Project description:The SARS-CoV-2 outbreak started on December 2019 in China and rapidly spread worldwide. Clinical manifestations of Coronavirus-disease 2019 (COVID-19) vary broadly, ranging from asymptomatic infection to acute respiratory failure and death, yet the underlying mechanisms and predictive biomarkers for this high variability are still unknown. Emerging evidence has shown that circulating extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of physiologic and pathologic processes. To test the hypothesis that these extracellular components are a key determinant of severity in COVID-19, we collected 31 serum samples from mild COVID-19 patients at admission in single center. After standard therapy without corticosteroids, 9 of 31 patients became severe COVID-19. We analyzed exRNA profiles from the 31 serums and 10 healthy controls for predicting COVID-19 severity value.
Project description:Genomic DNA from 191 asy1/+ Col x Ler F2 individuals was extracted using CTAB and used to generate sequencing libraries as described (Lawrence et al, 2019 Current Biology). Sequencing data was analysed to identify crossovers using the TIGER pipeline as previously described (Rowan et al, 2015 G3 (Bethesda); Yelina et al, 2015 Genes & Dev; Lawrence et al, 2019 Current Biology).
Project description:Genomic DNA from 187 wild type and 169 asy1 Col-0 x Ws-4 F2 individuals was extracted using CTAB and used to generate sequencing libraries as described (Lawrence et al, 2019 Current Biology). Sequencing data was analysed to identify crossovers using the TIGER pipeline as previously described (Rowan et al, 2015 G3 (Bethesda); Yelina et al, 2015 Genes & Dev; Lawrence et al, 2019 Current Biology).
