Powell, R. | bioRxiv Science

bioRxiv2021

3D genomic capture of regulatory immuno-genetic profiles in COVID-19 patients for prognosis of severe COVID disease outcome

Human infection with the SARS-CoV-2 virus leads to coronavirus disease (COVID-19). A striking characteristic of COVID-19 infection in humans is the highly variable host response and the diverse clinical outcomes, ranging from clinically asymptomatic to severe immune reactions leading to hospitalization and death. Here we used a 3D genomic approach to analyse blood samples at the time of COVID diagnosis, from a global cohort of 80 COVID-19 patients, with different degrees of clinical disease outcomes. Using 3D whole genome EpiSwitch(R) arrays to generate over 1 million data points per patient, we identified a distinct and measurable set of differences in genomic organization at immune-related loci that demonstrated prognostic power at baseline to stratify patients with mild forms of illness and those with severe forms that required hospitalization and intensive care unit (ICU) support. Further analysis revealed both well established and new COVID-related dysregulated pathways and loci, including innate and adaptive immunity; ACE2; olfactory, G{beta}{psi}, Ca2+ and nitric oxide (NO) signalling; prostaglandin E2 (PGE2), the acute inflammatory cytokine CCL3, and the T-cell derived chemotactic cytokine CCL5. We identified potential therapeutic agents for mitigation of severe disease outcome, with several already being tested independently, including mTOR inhibitors (rapamycin and tacrolimus) and general immunosuppressants (dexamethasone and hydrocortisone). Machine learning algorithms based on established EpiSwitch(R) methodology further identified a subset of 3D genomic changes that could be used as prognostic molecular biomarker leads for the development of a COVID-19 disease severity test.

biochemistry↗

bioRxiv2020

Physiological diversity enhanced by recurrent divergence and secondary gene flow within a grass species

O_LIC4 photosynthesis evolved multiple times independently in angiosperms, but most origins are relatively old so that the early events linked to photosynthetic diversification are blurred. The grass Alloteropsis semialata is an exception, as this single species encompasses C4 and non-C4 populations. C_LIO_LIUsing phylogenomics and population genomics, we infer the history of dispersal and secondary exchanges before, during, and after photosynthetic divergence in A. semialata. We further establish the genetic origins of polyploids in this species. C_LIO_LIOrganelle phylogenies indicate limited seed dispersal within the Central Zambezian region of Africa, where the species originated [~] 2-3 Ma. Outside this region, the species spread rapidly across the paleotropics to Australia. Comparison of nuclear and organelle phylogenies and analyses of whole genomes reveal extensive secondary gene flow. In particular, the genomic group corresponding to the C4 trait was swept into seeds from distinct geographic regions. Multiple segmental allopolyploidy events mediated additional secondary genetic exchanges between photosynthetic types. C_LIO_LILimited dispersal and isolation allowed lineage divergence, while episodic secondary exchanges led to the pollen-mediated, rapid spread of the derived C4 physiology. Overall, our study suggests that local adaptation followed by recurrent secondary gene flow promoted physiological diversification in this grass species. C_LI

evolutionary biology↗