Genomic Studies in a Large Cohort of Hearing Impaired Italian Patients Revealed Several New Alleles, a Rare Case of Uniparental Disomy (UPD) and the Importance to Search for Copy Number Variations

Hereditary hearing loss (HHL) is a common disorder characterized by a huge genetic heterogeneity. The definition of a correct molecular diagnosis is essential for proper genetic counseling, recurrence risk estimation, and therapeutic options. From 20 to 40% of patients carry mutations in GJB2 gene, thus, in more than half of cases it is necessary to look for causative variants in the other genes so far identified (~100). In this light, the use of next-generation sequencing technologies has proved to be the best solution for mutational screening, even though it is not always conclusive. Here we describe a combined approach, based on targeted re-sequencing (TRS) of 96 HHL genes followed by high-density SNP arrays, aimed at the identification of the molecular causes of non-syndromic HHL (NSHL). This strategy has been applied to study 103 Italian unrelated cases, negative for mutations in GJB2, and led to the characterization of 31% of them (i.e., 37% of familial and 26.3% of sporadic cases). In particular, TRS revealed TECTA and ACTG1 genes as major players in the Italian population. Furthermore, two de novo missense variants in ACTG1 have been identified and investigated through protein modeling and molecular dynamics simulations, confirming their likely pathogenic effect. Among the selected patients analyzed by SNP arrays (negative to TRS, or with a single variant in a recessive gene) a molecular diagnosis was reached in ~36% of cases, highlighting the importance to look for large insertions/deletions. Moreover, copy number variants analysis led to the identification of the first case of uniparental disomy involving LOXHD1 gene. Overall, taking into account the contribution of GJB2, plus the results from TRS and SNP arrays, it was possible to reach a molecular diagnosis in ~51% of NSHL cases. These data proved the usefulness of a combined approach for the analysis of NSHL and for the definition of the epidemiological picture of HHL in the Italian population

A Strategy to Enhance Secretion of Extracellular Matrix Components by Stem Cells: Relevance to Tissue Engineering

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Molecular explanations for the structural changes.

<p>The rigidity analysis provided information based on the structural rigidity and flexibility of residues. (A) 10 ns snapshots of a) WT and b) Arg177His, (B) 9 ns snapshots of a) WT and b) Ala216Thr and (C) 1 ns snapshots of a) WT and b) Glu258Lys. Here, blue represents rigid regions and black and gray indicates flexible regions. The mutational spots are shown in yellow arrow. As the Ala216Thr affected the distal region of the domain, the position of this mutation has not shown. The hydrogen bonds (red lines) that are missing in the mutants are marked in black and the newly formed hydrogen bonds in the mutants are shown in light blue.</p

Structural features of the domain C1 of cMyBP-C.

<p>Positions of the examined HCM causing mutations are shown in red. The C1 consists of seven β-stands that form two β-sheets, where sheet-1 consists of strands A, C, F and G while sheet-2 comprises strands B, D and E both with anti-parallel packing of adjacent strands. Refer <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059206#pone-0059206-g004" target="_blank">Figure 4</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059206#pone-0059206-g006" target="_blank">6</a> for the key residues.</p

Fluctuations of the WT and mutant residues during MD simulations.

<p>The average RMSF of the mutated residues for 10 ns are plotted in 2D bar graph. The bars in gray and in different colours (green, orange and aqua green) represent the WT and the mutants, respectively.</p

Trajectory-based structural stability analyses of WT and mutants.

<p>(A) Root mean square deviation (RMSD) and (B) average root mean square fluctuation (RMSF) of residues during MD simulations.</p

Intra-molecular interactions.

<p>For the represented snapshots of MD simulations (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059206#pone-0059206-g003" target="_blank">Figure 3</a>), two layers of neighbouring residues between corresponding WT and mutant residues along with their hydrogen bonds are displayed. Here, (A) a) WT and b) Arg177His at 10 ns, (B) Ala216Thr at 9 ns and (C) WT at 1 ns. At 9 ns Ala216 of WT and at 1 ns Lys258 of Glu258Lys did not make any interactions, hence they are not shown. WT and mutant residues 177, 216 and 258 are shown in yellow, and the residues directly interacting with these residues are shown in pink and are described as first layer. The residues that are interacting with first layer of residues are depicted as second layer and shown in violet.</p

Electrostatic surface potential map.

<p>Front view and back view of surface electrostatic potential map for the snapshots shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059206#pone-0059206-g003" target="_blank">Figure 3</a>. Where, blue, red and white represent positive, negative and hydrophobic electrostatic potential, respectively. WT at 10 ns, 9 ns and 1 ns were in different conformational states due to the simulations that were performed after the equilibration. In addition, the N-terminal of the protein was highly flexible during all 4 simulations (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0059206#pone-0059206-g002" target="_blank">Figure 2b</a>), hence the electrostatic surface map of the representative snapshots shows considerable change at their N-terminal.</p