DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins.

High-throughput sequencing methods are generating enormous amounts of genomic data, giving unprecedented insights into human genetic variation and its relation to disease. An individual human genome contains millions of Single Nucleotide Variants: to discriminate the deleterious from the benign ones, a variety of methods have been developed that predict whether a protein-coding variant likely affects the carrier individual's health. We present such a method, DEOGEN2, which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates. This extensive contextual information is non-linearly mapped into one single deleteriousness score for each variant. Since for the non-expert user it is sometimes still difficult to assess what this score means, how it relates to the encoded protein, and where it originates from, we developed an interactive online framework (http://deogen2.mutaframe.com/) to better present the DEOGEN2 deleteriousness predictions of all possible variants in all human proteins. The prediction is visualized so both expert and non-expert users can gain insights into the meaning, protein context and origins of each prediction.

Bi-allelic variants in COL3A1 encoding the ligand to GPR56 are associated with cobblestone-like cortical malformation, white matter changes and cerebellar cysts.

BACKGROUND: Collagens are one of the major constituents of the pial membrane, which plays a crucial role in neuronal migration and cortical lamination during brain development. Type III procollagen, the chains of which are encoded by COL3A1, is the ligand of the G protein-coupled receptor 56 (GPR56), also known as adhesion G protein-coupled receptor G1. Bi-allelic mutations in GPR56 give rise to cobblestone-like malformation, white matter changes and cerebellar dysplasia. This report shows that bi-allelic mutations in COL3A1 are associated with a similar phenotype. METHODS: Exome analysis was performed in a family consisting of two affected and two non-affected siblings. Brain imaging studies of this family and of two previously reported individuals with bi-allelic mutations in COL3A1 were reviewed. Functional assays were performed on dermal fibroblasts. RESULTS: Exome analysis revealed a novel homozygous variant c.145C>G (p.Pro49Ala) in exon 2 of COL3A1. Brain MRI in the affected siblings as well as in the two previously reported individuals with bi-allelic COL3A1 mutations showed a brain phenotype similar to that associated with mutations in GPR56. CONCLUSION: Homozygous or compound heterozygous mutations in COL3A1 are associated with cobblestone-like malformation in all three families reported to date. The variability of the phenotype across patients suggests that genetic alterations in distinct domains of type III procollagen can lead to different outcomes. The presence of cobblestone-like malformation in patients with bi-allelic COL3A1 mutations emphasises the critical role of the type III collagen-GPR56 axis and the pial membrane in the regulation of brain development and cortical lamination.

I-PV: a CIRCOS module for interactive protein sequence visualization.

SUMMARY: Today's genome browsers and protein databanks supply vast amounts of information about proteins. The challenge is to concisely bring together this information in an interactive and easy to generate format. AVAILABILITY AND IMPLEMENTATION: We have developed an interactive CIRCOS module called i-PV to visualize user supplied protein sequence, conservation and SNV data in a live presentable format. I-PV can be downloaded from http://www.i-pv.org. CONTACT: ibrahim.tanyalcin@i-pv.org, itanyalc@vub.ac.be or support@i-pv.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Convert your favorite protein modeling program into a mutation predictor: "MODICT".

BACKGROUND: Predict whether a mutation is deleterious based on the custom 3D model of a protein. RESULTS: We have developed MODICT, a mutation prediction tool which is based on per residue RMSD (root mean square deviation) values of superimposed 3D protein models. Our mathematical algorithm was tested for 42 described mutations in multiple genes including renin (REN), beta-tubulin (TUBB2B), biotinidase (BTD), sphingomyelin phosphodiesterase-1 (SMPD1), phenylalanine hydroxylase (PAH) and medium chain Acyl-Coa dehydrogenase (ACADM). Moreover, MODICT scores corresponded to experimentally verified residual enzyme activities in mutated biotinidase, phenylalanine hydroxylase and medium chain Acyl-CoA dehydrogenase. Several commercially available prediction algorithms were tested and results were compared. The MODICT PERL package and the manual can be downloaded from https://github.com/IbrahimTanyalcin/MODICT . CONCLUSIONS: We show here that MODICT is capable tool for mutation effect prediction at the protein level, using superimposed 3D protein models instead of sequence based algorithms used by POLYPHEN and SIFT.

Thin genu of the corpus callosum points to mutation in FOXG1 in a child with acquired microcephaly, trigonocephaly, and intellectual developmental disorder: a case report and review of literature.

The FOXG1 syndrome is emerging as a relative new entity in paediatric neurology. We report a boy with acquired microcephaly, mental retardation and a thin genu of the corpus callosum. The combination of these findings led to mutation analysis of FOXG1. The patient was found to be heterozygous for a novel mutation in FOXG1, c.506dup (p.Lys170GInfsX285), which occurred de novo. This frameshift mutation disturbs the three functional domains of the FOXG1 gene. Hypo- or agenesis of the anterior corpus callosum in combination with acquired microcephaly and neurologic impairment can be an important clue for identifying patients with a mutation in FOXG1.

Elaborating the phenotypic spectrum associated with mutations in ARFGEF2: case study and literature review.

BACKGROUND: The BIG2 protein, coded by ARFGEF2 indirectly assists neuronal proliferation and migration during cortical development. Mutations in ARFGEF2 have been reported as a rare cause of periventricular heterotopia. METHODS: The presence of periventricular heterotopia, acquired microcephaly and suspected recessive inheritance led to mutation analysis of ARFGEF2 in two affected siblings and their healthy consanguineous parents, after mutations in FLNA had been ruled out. RESULTS: A homozygous c.242_249delins7 (p.Pro81fs) mutation in exon 3 of ARFGEF2 was identified in the siblings. The alteration is a combination of 2 missense mutations (c.242C > A and c.247G > T) and a frameshift mutation (c.249delA) resulting in a premature stop codon. The clinical phenotype was characterized by dystonic quadriplegia, marked developmental delay, obstructive cardiomyopathy, recurrent infections and feeding difficulties. Degenerative features included early regression, acquired microcephaly and cerebral atrophy. Brain MRI revealed bilateral periventricular heterotopia, small corpus callosum, cerebral and hippocampal atrophy and hyperintensity in the putamen. CONCLUSION: Mutations in ARFGEF2 can be anticipated based on characteristic clinical and imaging features.