scholarly journals A Monoallelic Variant in REST Is Associated with Non-Syndromic Autosomal Dominant Hearing Impairment in a South African Family

Genes ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1765
Author(s):  
Noluthando Manyisa ◽  
Isabelle Schrauwen ◽  
Leonardo Alves de Souza Rios ◽  
Shaheen Mowla ◽  
Cedrik Tekendo-Ngongang ◽  
...  
Keyword(s):  
Hearing Impairment ◽  
South African ◽  
Autosomal Dominant ◽  
Tertiary Structure ◽  
In Silico Analysis ◽  
Hek 293 ◽  
Disulphide Bonds ◽  
Whole Exome ◽  
293 Cells ◽  
Silico Analysis

Hearing impairment (HI) is a sensory disorder with a prevalence of 0.0055 live births in South Africa. DNA samples from a South African family presenting with progressive, autosomal dominant non-syndromic HI were subjected to whole-exome sequencing, and a novel monoallelic variant in REST [c.1244GC; p.(C415S)], was identified as the putative causative variant. The co-segregation of the variant was confirmed with Sanger Sequencing. The variant is absent from databases, 103 healthy South African controls, and 52 South African probands with isolated HI. In silico analysis indicates that the p.C415S variant in REST substitutes a conserved cysteine and results in changes to the surrounding secondary structure and the disulphide bonds, culminating in alteration of the tertiary structure of REST. Localization studies using ectopically expressed GFP-tagged Wild type (WT) and mutant REST in HEK-293 cells show that WT REST localizes exclusively to the nucleus; however, the mutant protein localizes throughout the cell. Additionally, mutant REST has an impaired ability to repress its known target AF1q. The data demonstrates that the identified mutation compromises the function of REST and support its implication in HI. This study is the second report, worldwide, to implicate REST in HI and suggests that it should be included in diagnostic HI panels.

scholarly journals In silico analysis of CDC73 gene revealing 11 novel SNPs associated with Jaw Tumor Syndrome

2019 ◽  
Author(s):  
Abdelrahman H. Abdelmoneim ◽  
Alaa I. Mohammed ◽  
Esraa O. Gadim ◽  
Mayada A.Mohammed ◽  
Sara H. Hamza ◽  
...  
Keyword(s):  
In Silico ◽  
Autosomal Dominant ◽  
In Silico Analysis ◽  
Autosomal Dominant Disorder ◽  
Variable Expression ◽  
Back Ground ◽  
And Function ◽  
Molecular Aberrations ◽  
The Impact ◽  
Silico Analysis

AbstractBack groundhyperparathyroidism-jaw tumor (HPT-JT) is an autosomal dominant disorder with variable expression, with an estimated prevalence of 6.7 per 1,000 population. Genetic testing for predisposing CDC73 (HRPT2) mutations has been an important clinical advance, aimed at early detection and/or treatment to prevent advanced disease. The aim of this study is to assess the effect of SNPs on CDC73 structure and function using different bioinformatics tools.MethodComputational analysis using eight different in-silico tools including SIFT, PROVEAN, PolyPhen-2, SNAP2, PhD-SNP, SNPs&GO, PMut and Imutant were used to identify the impact on the structure and/or function of CDC73 gene that might be causing jaw tumour.ResultsFrom (733) SNPs identified in the CDC73 gene we found that only Eleven were deleterious to the function and structure of protein and expected to cause syndrome.ConclusionEleven substantial genetic/molecular aberrations in CDC73 gene were identified that could serve as actionable targets for chemotherapeutic intervention in patients whose disease is no longer surgically curable.

scholarly journals A Comprehensive Review on Inherited Sensorineural Hearing Loss and Their Syndromes

