720a8bd9-b697-4c16-9025-e65664ccad6b - samples
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PROVIDER: EGAD00001008357 | EGA |
REPOSITORIES: EGA
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Project description:Purpose : Identification of the regulons directly and indirectly affected by the main regulators of flagellation in Shewanella putrefaciens CN-32 Methods : mRNA profiles were generated for Shewanella putrefaciens CN-32 samples by deep sequencing. The removal of ribosomal RNA was performed using the Ribo-Zero Bacteria Kit (Illumina) and cDNA libraries were generated with the ScriptSeq v2 Kit (Illumina) . The samples were sequenced in single end mode on an Illumina HiSeq 2500 device and mRNA reads were trimmed using the tool ‘cutadapt’ (version 3.5) with default settings and mapped to the NC_009438.1 (Shewanella putrefaciens CN-32) reference genome from NCBI using ‘bowtie2’ (version 2.3.5.1) with default settings for single-end sequencing.
2022-12-21 | GSE207531 | GEO
Project description:RNA-seq analysis was performed to understand the role of type I IFN response during SARS CoV-2 infection using transgenic mice. Each sample was collected from an individual C57BL/6J mouse. The total RNA was extracted from uninfected and SARS-CoV-2 infected mice lung tissue using RNeasy mini kit (QIAGEN #74104). The quantity of RNA was determined using Qubit RNA assay kit with Qubit 4.0 and the quality of RNA was tested using agarose gel electrophoresis and High Sensitivity Tape station Kit (Agilent 2200, #5067-5576, #5067-5577 and #5067-5578). After assessing the quality of RNA, ~900 ng of total RNA was taken for library preparation using NEBNext®Ultra™ II Directional RNA Library kit for Illumina (# E7760L) and NEBNext Poly (A) mRNA Magnetic Isolation Module (# E7490L) as per manufacturer's protocol. The prepared library was quantified using Qubit dsDNA assay kit (Invitrogen, Q32851) followed by quality check (QC) and fragment size distribution using a High Sensitivity Tape station Kit (Agilent 2200, #5067-5584 and #5067-5585). The library was sequenced using the HiSeq 4000 Illumina platform. The paired-end (PE) reads quality checks for each sample were carried out using FastQC v.0.11.5 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). The adapter sequence was trimmed using the BBDuk version 37.58 version 37.58 and the alignment was performed using STAR v.2.5.3a with default parameters with human hg38 genome build, gencode v21 gtf 9GRCh38) from the gencode. The duplicates were discarded using Picard-2.9.4 (https://broadinstitute.github.io/picard/) from the aligned bam files and read counts were generated using featureCount v.1.5.3 from subread-1.5.3 package (https://bioinf.wehi.edu.au/) with Q = 10 for mapping quality. The count files were used as input for downstream differential gene expression analysis with DESeq2 version 1.14.1 9. The genes with read counts of ≤ 10 in any comparison were discarded followed by count transformation and statistical analysis using DESeq “R”. The “P” value were adjusted using the Benjamini and Hochberg multiple testing correction and the differentially expressed genes were identified (fold change of ≥1.5, P-value < 0.05). A unified non-redundant gene list was made for different comparisons and subjected to gene ontology (GO) analysis using the reactome database (https://reactome.org/). The top pathways (p < 0.05) were used for generating heat maps using Complexheatmap (Version 2.0.0) through unsupervised hierarchical clustering. The expression clusters were annotated based on enriched GO terms. Normalized gene expression was used to generate the boxplots with a median depicting the trends in the expression across the different conditions using ggplot2 [version 3.3.5]. The pathways analysis was performed using Metascape database (https://metascape.org/gp/index.html#/main/step1). The top pathways (p < 0.05) were taken for constructing bubble plots using ggplot2 [version 3.3.5].
