Genome Alert!: A standardized procedure for genomic variant reinterpretation and automated gene-phenotype reassessment in clinical routine.

PURPOSE: Retrospective interpretation of sequenced data in light of the current literature is a major concern of the field. Such reinterpretation is manual and both human resources and variable operating procedures are the main bottlenecks. METHODS: Genome Alert! method automatically reports changes with potential clinical significance in variant classification between releases of the ClinVar database. Using ClinVar submissions across time, this method assigns validity category to gene-disease associations. RESULTS: Between July 2017 and December 2019, the retrospective analysis of ClinVar submissions revealed a monthly median of 1247 changes in variant classification with potential clinical significance and 23 new gene-disease associations. Re-examination of 4929 targeted sequencing files highlighted 45 changes in variant classification, and of these classifications, 89% were expert validated, leading to 4 additional diagnoses. Genome Alert! gene-disease association catalog provided 75 high-confidence associations not available in the OMIM morbid list; of which, 20% became available in OMIM morbid list For more than 356 negative exome sequencing data that were reannotated for variants in these 75 genes, this elective approach led to a new diagnosis. CONCLUSION: Genome Alert! (https://genomealert.univ-grenoble-alpes.fr/) enables systematic and reproducible reinterpretation of acquired sequencing data in a clinical routine with limited human resource effect.

Coil conversion to ß-strand induced by dimerization.

Most molecular processes in living organisms rely on protein-protein interactions, many of which are mediated by ß-sheet interfaces; this study investigates the formation of ß-sheet interfaces through the conversion of coils into ß-strands. Following an exhaustive search in the Protein Data Bank, the corresponding structural dimorphic fragments were extracted, characterized, and analyzed. Their short strand lengths and specific amino acid profiles indicate that dimorphic ß-strand interfaces are likely to be less stable than standard ones and could even convert to coil interfaces if their environment changes. Moreover, the construction of a simple classifier able to discriminate between the sequences of dimorphic and standard ß-strand interfaces suggests that the nature of those dimorphic sequences could be predicted, providing a novel means of identifying proteins capable of forming dimers.