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Tobias J, Cunningham A, Krakauer K, Nacharaju D, Moss L, Galindo C, Roberts M, Hamilton NA, Olsen K, Emmons M, Quackenbush J, Schreiber MA, Burns BS, Sheridan D, Hoffman B, Gallardo A, Jafri MA. Protect Our Kids: a novel program bringing hemorrhage control to schools. Inj Epidemiol 2021; 8:31. [PMID: 34517905 PMCID: PMC8436006 DOI: 10.1186/s40621-021-00318-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 02/24/2021] [Accepted: 03/09/2021] [Indexed: 11/15/2022] Open
Abstract
Background Following the shooting at Sandy Hook Elementary School, the Hartford Consensus produced the Stop the Bleed program to train bystanders in hemorrhage control. In our region, the police bureau delivers critical incident training to public schools, offering instruction in responding to violent or dangerous situations. Until now, widespread training in hemorrhage control has been lacking. Our group developed, implemented and evaluated a novel program integrating hemorrhage control into critical incident training for school staff in order to blunt the impact of mass casualty events on children. Methods The staff of 25 elementary and middle schools attended a 90-minute course incorporating Stop the Bleed into the critical incident training curriculum, delivered on-site by police officers, nurses and doctors over a three-day period. The joint program was named Protect Our Kids. At the conclusion of the course, hemorrhage control kits and educational materials were provided and a four-question survey to assess the quality of training using a ten-point Likert scale was completed by participants and trainers. Results One thousand eighteen educators underwent training. A majority were teachers (78.2%), followed by para-educators (5.8%), counselors (4.4%) and principals (2%). Widely covered by local and state media, the Protect Our Kids program was rated as excellent and effective by a majority of trainees and all trainers rated the program as excellent. Conclusions Through collaboration between trauma centers, police and school systems, a large-scale training program for hemorrhage control and critical incident response can be effectively delivered to schools.
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Affiliation(s)
- Joseph Tobias
- Department of Surgery, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA.
| | - Aaron Cunningham
- Department of Surgery, Oregon Health & Science University, 3181 SW Sam Jackson Park Rd, Portland, OR, 97239, USA
| | - Kelsi Krakauer
- School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Deepthi Nacharaju
- School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Lori Moss
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Science University, Portland, OR, USA
| | | | | | - Nicholas A Hamilton
- Department of Surgery, Division of Pediatric Surgery, Oregon Health & Science University, Portland, OR, USA
| | - Kyle Olsen
- Portland Public Schools, Portland, OR, USA
| | | | | | - Martin A Schreiber
- Division of Trauma, Critical Care and Acute Care Surgery, Department of Surgery, Oregon Health & Science University, Portland, OR, USA
| | - Beech S Burns
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Science University, Portland, OR, USA.,Department of Emergency Medicine, Oregon Health & Science University, Portland, OR, USA
| | - David Sheridan
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Science University, Portland, OR, USA.,Department of Emergency Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Benjamin Hoffman
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Science University, Portland, OR, USA
| | - Adrienne Gallardo
- Department of Pediatrics, Doernbecher Children's Hospital, Oregon Health & Science University, Portland, OR, USA
| | - Mubeen A Jafri
- Department of Surgery, Division of Pediatric Surgery, Oregon Health & Science University, Portland, OR, USA.,Division of Pediatric Surgery, Randall Children's Hospital at Legacy Emanuel, Portland, OR, USA
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Abstract
SummaryTo review the current state of the art in computational methods for the analysis of DNA microarray data.The review considers methods of microarray data collection, transformation and representation, comparisons and predictions of gene expression from the data, their mechanistic analysis, related systems biology, and the application of clustering techniques.Functional genomics approaches have greatly increased the rate at which data on biological systems is generated, leading to corresponding challenges in analyzing the data through advanced computational techniques . The paper compares and contrasts the application of computational clustering for discovery, comparison, and prediction of gene expression classes, together with their evaluation and relation to mechanistic analyses of biological systems.Methods for assaying gene expression levels by DNA microarray experiments produce considerably more data than other techniques, and require a wide variety of computational techniques for identifying patterns of expression that may be biologically significant. These will have to be verified and validated by comparison to results from other methods, integrated with other systems data, and provide the feedback for further experimentation for testing mechanistic or other biological hypotheses.