2020 ◽  
Author(s):  
Muhammad Noman ◽  
Shazia Anwer Bukhari ◽  
Muhammad Tahir ◽  
Shehbaz Ali
Keyword(s):  
Hearing Loss ◽  
Hearing Impairment ◽  
Autosomal Dominant ◽  
Genetic Disorders ◽  
World Population ◽  
Pathogenic Variants ◽  
Pathogenic Genes ◽  
Whole Exome ◽  
Specific Locus ◽  
Population Effects

Hearing impairment is an immensely diagnosed genetic cause, 5% of the total world population effects with different kind of congenital hearing loss (HL). In third-world countries or countries where consanguineous marriages are more common the frequency rate of genetic disorders are at its zenith. Approximately, the incidence of hearing afflictions is ostensibly 7-8:1000 individuals whereas it is estimated that about 466 million peoples suffer with significant HL, and of theses deaf cases 34 million are children’s up to March, 2020. Several genes and colossal numbers of pathogenic variants cause hearing impairment, which aided in next-generation with recessive, dominant or X-linked inheritance traits. This review highlights on syndromic and non-syndromic HL (SHL and NSHL), and categorized as conductive, sensorineural and mixed HL, which having autosomal dominant and recessive, and X-linked or mitochondrial mode of inheritance. Many hundred genes involved in HL are reported, and their mutation spectrum becomes very wide. Mapping of pathogenic genes in consanguinity family is facilitated to understand the disease history. Review presents the bases of HL and also focused on various genetic factors that cause deafness like the basics of genetic inheritance, and classic and well-characterized inherited factors of it. It also overviews the application of linkage analysis, SNPs genotyping and whole exome sequencing methods, in mapping and identification of new locus, causative genes and their variants in families inherited with HL. Conclusively, this review supports researchers in understanding the location of chromosome, the causative genes and specific locus which causing deafness in humans.

scholarly journals Bayesian modeling to predict malignant hyperthermia susceptibility and pathogenicity of RYR1, CACNA1S and STAC3 variants

2019 ◽  
Vol 20 (14) ◽  
pp. 989-1003
Author(s):  
Senthilkumar Sadhasivam ◽  
Barbara W Brandom ◽  
Richard A Henker ◽  
John J McAuliffe
Keyword(s):  
Malignant Hyperthermia ◽  
Bayesian Statistics ◽  
Bayesian Modeling ◽  
In Silico Analysis ◽  
Malignant Hyperthermia Susceptibility ◽  
Degree Relative ◽  
New Approach ◽  
Whole Exome ◽  
Uncertain Significance ◽  
Silico Analysis

Aim: Identify variants in RYR1, CACNA1S and STAC3, and predict malignant hyperthermia (MH) pathogenicity using Bayesian statistics in individuals clinically treated as MH susceptible (MHS). Materials & methods: Whole exome sequencing including RYR1, CACNA1S and STAC3 performed on 64 subjects with: MHS; suspected MH event or first-degree relative; and MH negative. Variant pathogenicity was estimated using in silico analysis, allele frequency and prior data to calculate Bayesian posterior probabilities. Results: Bayesian statistics predicted CACNA1S variant p.Thr1009Lys and RYR1 variants p.Ser1728Phe and p.Leu4824Pro are likely pathogenic, and novel STAC3 variant p.Met187Thr has uncertain significance. Nearly a third of MHS subjects had only benign variants. Conclusion: Bayesian method provides new approach to predict MH pathogenicity of genetic variants.

scholarly journals Identification of two novel COL10A1 heterozygous mutations in two Chinese pedigrees with Schmid-type metaphyseal chondrodysplasia

2019 ◽  
Author(s):  
Lingchi Kong ◽  
Li Shi ◽  
Wenbo Wang ◽  
Rongtai Zuo ◽  
Mengwei Wang ◽  
...  
Keyword(s):  
Family Members ◽  
In Silico Analysis ◽  
Coxa Vara ◽  
Missense Mutations ◽  
Autosomal Dominant Disorder ◽  
Metaphyseal Chondrodysplasia ◽  
Whole Exome ◽  
Col10a1 Gene ◽  
Silico Analysis ◽  
Nc1 Domain

