Microarray dataset on the genome-wide expression profile of an M. smegmatis amtR mutant (JR258) compared to M. smegmatis mc2155

Transcriptome sequencing to explore the effect of miR-214 on chicken primary myoblasts

MicroRNAs are involved in a series of biological processes, such as proliferation, differentiation and apoptosis of primary myoblasts. The research group found that miR-214 is highly expressed in chicken primary myoblasts (CPMs), so we used miR-214 as a starting point to explore the biological function of miR-214 in skeletal muscle growth and development. In this experiment, CPMs were cultured in vitro; miR-214 was overexpressed in CPMs; and cell samples were collected for subsequent transcriptome sequencing (RNA-seq). After miR-214 overexpression, we identified 97 differentially expressed genes (DEGs), of which 21 DEGs were up-regulated and 76 DEGs were down-regulated. After bioinformatics analysis, these DEGs were found to be significantly enriched in myofibrils, muscle system processes, myofibril assembly and other biological processes related to muscle development. The significantly enriched KEGGs include focal adhesion and type II diabetes mellitus. The protein network of DEGs was drawn by STRING and Cytoscape software, and 5 DEGs were randomly selected to verify the sequencing results by real-time fluorescence quantification. CAV3 is not only an important node protein in the protein network but also a member of the focal adhesion signaling pathway. It is speculated that miR-214 may regulate muscle development through the focal adhesion signaling pathway.

Correlation between RNA-Seq and microarrays results using TCGA data

RNA sequencing (RNA-Seq) and microarray are two of the most commonly used high-throughput technologies for transcriptome profiling; however, they both have their own inherent strengths and limitations. This research aims to analyze the correlation between microarrays and RNA-Seq detection of transcripts in the same tissue sample to explore the reproducibility between the techniques. Using data of RNA-Seq v2 and three different microarrays provided by The Cancer Genome Atlas, 11,120 genes of 111 lung squamous cell carcinoma samples were simultaneously detected by the four methods. Then we analyzed the Pearson correlation between microarrays and RNA-Seq. Finally, in the six comparison results, 9984 (89.8%) genes, irrespective of which two methods were used, simultaneously showed the existence of correlation, whereas only 83 (0.1%) genes proved to have no significant correlation in either comparison. In addition, the comparisons between 3266 (29.3%) genes showed high correlation (R≥0.8) in all six comparisons, only for 1643 (14.8%) genes correlation were not as high in either comparison. Meanwhile, transcripts with extreme high or low expression levels were more highly discrepant across the methods. In conclusion, we found that, for most transcripts, the results obtained by RNA-Seq and microarrays were highly reproducible.