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PNAS Papers on Coronavirus Pathogenicity, RNA Modification-Related Mutations, PRDD-Seq

Editor's Note: Some of the articles described below are not yet available at the PNAS site, but they are scheduled to be posted some time this week.

Researchers from the National Institutes of Health, the Broad Institute, and elsewhere share findings from a machine learning and comparative genomics-based search for features associated with enhanced case fatality rates among coronaviruses such as SARS-CoV-2 and MERS-CoV compared to hundreds of other coronaviruses sequenced previously. The team notes that the particularly pathogenic, "high case fatality rate" coronavirus genomes contained changes affecting the receptor protein-interacting spike protein and the nuclear localization capability of the nucleocapsid protein, hinting that these regions may contribute to pathogenicity in these coronaviruses and others that may appear in the future. GenomeWeb has more on the study, here.

In a paper slated to appear in PNAS this week, an international team led by investigators in Hungary describe a multi-system syndrome found in members of two families affected by mutations in DKC1 or NOP10 — two of the four genes that code for components of the RNA modifying snoRNP complex, which is involved in the pseudouridylation of RNA. Using exome sequencing, linkage disequilibrium, and other analyses, the researchers uncovered DKC1 and NOP10 mutations in affected members of two families with kidney, eye, gastrointestinal, and hearing symptoms. Through follow-up analyses and experiments in zebrafish, they found evidence that these snoRNP complex alterations fell at a conserved site affecting a conserved pseudouridylation catalytic site in the complex, apparently leading to downstream ribosomal defects stemming from ribosomal RNA modification changes. 

Finally, investigators from Boston Children's Hospital, Harvard, the Broad, and elsewhere introduce a "parallel RNA and DNA analysis after deep sequencing" (PRDD-seq) method for profiling expression and somatic mutation patterns in individual cells — an approach they used to retrace the formation and divergence of excitatory and inhibitory neurons from progenitor cell types in post-mortem brain samples from two individuals. The PRDD-seq strategy "combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single-cell and bulk DNA sequencing by single-cell MosaicHunter," the team explains, noting that the sequencing method "can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition."