1
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Wagner J, Olson ND, Harris L, Khan Z, Farek J, Mahmoud M, Stankovic A, Kovacevic V, Yoo B, Miller N, Rosenfeld JA, Ni B, Zarate S, Kirsche M, Aganezov S, Schatz MC, Narzisi G, Byrska-Bishop M, Clarke W, Evani US, Markello C, Shafin K, Zhou X, Sidow A, Bansal V, Ebert P, Marschall T, Lansdorp P, Hanlon V, Mattsson CA, Barrio AM, Fiddes IT, Xiao C, Fungtammasan A, Chin CS, Wenger AM, Rowell WJ, Sedlazeck FJ, Carroll A, Salit M, Zook JM. Benchmarking challenging small variants with linked and long reads. Cell Genom 2022; 2:100128. [PMID: 36452119 PMCID: PMC9706577 DOI: 10.1016/j.xgen.2022.100128] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as PMS2. For HG002, we include 92% of the autosomal GRCh38 assembly while excluding regions problematic for benchmarking small variants, such as copy number variants, that should not have been in the previous version, which included 85% of GRCh38. It identifies eight times more false negatives in a short read variant call set relative to our previous benchmark. We demonstrate that this benchmark reliably identifies false positives and false negatives across technologies, enabling ongoing methods development.
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Affiliation(s)
- Justin Wagner
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
| | - Nathan D. Olson
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Lindsay Harris
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
| | - Ziad Khan
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Jesse Farek
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Medhat Mahmoud
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Ana Stankovic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Vladimir Kovacevic
- Seven Bridges, Omladinskih brigada 90g, 11070 Belgrade, Republic of Serbia
| | - Byunggil Yoo
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | - Neil Miller
- Children’s Mercy Kansas City, Kansas City, MO, USA
| | | | - Bohan Ni
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Giuseppe Narzisi
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | | | - Wayne Clarke
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Uday S. Evani
- New York Genome Center, 101 Avenue of the Americas, New York, NY, USA
| | - Charles Markello
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Kishwar Shafin
- University of California at Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA, USA
| | - Xin Zhou
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Arend Sidow
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Vikas Bansal
- Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Peter Ebert
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Tobias Marschall
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Peter Lansdorp
- Institute of Medical Biometry and Bioinformatics, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Vincent Hanlon
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Carl-Adam Mattsson
- Terry Fox Laboratory, BC Cancer Research Institute and Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD 20894, USA
| | | | | | | | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA
| | - Andrew Carroll
- Google Inc., 1600 Amphitheatre Pkwy., Mountain View, CA 94040, USA
| | - Marc Salit
- Joint Initiative for Metrology in Biology, SLAC National Laboratory, Stanford, CA, USA
| | - Justin M. Zook
- Material Measurement Laboratory, National Institute of Standards and Technology, 100 Bureau Dr, MS8312, Gaithersburg, MD 20899, USA
- Corresponding author
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2
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Aganezov S, Yan SM, Soto DC, Kirsche M, Zarate S, Avdeyev P, Taylor DJ, Shafin K, Shumate A, Xiao C, Wagner J, McDaniel J, Olson ND, Sauria MEG, Vollger MR, Rhie A, Meredith M, Martin S, Lee J, Koren S, Rosenfeld JA, Paten B, Layer R, Chin CS, Sedlazeck FJ, Hansen NF, Miller DE, Phillippy AM, Miga KH, McCoy RC, Dennis MY, Zook JM, Schatz MC. A complete reference genome improves analysis of human genetic variation. Science 2022; 376:eabl3533. [PMID: 35357935 DOI: 10.1126/science.abl3533] [Citation(s) in RCA: 94] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.
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Affiliation(s)
- Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie M Yan
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela C Soto
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel Avdeyev
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Dylan J Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, USA
| | - Justin Wagner
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Mitchell R Vollger
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Arang Rhie
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Melissa Meredith
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Skylar Martin
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Sergey Koren
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Ryan Layer
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | | | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nancy F Hansen
- Comparative Genomics Analysis Unit, National Human Genome Research Institute, Rockville, MD, USA
| | - Danny E Miller
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.,Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children's Hospital, Seattle, WA, USA
| | - Adam M Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Karen H Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Rajiv C McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y Dennis
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Justin M Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA.,Department of Biology, Johns Hopkins University, Baltimore, MD, USA.,Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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3
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Nurk S, Koren S, Rhie A, Rautiainen M, Bzikadze AV, Mikheenko A, Vollger MR, Altemose N, Uralsky L, Gershman A, Aganezov S, Hoyt SJ, Diekhans M, Logsdon GA, Alonge M, Antonarakis SE, Borchers M, Bouffard GG, Brooks SY, Caldas GV, Chen NC, Cheng H, Chin CS, Chow W, de Lima LG, Dishuck PC, Durbin R, Dvorkina T, Fiddes IT, Formenti G, Fulton RS, Fungtammasan A, Garrison E, Grady PG, Graves-Lindsay TA, Hall IM, Hansen NF, Hartley GA, Haukness M, Howe K, Hunkapiller MW, Jain C, Jain M, Jarvis ED, Kerpedjiev P, Kirsche M, Kolmogorov M, Korlach J, Kremitzki M, Li H, Maduro VV, Marschall T, McCartney AM, McDaniel J, Miller DE, Mullikin JC, Myers EW, Olson ND, Paten B, Peluso P, Pevzner PA, Porubsky D, Potapova T, Rogaev EI, Rosenfeld JA, Salzberg SL, Schneider VA, Sedlazeck FJ, Shafin K, Shew CJ, Shumate A, Sims Y, Smit AFA, Soto DC, Sović I, Storer JM, Streets A, Sullivan BA, Thibaud-Nissen F, Torrance J, Wagner J, Walenz BP, Wenger A, Wood JMD, Xiao C, Yan SM, Young AC, Zarate S, Surti U, McCoy RC, Dennis MY, Alexandrov IA, Gerton JL, O’Neill RJ, Timp W, Zook JM, Schatz MC, Eichler EE, Miga KH, Phillippy AM. The complete sequence of a human genome. Science 2022; 376:44-53. [PMID: 35357919 PMCID: PMC9186530 DOI: 10.1126/science.abj6987] [Citation(s) in RCA: 894] [Impact Index Per Article: 447.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion-base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.
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Affiliation(s)
- Sergey Nurk
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Mikko Rautiainen
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Andrey V. Bzikadze
- Graduate Program in Bioinformatics and Systems Biology, University of California, San Diego; La Jolla, CA, USA
| | - Alla Mikheenko
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | - Mitchell R. Vollger
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Nicolas Altemose
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
| | - Lev Uralsky
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
| | - Ariel Gershman
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
| | - Sergey Aganezov
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Savannah J. Hoyt
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Mark Diekhans
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Glennis A. Logsdon
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Michael Alonge
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | | | | | - Gerard G. Bouffard
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Shelise Y. Brooks
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gina V. Caldas
- Department of Molecular and Cell Biology, University of California, Berkeley; Berkeley, CA, USA
| | - Nae-Chyun Chen
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Haoyu Cheng
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | | | | | | | - Philip C. Dishuck
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Richard Durbin
- Wellcome Sanger Institute; Cambridge, UK
- Department of Genetics, University of Cambridge; Cambridge, UK
| | - Tatiana Dvorkina
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
| | | | - Giulio Formenti
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Robert S. Fulton
- Department of Genetics, Washington University School of Medicine; St. Louis, MO, USA
| | | | - Erik Garrison
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- University of Tennessee Health Science Center; Memphis, TN, USA
| | - Patrick G.S. Grady
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | | | - Ira M. Hall
- Department of Genetics, Yale University School of Medicine; New Haven, CT, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Gabrielle A. Hartley
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Marina Haukness
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | | | - Chirag Jain
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
- Department of Computational and Data Sciences, Indian Institute of Science; Bangalore KA, India
| | - Miten Jain
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Erich D. Jarvis
- Laboratory of Neurogenetics of Language and The Vertebrate Genome Lab, The Rockefeller University; New York, NY, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | | | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Mikhail Kolmogorov
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | | | - Milinn Kremitzki
- McDonnell Genome Institute, Washington University in St. Louis; St. Louis, MO, USA
| | - Heng Li
- Department of Data Sciences, Dana-Farber Cancer Institute; Boston, MA
- Department of Biomedical Informatics, Harvard Medical School; Boston, MA
| | - Valerie V. Maduro
- Undiagnosed Diseases Program, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Tobias Marschall
- Heinrich Heine University Düsseldorf, Medical Faculty, Institute for Medical Biometry and Bioinformatics; Düsseldorf, Germany
| | - Ann M. McCartney
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | - Jennifer McDaniel
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital; Seattle, WA, USA
| | - James C. Mullikin
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
- Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Eugene W. Myers
- Max-Planck Institute of Molecular Cell Biology and Genetics; Dresden, Germany
| | - Nathan D. Olson
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | | | - Pavel A. Pevzner
- Department of Computer Science and Engineering, University of California, San Diego; San Diego, CA, USA
| | - David Porubsky
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
| | - Tamara Potapova
- Stowers Institute for Medical Research; Kansas City, MO, USA
| | - Evgeny I. Rogaev
- Sirius University of Science and Technology; Sochi, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Department of Psychiatry, University of Massachusetts Medical School; Worcester, MA, USA
- Faculty of Biology, Lomonosov Moscow State University; Moscow, Russia
| | | | - Steven L. Salzberg
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Valerie A. Schneider
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine; Houston TX, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
| | - Colin J. Shew
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Ying Sims
- Wellcome Sanger Institute; Cambridge, UK
| | | | - Daniela C. Soto
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan Sović
- Pacific Biosciences; Menlo Park, CA, USA
- Digital BioLogic d.o.o.; Ivanić-Grad, Croatia
| | | | - Aaron Streets
- Department of Bioengineering, University of California, Berkeley; Berkeley, CA, USA
- Chan Zuckerberg Biohub; San Francisco, CA, USA
| | - Beth A. Sullivan
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine; Durham, NC, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | | | - Justin Wagner
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Brian P. Walenz
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
| | | | | | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health; Bethesda, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Alice C. Young
- NIH Intramural Sequencing Center, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
| | - Urvashi Surti
- Department of Pathology, University of Pittsburgh; Pittsburgh, PA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Megan Y. Dennis
- Genome Center, MIND Institute, Department of Biochemistry and Molecular Medicine, University of California, Davis; CA, USA
| | - Ivan A. Alexandrov
- Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, Saint Petersburg State University; Saint Petersburg, Russia
- Vavilov Institute of General Genetics; Moscow, Russia
- Research Center of Biotechnology of the Russian Academy of Sciences; Moscow, Russia
| | - Jennifer L. Gerton
- Stowers Institute for Medical Research; Kansas City, MO, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical School; Kansas City, MO, USA
| | - Rachel J. O’Neill
- Institute for Systems Genomics and Department of Molecular and Cell Biology, University of Connecticut; Storrs, CT, USA
| | - Winston Timp
- Department of Molecular Biology and Genetics, Johns Hopkins University; Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD, USA
| | - Justin M. Zook
- Biosystems and Biomaterials Division, National Institute of Standards and Technology; Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University; Baltimore, MD, USA
- Department of Biology, Johns Hopkins University; Baltimore, MD, USA
| | - Evan E. Eichler
- Department of Genome Sciences, University of Washington School of Medicine; Seattle, WA, USA
- Howard Hughes Medical Institute; Chevy Chase, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA, USA
- Department of Biomolecular Engineering, University of California Santa Cruz, CA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health; Bethesda, MD USA
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4
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Butler D, Mozsary C, Meydan C, Foox J, Rosiene J, Shaiber A, Danko D, Afshinnekoo E, MacKay M, Sedlazeck FJ, Ivanov NA, Sierra M, Pohle D, Zietz M, Gisladottir U, Ramlall V, Sholle ET, Schenck EJ, Westover CD, Hassan C, Ryon K, Young B, Bhattacharya C, Ng DL, Granados AC, Santos YA, Servellita V, Federman S, Ruggiero P, Fungtammasan A, Chin CS, Pearson NM, Langhorst BW, Tanner NA, Kim Y, Reeves JW, Hether TD, Warren SE, Bailey M, Gawrys J, Meleshko D, Xu D, Couto-Rodriguez M, Nagy-Szakal D, Barrows J, Wells H, O'Hara NB, Rosenfeld JA, Chen Y, Steel PAD, Shemesh AJ, Xiang J, Thierry-Mieg J, Thierry-Mieg D, Iftner A, Bezdan D, Sanchez E, Campion TR, Sipley J, Cong L, Craney A, Velu P, Melnick AM, Shapira S, Hajirasouliha I, Borczuk A, Iftner T, Salvatore M, Loda M, Westblade LF, Cushing M, Wu S, Levy S, Chiu C, Schwartz RE, Tatonetti N, Rennert H, Imielinski M, Mason CE. Shotgun transcriptome, spatial omics, and isothermal profiling of SARS-CoV-2 infection reveals unique host responses, viral diversification, and drug interactions. Nat Commun 2021; 12:1660. [PMID: 33712587 PMCID: PMC7954844 DOI: 10.1038/s41467-021-21361-7] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Accepted: 01/25/2021] [Indexed: 02/08/2023] Open
Abstract
In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin-angiotensin-aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.
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Affiliation(s)
- Daniel Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Christopher Mozsary
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Cem Meydan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Jonathan Foox
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Joel Rosiene
- New York Genome Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Alon Shaiber
- New York Genome Center, New York, NY, USA
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - David Danko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA
| | - Matthew MacKay
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Fritz J Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nikolay A Ivanov
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Clinical & Translational Science Center, Weill Cornell Medicine, New York, NY, USA
| | - Maria Sierra
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Diana Pohle
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Michael Zietz
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Undina Gisladottir
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Vijendra Ramlall
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
- Department of Cellular, Molecular Physiology & Biophysics, Columbia University, Columbia, NY, USA
| | - Evan T Sholle
- Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, USA
| | - Edward J Schenck
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Craig D Westover
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Ciaran Hassan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Krista Ryon
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Benjamin Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | | | - Dianna L Ng
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
| | - Andrea C Granados
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Yale A Santos
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Venice Servellita
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Scot Federman
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
| | - Phyllis Ruggiero
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | | | | | | | | | | | | | | | | | | | | | - Justyna Gawrys
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Dmitry Meleshko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- Tri-Institutional Computational Biology & Medicine Program, Weill Cornell Medicine, New York, NY, USA
| | - Dong Xu
- Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, USA
| | | | - Dorottya Nagy-Szakal
- Biotia, Inc., New York, NY, USA
- Department of Cell Biology, SUNY Downstate Health Sciences University, New York, NY, USA
| | | | | | - Niamh B O'Hara
- Biotia, Inc., New York, NY, USA
- Department of Cell Biology, SUNY Downstate Health Sciences University, New York, NY, USA
| | - Jeffrey A Rosenfeld
- Rutgers Cancer Institute of New Jersey, New York, NJ, USA
- Department of Pathology, Robert Wood Johnson Medical School, New York, NJ, USA
| | - Ying Chen
- Rutgers Cancer Institute of New Jersey, New York, NJ, USA
| | - Peter A D Steel
- Department of Emergency Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Amos J Shemesh
- Department of Emergency Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jenny Xiang
- Genomics Resources Core Facility, Weill Cornell Medicine, New York, NY, USA
| | - Jean Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Danielle Thierry-Mieg
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Angelika Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Daniela Bezdan
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | | | - Thomas R Campion
- Information Technologies & Services Department, Weill Cornell Medicine, New York, NY, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - John Sipley
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Lin Cong
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Arryn Craney
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Priya Velu
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Ari M Melnick
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Sagi Shapira
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA
| | - Iman Hajirasouliha
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Alain Borczuk
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Thomas Iftner
- Institute of Medical Virology and Epidemiology of Viral Diseases, University Hospital Tuebingen, Tuebingen, Germany
| | - Mirella Salvatore
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Massimo Loda
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Lars F Westblade
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Melissa Cushing
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Shixiu Wu
- Hangzhou Cancer Institute, Hangzhou Cancer Hospital, Hangzhou, China
- Department of Radiation Oncology, Hangzhou Cancer Hospital, Hangzhou, China
| | - Shawn Levy
- HudsonAlpha Discovery Institute, Huntsville, AL, USA
| | - Charles Chiu
- Department of Laboratory Medicine, University of California, San Francisco, CA, USA
- UCSF-Abbott Viral Diagnostics and Discovery Center, San Francisco, CA, USA
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, CA, USA
| | | | - Nicholas Tatonetti
- Department of Biomedical Informatics, Department of Systems Biology, Department of Medicine, Institute for Genomic Medicine, Columbia University, Columbia, NY, USA.
| | - Hanna Rennert
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
| | - Marcin Imielinski
- New York Genome Center, New York, NY, USA.
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA.
- Englander Institute for Precision Medicine and the Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
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5
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Abstract
Immune checkpoint blockade leads to unprecedented responses in many cancers. Although currently available agents mostly target the PD-1 and CTLA-4 pathways, agents targeting the immune checkpoint protein LAG-3 are under active clinical development, and early clinical data show that LAG-3 expression is a biomarker of response to LAG-3 blockade. To determine which cancers may benefit most from LAG-3 blockade, we performed a pan-cancer analysis of The Cancer Genome Atlas dataset to identify genomic and immunologic correlates of LAG-3 expression. High mutation burden, and expression of exogenous virus (EBV, HPV) or endogenous retrovirus (ERV3-2), were associated with overexpression of LAG-3 in multiple cancers. Although CD8+ T-cell marker (CD8A) and LAG-3 were strongly co-expressed with each other and with PD-L1 in most cancers, there were three notable exceptions: HPV+ head-neck squamous cell cancer, renal cell cancer, and glioblastoma. These results may have important implications for guiding development clinical trials of LAG-3 blockade.
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Affiliation(s)
- Anshuman Panda
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Jeffrey A. Rosenfeld
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Eric A. Singer
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
- Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
| | - Gyan Bhanot
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
- Department of Physics and Astronomy, Rutgers University, Piscataway, NJ, USA
- Department of Molecular Biology and Biochemistry, Rutgers University, Piscataway, NJ, USA
- Moores Cancer Center at UC San Diego Health, University of California at San Diego, La Jolla, CA, USA
| | - Shridar Ganesan
- Rutgers Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
- Department of Medicine, Rutgers Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA
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6
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Contractor T, Clausen R, Harris GR, Rosenfeld JA, Carpizo DR, Tang L, Harris CR. IGF2 drives formation of ileal neuroendocrine tumors in patients and mice. Endocr Relat Cancer 2020; 27:175-186. [PMID: 31951591 DOI: 10.1530/erc-19-0505] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 01/16/2020] [Indexed: 11/08/2022]
Abstract
By the strictest of definitions, a genetic driver of tumorigenesis should fulfill two criteria: it should be altered in a high percentage of patient tumors, and it should also be able to cause the same type of tumor to form in mice. No gene that fits either of these criteria has ever been found for ileal neuroendocrine tumors (I-NETs), which in humans are known for an unusual lack of recurrently mutated genes, and which have never been detected in mice. In the following report, we show that I-NETs can be generated by transgenic RT2 mice, which is a classic model for a genetically unrelated disease, pancreatic neuroendocrine tumors (PNETs). The ability of RT2 mice to generate I-NETs depended upon genetic background. I-NETs appeared in a B6AF1 genetic background, but not in a B6 background nor even in an AB6F1 background. AB6F1 and B6AF1 have identical nuclear DNA but can potentially express different allelic forms of imprinted genes. This led us to test human I-NETs for loss of imprinting, and we discovered that the IGF2 gene showed loss of imprinting and increased expression in the I-NETs of 57% of patients. By increasing IGF2 activity genetically, I-NETs could be produced by RT2 mice in a B6 genetic background, which otherwise never developed I-NETs. The facts that IGF2 is altered in a high percentage of patients with I-NETs and that I-NETs can form in mice that have elevated IGF2 activity, define IGF2 as the first genetic driver of ileal neuroendocrine tumorigenesis.
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Affiliation(s)
| | - Richard Clausen
- Raymond and Beverly Sackler Foundation, New Brunswick, New Jersey, USA
| | - Grant R Harris
- Raymond and Beverly Sackler Foundation, New Brunswick, New Jersey, USA
| | | | - Darren R Carpizo
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
| | - Laura Tang
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Chris R Harris
- Raymond and Beverly Sackler Foundation, New Brunswick, New Jersey, USA
- Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey, USA
- Department of Surgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA
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7
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Tomoiaga D, Aguiar-Pulido V, Shrestha S, Feinstein P, Levy SE, Mason CE, Rosenfeld JA. Single-cell sperm transcriptomes and variants from fathers of children with and without autism spectrum disorder. NPJ Genom Med 2020; 5:14. [PMID: 32133155 PMCID: PMC7035312 DOI: 10.1038/s41525-020-0117-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 01/02/2020] [Indexed: 11/17/2022] Open
Abstract
The human sperm is one of the smallest cells in the body, but also one of the most important, as it serves as the entire paternal genetic contribution to a child. Investigating RNA and mutations in sperm is especially relevant for diseases such as autism spectrum disorders (ASD), which have been correlated with advanced paternal age. Historically, studies have focused on the assessment of bulk sperm, wherein millions of individual sperm are present and only high-frequency variants can be detected. Using 10× Chromium single-cell sequencing technology, we assessed the transcriptome from >65,000 single spermatozoa across six sperm donors (scSperm-RNA-seq), including two who fathered multiple children with ASD and four fathers of neurotypical children. Using RNA-seq methods for differential expression and variant analysis, we found clusters of sperm mutations in each donor that are indicative of the sperm being produced by different stem cell pools. Finally, we have shown that genetic variations can be found in single sperm.
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Affiliation(s)
- Delia Tomoiaga
- 1Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY USA
| | - Vanessa Aguiar-Pulido
- 2The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY USA
| | | | - Paul Feinstein
- 4Hunter College, City University of New York, New York, NY USA
| | - Shawn E Levy
- 3Hudson Alpha Institute for Biotechnology, Huntsville, AL USA
| | - Christopher E Mason
- 1Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY USA.,2The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY USA.,5The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY USA.,6The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY USA
| | - Jeffrey A Rosenfeld
- 7Rutgers Cancer Institute of New Jersey, New Brunswick, NJ USA.,8Department of Pathology, Robert Wood Johnson Medical School, New Brunswick, NJ USA
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8
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Oppenheim S, Cao X, Rueppel O, Krongdang S, Phokasem P, DeSalle R, Goodwin S, Xing J, Chantawannakul P, Rosenfeld JA. Whole Genome Sequencing and Assembly of the Asian Honey Bee Apis dorsata. Genome Biol Evol 2020; 12:3677-3683. [PMID: 31860080 PMCID: PMC6953811 DOI: 10.1093/gbe/evz277] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/13/2019] [Indexed: 12/16/2022] Open
Abstract
The Asian honey bee (Apis dorsata) is distinct from its more widely distributed cousin Apis mellifera by a few key characteristics. Most prominently, A. dorsata, nest in the open by forming a colony clustered around the honeycomb, whereas A. mellifera nest in concealed cavities. Additionally, the worker and reproductive castes are all of the same size in A. dorsata. In order to investigate these differences, we performed whole genome sequencing of A. dorsata using a hybrid Oxford Nanopore and Illumina approach. The 223 Mb genome has an N50 of 35 kb with the largest scaffold of 302 kb. We have found that there are many genes in the dorsata genome that are distinct from other hymenoptera and also large amounts of transposable elements, and we suggest some candidate genes for A. dorsata's exceptional level of defensive aggression.
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Affiliation(s)
- Sara Oppenheim
- Sackler Institute for Comparative Genomics, American Museum of Natural History
| | - Xiaolong Cao
- Department of Genetics, Human Genetic Institute of New Jersey, Rutgers, The State University of New Jersey
| | - Olav Rueppel
- Biology Department, University of North Carolina at Greensboro
| | - Sasiprapa Krongdang
- Department of Biology & Environmental Science Research Center (ESRC), Faculty of Science, Chiang Mai University, Thailand
| | - Patcharin Phokasem
- Department of Biology & Environmental Science Research Center (ESRC), Faculty of Science, Chiang Mai University, Thailand
| | - Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History
| | | | - Jinchuan Xing
- Department of Genetics, Human Genetic Institute of New Jersey, Rutgers, The State University of New Jersey
| | - Panuwan Chantawannakul
- Department of Biology & Environmental Science Research Center (ESRC), Faculty of Science, Chiang Mai University, Thailand
| | - Jeffrey A Rosenfeld
- Sackler Institute for Comparative Genomics, American Museum of Natural History
- Rutgers Cancer Institute of New Jersey
- Department of Pathology, Robert Wood Johnson Medical School
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9
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Lee GT, Rosenfeld JA, Kim WT, Kwon YS, Palapattu G, Mehra R, Kim WJ, Kim IY. TCF4 induces enzalutamide resistance via neuroendocrine differentiation in prostate cancer. PLoS One 2019; 14:e0213488. [PMID: 31536510 PMCID: PMC6752758 DOI: 10.1371/journal.pone.0213488] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 08/17/2019] [Indexed: 12/21/2022] Open
Abstract
In treating patients with castration resistant prostate cancer (CRPC), enzalutamide, the second-generation androgen receptor (AR) antagonist, is an accepted standard of care. However, clinical benefits are limited to a median time of 4.8 months because resistance inevitably emerges. To determine the mechanism of treatment resistance, we carried out a RNA sequence analysis and found increased expression levels of neuroendocrine markers in the enzalutamide-resistant LNCaP human prostate cancer (CaP) cell line when compared to the parental cell line. Subsequent studies demonstrated that Transcription Factor-4 (TCF4), a transcription factor implicated in WNT signaling, mediated neuroendocrine differentiation (NED) in response to enzalutamide treatment and was elevated in the enzalutamide-resistant LNCaP. In addition, we observed that PTHrP mediated enzalutamide resistance in tissue culture and inducible TCF4 overexpression resulted in enzalutamide-resistance in a mouse xenograft model. Finally, small molecule inhibitors of TCF4 or PTHrP partially reversed enzalutamide resistance in CaP cells. When tissues obtained from men who died of metastatic CaP were examined, a positive correlation was found between the expression levels of TCF4 and PTHrP. Taken together, the current results indicate that TCF4 induces enzalutamide resistance via NED in CaP.
