Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and L2hgdh-/- mice brain Transcriptomes
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE89806 | GEO | 2017/02/20
SECONDARY ACCESSION(S): PRJNA353363
REPOSITORIES: GEO
Similar Datasets
Project description:PurposeNext-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.MethodsRetinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl(-/-)) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows-Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT-PCR validation was performed using TaqMan and SYBR Green assays.ResultsUsing an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl(-/-) mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT-PCR. RNA-seq data had a linear relationship with qRT-PCR for more than four orders of magnitude and a goodness of fit (R(2)) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl(-/-) retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT-PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling.ConclusionsOur study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
| S-EPMC3233386 | biostudies-literature
Project description:Analysis the difference in the transcriptomes (expression and alternative splicing) of either spermatocytes or round spermatids between Larp7 conditional knock-out and control mice
2019-11-07 | GSE128832 | GEO
Project description:We analyzed the transcriptomic differences of cultured mouse spermatocytes (GC2 cells) stably transfected with PHB-targeting shRNA (called PHB KD GC2) from those with a control shRNA (called Ctrl GC2). Furthermore, we also analyzed the difference in the transcriptomes of spermatocytes between Phb conditional knock-out and control mice.
2020-04-02 | GSE140346 | 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 brain transcriptome profiling (RNA-seq) to reveal the difference of cellular pathways in adult brains of wild type (WT) and monocyte-depleted (CCR2-DTR) mice 8 days post infection of Trichinella spiralis. Methods: Illumina compatible RNAseq library was prepared using NEB next ultra RNAseq library preparation kit. The sequencing of the cDNA libraries was performed on the Illumina NextSeq platform (Illumina, San Diego, CA) using the high output 1X75 cycles configuration. CLC Genomics Workbench 11.0.1 version (http://www.clcbio.com/products/clc-genomics-workbench/ ; Qiagen) was used for RNA-seq analysis. De-multiplexed fastq files from RNA-Seq libraries are imported into the CLC software. Bases with low quality were trimmed and reads are mapped to reference genome Mus musculus genome GRCm38. The reference genome sequence and annotation files were downloaded from ENSEMBLE, release.92 (Mus_musculus.GRCm38.92.fa, and Mus_musculus.GRCm38.92.gtf). The aligned reads were obtained using the RNA-Seq Analysis Tool of CLC Genomics Workbench. Statistical analysis of differentially expressed genes is carried out based on a negative binomial model using a tool in CLC Genomic Workbench. The reference genome sequence and annotation files were downloaded from ENSEMBL, release.92 (Mus_musculus.GRCm38.92.fa, and Mus_musculus.GRCm38.92.gtf). The aligned reads were obtained using the RNA-Seq Analysis Tool of CLC Genomics Workbench. Results: Using an optimized data analysis workflow, we mapped over 50 million sequence reads per sample to the mouse genome (GRCm38) and found that Trichinella-infected mice depleted of monocytes presented with significantly increased expression of proinflammatory genes compared to controls.
2022-08-25 | GSE190493 | GEO
Project description:Conclusion: Otud1 knock out mice are less sensitive to DSS (Dextran sulfate) induced colitics
2021-11-07 | GSE140058 | GEO
Project description:We report the transcriptional difference of LATS1/2 gene knock out MCF-7 cells with wild type control using RNA-seq technology.
2021-01-23 | GSE134615 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare the brain of atrn wildtype and homozygous adult zebrafish 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: Total RNA was isolated from single brain of the wildtype and atrn-/- zebrafish using TRIzol reagent (Invitrogen) respectively by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Bioinformatics analysis of the transcriptome sequencing found that the steroid synthesis pathway was enriched in results of the mutant brain. By analyzing the data of male and female zebrafish with atrn mutations, it was found that the expression levels of related genes in the steroid synthesis pathway were up-regulated, mainly including the gene encoding the key enzyme for cholesterol synthesis, cyp51 and the gene encoding the key enzyme for testosterone synthesis, hsd17b7.
2021-12-08 | GSE178506 | 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 brain transcriptome. Methods: Brain mRNA profiles of 28-day-old wild-type (WT) and methyltransferase like 5 knockout (Mettl5−/−) mice were generated by using oligo(dT)-attached magnetic beads enrichemnt. The sequence reads that passed twice quality filters were analyzed at the transcript isoform level with Bowtie2 for quantitative gene analysis and with DEGseq for differentially expressed genes analysis. Results: 6 samples were tested by using the BGISEq-500 platform, and each sample produced 21.45 M data on average. The average ratio of samples to genomes (mm10) was over 96%; A total of 18,491 genes were detected.
2020-10-01 | GSE153138 | GEO
Project description:Purpose:Next-generation sequencing has revolutionized sytems-level celluar pathway analysis. The goals of this study are to compare the U87 cell xenograft GBM mice (U87 cell line) to TWIST1 knock out U87 cell xenograft GBM mice (TWIST1 knock out U87 cell line) using their transcriptomes
2018-05-01 | GSE106159 | 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: Retinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl-/-) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Retinal mRNA profiles of 21-day old wild type (WT) and Nrl-/- mice were generated by deep sequencing, in triplicate, using Illumina GAIIx.
2011-10-25 | E-GEOD-33141 | biostudies-arrayexpress