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Author

Ghassan Ghandour

Other affiliations: Affymetrix
Bio: Ghassan Ghandour is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: SNP array & Genome. The author has an hindex of 1, co-authored 3 publications receiving 2344 citations. Previous affiliations of Ghassan Ghandour include Affymetrix.

Papers
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Journal ArticleDOI
15 May 1998-Science
TL;DR: A large-scale survey for SNPs was examined by a combination of gel-based sequencing and high-density variation-detection DNA chips, and a genetic map was constructed showing the location of 2227 candidate SNPs.
Abstract: Single-nucleotide polymorphisms (SNPs) are the most frequent type of variation in the human genome, and they provide powerful tools for a variety of medical genetic studies. In a large-scale survey for SNPs, 2.3 megabases of human genomic DNA was examined by a combination of gel-based sequencing and high-density variation-detection DNA chips. A total of 3241 candidate SNPs were identified. A genetic map was constructed showing the location of 2227 of these SNPs. Prototype genotyping chips were developed that allow simultaneous genotyping of 500 SNPs. The results provide a characterization of human diversity at the nucleotide level and demonstrate the feasibility of large-scale identification of human SNPs.

2,383 citations

Patent
07 Feb 1997
TL;DR: The authors concerne des ensembles a base d'oligonucleotides, ainsi que des procedes for determiner les especes and les phenotypes d'organismes.
Abstract: L'invention concerne des ensembles a base d'oligonucleotides, ainsi que des procedes pour determiner les especes et les phenotypes d'organismes, par exemple, a l'aide de sequences d'oligonucleotides basees sur le gene Mycobacterium tuberculosis rpoB. Les groupes ou les especes auxquels appartient un organisme peuvent etre determines par comparaison de schemas d'hybridation d'acide nucleique cible provenant de l'organisme avec des schemas d'hybridation conserves dans une base de donnees.

Cited by
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Book ChapterDOI
TL;DR: This chapter assumes acquaintance with the principles and practice of PCR, as outlined in, for example, refs.
Abstract: 1. Introduction Designing PCR and sequencing primers are essential activities for molecular biologists around the world. This chapter assumes acquaintance with the principles and practice of PCR, as outlined in, for example, refs. 1–4. Primer3 is a computer program that suggests PCR primers for a variety of applications, for example to create STSs (sequence tagged sites) for radiation hybrid mapping (5), or to amplify sequences for single nucleotide polymor-phism discovery (6). Primer3 can also select single primers for sequencing reactions and can design oligonucleotide hybridization probes. In selecting oligos for primers or hybridization probes, Primer3 can consider many factors. These include oligo melting temperature, length, GC content , 3′ stability, estimated secondary structure, the likelihood of annealing to or amplifying undesirable sequences (for example interspersed repeats), the likelihood of primer–dimer formation between two copies of the same primer, and the accuracy of the source sequence. In the design of primer pairs Primer3 can consider product size and melting temperature, the likelihood of primer– dimer formation between the two primers in the pair, the difference between primer melting temperatures, and primer location relative to particular regions of interest or to be avoided.

16,407 citations

Journal ArticleDOI
J. Craig Venter1, Mark Raymond Adams1, Eugene W. Myers1, Peter W. Li1  +269 moreInstitutions (12)
16 Feb 2001-Science
TL;DR: Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems are indicated.
Abstract: A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies-a whole-genome assembly and a regional chromosome assembly-were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional approximately 12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