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Affiliation(s)
- Geun Taek Lee
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey, and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States of America
| | - Jeffrey A. Rosenfeld
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey, and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States of America
| | - Won Tae Kim
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey, and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States of America
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Young Suk Kwon
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey, and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States of America
| | - Ganesh Palapattu
- Department of Urology, University of Michigan, Ann Arbor, MI, United States of America
| | - Rohit Mehra
- Department of Urology, University of Michigan, Ann Arbor, MI, United States of America
| | - Wun-Jae Kim
- Department of Urology, Chungbuk National University College of Medicine, Cheongju, Korea
| | - Isaac Yi Kim
- Section of Urologic Oncology, Rutgers Cancer Institute of New Jersey, and Division of Urology, Rutgers Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, New Brunswick, NJ, United States of America
- * E-mail:
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10
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Oppenheim SJ, Rosenfeld JA, DeSalle R. Genome content analysis yields new insights into the relationship between the human malaria parasite Plasmodium falciparum and its anopheline vectors. BMC Genomics 2017; 18:205. [PMID: 28241792 PMCID: PMC5327517 DOI: 10.1186/s12864-017-3590-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Accepted: 02/13/2017] [Indexed: 11/24/2022] Open
Abstract
Background The persistent and growing gap between the availability of sequenced genomes and the ability to assign functions to sequenced genes led us to explore ways to maximize the information content of automated annotation for studies of anopheline mosquitos. Specifically, we use genome content analysis of a large number of previously sequenced anopheline mosquitos to follow the loss and gain of protein families over the evolutionary history of this group. The importance of this endeavor lies in the potential for comparative genomic studies between Anopheles and closely related non-vector species to reveal ancestral genome content dynamics involved in vector competence. In addition, comparisons within Anopheles could identify genome content changes responsible for variation in the vectorial capacity of this family of important parasite vectors. Results The competence and capacity of P. falciparum vectors do not appear to be phylogenetically constrained within the Anophelinae. Instead, using ancestral reconstruction methods, we suggest that a previously unexamined component of vector biology, anopheline nucleotide metabolism, may contribute to the unique status of anophelines as P. falciparum vectors. While the fitness effects of nucleotide co-option by P. falciparum parasites on their anopheline hosts are not yet known, our results suggest that anopheline genome content may be responding to selection pressure from P. falciparum. Whether this response is defensive, in an attempt to redress improper nucleotide balance resulting from P. falciparum infection, or perhaps symbiotic, resulting from an as-yet-unknown mutualism between anophelines and P. falciparum, is an open question that deserves further study. Conclusions Clearly, there is a wealth of functional information to be gained from detailed manual genome annotation, yet the rapid increase in the number of available sequences means that most researchers will not have the time or resources to manually annotate all the sequence data they generate. We believe that efforts to maximize the amount of information obtained from automated annotation can help address the functional annotation deficit that most evolutionary biologists now face, and here demonstrate the value of such an approach. Electronic supplementary material The online version of this article (doi:10.1186/s12864-017-3590-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sara J Oppenheim
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, NY, 10024, USA.
| | - Jeffrey A Rosenfeld
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, NY, 10024, USA.,Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, NY, 10024, USA
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11
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Gillentine MA, Berry LN, Goin-Kochel RP, Ali MA, Ge J, Guffey D, Rosenfeld JA, Hannig V, Bader P, Proud M, Shinawi M, Graham BH, Lin A, Lalani SR, Reynolds J, Chen M, Grebe T, Minard CG, Stankiewicz P, Beaudet AL, Schaaf CP. Erratum to: The Cognitive and Behavioral Phenotypes of Individuals with CHRNA7 Duplications. J Autism Dev Disord 2017; 47:563. [PMID: 28168676 DOI: 10.1007/s10803-017-3047-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- M A Gillentine
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Moursund Street, Ste. 1325, Houston, TX, USA
| | - L N Berry
- Autism Center, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - R P Goin-Kochel
- Autism Center, Texas Children's Hospital, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - M A Ali
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Moursund Street, Ste. 1325, Houston, TX, USA
| | - J Ge
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - D Guffey
- Dan L. Duncan Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - J A Rosenfeld
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - V Hannig
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, USA
| | - P Bader
- Northeast Indiana Genetics, Fort Wayne, IN, USA
| | - M Proud
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.,Department of Neurology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - M Shinawi
- Department of Pediatrics, Division of Genetics and Genomic Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - B H Graham
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - A Lin
- Medical Genetics, MassGeneral Hospital for Children, Harvard Medical School, Boston, MA, USA
| | - S R Lalani
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - J Reynolds
- Medical Genetics, Shodair Children's Hospital, Helena, MT, USA
| | - M Chen
- Department of Pediatrics-Diabetes and Endocrinology, Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - T Grebe
- Department of Child Health, Division of Genetics and Metabolism, Phoenix Children's Hospital, University of Arizona College of Medicine, Phoenix, AZ, USA
| | - C G Minard
- Dan L. Duncan Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - P Stankiewicz
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - A L Beaudet
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - C P Schaaf
- Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA. .,Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Moursund Street, Ste. 1325, Houston, TX, USA.
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12
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Zak J, Vives V, Szumska D, Vernet A, Schneider JE, Miller P, Slee EA, Joss S, Lacassie Y, Chen E, Escobar LF, Tucker M, Aylsworth AS, Dubbs HA, Collins AT, Andrieux J, Dieux-Coeslier A, Haberlandt E, Kotzot D, Scott DA, Parker MJ, Zakaria Z, Choy YS, Wieczorek D, Innes AM, Jun KR, Zinner S, Prin F, Lygate CA, Pretorius P, Rosenfeld JA, Mohun TJ, Lu X. ASPP2 deficiency causes features of 1q41q42 microdeletion syndrome. Cell Death Differ 2016; 23:1973-1984. [PMID: 27447114 PMCID: PMC5136487 DOI: 10.1038/cdd.2016.76] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 06/09/2016] [Accepted: 06/13/2016] [Indexed: 11/09/2022] Open
Abstract
Chromosomal abnormalities are implicated in a substantial number of human developmental syndromes, but for many such disorders little is known about the causative genes. The recently described 1q41q42 microdeletion syndrome is characterized by characteristic dysmorphic features, intellectual disability and brain morphological abnormalities, but the precise genetic basis for these abnormalities remains unknown. Here, our detailed analysis of the genetic abnormalities of 1q41q42 microdeletion cases identified TP53BP2, which encodes apoptosis-stimulating protein of p53 2 (ASPP2), as a candidate gene for brain abnormalities. Consistent with this, Trp53bp2-deficient mice show dilation of lateral ventricles resembling the phenotype of 1q41q42 microdeletion patients. Trp53bp2 deficiency causes 100% neonatal lethality in the C57BL/6 background associated with a high incidence of neural tube defects and a range of developmental abnormalities such as congenital heart defects, coloboma, microphthalmia, urogenital and craniofacial abnormalities. Interestingly, abnormalities show a high degree of overlap with 1q41q42 microdeletion-associated abnormalities. These findings identify TP53BP2 as a strong candidate causative gene for central nervous system (CNS) defects in 1q41q42 microdeletion syndrome, and open new avenues for investigation of the mechanisms underlying CNS abnormalities.
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Affiliation(s)
- J Zak
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7DQ, UK
| | - V Vives
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7DQ, UK
| | - D Szumska
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - A Vernet
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - J E Schneider
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - P Miller
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7DQ, UK
| | - E A Slee
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7DQ, UK
| | - S Joss
- Queen Elizabeth University Hospital Glasgow, Glasgow G51 4TF, UK
| | - Y Lacassie
- Department of Pediatrics, Louisiana State University, New Orleans, LA 70118, USA
- Genetics Services, Children's Hospital New Orleans, New Orleans, LA 70118, USA
| | - E Chen
- Kaiser Permanente, San Francisco Medical Center, San Francisco, CA 94115, USA
| | - L F Escobar
- St Vincent Children's Hospital, Indianapolis, IN 46260, USA
| | - M Tucker
- St Vincent Children's Hospital, Indianapolis, IN 46260, USA
| | - A S Aylsworth
- Departments of Pediatrics and Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - H A Dubbs
- Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - A T Collins
- Seattle Children's Hospital, Seattle, WA 98105, USA
| | - J Andrieux
- Institute of Medical Genetics, Jeanne de Flandre Hospital, CHRU de Lille, Lille 59000, France
| | | | - E Haberlandt
- Clinical Department of Pediatrics, Innsbruck Medical University, Innsbruck A-6020, Austria
| | - D Kotzot
- Division of Human Genetics, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck A-6020, Austria
| | - D A Scott
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - M J Parker
- Sheffield Children's Hospital NHS Foundation Trust, Western Bank, Sheffield, S10 2TH, UK
| | - Z Zakaria
- Institute for Medical Research, Kuala Lumpur, Jalan Pahang 50588, Malaysia
| | - Y S Choy
- Prince Court Medical Centre, Kuala Lumpur 50450, Malaysia
| | - D Wieczorek
- Institute of Human Genetics, University Clinic Essen, Duisburg-Essen University, Essen 45122, Germany
- Institute of Human Genetics, University Clinic, Heinrich-Heine University, Düsseldorf 40225, Germany
| | - A M Innes
- Department of Medical Genetics and Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada T3B 6A8
| | - K R Jun
- Department of Laboratory Medicine, Haeundae Paik Hospital, Inje University, Haeundae-gu, Busan, Korea
| | - S Zinner
- Seattle Children's Hospital, Seattle, WA 98105, USA
| | - F Prin
- The Francis Crick Institute Mill Hill Laboratory, London NW7 1AA, UK
| | - C A Lygate
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7BN, UK
| | - P Pretorius
- Department of Neuroradiology, John Radcliffe Hospital, Oxford University Hospitals NHS Trust, Oxford OX3 9DU, UK
| | - J A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA
| | - T J Mohun
- The Francis Crick Institute Mill Hill Laboratory, London NW7 1AA, UK
| | - X Lu
- Ludwig Institute for Cancer Research, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7DQ, UK
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13
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Kolokotronis SO, Foox J, Rosenfeld JA, Brugler MR, Reeves D, Benoit JB, Booth W, Robison G, Steffen M, Sakas Z, Palli SR, Schal C, Richards S, Narechania A, Baker RH, Sorkin LN, Amato G, Mason CE, Siddall ME, DeSalle R. The mitogenome of the bed bug Cimex lectularius (Hemiptera: Cimicidae). Mitochondrial DNA B Resour 2016; 1:425-427. [PMID: 27617305 PMCID: PMC5012718 DOI: 10.1080/23802359.2016.1180268] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
We report the extraction of a bed bug mitogenome from high-throughput sequencing projects originally focused on the nuclear genome of Cimex lectularius. The assembled mitogenome has a similar AT nucleotide composition bias found in other insects. Phylogenetic analysis of all protein-coding genes indicates that C. lectularius is clearly a member of a paraphyletic Cimicomorpha clade within the Order Hemiptera.
