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Urnikyte A, Domarkiene I, Stoma S, Ambrozaityte L, Uktveryte I, Meskiene R, Kasiulevičius V, Burokiene N, Kučinskas V. CNV analysis in the Lithuanian population. BMC Genet 2016; 17:64. [PMID: 27142071 PMCID: PMC4855864 DOI: 10.1186/s12863-016-0373-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2015] [Accepted: 04/22/2016] [Indexed: 12/13/2022] Open
Abstract
Background Although copy number variation (CNV) has received much attention, knowledge about the characteristics of CNVs such as occurrence rate and distribution in the genome between populations and within the same population is still insufficient. In this study, Illumina 770 K HumanOmniExpress-12 v1.0 (and v1.1) arrays were used to examine the diversity and distribution of CNVs in 286 unrelated individuals from the two main ethnolinguistic groups of the Lithuanian population (Aukštaičiai and Žemaičiai) (see Additional file 3). For primary data analysis, the Illumina GenomeStudio™ Genotyping Module v1.9 and two algorithms, cnvPartition 3.2.0 and QuantiSNP 2.0, were used to identify high-confidence CNVs. Results A total of 478 autosomal CNVs were detected by both algorithms, and those were clustered in 87 copy number variation regions (CNVRs), spanning ~12.5 Mb of the genome (see Table 1). At least 8.6 % of the CNVRs were unique and had not been reported in the Database of Genomic Variants. Most CNVRs (57.5 %) were rare, with a frequency of <1 %, whereas common CNVRs with at least 5 % frequency made up only 1.1 % of all CNVRs identified. About 49 % of non-singleton CNVRs were shared between Aukštaičiai and Žemaičiai, and the remaining CNVRs were specific to each group. Many of the CNVs detected (66 %) overlapped with known UCSC gene regions. Conclusions The ethnolinguistic groups of the Lithuanian population could not be differentiated based on CNV profiles, which may reflect their geographical proximity and suggest the homogeneity of the Lithuanian population. In addition, putative novel CNVs unique to the Lithuanian population were identified. The results of our study enhance the CNV map of the Lithuanian population. Electronic supplementary material The online version of this article (doi:10.1186/s12863-016-0373-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- A Urnikyte
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania.
| | - I Domarkiene
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - S Stoma
- Master of Science (MSc), Bioinformatics student, VU University Amsterdam, Amsterdam, Netherlands
| | - L Ambrozaityte
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - I Uktveryte
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - R Meskiene
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - V Kasiulevičius
- Clinics of Internal Diseases, Family Medicine and Oncology, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - N Burokiene
- Clinics of Internal Diseases, Family Medicine and Oncology, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
| | - V Kučinskas
- Department of Human and Medical Genetics, Faculty of Medicine, Vilnius University, Santariskiu St. 2, LT-08661, Vilnius, Lithuania
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152
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Williams RC, Elston RC, Kumar P, Knowler WC, Abboud HE, Adler S, Bowden DW, Divers J, Freedman BI, Igo RP, Ipp E, Iyengar SK, Kimmel PL, Klag MJ, Kohn O, Langefeld CD, Leehey DJ, Nelson RG, Nicholas SB, Pahl MV, Parekh RS, Rotter JI, Schelling JR, Sedor JR, Shah VO, Smith MW, Taylor KD, Thameem F, Thornley-Brown D, Winkler CA, Guo X, Zager P, Hanson RL. Selecting SNPs informative for African, American Indian and European Ancestry: application to the Family Investigation of Nephropathy and Diabetes (FIND). BMC Genomics 2016; 17:325. [PMID: 27142425 PMCID: PMC4855449 DOI: 10.1186/s12864-016-2654-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Accepted: 04/22/2016] [Indexed: 01/06/2023] Open
Abstract
Background The presence of population structure in a sample may confound the search for important genetic loci associated with disease. Our four samples in the Family Investigation of Nephropathy and Diabetes (FIND), European Americans, Mexican Americans, African Americans, and American Indians are part of a genome- wide association study in which population structure might be particularly important. We therefore decided to study in detail one component of this, individual genetic ancestry (IGA). From SNPs present on the Affymetrix 6.0 Human SNP array, we identified 3 sets of ancestry informative markers (AIMs), each maximized for the information in one the three contrasts among ancestral populations: Europeans (HAPMAP, CEU), Africans (HAPMAP, YRI and LWK), and Native Americans (full heritage Pima Indians). We estimate IGA and present an algorithm for their standard errors, compare IGA to principal components, emphasize the importance of balancing information in the ancestry informative markers (AIMs), and test the association of IGA with diabetic nephropathy in the combined sample. Results A fixed parental allele maximum likelihood algorithm was applied to the FIND to estimate IGA in four samples: 869 American Indians; 1385 African Americans; 1451 Mexican Americans; and 826 European Americans. When the information in the AIMs is unbalanced, the estimates are incorrect with large error. Individual genetic admixture is highly correlated with principle components for capturing population structure. It takes ~700 SNPs to reduce the average standard error of individual admixture below 0.01. When the samples are combined, the resulting population structure creates associations between IGA and diabetic nephropathy. Conclusions The identified set of AIMs, which include American Indian parental allele frequencies, may be particularly useful for estimating genetic admixture in populations from the Americas. Failure to balance information in maximum likelihood, poly-ancestry models creates biased estimates of individual admixture with large error. This also occurs when estimating IGA using the Bayesian clustering method as implemented in the program STRUCTURE. Odds ratios for the associations of IGA with disease are consistent with what is known about the incidence and prevalence of diabetic nephropathy in these populations. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2654-x) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Robert C Williams
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA.
| | - Robert C Elston
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Pankaj Kumar
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - Hanna E Abboud
- Division of Nephrology, The University of Texas Health Science Center, San Antonio, TX, 78229, USA
| | - Sharon Adler
- Department of Nephrology, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Donald W Bowden
- Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | - Jasmin Divers
- Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA
| | | | - Robert P Igo
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Eli Ipp
- Department of Nephrology, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Sudha K Iyengar
- Genetic Analysis and Data Coordinating Center, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Paul L Kimmel
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 20892, USA
| | - Michael J Klag
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, MD, 21205, USA
| | - Orly Kohn
- The University of Chicago Medical Center, Chicago, IL, 60637, USA
| | | | - David J Leehey
- Loyola University Medical Center, Chicago, IL, 60153, USA
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
| | - Susanne B Nicholas
- Divisions of Nephrology and Endocrinology, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Madeleine V Pahl
- Division of Nephrology and Hypertension, Department of Medicine, UC Irvine School of Medicine, University of California, Orange, 92868, CA, USA
| | - Rulan S Parekh
- Hospital for Sick Children, University Health Network and the University of Toronto, Ontario, M5G1X8, Canada
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Jeffrey R Schelling
- Departments of Medicine and Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - John R Sedor
- Departments of Medicine and Physiology and Biophysics, Case Western Reserve University, Cleveland, OH, 44104, USA
| | - Vallabh O Shah
- The University of New Mexico, Albuquerque, NM, 87131, USA
| | - Michael W Smith
- National Human Genome Research Institute, NIH, Bethesda, MD, 20892, USA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Farook Thameem
- Division of Nephrology, The University of Texas Health Science Center, San Antonio, TX, 78229, USA.,Department of Biochemistry, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait
| | | | - Cheryl A Winkler
- Center for Cancer Research, National Cancer Institute, NIH, Leidos Biomedical, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Phillip Zager
- The University of New Mexico, Albuquerque, NM, 87131, USA
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, 85014, USA
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Stamoulis C, Betensky RA. Optimization of Signal Decomposition Matched Filtering (SDMF) for Improved Detection of Copy-Number Variations. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2016; 13:584-591. [PMID: 27295643 PMCID: PMC4905595 DOI: 10.1109/tcbb.2015.2448077] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
We aim to improve the performance of the previously proposed signal decomposition matched filtering (SDMF) method [26] for the detection of copy-number variations (CNV) in the human genome. Through simulations, we show that the modified SDMF is robust even at high noise levels and outperforms the original SDMF method, which indirectly depends on CNV frequency. Simulations are also used to develop a systematic approach for selecting relevant parameter thresholds in order to optimize sensitivity, specificity and computational efficiency. We apply the modified method to array CGH data from normal samples in the cancer genome atlas (TCGA) and compare detected CNVs to those estimated using circular binary segmentation (CBS) [19], a hidden Markov model (HMM)-based approach [11] and a subset of CNVs in the Database of Genomic Variants. We show that a substantial number of previously identified CNVs are detected by the optimized SDMF, which also outperforms the other two methods.
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Affiliation(s)
- Catherine Stamoulis
- Department of Radiology, Harvard Medical School and Boston Children’s Hospital, Boston, MA 02115
| | - Rebecca A. Betensky
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115
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154
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Mohan S, Nampoothiri S, Yesodharan D, Venkatesan V, Koshy T, Paul SFD, Perumal V. Reciprocal Microduplication of the Williams-Beuren Syndrome Chromosome Region in a 9-Year-Old Omani Boy. Lab Med 2016; 47:171-5. [PMID: 27069036 DOI: 10.1093/labmed/lmw005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Microdeletions of the 7q11.23 Williams-Beuren syndrome chromosome region (WBSCR) are reported with a frequency of 1 in 10,000, whereas microduplications of the region, although expected to occur at the same frequency, are not widely reported. METHOD We evaluated a 9-year old Omani boy for idiopathic intellectual disability using genetic methods, including multiplex ligation-dependent probe amplification (MLPA), for detection of microdeletions (P064-B3). RESULTS MLPA analysis revealed that the boy has a rare microduplication of the WBSCR. Prominent clinical features include global developmental delay with pronounced speech delay, dysmorphic facies, and autistic features. CONCLUSION Microduplications, in general, are reported at a lesser frequency, perhaps owing to their milder phenotype. Complete genetic assessment in children with idiopathic intellectual disability would help in identifying rare conditions such as duplication of the WBSCR.
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Affiliation(s)
- Shruthi Mohan
- Department of Human Genetics, Sri Ramachandra University, Chennai, India
| | - Sheela Nampoothiri
- Department of Pediatric Genetics, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | - Dhanya Yesodharan
- Department of Pediatric Genetics, Amrita Institute of Medical Sciences & Research Center, Kochi, India
| | | | - Teena Koshy
- Department of Human Genetics, Sri Ramachandra University, Chennai, India
| | - Solomon F D Paul
- Department of Human Genetics, Sri Ramachandra University, Chennai, India
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155
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Saadati HR, Wittig M, Helbig I, Häsler R, Anderson CA, Mathew CG, Kupcinskas L, Parkes M, Karlsen TH, Rosenstiel P, Schreiber S, Franke A. Genome-wide rare copy number variation screening in ulcerative colitis identifies potential susceptibility loci. BMC MEDICAL GENETICS 2016; 17:26. [PMID: 27037036 PMCID: PMC4818401 DOI: 10.1186/s12881-016-0289-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Accepted: 03/23/2016] [Indexed: 12/30/2022]
Abstract
Background Ulcerative colitis (UC), a complex polygenic disorder, is one of the main subphenotypes of inflammatory bowel disease. A comprehensive dissection of the genetic etiology of UC needs to assess the contribution of rare genetic variants including copy number variations (CNVs) to disease risk. In this study, we performed a multi-step genome-wide case-control analysis to interrogate the presence of disease-relevant rare copy number variants. Methods One thousand one hundred twenty-one German UC patients and 1770 healthy controls were initially screened for rare deletions and duplications employing SNP-array data. Quantitative PCR and high density custom array-CGH were used for validation of identified CNVs and fine mapping. Two main follow-up panels consisted of an independent cohort of 451 cases and 1274 controls, in which CNVs were assayed through quantitative PCR, and a British cohort of 2396 cases versus 4886 controls with CNV genotypes based on array data. Additional sample sets were assessed for targeted and in silico replication. Results Twenty-four rare copy number variants (14 deletions and 10 duplications), overrepresented in UC patients were identified in the initial screening panel. Follow-up of these CNV regions in four independent case-control series as well as an additional public in silico control group (totaling 4439 UC patients and 15,961 healthy controls) revealed three copy number variants enriched in UC patients; a 15.8 kb deletion upstream of ABCC4 and CLDN10 at13q32.1 (0.43 % cases, 0.11 % controls), a 119 kb duplication at 7p22.1, overlapping RNF216, ZNF815, OCM and CCZ1 (0.13 % cases, 0.01 % controls) and a 134 kb large duplication upstream of the KCNK9 gene at 8q24.3 (0.22 % carriers among cases, 0.03 % carriers among controls). The trend of association with UC was present after the P-values were corrected for combining data from different subpopulations. Break-point mapping of the deleted region suggested non-allelic homologous recombination as the mechanism underlying its formation. Conclusion Our study presents a pragmatic approach for effective rare CNV screening of SNP-array data sets and implicates the potential contribution of rare structural variants in the pathogenesis of UC. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0289-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Hamid Reza Saadati
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany
| | - Ingo Helbig
- Department of Neuropediatrics, University Clinic Schleswig-Holstein, Campus Kiel, Arnold-Heller-Strasse 3, Building 9, 24105, Kiel, Germany
| | - Robert Häsler
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany
| | - Carl A Anderson
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
| | - Christopher G Mathew
- Department of Medical and Molecular Genetics, King's College London School of Medicine, London, UK
| | - Limas Kupcinskas
- Institute for Digestive Research, Lithuanian University of Health Sciences, Mickeviciaus 9, Kaunas, LT, 44307, Lithuania
| | - Miles Parkes
- Inflammatory Bowel Disease Research Group, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 2QQ, UK
| | - Tom Hemming Karlsen
- Norwegian PSC Research Center, Clinic for Specialized Medicine and Surgery, Oslo University Hospital, Rikshospitalet, 0027, Oslo, Norway
| | - Philip Rosenstiel
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany.,Department of Internal Medicine, University Hospital Schleswig-Holstein, Schittenhelmstraße 12, 24105, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Schittenhelmstr. 12, 24105, Kiel, Germany.
