Browsing by Subject "gene sequence"
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Item Open Access The bonobo genome compared with the chimpanzee and human genomes(2012) Prüfer, K.; Munch, K.; Hellmann I.; Akagi, K.; Miller J.R.; Walenz, B.; Koren, S.; Sutton G.; Kodira, C.; Winer, R.; Knight J.R.; Mullikin J.C.; Meader, S.J.; Ponting, C.P.; Lunter G.; Higashino, S.; Hobolth, A.; Dutheil J.; Karakoç, E.; Alkan, C.; Sajjadian, S.; Catacchio, C.R.; Ventura, M.; Marques-Bonet, T.; Eichler, E.E.; André, C.; Atencia, R.; Mugisha L.; Junhold J.; Patterson, N.; Siebauer, M.; Good J.M.; Fischer, A.; Ptak, S.E.; Lachmann, M.; Symer, D.E.; Mailund, T.; Schierup, M.H.; Andrés, A.M.; Kelso J.; Pääbo, S.Two African apes are the closest living relatives of humans: the chimpanzee (Pan troglodytes) and the bonobo (Pan paniscus). Although they are similar in many respects, bonobos and chimpanzees differ strikingly in key social and sexual behaviours, and for some of these traits they show more similarity with humans than with each other. Here we report the sequencing and assembly of the bonobo genome to study its evolutionary relationship with the chimpanzee and human genomes. We find that more than three per cent of the human genome is more closely related to either the bonobo or the chimpanzee genome than these are to each other. These regions allow various aspects of the ancestry of the two ape species to be reconstructed. In addition, many of the regions that overlap genes may eventually help us understand the genetic basis of phenotypes that humans share with one of the two apes to the exclusion of the other. © 2012 Macmillan Publishers Limited. All rights reserved.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 Copy number variation of individual cattle genomes using next-generation sequencing(2012) Bickhart, D.M.; Hou, Y.; Schroeder, S.G.; Alkan C.; Cardone, M.F.; Matukumalli L.K.; Song J.; Schnabel, R.D.; Ventura M.; Taylor J.F.; Garcia J.F.; Van Tassell, C.P.; Sonstegard, T.S.; Eichler, E. E.; Liu G.E.Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome - wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising ∼55.6-Mbp sequence-476 of which (~38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (∼52%, χ 2 test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome. © 2012 by Cold Spring Harbor Laboratory Press.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 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 SIP1 is downregulated in hepatocellular carcinoma by promoter hypermethylation(2011) Acun, T.; Oztas, E.; Yagci, T.; Yakicier, M.C.Background: Smad interacting protein-1 is a transcription factor that is implicated in transforming growth factor-β/bone morphogenetic protein signaling and a repressor of E-cadherin and human telomerase reverse transcriptase. It is also involved in epithelial-mesenchymal transition and tumorigenesis. However, genetic and epigenetic alterations of SIP1 have not been fully elucidated in cancers. In this study, we investigated mutations and promoter hypermethylation of the SIP1 gene in human hepatocellular carcinomas.Methods: SIP1 expression was analyzed in HCC cell lines and primary tumors in comparison to normal and non-tumor liver tissues by using semi-quantitative RT-PCR, quantitative real-time RT-PCR and immunohistochemistry. Mutation and deletion screening of the SIP1 gene were performed by direct sequencing in HCC-derived cells. Restoration of SIP1 expression was sought by treating HCC cell lines with the DNA methyl transferase inhibitor, 5-AzaC, and the histone deacetylase inhibitor, TSA. SIP1 promoter methylation was analyzed by the combined bisulfite restriction analysis assay in in silico-predicted putative promoter and CpG island regions.Results: We found that the expression of SIP1 was completely lost or reduced in five of 14 (36%) HCC cell lines and 17 of 23 (74%) primary HCC tumors. Immunohistochemical analysis confirmed that SIP1 mRNA downregulation was associated with decreased expression of the SIP1 protein in HCC tissues (82.8%). No somatic mutation was observed in SIP1 exons in any of the 14 HCC cell lines. Combined treatment with DNA methyl transferase and histone deacetylase inhibitors synergistically restored SIP1 expression in SIP1-negative cell lines. Analysis of three putative gene regulatory regions revealed tumor-specific methylation in more than half of the HCC cases.Conclusions: Epigenetic mechanisms contribute significantly to the downregulation of SIP1 expression in HCC. This finding adds a new level of complexity to the role of SIP1 in hepatocarcinogenesis. © 2011 Acun et al; licensee BioMed Central Ltd.