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Domenyuk V, Gatalica Z, Santhanam R, Wei X, Stark A, Kennedy P, Toussaint B, Levenberg S, Wang R, Xiao N, Greil R, Rinnerthaler G, Gampenrieder S, Heimberger AB, Berry DJ, Barker A, Demetri GD, Quackenbush J, Marshall JL, Poste G, Vacirca JL, Vidal GA, Schwartzberg LS, Halbert DD, Voss A, Miglarese MR, Famulok M, Mayer G, Spetzler D. Abstract P2-09-09: Polyligand profiling differentiates cancer patients according to their benefit of treatment. Cancer Res 2018. [DOI: 10.1158/1538-7445.sabcs17-p2-09-09] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Introduction: Deconvolution of multi-nodal perturbations in cancer network architecture demands highly multiplexed profiling assays. We demonstrate the value of polyligand profiling of tumor systems states using libraries of single stranded oligodeoxynucleotides (ssODN) to distinguish between tumor tissue from breast cancer patients who did or did not derive benefit from treatment regimens containing trastuzumab.
Methods: This study included cases from women with invasive breast cancer who received chemotherapy+ trastuzumab (C+T) or trastuzumab monotherapy with available retrospective data on the time to next treatment (TTNT). A library of 2x1012 unique ssODN was exposed to FFPE tissues from patients who benefited (B) or not (NB) from trastuzumab-based regimens in several rounds of positive and negative selection. Two enriched libraries were screened on independent set of 42 B and 19 NB cases using a modified IHC protocol for detection of bound ssODNs. Poly-Ligand Profiles (PLP) were scored by a blinded pathologist. Two libraries, EL-NB and EL-B, showed significant p-values between groups of responders and non-responders. A Cox-PH model was fitted using either tumors' HER2 status or PLP test results as the independent variable. Median survival time was calculated from the Kaplan-Meier estimate. A separate group of 63 cases with TTNT data from chemotherapy without trastuzumab was used as a control to distinguish prognostic from predictive performance.
Results: The PLP scores of EL-NB and EL-B were assessed by receiver operating characteristic (ROC) curves and resulted in a combined AUC value of 0.81. EL-NB and EL-B were able to effectively classify B and NB patients with either HER2-negative/equivocal (AUC = 0.73) or HER2-positive cancers (AUC = 0.84). In contrast, HER2 status alone yielded an AUC value of 0.47. The combined PLP scores for the independent set of 63 patients treated with C excluding trastuzumab resulted in an AUC value of 0.53, indicating that the assay was predictive and not simply prognostic. Kaplan-Meier curves analysis shows that PLP+ cases have 429 days median TTNT, while PLP- cases have 129 days (HR = 0.38, log-rank p = 0.001). Analysis based on HER2 status showed no significant difference in TTNT between patients that were HER2+ (280 days) or HER2-negative/equivocal (336 days, HR = 1.27, log-rank p =0.45).
Summary: Performance of the PLP assay in differentiating patients who did or did not benefit from trastuzumab therapy outperforms the standard IHC assay for HER2 status. These results represent a promising step towards the development of a CDx to identify the 50-70% of HER2+ patients who will not benefit from trastuzumab. In addition, PLP also has the potential to identify the HER2-negative/equivocal patients who may benefit from trastuzumab-containing regimens.
Citation Format: Domenyuk V, Gatalica Z, Santhanam R, Wei X, Stark A, Kennedy P, Toussaint B, Levenberg S, Wang R, Xiao N, Greil R, Rinnerthaler G, Gampenrieder S, Heimberger AB, Berry DJ, Barker A, Demetri GD, Quackenbush J, Marshall JL, Poste G, Vacirca JL, Vidal GA, Schwartzberg LS, Halbert DD, Voss A, Miglarese MR, Famulok M, Mayer G, Spetzler D. Polyligand profiling differentiates cancer patients according to their benefit of treatment [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-09-09.