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156
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Huang MC, Chuang TP, Chen CH, Wu JY, Chen YT, Li LH, Yang HC. An integrated analysis tool for analyzing hybridization intensities and genotypes using new-generation population-optimized human arrays. BMC Genomics 2016; 17:266. [PMID: 27029637 PMCID: PMC4815280 DOI: 10.1186/s12864-016-2478-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 02/16/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Affymetrix Axiom single nucleotide polymorphism (SNP) arrays provide a cost-effective, high-density, and high-throughput genotyping solution for population-optimized analyses. However, no public software is available for the integrated genomic analysis of hybridization intensities and genotypes for this new-generation population-optimized genotyping platform. RESULTS A set of statistical methods was developed for an integrated analysis of allele frequency (AF), allelic imbalance (AI), loss of heterozygosity (LOH), long contiguous stretch of homozygosity (LCSH), and copy number variation or alteration (CNV/CNA) on the basis of SNP probe hybridization intensities and genotypes. This study analyzed 3,236 samples that were genotyped using different SNP platforms. The proposed AF adjustment method considerably increased the accuracy of AF estimation. The proposed quick circular binary segmentation algorithm for segmenting copy number reduced the computation time of the original segmentation method by 30-67 %. The proposed CNV/CNA detection, which integrates AI and LOH/LCSH detection, had a promising true positive rate and well-controlled false positive rate in simulation studies. Moreover, our real-time quantitative polymerase chain reaction experiments successfully validated the CNVs/CNAs that were identified in the Axiom data analyses using the proposed methods; some of the validated CNVs/CNAs were not detected in the Affymetrix Array 6.0 data analysis using the Affymetrix Genotyping Console. All the analysis functions are packaged into the ALICE (AF/LOH/LCSH/AI/CNV/CNA Enterprise) software. CONCLUSIONS ALICE and the used genomic reference databases, which can be downloaded from http://hcyang.stat.sinica.edu.tw/software/ALICE.html , are useful resources for analyzing genomic data from the Axiom and other SNP arrays.
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Affiliation(s)
- Mei-Chu Huang
- Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan.,Institute of Statistical Science, Academia Sinica, No 128, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan.,Institute of Biomedical Informatics, National Yang-Ming University, Taipei, 112, Taiwan
| | - Tzu-Po Chuang
- Taiwan International Graduate Program in Molecular Medicine, National Yang-Ming University and Academia Sinica, Taipei, 115, Taiwan.,Institute of Biochemistry and Molecular Biology, National Yang-Ming University, Taipei, 112, Taiwan
| | - Chien-Hsiun Chen
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Jer-Yuarn Wu
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Yuan-Tsong Chen
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan
| | - Ling-Hui Li
- Institute of Biomedical Sciences, Academia Sinica, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan.
| | - Hsin-Chou Yang
- Bioinformatics Program, Taiwan International Graduate Program, Institute of Information Science, Academia Sinica, Taipei, 115, Taiwan. .,Institute of Statistical Science, Academia Sinica, No 128, Academia Rd, Sec 2, Nankang, Taipei, 115, Taiwan. .,Institute of Public Health, National Yang Ming University, Taipei, 112, Taiwan. .,Department of Statistics, National Cheng Kung University, Tainan, 701, Taiwan. .,Institute of Statistics, National Tsing Hua University, Hsinchu, 300, Taiwan. .,School of Public Health, National Defense Medical Center, Taipei, 114, Taiwan.
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157
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Xu L, Hou Y, Bickhart DM, Zhou Y, Hay EHA, Song J, Sonstegard TS, Van Tassell CP, Liu GE. Population-genetic properties of differentiated copy number variations in cattle. Sci Rep 2016; 6:23161. [PMID: 27005566 PMCID: PMC4804293 DOI: 10.1038/srep23161] [Citation(s) in RCA: 53] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 02/25/2016] [Indexed: 01/24/2023] Open
Abstract
While single nucleotide polymorphism (SNP) is typically the variant of choice for population genetics, copy number variation (CNV) which comprises insertion, deletion and duplication of genomic sequence, is an informative type of genetic variation. CNVs have been shown to be both common in mammals and important for understanding the relationship between genotype and phenotype. However, CNV differentiation, selection and its population genetic properties are not well understood across diverse populations. We performed a population genetics survey based on CNVs derived from the BovineHD SNP array data of eight distinct cattle breeds. We generated high resolution results that show geographical patterns of variations and genome-wide admixture proportions within and among breeds. Similar to the previous SNP-based studies, our CNV-based results displayed a strong correlation of population structure and geographical location. By conducting three pairwise comparisons among European taurine, African taurine, and indicine groups, we further identified 78 unique CNV regions that were highly differentiated, some of which might be due to selection. These CNV regions overlapped with genes involved in traits related to parasite resistance, immunity response, body size, fertility, and milk production. Our results characterize CNV diversity among cattle populations and provide a list of lineage-differentiated CNVs.
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Affiliation(s)
- Lingyang Xu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Yali Hou
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, 100101, China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Yang Zhou
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
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158
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Genome-wide screening identifies a KCNIP1 copy number variant as a genetic predictor for atrial fibrillation. Nat Commun 2016; 7:10190. [PMID: 26831368 PMCID: PMC4740744 DOI: 10.1038/ncomms10190] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2014] [Accepted: 11/16/2015] [Indexed: 01/01/2023] Open
Abstract
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Previous genome-wide association studies had identified single-nucleotide polymorphisms in several genomic regions to be associated with AF. In human genome, copy number variations (CNVs) are known to contribute to disease susceptibility. Using a genome-wide multistage approach to identify AF susceptibility CNVs, we here show a common 4,470-bp diallelic CNV in the first intron of potassium interacting channel 1 gene (KCNIP1) is strongly associated with AF in Taiwanese populations (odds ratio=2.27 for insertion allele; P=6.23 × 10(-24)). KCNIP1 insertion is associated with higher KCNIP1 mRNA expression. KCNIP1-encoded protein potassium interacting channel 1 (KCHIP1) is physically associated with potassium Kv channels and modulates atrial transient outward current in cardiac myocytes. Overexpression of KCNIP1 results in inducible AF in zebrafish. In conclusions, a common CNV in KCNIP1 gene is a genetic predictor of AF risk possibly pointing to a functional pathway.
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159
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Zhang Z, Zheng Y, Zhang X, Liu C, Joyce BT, Kibbe WA, Hou L, Zhang W. Linking short tandem repeat polymorphisms with cytosine modifications in human lymphoblastoid cell lines. Hum Genet 2016; 135:223-32. [PMID: 26714498 PMCID: PMC4715638 DOI: 10.1007/s00439-015-1628-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 12/17/2015] [Indexed: 01/26/2023]
Abstract
Inter-individual variation in cytosine modifications has been linked to complex traits in humans. Cytosine modification variation is partially controlled by single nucleotide polymorphisms (SNPs), known as modified cytosine quantitative trait loci (mQTL). However, little is known about the role of short tandem repeat polymorphisms (STRPs), a class of structural genetic variants, in regulating cytosine modifications. Utilizing the published data on the International HapMap Project lymphoblastoid cell lines (LCLs), we assessed the relationships between 721 STRPs and the modification levels of 283,540 autosomal CpG sites. Our findings suggest that, in contrast to the predominant cis-acting mode for SNP-based mQTL, STRPs are associated with cytosine modification levels in both cis-acting (local) and trans-acting (distant) modes. In local scans within the ±1 Mb windows of target CpGs, 21, 9, and 21 cis-acting STRP-based mQTL were detected in CEU (Caucasian residents from Utah, USA), YRI (Yoruba people from Ibadan, Nigeria), and the combined samples, respectively. In contrast, 139,420, 76,817, and 121,866 trans-acting STRP-based mQTL were identified in CEU, YRI, and the combined samples, respectively. A substantial proportion of CpG sites detected with local STRP-based mQTL were not associated with SNP-based mQTL, suggesting that STRPs represent an independent class of mQTL. Functionally, genetic variants neighboring CpG-associated STRPs are enriched with genome-wide association study (GWAS) loci for a variety of complex traits and diseases, including cancers, based on the National Human Genome Research Institute (NHGRI) GWAS Catalog. Therefore, elucidating these STRP-based mQTL in addition to SNP-based mQTL can provide novel insights into the genetic architectures of complex traits.
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Affiliation(s)
- Zhou Zhang
- Driskill Graduate Program in Life Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Dr., Suite 1400, Chicago, IL, 60611, USA
| | - Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Dr., Suite 1400, Chicago, IL, 60611, USA
- Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Xu Zhang
- Section of Hematology/Oncology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Cong Liu
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Brian Thomas Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Dr., Suite 1400, Chicago, IL, 60611, USA
- Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL, 60612, USA
| | - Warren A Kibbe
- Center for Biomedical Informatics and Information Technology, National Cancer Institute, Rockville, MD, 20850, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Dr., Suite 1400, Chicago, IL, 60611, USA
- The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Wei Zhang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N. Lake Shore Dr., Suite 1400, Chicago, IL, 60611, USA.
- The Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
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160
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Abstract
Chromosomal copy number changes are frequently associated with harmful consequences and are thought of as an underlying mechanism for the development of diseases. However, changes in copy number are observed during development and occur during normal biological processes. In this review, we highlight the causes and consequences of copy number changes in normal physiologic processes as well as cover their associations with cancer and acquired drug resistance. We discuss the permanent and transient nature of copy number gains and relate these observations to a new mechanism driving transient site-specific copy gains (TSSGs). Finally, we discuss implications of TSSGs in generating intratumoral heterogeneity and tumor evolution and how TSSGs can influence the therapeutic response in cancer.
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Affiliation(s)
- Sweta Mishra
- Massachusetts General Hospital Cancer Center and Department of Medicine, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Johnathan R Whetstine
- Massachusetts General Hospital Cancer Center and Department of Medicine, Harvard Medical School, Charlestown, Massachusetts, USA
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161
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Wang MD, Dzama K, Rees DJG, Muchadeyi FC. Tropically adapted cattle of Africa: perspectives on potential role of copy number variations. Anim Genet 2015; 47:154-64. [DOI: 10.1111/age.12391] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/01/2015] [Indexed: 12/12/2022]
Affiliation(s)
- M. D. Wang
- Department of Animal Sciences; University of Stellenbosch; Private Bag X1 Matieland 7602 South Africa
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
| | - K. Dzama
- Department of Animal Sciences; University of Stellenbosch; Private Bag X1 Matieland 7602 South Africa
| | - D. J. G. Rees
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
| | - F. C. Muchadeyi
- Biotechnology Platform; Agricultural Research Council; Private Bag X5 Onderstepoort 0110 South Africa
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162
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Expression Differentiation Is Constrained to Low-Expression Proteins over Ecological Timescales. Genetics 2015; 202:273-83. [PMID: 26546003 DOI: 10.1534/genetics.115.180547] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2015] [Accepted: 11/04/2015] [Indexed: 02/03/2023] Open
Abstract
Protein expression level is one of the strongest predictors of protein sequence evolutionary rate, with high-expression protein sequences evolving at slower rates than low-expression protein sequences largely because of constraints on protein folding and function. Expression evolutionary rates also have been shown to be negatively correlated with expression level across human and mouse orthologs over relatively long divergence times (i.e., ∼100 million years). Long-term evolutionary patterns, however, often cannot be extrapolated to microevolutionary processes (and vice versa), and whether this relationship holds for traits evolving under directional selection within a single species over ecological timescales (i.e., <5000 years) is unknown and not necessarily expected. Expression is a metabolically costly process, and the expression level of a particular protein is predicted to be a tradeoff between the benefit of its function and the costs of its expression. Selection should drive the expression level of all proteins close to values that maximize fitness, particularly for high-expression proteins because of the increased energetic cost of production. Therefore, stabilizing selection may reduce the amount of standing expression variation for high-expression proteins, and in combination with physiological constraints that may place an upper bound on the range of beneficial expression variation, these constraints could severely limit the availability of beneficial expression variants. To determine whether rapid-expression evolution was restricted to low-expression proteins owing to these constraints on highly expressed proteins over ecological timescales, we compared venom protein expression levels across mainland and island populations for three species of pit vipers. We detected significant differentiation in protein expression levels in two of the three species and found that rapid-expression differentiation was restricted to low-expression proteins. Our results suggest that various constraints on high-expression proteins reduce the availability of beneficial expression variants relative to low-expression proteins, enabling low-expression proteins to evolve and potentially lead to more rapid adaptation.
