In Silico Analysis of Variants of Uncertain Significance in AP4S1 Gene

  • Sobia Nazir Chaudry Department of Life Sciences, University of Management and Technology, Lahore, Pakistan
  • Ammara Akhtar Department of Life Sciences, University of Management and Technology, Lahore, Pakistan
  • Ayman Naeem Department of Life Sciences, University of Management and Technology, Lahore, Pakistan
  • Dr. Mureed Husaain Department of Life Sciences, University of Management and Technology, Lahore, Pakistan
DOI: https://doi.org/10.32350/BSR.0201.01
Keywords: AP4S1, heredity spastic paraplegia, in silico prediction, SNPs

Abstract

Abstract Views: 305

Hereditary spastic paraplegia is a group of heterogeneous neurological disorders with genetic etiologies. It is characterized by spasticity in lower limbs along with neurological complications. Sequencing technologies have identified numerous disease causing variants in AP4S1 gene. However, many very low frequency variations in AP4S1 have the potential to cause hereditary spastic paraplegia in a recessive inheritance manner. This study was designed to identify these potential disease causing variants in AP4S1 gene using in silico tools. These tools predict the effects of deleterious variants on protein function and pre-mRNA splicing. To predict the pathogenicity of missense variants PhD-SNPg, PROVEAN, SNPs&GO, and CADD were used. Splice site variants were analyzed using Spliceman, SPiCE, and Human Splice Finder (HSF). In silico analysis identified six missense and five splice site variants with the potential to cause hereditary spastic paraplegia.

Copyright(c) The Author

Downloads

Download data is not yet available.

References

. Salinas S, Proukakis C, Crosby A, Warner TT. Hereditary spastic paraplegia: clinical features and pathogenetic mechanisms. Lancet Neurol. 2008;7(12): 1127-1138.

. Moreno-De-Luca A, Helmers SL, Mao H, et al. 2011. Adaptor protein complex-4 (AP-4) deficiency causes a novel autosomal recessive cerebral palsy syndrome with microcephaly and intellectual disability. J Med Genet. 2011;48(2): 141-144.

. Blackstone C. Cellular pathways of hereditary spastic paraplegia. Annu Rev Neurosci. 2012;35: 25-47.

. Morais S, Raymond L, Mairey M, et al. Massive sequencing of 70 genes reveals a myriad of missing genes or mechanisms to be uncovered in hereditary spastic paraplegias. Eur J Hum Genet. 2017;25(11): 1217-1228.

. Boutry M, Morais S, Stevanin G. Update on the genetics of spastic paraplegias. Curr Neurol Neurosci Rep. 2019;19(4): 18.

. Vitner EB, Platt FM, Futerman AH. Common and uncommon pathogenic cascades in lysosomal storage diseases. J Biol Chem. 2010;285(27): 20423-20427.

. Yalçın B, Zhao L, Stofanko M, et al. Modeling of axonal endoplasmic reticulum network by spastic paraplegia proteins. Elife. 2017;6: e23882.

. Davies AK, Itzhak DN, Edgar JR, et al. AP-4 vesicles contribute to spatial control of autophagy via RUSC-dependent peripheral delivery of ATG9A. Nat Commun. 2018;9(1): 1-21.

. Hirst J, Irving C, Borner GH. Adaptor protein complexes AP‐4 and AP‐5: new players in endosomal trafficking and progressive spastic paraplegia. Traffic. 2013;14(2): 153-164.

. Abou Jamra R, Philippe O, Raas A-R, et al. Adaptor protein complex 4 deficiency causes severe autosomal-recessive intellectual disability, progressive spastic paraplegia, shy character, and short stature. Am J Hum Genet. 2011; 88(6): 788-795.

. Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM, Shendure J. A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 2014; 46(3): 310-315.

. Capriotti E, Fariselli P. PhD-SNPg: a webserver and lightweight tool for scoring single nucleotide variants. Nucleic Acids Res. 2017;45(W1): W247-W252.

. Yongwook C, Agnes PC. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels. Bioinformatics. 2015; 31(16): 2745–2747. https://doi.org/10.1093/bioinformatics/btv195

. Capriotti E, Calabrese R, Fariselli P, Martelli PL, Altman RB, Casadio R. WS-SNPs & GO: a web server for predicting the deleterious effect of human protein variants using functional annotation. BMC Genomics. 2013; 14(3): S6.

. Anna A, Monika G. Splicing mutations in human genetic disorders: examples, detection, and confirmation. J Appl Genet. 2018; 59(3): 253-268.

. Lim KH, Fairbrother WG. Spliceman - a computational web server that predicts sequence variations in pre-mRNA splicing. Bioinformatics. 2012; 28(7): 1031-1032.

. Leman R, Gaildrat P, Le Gac G, et al. Novel diagnostic tool for prediction of variant spliceogenicity derived from a set of 395 combined in silico / in vitro studies: an international collaborative effort. Nucleic Acids Res. 2018; 46(15): 7913-7923.

. Shapiro MB, Senapathy P. RNA splice junctions of different classes of eukaryotes: sequence statistics and functional implications in gene expression. Nucleic Acids Res. 1987; 15(17): 7155-7174.

. Yeo G, Burge CB. Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals. J Comput Biol. 2004; 11(2-3): 377-394.

. Desmet F-O, Hamroun D, Lalande M, Collod G-B, Claustres M, Béroud C. Human splicing finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009; 37(9): 67-e67.

. Rentzsch P, Witten D, Cooper GM, Shendure J, Kircher M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res. 2018; 47(D1): D886-D894.

. Chen CW, Lin MH, Liao CC, Chang HP, Chu YW. iStable 2.0: Predicting protein thermal stability changes by integrating various characteristic modules. Comput Struct Biotechnol J. 2020; 18: 622-630.

. Capriotti E, Fariselli P, Casadio R. I-Mutant 2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 2005; 33: W306-W310.

. van den Berg BA, Reinders MJ, Roubos JA, de Ridder D. SPiCE: a web-based tool for sequence-based protein classification and exploration. BMC Bioinf. 2014; 15(1): 93.

. Tchernitchko D, Goossens M, Wajcman H. In silico prediction of the deleterious effect of a mutation: proceed with caution in clinical genetics. Clin Chem. 2004; 50(11): 1974-1978.

. Landrum MJ, Kattman BL. Clin Var at five years: delivering on the promise. Hum Mutat. 2018; 39(11): 1623-1630.

Published
2020-03-10
How to Cite
Chaudry, S. N., Akhtar, A., Naeem, A., & Husaain, D. M. (2020). In Silico Analysis of Variants of Uncertain Significance in AP4S1 Gene. BioScientific Review, 2(1), 01–09. https://doi.org/10.32350/BSR.0201.01
Issue
Vol 2 No 1 (2020): March
Section
Research Articles

Copyright (c) 2020 Sobia Nazir Chaudry, Ammara Akhtar, Ayman Naeem, Dr. Mureed Husaain

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

BSR follows an open-access publishing policy and full text of all published articles is available free, immediately upon publication of an issue. The journal’s contents are published and distributed under the terms of the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Thus, the work submitted to the journal implies that it is original, unpublished work of the authors (neither published previously nor accepted/under consideration for publication elsewhere). On acceptance of a manuscript for publication, a corresponding author on the behalf of all co-authors of the manuscript will sign and submit a completed the Copyright and Author Consent Form.