Abstract Background: Schmid-type metaphyseal chondrodysplasia (MCDS) is an autosomal dominant disorder caused by COL10A1 mutations, which is characterized by short stature, waddling gait, coxa vara and bowing of the long bones. However, descriptions of the expressivity of MCDS are rare. Methods: Two probands and available family members affected with MCDS were subjected to clinical and radiological examination. Genomic DNA of all affected individuals was subjected to whole-exome sequencing, and candidate mutations were verified by Sanger sequencing in all available family members and in 250 normal control donors. A spatial model of the type X collagen (α1) C-terminal noncollagenous (NC1) domain was further constructed. Results: We found that the phenotype of affected family members exhibited irregular dominance. Mutation analysis indicated that there were two novel heterozygous missense mutations, [c.1765T>A (p.Phe589Ile)] and [c.1846A>G (p.Lys616Glu)] in the COL10A1 gene in family 1 and 2, respectively. The two novel substitution sites were highly conserved and the mutations were predicted to be deleterious by in silico analysis. Furthermore, protein modeling revealed that the two substitutions were located in the NC1 domain of collagen X (α1), which potentially impacted the trimerization of collagen X (α1) and combination with molecules in the pericellular matrix. Conclusion: Two novel mutations were identified in the present study, which will facilitate diagnosis of MCDS and further expand the spectrum of the COL10A1 mutations associated with MCDS patients. In addition, our research revealed the phenomenon of irregular dominance in MCDS.

scholarly journals Extensive In Silico Analysis of the Functional and Structural Consequences of SNPs in Human ARX Gene

2020 ◽  
Author(s):  
Mujahed I. Mustafa ◽  
Naseem S. Murshed ◽  
Abdelrahman H. Abdelmoneim ◽  
Abdelrafie M. Makhawi
Keyword(s):  
In Silico ◽  
Tertiary Structure ◽  
Motor Impairment ◽  
Gene Mutations ◽  
In Silico Analysis ◽  
Epileptic Encephalopathy ◽  
Nucleotide Polymorphisms ◽  
Severe Intellectual Disability ◽  
Structural Impacts ◽  
Silico Analysis

AbstractEarly infantile epileptic encephalopathy 1 (EIEE1) is a rare but devastating neurologic disorder that displays concomitant cognitive and motor impairment, and is often presented in the first months of life with severe intellectual disability. The objective of this study is to classify the most deleterious nsSNPs in ARX gene that may cause EIEE1 disease. Despite the reported association of ARX gene mutations with vulnerability to several neurologic condition, there is lack of in silico analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the ARX at protein level. Therefore, the pathogenic nsSNPs in the human ARX obtained from NCBI were analyzed for their functional and structural impact using bioinformatics tools like SIFT, Polyphen, PROVEAN, I-Mutant, and MUPro. The effects of the mutations on tertiary structure of the human ARX protein were predicted using RaptorX and visualized by UCSF Chimera while STRING was used to investigate its protein–protein interaction. Our extensive in silico analysis revealed 11 mutations that will significantly alter the structure of human ARX protein; that may disturb the domain which will affect the function of the protein. Extensive in silico analysis of the functional and structural consequences of SNPs in human ARX gene revealed 11 mutations (L535Q, R528S, R380L, V374D, L343Q, T333N, T333S, R332H, R330H, G34R and L33P) that may cause EIEE1.Therefore, can be used as diagnostic markers for EIEE1.

scholarly journals Bioinformatics Resources for In Silico Proteome Analysis

2003 ◽  
Vol 2003 (4) ◽  
pp. 231-236 ◽  
Author(s):  
Manuela Pruess ◽  
Rolf Apweiler
Keyword(s):  
In Silico ◽  
Computational Analysis ◽  
Tertiary Structure ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Proteome Analysis ◽  
Protein Modelling ◽  
Similarity Searches ◽  
Silico Analysis

In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species—mainly the human—have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.

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