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163
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Visvikis-Siest S, Stathopoulou MG. Beyond genome-wide association studies: identifying variants using -omics approaches. Per Med 2015; 12:529-531. [PMID: 29750611 DOI: 10.2217/pme.15.34] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Affiliation(s)
- Sophie Visvikis-Siest
- INSERM UMR U1122; IGE-PCV "Interactions Gène-Environnement en Physiopathologie CardioVasculaire", Université de Lorraine, Faculté de Pharmacie, 30 Rue Lionnois, 54000 Nancy, France
| | - Maria G Stathopoulou
- INSERM UMR U1122; IGE-PCV "Interactions Gène-Environnement en Physiopathologie CardioVasculaire", Université de Lorraine, Faculté de Pharmacie, 30 Rue Lionnois, 54000 Nancy, France
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164
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Gene copy number variation analysis reveals dosage-insensitive expression of CYP2E1. THE PHARMACOGENOMICS JOURNAL 2015; 16:551-558. [PMID: 26503817 DOI: 10.1038/tpj.2015.69] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2015] [Revised: 08/06/2015] [Accepted: 08/19/2015] [Indexed: 01/21/2023]
Abstract
Gene copy number variants (CNVs) of CYP2E1 have been described but not functionally characterized. Here we investigated effects of CNVs on hepatic and lymphoblastoid CYP2E1 expression. Using available single-nuleotide polymorphism microarray data and quantitative PCR, CYP2E1 gene duplication and deletion carriers were identified. CYP2E1 mRNA, protein and enzyme activity (chlorzoxazone-6-hydroxylation) phenotypes of CYP2E1 were not associated with gene copy number. Analysis of gene expression in lymphoblastoid cell lines in relation to CNV confirmed this finding in an extrahepatic tissue and for other ethnicities. Further analyses identified a linked haplotype cluster with possible influence on gene expression. In summary, our data suggest a homeostatic, gene dosage-insensitive regulation of CYP2E1 expression by unknown gene dosage compensation mechanisms. This is in striking contrast to well-known structural variations of CYP2A6 and CYP2D6 that have a strong impact on expression and activity. These findings are important in the context of pharmacogenetic prediction.
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165
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Sudmant PH, Rausch T, Gardner EJ, Handsaker RE, Abyzov A, Huddleston J, Zhang Y, Ye K, Jun G, Hsi-Yang Fritz M, Konkel MK, Malhotra A, Stütz AM, Shi X, Paolo Casale F, Chen J, Hormozdiari F, Dayama G, Chen K, Malig M, Chaisson MJP, Walter K, Meiers S, Kashin S, Garrison E, Auton A, Lam HYK, Jasmine Mu X, Alkan C, Antaki D, Bae T, Cerveira E, Chines P, Chong Z, Clarke L, Dal E, Ding L, Emery S, Fan X, Gujral M, Kahveci F, Kidd JM, Kong Y, Lameijer EW, McCarthy S, Flicek P, Gibbs RA, Marth G, Mason CE, Menelaou A, Muzny DM, Nelson BJ, Noor A, Parrish NF, Pendleton M, Quitadamo A, Raeder B, Schadt EE, Romanovitch M, Schlattl A, Sebra R, Shabalin AA, Untergasser A, Walker JA, Wang M, Yu F, Zhang C, Zhang J, Zheng-Bradley X, Zhou W, Zichner T, Sebat J, Batzer MA, McCarroll SA, Mills RE, Gerstein MB, Bashir A, Stegle O, Devine SE, Lee C, Eichler EE, Korbel JO. An integrated map of structural variation in 2,504 human genomes. Nature 2015; 526:75-81. [PMID: 26432246 PMCID: PMC4617611 DOI: 10.1038/nature15394] [Citation(s) in RCA: 1422] [Impact Index Per Article: 158.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2015] [Accepted: 08/20/2015] [Indexed: 12/11/2022]
Abstract
Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.
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Affiliation(s)
- Peter H. Sudmant
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
| | - Tobias Rausch
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Eugene J. Gardner
- Institute for Genome Sciences, University of Maryland School of Medicine, 801 W Baltimore Street, Baltimore, 21201 Maryland USA
| | - Robert E. Handsaker
- Department of Genetics, Harvard Medical School, 25 Shattuck Street, Boston, Boston, 02115 Massachusetts USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
| | - Alexej Abyzov
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, 200 First Street SW, Rochester, 55905 Minnesota USA
| | - John Huddleston
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
- Howard Hughes Medical Institute, University of Washington, Seattle, 98195 Washington USA
| | - Yan Zhang
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Department of Molecular Biophysics and Biochemistry, School of Medicine, Yale University, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
| | - Kai Ye
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Department of Genetics, Washington University in St Louis, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
| | - Goo Jun
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, 48109 Michigan USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, 77030 Texas USA
| | - Markus Hsi-Yang Fritz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Miriam K. Konkel
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, 70803 Louisiana USA
| | - Ankit Malhotra
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
| | - Adrian M. Stütz
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Xinghua Shi
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, 28223 North Carolina USA
| | - Francesco Paolo Casale
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
| | - Jieming Chen
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, 06520 Connecticut USA
| | - Fereydoun Hormozdiari
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
| | - Gargi Dayama
- Department of Computational Medicine & Bioinformatics, University of Michigan, 500 S. State Street, Ann Arbor, 48109 Michigan USA
| | - Ken Chen
- The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, 77030 Texas USA
| | - Maika Malig
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
| | - Mark J. P. Chaisson
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
| | - Klaudia Walter
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA Cambridge UK
| | - Sascha Meiers
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Seva Kashin
- Department of Genetics, Harvard Medical School, 25 Shattuck Street, Boston, Boston, 02115 Massachusetts USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
| | - Erik Garrison
- Department of Biology, Boston College, 355 Higgins Hall, 140 Commonwealth Avenue, Chestnut Hill, 02467 Massachusetts USA
| | - Adam Auton
- Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, 10461 New York USA
| | - Hugo Y. K. Lam
- Bina Technologies, Roche Sequencing, 555 Twin Dolphin Drive, Redwood City, 94065 California USA
| | - Xinmeng Jasmine Mu
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Cancer Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
| | - Can Alkan
- Department of Computer Engineering, Bilkent University, Ankara, 06800 Turkey
| | - Danny Antaki
- University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, 92093 California USA
| | - Taejeong Bae
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, 200 First Street SW, Rochester, 55905 Minnesota USA
| | - Eliza Cerveira
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
| | - Peter Chines
- National Human Genome Research Institute, National Institutes of Health, Bethesda, 20892 Maryland USA
| | - Zechen Chong
- The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, 77030 Texas USA
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
| | - Elif Dal
- Department of Computer Engineering, Bilkent University, Ankara, 06800 Turkey
| | - Li Ding
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Department of Genetics, Washington University in St Louis, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Department of Medicine, Washington University in St Louis, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Siteman Cancer Center, 660 South Euclid Avenue, St Louis, 63110 Missouri USA
| | - Sarah Emery
- Department of Human Genetics, University of Michigan, 1241 Catherine Street, Ann Arbor, 48109 Michigan USA
| | - Xian Fan
- The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, 77030 Texas USA
| | - Madhusudan Gujral
- University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, 92093 California USA
| | - Fatma Kahveci
- Department of Computer Engineering, Bilkent University, Ankara, 06800 Turkey
| | - Jeffrey M. Kidd
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, 48109 Michigan USA
- Department of Human Genetics, University of Michigan, 1241 Catherine Street, Ann Arbor, 48109 Michigan USA
| | - Yu Kong
- Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, 10461 New York USA
| | - Eric-Wubbo Lameijer
- Molecular Epidemiology, Leiden University Medical Center, Leiden, 2300RA The Netherlands
| | - Shane McCarthy
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA Cambridge UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
| | - Richard A. Gibbs
- Baylor College of Medicine, 1 Baylor Plaza, Houston, 77030 Texas USA
| | - Gabor Marth
- Department of Biology, Boston College, 355 Higgins Hall, 140 Commonwealth Avenue, Chestnut Hill, 02467 Massachusetts USA
| | - Christopher E. Mason
- The Department of Physiology and Biophysics and the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, 1305 York Avenue, Weill Cornell Medical College, New York, 10065 New York USA
- The Feil Family Brain and Mind Research Institute, 413 East 69th St, Weill Cornell Medical College, New York, 10065 New York USA
| | - Androniki Menelaou
- University of Oxford, 1 South Parks Road, Oxford, OX3 9DS UK
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, 3584 CG The Netherlands
| | - Donna M. Muzny
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
| | - Bradley J. Nelson
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
| | - Amina Noor
- University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, 92093 California USA
| | - Nicholas F. Parrish
- Institute for Virus Research, Kyoto University, 53 Shogoin Kawahara-cho, Sakyo-ku, 606-8507 Kyoto Japan
| | - Matthew Pendleton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
| | - Andrew Quitadamo
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, 28223 North Carolina USA
| | - Benjamin Raeder
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Eric E. Schadt
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
| | - Mallory Romanovitch
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
| | - Andreas Schlattl
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
| | - Andrey A. Shabalin
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, McGuire Hall, Richmond, 23298-0581 Virginia USA
| | - Andreas Untergasser
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
- Zentrum für Molekulare Biologie, University of Heidelberg, Im Neuenheimer Feld 282, Heidelberg, 69120 Germany
| | - Jerilyn A. Walker
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, 70803 Louisiana USA
| | - Min Wang
- Baylor College of Medicine, 1 Baylor Plaza, Houston, 77030 Texas USA
| | - Fuli Yu
- Baylor College of Medicine, 1 Baylor Plaza, Houston, 77030 Texas USA
| | - Chengsheng Zhang
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
| | - Jing Zhang
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Department of Molecular Biophysics and Biochemistry, School of Medicine, Yale University, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
| | - Xiangqun Zheng-Bradley
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
| | - Wanding Zhou
- The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, 77030 Texas USA
| | - Thomas Zichner
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
| | - Jonathan Sebat
- University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, 92093 California USA
| | - Mark A. Batzer
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, 70803 Louisiana USA
| | - Steven A. McCarroll
- Department of Genetics, Harvard Medical School, 25 Shattuck Street, Boston, Boston, 02115 Massachusetts USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
| | - The 1000 Genomes Project Consortium
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
- Institute for Genome Sciences, University of Maryland School of Medicine, 801 W Baltimore Street, Baltimore, 21201 Maryland USA
- Department of Genetics, Harvard Medical School, 25 Shattuck Street, Boston, Boston, 02115 Massachusetts USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
- Department of Health Sciences Research, Center for Individualized Medicine, Mayo Clinic, 200 First Street SW, Rochester, 55905 Minnesota USA
- Howard Hughes Medical Institute, University of Washington, Seattle, 98195 Washington USA
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Department of Molecular Biophysics and Biochemistry, School of Medicine, Yale University, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- The Genome Institute, Washington University School of Medicine, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Department of Genetics, Washington University in St Louis, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, 48109 Michigan USA
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler St., Houston, 77030 Texas USA
- Department of Biological Sciences, Louisiana State University, 202 Life Sciences Building, Baton Rouge, 70803 Louisiana USA
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
- Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, 28223 North Carolina USA
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
- Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, 06520 Connecticut USA
- Department of Computational Medicine & Bioinformatics, University of Michigan, 500 S. State Street, Ann Arbor, 48109 Michigan USA
- The University of Texas MD Anderson Cancer Center, 1515 Holcombe Boulevard, Houston, 77030 Texas USA
- The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, CB10 1SA Cambridge UK
- Department of Biology, Boston College, 355 Higgins Hall, 140 Commonwealth Avenue, Chestnut Hill, 02467 Massachusetts USA
- Department of Genetics, Albert Einstein College of Medicine, 1301 Morris Park Avenue, Bronx, 10461 New York USA
- Bina Technologies, Roche Sequencing, 555 Twin Dolphin Drive, Redwood City, 94065 California USA
- Cancer Program, Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, 02142 Massachusetts USA
- Department of Computer Engineering, Bilkent University, Ankara, 06800 Turkey
- University of California San Diego (UCSD), 9500 Gilman Drive, La Jolla, 92093 California USA
- National Human Genome Research Institute, National Institutes of Health, Bethesda, 20892 Maryland USA
- Department of Medicine, Washington University in St Louis, 4444 Forest Park Avenue, St Louis, 63108 Missouri USA
- Siteman Cancer Center, 660 South Euclid Avenue, St Louis, 63110 Missouri USA
- Department of Human Genetics, University of Michigan, 1241 Catherine Street, Ann Arbor, 48109 Michigan USA
- Molecular Epidemiology, Leiden University Medical Center, Leiden, 2300RA The Netherlands
- Baylor College of Medicine, 1 Baylor Plaza, Houston, 77030 Texas USA
- The Department of Physiology and Biophysics and the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, 1305 York Avenue, Weill Cornell Medical College, New York, 10065 New York USA
- The Feil Family Brain and Mind Research Institute, 413 East 69th St, Weill Cornell Medical College, New York, 10065 New York USA
- University of Oxford, 1 South Parks Road, Oxford, OX3 9DS UK
- Department of Medical Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, 3584 CG The Netherlands
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
- Institute for Virus Research, Kyoto University, 53 Shogoin Kawahara-cho, Sakyo-ku, 606-8507 Kyoto Japan
- Center for Biomarker Research and Precision Medicine, Virginia Commonwealth University, 1112 East Clay Street, McGuire Hall, Richmond, 23298-0581 Virginia USA
- Zentrum für Molekulare Biologie, University of Heidelberg, Im Neuenheimer Feld 282, Heidelberg, 69120 Germany
- Department of Computer Science, Yale University, 51 Prospect Street, New Haven, 06511 Connecticut USA
- Department of Graduate Studies – Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, 120-750 Seoul South Korea
| | - Ryan E. Mills
- Department of Computational Medicine & Bioinformatics, University of Michigan, 500 S. State Street, Ann Arbor, 48109 Michigan USA
- Department of Human Genetics, University of Michigan, 1241 Catherine Street, Ann Arbor, 48109 Michigan USA
| | - Mark B. Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, BASS 432 & 437, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Department of Molecular Biophysics and Biochemistry, School of Medicine, Yale University, 266 Whitney Avenue, New Haven, 06520 Connecticut USA
- Department of Computer Science, Yale University, 51 Prospect Street, New Haven, 06511 Connecticut USA
| | - Ali Bashir
- Department of Genetics and Genomic Sciences, Icahn School of Medicine, New York School of Natural Sciences, 1428 Madison Avenue, New York, 10029 New York USA
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
| | - Scott E. Devine
- Institute for Genome Sciences, University of Maryland School of Medicine, 801 W Baltimore Street, Baltimore, 21201 Maryland USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, 10 Discovery 263 Farmington Avenue, Farmington, 06030 Connecticut USA
- Department of Graduate Studies – Life Sciences, Ewha Womans University, Ewhayeodae-gil, Seodaemun-gu, 120-750 Seoul South Korea
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington, 3720 15th Avenue NE, Seattle, 98195-5065 Washington USA
- Howard Hughes Medical Institute, University of Washington, Seattle, 98195 Washington USA
| | - Jan O. Korbel
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Meyerhofstrasse 1, Heidelberg, 69117 Germany
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, CB10 1SD Cambridge UK
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Anjum S, Morganella S, D'Angelo F, Iavarone A, Ceccarelli M. VEGAWES: variational segmentation on whole exome sequencing for copy number detection. BMC Bioinformatics 2015; 16:315. [PMID: 26416038 PMCID: PMC4587906 DOI: 10.1186/s12859-015-0748-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2015] [Accepted: 09/16/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Copy number variations are important in the detection and progression of significant tumors and diseases. Recently, Whole Exome Sequencing is gaining popularity with copy number variations detection due to low cost and better efficiency. In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data. RESULTS We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. The results on the real data were analyzed with segmentation obtained from Single-nucleotide polymorphism data as ground truth. We compared our results with two other segmentation algorithms and assessed the performance based on accuracy and time. CONCLUSIONS In terms of both accuracy and time, VEGAWES provided better results on the synthetic data and tumor samples demonstrating its potential in robust detection of aberrant regions in the genome.
