A computational report on the variants of ZSCAN4 gene in treating down syndrome

Paper Details

Research Paper 01/04/2017
Views (327) Download (16)
current_issue_feature_image
publication_file

A computational report on the variants of ZSCAN4 gene in treating down syndrome

Pratichi Singh, Rashi Nagotra, Arthi Venkatesan, J. Febin Prabhu Dass
Int. J. Biosci.10( 4), 41-48, April 2017.
Certificate: IJB 2017 [Generate Certificate]

Abstract

Down syndrome (DS), also known as trisomy 21 is the most commonly known aneuploidy condition. It causes severe problems in human growth, function and its development. Recent reports suggest Zinc finger and SCAN domain containing 4 gene (ZSCAN4) as a new therapy for chromosome abnormalities, hence helps in treating the down syndrome. The expression of ZSCAN4 gene located on chromosome 19 increases the telomere length in human adult cells. This study deals with Insilico approach to find the deleterious SNPs in ZSCAN4 that are linked with this disease condition. Single Nucleotide Polymorphism (SNPs) in ZSCAN4is retrieved to predict the harmful effect in protein using computational tools like SNAP2, PolyPhen 2,I Mutant 2 and SIFT.  As a result, two common SNPs are found to be highly deleterious with rs-id377104601 (R151I) and rs-id545052223 (I154T). Further, the structural analysis was performed and the result shows no similarity between the native and mutant protein. Therefore, these reported mutations(R151I and I154T) may alter the function and expression of ZSCAN4 gene and may perhaps not be helpful in treating Down syndrome.

VIEWS 16

Adamczak R, Porollo A, Meller J. 2004. Accurate prediction of solvent accessibility using neural networks-based regression. Proteins 56(4), 753-767. https://doi.org/10.1002/prot.20176

Akinci A, Oner O, Bozkurt OH, Guven A, Degerliyurt A, Munir K. 2009. Refractive Errors and Strabismus in Children With Down Syndrome: A Controlled Study. Journal of Pediatric Ophthalmology and Strabismus 46(2), 83-86.

Amano T, Hirata T, Falco G, Monti M, Sharova LV, Amano M, Ko MSH. 2013. Zscan4 restores the developmental potency of embryonic stem cells. Nature Communications 4, 1966. https://doi.org/10.1038/ncomms2966

Cheng J, Randall AZ, Sweredoski MJ,Baldi P. 2005. SCRATCH: a protein structure and structural feature prediction server. Nucleic Acids Research, 33, 72-76. https://doi.org/10.1093/nar/gki396

Evans HJ. 1987. The consequences of chromosome imbalance: Principles, mechanisms and models. Trends in Genetics 3, 28-29. https://doi.org/10.1016/0168-9525(87)90160-0

Falco G, Lee SL, Stanghellini I, Bassey UC, Hamatani T, Ko MSH. 2007. Zscan4: a novel gene expressed exclusively in late 2-cell embryos and embryonic stem cells. Developmental Biology 307(2), 539-550. https://doi.org/10.1016/j.ydbio.2007.05.003

Flanagan T, Russo N, Flores H, Burack J. 2008. The developmental approach to the study of Down syndrome: Contemporary issues in historical perspective. https://doi.org/10.3104/reviews/2081

Hung SSC, Wong RCB, Sharov AA, Nakatake Y, Yu H, Ko MSH. 2013. Repression of global protein synthesis by Eif1a-like genes that are expressed specifically in the two-cell embryos and the transient Zscan4-positive state of embryonic stem cells. DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes, 20(4), 391-402. https://doi.org/10.1093/dnares/dst018

Kiefer F, Arnold K, Künzli M, Bordoli L, Schwede T. 2009.The SWISS-MODEL Repository and associated resources. Nucleic Acids Research 37, 387-392. https://doi.org/10.1093/nar/gkn750

Kormann MSD, Hasenpusch G, Aneja MK, Nica G, Flemmer AW, Herber-Jonat S, Rudolph C. 2011. Expression of therapeutic proteins after delivery of chemically modified mRNA in mice. Nature Biotechnology 29(2), 154-157. https://doi.org/10.1038/nbt.1733

Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM. 1996. AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. Journal of Biomolecular NMR 8(4), 477-486.

Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N. 2009.1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAM tools. Bioinformatics (Oxford, England) 25(16), 2078-2079. https://doi.org/10.1093/bioinformatics/btp352

Liu B, Filippi S, Roy A, Roberts I. (2015). Stem and progenitor cell dysfunction in human trisomies. EMBO Reports 16(1), 44-62. https://doi.org/10.15252/embr.201439583

Mégarbané A, Ravel A, Mircher C, Sturtz F, Grattau Y, Rethoré MO, Mobley WC. 2009. The 50th anniversary of the discovery of trisomy 21: the past, present, and future of research and treatment of Down syndrome. Genetics in Medicine: Official Journal of the American College of Medical Genetics 11(9), 611-616. https://doi.org/10.1097/GIM.0b013e3181b2e34c

Morris JK, Alberman E. 2009. Trends in Down’s syndrome live births and antenatal diagnoses in England and Wales from 1989 to 2008: analysis of data from the National Down Syndrome Cytogenetic Register. BMJ (Clinical Research Ed.) 339, 3794.

Porollo A, Meller J. 2007. Versatile annotation and publication quality visualization of protein complexes using POLYVIEW-3D.BMC Bioinformatics 8, 316. https://doi.org/10.1186/1471-2105-8-316

Rajamanika S, Vanajothi R, Sudha A, Rameshthan P, Srinivasan P. 2012. In silico Analysis of Deleterious SNPs of the FGFR2 Gene. Journal of Biological Science 12(2), 83-90. https://doi.org/10.3923/jbs.2012.83.90

Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. 2011. Integrative Genomics Viewer. Nature Biotechnology 29(1), 24-26. https://doi.org/10.1038/nbt.1754

Seki S, Matano T. 2013. Development of Vaccines Using SeV Vectors Against AIDS and Other Infectious Diseases. In Y. Nagai (Ed.), Sendai Virus Vector, 127-149. Springer Japan. Retrieved from http://link.springer.com/chapter/10.1007/978-4431-54556-9_5

Singh P, Dass JFP. 2016. A multifaceted computational report on the variants effect on KIR2DL3 and IFNL3 candidate gene in HCV clearance. Molecular Biology Reports 43(10), 1101-1117. https://doi.org/10.1007/s11033-016-4044-5

Smith N, Witham S, Sarkar S, Zhang J, Li L, Li C,  Alexov E. 2012. DelPhi web server v2: incorporating atomic-style geometrical figures into the computational protocol. Bioinformatics (Oxford, England) 28(12), 1655-1657. https://doi.org/10.1093/bioinformatics/bts200

Song J, Tan H, Takemoto K,  Akutsu T. 2008. HSEpred: predict half-sphere exposure from protein sequences. Bioinformatics 24(13), 1489-1497. https://doi.org/10.1093/bioinformatics/btn222

Teer J K, Green ED, Mullikin JC,  Biesecker LG. 2012. VarSifter: visualizing and analyzingexome-scale sequence variation data on a desktop computer. Bioinformatics (Oxford, England) 28(4), 599-600. https://doi.org/10.1093/bioinformatics/btr711

Thiltgen G, Goldstein RA. 2012. Assessing Predictors of Changes in Protein Stability upon Mutation Using Self-Consistency. PLOS ONE 7(10), e46084. https://doi.org/10.1371/journal.pone.0046084

Torres EM, Williams BR, Amon A. 2008. Aneuploidy: cells losing their balance. Genetics 179(2), 737-746. https://doi.org/10.1534/genetics.108.090878

Wiseman FK, Alford KA, Tybulewicz VLJ,  Fisher EMC. 2009. Down syndrome–recent progress and future prospects. Human Molecular Genetics 18, 75-83. https://doi.org/10.1093/hmg/ddp010

Yonemitsu Y, Matsumoto T, Itoh H, Okazaki J, Uchiyama M, Yoshida K, Maehara Y. 2013. DVC1-0101 to treat peripheral arterial disease: a Phase I/IIa open-label dose-escalation clinical trial. Molecular Therapy: The Journal of the American Society of Gene Therapy 21(3), 707-714. https://doi.org/10.1038/mt.2012.279

Zalzman M, Falco G, Sharova LV, Nishiyama A, Thomas M, Lee SL, Ko MSH. 2010. Zscan4 regulates telomere elongation and genomic stability in ES cells. Nature 464(7290), 858-863. https://doi.org/10.1038/nature08882