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Affiliation(s)
- Sergios-Orestis Kolokotronis
- Department of Biological Sciences, Fordham University, Bronx, NY, USA.,Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Jonathan Foox
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Jeffrey A Rosenfeld
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA.,Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, USA
| | - Mercer R Brugler
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA.,Biological Sciences Department, NYC College of Technology, City University of New York, Brooklyn, NY, USA
| | - Darryl Reeves
- Department of Physiology and Biophysics and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Joshua B Benoit
- Department of Biological Sciences, University of Cincinnati, Cincinnati, OH, USA
| | - Warren Booth
- Department of Biological Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Grant Robison
- Department of Biological Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Michael Steffen
- Department of Biological Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Zoe Sakas
- Department of Biological Sciences, Fordham University, Bronx, NY, USA
| | - Subba R Palli
- Department of Entomology, University of Kentucky, Lexington, KY, USA
| | - Coby Schal
- Department of Entomology and W.M. Keck Center for Behavioral Biology, North Carolina State University, Raleigh, NC, USA
| | - Stephen Richards
- Human Genome Sequencing Center, Department of Human and Molecular Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Apurva Narechania
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Richard H Baker
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Louis N Sorkin
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - George Amato
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics and HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Mark E Siddall
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Rob DeSalle
- Sackler Institute for Comparative Genomics and Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA
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14
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Rosenfeld JA, Foox J, DeSalle R. Insect genome content phylogeny and functional annotation of core insect genomes. Mol Phylogenet Evol 2016; 97:224-232. [DOI: 10.1016/j.ympev.2015.10.014] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2015] [Revised: 09/02/2015] [Accepted: 10/13/2015] [Indexed: 10/22/2022]
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15
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Rosenfeld JA, Reeves D, Brugler MR, Narechania A, Simon S, Durrett R, Foox J, Shianna K, Schatz MC, Gandara J, Afshinnekoo E, Lam ET, Hastie AR, Chan S, Cao H, Saghbini M, Kentsis A, Planet PJ, Kholodovych V, Tessler M, Baker R, DeSalle R, Sorkin LN, Kolokotronis SO, Siddall ME, Amato G, Mason CE. Genome assembly and geospatial phylogenomics of the bed bug Cimex lectularius. Nat Commun 2016; 7:10164. [PMID: 26836631 PMCID: PMC4740774 DOI: 10.1038/ncomms10164] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Accepted: 11/10/2015] [Indexed: 01/21/2023] Open
Abstract
The common bed bug (Cimex lectularius) has been a persistent pest of humans for thousands of years, yet the genetic basis of the bed bug's basic biology and adaptation to dense human environments is largely unknown. Here we report the assembly, annotation and phylogenetic mapping of the 697.9-Mb Cimex lectularius genome, with an N50 of 971 kb, using both long and short read technologies. A RNA-seq time course across all five developmental stages and male and female adults generated 36,985 coding and noncoding gene models. The most pronounced change in gene expression during the life cycle occurs after feeding on human blood and included genes from the Wolbachia endosymbiont, which shows a simultaneous and coordinated host/commensal response to haematophagous activity. These data provide a rich genetic resource for mapping activity and density of C. lectularius across human hosts and cities, which can help track, manage and control bed bug infestations.
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Affiliation(s)
- Jeffrey A Rosenfeld
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA.,Cancer Institute of New Jersey, Rutgers University, New Brunswick, New Jersey 08908, USA
| | - Darryl Reeves
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, New York 10065, USA.,Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York 10065, USA
| | - Mercer R Brugler
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA.,Biological Sciences Department, NYC College of Technology (CUNY), Brooklyn, New York 11201, USA
| | - Apurva Narechania
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Sabrina Simon
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Biosystematics, Wageningen University, Wageningen 6708 PB, The Netherlands
| | - Russell Durrett
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, New York 10065, USA
| | - Jonathan Foox
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Kevin Shianna
- Illumina Inc. 5200 Illumina Way, San Diego, California 92122, USA
| | - Michael C Schatz
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Jorge Gandara
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, New York 10065, USA
| | - Ebrahim Afshinnekoo
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, New York 10065, USA
| | - Ernest T Lam
- BioNanoGenomics Inc. 9640 Towne Centre Drive Ste. 100, San Diego, California 92121, USA
| | - Alex R Hastie
- BioNanoGenomics Inc. 9640 Towne Centre Drive Ste. 100, San Diego, California 92121, USA
| | - Saki Chan
- BioNanoGenomics Inc. 9640 Towne Centre Drive Ste. 100, San Diego, California 92121, USA
| | - Han Cao
- BioNanoGenomics Inc. 9640 Towne Centre Drive Ste. 100, San Diego, California 92121, USA
| | - Michael Saghbini
- BioNanoGenomics Inc. 9640 Towne Centre Drive Ste. 100, San Diego, California 92121, USA
| | - Alex Kentsis
- Molecular Pharmacology and Chemistry Program, Department of Pediatrics, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York 10065, USA.,Department of Pediatrics, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, Cornell University, New York, New York 10065, USA
| | - Paul J Planet
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA.,Division of Pediatric Infectious Diseases, College of Physicians and Surgeons, Columbia University, New York, New York 10032, USA
| | - Vladyslav Kholodovych
- High Performance and Research Computing Group, Rutgers Biomedical and Health Sciences, Newark, New Jersey 07103, USA
| | - Michael Tessler
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Richard Baker
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Louis N Sorkin
- Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Sergios-Orestis Kolokotronis
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA.,Department of Biological Sciences, Fordham University, Bronx, New York 10458, USA
| | - Mark E Siddall
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - George Amato
- Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, New York 10024, USA.,Division of Invertebrate Zoology, American Museum of Natural History, New York, New York 10024, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, New York, New York 10065, USA.,Tri-Institutional Training Program in Computational Biology and Medicine, New York, New York 10065, USA.,The Feil Family Brain and Mind Research Institute, New York, New York 10065, USA
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16
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Rosenfeld JA, Tucker ME, Escobar LF, Neill NJ, Torchia BS, McDaniel LD, Schultz RA, Chong K, Chitayat D. Diagnostic utility of microarray testing in pregnancy loss. Ultrasound Obstet Gynecol 2015; 46:478-486. [PMID: 25846569 DOI: 10.1002/uog.14866] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Revised: 03/25/2015] [Accepted: 03/29/2015] [Indexed: 06/04/2023]
Abstract
OBJECTIVES To determine the frequency of clinically significant chromosomal abnormalities identified by chromosomal microarray in pregnancy losses at any gestational age and to compare microarray performance with that of traditional cytogenetic analysis when testing pregnancy losses. METHODS Among 535 fetal demise specimens of any gestational age, clinical microarray-based comparative genomic hybridization (aCGH) was performed successfully on 515, and a subset of 107 specimens underwent additional single nucleotide polymorphism (SNP) analysis. RESULTS Overall, clinically significant abnormalities were identified in 12.8% (64/499) of specimens referred with normal or unknown karyotypes. Detection rates were significantly higher with earlier gestational age. In the subset with normal karyotype, clinically significant abnormalities were identified in 6.9% (20/288). This detection rate did not vary significantly with gestational age, suggesting that, unlike aneuploidy, the contribution of submicroscopic chromosomal abnormalities to fetal demise does not vary with gestational age. In the 107 specimens that underwent aCGH and SNP analysis, seven cases (6.5%) had abnormalities of potential clinical significance detected by the SNP component, including female triploidy. aCGH failed to yield fetal results in 8.3%, which is an improvement over traditional cytogenetic analysis of fetal demise specimens. CONCLUSIONS Both the provision of results in cases in which karyotype fails and the detection of abnormalities in the presence of a normal karyotype demonstrate the increased diagnostic utility of microarray in pregnancy loss. Thus, chromosomal microarray testing is a preferable, robust method of analyzing cases of pregnancy loss to better delineate possible genetic etiologies, regardless of gestational age.
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Affiliation(s)
- J A Rosenfeld
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, WA, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - M E Tucker
- St. Vincent Hospital, Indianapolis, IN, USA
| | | | - N J Neill
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, WA, USA
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - B S Torchia
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, WA, USA
| | - L D McDaniel
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, WA, USA
| | - R A Schultz
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, WA, USA
| | - K Chong
- The Prenatal Diagnosis and Medical Genetics Program, Mount Sinai Hospital, University of Toronto, Ontario, Canada
| | - D Chitayat
- The Prenatal Diagnosis and Medical Genetics Program, Mount Sinai Hospital, University of Toronto, Ontario, Canada
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17
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Chhangawala S, Rudy G, Mason CE, Rosenfeld JA. The impact of read length on quantification of differentially expressed genes and splice junction detection. Genome Biol 2015; 16:131. [PMID: 26100517 PMCID: PMC4531809 DOI: 10.1186/s13059-015-0697-y] [Citation(s) in RCA: 76] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Background The initial next-generation sequencing technologies produced reads of 25 or 36 bp, and only from a single-end of the library sequence. Currently, it is possible to reliably produce 300 bp paired-end sequences for RNA expression analysis. While read lengths have consistently increased, people have assumed that longer reads are more informative and that paired-end reads produce better results than single-end reads. We used paired-end 101 bp reads and trimmed them to simulate different read lengths, and also separated the pairs to produce single-end reads. For each read length and paired status, we evaluated differential expression levels between two standard samples and compared the results to those obtained by qPCR. Results We found that, with the exception of 25 bp reads, there is little difference for the detection of differential expression regardless of the read length. Once single-end reads are at a length of 50 bp, the results do not change substantially for any level up to, and including, 100 bp paired-end. However, splice junction detection significantly improves as the read length increases with 100 bp paired-end showing the best performance. We performed the same analysis on two ENCODE samples and found consistent results confirming that our conclusions have broad application. Conclusions A researcher could save substantial resources by using 50 bp single-end reads for differential expression analysis instead of using longer reads. However, splicing detection is unquestionably improved by paired-end and longer reads. Therefore, an appropriate read length should be used based on the final goal of the study. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0697-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Sagar Chhangawala
- The Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, 10021, USA. .,Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, 10021, USA.
| | - Gabe Rudy
- Golden Helix, 203 Enterprise Blvd, Suite 1, Bozeman, MT, 59718, USA.
| | - Christopher E Mason
- The Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY, 10021, USA. .,Rutgers-Cancer Institute of New Jersey, New Brunswick, NJ, 08901, USA.
| | - Jeffrey A Rosenfeld
- Rutgers-Cancer Institute of New Jersey, New Brunswick, NJ, 08901, USA. .,American Museum of Natural History, New York, NY, USA.
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18
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Probst FJ, James RA, Burrage LC, Rosenfeld JA, Bohan TP, Ward Melver CH, Magoulas P, Austin E, Franklin AIA, Azamian M, Xia F, Patel A, Bi W, Bacino C, Belmont JW, Ware SM, Shaw C, Cheung SW, Lalani SR. De novo deletions and duplications of 17q25.3 cause susceptibility to cardiovascular malformations. Orphanet J Rare Dis 2015; 10:75. [PMID: 26070612 PMCID: PMC4472615 DOI: 10.1186/s13023-015-0291-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2015] [Accepted: 06/02/2015] [Indexed: 01/28/2023] Open
Abstract
Background Genomic disorders resulting from deletion or duplication of genomic segments are known to be an important cause of cardiovascular malformations (CVMs). In our previous study, we identified a unique individual with a de novo 17q25.3 deletion from a study of 714 individuals with CVM. Methods To understand the contribution of this locus to cardiac malformations, we reviewed the data on 60,000 samples submitted for array comparative genomic hybridization (CGH) studies to Medical Genetics Laboratories at Baylor College of Medicine, and ascertained seven individuals with segmental aneusomy of 17q25. We validated our findings by studying another individual with a de novo submicroscopic deletion of this region from Cytogenetics Laboratory at Cincinnati Children’s Hospital. Using bioinformatic analyses including protein-protein interaction network, human tissue expression patterns, haploinsufficiency scores, and other annotation systems, including a training set of 251 genes known to be linked to human cardiac disease, we constructed a pathogenicity score for cardiac phenotype for each of the 57 genes within the terminal 2.0 Mb of 17q25.3. Results We found relatively high penetrance of cardiovascular defects (~60 %) with five deletions and three duplications, observed in eight unrelated individuals. Distinct cardiac phenotypes were present in four of these subjects with non-recurrent de novo deletions (range 0.08 Mb–1.4 Mb) in the subtelomeric region of 17q25.3. These included coarctation of the aorta (CoA), total anomalous pulmonary venous return (TAPVR), ventricular septal defect (VSD) and atrial septal defect (ASD). Amongst the three individuals with variable size duplications of this region, one had patent ductus arteriosus (PDA) at 8 months of age. Conclusion The distinct cardiac lesions observed in the affected patients and the bioinformatics analyses suggest that multiple genes may be plausible drivers of the cardiac phenotype within this gene-rich critical interval of 17q25.3. Electronic supplementary material The online version of this article (doi:10.1186/s13023-015-0291-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- F J Probst
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - R A James
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - L C Burrage
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - J A Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - T P Bohan
- Department of Neurology, Memorial Hermann Texas Medical Center, Houston, TX, USA
| | - C H Ward Melver
- Genetic Center, Children's Hospital Medical Center Of Akron, Akron, OH, USA
| | - P Magoulas
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - E Austin
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - A I A Franklin
- Department of Developmental Pediatrics, Texas Children's Hospital, Houston, TX, USA
| | - M Azamian
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - F Xia
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - A Patel
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - W Bi
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - C Bacino
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - J W Belmont
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - S M Ware
- Departments of Pediatrics and Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - C Shaw
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - S W Cheung
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA
| | - S R Lalani
- Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, MS BCM225, Houston, TX, USA.
