|
| Status |
Public on Jul 03, 2014 |
| Title |
Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and dKO round spermatids Transcriptomes |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by high throughput sequencing
|
| Summary |
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.
|
| |
|
| Overall design |
Adult wild type (WT) and dKO mouse round spermatids were generated by deep sequencing, in dulplicate, using Illumina GAIIx.
|
| |
|
| Contributor(s) |
Smith RA, Tang C, Yu T, Yan W |
| Citation missing |
Has this study been published? Please login to update or notify GEO. |
| Submission date |
Jul 02, 2014 |
| Last update date |
May 15, 2019 |
| Contact name |
Wei Yan |
| E-mail(s) |
wyan@medicine.nevada.edu
|
| Phone |
(775) 784-7765
|
| Organization name |
University of Nevada
|
| Department |
Physiology
|
| Lab |
Wei Yan Lab
|
| Street address |
1664 N. Virginia Street
|
| City |
reno |
| State/province |
NV |
| ZIP/Postal code |
89557 |
| Country |
USA |
| |
|
| Platforms (1) |
| GPL11002 |
Illumina Genome Analyzer IIx (Mus musculus) |
|
| Samples (4)
|
|
| Relations |
| BioProject |
PRJNA254123 |
| SRA |
SRP044007 |
Less...
More...