DOI: 10.57760/sciencedb.27341
title: RNA-Seq rawdata of different tissues from Drosophila under sleep deprivation (SD).
title: RNA-Seq rawdata of different tissues from Drosophila under sleep deprivation (SD).

description: Aims and Methods:To identify the potential genes or pathways involved in ROS generation following 1-d SD, we collected tissues containing the head and gut from WT Drosophila for RNA sequencing (RNA-seq). And to gain more insights into the processes involved in RET-ROS and humoral response of hemocytes during SD, we conducted RNA-seq of hemocytes harvested from non-SD and 1-day SD groups.  Hemocyte samples were collected from approximately 60 adult female flies (Figure 5E). For hemocyte isolation, 20 flies were loaded onto a 30 μm filter in a Mobicol spin column (MOBITEC), covered with glass beads, and centrifuged at 10,000 rpm for 20 min at 4°C. This procedure was repeated twice using a total of 40 flies, with recovered hemolymph pooled in 300 μl TRIzol reagent. Head-gut samples consisted of 50 head-gut complexes in 500 μl TRIzol (Figure 2A).          Total RNA was extracted using the UNlQ-10 Column Trizol Total RNA Isolation Kit (Sangon Biotech) followed by DNaseI (BBI) treatment. RNA purification employed Oligo dT magnetic beads, with final samples stored at -80°C until analysis. For RNA-seq, cDNA libraries were prepared with the Illumina TruSeq stranded mRNA library prep kit and sequenced on an Illumina platform using paired-end (PE) sequencing. Raw reads were processed to obtain clean reads by removing contaminants, duplicates, and low-quality sequences. Transcriptome analysis included: (1) quality control, (2) alignment analysis, and (3) in-depth annotation including Multi-platform Gene Ontology (GO). Differential expression was determined using volcano plot filtering |log2-fold change| ≥ 0.58 (≥1.5-fold changes) and false discovery rate (FDR) &lt; 0.05.Files: The file names started with Non-SD or SD are the data file from hemocytes (12 files in total, with 6 Non-SD and 6 SD samples), while the others are from head+gut tissues (12 files in total, with 6 Non-SD and 6 SD samples). Software: Initially, in the quality control (QC) phase, Cutadapt (version V1.9.1) and FastQC (version V0.10.1) are employed. Moving on to the mapping stage, HISAT2 (version V2.2.1) is used for sequence alignment. Gene expression analysis is conducted with HTSEQ (version V0.6.1). Transcript assembly is performed using Stringtie (version V1.3.3b). For differential expression analysis, three different software tools are utilized: DESeq2 (version V1.26.0), DESeq (version V1.38.0), and EdgeR (version V3.28.1). Additionally, Cuffdiff (version V2.2.1) is also employed for this analysis. Finally, in the GO enrichment analysis, GOSeq (version V1.34.1) and TopGO (version V2.18.0) are the software tools used.
description: Aims and Methods:To identify the potential genes or pathways involved in ROS generation following 1-d SD, we collected tissues containing the head and gut from WT Drosophila for RNA sequencing (RNA-seq). And to gain more insights into the processes involved in RET-ROS and humoral response of hemocytes during SD, we conducted RNA-seq of hemocytes harvested from non-SD and 1-day SD groups.  Hemocyte samples were collected from approximately 60 adult female flies (Figure 5E). For hemocyte isolation, 20 flies were loaded onto a 30 μm filter in a Mobicol spin column (MOBITEC), covered with glass beads, and centrifuged at 10,000 rpm for 20 min at 4°C. This procedure was repeated twice using a total of 40 flies, with recovered hemolymph pooled in 300 μl TRIzol reagent. Head-gut samples consisted of 50 head-gut complexes in 500 μl TRIzol (Figure 2A).          Total RNA was extracted using the UNlQ-10 Column Trizol Total RNA Isolation Kit (Sangon Biotech) followed by DNaseI (BBI) treatment. RNA purification employed Oligo dT magnetic beads, with final samples stored at -80°C until analysis. For RNA-seq, cDNA libraries were prepared with the Illumina TruSeq stranded mRNA library prep kit and sequenced on an Illumina platform using paired-end (PE) sequencing. Raw reads were processed to obtain clean reads by removing contaminants, duplicates, and low-quality sequences. Transcriptome analysis included: (1) quality control, (2) alignment analysis, and (3) in-depth annotation including Multi-platform Gene Ontology (GO). Differential expression was determined using volcano plot filtering |log2-fold change| ≥ 0.58 (≥1.5-fold changes) and false discovery rate (FDR) &lt; 0.05.Files: The file names started with Non-SD or SD are the data file from hemocytes (12 files in total, with 6 Non-SD and 6 SD samples), while the others are from head+gut tissues (12 files in total, with 6 Non-SD and 6 SD samples). Software: Initially, in the quality control (QC) phase, Cutadapt (version V1.9.1) and FastQC (version V0.10.1) are employed. Moving on to the mapping stage, HISAT2 (version V2.2.1) is used for sequence alignment. Gene expression analysis is conducted with HTSEQ (version V0.6.1). Transcript assembly is performed using Stringtie (version V1.3.3b). For differential expression analysis, three different software tools are utilized: DESeq2 (version V1.26.0), DESeq (version V1.38.0), and EdgeR (version V3.28.1). Additionally, Cuffdiff (version V2.2.1) is also employed for this analysis. Finally, in the GO enrichment analysis, GOSeq (version V1.34.1) and TopGO (version V2.18.0) are the software tools used.