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19
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Khurana E, Fu Y, Colonna V, Mu XJ, Kang HM, Lappalainen T, Sboner A, Lochovsky L, Chen J, Harmanci A, Das J, Abyzov A, Balasubramanian S, Beal K, Chakravarty D, Challis D, Chen Y, Clarke D, Clarke L, Cunningham F, Evani US, Flicek P, Fragoza R, Garrison E, Gibbs R, Gümüş ZH, Herrero J, Kitabayashi N, Kong Y, Lage K, Liluashvili V, Lipkin SM, MacArthur DG, Marth G, Muzny D, Pers TH, Ritchie GRS, Rosenfeld JA, Sisu C, Wei X, Wilson M, Xue Y, Yu F, Dermitzakis ET, Yu H, Rubin MA, Tyler-Smith C, Gerstein M. Integrative annotation of variants from 1092 humans: application to cancer genomics. Science 2013; 342:1235587. [PMID: 24092746 DOI: 10.1126/science.1235587] [Citation(s) in RCA: 269] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations ("ultrasensitive") and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, "motif-breakers"). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.
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Affiliation(s)
- Ekta Khurana
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yao Fu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Vincenza Colonna
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK.,Institute of Genetics and Biophysics, National Research Council (CNR), 80131 Naples, Italy
| | - Xinmeng Jasmine Mu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Hyun Min Kang
- Center for Statistical Genetics, Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Tuuli Lappalainen
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.,Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland.,Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Andrea Sboner
- Institute for Precision Medicine and the Department of Pathology and Laboratory Medicine, Weill Cornell Medical College and New York-Presbyterian Hospital, New York, NY 10065, USA.,The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA
| | - Lucas Lochovsky
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Jieming Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Integrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, CT 06520, USA
| | - Arif Harmanci
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jishnu Das
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
| | - Alexej Abyzov
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suganthi Balasubramanian
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Kathryn Beal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Dimple Chakravarty
- Institute for Precision Medicine and the Department of Pathology and Laboratory Medicine, Weill Cornell Medical College and New York-Presbyterian Hospital, New York, NY 10065, USA
| | - Daniel Challis
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX 77030, USA
| | - Yuan Chen
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Declan Clarke
- Department of Chemistry, Yale University, New Haven, CT 06520, USA
| | - Laura Clarke
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Uday S Evani
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX 77030, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Robert Fragoza
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.,Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Erik Garrison
- Department of Biology, Boston College, Chestnut Hill, MA 02467, USA
| | - Richard Gibbs
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX 77030, USA
| | - Zeynep H Gümüş
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA.,Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, 10065, USA
| | - Javier Herrero
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Naoki Kitabayashi
- Institute for Precision Medicine and the Department of Pathology and Laboratory Medicine, Weill Cornell Medical College and New York-Presbyterian Hospital, New York, NY 10065, USA
| | - Yong Kong
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.,Keck Biotechnology Resource Laboratory, Yale University, New Haven, CT 06511, USA
| | - Kasper Lage
- Pediatric Surgical Research Laboratories, MassGeneral Hospital for Children, Massachusetts General Hospital, Boston, MA 02114, USA.,Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.,Harvard Medical School, Boston, MA 02115, USA.,Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.,Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Vaja Liluashvili
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, NY 10021, USA.,Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, 10065, USA
| | - Steven M Lipkin
- Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Daniel G MacArthur
- Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA.,Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA 02142, USA
| | - Gabor Marth
- Department of Biology, Boston College, Chestnut Hill, MA 02467, USA
| | - Donna Muzny
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX 77030, USA
| | - Tune H Pers
- Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Lyngby, Denmark.,Division of Endocrinology and Center for Basic and Translational Obesity Research, Children's Hospital, Boston, MA 02115, USA.,Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Graham R S Ritchie
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jeffrey A Rosenfeld
- Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ 07101, USA.,IST/High Performance and Research Computing, Rutgers University Newark, NJ 07101, USA.,Sackler Institute for Comparative Genomics, American Museum of Natural History, New York, NY 10024, USA
| | - Cristina Sisu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiaomu Wei
- Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.,Department of Medicine, Weill Cornell Medical College, New York, NY 10065, USA
| | - Michael Wilson
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Yali Xue
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Fuli Yu
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX 77030, USA
| | | | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.,Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, 1211 Geneva, Switzerland.,Swiss Institute of Bioinformatics, 1211 Geneva, Switzerland
| | - Haiyuan Yu
- Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY 14853, USA.,Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA
| | - Mark A Rubin
- Institute for Precision Medicine and the Department of Pathology and Laboratory Medicine, Weill Cornell Medical College and New York-Presbyterian Hospital, New York, NY 10065, USA
| | - Chris Tyler-Smith
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.,Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA.,Department of Computer Science, Yale University, New Haven, CT 06520, USA
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20
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Abstract
The scope and eligibility of patents for genetic sequences have been debated for decades, but a critical case regarding gene patents (Association of Molecular Pathologists v. Myriad Genetics) is now reaching the US Supreme Court. Recent court rulings have supported the assertion that such patents can provide intellectual property rights on sequences as small as 15 nucleotides (15mers), but an analysis of all current US patent claims and the human genome presented here shows that 15mer sequences from all human genes match at least one other gene. The average gene matches 364 other genes as 15mers; the breast-cancer-associated gene BRCA1 has 15mers matching at least 689 other genes. Longer sequences (1,000 bp) still showed extensive cross-gene matches. Furthermore, 15mer-length claims from bovine and other animal patents could also claim as much as 84% of the genes in the human genome. In addition, when we expanded our analysis to full-length patent claims on DNA from all US patents to date, we found that 41% of the genes in the human genome have been claimed. Thus, current patents for both short and long nucleotide sequences are extraordinarily non-specific and create an uncertain, problematic liability for genomic medicine, especially in regard to targeted re-sequencing and other sequence diagnostic assays.
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Affiliation(s)
- Jeffrey A Rosenfeld
- IST/Division of High Performance and Research Computing at the University of Medicine & Dentistry of New Jersey, South Orange Avenue, Newark, NJ 07103, USA ; American Museum of Natural History, Sackler Institute for Comparative Genomics, Central Park West at 79th Street, New York, NY 10024, USA
| | - Christopher E Mason
- Department of Physiology and Biophysics, Weill Medical College, Cornell University, New York, NY 10065, USA ; HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Medical College, Cornell University, New York, NY 10065, USA ; The Information Society Project, Yale Law School, New Haven, CT 06520, USA
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21
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Guha S, Rees E, Darvasi A, Ivanov D, Ikeda M, Bergen SE, Magnusson PK, Cormican P, Morris D, Gill M, Cichon S, Rosenfeld JA, Lee A, Gregersen PK, Kane JM, Malhotra AK, Rietschel M, Nöthen MM, Degenhardt F, Priebe L, Breuer R, Strohmaier J, Ruderfer DM, Moran JL, Chambert KD, Sanders AR, Shi J, Kendler K, Riley B, O’Neill T, Walsh D, Malhotra D, Corvin A, Purcell S, Sklar P, Iwata N, Hultman CM, Sullivan PF, Sebat J, McCarthy S, Gejman PV, Levinson DF, Owen MJ, O’Donovan MC, Lencz T, Kirov G. Implication of a rare deletion at distal 16p11.2 in schizophrenia. JAMA Psychiatry 2013; 70:253-60. [PMID: 23325106 PMCID: PMC3750982 DOI: 10.1001/2013.jamapsychiatry.71] [Citation(s) in RCA: 58] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
CONTEXT Large genomic copy number variations have been implicated as strong risk factors for schizophrenia. However, the rarity of these events has created challenges for the identification of further pathogenic loci, and extremely large samples are required to provide convincing replication. OBJECTIVE To detect novel copy number variations that increase the susceptibility to schizophrenia by using 2 ethnically homogeneous discovery cohorts and replication in large samples. DESIGN Genetic association study of microarray data. SETTING Samples of DNA were collected at 9 sites from different countries. PARTICIPANTS Two discovery cohorts consisted of 790 cases with schizophrenia and schizoaffective disorder and 1347 controls of Ashkenazi Jewish descent and 662 parent-offspring trios from Bulgaria, of which the offspring had schizophrenia or schizoaffective disorder. Replication data sets consisted of 12,398 cases and 17,945 controls. MAIN OUTCOME MEASURES Statistically increased rate of specific copy number variations in cases vs controls. RESULTS One novel locus was implicated: a deletion at distal 16p11.2, which does not overlap the proximal 16p11.2 locus previously reported in schizophrenia and autism. Deletions at this locus were found in 13 of 13,850 cases (0.094%) and 3 of 19,954 controls (0.015%) (odds ratio, 6.25 [95% CI, 1.78-21.93]; P = .001, Fisher exact test). CONCLUSIONS Deletions at distal 16p11.2 have been previously implicated in developmental delay and obesity. The region contains 9 genes, several of which are implicated in neurological diseases, regulation of body weight, and glucose homeostasis. A telomeric extension of the deletion, observed in about half the cases but no controls, potentially implicates an additional 8 genes. Our findings add a new locus to the list of copy number variations that increase the risk for development of schizophrenia.
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Affiliation(s)
- Saurav Guha
- The Zucker Hillside Hospital, Psychiatry Research, 75–59 263rd Street, Glen Oaks, NY 11004, USA
| | - Elliott Rees
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Heath Park, Cardiff CF4 4XN, UK
| | - Ariel Darvasi
- Department of Genetics, The Institute of Life Sciences, The Hebrew University of Jerusalem, Givat Ram, Jerusalem, Israel
| | - Dobril Ivanov
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Heath Park, Cardiff CF4 4XN, UK
| | - Masashi Ikeda
- Fujita Healt University School of Medicine, 1–98 Kutsukake-cho Dengakugakubo, Toyoake, Aichi, 470–1192, Japan
| | - Sarah E. Bergen
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, 7 Cambridge Center, Cambridge, MA, USA
| | - Patrik K Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Paul Cormican
- Trinity College Dublin, Dept Psychiatry, College Green, Dublin, Ireland
| | - Derek Morris
- Trinity College Dublin, Dept Psychiatry, College Green, Dublin, Ireland
| | - Michael Gill
- Trinity College Dublin, Dept Psychiatry, College Green, Dublin, Ireland
| | - Sven Cichon
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn
- Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany
| | - Jeffrey A. Rosenfeld
- The Zucker Hillside Hospital, Psychiatry Research, 75–59 263rd Street, Glen Oaks, NY 11004, USA
| | - Annette Lee
- Robert S. Boas Center for Human Genetics and Genomics, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Peter K. Gregersen
- Robert S. Boas Center for Human Genetics and Genomics, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - John M. Kane
- The Zucker Hillside Hospital, Psychiatry Research, 75–59 263rd Street, Glen Oaks, NY 11004, USA
| | - Anil K. Malhotra
- The Zucker Hillside Hospital, Psychiatry Research, 75–59 263rd Street, Glen Oaks, NY 11004, USA
| | - Marcella Rietschel
- Dept. of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn
- German Center for Neurodegenerative Diseases (DZNE), Mount Siani school of Medicine, NY
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn
| | - Lutz Priebe
- Institute of Human Genetics, University of Bonn, Bonn, Germany
- Department of Genomics, Life & Brain Center, University of Bonn
| | - René Breuer
- Dept. of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim
| | - Jana Strohmaier
- Dept. of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Mannheim
| | - Douglas M Ruderfer
- Division of Psychiatric Genomics, Department Psychiatric, Mount Siani school of Medicine, NY
| | - Jennifer L Moran
- Stanley Center for Psychiatric Research, Broad Institute, 7 Cambridge Center, Cambridge, MA, USA
| | - Kimberly D Chambert
- Stanley Center for Psychiatric Research, Broad Institute, 7 Cambridge Center, Cambridge, MA, USA
| | - Alan R. Sanders
- Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem Research Institute, Evanston, IL & Department of Psychiatry and Behavioral Sciences, University of Chicago, Chicago, Illinois, USA
| | | | | | | | - Kenneth Kendler
- Virginia Institute for Psychatry and Behavioral Genetics, School of Medicine, Virginia Commonwealth University, Virginia, USA
| | - Brien Riley
- Department of Psychiatry, School of Medicine, Virginia Commonwealth University, Virginia, USA
| | - Tony O’Neill
- Department of Psychiatry, Queens University Belfast, Ireland
| | | | - Dheeraj Malhotra
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA
| | - Aiden Corvin
- Trinity College Dublin, Dept Psychiatry, College Green, Dublin, Ireland
| | - Shaun Purcell
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, 7 Cambridge Center, Cambridge, MA, USA
| | - Pamela Sklar
- Division of Psychiatric Genomics, Department Psychiatric, Mount Siani school of Medicine, NY
| | - Nakao Iwata
- Fujita Healt University School of Medicine, 1–98 Kutsukake-cho Dengakugakubo, Toyoake, Aichi, 470–1192, Japan
| | - Christina M Hultman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - Patrick F. Sullivan
- Departments of Genetics, Psychiatry, and Epidemiology, University of North Carolina at Chapel Hill, USA
| | - Jonathan Sebat
- Beyster Center for Genomics of Psychiatric Diseases, University of California, San Diego, La Jolla, CA 92093, USA
| | - Shane McCarthy
- Stanley Institute for Cognitive Genomics. Woodbury Genome Center. Cold Spring Harbor Laboratory. Cold Spring Harbor, NY, USA
| | - Pablo V. Gejman
- Department of Psychiatry and Behavioral Sciences, NorthShore University HealthSystem Research Institute, Evanston, IL & Department of Psychiatry and Behavioral Sciences, University of Chicago, Chicago, Illinois, USA
| | - Douglas F. Levinson
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Heath Park, Cardiff CF4 4XN, UK
| | - Michael C O’Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Heath Park, Cardiff CF4 4XN, UK
| | - Todd Lencz
- The Zucker Hillside Hospital, Psychiatry Research, 75–59 263rd Street, Glen Oaks, NY 11004, USA
| | - George Kirov
- MRC Centre for Neuropsychiatric Genetics and Genomics, and Neuroscience and Mental Health Research Institute, Cardiff University, Heath Park, Cardiff CF4 4XN, UK
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22
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Rosenfeld JA, Kim KH, Angle B, Troxell R, Gorski JL, Westemeyer M, Frydman M, Senturias Y, Earl D, Torchia B, Schultz RA, Ellison JW, Tsuchiya K, Zimmerman S, Smolarek TA, Ballif BC, Shaffer LG. Further Evidence of Contrasting Phenotypes Caused by Reciprocal Deletions and Duplications: Duplication of NSD1 Causes Growth Retardation and Microcephaly. Mol Syndromol 2013; 3:247-54. [PMID: 23599694 DOI: 10.1159/000345578] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/29/2012] [Indexed: 12/15/2022] Open
Abstract
Microduplications of the Sotos syndrome region containing NSD1 on 5q35 have recently been proposed to cause a syndrome of microcephaly, short stature and developmental delay. To further characterize this emerging syndrome, we report the clinical details of 12 individuals from 8 families found to have interstitial duplications involving NSD1, ranging in size from 370 kb to 3.7 Mb. All individuals are microcephalic, and height and childhood weight range from below average to severely restricted. Mild-to-moderate learning disabilities and/or developmental delay are present in all individuals, including carrier family members of probands; dysmorphic features and digital anomalies are present in a majority. Craniosynostosis is present in the individual with the largest duplication, though the duplication does not include MSX2, mutations of which can cause craniosynostosis, on 5q35.2. A comparison of the smallest duplication in our cohort that includes the entire NSD1 gene to the individual with the largest duplication that only partially overlaps NSD1 suggests that whole-gene duplication of NSD1 in and of itself may be sufficient to cause the abnormal growth parameters seen in these patients. NSD1 duplications may therefore be added to a growing list of copy number variations for which deletion and duplication of specific genes have contrasting effects on body development.
