Data: Comprehensive transcriptome assessment in PBMCs of post-COVID patients at a median follow-up of 28 months following a mild COVID infection

<b>Overview</b>Clinical symptoms that persist for at least three months after infection by SARS-CoV-2, i.e. post-acute sequelae of SARS-CoV-2 (PASC), is an escalating global health problem. The mechanisms underlying post-COVID are still unclear, in particular there is a lack of large studies concerning patients with chronic symptoms persisting for several years after a mild COVID-19 infection. The aim of this study was to investigate possible molecular signatures and persistent SARS-CoV-2 gene fragments in patients with PASC up to 28 months after a mild infection.<br><b>Summary</b>We analyzed the gene expression profile in PBMCs from 60 middle-aged post-COVID patients and 50 age-matched controls, all of whom experienced a mild SARS-CoV-2 infections between March 2020 and February 2022. The uploaded data consist of count table and sample information and can be used for gene expression analysis of patients and controls.<br><b>Generation of Data</b>Sequencing libraries were prepared from 500ng/μg of polyA selected RNA using the TruSeq stranded mRNA library preparation kit (cat# 20020595, Illumina Inc.). Unique dual indexes (cat# 20022371, Illumina Inc.) were used. The library preparation was performed according to the manufacturers’ protocol (#1000000040498). Sequencing was performed using paired-end 150 bp read length on a NovaSeq X Plus system, 10B flow cell and XLEAP-SBS sequencing chemistry. Samples were analyzed with the nf-core RNA sequencing pipeline release 3.15.1 (nf-co.re/rnaseq). In brief, the pipeline processes raw data from FastQ inputs, aligns the reads, generates counts relative to genes or transcripts and performs extensive quality-control of results.<br><b>Data</b><i>Count Data:</i><i> </i>Samples were analyzed with the nf-core RNA sequencing pipeline release 3.15.1 (nf-co.re/rnaseq). In brief, the pipeline processes raw data from FastQ inputs, aligns the reads, generates counts relative to genes or transcripts and performs extensive quality-control of results.<i>Sample Data:</i> Information regarding SampleName, Sample and Condition