Browsing by Subject "single nucleotide polymorphism"
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Item Open Access Common telomerase reverse transcriptase promoter mutations in hepatocellular carcinomas from different geographical locations(WJG Press, 2015) Cevik, D.; Yildiz G.; Ozturk, M.AIM: To determine the mutation status of human telomerase reverse transcriptase gene (TERT ) promoter region in hepatocellular carcinoma (HCC) from different geographical regions. METHODS: We analyzed the genomic DNA sequences of 59 HCC samples comprising 15 cell lines and 44 primary tumors, collected from patients living in Asia, Europe and Africa. We amplified a 474 bp DNA fragment of the promoter region of TERT gene including the 1295228 and 1295250 sequence of chromosome 5 by using PCR. Amplicons were then sequenced by Sanger technique and the sequence data were analyzed with by using DNADynamo software in comparison with wild type TERT gene sequence as a reference. RESULTS: The TERT mutations were found highly frequent in HCC. Eight of the fifteen tested cell lines displayed C228T mutation, and one had C250T mutation with a mutation frequency up to 60%. All of the mutations were heterozygous and mutually exclusive. Ten out of forty-four tumors displayed C228T mutation, and additional five tumors had C250T mutation providing evidence for mutation frequency of 34% in primary tumors. Considering the geographic origins of HCC tumors tested, TERT promoter mutation frequencies were higher in African (53%), when compared to non-African (24%) tumors (P = 0.056). There was also a weak inverse correlation between TERT promoter mutations and murine double minute 2 single nucleotide polymorphism 309 TG polymorphism (P = 0.058). Mutation frequency was nearly two times higher in established HCC cell lines (60%) compared to the primary tumors (34%). CONCLUSION: TERT promoter is one of most frequent mutational targets in liver cancer, and hepatocellular carcinogenesis is highly associated with the loss of telomere-dependent cellular senescence control. © The Author(s) 2015.Item Open Access Extreme clonality in lymphoblastoid cell lines with implications for allele specific expression analyses(2008) Plagnol V.; Uz, E.; Wallace, C.; Stevens H.; Clayton, D.; Ozcelik, T.; Todd J.A.Lymphoblastoid cell lines (LCL) are being actively and extensively used to examine the expression of specific genes and (genome-wide expression profiles, including allele specific expression assays. However, it has recently been shown that approximately 10% of human genes exhibit random patterns of monoallelic expression within single clones of LCLs. Consequently allelic imbalance studies could be significantly compromised if bulk populations of donor cells are clonal, or near clonal. Here, using X chromosome inactivation as a readout, we confirm and quantify widespread near monoclonality in two independent sets of cell lines. Consequently, we recommend where possible the use of bulk, non cell line, ex vivo cells for allele specific expression assays. © 2008 Plagnol et al.Item Open Access Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel(Nature Publishing Group, 2014) Delaneau O.; Marchini J.; McVeanh G.A.; Donnelly P.; Lunter G.; Marchini J.L.; Myers, S.; Gupta-Hinch, A.; Iqbal, Z.; Mathieson I.; Rimmer, A.; Xifara, D.K.; Kerasidou, A.; Churchhouse, C.; Altshuler, D.M.; Gabriel, S.B.; Lander, E.S.; Gupta, N.; Daly, M.J.; DePristo, M.A.; Banks, E.; Bhatia G.; Carneiro, M.O.; Del Angel G.; Genovese G.; Handsaker, R.E.; Hartl, C.; McCarroll, S.A.; Nemesh J.C.; Poplin, R.E.; Schaffner, S.F.; Shakir, K.; Sabeti P.C.; Grossman, S.R.; Tabrizi, S.; Tariyal, R.; Li H.; Reich, D.; Durbin, R.M.; Hurles, M.E.; Balasubramaniam, S.; Burton J.; Danecek P.; Keane, T.M.; Kolb-Kokocinski, A.; McCarthy, S.; Stalker J.; Quail, M.; Ayub Q.; Chen, Y.; Coffey, A.J.; Colonna V.; Huang, N.; Jostins L.; Scally, A.; Walter, K.; Xue, Y.; Zhang, Y.; Blackburne, B.; Lindsay, S.J.; Ning, Z.; Frankish, A.; Harrow J.; Chris, T.