PLX211032

GSE85214: MicroRNAs underlie genome-wide transcriptome and translatome regulation in asthma as revealed by Frac-seq (RNA-Seq)

• Organsim human
• Type RNASEQ
• Target gene
• Project ARCHS4

Transcription and translation correlate poorly, as mRNA undergoes multiple regulatory steps such as alternative splicing and microRNA regulation that determine its translationability into protein. Measures of transcriptional mRNA levels may therefore misrepresent cellular activation. To test this hypothesis employing human physiological mRNA levels, we analyzed cytoplasmic and polyribosome-bound mRNA expression (Frac-seq) combined with microRNA profiling by small RNA-seq in bronchoepithelial cells from healthy and severe asthma (SA) donors, SA being a chronic inflammatory airways disease, poorly understood at the molecular level. We found 275 genes bound to polyribosomes differentially between healthy and severe asthma, of which only 11.64% overlapped with differentially expressed cytoplasmic mRNAs (226 genes). We found 335 alternatively spliced mRNA isoforms differentially bound to polyribosomes of which only ~8% were revealed by cytoplasmic mRNA analysis. Approximately two thirds of differentially expressed isoforms could not be found at the gene level in both cytoplasmic and polyribosome bound fractions, demonstrating the disruption of splicing in asthma. Only the analysis of differentially expressed isoforms bound to polyribosomes revealed disease-related pathways overlooked in total mRNA. We detected a network of 21 microRNAs differentially expressed, with 8 microRNAs accounting for more than 80% targeting observed in both cytoplasmic and polyribosome bound mRNA isoforms. Importantly, microRNAs target distinct cytoplasmic and polyribosome bound mRNAs. Hence this work, integrating deep-sequencing, subcellular fractionation and microRNA profiling, demonstrates the disruption of post-transcriptional regulatory processes as the main disease causing molecular mechanism in asthma, something that cannot be dissected employing more classic transcriptomics approaches alone. SOURCE: Rocio Teresa Martinez-Nunez (rocio.martinez_nunez@kcl.ac.uk) - Rocio T Martinez-Nunez King's College London