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Affiliation(s)
- Samreen Anjum
- Computational Sciences and Engineering, Qatar Computing Research Institute, Doha, P. O. Box 5825, Qatar.
| | - Sandro Morganella
- European Molecular Biology Laboratory, European Bioinformatics Institute, (EMBL -EBI), Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK.
| | | | - Antonio Iavarone
- Institute for Cancer Genetics, Columbia University, New York, 10027, USA.
| | - Michele Ceccarelli
- Computational Sciences and Engineering, Qatar Computing Research Institute, Doha, P. O. Box 5825, Qatar. .,Department of Science and Technology, University of Sannio, Benevento, 82100, Italy.
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167
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Somatic mosaicism for copy-neutral loss of heterozygosity and DNA copy number variations in the human genome. BMC Genomics 2015; 16:703. [PMID: 26376747 PMCID: PMC4573927 DOI: 10.1186/s12864-015-1916-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2015] [Accepted: 09/09/2015] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Somatic mosaicism denotes the presence of genetically distinct populations of somatic cells in one individual who has developed from a single fertilised oocyte. Mosaicism may result from a mutation that occurs during postzygotic development and is propagated to only a subset of the adult cells. Our aim was to investigate both somatic mosaicism for copy-neutral loss of heterozygosity (cn-LOH) events and DNA copy number variations (CNVs) in fully differentiated tissues. RESULTS We studied panels of tissue samples (11-12 tissues per individual) from four autopsy subjects using high-resolution Illumina HumanOmniExpress-12 BeadChips to reveal the presence of possible intra-individual tissue-specific cn-LOH and CNV patterns. We detected five mosaic cn-LOH regions >5 Mb in some tissue samples in three out of four individuals. We also detected three CNVs that affected only a portion of the tissues studied in one out of four individuals. These three somatic CNVs range from 123 to 796 kb and are also found in the general population. An attempt was made to explain the succession of genomic events that led to the observed somatic genetic mosaicism under the assumption that the specific mosaic patterns of CNV and cn-LOH changes reflect their formation during the postzygotic embryonic development of germinal layers and organ systems. CONCLUSIONS Our results give further support to the idea that somatic mosaicism for CNVs, and also cn-LOHs, is a common phenomenon in phenotypically normal humans. Thus, the examination of only a single tissue might not provide enough information to diagnose potentially deleterious CNVs within an individual. During routine CNV and cn-LOH analysis, DNA derived from a buccal swab can be used in addition to blood DNA to get information about the CNV/cn-LOH content in tissues of both mesodermal and ectodermal origin. Currently, the real frequency and possible phenotypic consequences of both CNVs and cn-LOHs that display somatic mosaicism remain largely unknown. To answer these questions, future studies should involve larger cohorts of individuals and a range of tissues.
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168
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Sudmant PH, Mallick S, Nelson BJ, Hormozdiari F, Krumm N, Huddleston J, Coe BP, Baker C, Nordenfelt S, Bamshad M, Jorde LB, Posukh OL, Sahakyan H, Watkins WS, Yepiskoposyan L, Abdullah MS, Bravi CM, Capelli C, Hervig T, Wee JTS, Tyler-Smith C, van Driem G, Romero IG, Jha AR, Karachanak-Yankova S, Toncheva D, Comas D, Henn B, Kivisild T, Ruiz-Linares A, Sajantila A, Metspalu E, Parik J, Villems R, Starikovskaya EB, Ayodo G, Beall CM, Di Rienzo A, Hammer MF, Khusainova R, Khusnutdinova E, Klitz W, Winkler C, Labuda D, Metspalu M, Tishkoff SA, Dryomov S, Sukernik R, Patterson N, Reich D, Eichler EE. Global diversity, population stratification, and selection of human copy-number variation. Science 2015; 349:aab3761. [PMID: 26249230 PMCID: PMC4568308 DOI: 10.1126/science.aab3761] [Citation(s) in RCA: 231] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2015] [Accepted: 07/29/2015] [Indexed: 12/14/2022]
Abstract
In order to explore the diversity and selective signatures of duplication and deletion human copy-number variants (CNVs), we sequenced 236 individuals from 125 distinct human populations. We observed that duplications exhibit fundamentally different population genetic and selective signatures than deletions and are more likely to be stratified between human populations. Through reconstruction of the ancestral human genome, we identify megabases of DNA lost in different human lineages and pinpoint large duplications that introgressed from the extinct Denisova lineage now found at high frequency exclusively in Oceanic populations. We find that the proportion of CNV base pairs to single-nucleotide-variant base pairs is greater among non-Africans than it is among African populations, but we conclude that this difference is likely due to unique aspects of non-African population history as opposed to differences in CNV load.
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Affiliation(s)
- Peter H Sudmant
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Swapan Mallick
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Bradley J Nelson
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | | | - Niklas Krumm
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - John Huddleston
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
| | - Bradley P Coe
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Carl Baker
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Susanne Nordenfelt
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Michael Bamshad
- Department of Pediatrics, University of Washington, Seattle, WA 98119, USA
| | - Lynn B Jorde
- Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Olga L Posukh
- Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Novosibirsk State University, Novosibirsk 630090, Russia
| | - Hovhannes Sahakyan
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia. Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - W Scott Watkins
- Department of Human Genetics, Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Levon Yepiskoposyan
- Laboratory of Ethnogenomics, Institute of Molecular Biology, National Academy of Sciences of Armenia, Yerevan 0014, Armenia
| | - M Syafiq Abdullah
- Raja Isteri Pengiran Anak Saleha (RIPAS) Hospital, Bandar Seri Begawan, Brunei Darussalam
| | - Claudio M Bravi
- Laboratorio de Genética Molecular Poblacional, Instituto Multidisciplinario de Biología Celular (IMBICE), Centro Científico y Tecnológico-Consejo Nacional de Investigaciones Científicas y Técnicas (CCT-CONICET) and Comisión de Investigaciones Científicas de la Provincia de Buenos Aires (CICPBA), La Plata B1906APO, Argentina
| | | | - Tor Hervig
- Department of Clinical Science, University of Bergen, Bergen 5021, Norway
| | | | - Chris Tyler-Smith
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | - George van Driem
- Institute of Linguistics, University of Bern, Bern CH-3012, Switzerland
| | | | - Aashish R Jha
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Sena Karachanak-Yankova
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - Draga Toncheva
- Department of Medical Genetics, National Human Genome Center, Medical University Sofia, Sofia 1431, Bulgaria
| | - David Comas
- Institut de Biologia Evolutiva [Consejo Superior de Investigaciones Científicas-Universitat Pompeu Fabra (CSIC-UPF)], Departament de Ciències Experimentals i de la Salut, UPF, Barcelona 08003, Spain
| | - Brenna Henn
- Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY 11794, USA
| | - Toomas Kivisild
- Division of Biological Anthropology, University of Cambridge, Fitzwilliam Street, Cambridge CB2 1QH, UK
| | - Andres Ruiz-Linares
- Department of Genetics, Evolution and Environment, University College London, WC1E 6BT, UK
| | - Antti Sajantila
- University of Helsinki, Department of Forensic Medicine, Helsinki 00014, Finland
| | - Ene Metspalu
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia. University of Tartu, Department of Evolutionary Biology, Tartu 5101, Estonia
| | - Jüri Parik
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Richard Villems
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Elena B Starikovskaya
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - George Ayodo
- Center for Global Health and Child Development, Kisumu 40100, Kenya
| | - Cynthia M Beall
- Department of Anthropology, Case Western Reserve University, Cleveland, OH 44106-7125, USA
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Michael F Hammer
- Arizona Research Laboratories Division of Biotechnology, University of Arizona, Tucson, AZ 85721, USA
| | - Rita Khusainova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia. Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - Elza Khusnutdinova
- Institute of Biochemistry and Genetics, Ufa Research Centre, Russian Academy of Sciences, Ufa 450054, Russia. Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa 450074, Russia
| | - William Klitz
- Integrative Biology, University of California, Berkeley, CA 94720-3140, USA
| | - Cheryl Winkler
- Basic Research Laboratory, Center for Cancer Research, National Cancer Institute, Leidos Biomedical Research, Incorporated, Frederick National Laboratory, Frederick, MD 21702, USA
| | - Damian Labuda
- Centre Hospitalier Universitaire (CHU) Sainte-Justine, Département de Pédiatrie, Université de Montréal, QC H3T 1C5, Canada
| | - Mait Metspalu
- Estonian Biocentre, Evolutionary Biology Group, Tartu 51010, Estonia
| | - Sarah A Tishkoff
- Departments of Biology and Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Stanislav Dryomov
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Department of Paleolithic Archaeology, Institute of Archaeology and Ethnography, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia
| | - Rem Sukernik
- Laboratory of Human Molecular Genetics, Institute of Molecular and Cellular Biology, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630090, Russia. Altai State University, Barnaul 656000, Russia
| | - Nick Patterson
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - David Reich
- Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142, USA. Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Evan E Eichler
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA. Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA.
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Nutsua ME, Fischer A, Nebel A, Hofmann S, Schreiber S, Krawczak M, Nothnagel M. Family-Based Benchmarking of Copy Number Variation Detection Software. PLoS One 2015. [PMID: 26197066 PMCID: PMC4510559 DOI: 10.1371/journal.pone.0133465] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.
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Affiliation(s)
- Marcel Elie Nutsua
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Annegret Fischer
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Sylvia Hofmann
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Stefan Schreiber
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Michael Krawczak
- Institute of Medical Informatics and Statistics, Christian-Albrechts University, Kiel, Germany
| | - Michael Nothnagel
- Institute of Medical Informatics and Statistics, Christian-Albrechts University, Kiel, Germany; Cologne Center for Genomics, University of Cologne, Cologne, Germany
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170
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Abstract
Hundreds of copy number variants are complex and multi-allelic, in that they have many structural alleles and have rearranged multiple times in the ancestors who contributed chromosomes to current humans. Not only are the relationships of these multi-allelic CNVs (mCNVs) to phenotypes generally unknown, but many mCNVs have not yet been described at the basic levels—alleles, allele frequencies, structural features—that support genetic investigation. To date, most reported disease associations to these variants have been ascertained through candidate gene studies. However, only a few associations have reached the level of acceptance defined by durable replications in many cohorts. This likely stems from longstanding challenges in making precise molecular measurements of the alleles individuals have at these loci. However, approaches for mCNV analysis are improving quickly, and some of the unique characteristics of mCNVs may assist future association studies. Their various structural alleles are likely to have different magnitudes of effect, creating a natural allelic series of growing phenotypic impact and giving investigators a set of natural predictions and testable hypotheses about the extent to which each allele of an mCNV predisposes to a phenotype. Also, mCNVs’ low-to-modest correlation to individual single-nucleotide polymorphisms (SNPs) may make it easier to distinguish between mCNVs and nearby SNPs as the drivers of an association signal, and perhaps, make it possible to preliminarily screen candidate loci, or the entire genome, for the many mCNV–disease relationships that remain to be discovered.