-S.; Abecasis G.R.; Kang H.M.; Anderson P.; Blackwell, T.; Busonero F.; Fuchsberger, C.; Jun G.; Maschio, A.; Porcu, E.; Sidore, C.; Tan, A.; Trost, M.K.; Bentley, D.R.; Grocock, R.; Humphray, S.; James, T.; Kingsbury, Z.; Bauer, M.; Cheetham, R.K.; Cox, T.; Eberle, M.; Murray L.; Shaw, R.; Chakravarti, A.; Clark, A.G.; Keinan, A.; Rodriguez-Flores J.L.; De LaVega F.M.; Degenhardt J.; Eichler, E.E.; Flicek P.; Clarke L.; Leinonen, R.; Smith, R.E.; Zheng-Bradley X.; Beal, K.; Cunningham F.; Herrero J.; McLaren W.M.; Ritchie G.R.S.; Barker J.; Kelman G.; Kulesha, E.; Radhakrishnan, R.; Roa, A.; Smirnov, D.; Streeter I.; Toneva I.; Gibbs, R.A.; Dinh H.; Kovar, C.; Lee, S.; Lewis L.; Muzny, D.; Reid J.; Wang, M.; Yu F.; Bainbridge, M.; Challis, D.; Evani, U.S.; Lu J.; Nagaswamy, U.; Sabo, A.; Wang, Y.; Yu J.; Fowler G.; Hale W.; Kalra, D.; Green, E.D.; Knoppers, B.M.; Korbel J.O.; Rausch, T.; Sttz, A.M.; Lee, C.; Griffin L.; Hsieh, C.-H.; Mills, R.E.; Von Grotthuss, M.; Zhang, C.; Shi X.; Lehrach H.; Sudbrak, R.; Amstislavskiy V.S.; Lienhard, M.; Mertes F.; Sultan, M.; Timmermann, B.; Yaspo, M.L.; Herwig, S.R.; Mardis, E.R.; Wilson, R.K.; Fulton L.; Fulton, R.; Weinstock G.M.; Chinwalla, A.; Ding L.; Dooling, D.; Koboldt, D.C.; McLellan, M.D.; Wallis J.W.; Wendl, M.C.; Zhang Q.; Marth G.T.; Garrison, E.P.; Kural, D.; Lee W.-P.; Leong W.F.; Ward, A.N.; Wu J.; Zhang, M.; Nickerson, D.A.; Alkan, C.; Hormozdiari F.; Ko, A.; Sudmant P.H.; Schmidt J.P.; Davies, C.J.; Gollub J.; Webster, T.; Wong, B.; Zhan, Y.; Sherry, S.T.; Xiao, C.; Church, D.; Ananiev V.; Belaia, Z.; Beloslyudtsev, D.; Bouk, N.; Chen, C.; Cohen, R.; Cook, C.; Garner J.; Hefferon, T.; Kimelman, M.; Liu, C.; Lopez J.; Meric P.; Ostapchuk, Y.; Phan L.; Ponomarov, S.; Schneider V.; Shekhtman, E.; Sirotkin, K.; Slotta, D.; Zhang H.; Wang J.; Fang X.; Guo X.; Jian, M.; Jiang H.; Jin X.; Li G.; Li J.; Li, Y.; Liu X.; Lu, Y.; Ma X.; Tai, S.; Tang, M.; Wang, B.; Wang G.; Wu H.; Wu, R.; Yin, Y.; Zhang W.; Zhao J.; Zhao, M.; Zheng X.; Lachlan H.; Fang L.; Li Q.; Li, Z.; Lin H.; Liu, B.; Luo, R.; Shao H.; Wang, B.; Xie, Y.; Ye, C.; Yu, C.; Zheng H.; Zhu H.; Cai H.; Cao H.; Su, Y.; Tian, Z.; Yang H.; Yang L.; Zhu J.; Cai, Z.; Wang J.; Albrecht, M.W.; Borodina, T.A.; Auton, A.; Yoon, S.C.; Lihm J.; Makarov V.; Jin H.; Kim W.; Kim, K.C.; Gottipati, S.; Jones, D.; Cooper, D.N.; Ball, E.V.; Stenson P.D.; Barnes, B.; Kahn, S.; Ye, K.; Batzer, M.A.; Konkel, M.K.; Walker J.A.; MacArthur, D.G.; Lek, M.; Shriver, M.D.; Bustamante, C.D.; Gravel, S.; Kenny, E.E.; Kidd J.M.; Lacroute P.; Maples, B.K.; Moreno-Estrada, A.; Zakharia F.; Henn, B.; Sandoval, K.; Byrnes J.K.; Halperin, E.; Baran, Y.; Craig, D.W.; Christoforides, A.; Izatt, T.; Kurdoglu, A.A.; Sinari, S.A.; Homer, N.; Squire, K.; Sebat J.; Bafna V.; Ye, K.; Burchard, E.G.; Hernandez, R.D.; Gignoux, C.R.; Haussler, D.; Katzman, S.J.; Kent W.J.; Howie, B.; Ruiz-Linares, A.; Dermitzakis, E.T.; Lappalainen, T.; Devine, S.E.; Liu X.; Maroo, A.; Tallon L.J.; Rosenfeld J.A.; Michelson L.P.; Angius, A.; Cucca F.; Sanna, S.; Bigham, A.; Jones, C.; Reinier F.; Li, Y.; Lyons, R.; Schlessinger, D.; Awadalla P.; Hodgkinson, A.; Oleksyk, T.K.; Martinez-Cruzado J.C.; Fu, Y.; Liu X.; Xiong, M.; Jorde L.; Witherspoon, D.; Xing J.; Browning, B.L.; Hajirasouliha I.; Chen, K.; Albers, C.A.; Gerstein, M.B.; Abyzov, A.; Chen J.; Fu, Y.; Habegger L.; Harmanci, A.O.; Mu X.J.; Sisu, C.; Balasubramanian, S.; Jin, M.; Khurana, E.; Clarke, D.; Michaelson J.J.; OSullivan, C.; Barnes, K.C.; Gharani, N.; Toji L.H.; Gerry, N.; Kaye J.S.; Kent, A.; Mathias, R.; Ossorio P.N.; Parker, M.; Rotimi, C.N.; Royal, C.D.; Tishkoff, S.; Via, M.; Bodmer W.; Bedoya G.; Yang G.; You, C.J.; Garcia-Montero, A.; Orfao, A.; Dutil J.; Brooks L.D.; Felsenfeld, A.L.; McEwen J.E.; Clemm, N.C.; Guyer, M.S.; Peterson J.L.; Duncanson, A.; Dunn, M.; Peltonen L.A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved.Item Open Access Mdm2 Snp309 G allele displays high frequency and inverse correlation with somatic P53 mutations in hepatocellular carcinoma(Elsevier, 2010) Acun T.; Terzioǧlu-Kara, E.; Konu, O.; Ozturk, M.; Yakicier, M. C.Loss of function of the p53 protein, which may occur through a range of molecular events, is critical in hepatocellular carcinoma (HCC) evolution. MDM2, an oncogene, acts as a major regulator of the p53 protein. A polymorphism in the MDM2 promoter, SNP309 (T/G), has been shown to alter protein expression and may thus play a role in carcinogenesis. MDM2 SNP309 is also associated with HCC. However, the role of SNP309 in hepatocarcinogenesis with respect to TP53 mutations is unknown. In this study, we investigated the distribution of the MDM2 SNP309 genotype and somatic TP53 (the p53 tumor suppressor gene) mutations in 99 human HCC samples from Africa, Europe, China and Japan. Samples exhibited striking geographical differences in their distribution of SNP309 genotypes. The frequency and spectrum of p53 mutations also varied geographically; TP53 mutations were frequent in Africa, where the SNP309 T/T genotype predominated but were rare in Europe and Japan, where the SNP309 G allele was present more frequently. TP53 mutations were detected in 18% (4/22) of SNP309 T/G and G/G and 82% (18/22) of SNP309 T/T genotype holders; this difference was statistically highly significant (P-value = 0.0006). Our results indicated that the presence of the SNP309 G allele is inversely associated with the presence of somatic TP53 mutations because they only coincided in 4% of HCC cases. This finding suggests that the SNP309 G allele may functionally replace p53 mutations, and in addition to known etiological factors, may be partly responsible for differential HCC prevalence. © 2009 Elsevier B.V. All rights reserved.Item Open Access De novo insertions and deletions of predominantly paternal origin are associated with autism spectrum disorder(Elsevier, 2014) Dong, S.; Walker, M.F.; Carriero, N.J.; DiCola, M.; Willsey, A.; Ye, A.Y.; Waqar, Z.; Gonzalez L.E.; Overton J.D.; Frahm, S.; Keaney J.F.; III, Teran, N.A.; Dea J.; Mandell J.D.; HusBal V.; Sullivan, C.A.; DiLullo, N.M.; Khalil, R.O.; Gockley J.; Yuksel, Z.; Sertel, S.M.; Ercan-Sencicek, A.G.; Gupta, A.R.; Mane, S.M.; Sheldon, M.; Brooks, A.I.; Roeder, K.; Devlin, B.; State, M.W.; Wei L.; Sanders, S.J.Whole-exome sequencing (WES) studies have demonstrated the contribution of de novo loss-of-function single-nucleotide variants (SNVs) to autism spectrum disorder (ASD). However, challenges in the reliable detection of de novo insertions and deletions (indels) have limited inclusion of these variants in prior analyses. By applying a robust indel detection method to WES data from 787 ASD families (2,963 individuals), we demonstrate that de novo frameshift indels contribute to ASD risk (OR= 1.6; 95% CI= 1.0-2.7; p= 0.03), are more common in female probands (p= 0.02), are enriched among genes encoding FMRP targets (p= 6× 10-9), and arise predominantly on the paternal chromosome (p< 0.001). On the basis of mutation rates in probands versus unaffected siblings, we conclude that de novo frameshift indels contribute to risk in approximately 3% of individuals with ASD. Finally, by observing clustering of mutations in unrelated probands, we uncover two ASD-associated genes: KMT2E (MLL5), a chromatin regulator, and RIMS1, a regulator of synaptic vesicle release. © 2014 The Authors.Item Open Access PTPRD is homozygously deleted and epigenetically downregulated in human hepatocellular carcinomas(Mary Ann Liebert Inc., 2015) Acun, T.; Demir, K.; Oztas, E.; Arango, D.; Yakicier, M.C.PTPRD (protein tyrosine phosphatase, receptor type, D) is a tumor suppressor gene, frequently inactivated through deletions or epigenetic mechanisms in several cancers with importance for global health. In this study, we provide new and functionally integrated evidence on genetic and epigenetic alterations of PTPRD gene in hepatocellular carcinomas (HCCs). Importantly, HCC is the sixth most common malignancy and the third most common cause of cancer-related mortality worldwide. We used a high throughput single nucleotide polymorphism (SNP) microarray assay (Affymetrix, 10K2.0 Assay) covering the whole genome to screen an extensive panel of HCC cell lines (N=14 in total) to detect DNA copy number changes. PTPRD expression was determined in human HCCs by Q-RT-PCR and immunohistochemistry. Promoter hypermethylation was assessed by combined bisulfite restriction analysis (COBRA). DNA methyl transferase inhibitor 5-azacytidine (5-AzaC) and/or histone deacetylase inhibitor Trichostain A (TSA) were used to restore the expression. We identified homozygous deletions in Mahlavu and SNU475 cells, in the 5′UTR and coding regions, respectively. PTPRD mRNA expression was downregulated in 78.5% of cell lines and 82.6% of primary HCCs. PTPRD protein expression was also found to be lost or reduced in HCC tumor tissues. We found promoter hypermethylation in 22.2% of the paired HCC samples and restored PTPRD expression by 5-AzaC and/or TSA treatments. In conclusion, PTPRD is homozygously deleted and epigenetically downregulated in HCCs. We hypothesize PTPRD as a tumor suppressor candidate and potential cancer biomarker in human HCCs. This hypothesis is consistent with compelling evidences in other organ systems, as discussed in this article. Further functional assays in larger samples may ascertain the contribution of PTPRD to hepatocarcinogenesis in greater detail, not to forget its broader importance for diagnostic medicine and the emerging field of personalized medicine in oncology. © Copyright 2015, Mary Ann Liebert, Inc. 2015.Item Open Access Robustness of massively parallel sequencing platforms(Public Library of Science, 2015) Kavak P.; Yüksel, B.; Aksu, S.; Kulekci, M.O.; Güngör, T.; Hach F.; Şahinalp, S.C.; Alkan, C.; Saʇiroʇlu, M.Ş.The improvements in high throughput sequencing technologies (HTS) made clinical sequencing projects such as ClinSeq and Genomics England feasible. Although there are significant improvements in accuracy and reproducibility of HTS based analyses, the usability of these types of data for diagnostic and prognostic applications necessitates a near perfect data generation. To assess the usability of a widely used HTS platform for accurate and reproducible clinical applications in terms of robustness, we generated whole genome shotgun (WGS) sequence data from the genomes of two human individuals in two different genome sequencing centers. After analyzing the data to characterize SNPs and indels using the same tools (BWA, SAMtools, and GATK), we observed significant number of discrepancies in the call sets. As expected, the most of the disagreements between the call sets were found within genomic regions containing common repeats and segmental duplications, albeit only a small fraction of the discordant variants were within the exons and other functionally relevant regions such as promoters. We conclude that although HTS platforms are sufficiently powerful for providing data for first-pass clinical tests, the variant predictions still need to be confirmed using orthogonal methods before using in clinical applications. © 2015 Kavak et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.