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Neuronal migration disorders are a clinically and genetically heterogeneous group of malformations of cortical development, frequently responsible for severe disability. Despite the increasing knowledge of the molecular mechanisms underlying this group of diseases, their genetic diagnosis remains unattainable in a high proportion of cases. Here, we present the results of 38 patients with lissencephaly, periventricular heterotopia and subcortical band heterotopia from Argentina. We performed Sanger and Next Generation Sequencing (NGS) of DCX, FLNA and ARX and searched for copy number variations by MLPA in PAFAH1B1, DCX, POMT1, and POMGNT1. Additionally, somatic mosaicism at 5% or higher was investigated by means of targeted high coverage NGS of DCX, ARX, and PAFAH1B1. Our approach had a diagnostic yield of 36%. Pathogenic or likely pathogenic variants were identified in 14 patients, including 10 germline (five novel) and 4 somatic mutations in FLNA, DCX, ARX and PAFAH1B1 genes. This study represents the largest series of patients comprehensively characterized in our population. Our findings reinforce the importance of somatic mutations in the pathophysiology and diagnosis of neuronal migration disorders and contribute to expand their phenotype-genotype correlations.

Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Despite the existence of several bioinformatic algorithms and servers that predict if a SAS is pathogenic or not, they give little or no information at all on the reasons for pathogenicity prediction and on the actual predicted effect of the SAS on the protein function. Moreover, few actual methods take into account structural information when available for automated analysis. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ is a bioinformatic pipeline that incorporates structural information for the detailed analysis and prediction of SAS effect on protein function. It is an online tool which uses UniProt id and automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions, among others. We show that structural information, when available, can improve the SAS pathogenicity diagnosis and more important explain its causes. We show that VarQ is able to correctly reproduce previous analysis of RASopathies related mutations, saving extensive and time consuming manual curation. VarQ assessment was performed over a set of previously manually curated RASopathies (diseases that affects the RAS/MAPK signaling pathway) related variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/. Supporting Information & Tutorials may be found in the webpage of the tool.