GenesGenetic & Genomic MedicinePeer-reviewed journal article
Poking COVID-19: insights on genomic constraints among immune-related genes between Qatari and Italian populations
Hamdi MbarekiD, Massimiliano CoccaiD, Yasser A. Al-SarrajiD, Chadi SaadiD, Massimo MezzavillaiD, Wadha Al‐MuftahiD, Dario CocciadiferroiD, Antonio NovelliiD, Isabella QuintiiD, Azza Al-Tawashi, Salvino A. SalvaggioiD, Asma Al-ThaniiD, Giuseppe NovelliiD, Said I. IsmailiD
Abstract
Host genomic information, specifically genomic variations, may characterize susceptibility to disease and identify people with a higher risk of harm, leading to better targeting of care and vaccination. Italy was the epicentre for the spread of COVID-19 in Europe, the first country to go into a national lockdown and has one of the highest COVID-19 associated mortality rates. Qatar, on the other hand has a very low mortality rate. In this study, we compared whole-genome sequencing data of 14398 adults and Qatari-national to 925 Italian individuals. We also included in the comparison whole-exome sequence data from 189 Italian laboratory confirmed COVID-19 cases. We focused our study on a curated list of 3619 candidate genes involved in innate immunity and host-pathogen interaction. Two population-gene metric scores, the Delta Singleton-Cohort variant score (DSC) and Sum Singleton-Cohort variant score (SSC), were applied to estimate the presence of selective constraints in the Qatari population and in the Italian cohorts. Results based on DSC SSC metrics demonstrated a different selective pressure on three genes (MUC5AC, ABCA7, FLNA) between Qatari and Italian populations. This study highlighted the genetic differences between Qatari and Italian populations and identified a subset of genes involved in innate immunity and host-pathogen interaction.
- organism: human
- assay: whole-genome sequencing
- assay: whole-exome sequencing
- research focus: differential expression
- research focus: variant effect prediction
- research focus: gene regulatory network inference
- research focus: benchmarking
- approach: statistical model
- Citations
- 3
- FWCI
- 0.28
- Field percentile
- top 46%
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