An RNA-immunoprecipitation via CRISPR/dCas13 reveals an interaction between the SARS-CoV-2 5'UTR RNA and the process of human lipid metabolism.

We herein elucidate the function of SARS-CoV-2derived 5'UTR in the human cells. 5'UTR bound host cellular RNAs were immunoprecipitated by gRNA-dCas13 (targeting luciferase RNA fused to SARS-CoV-2 5'UTR) in HEK293T and A549 cells. The 5'UTR bound RNA extractions were predominantly enriched for regulating lipid metabolism. Overexpression of SARS-CoV-2 5'UTR RNA altered the expression of factors involved in the process of the human Mevalonate pathway. In addition, we found that HMG-CoA reductase inhibitors were shown to suppress SARS-CoV-2 5'UTR-mediated translation activities. In conclusion, we deduce the array of host RNAs interacting with SARS-CoV-2 5'UTR that drives SARS-CoV-2 translation and influences host metabolic pathways.

An efficient and high-throughput approach for experimental validation of novel human gene predictions.

A highly automated RT-PCR-based approach has been established to validate novel human gene predictions with no prior experimental evidence of mRNA splicing (ab initio predictions). Ab initio gene predictions were selected for high-throughput validation using predicted protein classification, sequence similarity to other genomes, colocalization with an MPSS tag, or microarray expression. Initial microarray prioritization followed by RT-PCR validation was the most efficient combination, resulting in approximately 35% of the ab initio predictions being validated by RT-PCR. Of the 7252 novel genes that were prioritized and processed, 796 constituted real transcripts. In addition, high-throughput RACE successfully extended the 5' and/or 3' ends of >60% of RT-PCR-validated genes. Reevaluation of these transcripts produced 574 novel transcripts using RefSeq as a reference. RT-PCR sequencing in combination with RACE on ab initio gene predictions could be used to define the transcriptome across all species.