Additional file 1: of A homozygous splicing mutation in ELAC2 suggests phenotypic variability including intellectual disability with minimal cardiac involvement

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The three-dimensional structure of endoglin monomer showing the locations of the twenty five missense mutants studied in this aricle.

<p>Endoglin consists of a small c-terminal intracellular domain and three extracellular domains that include the ZP-C (green), ZP-N (Orange) and orphan (yellow) domains. The endoglin model structure (Llorca et al. 2007) file was provided by Dr Carmelo Bernabeu and then was manipulated using RasMol 2.7 (<a href="http://www.RasMol.org" target="_blank">www.RasMol.org</a>). The ball and stick represntation of the ER-retained (back) and the predominantly plasma membrane (purple) mutants are indicated on the strucure. It is clear that the majority of the mutants affecting the orphan domain resulted in the retention of the protein in the ER whereas those affecting the ZP domains retained their plasma membrane localization.</p

The majority of the missense mutants in the ZP and intraceullar domains traffic normally to the plasma membrane.

<p>HeLa cells were transiently co-transfected with the C-terminally HA-tagged Endoglin pCMV5 plasmids and the EGFP-tagged H-Ras plasmid and 24 hours later the cells were processed for fluorescence confocal microscopy as described in the methods. The following missense mutanst were shown to traffic predominantly to the plama membrane as eviednced by their co-localization with GFP-H-Ras: C382G ( data not shoiwn due to space limitations), F403S (panles A–C), S407N (not shown), C412S (not shown), G413V (not shown), N423S (panels D–F), R437W (not shown), A452G (not shown), Q476H (not shown), V504M (panels J–L), R571H (panels M–O ) and P615L (panels P–R).</p

Comparison of the subcellular localization of wild type Endoglin with two (L32R and C53R) orphan domain HHT1-causing mutants.

<p>HeLa cells were transiently transfected with the C-terminally HA-tagged Endoglin pCMV5 plasmids (panels A-C, G-I and M-O) or co-transfected with the same plasmids and the EGFP-tagged H-Ras plasmid (Panels D–F, J–L and P–R) and processed for fluorescence confocal microscopy as described in the methods. The HA tagged proteins were detected with Anti-HA monoclonal antibodies (red panels A, D, G, J. M and P) and the ER marker calnexin was detected with anti-calnexin polyclonal antibodies (panels B, H and N). GFP-H-Ras staining is shown in panels E, K and Q. The wild type predominantly showed plasma membrane localization as evidenced by its co-localization with Ras (D–F). On the other hand the two mutants (L32R and C53R) showed ER localization (G–R).</p

Endoglycosidase H (EndoH) analysis of the expressed missense mutants.

<p>The pCMV5 HA-tagged endoglin plasmids were transfected into HEK293 cells and were allowed to express the proteins as described in the methods. This was followed by lysis of the cells and the immuoprecipitation of the proteins with anti-HA monoclonal antibodies. Each immunoprecipitate was divided into two sample with one of them was treated (+) with EndoH or left untreated (−). Both samples were then electrophorese and western blotted using anti-HA monoclonal antibodies as described in the methods section. The majority of the WT protein did not change mobility upon EndoH treatment indicating its maturation and acquisition of complex N-glycan moieties in the post ER compartments. The missense mutants L32R, V49F, C53R, V125D, A160D, P165L, I271N, A308D, C363Y and C382W showed a single band indicating an exclusively ER premature forms. The other mutants either showed two bands or a simple high molecular weight band indicating that at least a significant proportion of the expressed protein matured in post ER compartments. The EndoH treatment data are in agreement with the confocal microscopy data.</p

An Integrative Computational Approach for Prioritization of Genomic Variants

<div><p>An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.</p></div

Docked folate conformations (blue: native, red: H27R mutant-bound folate molecules) showing the distinct change in the optimal conformation between native and the mutant.

<p>Docked folate conformations (blue: native, red: H27R mutant-bound folate molecules) showing the distinct change in the optimal conformation between native and the mutant.</p

Integration of services in the described analytical environment.

<p>Lynx logo © 2013–2014 Department of Genetics, University of Chicago. RViewer logo © 2010–2012 The Regents of the University of California.</p

Access to the analytical tools within the described bioinformatics environment.

<p>Access to the analytical tools within the described bioinformatics environment.</p

Analytical workflow for identification of spina bifida candidate genes.

<p>Analytical workflow for identification of spina bifida candidate genes.</p