2023-12-29 | E-MTAB-12681 | biostudies-arrayexpress
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: RNA from 14-day-old seedlings of wild-type and pkl was isolated using the RNAprep Pure Plant Kit as described above. RNAs from three biological replicates was sequenced separately at Novogene, using Illumina Hiseq X-Ten (Sequencing method: Hiseq-PE150). Results: Reads were mapped to the TAIR10 Arabidopsis genome using TopHat (Galaxy V2.1.1 in usegalaxy.org) with default settings, except that a minimum intron length of 20 bp and a maximum intron length of 5,000 bp were required (Paired-end). Then, mapped reads were assembled according to TAIR10 version of genome annotation using cufflinks (version 2.1.1) with default settings. To analyze differential expression, the assembled transcripts from three independent biological replicates in Col and other mutants were included and compared using Cuffdiff (version 2.1.1) with default settings. 14-day-old seedling of WT and pkl were performed RNA-seq to analyzed their differential expression genes in Arabidopsis.
2022-12-12 | GSE186152 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: RNA from 14-day-old seedlings of wild-type and pkl was isolated using the RNAprep Pure Plant Kit as described above. RNAs from three biological replicates was sequenced separately at Novogene, using Illumina Hiseq X-Ten (Sequencing method: Hiseq-PE150). Results: Reads were mapped to the TAIR10 Arabidopsis genome using TopHat (Galaxy V2.1.1 in usegalaxy.org) with default settings, except that a minimum intron length of 20 bp and a maximum intron length of 5,000 bp were required (Paired-end). Then, mapped reads were assembled according to TAIR10 version of genome annotation using cufflinks (version 2.1.1) with default settings. To analyze differential expression, the assembled transcripts from three independent biological replicates in Col and other mutants were included and compared using Cuffdiff (version 2.1.1) with default settings. 14-day-old seedling of WT and val1 val2 pkl were performed RNA-seq to analyzed their differential expression genes in Arabidopsis.
2022-12-12 | GSE186156 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: RNA from 14-day-old seedlings of wild-type, brip1, brip2, brm-3, brm-1, brip1 brip2, brip1 brip2 brm-3 and brip1 brip2 brm-1 was isolated using the RNAprep Pure Plant Kit as described above. RNAs from three biological replicates was sequenced separately at Novogene, using Illumina Hiseq X-Ten (Sequencing method: Hiseq-PE150). Results: Reads were mapped to the TAIR10 Arabidopsis genome using TopHat (Galaxy V2.1.1 in usegalaxy.org) with default settings, except that a minimum intron length of 20 bp and a maximum intron length of 4,000 bp were required (Paired-end). Then, mapped reads were assembled according to TAIR10 version of genome annotation using cufflinks (version 2.1.1) with default settings. To analyze differential expression, the assembled transcripts from three independent biological replicates in Col and other mutants were included and compared using Cuffdiff (version 2.1.1) with default settings. Conclusions: Our study represents the first detailed analysis of brip1, brip2, brip1 brip2 transcriptomes, with biologic replicates, generated by RNA-seq technology.
2021-03-22 | GSE161516 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: RNA from 14-day-old seedlings of wild-type, brip1, brip2, brm-3, brm-1, brip1 brip2, brip1 brip2 brm-3 and brip1 brip2 brm-1 was isolated using the RNAprep Pure Plant Kit as described above. RNAs from three biological replicates was sequenced separately at Novogene, using Illumina Hiseq X-Ten (Sequencing method: Hiseq-PE150). Results: Reads were mapped to the TAIR10 Arabidopsis genome using TopHat (Galaxy V2.1.1 in usegalaxy.org) with default settings, except that a minimum intron length of 20 bp and a maximum intron length of 4,000 bp were required (Paired-end). Then, mapped reads were assembled according to TAIR10 version of genome annotation using cufflinks (version 2.1.1) with default settings. To analyze differential expression, the assembled transcripts from three independent biological replicates in Col and other mutants were included and compared using Cuffdiff (version 2.1.1) with default settings. Conclusions: Our study represents the first detailed analysis of brip1, brip2, brip1 brip2 transcriptomes, with biologic replicates, generated by RNA-seq technology.