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171
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Mason AS, Takahira J, Atri C, Samans B, Hayward A, Cowling WA, Batley J, Nelson MN. Microspore culture reveals complex meiotic behaviour in a trigenomic Brassica hybrid. BMC PLANT BIOLOGY 2015; 15:173. [PMID: 26152188 PMCID: PMC4493989 DOI: 10.1186/s12870-015-0555-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2015] [Accepted: 06/16/2015] [Indexed: 05/10/2023]
Abstract
BACKGROUND Development of synthetic allohexaploid Brassica (2n = AABBCC) would be beneficial for agriculture, as allelic contributions from three genomes could increase hybrid vigour and broaden adaptation. Microspore culture of a near-allohexaploid hybrid derived from the cross (B. napus × B. carinata) × B. juncea was undertaken in order to assess the frequency and distribution of homologous and homoeologous crossovers in this trigenomic hybrid. SNP and SSR molecular markers were used to detect inheritance of A, B and C genome alleles in microspore-derived (MD) progeny. SNP allele copy number was also assessed. The MD progeny were also compared to progeny derived by self-pollination and open-pollination for fertility (estimated by self-pollinated seed set and pollen viability) and DNA ploidy (measured by flow cytometry). RESULTS In the trigenomic hybrid, homologous chromosome pairs A(j)-A(n), B(j)-B(c) and C(n)-C(c) had similar meiotic crossover frequencies and segregation to that previously observed in established Brassica species, as demonstrated by marker haplotype analysis of the MD population. Homoeologous pairing between chromosomes A1-C1, A2-C2 and A7-C6 was detected at frequencies of 12-18 %, with other homoeologous chromosome regions associating from 8 % (A3-C3) to 0-1 % (A8-C8, A8-C9) of the time. Copy number analysis revealed eight instances of additional chromosomes and 20 instances of chromosomes present in one copy in somatically doubled MD progeny. Presence of chromosome A6 was positively correlated with self-pollinated seed set and pollen viability in the MD population. Many MD progeny were unable to produce self-pollinated seed (76 %) or viable pollen (53 %), although one MD plant produced 198 self-pollinated seeds. Average fertility was significantly lower in progeny obtained by microspore culture than progeny obtained by self-pollination or open-pollination, after excluding MD progeny which had not undergone chromosome doubling. CONCLUSIONS Based on SNP data analysis of the microspore-derived progeny, crossover frequency per chromosome in the allohexaploid hybrid was found to be similar to that in established Brassica species, suggesting that the higher chromosome number did not significantly disrupt cellular regulation of meiosis. SNP allele copy number analysis revealed the occurrence not only of homoeologous duplication/deletion events but also other cryptic duplications and deletions that may have been the result of mitotic instability. Microspore culture simplified the assessment of chromosome behaviour in the allohexaploid hybrid but yielded progeny with lower fertility and a greater range of ploidy levels compared to progeny obtained by self- or open-pollination.
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Affiliation(s)
- Annaliese S Mason
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, 4072, Australia.
- Centre for Integrative Legume Research, The University of Queensland, Brisbane, 4072, Australia.
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany.
| | - Junko Takahira
- School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
| | - Chhaya Atri
- School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
- Plant Breeding & Genetics Department, Punjab Agricultural University, Ferozepur Road, Ludhiana, Punjab, 141004, India.
| | - Birgit Samans
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392, Giessen, Germany.
| | - Alice Hayward
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, 4072, Australia.
- Centre for Integrative Legume Research, The University of Queensland, Brisbane, 4072, Australia.
| | - Wallace A Cowling
- The UWA Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
| | - Jacqueline Batley
- School of Agriculture and Food Sciences, The University of Queensland, Brisbane, 4072, Australia.
- Centre for Integrative Legume Research, The University of Queensland, Brisbane, 4072, Australia.
- School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
| | - Matthew N Nelson
- School of Plant Biology, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
- The UWA Institute of Agriculture, The University of Western Australia, 35 Stirling Highway, Crawley, 6009, Perth, Australia.
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Lou H, Lu Y, Lu D, Fu R, Wang X, Feng Q, Wu S, Yang Y, Li S, Kang L, Guan Y, Hoh BP, Chung YJ, Jin L, Su B, Xu S. A 3.4-kb Copy-Number Deletion near EPAS1 Is Significantly Enriched in High-Altitude Tibetans but Absent from the Denisovan Sequence. Am J Hum Genet 2015; 97:54-66. [PMID: 26073780 DOI: 10.1016/j.ajhg.2015.05.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2015] [Accepted: 05/07/2015] [Indexed: 10/23/2022] Open
Abstract
Tibetan high-altitude adaptation (HAA) has been studied extensively, and many candidate genes have been reported. Subsequent efforts targeting HAA functional variants, however, have not been that successful (e.g., no functional variant has been suggested for the top candidate HAA gene, EPAS1). With WinXPCNVer, a method developed in this study, we detected in microarray data a Tibetan-enriched deletion (TED) carried by 90% of Tibetans; 50% were homozygous for the deletion, whereas only 3% carried the TED and 0% carried the homozygous deletion in 2,792 worldwide samples (p < 10(-15)). We employed long PCR and Sanger sequencing technologies to determine the exact copy number and breakpoints of the TED in 70 additional Tibetan and 182 diverse samples. The TED had identical boundaries (chr2: 46,694,276-46,697,683; hg19) and was 80 kb downstream of EPAS1. Notably, the TED was in strong linkage disequilibrium (LD; r(2) = 0.8) with EPAS1 variants associated with reduced blood concentrations of hemoglobin. It was also in complete LD with the 5-SNP motif, which was suspected to be introgressed from Denisovans, but the deletion itself was absent from the Denisovan sequence. Correspondingly, we detected that footprints of positive selection for the TED occurred 12,803 (95% confidence interval = 12,075-14,725) years ago. We further whole-genome deep sequenced (>60×) seven Tibetans and verified the TED but failed to identify any other copy-number variations with comparable patterns, giving this TED top priority for further study. We speculate that the specific patterns of the TED resulted from its own functionality in HAA of Tibetans or LD with a functional variant of EPAS1.
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173
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Li P, Wang YD, Cheng J, Chen JC, Ha MW. Association between polymorphisms of BAG-1 and XPD and chemotherapy sensitivity in advanced non-small-cell lung cancer patients treated with vinorelbine combined cisplatin regimen. Tumour Biol 2015; 36:9465-73. [PMID: 26124006 DOI: 10.1007/s13277-015-3672-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2015] [Accepted: 06/15/2015] [Indexed: 12/18/2022] Open
Abstract
BCL-2 Associated athanogene 1 (BAG-1) and Xeroderma pigmentosum group D (XPD) are involved in the nucleotide excision repair pathway and DNA repair. We aimed to investigate whether polymorphisms in BAG-1 and XPD have effects on chemotherapy sensitivity and survival in patients with advanced non-small-cell lung cancer (NSCLC) treated with vinorelbine combined cisplatin (NP) regimen. A total of 142 patients with diagnosed advanced NSCLC were recruited in the current study. NP regimen was applied for all eligible patients. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was used for BAG-1 (codon 324) and XPD (codons 312 and 751) genotyping. The treatment response was evaluated according to the RECIST guidelines. Progression-free survival (PFS) and overall survival (OS) were record as median and end point, respectively. As for BAG-1 codon 324, the chemotherapy sensitivity in NSCLC patients with CT genotype was 0.383 times of those with CC genotype (P < 0.05). With respect to XPD codon 751, the chemotherapy sensitivity in NSCLC patients with Lys/Gln genotype was 0.400 times of those with Lys/Lys genotype (P < 0.05). In addition, NSCLC patients carrying combined C/C genotype at codon 324 in BAG-1, Asp/Asp of XPD codon 312, and Lys/Lys of XPD codon 751 produced a higher efficacy of NP chemotherapy compared to those carrying mutation genotypes (all P < 0.05). Further, there were significant differences in PFS between patients with combined C/C genotype of BAG-1 codon 324, Lys/Lys genotype of XPD codon 751, and Asp/Asp genotype of XPD codon 312 and patients carrying BAG-1 codon 324 C/T genotype, XPD codon751 Lys/Gln genotype, and XPD codon312 Asp/Asn genotype (P < 0.05). Multivariate Cox regression analysis indicated that the combined wild-type of codon 324 XPD, codon 751 XPD, and codon 312 BAG-1 is the protective factor for OS and PFS, and clinical stages is the risk factor for OS and PFS. In conclusion, our research demonstrated the combined effects of BAG-1 and XPD polymorphisms on chemotherapy sensitivity and survival in patients with advanced NSCLC, which might be the important predictive markers for platinum-based chemotherapy efficacy.
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Affiliation(s)
- Ping Li
- Department of Oncology, The First Affiliated Hospital of Liaoning Medical University, Five Section of Renmin Street No. 2, Guta District, Jinzhou, 121000, People's Republic of China
| | - Ya-Di Wang
- Department of Oncology, The Third Affiliated Hospital of Liaoning Medical University, Jinzhou, 121000, People's Republic of China
| | - Jian Cheng
- Department of Oncology, Binzhou Medical University Hospital, Binzhou, 256603, People's Republic of China
| | - Jun-Chen Chen
- Department of Thoracic Surgery, Hubei Rongjun Hospital, Wuhan, 430079, People's Republic of China
| | - Min-Wen Ha
- Department of Oncology, The First Affiliated Hospital of Liaoning Medical University, Five Section of Renmin Street No. 2, Guta District, Jinzhou, 121000, People's Republic of China.
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174
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Ng J, Trask JS, Smith DG, Kanthaswamy S. Heterospecific SNP diversity in humans and rhesus macaque (Macaca mulatta). J Med Primatol 2015; 44:194-201. [PMID: 25963897 DOI: 10.1111/jmp.12174] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/09/2015] [Indexed: 11/30/2022]
Abstract
BACKGROUND Conservation of single nucleotide polymorphisms (SNPs) between human and other primates (i.e., heterospecific SNPs) in candidate genes can be used to assess the utility of those organisms as models for human biomedical research. METHODS A total of 59,691 heterospecific SNPs in 22 rhesus macaques and 20 humans were analyzed for human trait associations and 4207 heterospecific SNPs biallelic in both taxa were compared for genetic variation. RESULTS Variation comparisons at the 4207 SNPs showed that humans were more genetically diverse than rhesus macaques with observed and expected heterozygosities of 0.337 and 0.323 vs. 0.119 and 0.102, and minor allele frequencies of 0.239 and 0.063, respectively. In total, 431 of the 59,691 heterospecific SNPs are reportedly associated with human-specific traits. CONCLUSION While comparisons between human and rhesus macaque genomes are plausible, functional studies of heterospecific SNPs are necessary to determine whether rhesus macaque alleles are associated with the same phenotypes as their corresponding human alleles.
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Affiliation(s)
- Jillian Ng
- Molecular Anthropology Laboratory, Department of Anthropology, University of California, Davis, CA, USA
| | - Jessica Satkoski Trask
- Molecular Anthropology Laboratory, Department of Anthropology, University of California, Davis, CA, USA.,California National Primate Research Center, University of California, Davis, CA, USA
| | - David Glenn Smith
- Molecular Anthropology Laboratory, Department of Anthropology, University of California, Davis, CA, USA.,California National Primate Research Center, University of California, Davis, CA, USA
| | - Sree Kanthaswamy
- Molecular Anthropology Laboratory, Department of Anthropology, University of California, Davis, CA, USA.,California National Primate Research Center, University of California, Davis, CA, USA.,School of Mathematics and Natural Sciences, Arizona State University (ASU) at the West Campus, Glendale, AZ, USA.,Department of Environmental Toxicology, University of California, Davis, CA, USA
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175
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Cui H, Dhroso A, Johnson N, Korkin D. The variation game: Cracking complex genetic disorders with NGS and omics data. Methods 2015; 79-80:18-31. [PMID: 25944472 DOI: 10.1016/j.ymeth.2015.04.018] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2014] [Revised: 03/27/2015] [Accepted: 04/17/2015] [Indexed: 12/14/2022] Open
Abstract
Tremendous advances in Next Generation Sequencing (NGS) and high-throughput omics methods have brought us one step closer towards mechanistic understanding of the complex disease at the molecular level. In this review, we discuss four basic regulatory mechanisms implicated in complex genetic diseases, such as cancer, neurological disorders, heart disease, diabetes, and many others. The mechanisms, including genetic variations, copy-number variations, posttranscriptional variations, and epigenetic variations, can be detected using a variety of NGS methods. We propose that malfunctions detected in these mechanisms are not necessarily independent, since these malfunctions are often found associated with the same disease and targeting the same gene, group of genes, or functional pathway. As an example, we discuss possible rewiring effects of the cancer-associated genetic, structural, and posttranscriptional variations on the protein-protein interaction (PPI) network centered around P53 protein. The review highlights multi-layered complexity of common genetic disorders and suggests that integration of NGS and omics data is a critical step in developing new computational methods capable of deciphering this complexity.
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Affiliation(s)
- Hongzhu Cui
- Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States
| | - Andi Dhroso
- Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States
| | - Nathan Johnson
- Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States
| | - Dmitry Korkin
- Department of Computer Science, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States; Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 01609, United States
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176
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Abstract
Recent years have witnessed a flurry of important technological and methodological developments in the discovery and analysis of copy number variations (CNVs), which are increasingly enabling the systematic evaluation of their impact on a broad range of phenotypes from molecular-level (intermediate) traits to higher-order clinical phenotypes. Like single nucleotide variants in the human genome, CNVs have been linked to complex traits in humans, including disease and drug response. These recent developments underscore the importance of incorporating complex forms of genetic variation into disease mapping studies and promise to transform our understanding of genome function and the genetic basis of disease. Here we review some of the findings that have emerged from transcriptome studies of CNVs facilitated by the rapid advances in -omics technologies and corresponding methodologies.
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177
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Haplotype phasing and inheritance of copy number variants in nuclear families. PLoS One 2015; 10:e0122713. [PMID: 25853576 PMCID: PMC4390228 DOI: 10.1371/journal.pone.0122713] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2014] [Accepted: 02/12/2015] [Indexed: 11/19/2022] Open
Abstract
DNA copy number variants (CNVs) that alter the copy number of a particular DNA segment in the genome play an important role in human phenotypic variability and disease susceptibility. A number of CNVs overlapping with genes have been shown to confer risk to a variety of human diseases thus highlighting the relevance of addressing the variability of CNVs at a higher resolution. So far, it has not been possible to deterministically infer the allelic composition of different haplotypes present within the CNV regions. We have developed a novel computational method, called PiCNV, which enables to resolve the haplotype sequence composition within CNV regions in nuclear families based on SNP genotyping microarray data. The algorithm allows to i) phase normal and CNV-carrying haplotypes in the copy number variable regions, ii) resolve the allelic copies of rearranged DNA sequence within the haplotypes and iii) infer the heritability of identified haplotypes in trios or larger nuclear families. To our knowledge this is the first program available that can deterministically phase null, mono-, di-, tri- and tetraploid genotypes in CNV loci. We applied our method to study the composition and inheritance of haplotypes in CNV regions of 30 HapMap Yoruban trios and 34 Estonian families. For 93.6% of the CNV loci, PiCNV enabled to unambiguously phase normal and CNV-carrying haplotypes and follow their transmission in the corresponding families. Furthermore, allelic composition analysis identified the co-occurrence of alternative allelic copies within 66.7% of haplotypes carrying copy number gains. We also observed less frequent transmission of CNV-carrying haplotypes from parents to children compared to normal haplotypes and identified an emergence of several de novo deletions and duplications in the offspring.
