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James R. Lupski

Bio: James R. Lupski is an academic researcher from Baylor College of Medicine. The author has contributed to research in topics: Exome sequencing & Gene duplication. The author has an hindex of 136, co-authored 844 publications receiving 74256 citations. Previous affiliations of James R. Lupski include University of Texas Health Science Center at Houston & Texas Medical Center.


Papers
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Journal ArticleDOI
17 Apr 2008-Nature
TL;DR: This sequence was completed in two months at approximately one-hundredth of the cost of traditional capillary electrophoresis methods and demonstrated the acquisition of novel human sequence, including novel genes not previously identified by traditional genomic sequencing, which is the first genome sequenced by next-generation technologies.
Abstract: Next-generation sequencing technologies are revolutionizing human genomics, promising to yield draft genomes cheaply and quickly. One such technology has now been used to analyse much of the genetic code of a single individual — who happens to be James D. Watson. The procedure, which involves no cloning of the genomic DNA, makes use of the latest 454 parallel sequencing instrument. The sequence cost less than US$1 million (and a mere two months) to produce, compared to the approximately US$100 million reported for sequencing Craig Venter's genome by traditional methods. Still a major undertaking, but another step towards the goal of 'personalized genomes' and 'personalized medicine'. The DNA sequence of a diploid genome of a single individual, James D. Watson, sequenced to 7.4-fold redundancy in two months using massively parallel sequencing in picolitre-size reaction vessels is reported. The association of genetic variation with disease and drug response, and improvements in nucleic acid technologies, have given great optimism for the impact of ‘genomic medicine’. However, the formidable size of the diploid human genome1, approximately 6 gigabases, has prevented the routine application of sequencing methods to deciphering complete individual human genomes. To realize the full potential of genomics for human health, this limitation must be overcome. Here we report the DNA sequence of a diploid genome of a single individual, James D. Watson, sequenced to 7.4-fold redundancy in two months using massively parallel sequencing in picolitre-size reaction vessels. This sequence was completed in two months at approximately one-hundredth of the cost of traditional capillary electrophoresis methods. Comparison of the sequence to the reference genome led to the identification of 3.3 million single nucleotide polymorphisms, of which 10,654 cause amino-acid substitution within the coding sequence. In addition, we accurately identified small-scale (2–40,000 base pair (bp)) insertion and deletion polymorphism as well as copy number variation resulting in the large-scale gain and loss of chromosomal segments ranging from 26,000 to 1.5 million base pairs. Overall, these results agree well with recent results of sequencing of a single individual2 by traditional methods. However, in addition to being faster and significantly less expensive, this sequencing technology avoids the arbitrary loss of genomic sequences inherent in random shotgun sequencing by bacterial cloning because it amplifies DNA in a cell-free system. As a result, we further demonstrate the acquisition of novel human sequence, including novel genes not previously identified by traditional genomic sequencing. This is the first genome sequenced by next-generation technologies. Therefore it is a pilot for the future challenges of ‘personalized genome sequencing’.

1,879 citations

Journal ArticleDOI
TL;DR: W whole-exome sequencing identified the underlying genetic defect in 25% of consecutive patients referred for evaluation of a possible genetic condition.
Abstract: Background Whole-exome sequencing is a diagnostic approach for the identification of molecular defects in patients with suspected genetic disorders. Methods We developed technical, bioinformatic, interpretive, and validation pipelines for whole-exome sequencing in a certified clinical laboratory to identify sequence variants underlying disease phenotypes in patients. Results We present data on the first 250 probands for whom referring physicians ordered whole-exome sequencing. Patients presented with a range of phenotypes suggesting potential genetic causes. Approximately 80% were children with neurologic phenotypes. Insurance coverage was similar to that for established genetic tests. We identified 86 mutated alleles that were highly likely to be causative in 62 of the 250 patients, achieving a 25% molecular diagnostic rate (95% confidence interval, 20 to 31). Among the 62 patients, 33 had autosomal dominant disease, 16 had autosomal recessive disease, and 9 had X-linked disease. A total of 4 probands re...

