Browsing by Subject "genetic association"

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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.
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.
Open Access
Mutation in TOR1AIP1 encoding LAP1B in a form of muscular dystrophy: A novel gene related to nuclear envelopathies
(Elsevier Ltd, 2014) Kayman-Kurekci G.; Talim, B.; Korkusuz P.; Sayar, N.; Sarioglu, T.; Oncel I.; Sharafi P.; Gundesli H.; Balci-Hayta, B.; Purali, N.; Serdaroglu-Oflazer P.; Topaloglu H.; Dincer P.
We performed genome-wide homozygosity mapping and mapped a novel myopathic phenotype to chromosomal region 1q25 in a consanguineous family with three affected individuals manifesting proximal and distal weakness and atrophy, rigid spine and contractures of the proximal and distal interphalangeal hand joints. Additionally, cardiomyopathy and respiratory involvement were noted. DNA sequencing of torsinA-interacting protein 1 (TOR1AIP1) gene encoding lamina-associated polypeptide 1B (LAP1B), showed a homozygous c.186delG mutation that causes a frameshift resulting in a premature stop codon (p.E62fsTer25). We observed that expression of LAP1B was absent in the patient skeletal muscle fibres. Ultrastructural examination showed intact sarcomeric organization but alterations of the nuclear envelope including nuclear fragmentation, chromatin bleb formation and naked chromatin. LAP1B is a type-2 integral membrane protein localized in the inner nuclear membrane that binds to both A- and B-type lamins, and is involved in the regulation of torsinA ATPase. Interestingly, luminal domain-like LAP1 (LULL1)-an endoplasmic reticulum-localized partner of torsinA-was overexpressed in the patient's muscle in the absence of LAP1B. Therefore, the findings suggest that LAP1 and LULL1 might have a compensatory effect on each other. This study expands the spectrum of genes associated with nuclear envelopathies and highlights the critical function for LAP1B in striated muscle. © 2014 Elsevier B.V.
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.
Open Access
A ranking-based meta-analysis reveals let-7 family as a meta-signature for grade classification in breast cancer
(Public Library of Science, 2015) Oztemur, Y.; Bekmez, T.; Aydos, A.; Yulug I.G.; Bozkurt, B.; Dedeoglu, B.G.
Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRTPCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms. © 2015 Oztemur et al.