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178
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Abstract
Significant progress in our understanding of Crohn's disease (CD), an archetypal common, complex disease, has now been achieved. Our ability to interrogate the deep complexities of the biological processes involved in maintaining gut mucosal homeostasis is a major over-riding factor underpinning this rapid progress. Key studies now offer many novel and expansive insights into the interacting roles of genetic susceptibility, immune function, and the gut microbiota in CD. Here, we provide overviews of these recent advances and new mechanistic themes, and address the challenges and prospects for translation from concept to clinic.
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Affiliation(s)
- Ray Boyapati
- Centre for Inflammation Research, Queens Medical Research Institute, University of EdinburghEdinburgh, EH16 4TJUK
- Gastrointestinal Unit, Institute of Genetics and Molecular Medicine, Western General HospitalEdinburgh, EH4 2XUUK
| | - Jack Satsangi
- Centre for Inflammation Research, Queens Medical Research Institute, University of EdinburghEdinburgh, EH16 4TJUK
- Gastrointestinal Unit, Institute of Genetics and Molecular Medicine, Western General HospitalEdinburgh, EH4 2XUUK
| | - Gwo-Tzer Ho
- Centre for Inflammation Research, Queens Medical Research Institute, University of EdinburghEdinburgh, EH16 4TJUK
- Gastrointestinal Unit, Institute of Genetics and Molecular Medicine, Western General HospitalEdinburgh, EH4 2XUUK
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179
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Jordan VK, Rosenfeld JA, Lalani SR, Scott DA. Duplication of HEY2 in cardiac and neurologic development. Am J Med Genet A 2015; 167A:2145-9. [PMID: 25832314 DOI: 10.1002/ajmg.a.37086] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Accepted: 03/15/2015] [Indexed: 11/10/2022]
Abstract
HEY2 is a basic helix-loop-helix (bHLH) transcription factor that plays an important role in the developing mammalian heart and brain. In humans, nonsynonymous mutations in HEY2 have been described in patients with atrial ventricular septal defects, and a subset of individuals with chromosomal deletions involving HEY2 have cardiac defects and cognitive impairment. Less is known about the potential effects of HEY2 overexpression. Here, we describe a female child with tetralogy of Fallot who developed severe right ventricular outflow tract obstruction due to a combination of infundibular and valvular pulmonary stenosis. She was also noted to have hypotonia, lower extremity weakness, fine motor delay and speech delay. A copy number variation (CNV) detection analysis followed by real-time quantitative PCR analysis revealed a single gene duplication of HEY2. This is the only duplication involving HEY2 identified in our database of over 70,000 individuals referred for CNV analysis. In the developing heart, overexpression of HEY2 is predicted to cause decreased expression of the cardiac transcription factor GATA4 which, in turn, has been shown to cause tetralogy of Fallot. In mice, misexpression of Hey2 in the developing brain leads to inhibition of neurogenesis and promotion of gliogenesis. Hence, duplication of HEY2 may be a contributing factor to both the congenital heart defects and the neurodevelopmental problems evident in our patient. These results suggest that individuals with HEY2 duplications should be screened for congenital heart defects and monitored closely for evidence of developmental delay and/or cognitive impairment.
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Affiliation(s)
- Valerie K Jordan
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX
| | - Jill A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Seema R Lalani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Daryl A Scott
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, Houston, TX.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
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180
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Chimusa ER, Meintjies A, Tchanga M, Mulder N, Seoighe C, Soodyall H, Ramesar R. A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations. PLoS Genet 2015; 11:e1005052. [PMID: 25811879 PMCID: PMC4374865 DOI: 10.1371/journal.pgen.1005052] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 02/02/2015] [Indexed: 11/21/2022] Open
Abstract
We report a study of genome-wide, dense SNP (∼900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region. Genome-wide analysis of human populations is useful in shedding light on the evolutionary history of the human genome, with a wide range of applications from reconstructing past associations between different population histories to disease mapping. In this manuscript we report on the application of genome-wide data to southern African populations and the identification of genome-wide signatures of selection pre- and post-admixture. Several signals of selection, before and after admixture, were identified, some of which involved loci associated with human diseases, including malaria, influenza, tuberculosis and HIV/AIDS. These results may reflect adaptations of southern African populations to infectious diseases. Consistent with previous studies, this study highlights the significance of the San in the genetics of human populations, as they are distinct from the other populations in many respects i.e. haplotype structure, locations of recombination hotspots, copy number and population structure. Furthermore, our study demonstrates the admixture of the San, Bantu-speaking populations and populations of Eurasian ancestry in some of the southern and eastern African populations. It illustrates the value in correcting for this stratification in future genome-wide association studies, and suggests that a future admixture mapping in these populations would likely be warranted and successful.
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Affiliation(s)
- Emile R. Chimusa
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | - Ayton Meintjies
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Milaine Tchanga
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Nicola Mulder
- Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
| | - Cathal Seoighe
- School of Mathematics, Statistics and Applied Mathematics, National University of Ireland Galway, Galway, Ireland
| | - Himla Soodyall
- Division of Human Genetics, School of Pathology, Faculty of Health Sciences, University of Witwatersrand and the National Health Laboratory Service, Johannesburg, South Africa
| | - Rajkumar Ramesar
- MRC Human Genetics Research Unit, Division of Human Genetics, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
- * E-mail:
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181
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Fjeld K, Weiss FU, Lasher D, Rosendahl J, Chen JM, Johansson BB, Kirsten H, Ruffert C, Masson E, Steine SJ, Bugert P, Cnop M, Grützmann R, Mayerle J, Mössner J, Ringdal M, Schulz HU, Sendler M, Simon P, Sztromwasser P, Torsvik J, Scholz M, Tjora E, Férec C, Witt H, Lerch MM, Njølstad PR, Johansson S, Molven A. A recombined allele of the lipase gene CEL and its pseudogene CELP confers susceptibility to chronic pancreatitis. Nat Genet 2015; 47:518-522. [PMID: 25774637 PMCID: PMC5321495 DOI: 10.1038/ng.3249] [Citation(s) in RCA: 125] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Accepted: 02/19/2015] [Indexed: 12/13/2022]
Abstract
Carboxyl-ester lipase is a digestive pancreatic enzyme encoded by the highly polymorphic CEL gene1. Mutations in CEL cause maturity-onset diabetes of the young (MODY) with pancreatic exocrine dysfunction2. Here we identified a hybrid allele (CEL-HYB), originating from a crossover between CEL and its neighboring pseudogene CELP. In a discovery cohort of familial chronic pancreatitis cases, the carrier frequency of CEL-HYB was 14.1% (10/71) compared with 1.0% (5/478) in controls (odds ratio [OR] = 15.5, 95% confidence interval [CI] = 5.1-46.9, P = 1.3 × 10−6). Three replication studies in non-alcoholic chronic pancreatitis cohorts identified CEL-HYB in a total of 3.7% (42/1,122) cases and 0.7% (30/4,152) controls (OR = 5.2, 95% CI = 3.2-8.5, P = 1.2 × 10−11; formal meta-analysis). The allele was also enriched in alcoholic chronic pancreatitis. Expression of CEL-HYB in cellular models revealed reduced lipolytic activity, impaired secretion, prominent intracellular accumulation and induced autophagy. The hybrid variant of CEL is the first chronic pancreatitis gene identified outside the protease/antiprotease system of pancreatic acinar cells.
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Affiliation(s)
- Karianne Fjeld
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Frank Ulrich Weiss
- Department of Internal Medicine A, Ernst-Moritz-Arndt University, Greifswald, Germany
| | - Denise Lasher
- Pediatric Nutritional Medicine, Technische Universität München (TUM), Freising, Germany.,Else Kröner-Fresenius-Zentrum für Ernährungsmedizin (EKFZ), Technische Universität München (TUM), Freising, Germany
| | - Jonas Rosendahl
- Department for Internal Medicine, Neurology and Dermatology, Division of Gastroenterology, University of Leipzig, Leipzig, Germany
| | - Jian-Min Chen
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France.,Faculté de Médecine et des Sciences de la Santé, Université de Bretagne Occidentale, Brest, France
| | - Bente B Johansson
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Holger Kirsten
- Fraunhofer Institute for Cell Therapy and Immunology (IZI), Leipzig, Germany.,LIFE-Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universität Leipzig, Leipzig, Germany
| | - Claudia Ruffert
- Department for Internal Medicine, Neurology and Dermatology, Division of Gastroenterology, University of Leipzig, Leipzig, Germany.,Department of Internal Medicine, Neurology and Dermatology, Division of Endocrinology, University of Leipzig, Leipzig, Germany.,Integrated Research and Treatment Centre (IFB) Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Emmanuelle Masson
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Laboratoire de Génétique Moléculaire et d'Histocompatibilité, Centre Hospitalier Universitaire (CHU) Brest, Hôpital Morvan, Brest, France
| | - Solrun J Steine
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Peter Bugert
- Institute of Transfusion Medicine and Immunology, Medical Faculty Mannheim, Heidelberg University, German Red Cross Blood Service of Baden-Württemberg-Hessen, Mannheim, Germany
| | - Miriam Cnop
- ULB Center for Diabetes Research, Université Libre de Bruxelles, Brussels, Belgium.,Division of Endocrinology, Erasmus Hospital, Brussels, Belgium
| | - Robert Grützmann
- Department of Surgery, Universitätsklinikum Dresden, Dresden, Germany
| | - Julia Mayerle
- Department of Internal Medicine A, Ernst-Moritz-Arndt University, Greifswald, Germany
| | - Joachim Mössner
- Department for Internal Medicine, Neurology and Dermatology, Division of Gastroenterology, University of Leipzig, Leipzig, Germany
| | - Monika Ringdal
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Hans-Ulrich Schulz
- Department of Surgery, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Matthias Sendler
- Department of Internal Medicine A, Ernst-Moritz-Arndt University, Greifswald, Germany
| | - Peter Simon
- Department of Internal Medicine A, Ernst-Moritz-Arndt University, Greifswald, Germany
| | - Paweł Sztromwasser
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway.,Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - Janniche Torsvik
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Markus Scholz
- LIFE-Leipzig Research Center for Civilization Diseases, Universität Leipzig, Leipzig, Germany.,Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Universität Leipzig, Leipzig, Germany
| | - Erling Tjora
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Claude Férec
- Institut National de la Santé et de la Recherche Médicale (INSERM), U1078, Brest, France.,Etablissement Français du Sang (EFS)-Bretagne, Brest, France.,Faculté de Médecine et des Sciences de la Santé, Université de Bretagne Occidentale, Brest, France.,Laboratoire de Génétique Moléculaire et d'Histocompatibilité, Centre Hospitalier Universitaire (CHU) Brest, Hôpital Morvan, Brest, France
| | - Heiko Witt
- Pediatric Nutritional Medicine, Technische Universität München (TUM), Freising, Germany.,Else Kröner-Fresenius-Zentrum für Ernährungsmedizin (EKFZ), Technische Universität München (TUM), Freising, Germany
| | - Markus M Lerch
- Department of Internal Medicine A, Ernst-Moritz-Arndt University, Greifswald, Germany
| | - Pål R Njølstad
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Department of Pediatrics, Haukeland University Hospital, Bergen, Norway
| | - Stefan Johansson
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Anders Molven
- KG Jebsen Center for Diabetes Research, Department of Clinical Science, University of Bergen, Bergen, Norway.,Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.,Department of Pathology, Haukeland University Hospital, Bergen, Norway
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182
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Integrated genomic characterization of papillary thyroid carcinoma. Cell 2015; 159:676-90. [PMID: 25417114 DOI: 10.1016/j.cell.2014.09.050] [Citation(s) in RCA: 2007] [Impact Index Per Article: 223.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2014] [Revised: 09/16/2014] [Accepted: 09/23/2014] [Indexed: 02/07/2023]
Abstract
Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Here, we describe the genomic landscape of 496 PTCs. We observed a low frequency of somatic alterations (relative to other carcinomas) and extended the set of known PTC driver alterations to include EIF1AX, PPM1D, and CHEK2 and diverse gene fusions. These discoveries reduced the fraction of PTC cases with unknown oncogenic driver from 25% to 3.5%. Combined analyses of genomic variants, gene expression, and methylation demonstrated that different driver groups lead to different pathologies with distinct signaling and differentiation characteristics. Similarly, we identified distinct molecular subgroups of BRAF-mutant tumors, and multidimensional analyses highlighted a potential involvement of oncomiRs in less-differentiated subgroups. Our results propose a reclassification of thyroid cancers into molecular subtypes that better reflect their underlying signaling and differentiation properties, which has the potential to improve their pathological classification and better inform the management of the disease.
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Affiliation(s)
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- Cancer Genome Atlas Program Office, National Cancer Institute at NIH, 31 Center Drive, Bldg. 31, Suite 3A20, Bethesda MD 20892, USA.
