Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and L3mbtl2 cKO Testicular Transcriptomes
Ontology highlight
ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE109921 | GEO | 2018/08/01
REPOSITORIES: GEO
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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 femoral diaphysis and metaphysis transcriptome profiling (RNA-seq) to determine pathways and networks dependent on Dlx3 during bone development and homeostasis. Methods: mRNA profiles of diaphysis and metaphysis isolated from the femur of 5-week-old wild-type (WT) and Dlx3Oc-cKO (OC-cre;Dlx3f/-) conditional knockout mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level by ANOVA (ANOVA) and TopHat. qRT-PCR validation was performed using SYBR Green assay. Results: RNA-Seq data were generated with Illumina's HiSeq 2000 system. Raw sequencing data were processed with CASAVA 1.8.2 to generate fastq files. Reads of 50 bases were mapped to the mouse transcriptome and genome mm9 using TopHat 1.3.2. Gene expression values (RPKM) were calculated with Partek Genomics Suite 6.6, which was also used for the ANOVA analysis to determine significantly differentially expressed genes. Conclusions: Our study represents the first detailed analysis of Dlx3Oc-cKO diaphysis and metaphysis from femurs, with biologic triplicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Diaphysis and metaphysis mRNA profiles of metaphysis and diaphysis from femurs of 5-wk-old (WT) and Dlx3Oc-cKO male mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000.
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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 WT and dKO round spermatids transcriptome profiling (RNA-seq) Methods: Adult WT and dKO round spermatids mRNA profiles mice were generated by deep sequencing, in dulplicate. 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 dKO round spermatids, 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. Adult wild type (WT) and dKO mouse round spermatids were generated by deep sequencing, in dulplicate, using Illumina GAIIx.
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