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Affiliation(s)
- J A Rosenfeld
- Signature Genomic Laboratories, PerkinElmer, Inc., Spokane, Wash., USA
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23
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Traylor RN, Dobyns WB, Rosenfeld JA, Wheeler P, Spence JE, Bandholz AM, Bawle EV, Carmany EP, Powell CM, Hudson B, Schultz RA, Shaffer LG, Ballif BC. Investigation of TBR1 Hemizygosity: Four Individuals with 2q24 Microdeletions. Mol Syndromol 2012; 3:102-112. [PMID: 23112752 DOI: 10.1159/000342008] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/13/2012] [Indexed: 12/19/2022] Open
Abstract
TBR1 encodes a transcription factor with critical roles in corticogenesis, including cortical neuron migration and axon pathfinding, establishment of regional and laminar identity of cortical neurons, and control of glutamatergic neuronal cell fate. Based upon TBR1's role in cortical development, we sought to investigate TBR1 hemizygosity in individuals referred for genetic evaluation of intellectual disability and developmental delay. We describe 4 patients with microdeletions identified by molecular cytogenetic techniques, encompassing TBR1 and spanning 2q24.1q31.1, ranging in size from 2.17 to 12.34 Mb. Only the patient with the largest deletion had a possible cortical malformation. Mild ventriculomegaly is the only common brain anomaly, present in all patients; a Chiari I malformation is seen in 2 patients, and mega cisterna magna is seen in a third. Our findings are consistent with Tbr1 mouse models showing that hemizygosity of the gene requires additional genetic factors for the manifestation of severe structural brain malformations. Other syndromic features are present in these patients, including autism spectrum disorders, ocular colobomas, and craniosynostosis, features that are likely affected by the deletion of genes other than TBR1.
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Affiliation(s)
- R N Traylor
- Signature Genomic Laboratories, PerkinElmer Inc., Spokane, Wash., USA
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24
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Abstract
Data from the 1000 genomes project (1KGP) and Complete Genomics (CG) have dramatically increased the numbers of known genetic variants and challenge several assumptions about the reference genome and its uses in both clinical and research settings. Specifically, 34% of published array-based GWAS studies for a variety of diseases utilize probes that overlap unanticipated single nucleotide polymorphisms (SNPs), indels, or structural variants. Linkage disequilibrium (LD) block length depends on the numbers of markers used, and the mean LD block size decreases from 16 kb to 7 kb,when HapMap-based calculations are compared to blocks computed from1KGP data. Additionally, when 1KGP and CG variants are compared, 19% of the single nucleotide variants (SNVs) reported from common genomes are unique to one dataset; likely a result of differences in data collection methodology, alignment of reads to the reference genome, and variant-calling algorithms. Together these observations indicate that current research resources and informatics methods do not adequately account for the high level of variation that already exists in the human population and significant efforts are needed to create resources that can accurately assess personal genomics for health, disease, and predict treatment outcomes.
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Affiliation(s)
- Jeffrey A. Rosenfeld
- Division of High Performance and Research Computing, University of Medicine & Dentistry of New Jersey, Newark, New Jersey, United States of America
- American Museum of Natural History, Sackler Institute for Comparative Genomics, New York, New York, United States of America
| | - Christopher E. Mason
- Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York, United States of America
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, New York, New York, United States of America
| | - Todd M. Smith
- PerkinElmer, Seattle, Washington, United States of America
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25
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MacArthur DG, Balasubramanian S, Frankish A, Huang N, Morris J, Walter K, Jostins L, Habegger L, Pickrell JK, Montgomery SB, Albers CA, Zhang ZD, Conrad DF, Lunter G, Zheng H, Ayub Q, DePristo MA, Banks E, Hu M, Handsaker RE, Rosenfeld JA, Fromer M, Jin M, Mu XJ, Khurana E, Ye K, Kay M, Saunders GI, Suner MM, Hunt T, Barnes IHA, Amid C, Carvalho-Silva DR, Bignell AH, Snow C, Yngvadottir B, Bumpstead S, Cooper DN, Xue Y, Romero IG, Wang J, Li Y, Gibbs RA, McCarroll SA, Dermitzakis ET, Pritchard JK, Barrett JC, Harrow J, Hurles ME, Gerstein MB, Tyler-Smith C. A systematic survey of loss-of-function variants in human protein-coding genes. Science 2012; 335:823-8. [PMID: 22344438 PMCID: PMC3299548 DOI: 10.1126/science.1215040] [Citation(s) in RCA: 869] [Impact Index Per Article: 72.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies.
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Rosenfeld JA, DeSalle R. E value cutoff and eukaryotic genome content phylogenetics. Mol Phylogenet Evol 2012; 63:342-50. [PMID: 22306824 DOI: 10.1016/j.ympev.2012.01.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2011] [Revised: 01/02/2012] [Accepted: 01/03/2012] [Indexed: 10/14/2022]
Abstract
Genome content analysis has been used as a source of phylogenetic information in large prokaryotic tree of life studies. Recently the sequencing of many eukaryotic genomes has allowed for the similar use of genome content analysis for these organisms too. In this communication we examine the utility of genome content analysis for recovering phylogenetic patterns in several eukaryotic groups. By constructing multiple matrices using different e value cutoffs we examine the dynamics of altering the e value cutoff on five eukaryotic genome data sets. Our analysis indicates that the e value cutoff that is used as a criterion in the construction of the genome content matrix is a critical factor in both the accuracy and information content of the analysis. Strikingly, genome content by itself is not a reliable or accurate source of characters for phylogenetic analysis of the taxa in the five data sets we analyzed. We discuss two problems--small genome attraction and genome duplications as being involved in the rather poor performance of genome content data in recovering eukaryotic phylogeny.
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Affiliation(s)
- Jeffrey A Rosenfeld
- IST/High Performance and Research Computing, University of Medicine and Dentistry of New Jersey, Newark, NJ 07103, United States.
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Guha S, Rosenfeld JA, Malhotra AK, Lee AT, Gregersen PK, Kane JM, Pe'er I, Darvasi A, Lencz T. Implications for health and disease in the genetic signature of the Ashkenazi Jewish population. Genome Biol 2012; 13:R2. [PMID: 22277159 PMCID: PMC3334583 DOI: 10.1186/gb-2012-13-1-r2] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2011] [Revised: 01/13/2012] [Accepted: 01/25/2012] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Relatively small, reproductively isolated populations with reduced genetic diversity may have advantages for genomewide association mapping in disease genetics. The Ashkenazi Jewish population represents a unique population for study based on its recent (< 1,000 year) history of a limited number of founders, population bottlenecks and tradition of marriage within the community. We genotyped more than 1,300 Ashkenazi Jewish healthy volunteers from the Hebrew University Genetic Resource with the Illumina HumanOmni1-Quad platform. Comparison of the genotyping data with that of neighboring European and Asian populations enabled the Ashkenazi Jewish-specific component of the variance to be characterized with respect to disease-relevant alleles and pathways. RESULTS Using clustering, principal components, and pairwise genetic distance as converging approaches, we identified an Ashkenazi Jewish-specific genetic signature that differentiated these subjects from both European and Middle Eastern samples. Most notably, gene ontology analysis of the Ashkenazi Jewish genetic signature revealed an enrichment of genes functioning in transepithelial chloride transport, such as CFTR, and in equilibrioception, potentially shedding light on cystic fibrosis, Usher syndrome and other diseases over-represented in the Ashkenazi Jewish population. Results also impact risk profiles for autoimmune and metabolic disorders in this population. Finally, residual intra-Ashkenazi population structure was minimal, primarily determined by class 1 MHC alleles, and not related to host country of origin. CONCLUSIONS The Ashkenazi Jewish population is of potential utility in disease-mapping studies due to its relative homogeneity and distinct genomic signature. Results suggest that Ashkenazi-associated disease genes may be components of population-specific genomic differences in key functional pathways.
