values for PBS, NAD and CTRL, calculated as log2((FPKM + 1) / (FPKM of PBS + 1)). Column 2 (PBS) is therefore always 0. The PDF/PNG/EPS files plot the expression trends of each cluster.
• Venn/PBS_NAD/ and Venn/PBS_NAD_CTRL/: Venn diagrams (PDF/PNG) of genes expressed (FPKM > 1) in each group. Each .txt file lists the Ensembl gene IDs in one area of the diagram. For example, PBS_NAD.txt contains genes expressed in both PBS and NAD, and PBS.txt genes expressed only in PBS. In PBS_NAD_CTRL/, PBS_NAD.txt contains genes expressed in PBS and NAD but not CTRL.
• DiffExprAnalysis.README.txt: detailed explanation of this folder.

5.Enrichment – GO, KEGG and Reactome enrichment

The folder has three subfolders, GO, KEGG and Reactome, with the same structure: <database>/<comparison>/<subset>/. The subset ALL contains the analysis of all DEGs of the comparison, UP of the upregulated DEGs only, and DOWN of the downregulated DEGs only. Files are named <comparison>_<all|up|down>.<suffix>.

• *.GOenrich.tsv, *.KEGGenrich.tsv, *.Reactomeenrich.tsv: enrichment results for all tested terms or pathways.
• *.GOenrich.significant.tsv, *.KEGGenrich.significant.tsv, *.Reactomeenrich.significant.tsv: significantly enriched terms or pathways only (padj < 0.05).
• Variables in all enrichment tables:
  • Category: source of the term. For GO, the domain (BP = biological process, CC = cellular component, MF = molecular function). For the other analyses, "KEGG" or "Reactome".
  • ID: term identifier (GO:xxxxxxx, KEGG pathway ID mmuxxxxx, or Reactome ID R-MMU-xxxxx)
  • Description: term or pathway name
  • GeneRatio: number of DEGs annotated to the term / number of DEGs with any annotation in that database
  • BgRatio: number of genes in the genome annotated to the term / number of genes with any annotation in that database
  • pvalue: hypergeometric test p-value
  • padj: Benjamini–Hochberg adjusted p-value
  • geneID: symbols of the DEGs annotated to the term, separated by "/"
  • Count: number of DEGs annotated to the term
• *.bar.pdf|png: bar charts of the top enriched terms. For GO, *.BPbar, *.CCbar and *.MFbar show each domain separately.
• *.dot.pdf|png: dot plots of the top enriched terms. The x-axis is GeneRatio, dot size is Count, and colour is padj.
• GO/…/*.GObp_DAG.pdf|png, *.GOcc_DAG.pdf|png and *.GOmf_DAG.pdf|png: directed acyclic graphs of the enriched terms within the GO hierarchy.
• The files PBSvsNAD_down.KEGGenrich.significant and PBSvsNAD_down.Reactomeenrich.significant are not included, because no KEGG or Reactome pathway was significantly enriched among the 3 genes downregulated in PBS vs NAD. The corresponding full tables (PBSvsNAD_down.KEGGenrich.tsv, PBSvsNAD_down.Reactomeenrich.tsv) are included.
• The KEGG pathway maps that Novogene provided (KEGG/…/pathway/*.pathview.pdf|png) are not included, because the KEGG pathway images are copyrighted by Kanehisa Laboratories. The maps can be regenerated from the KEGGenrich and DEG tables with the R package pathview.
• Enrichment.README.txt: detailed explanation of this folder. This general Novogene document also describes a DO (Disease Ontology) analysis, which is not part of this dataset.

6.PPI – protein–protein interaction networks

• <comparison>_<all|up|down>.ppi.tsv: interactions between the proteins encoded by the DEGs of a comparison (all, upregulated or downregulated DEGs), retrieved from the STRING database. These files have no header row. Columns:
  • Column 1 (protein 1) and column 2 (protein 2): Ensembl protein ID, followed by the corresponding Ensembl gene ID in parentheses, e.g., ENSMUSP00000000186(ENSMUSG00000000182)
  • Column 3: STRING combined interaction score (0–1000; only interactions with a score ≥ 700, i.e., high confidence, are included)
• The files can be imported into Cytoscape (https://cytoscape.org) as a network (source, target and edge attribute columns).
• PBSvsNAD_down.ppi is not included, because there were no interactions among the 3 genes downregulated in PBS vs NAD (the original file was empty).
• ProteinNetwork.README.txt: detailed explanation of this folder.

Changes to the Novogene report

Compared with the report delivered by Novogene, we made the following changes to X202SC19041039-Z01-F001_Mus_musculus_mm10_MED_result.zip:

• Novogene's interactive report viewer (NovoSmart.tar.gz), the directory listing (result_tree.html), the Cytoscape user manual (6.PPI/CytoscapeQuickStart.pdf) and the KEGG pathway maps (5.Enrichment/KEGG/…/pathway/) were removed because they contain third-party copyrighted or licensed material. All results contained in NovoSmart.tar.gz are included as individual files in the folders described above.
• Files that contained only a header row or were empty were removed (see the notes in the sections above).
• Tabular files delivered with an ".xls" extension were plain tab-separated text and were renamed to ".tsv" (single-column gene lists to ".txt"). The extensionless subcluster_* files and the .ppi.txt files were given the ".tsv" extension. All text files were converted to UTF-8 with Unix line endings, and the file references in the *.README.txt files were updated accordingly.

Note on ".xls" file extensions: Files with an ".xls" extension from the sequencing provider are not Excel workbooks but tab-separated text files and should be read as ".tsv" files. If you encounter any file with an ".xls" extension in this dataset, open it as tab-separated text (e.g., read.delim() in R or pandas.read_csv(sep="\t") in Python, or import it into Excel as tab-delimited text). Gene_Description.xlsx is a genuine Excel workbook.

Software

• FASTQ and BAM files: FastQC, SAMtools, IGV, STAR or other standard bioinformatics tools.
• Tables (.tsv, .txt, .xlsx): any text editor or spreadsheet software (Excel, LibreOffice), R or Python.
• Figures: any PDF or image viewer. EPS files open in Adobe Illustrator, Inkscape or Ghostscript.
• Analysis software used by Novogene: STAR (alignment), edgeR (differential expression) and clusterProfiler (GO, KEGG and Reactome enrichment), all in R/Bioconductor, and the STRING database (PPI).
• PPI networks: Cytoscape.