Pluto Biosciences, Inc

GSE153512: Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and METTL14 KO bone marrow-derived macrophages(BMDM) Transcriptomes

Bulk RNA sequencing

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived BMDM transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRTPCR) methods and to evaluate protocols for optimal high-throughput data analysis; Methods: BMDM mRNA profiles of 6-week-old wild-type (WT) and METTL14 knockout (M14/) mice with or without LPS treatment were generated by deep sequencing, in triplicate, using Illumina Hi-Seq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: BurrowsWheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRTPCR validation was performed using TaqMan and SYBR Green assays; Results: Using an optimized data analysis workflow, we mapped about 20 million sequence reads per sample to the mouse genome (build mm9) and identified 11,902 transcripts in WT and M14/ BMDMs with BWA workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRTPCR. RNA-seq data had a linear relationship with qRTPCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 20% of the transcripts showed differential expression between the WT and M14/ BMDMs, with a fold change 1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRTPCR, 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 BMDM 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 BMDM 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. SOURCE: Jie Du (jdu3@uchicago.edu) - University of Chicago

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