12,098 citations

Journal ArticleDOI
John W. Belmont1, Paul Hardenbol, Thomas D. Willis, Fuli Yu1, Huanming Yang2, Lan Yang Ch'Ang, Wei Huang3, Bin Liu2, Yan Shen3, Paul K.H. Tam4, Lap-Chee Tsui4, Mary M.Y. Waye5, Jeffrey Tze Fei Wong6, Changqing Zeng2, Qingrun Zhang2, Mark S. Chee7, Luana Galver7, Semyon Kruglyak7, Sarah S. Murray7, Arnold Oliphant7, Alexandre Montpetit8, Fanny Chagnon8, Vincent Ferretti8, Martin Leboeuf8, Michael S. Phillips8, Andrei Verner8, Shenghui Duan9, Denise L. Lind10, Raymond D. Miller9, John P. Rice9, Nancy L. Saccone9, Patricia Taillon-Miller9, Ming Xiao10, Akihiro Sekine, Koki Sorimachi, Yoichi Tanaka, Tatsuhiko Tsunoda, Eiji Yoshino, David R. Bentley11, Sarah E. Hunt11, Don Powell11, Houcan Zhang12, Ichiro Matsuda13, Yoshimitsu Fukushima14, Darryl Macer15, Eiko Suda15, Charles N. Rotimi16, Clement Adebamowo17, Toyin Aniagwu17, Patricia A. Marshall18, Olayemi Matthew17, Chibuzor Nkwodimmah17, Charmaine D.M. Royal16, Mark Leppert19, Missy Dixon19, Fiona Cunningham20, Ardavan Kanani20, Gudmundur A. Thorisson20, Peter E. Chen21, David J. Cutler21, Carl S. Kashuk21, Peter Donnelly22, Jonathan Marchini22, Gilean McVean22, Simon Myers22, Lon R. Cardon22, Andrew P. Morris22, Bruce S. Weir23, James C. Mullikin24, Michael Feolo24, Mark J. Daly25, Renzong Qiu26, Alastair Kent, Georgia M. Dunston16, Kazuto Kato27, Norio Niikawa28, Jessica Watkin29, Richard A. Gibbs1, Erica Sodergren1, George M. Weinstock1, Richard K. Wilson9, Lucinda Fulton9, Jane Rogers11, Bruce W. Birren25, Hua Han2, Hongguang Wang, Martin Godbout30, John C. Wallenburg8, Paul L'Archevêque, Guy Bellemare, Kazuo Todani, Takashi Fujita, Satoshi Tanaka, Arthur L. Holden, Francis S. Collins24, Lisa D. Brooks24, Jean E. McEwen24, Mark S. Guyer24, Elke Jordan31, Jane Peterson24, Jack Spiegel24, Lawrence M. Sung32, Lynn F. Zacharia24, Karen Kennedy29, Michael Dunn29, Richard Seabrook29, Mark Shillito, Barbara Skene29, John Stewart29, David Valle21, Ellen Wright Clayton33, Lynn B. Jorde19, Aravinda Chakravarti21, Mildred K. Cho34, Troy Duster35, Troy Duster36, Morris W. Foster37, Maria Jasperse38, Bartha Maria Knoppers39, Pui-Yan Kwok10, Julio Licinio40, Jeffrey C. Long41, Pilar N. Ossorio42, Vivian Ota Wang33, Charles N. Rotimi16, Patricia Spallone29, Patricia Spallone43, Sharon F. Terry44, Eric S. Lander25, Eric H. Lai45, Deborah A. Nickerson46, Gonçalo R. Abecasis41, David Altshuler47, Michael Boehnke41, Panos Deloukas11, Julie A. Douglas41, Stacey Gabriel25, Richard R. Hudson48, Thomas J. Hudson8, Leonid Kruglyak49, Yusuke Nakamura50, Robert L. Nussbaum24, Stephen F. Schaffner25, Stephen T. Sherry24, Lincoln Stein20, Toshihiro Tanaka 
18 Dec 2003-Nature
TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
Abstract: The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention.

5,926 citations

Journal ArticleDOI
TL;DR: The performance of the genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.
Abstract: A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. To achieve this goal, we propose a statistical method that has several optimal properties: It can be used with case control data and yet, like family-based designs, controls for population heterogeneity; it is insensitive to the usual violations of model assumptions, such as cases failing to be strictly independent; and, by using Bayesian outlier methods, it circumvents the need for Bonferroni correction for multiple tests, leading to better performance in many settings while still constraining risk for false positives. The performance of our genomic control method is quite good for plausible effects of liability genes, which bodes well for future genetic analyses of complex disorders.

3,130 citations

Journal ArticleDOI
15 Feb 2001-Nature
TL;DR: This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.
Abstract: We describe a map of 1.42 million single nucleotide polymorphisms (SNPs) distributed throughout the human genome, providing an average density on available sequence of one SNP every 1.9 kilobases. These SNPs were primarily discovered by two projects: The SNP Consortium and the analysis of clone overlaps by the International Human Genome Sequencing Consortium. The map integrates all publicly available SNPs with described genes and other genomic features. We estimate that 60,000 SNPs fall within exon (coding and untranslated regions), and 85% of exons are within 5 kb of the nearest SNP. Nucleotide diversity varies greatly across the genome, in a manner broadly consistent with a standard population genetic model of human history. This high-density SNP map provides a public resource for defining haplotype variation across the genome, and should help to identify biomedically important genes for diagnosis and therapy.

2,908 citations