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Affiliation(s)
- Saurav Guha
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore - Long Island Jewish Health System, 75-59, 263rd St Glen Oaks, NY 11004, USA
| | - Jeffrey A Rosenfeld
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore - Long Island Jewish Health System, 75-59, 263rd St Glen Oaks, NY 11004, USA
| | - Anil K Malhotra
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore - Long Island Jewish Health System, 75-59, 263rd St Glen Oaks, NY 11004, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA
- Department of Psychiatry and Behavioral Science, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Ave, Bronx, NY 10461, USA
- Department of Psychiatry, Hofstra University School of Medicine, Hempstead, NY 11549, USA
- Department of Molecular Medicine, Hofstra University School of Medicine, Hempstead, NY 11549, USA
| | - Annette T Lee
- Robert S Boas Center for Human Genetics and Genomics, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA
| | - Peter K Gregersen
- Department of Molecular Medicine, Hofstra University School of Medicine, Hempstead, NY 11549, USA
- Robert S Boas Center for Human Genetics and Genomics, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA
| | - John M Kane
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore - Long Island Jewish Health System, 75-59, 263rd St Glen Oaks, NY 11004, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA
- Department of Psychiatry and Behavioral Science, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Ave, Bronx, NY 10461, USA
- Department of Psychiatry, Hofstra University School of Medicine, Hempstead, NY 11549, USA
- Department of Molecular Medicine, Hofstra University School of Medicine, Hempstead, NY 11549, USA
| | - Itsik Pe'er
- Department of Computer Science, Columbia University, 500 W 120th St New York, NY 10027, USA
| | - Ariel Darvasi
- Department of Genetics The Institute of Life Sciences, The Hebrew University of Jerusalem, Givat Ram, Jerusalem, 91904, Israel
| | - Todd Lencz
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of the North Shore - Long Island Jewish Health System, 75-59, 263rd St Glen Oaks, NY 11004, USA
- Center for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, 350 Community Drive, Manhasset, NY 11030, USA
- Department of Psychiatry and Behavioral Science, Albert Einstein College of Medicine of Yeshiva University, 1300 Morris Park Ave, Bronx, NY 10461, USA
- Department of Psychiatry, Hofstra University School of Medicine, Hempstead, NY 11549, USA
- Department of Molecular Medicine, Hofstra University School of Medicine, Hempstead, NY 11549, USA
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Kurt Lienau E, DeSalle R, Allard M, Brown EW, Swofford D, Rosenfeld JA, Sarkar IN, Planet PJ. The mega-matrix tree of life: using genome-scale horizontal gene transfer and sequence evolution data as information about the vertical history of life. Cladistics 2011; 27:417-427. [PMID: 34875790 DOI: 10.1111/j.1096-0031.2010.00337.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Because horizontal gene transfer can confound the recovery of the largely prokaryotic tree of life (ToL), most genome-based techniques seek to eliminate horizontal signal from ToL analyses, commonly by sieving out incongruent genes and data. This approach greatly limits the number of gene families analysed to a subset thought to be representative of vertical evolutionary history. However, formalized tests have not been performed to determine whether combining the massive amounts of information available in fully sequenced genomes can recover a reasonable ToL. Consequently, we used empirically defined gene homology definitions from a previous study that delineate xenologous gene families (gene families derived from a common transfer event) to generate a massively concatenated, combined-data ToL matrix derived from 323 404 translated open reading frames arranged into 12 381 gene homologue groups coded as amino acid data and 63 336, 64 105, 65 153, 66 922 and 67 109 gene homologue groups coded as gene presence/absence data for 166 fully sequenced genomes. This whole-genome gene presence/absence and amino acid sequence ToL data matrix is composed of 4867 184 characters (a combined data-type mega-matrix). Phylogenetic analysis of this mega-matrix yielded a fully resolved ToL that classifies all three commonly accepted domains of life as monophyletic and groups most taxa in traditionally recognized locations with high support. Most importantly, these results corroborate the existence of a common evolutionary history for these taxa present in both data types that is evident only when these data are analysed in combination. © The Willi Hennig Society 2010.
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Affiliation(s)
- E Kurt Lienau
- Sackler Institute for Comparative Genomics, American Museum of Natural History, Central Park West at 79th St, New York, NY 10024, USA.,Department of Biology, Graduate School of Arts and Science, New York University, 100 Washington Square East, New York, NY 10003, USA.,Division of Microbiology, Center for Food Safety and Nutrition, Food and Drug Administration, 5100 Paint Branch Parkway, College Park, MD 20740, USA
| | - Rob DeSalle
- Sackler Institute for Comparative Genomics, American Museum of Natural History, Central Park West at 79th St, New York, NY 10024, USA
| | - Marc Allard
- Division of Microbiology, Center for Food Safety and Nutrition, Food and Drug Administration, 5100 Paint Branch Parkway, College Park, MD 20740, USA
| | - Eric W Brown
- Division of Microbiology, Center for Food Safety and Nutrition, Food and Drug Administration, 5100 Paint Branch Parkway, College Park, MD 20740, USA
| | - David Swofford
- Duke Institute for Genomes and Science Policy, 366 BioSci, Duke University, Durham, NC 27708, USA
| | - Jeffrey A Rosenfeld
- Department of Biology, Graduate School of Arts and Science, New York University, 100 Washington Square East, New York, NY 10003, USA
| | - Indra N Sarkar
- Marine Biological Laboratory, 7 MBL Street, Woods Hole, MA 02543, USA
| | - Paul J Planet
- Sackler Institute for Comparative Genomics, American Museum of Natural History, Central Park West at 79th St, New York, NY 10024, USA.,Department of Pediatrics, Children's Hospital of New York, Columbia University, College of Physicians and Surgeons, New York, NY 10032, USA
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Theisen A, Rosenfeld JA, Shane K, McBride KL, Atkin JF, Gaba C, Hoo J, Kurczynski TW, Schnur RE, Coffey LB, Zackai EH, Schimmenti L, Friedman N, Zabukovec M, Ball S, Pagon R, Lucas A, Brasington CK, Spence JE, Sparks S, Banks V, Smith W, Friedberg T, Wyatt PR, Aust M, Tervo R, Crowley A, Skidmore D, Lamb AN, Ravnan B, Sahoo T, Schultz R, Torchia BS, Sgro M, Chitayat D, Shaffer LG. Refinement of the Region for Split Hand/Foot Malformation 5 on 2q31.1. Mol Syndromol 2011; 1:262-271. [PMID: 22140379 DOI: 10.1159/000328405] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/04/2011] [Indexed: 12/23/2022] Open
Abstract
Background: Deletions that encompass 2q31.1 have been proposed as a microdeletion syndrome with common clinical features, including intellectual disability/developmental delay, microcephaly, cleft palate, growth delay, and hand/foot anomalies. In addition, several genes within this region have been proposed as candidates for split hand-foot malformation 5 (SHFM5). Methods: To delineate the genotype-phenotype correlation between deletions of this region, we identified 14 individuals with deletions at 2q31.1 detected by microarray analysis for physical and developmental disabilities. Results: All subjects for whom detailed clinical records were available had neurological deficits of varying degree. Seven subjects with deletions encompassing the HOXD cluster had hand/foot anomalies of varying severity, including syndactyly, brachydactyly, and ectrodactyly. Of 7 subjects with deletions proximal to the HOXD cluster, 5 of which encompassed DLX1/DLX2, none had clinically significant hand/foot anomalies. In contrast to previous reports, the individuals in our study did not display a characteristic gestalt of dysmorphic facial features. Conclusion: The absence of hand/foot anomalies in any of the individuals with deletions of DLX1/DLX2 but not the HOXD cluster supports the hypothesis that haploinsufficiency of the HOXD cluster, rather than DLX1/DLX2, accounts for the skeletal abnormalities in subjects with 2q31.1 microdeletions.
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Affiliation(s)
- A Theisen
- Signature Genomic Laboratories, Spokane, Wash
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Williams PG, Wetherbee JJ, Rosenfeld JA, Hersh JH. 20p11 deletion in a female child with panhypopituitarism, cleft lip and palate, dysmorphic facial features, global developmental delay and seizure disorder. Am J Med Genet A 2011; 155A:186-91. [PMID: 21204230 DOI: 10.1002/ajmg.a.33763] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Deletions of 20p are rare with the majority of reported cases involving individuals with 20p12 deletions associated with Alagille syndrome. We report on a child with a de novo mosaic 20p11 deletion who presents with panhypopituitarism; hypoplastic pituitary gland and ectopic posterior pituitary gland on MRI of the brain; cleft lip and palate; kyphosis with anterior beaking of L1 and L2 vertebral bodies; pulmonic stenosis; dysmorphic facial features including flat nasal bridge, hypoplastic premaxilla, hypotelorism, preauricular pit, and cupped ears; seizure disorder; variable muscle tone; and global developmental delay. Array comparative genomic hybridization revealed this deletion to be approximately 5.4 Mb in size, containing 35 genes. Previously, an infant with 20p11.22 deletion who had panhypopituitarism, craniofacial, and genital abnormalities was reported, but the precise parameters of that deletion are unavailable. Several other reported cases of 20p11 deletions also have phenotypic overlap with our case. The similarities in clinical features of these patients suggest that the genes at 20p11 have a critical role in development of midline brain structures.
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Affiliation(s)
- P G Williams
- Department of Pediatrics, University of Louisville, Kentucky.
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Balasubramanian M, Smith K, Basel-Vanagaite L, Feingold MF, Brock P, Gowans GC, Vasudevan PC, Cresswell L, Taylor EJ, Harris CJ, Friedman N, Moran R, Feret H, Zackai EH, Theisen A, Rosenfeld JA, Parker MJ. Case series: 2q33.1 microdeletion syndrome--further delineation of the phenotype. J Med Genet 2011; 48:290-8. [PMID: 21343628 DOI: 10.1136/jmg.2010.084491] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
Recurrent deletions of 2q32q33 have recently been reported as a new microdeletion syndrome, clinical features of which include significant learning difficulties, growth retardation, dysmorphic features, thin and sparse hair, feeding difficulties, and cleft or high palate. Haploinsufficiency of one gene within the deleted region, SATB2, has been suggested to be responsible for most of the features of the syndrome. This article describes seven previously unreported patients with deletions at 2q33.1, all partially overlapping the previously described critical region for the 2q33.1 microdeletion syndrome. The deletions ranged in size from 35 kb to 10.4 Mb, with the smallest deletion entirely within the SATB2 gene. Patients demonstrated significant developmental delay and challenging behaviour, a particular behavioural phenotype that seems to be emerging with more reported patients with this condition. One patient in this cohort has a deletion entirely within SATB2 and has a cleft palate, whereas several patients with larger deletions have a high arched palate. In addition, one other patient has significant orthopaedic problems with ligamentous laxity. Interestingly, this patient has a deletion that lies just distal to SATB2. The orthopaedic problems have not been reported previously and are possibly an additional feature of this syndrome. Overall, this report provides further evidence that the SATB2 gene is the critical gene in this microdeletion syndrome. In addition, because the individuals in this study range in age from 3-19 years, these patients will help define the natural progression of the phenotype in patients with this microdeletion.
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Affiliation(s)
- M Balasubramanian
- Sheffield Clinical Genetics Service, Sheffield NHS Foundation Trust, Western Bank, Sheffield S10 2TH, UK.
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Rosenfeld JA, Malhotra AK, Lencz T. Novel multi-nucleotide polymorphisms in the human genome characterized by whole genome and exome sequencing. Nucleic Acids Res 2010; 38:6102-11. [PMID: 20488869 PMCID: PMC2952858 DOI: 10.1093/nar/gkq408] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Genomic sequence comparisons between individuals are usually restricted to the analysis of single nucleotide polymorphisms (SNPs). While the interrogation of SNPs is efficient, they are not the only form of divergence between genomes. In this report, we expand the scope of polymorphism detection by investigating the occurrence of double nucleotide polymorphisms (DNPs) and triple nucleotide polymorphisms (TNPs), in which two or three consecutive nucleotides are altered compared to the reference sequence. We have found such DNPs and TNPs throughout two complete genomes and eight exomes. Within exons, these novel polymorphisms are over-represented amongst protein-altering variants; nearly all DNPs and TNPs result in a change in amino acid sequence and, in some cases, two adjacent amino acids are changed. DNPs and TNPs represent a potentially important new source of genetic variation which may underlie human disease and they should be included in future medical genetics studies. As a confirmation of the damaging nature of xNPs, we have identified changes in the exome of a glioblastoma cell line that are important in glioblastoma pathogenesis. We have found a TNP causing a single amino acid change in LAMC2 and a TNP causing a truncation of HUWE1.
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Affiliation(s)
- Jeffrey A Rosenfeld
- Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Glen Oaks, NY, USA.
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Abstract
Most histone modifications can easily be characterized as either activating or repressive. For example, histone3, lysine 4 trimethylation (H3K4me3) is generally considered a distinct sign of actively transcribed promoters while H3K27me3 is generally found at repressed genes. This is not the case for H3K9me3, the subject of this communication, which is a modification that has traditionally been considered a mark of constitutive heterochromatin, but has also been found in significant levels in expressed genes. We therefore sought to use new high-throughput genome-wide maps of H3K9me3 localization to investigate the conflicting hypotheses concerning the nature of this modification. Before we could accurately analyze the locations of H3K9me3 along the genome, and especially in repetitive locations, we developed a method for accurately utilizing short sequencing reads that do not map uniquely to a location in the genome. Investigating the locations of H3K9me3 along the genome allowed us to determine that, while there are high levels of H3K9me3 outside of genes, this modification is not absent from genes. Therefore, we suggest that H3K9me3 may have a role in chromatin organization rather than being directly related to gene expression. In addition, we have found that there is a need to include repetitively matching reads in any high-throughput sequencing experiment.
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Affiliation(s)
- Jeffrey A Rosenfeld
- Zucker Hillside Hospital, North Shore-Long Island Jewish Health System, Glen Oaks, NY, USA.