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183
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Wiktor P, Brunner A, Kahn P, Qiu J, Magee M, Bian X, Karthikeyan K, LaBaer J. Microreactor array device. Sci Rep 2015; 5:8736. [PMID: 25736721 PMCID: PMC4348619 DOI: 10.1038/srep08736] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Accepted: 01/28/2015] [Indexed: 11/22/2022] Open
Abstract
We report a device to fill an array of small chemical reaction chambers (microreactors) with reagent and then seal them using pressurized viscous liquid acting through a flexible membrane. The device enables multiple, independent chemical reactions involving free floating intermediate molecules without interference from neighboring reactions or external environments. The device is validated by protein expressed in situ directly from DNA in a microarray of ~10,000 spots with no diffusion during three hours incubation. Using the device to probe for an autoantibody cancer biomarker in blood serum sample gave five times higher signal to background ratio compared to standard protein microarray expressed on a flat microscope slide. Physical design principles to effectively fill the array of microreactors with reagent and experimental results of alternate methods for sealing the microreactors are presented.
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Affiliation(s)
- Peter Wiktor
- 1] Engineering Arts LLC, Tempe, Arizona, U.S.A [2] The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
| | - Al Brunner
- Engineering Arts LLC, Tempe, Arizona, U.S.A
| | - Peter Kahn
- Engineering Arts LLC, Tempe, Arizona, U.S.A
| | - Ji Qiu
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
| | - Mitch Magee
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
| | - Xiaofang Bian
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
| | - Kailash Karthikeyan
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
| | - Joshua LaBaer
- The Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona, U.S.A
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184
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Li D, Zhao H, Kranzler HR, Li MD, Jensen KP, Zayats T, Farrer LA, Gelernter J. Genome-wide association study of copy number variations (CNVs) with opioid dependence. Neuropsychopharmacology 2015; 40:1016-26. [PMID: 25345593 PMCID: PMC4330517 DOI: 10.1038/npp.2014.290] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2014] [Revised: 08/18/2014] [Accepted: 08/26/2014] [Indexed: 12/20/2022]
Abstract
Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P=2 × 10(-8) and OR (95% CI)=0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.
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Affiliation(s)
- Dawei Li
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- Department of Microbiology and Molecular Genetics, University of Vermont, Burlington, VT, USA
- Department of Computer Science, University of Vermont, Burlington, VT, USA
- Neuroscience, Behavior, and Health Initiative, University of Vermont, Burlington, VT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania School of Medicine and VISN 4 MIRECC, Philadelphia VAMC, Philadelphia, PA, USA
| | - Ming D Li
- Department of Psychiatry and Neurobehavioral Sciences, University of Virginia, Charlottesville, VA, USA
| | - Kevin P Jensen
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
| | - Tetyana Zayats
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
| | - Lindsay A Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Genetics and Genomics, Biostatistics, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, MA, USA
| | - Joel Gelernter
- Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, USA
- Department of Genetics, School of Medicine, Yale University, New Haven, CT, USA
- VA Connecticut Healthcare Center, Department of Neurobiology, Yale University School of Medicine, New Haven, CT, USA
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Abstract
The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and discover major cancer-causing genomic alterations to create a comprehensive "atlas" of cancer genomic profiles. So far, TCGA researchers have analysed large cohorts of over 30 human tumours through large-scale genome sequencing and integrated multi-dimensional analyses. Studies of individual cancer types, as well as comprehensive pan-cancer analyses have extended current knowledge of tumorigenesis. A major goal of the project was to provide publicly available datasets to help improve diagnostic methods, treatment standards, and finally to prevent cancer. This review discusses the current status of TCGA Research Network structure, purpose, and achievements.
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186
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Hu YJ, Lin DY, Sun W, Zeng D. A Likelihood-Based Framework for Association Analysis of Allele-Specific Copy Numbers. J Am Stat Assoc 2015; 109:1533-1545. [PMID: 25663726 DOI: 10.1080/01621459.2014.908777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) co-exist throughout the human genome and jointly contribute to phenotypic variations. Thus, it is desirable to consider both types of variants, as characterized by allele-specific copy numbers (ASCNs), in association studies of complex human diseases. Current SNP genotyping technologies capture the CNV and SNP information simultaneously via fluorescent intensity measurements. The common practice of calling ASCNs from the intensity measurements and then using the ASCN calls in downstream association analysis has important limitations. First, the association tests are prone to false-positive findings when differential measurement errors between cases and controls arise from differences in DNA quality or handling. Second, the uncertainties in the ASCN calls are ignored. We present a general framework for the integrated analysis of CNVs and SNPs, including the analysis of total copy numbers as a special case. Our approach combines the ASCN calling and the association analysis into a single step while allowing for differential measurement errors. We construct likelihood functions that properly account for case-control sampling and measurement errors. We establish the asymptotic properties of the maximum likelihood estimators and develop EM algorithms to implement the corresponding inference procedures. The advantages of the proposed methods over the existing ones are demonstrated through realistic simulation studies and an application to a genome-wide association study of schizophrenia. Extensions to next-generation sequencing data are discussed.
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187
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Genome-wide characteristics of copy number variation in Polish Holstein and Polish Red cattle using SNP genotyping assay. Genetica 2015; 143:145-55. [DOI: 10.1007/s10709-015-9822-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Accepted: 01/27/2015] [Indexed: 12/15/2022]
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188
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Zarrei M, MacDonald JR, Merico D, Scherer SW. A copy number variation map of the human genome. Nat Rev Genet 2015; 16:172-83. [DOI: 10.1038/nrg3871] [Citation(s) in RCA: 565] [Impact Index Per Article: 62.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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189
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Lee CT, Bendriem RM, Kindberg AA, Worden LT, Williams MP, Drgon T, Mallon BS, Harvey BK, Richie CT, Hamilton RS, Chen J, Errico SL, Tsai SYA, Uhl GR, Freed WJ. Functional consequences of 17q21.31/WNT3-WNT9B amplification in hPSCs with respect to neural differentiation. Cell Rep 2015; 10:616-32. [PMID: 25640183 DOI: 10.1016/j.celrep.2014.12.050] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2014] [Revised: 11/18/2014] [Accepted: 12/22/2014] [Indexed: 10/24/2022] Open
Abstract
Human pluripotent stem cell (hPSC) lines exhibit repeated patterns of genetic variation, which can alter in vitro properties as well as suitability for clinical use. We examined associations between copy-number variations (CNVs) on chromosome 17 and hPSC mesodiencephalic dopaminergic (mDA) differentiation. Among 24 hPSC lines, two karyotypically normal lines, BG03 and CT3, and BG01V2, with trisomy 17, exhibited amplification of the WNT3/WNT9B region and rapid mDA differentiation. In hPSC lines with amplified WNT3/WNT9B, basic fibroblast growth factor (bFGF) signaling through mitogen-activated protein kinase (MAPK)/ERK amplifies canonical WNT signaling by phosphorylating LRP6, resulting in enhanced undifferentiated proliferation. When bFGF is absent, noncanonical WNT signaling becomes dominant due to upregulation of SIAH2, enhancing JNK signaling and promoting loss of pluripotency. When bFGF is present during mDA differentiation, stabilization of canonical WNT signaling causes upregulation of LMX1A and mDA induction. Therefore, CNVs in 17q21.31, a "hot spot" for genetic variation, have multiple and complex effects on hPSC cellular phenotype.
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Affiliation(s)
- Chun-Ting Lee
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA.
| | - Raphael M Bendriem
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Abigail A Kindberg
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Lila T Worden
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Melanie P Williams
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Tomas Drgon
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Barbara S Mallon
- NIH Stem Cell Unit, Intramural Research Program, National Institute of Neurological Disorders and Stroke, Department of Health and Human Services, NIH, Bethesda, MD 20892, USA
| | - Brandon K Harvey
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Christopher T Richie
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Rebecca S Hamilton
- NIH Stem Cell Unit, Intramural Research Program, National Institute of Neurological Disorders and Stroke, Department of Health and Human Services, NIH, Bethesda, MD 20892, USA
| | - Jia Chen
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Stacie L Errico
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - Shang-Yi A Tsai
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - George R Uhl
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
| | - William J Freed
- Intramural Research Program, National Institute on Drug Abuse, Department of Health and Human Services, NIH, Baltimore, MD 21224, USA
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190
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Large multiallelic copy number variations in humans. Nat Genet 2015; 47:296-303. [PMID: 25621458 PMCID: PMC4405206 DOI: 10.1038/ng.3200] [Citation(s) in RCA: 265] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Accepted: 12/31/2014] [Indexed: 12/14/2022]
Abstract
Thousands of genomic segments appear to be present in widely varying copy numbers in different human genomes. We developed ways to use increasingly abundant whole-genome sequence data to identify the copy numbers, alleles and haplotypes present at most large multiallelic CNVs (mCNVs). We analyzed 849 genomes sequenced by the 1000 Genomes Project to identify most large (>5-kb) mCNVs, including 3,878 duplications, of which 1,356 appear to have 3 or more segregating alleles. We find that mCNVs give rise to most human variation in gene dosage-seven times the combined contribution of deletions and biallelic duplications-and that this variation in gene dosage generates abundant variation in gene expression. We describe 'runaway duplication haplotypes' in which genes, including HPR and ORM1, have mutated to high copy number on specific haplotypes. We also describe partially successful initial strategies for analyzing mCNVs via imputation and provide an initial data resource to support such analyses.
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191
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Jiang Y, Oldridge DA, Diskin SJ, Zhang NR. CODEX: a normalization and copy number variation detection method for whole exome sequencing. Nucleic Acids Res 2015; 43:e39. [PMID: 25618849 PMCID: PMC4381046 DOI: 10.1093/nar/gku1363] [Citation(s) in RCA: 100] [Impact Index Per Article: 11.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2014] [Accepted: 12/19/2014] [Indexed: 01/24/2023] Open
Abstract
High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.
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Affiliation(s)
- Yuchao Jiang
- Genomics and Computational Biology Graduate Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Derek A Oldridge
- Medical Scientist Training Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sharon J Diskin
- Division of Oncology and Center for Childhood Cancer Research, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nancy R Zhang
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
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192
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Cao H, Hastie AR, Cao D, Lam ET, Sun Y, Huang H, Liu X, Lin L, Andrews W, Chan S, Huang S, Tong X, Requa M, Anantharaman T, Krogh A, Yang H, Cao H, Xu X. Rapid detection of structural variation in a human genome using nanochannel-based genome mapping technology. Gigascience 2014; 3:34. [PMID: 25671094 PMCID: PMC4322599 DOI: 10.1186/2047-217x-3-34] [Citation(s) in RCA: 114] [Impact Index Per Article: 11.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2014] [Accepted: 11/28/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Structural variants (SVs) are less common than single nucleotide polymorphisms and indels in the population, but collectively account for a significant fraction of genetic polymorphism and diseases. Base pair differences arising from SVs are on a much higher order (>100 fold) than point mutations; however, none of the current detection methods are comprehensive, and currently available methodologies are incapable of providing sufficient resolution and unambiguous information across complex regions in the human genome. To address these challenges, we applied a high-throughput, cost-effective genome mapping technology to comprehensively discover genome-wide SVs and characterize complex regions of the YH genome using long single molecules (>150 kb) in a global fashion. RESULTS Utilizing nanochannel-based genome mapping technology, we obtained 708 insertions/deletions and 17 inversions larger than 1 kb. Excluding the 59 SVs (54 insertions/deletions, 5 inversions) that overlap with N-base gaps in the reference assembly hg19, 666 non-gap SVs remained, and 396 of them (60%) were verified by paired-end data from whole-genome sequencing-based re-sequencing or de novo assembly sequence from fosmid data. Of the remaining 270 SVs, 260 are insertions and 213 overlap known SVs in the Database of Genomic Variants. Overall, 609 out of 666 (90%) variants were supported by experimental orthogonal methods or historical evidence in public databases. At the same time, genome mapping also provides valuable information for complex regions with haplotypes in a straightforward fashion. In addition, with long single-molecule labeling patterns, exogenous viral sequences were mapped on a whole-genome scale, and sample heterogeneity was analyzed at a new level. CONCLUSION Our study highlights genome mapping technology as a comprehensive and cost-effective method for detecting structural variation and studying complex regions in the human genome, as well as deciphering viral integration into the host genome.
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Affiliation(s)
- Hongzhi Cao
- />BGI-Shenzhen, Shenzhen, 518083 China
- />Shenzhen Key Laboratory of Transomics Biotechnologies, Shenzhen, 518083 China
- />Department of Biology, University of Copenhagen, Copenhagen, 2200 Denmark
| | | | - Dandan Cao
- />BGI-Shenzhen, Shenzhen, 518083 China
- />Shenzhen Key Laboratory of Transomics Biotechnologies, Shenzhen, 518083 China
| | - Ernest T Lam
- />BioNano Genomics, San Diego, California 92121 USA
| | - Yuhui Sun
- />BGI-Shenzhen, Shenzhen, 518083 China
- />School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 511400 China
| | - Haodong Huang
- />BGI-Shenzhen, Shenzhen, 518083 China
- />School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 511400 China
| | - Xiao Liu
- />BGI-Shenzhen, Shenzhen, 518083 China
- />Department of Biology, University of Copenhagen, Copenhagen, 2200 Denmark
| | - Liya Lin
- />BGI-Shenzhen, Shenzhen, 518083 China
- />School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 511400 China
| | | | - Saki Chan
- />BioNano Genomics, San Diego, California 92121 USA
| | - Shujia Huang
- />BGI-Shenzhen, Shenzhen, 518083 China
- />School of Bioscience and Biotechnology, South China University of Technology, Guangzhou, 511400 China
| | - Xin Tong
- />BGI-Shenzhen, Shenzhen, 518083 China
| | | | | | - Anders Krogh
- />Department of Biology, University of Copenhagen, Copenhagen, 2200 Denmark
| | - Huanming Yang
- />BGI-Shenzhen, Shenzhen, 518083 China
- />Shenzhen Key Laboratory of Transomics Biotechnologies, Shenzhen, 518083 China
| | - Han Cao
- />BioNano Genomics, San Diego, California 92121 USA
| | - Xun Xu
- />BGI-Shenzhen, Shenzhen, 518083 China
- />Shenzhen Key Laboratory of Transomics Biotechnologies, Shenzhen, 518083 China
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193
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Merkle FT, Eggan K. Modeling human disease with pluripotent stem cells: from genome association to function. Cell Stem Cell 2014; 12:656-68. [PMID: 23746975 DOI: 10.1016/j.stem.2013.05.016] [Citation(s) in RCA: 144] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
Mechanistic insights into human disease may enable the development of treatments that are effective in broad patient populations. The confluence of gene-editing technologies, induced pluripotent stem cells, and genome-wide association as well as DNA sequencing studies is enabling new approaches for illuminating the molecular basis of human disease. We discuss the opportunities and challenges of combining these technologies and provide a workflow for interrogating the contribution of disease-associated candidate genetic variants to disease-relevant phenotypes. Finally, we discuss the potential utility of human pluripotent stem cells for placing disease-associated genetic variants into molecular pathways.
