Protein domains provide a new layer of information for classifying human variations in rare diseases.

Introduction: Using the ACMG-AMP guidelines for the interpretation of sequence variants, it remains difficult to meet the criterion associated with the protein domain, PM1, which is assigned in only about 10% of cases, whereas the criteria related to variant frequency, PM2/BA1/BS1, is reported in 50% of cases. To improve the classification of human missense variants using protein domains information, we developed the DOLPHIN system (https://dolphin.mmg-gbit.eu). Methods: We used Pfam alignments of eukaryotes to define DOLPHIN scores to identify protein domain residues and variants that have a significant impact. In parallel, we enriched gnomAD variants frequencies for each domains' residue. These were validated using ClinVar data. Results: We applied this method to all potential human transcripts' variants, resulting in 30.0% being assigned a PM1 label, whereas 33.2% were eligible for a new benign support criterion, BP8. We also showed that DOLPHIN provides an extrapolated frequency for 31.8% of the variants, compared to the original frequency available in gnomAD for 7.6% of them. Discussion: Overall, DOLPHIN allows a simplified use of the PM1 criterion, an expanded application of the PM2/BS1 criteria and the creation of a new BP8 criterion. DOLPHIN could facilitate the classification of amino acid substitutions in protein domains that cover nearly 40% of proteins and represent the sites of most pathogenic variants.

TP53 mutations correlate with the non-coding RNA content of small extracellular vesicles in melanoma.

Non-coding RNAs (ncRNAs) are important regulators of gene expression. They are expressed not only in cells, but also in cell-derived extracellular vesicles (EVs). The mechanisms controlling their loading and sorting remain poorly understood. Here, we investigated the impact of TP53 mutations on the non-coding RNA content of small melanoma EVs. After purification of small EVs from six different patient-derived melanoma cell lines, we characterized them by small RNA sequencing and lncRNA microarray analysis. We found that TP53 mutations are associated with a specific micro and long non-coding RNA content in small EVs. Then, we showed that long and small non-coding RNAs enriched in TP53 mutant small EVs share a common sequence motif, highly similar to the RNA-binding motif of Sam68, a protein interacting with hnRNP proteins. This protein thus may be an interesting partner of p53, involved in the expression and loading of the ncRNAs. To conclude, our data support the existence of cellular mechanisms associate with TP53 mutations which control the ncRNA content of small EVs in melanoma.