1,727 citations

Journal ArticleDOI
TL;DR: Mutational analysis of ABCR in STGD families revealed a total of 19 different mutations including homozygous mutations in two families with consanguineous parentage, indicating that ABCR is the causal gene of STGD/FFM.
Abstract: Stargardt disease (STGD, also known as fundus flavimaculatus; FFM) is an autosomal recessive retinal disorder characterized by a juvenile-onset macular dystrophy, alterations of the peripheral retina, and subretinal deposition of lipofuscin-like material A gene encoding an ATP-binding cassette (ABC) transporter was mapped to the 2-cM (centiMorgan) interval at 1p13-p21 previously shown by linkage analysis to harbour the STGD gene This gene, ABCR, is expressed exclusively and at high levels in the retina, in rod but not cone photoreceptors, as detected by in situ hybridization Mutational analysis of ABCR in STGD families revealed a total of 19 different mutations including homozygous mutations in two families with consanguineous parentage These data indicate that ABCR is the causal gene of STGD/FFM

1,363 citations

Journal ArticleDOI
26 Jul 1991-Cell
TL;DR: It is demonstrated that failure to recognize the molecular duplication can lead to misinterpretation of marker genotypes for affected individuals, identification of false recombinants, and incorrect localization of the disease locus.

1,293 citations


Cited by
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Journal ArticleDOI
Eric S. Lander1, Lauren Linton1, Bruce W. Birren1, Chad Nusbaum1  +245 moreInstitutions (29)
15 Feb 2001-Nature
TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

22,269 citations

Journal ArticleDOI
TL;DR: The GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

20,557 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: A unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs is presented.
Abstract: Recent advances in sequencing technology make it possible to comprehensively catalogue genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (1) initial read mapping; (2) local realignment around indels; (3) base quality score recalibration; (4) SNP discovery and genotyping to find all potential variants; and (5) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We discuss the application of these tools, instantiated in the Genome Analysis Toolkit (GATK), to deep whole-genome, whole-exome capture, and multi-sample low-pass (~4×) 1000 Genomes Project datasets.

10,056 citations

Journal ArticleDOI
Monkol Lek, Konrad J. Karczewski1, Konrad J. Karczewski2, Eric Vallabh Minikel2, Eric Vallabh Minikel1, Kaitlin E. Samocha, Eric Banks2, Timothy Fennell2, Anne H. O’Donnell-Luria2, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria3, James S. Ware, Andrew J. Hill4, Andrew J. Hill1, Andrew J. Hill2, Beryl B. Cummings2, Beryl B. Cummings1, Taru Tukiainen2, Taru Tukiainen1, Daniel P. Birnbaum2, Jack A. Kosmicki, Laramie E. Duncan2, Laramie E. Duncan1, Karol Estrada2, Karol Estrada1, Fengmei Zhao1, Fengmei Zhao2, James Zou2, Emma Pierce-Hoffman2, Emma Pierce-Hoffman1, Joanne Berghout5, David Neil Cooper6, Nicole A. Deflaux7, Mark A. DePristo2, Ron Do, Jason Flannick1, Jason Flannick2, Menachem Fromer, Laura D. Gauthier2, Jackie Goldstein2, Jackie Goldstein1, Namrata Gupta2, Daniel P. Howrigan1, Daniel P. Howrigan2, Adam Kiezun2, Mitja I. Kurki2, Mitja I. Kurki1, Ami Levy Moonshine2, Pradeep Natarajan, Lorena Orozco, Gina M. Peloso1, Gina M. Peloso2, Ryan Poplin2, Manuel A. Rivas2, Valentin Ruano-Rubio2, Samuel A. Rose2, Douglas M. Ruderfer8, Khalid Shakir2, Peter D. Stenson6, Christine Stevens2, Brett Thomas2, Brett Thomas1, Grace Tiao2, María Teresa Tusié-Luna, Ben Weisburd2, Hong-Hee Won9, Dongmei Yu, David Altshuler2, David Altshuler10, Diego Ardissino, Michael Boehnke11, John Danesh12, Stacey Donnelly2, Roberto Elosua, Jose C. Florez2, Jose C. Florez1, Stacey Gabriel2, Gad Getz1, Gad Getz2, Stephen J. Glatt13, Christina M. Hultman14, Sekar Kathiresan, Markku Laakso15, Steven A. McCarroll1, Steven A. McCarroll2, Mark I. McCarthy16, Mark I. McCarthy17, Dermot P.B. McGovern18, Ruth McPherson19, Benjamin M. Neale1, Benjamin M. Neale2, Aarno Palotie, Shaun Purcell8, Danish Saleheen20, Jeremiah M. Scharf, Pamela Sklar, Patrick F. Sullivan14, Patrick F. Sullivan21, Jaakko Tuomilehto22, Ming T. Tsuang23, Hugh Watkins16, Hugh Watkins17, James G. Wilson24, Mark J. Daly1, Mark J. Daly2, Daniel G. MacArthur1, Daniel G. MacArthur2 
18 Aug 2016-Nature
TL;DR: The aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC) provides direct evidence for the presence of widespread mutational recurrence.
Abstract: Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

8,758 citations