2020-06-21 | GSE142622 | GEO
Project description:Purpose:To take a comprehensive effort in characterizing the brain vasculature gene expression upon hyperglycemia. Methods: We extracted mRNA from brain microvasculature fragments isolated from a genetic mouse model of hyperglycemia (Ins2-AKITA) and WT mice and analyzed their transcriptome with RNA sequencing The samples were sequenced on an Illumina HiSeq 2500 sequencer at the SNP&SEQ sequencing facility (Science for Life laboratory (SciLifeLab), Uppsala sequencing node). The reads were aligned to the Ensembl mouse gene assembly (NCBIM37) using Tophat2 software (version 2.0.4). The duplicated reads were removed using the picard tool (version 1.92). To identify the genes significantly enriched in the pericyte samples as compared with microvascular samples, statistical tests were performed using the Cufflinks tool (version 2.2.1) Results: Twenty-three genes were significantly regulated in mutant when compared to WT (False Discovery Rate < 0.05)
2018-12-11 | GSE113919 | GEO
Project description:Purpose:In order to assess the toxicity of AFB1 in chicken liver and the mechanism of curcumin alleviating AFB1-induced liver toxicity in chicken, we established a co-administered model to investigate LncRNA and mRNA profiles of chicken liver. Methods: RNA extracted by Total RNA Extractor (Trizol) was utilized to construct the final library. Libraries were pooled and sequenced on a 150-bp paired-end Illumina HiSeq™ 2000 run. The sequencing data obtained from Illumina Hiseq™ was filtered to get clean reads using Trimmomatic. The reads themselves and their matching reads which length was less than 35nt were removed. Clean reads were aligned to the reference sequence (Gallus_gallus-5.0, NCBI) using HISAT2. Results: Sampling directly from the liver yielded sufficient quantities of RNA to assess transcripts from each chicken and mapped to 24,883 Gallus gallus genes. Conclusions: We used the method of RNA-seq to find the target genes and related signaling pathways involved in the co-administered (AFB1 and curcumin) and their underlying mechanisms.
2022-04-02 | GSE148014 | GEO
Project description:The goals of this study are to use Next-generation sequencing (NGS)to detect bacterial mRNA profiles of E. coli K-12 LE392, P. putida KT2440 and Acinetobacter baylyi ADP1 in response to various antidepressant concentrations for 2 h, in triplicate, using Illumina HiSeq 2500.The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the E. coli reference genome (NC_000913), Pseudomonas putida KT2440 genome (NCBI:txid160488) and Acinetobacter baylyi ADP1 genome (NCBI:txid62977) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.
2022-08-03 | GSE181900 | GEO
Project description:Human nontransformed retinal pigment epithelia RPE-PPM1D-T2 cells carrying a truncating mutation in exon 6 of the PPM1D were exposed to ionising radiation (3 Gy) and subsequently were grown in semisolid media for 8 weeks. Six spheroid clones (RPE-PPM1D-T2-SA clones 1-6) were recovered and then were cultivated in adherent conditions. DNA was isolated from asynchronically growing parental RPE-PPM1D-T2 and transformed RPE-PPM1D-T2-SA-1 to 6 cells and was subjected to whole exome sequencing. DNA sequencing libraries were prepared using KAPA EvoPlus Kit (Roche) and were sequenced on the NovaSeq 6000 system using NovaSeq S1 Reagent Kit v1.5, 200 cycles (Illumina) with mean coverage >35 DNA samples, respectively. DNA fastq files were mapped to the hg19 reference using Novoalign (novoalign_2.08.03). PCR duplicates were removed from the BAM files using Picard Tools (picard-tools 1.129), and variant calling was performed using GATK HaplotypeCaller (3.8). Copy number variations (CNV) were analyzed using CNVkit version 0.7.4. Areas with median coverage >20 were included in the analysis. RNA fastq files were mapped to the hg19 reference using STAR (STAR-2.5.2b). The PCR duplicates were removed using Picard Tools (picard-tools 1.129).
2024-04-05 | E-MTAB-13923 | biostudies-arrayexpress