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Affiliation(s)
- Florian T Merkle
- The Howard Hughes Medical Institute, the Harvard Stem Cell Institute, Department of Stem Cell and Regenerative Biology, and Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
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194
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Schadt EE, Buchanan S, Brennand KJ, Merchant KM. Evolving toward a human-cell based and multiscale approach to drug discovery for CNS disorders. Front Pharmacol 2014; 5:252. [PMID: 25520658 PMCID: PMC4251289 DOI: 10.3389/fphar.2014.00252] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2014] [Accepted: 10/30/2014] [Indexed: 12/14/2022] Open
Abstract
A disruptive approach to therapeutic discovery and development is required in order to significantly improve the success rate of drug discovery for central nervous system (CNS) disorders. In this review, we first assess the key factors contributing to the frequent clinical failures for novel drugs. Second, we discuss cancer translational research paradigms that addressed key issues in drug discovery and development and have resulted in delivering drugs with significantly improved outcomes for patients. Finally, we discuss two emerging technologies that could improve the success rate of CNS therapies: human induced pluripotent stem cell (hiPSC)-based studies and multiscale biology models. Coincident with advances in cellular technologies that enable the generation of hiPSCs directly from patient blood or skin cells, together with methods to differentiate these hiPSC lines into specific neural cell types relevant to neurological disease, it is also now possible to combine data from large-scale forward genetics and post-mortem global epigenetic and expression studies in order to generate novel predictive models. The application of systems biology approaches to account for the multiscale nature of different data types, from genetic to molecular and cellular to clinical, can lead to new insights into human diseases that are emergent properties of biological networks, not the result of changes to single genes. Such studies have demonstrated the heterogeneity in etiological pathways and the need for studies on model systems that are patient-derived and thereby recapitulate neurological disease pathways with higher fidelity. In the context of two common and presumably representative neurological diseases, the neurodegenerative disease Alzheimer's Disease, and the psychiatric disorder schizophrenia, we propose the need for, and exemplify the impact of, a multiscale biology approach that can integrate panomic, clinical, imaging, and literature data in order to construct predictive disease network models that can (i) elucidate subtypes of syndromic diseases, (ii) provide insights into disease networks and targets and (iii) facilitate a novel drug screening strategy using patient-derived hiPSCs to discover novel therapeutics for CNS disorders.
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Affiliation(s)
- Eric E Schadt
- Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai New York, NY, USA ; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai New York, NY, USA
| | - Sean Buchanan
- Lilly Research Laboratories, Eli Lilly and Company Indianapolis, IN, USA
| | - Kristen J Brennand
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai New York, NY, USA
| | - Kalpana M Merchant
- Lilly Research Laboratories, Eli Lilly and Company Indianapolis, IN, USA
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195
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Analysis of indel variations in the human disease-associated genes CDKN2AIP, WDR66, USP20 and OR7C2 in a Korean population. J Genet 2014. [DOI: 10.1007/s12041-012-0129-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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196
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Abstract
PURPOSE OF REVIEW Recent studies clearly demonstrate that copy number variations (CNVs) are widespread in our genome and play an important role in human genetic variation, accounting for both human population diversity and human genetic disease. This review will discuss the most current knowledge regarding our understanding of the biology of CNVs in relation to human genetic disease. RECENT FINDINGS CNVs associated with human genetic disease can be either recurrent, with a common size and breakpoint clustering, or nonrecurrent, with different sizes and variable breakpoints. Two types of recurrent CNVs have been distinguished, including the syndromic forms in which the phenotypic features are relatively consistent, and those in which the same recurrent CNV can be associated with a diverse set of diagnoses. Recently, the 'Two-hit model' was used to explain the phenotypic variability associated with the latter group of recurrent CNVs. Nonrecurrent CNVs, on the contrary, occur at a relatively lower frequency at the individual locus level but collectively they are as common as recurrent CNVs. Finally, the study of CNV burden in different diseases demonstrated a clear trend of an increasing CNV burden in diseases with more severe phenotypes. SUMMARY In spite of the advances in the study of the CNV landscape associated with human genetic disease, there still remain many unexplored questions especially regarding the role of CNVs in the pathogenesis of complex human genetic diseases.
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197
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Cooper NJ, Shtir CJ, Smyth DJ, Guo H, Swafford AD, Zanda M, Hurles ME, Walker NM, Plagnol V, Cooper JD, Howson JMM, Burren OS, Onengut-Gumuscu S, Rich SS, Todd JA. Detection and correction of artefacts in estimation of rare copy number variants and analysis of rare deletions in type 1 diabetes. Hum Mol Genet 2014; 24:1774-90. [PMID: 25424174 PMCID: PMC4381751 DOI: 10.1093/hmg/ddu581] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
Copy number variants (CNVs) have been proposed as a possible source of ‘missing heritability’ in complex human diseases. Two studies of type 1 diabetes (T1D) found null associations with common copy number polymorphisms, but CNVs of low frequency and high penetrance could still play a role. We used the Log-R-ratio intensity data from a dense single nucleotide polymorphism (SNP) array, ImmunoChip, to detect rare CNV deletions (rDELs) and duplications (rDUPs) in 6808 T1D cases, 9954 controls and 2206 families with T1D-affected offspring. Initial analyses detected CNV associations. However, these were shown to be false-positive findings, failing replication with polymerase chain reaction. We developed a pipeline of quality control (QC) tests that were calibrated using systematic testing of sensitivity and specificity. The case–control odds ratios (OR) of CNV burden on T1D risk resulting from this QC pipeline converged on unity, suggesting no global frequency difference in rDELs or rDUPs. There was evidence that deletions could impact T1D risk for a small minority of cases, with enrichment for rDELs longer than 400 kb (OR = 1.57, P = 0.005). There were also 18 de novo rDELs detected in affected offspring but none for unaffected siblings (P = 0.03). No specific CNV regions showed robust evidence for association with T1D, although frequencies were lower than expected (most less than 0.1%), substantially reducing statistical power, which was examined in detail. We present an R-package, plumbCNV, which provides an automated approach for QC and detection of rare CNVs that can facilitate equivalent analyses of large-scale SNP array datasets.
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Affiliation(s)
- Nicholas J Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Corina J Shtir
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Deborah J Smyth
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Hui Guo
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Austin D Swafford
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Manuela Zanda
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, University College London, Darwin Building, London WC1E 6BT, UK
| | - Matthew E Hurles
- Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Neil M Walker
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Vincent Plagnol
- University College London, Darwin Building, London WC1E 6BT, UK
| | - Jason D Cooper
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Joanna M M Howson
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK, Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge CB1 8RN, UK
| | - Oliver S Burren
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, West Complex, University of Virginia, Charlottesville, VA 22908, USA
| | - Stephen S Rich
- Center for Public Health Genomics, West Complex, University of Virginia, Charlottesville, VA 22908, USA
| | - John A Todd
- JDRF/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, NIHR Cambridge Biomedical Research Centre, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Cambridge Biomedical Campus, Cambridge CB2 0XY, UK,
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Bonatti F, Reina M, Neri TM, Martorana D. Genetic Susceptibility to ANCA-Associated Vasculitis: State of the Art. Front Immunol 2014; 5:577. [PMID: 25452756 PMCID: PMC4233908 DOI: 10.3389/fimmu.2014.00577] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2014] [Accepted: 10/28/2014] [Indexed: 12/12/2022] Open
Abstract
ANCA-associated vasculitis (AAV) is a group of disorders that is caused by inflammation affecting small blood vessels. Both arteries and veins are affected. AAV includes microscopic polyangiitis (MPA), granulomatosis with polyangiitis (GPA) renamed from Wegener’s granulomatosis, and eosinophilic granulomatosis with polyangiitis (EGPA), renamed from Churg–Strauss syndrome. AAV is primarily due to leukocyte migration and resultant damage. Despite decades of research, the mechanisms behind AAV disease etiology are still not fully understood, although it is clear that genetic and environmental factors are involved. To improve the understanding of the disease, the genetic component has been extensively studied by candidate association studies and two genome-wide association studies. The majority of the identified genetic AAV risk factors are common variants. These have uncovered information that still needs further investigation to clarify its importance. In this review, we summarize and discuss the results of the genetic studies in AAV. We also present the novel approaches to identifying the causal variants in complex susceptibility loci and disease mechanisms. Finally, we discuss the limitations of current methods and the challenges that we still have to face in order to incorporate genomic and epigenomic data into clinical practice.
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Affiliation(s)
- Francesco Bonatti
- Unit of Medical Genetics, Laboratory of Molecular Genetics, Diagnostic Department, University Hospital of Parma , Parma , Italy
| | - Michele Reina
- Unit of Medical Genetics, Laboratory of Molecular Genetics, Diagnostic Department, University Hospital of Parma , Parma , Italy
| | - Tauro Maria Neri
- Unit of Medical Genetics, Laboratory of Molecular Genetics, Diagnostic Department, University Hospital of Parma , Parma , Italy
| | - Davide Martorana
- Unit of Medical Genetics, Laboratory of Molecular Genetics, Diagnostic Department, University Hospital of Parma , Parma , Italy
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199
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Sapkota Y. Germline DNA variations in breast cancer predisposition and prognosis: a systematic review of the literature. Cytogenet Genome Res 2014; 144:77-91. [PMID: 25401968 DOI: 10.1159/000369045] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/06/2014] [Indexed: 11/19/2022] Open
Abstract
Breast cancer is the most common cancer and the second leading cause of death in women worldwide. The disease is caused by a combination of genetic, environmental, lifestyle, and reproductive risk factors. Linkage and family-based studies have identified many pathological germline mutations, which account for around 20% of the genetic risk of familial breast cancer. In recent years, single nucleotide polymorphism-based genetic association studies, especially genome-wide association studies (GWASs), have been very successful in uncovering low-penetrance common variants associated with breast cancer risk. These common variants alone may explain up to an additional 30% of the familial risk of breast cancer. With the advent of available genetic resources and growing collaborations among researchers across the globe, the much needed large sample size to capture variants with small effect sizes and low population frequencies is being addressed, and hence many more common variants are expected to be discovered in the coming days. Here, major GWASs conducted for breast cancer predisposition and prognosis until 2013 are summarized. Few studies investigating other forms of genetic variations contributing to breast cancer predisposition and disease outcomes are also discussed. Finally, the potential utility of the GWAS-identified variants in disease risk models and some future perspectives are presented.
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Affiliation(s)
- Yadav Sapkota
- The Neurogenetics Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Qld., Australia
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200
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Narang A, Jha P, Kumar D, Kutum R, Mondal AK, Dash D, Mukerji M. Extensive copy number variations in admixed Indian population of African ancestry: potential involvement in adaptation. Genome Biol Evol 2014; 6:3171-81. [PMID: 25398783 PMCID: PMC4986450 DOI: 10.1093/gbe/evu250] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Admixture mapping has been enormously resourceful in identifying genetic variations linked to phenotypes, adaptation, and diseases. In this study through analysis of copy number variable regions (CNVRs), we report extensive restructuring in the genomes of the recently admixed African-Indian population (OG-W-IP) that inhabits a highly saline environment in Western India. The study included subjects from OG-W-IP (OG), five different Indian and three HapMap populations that were genotyped using Affymetrix version 6.0 arrays. Copy number variations (CNVs) detected using Birdsuite were used to define CNVRs. Population structure with respect to CNVRs was delineated using random forest approach. OG genomes have a surprising excess of CNVs in comparison to other studied populations. Individual ancestry proportions computed using STRUCTURE also reveals a unique genetic component in OGs. Population structure analysis with CNV genotypes indicates OG to be distant from both the African and Indian ancestral populations. Interestingly, it shows genetic proximity with respect to CNVs to only one Indian population IE-W-LP4, which also happens to reside in the same geographical region. We also observe a significant enrichment of molecular processes related to ion binding and receptor activity in genes encompassing OG-specific CNVRs. Our results suggest that retention of CNVRs from ancestral natives and de novo acquisition of CNVRs could accelerate the process of adaptation especially in an extreme environment. Additionally, this population would be enormously useful for dissecting genes and delineating the involvement of CNVs in salt adaptation.
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Affiliation(s)
- Ankita Narang
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Pankaj Jha
- Genomics and Molecular Medicine, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Dhirendra Kumar
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Rintu Kutum
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Anupam Kumar Mondal
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | | | - Debasis Dash
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
| | - Mitali Mukerji
- G.N. Ramachandran Knowledge Centre for Genome Informatics, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India Genomics and Molecular Medicine, Council of Scientific and Industrial Research, Institute of Genomics and Integrative Biology, New Delhi, India
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