Stability and Motif Analysis of RNA-Seq Reads from COVID-19 Patients

RNA Sequencing (RNA-Seq) can facilitate prompt and precise management of many illnesses, including infection, especially when coupled with PCR. To further optimize RNA-Seq for the purposes of creating a RNA-Seq-informed PCR test, identifying reliable RNA primer targets is paramount. Essential criteria for constructing RNA primer targets include high gene expression or stability of transcripts. We hypothesize that free energy evaluation and motif analysis can demonstrate gene expression level or stability of transcripts to construct ideal RNA primers for RNA-Seq-informed PCR that can expedite the diagnosis and treatment of infection. Whole blood samples were collected from patients diagnosed with COVID-19 in the ICU at Rhode Island Hospital, stored in Paxgene tubes to preserve the integrity of the specimens, and submitted for RNA-Seq by a commercial sequencing service (Azenta/Genewiz). After quality assurance and quality control (QA/QC) measures are performed, we used RNAfold from the ViennaRNA Package to calculate the minimum free energy (MFE) and ensemble free energy (EFE) values to compare the stability among different secondary structures constructed from RNA-Seq read sequences. Energy parameters for calculations were set at 37 degree Celsius and standard physiological conditions at pH 7.4. In our analysis, we utilized multiple statistical tools, such as analysis of variance, Games-Howell post hoc tests, and a negative binomial regression. Of the 676 reads that aligned with SARS-CoV-2, there were 137 unique sequences among all patients. Among the unique read sequences, the average MFE was -30.46 kcal/mol and the average EFE was -32.94 in kcal/mol. There were 6 genes with these unique read sequences, two of which -- nucleocapsid ( N ) gene and spike ( S ) gene -- coded for integral structural proteins. Notably, the mean MFE and EFE of N gene were significantly different from ORF1ab gene (p = 2.81e-7; p = 0.005) and ORF6 gene (p = 0.023; p = 0.03). Our motif analysis demonstrated 7 motifs that corresponded to destabilization of the RNA, and a single motif (MEME-28) that corresponded to stabilization of the RNA. Within the nucleocapsid ( N ) gene, we found that reads from different regions also differed in stability. Our results demonstrate that the stability of reads from different genes varies in SARS-CoV-2 infections. Free energy evaluation and motif analysis are viable approaches to determine RNA structure stability or levels of differential gene expression. Stable transcripts that are highly expressed can be ideal RNA primers to be used in conjunction with PCR to expedite the management of infection.