Additional file 2 of Altered hippocampal transcriptome dynamics following sleep deprivation

Additional file 2: Table S1. RT-qPCR primers used. Validation of RNA-seq results was performed using RT-qPCR, SYBR technology, and custom designed primers. Table S2. Genes significantly upregulated by sleep deprivation. We compared non-sleep deprived and sleep deprived mice and identified 507 genes with a false discovery rate (FDR) < 0.1 that were upregulated after sleep deprivation. Gene types include antisense, bidirectional promoter long non-coding RNA (lncRNA), long intergenic non-coding RNA (lincRNA), processed transcript, protein coding, Small Cajal body-specific RNA (scaRNA), to be experimentally confirmed (TEC), transcribed processed pseudogene, transcribed unprocessed pseudogene, unitary pseudogene, and unprocessed pseudogene. LogFC denotes Log Fold Change, LogCPM denoted Log Counts Per Million, and F denotes the F-statistic from edgeR’s quasi-likelihood pipeline. Table S3. Enrichment networks in upregulated genes using PANTHER:BP. We used Network Analyst software and the PANTHER:Biological Processes (BP) classification to perform overrepresentation analysis (ORA) and identified 16 pathways enriched for upregulated genes. Hits represent the number of upregulated genes found in each network. Table S4. Cellular components enriched in upregulated genes using Panther:CC. We used Network Analyst software and the PANTHER: Cellular Components (CC) classification to perform overrepresentation analysis (ORA) and identified 10 networks enriched for upregulated genes. Hits represent the number of upregulated genes found in each network. Table S5. Genes significantly downregulated by sleep deprivation. We compared sleep deprived and undisturbed mice and identified 639 genes with an FDR < 0.1 that were downregulated after sleep deprivation. Gene types include antisense, bidirectional promoter lncRNA, lincRNA, microRNA, processed pseudogene, processed transcript, protein coding, sense intronic, TEC, transcribed processed pseudogene, and transcribed unprocessed pseudogene. LogFC denotes Log Fold Change, LogCPM denoted Log Counts Per Million, and F denotes the F-statistic from edgeR’s quasi-likelihood pipeline. Table S6. Enrichment networks in downregulated genes using PANTHER:BP. We used Network Analyst software and the PANTHER:BP classification to perform ORA and identified 19 pathways enriched for downregulated genes. Hits represent the number of downregulated genes found in each network. Table S7. Cellular components enriched in downregulated genes using PANTHER:CC. We used Network Analyst software and the PANTHER:CC classification to perform ORA and identified 19 networks enriched for upregulated genes. Hits represent the number of downregulated genes found in each network. Table S8. Genes significantly dysregulated by sleep deprivation (FDR < 0.05). We compared sleep deprived and undisturbed mice and identified 636 genes with an FDR < 0.05 that were either upregulated or downregulated after sleep deprivation. Gene types include antisense, lincRNA, processed pseudogene, processed transcript, protein coding, sense intronic, TEC, transcribed processed pseudogene, transcribed unprocessed pseudogene, and unitary pseudogene. LogFC denotes Log Fold Change, LogCPM denoted Log Counts Per Million, and F denotes the F-statistic from edgeR’s quasi-likelihood pipeline. Table S9. Genes significantly dysregulated by sleep deprivation (FDR < 0.2). We compared sleep deprived and undisturbed mice and identified 2294 genes with an FDR < 0.2 that were either upregulated or downregulated after sleep deprivation. Gene types include antisense, bidirectional promoter lncRNA, lincRNA, microRNA, Mt_tRNA, polymorphic pseudogene, processed pseudogene, processed transcript, protein coding, pseudogene, scaRNA, sense intronic, snoRNA, snRNA, TEC, transcribed processed pseudogene, transcribed unprocessed pseudogene, unitary pseudogene, and unprocessed pseudogene. LogFC denotes Log Fold Change, LogCPM denoted Log Counts Per Million, and F denotes the F-statistic from edgeR’s quasi-likelihood pipeline. Table S10. Genes found to be significantly dysregulated by sleep deprivation using microarray and RNA-seq. We compared our RNA-seq data to a previously completed microarray sleep deprivation study (GEO accession GSE33302) and identified 226 genes with an FDR < 0.1 that were either upregulated or downregulated in both studies. All data within this table is from the RNA-seq study. LogFC denotes Log Fold Change, LogCPM denoted Log Counts Per Million, and F denotes the F-statistic from edgeR’s quasi-likelihood pipeline. Table S11. Comparison of differentially expressed genes after sleep deprivation between whole hippocampal transcriptome and TRAP-Seq from excitatory neurons. To identify the sleep deprivation transcriptome and translatome we compared RNA-seq and TRAP-Seq datasets. The first column shows 1035 differentially expressed genes only found using RNA sequencing, the second column shows 111 differentially expressed genes found in both RNA sequencing and TRAP-Seq, and the third column shows 154 differentially expressed genes only found using TRAP-Seq. Lists are sorted alphabetically. Table S12. Molecular function networks enriched in genes significantly affected by sleep deprivation in RNA-seq and TRAP-Seq data sets using GO:MF. We used Network Analyst software and the Gene Ontology (GO): Molecular Function (MF) classification to perform ORA and identified 18 networks enriched for genes differentially expressed using RNA-seq and TRAP-Seq. Hits represent the number of genes found in each network. Table S13. Molecular function networks for genes differentially regulated by sleep deprivation only in whole hippocampal transcriptome using GO:MF. We used Network Analyst software and the Gene Ontology (GO): Molecular Function (MF) classification to perform ORA and identified 27 networks enriched for genes only differentially expressed using RNA sequencing. Hits represent the number of genes found in each network. Table S14. Molecular function networks for genes differentially regulated by sleep deprivation only in the TRAP-Seq data set using GO:MF. We used Network Analyst software and the GO:MF classification to perform ORA and identified 12 networks enriched for genes differentially expressed using only TRAP-Seq. Hits represent the number of genes found in each network.