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Rosenfeld JA, Wang Z, Schones DE, Zhao K, DeSalle R, Zhang MQ. Determination of enriched histone modifications in non-genic portions of the human genome. BMC Genomics 2009; 10:143. [PMID: 19335899 PMCID: PMC2667539 DOI: 10.1186/1471-2164-10-143] [Citation(s) in RCA: 157] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2008] [Accepted: 03/31/2009] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) has recently been used to identify the modification patterns for the methylation and acetylation of many different histone tails in genes and enhancers. RESULTS We have extended the analysis of histone modifications to gene deserts, pericentromeres and subtelomeres. Using data from human CD4+ T cells, we have found that each of these non-genic regions has a particular profile of histone modifications that distinguish it from the other non-coding regions. Different methylation states of H4K20, H3K9 and H3K27 were found to be enriched in each region relative to the other regions. These findings indicate that non-genic regions of the genome are variable with respect to histone modification patterns, rather than being monolithic. We furthermore used consensus sequences for unassembled centromeres and telomeres to identify the significant histone modifications in these regions. Finally, we compared the modification patterns in non-genic regions to those at silent genes and genes with higher levels of expression. For all tested methylations with the exception of H3K27me3, the enrichment level of each modification state for silent genes is between that of non-genic regions and expressed genes. For H3K27me3, the highest levels are found in silent genes. CONCLUSION In addition to the histone modification pattern difference between euchromatin and heterochromatin regions, as is illustrated by the enrichment of H3K9me2/3 in non-genic regions while H3K9me1 is enriched at active genes; the chromatin modifications within non-genic (heterochromatin-like) regions (e.g. subtelomeres, pericentromeres and gene deserts) are also quite different.
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Rosenfeld JA, DeSalle R, Lee EK, O'Grady P. Using whole genome presence/absence data to untangle function in 12 Drosophila genomes. Fly (Austin) 2008; 2:291-9. [PMID: 19139635 DOI: 10.4161/fly.7481] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The Drosophila 12 genome data set was used to construct whole genome, gene family presence/absence matrices using a broad range of E value cutoffs as criteria for gene family inclusion. The various matrices generated behave differently in phylogenetic analyses as a function of the e-value employed. Based on an optimality criterion that maximizes internal corroboration of information, we show that values of e(-105) to e(-125) extract the most internally consistent phylogenetic signal. Functional class of most genes and gene families can be accurately determined based on the D. melanogaster genome annotation. We used the gene ontology (GO) system to create partitions based on gene function. Several measures of phylogenetic congruence (diagnosis, consistency, partitioned support, hidden support) for different higher and lower level GO categories, were used to mine the data set for genes and gene families that show strong agreement or disagreement with the overall combined phylogenetic hypothesis. We propose that measures of phylogenetic congruence can be used as criteria to identify loci with related GO terms that have a significant impact on cladogenesis.
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Wang Z, Zang C, Rosenfeld JA, Schones DE, Barski A, Cuddapah S, Cui K, Roh TY, Peng W, Zhang MQ, Zhao K. Combinatorial patterns of histone acetylations and methylations in the human genome. Nat Genet 2008; 40:897-903. [PMID: 18552846 DOI: 10.1038/ng.154] [Citation(s) in RCA: 1669] [Impact Index Per Article: 104.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2007] [Accepted: 04/01/2008] [Indexed: 12/11/2022]
Abstract
Histones are characterized by numerous posttranslational modifications that influence gene transcription. However, because of the lack of global distribution data in higher eukaryotic systems, the extent to which gene-specific combinatorial patterns of histone modifications exist remains to be determined. Here, we report the patterns derived from the analysis of 39 histone modifications in human CD4(+) T cells. Our data indicate that a large number of patterns are associated with promoters and enhancers. In particular, we identify a common modification module consisting of 17 modifications detected at 3,286 promoters. These modifications tend to colocalize in the genome and correlate with each other at an individual nucleosome level. Genes associated with this module tend to have higher expression, and addition of more modifications to this module is associated with further increased expression. Our data suggest that these histone modifications may act cooperatively to prepare chromatin for transcriptional activation.
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Affiliation(s)
- Zhibin Wang
- Laboratory of Molecular Immunology, National Heart, Lung, and Blood Institute, US National Institutes of Health, Bethesda, Maryland 20892, USA
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Abstract
Phylogenies based on gene content rely on statements of primary homology to characterize gene presence or absence. These statements (hypotheses) are usually determined by techniques based on threshold similarity or distance measurements between genes. This fundamental but problematic step can be examined by evaluating each homology hypothesis by the extent to which it is corroborated by the rest of the data. Here we test the effects of varying the stringency for making primary homology statements using a range of similarity (e-value) cutoffs in 166 fully sequenced and annotated genomes spanning the tree of life. By evaluating each resulting data set with tree-based measurements of character consistency and information content, we find a set of homology statements that optimizes overall corroboration. The resulting data set produces well-resolved and well-supported trees of life and greatly ameliorates previously noted inconsistencies such as the misclassification of small genomes. The method presented here, which can be used to test any technique for recognizing primary homology, provides an objective framework for evaluating phylogenetic hypotheses and data sets for the tree of life. It also can serve as a technique for identifying well-corroborated sets of homologous genes for functional genomic applications.
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Affiliation(s)
- E Kurt Lienau
- American Museum of Natural History, Molecular Laboratories, Central Park West at 79th Street, (P.J.P.), New York, New York 10024, USA
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Abstract
UNLABELLED The ability to detect clusters of functionally related genes in multiple microbial genomes has enormous potential for enhancing studies on gene function and microbial evolution. The staggering amount of new genome sequence data presents a largely untapped resource for gene cluster discovery. To date, gene cluster analysis has not been fully automated, and one must rely on manual, tedious and time-consuming manipulation of sequences. To facilitate accurate and rapid identification of conserved gene clusters, we developed a database-driven web application, called ORFcurator. We used ORFcurator to find clusters containing any genes similar to those of the 14-gene Widespread Colonization Island of Actinobacillus actinomycetemcomitans. From 126 genomes, ORFcurator identified all 73 clusters previously determined by manual searching. AVAILABILITY ORFcurator and all associated scripts are freely available as supplementary information. SUPPLEMENTARY INFORMATION http://www.genomecurator.org/ORFcurator/
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Affiliation(s)
- Jeffrey A Rosenfeld
- Division of Invertebrate Zoology, Central Park West, 79th Street, American Museum of Natural History, New York, NY 10024, USA
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Kaneshiro ES, Rosenfeld JA, Basselin M, Bradshaw S, Stringer JR, Smulian AG, Giner JL. Pneumocystis carinii erg6 gene: sequencing and expression of recombinant SAM:sterol methyltransferase in heterologous systems. J Eukaryot Microbiol 2002; Suppl:144S-146S. [PMID: 11906033 DOI: 10.1111/j.1550-7408.2001.tb00491.x] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- E S Kaneshiro
- Department of Biological Sciences, University of Cincinnati, OH, USA.
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Peña KS, Rosenfeld JA. Evaluation and treatment of galactorrhea. Am Fam Physician 2001; 63:1763-70. [PMID: 11352287] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/16/2023]
Abstract
Galactorrhea, or inappropriate lactation, is a relatively common problem that occurs in approximately 20 to 25 percent of women. Lactation requires the presence of estrogen, progesterone and, most importantly, prolactin. Stress, suckling, sleep, sexual intercourse and medications may increase prolactin levels, whereas dopamine inhibits its release. The differential diagnosis of galactorrhea includes pituitary adenomas, neurologic disorders, hypothyroidism, numerous medications, breast stimulation, chest wall irritation and physiologic causes. The evaluation includes a thorough history and physical examination, as well as selected laboratory and imaging studies to rule out secondary causes such as an intracranial mass or a tumor. Diagnostic studies include a pregnancy test, a prolactin level, renal and thyroid function tests and, if indicated, magnetic resonance imaging of the brain. Treatment options for prolactinomas include observation, dopamine agonists, surgery and radiation therapy, depending on tumor size and associated symptoms. Fortunately, the prognosis for patients with prolactinomas is good: most prolactinomas remain stable or regress. In pregnant women, prolactinomas must be observed closely because the lesions may greatly increase in size.
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Affiliation(s)
- K S Peña
- Department of Family Practice, Franklin Square Hospital, Baltimore, Maryland 21237, USA.
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Rosenfeld JA, Everett K. Teenage women's use of contraceptives in two populations. J Am Board Fam Pract 2001; 14:1-6. [PMID: 11206688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
BACKGROUND Adolescent patterns of contraceptive use might be different in various populations and might have changed in the last 30 years. More appropriate use of contraception could prevent unplanned pregnancy. METHODS We interviewed 378 women in rural East Tennessee and 396 women in suburban-urban Baltimore, all of whom were aged 18 to 50 years, in a convenience sampling about their memories of sexual experiences and early contraceptive use. RESULTS First sexual experiences began at a younger age in women from Tennessee than in women from Baltimore. Sexual experiences occurred at an earlier age during the last 15 years in Baltimore women. Contraceptive use at first sexual experience has approximately doubled in both locations, from 7% to 15% in Tennessee and from 42% to 75% in Baltimore during the last 15 years. The primary reason in Baltimore is increased use of condoms. Condom use in Tennessee is very low. CONCLUSIONS These two populations are using contraception and condoms differently. Although the two populations are diverse, it could help physicians to learn about the particular contraceptive practices of their patient population to help their patients more appropriately with their contraceptive needs.
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Affiliation(s)
- J A Rosenfeld
- Franklin Square Family Practice, Baltimore, MD 21237, USA
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Rosenfeld JA. Can the prophylactic use of raloxifene, a selective estrogen-receptor modulator, prevent bone mineral loss and fractures in women with diagnosed osteoporosis or vertebral fractures? West J Med 2000; 173:186-8. [PMID: 10986186 PMCID: PMC1071083 DOI: 10.1136/ewjm.173.3.186-a] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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Abstract
For decades, coronary artery disease (CAD) was thought to be primarily a disease of middle-aged men, in whom most research was conducted. But CAD afflicts a diverse patient population, and a major subset of those patients--women--present special diagnostic and therapeutic challenges for the primary care physician. In this article, Dr Rosenfeld provides an overview of CAD in women and discusses its causes and risk factors, prevention strategies, and gender-specific characteristics. She also examines the effect of gender-biased research on the views of both patients and physicians.
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Affiliation(s)
- J A Rosenfeld
- Franklin Square Hospital Center, Baltimore, MD, USA.
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Rosenfeld JA. Annual physical examination for adolescents: a reassessment. J Am Board Fam Pract 2000; 13:224-5. [PMID: 10826875 DOI: 10.3122/15572625-13-3-224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Rosenfeld JA, Square F. Family practice and its midlife crisis. Fam Med 2000; 32:7. [PMID: 10645505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
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Rosenfeld JA. The natural history of Pap test screening in a rural population. Tenn Med 1998; 91:179-82. [PMID: 9584605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- J A Rosenfeld
- Bristol Family Practice Center, James H. Quillen College of Medicine, East Tennessee State University 37620, USA
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Abstract
Acute otitis media (AOM) is the most common reason parents bring children into the primary care physician's office. It is diagnosed by clinical symptoms of otalgia and often fever and irritability and by clinical otoscopy. Organisms common to the nasopharynx usually cause AOM. Many episodes of AOM resolve spontaneously. Because it is uncertain how many and which children will resolve without therapy, it is reasonable to treat all children with AOM with antibiotics. The first choice of antibiotics is amoxicillin. Other choices rest on a variety of factors.
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Affiliation(s)
- J A Rosenfeld
- East Tennessee State University James H. Quillen College of Medicine, Bristol, Tennessee 37620, USA
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Rosenfeld JA. Chronic pelvic pain: an integrated approach. Am Fam Physician 1996; 54:2187-8, 2193. [PMID: 8967320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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Rosenfeld JA, Zaborlik PM. Comparison of female and male graduates of southern Appalachian family practice residencies. Tenn Med 1996; 89:407-409. [PMID: 8942278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
Abstract
PURPOSE One aim of Southern Appalachian family practice residencies is to produce graduates for surrounding physician-needy areas. Some evidence suggests that women are less likely to go to rural areas and that they practice differently than men. This study investigated the practice patterns and location of Appalachian family practice residency female and male graduates. METHODS Surveys were sent to graduates of seven family practice residencies from 1984 to 1994 in the Southern Appalachian area to determine practice patterns, locations, and reasons for choosing practices. RESULTS Women were more likely than men to be single and not to have children. More women worked part-time. Women's and men's practice patterns and characteristics were similar except that women were more likely to provide prenatal care and do vaginal deliveries. Women in similar percentages practiced in small towns, and a greater percentage of women practiced in rural areas with populations of less than 2,500. CONCLUSIONS Female family practice residency graduates from Appalachian residencies are fulfilling the purposes of their residencies as well as male graduates, although more of them are working part-time.
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Affiliation(s)
- J A Rosenfeld
- Bristol Family Practice Residency, East Tennessee State University, Tenn, USA
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Rosenfeld JA. How should we measure competence. Fam Med 1996; 28:610. [PMID: 8909958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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