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Affiliation(s)
- V Domenyuk
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - Z Gatalica
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - R Santhanam
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - X Wei
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - A Stark
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - P Kennedy
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - B Toussaint
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - S Levenberg
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - R Wang
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - N Xiao
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - R Greil
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - G Rinnerthaler
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - S Gampenrieder
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - AB Heimberger
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - DJ Berry
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - A Barker
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - GD Demetri
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - J Quackenbush
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - JL Marshall
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - G Poste
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - JL Vacirca
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - GA Vidal
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - LS Schwartzberg
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - DD Halbert
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - A Voss
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - MR Miglarese
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - M Famulok
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - G Mayer
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
| | - D Spetzler
- Caris Life Sciences, Phoenix, AZ; Paracelsus Medical University Salzburg, Austria and Salzburg Cancer Research Institute, and Cancer Cluster Salzburg, Salzburg, Austria; University of Texas MD Anderson Cancer Center, Houston, TX; Complex Adaptive Systems Initiative, Arizona State University, Scottsdale, AZ; Dana-Farber Cancer Institute and Ludwig Center at Harvard Medical School, Boston, MA; Dana-Farber Cancer Institute, Boston, Boston, MA; Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC; North Shore Hematology Oncology Associates Cancer Center, New York, NY; University of Tennessee Health Science Center, Memphis, TN; LIMES Program Unit Chemical Biology & Medicinal Chemistry, c/o Kekulé Institute for Organic Chemistry and Biochemistry, University of Bonn, Bonn, Germany; Chemical Biology Max-Planck-Fellowship Group, Center of Advanced European Studies and Research (CAESAR, Bonn, Germany; Center of Aptamer Research and Development, University of Bonn, Bonn, Germany
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Ferrari G, Quackenbush J, Strobeck J, Johnson C, Shaw R, Brizzio M, Zapolanski A, Grau J. Genome-Wide Transcriptional Analysis of Human Left and Right Internal Mammary Arteries and their use in Coronary Artery Bypass Grafting. J Surg Res 2014. [DOI: 10.1016/j.jss.2013.11.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Doroshow J, Liu ET, Pellini M, Miller V, Palmer G, Averbuch S, Green G, Novotny J, Paoletti P, Patel K, Hoos A, Gaynor R, Melemed S, Reinhard C, Teh BT, Hong WK, Kim E, Herbst R, Papadimitrakopoulou V, Gold K, Wistuba I, Lee J, Lippman S, Jackson JR, Zitvogel L, Meisel C, Workman P, Dalton WS, Botwood N, Davis BJ, Batist G, Assouline S, Camlioglu E, Tetu B, Spatz A, Diaz Z, Aguilar-Mahecha A, Basik M, Rodon J, Dienstmann R, Cortes J, Saura C, Aura C, Hernandez-Losa J, Vivancos A, Joan J, del Campo J, Felip E, Seoane J, Tabernero JT, Friend SH, Tsimberidou AM, Hong DS, Wheler JJ, Ye Y, Fu S, Piha-Paul SA, Naing A, Falchook GS, Janku F, Luthra R, Wen S, Kurzrock R, Naley M, Johnson P, Schuerer K, Lopes M, Hood LE, Yarden Y, Quackenbush J. Lectures. Ann Oncol 2012. [DOI: 10.1093/annonc/mds160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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Quackenbush J. SP 130 Driving discovery through data integration and analysis. Eur J Cancer 2011. [DOI: 10.1016/s0959-8049(11)72607-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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Ilhan A, Wagner L, Maj M, Woehrer A, Czech T, Heinzl H, Marosi C, Base W, Preusser M, Jeuken JW, Navis AC, Sijben A, Boots-Sprenger SH, Bleeker FE, Gijtenbeek JM, Wesseling P, Seyed Sadr E, Tessier A, Seyed Sadr M, Alshami J, Anan M, Sabau C, Del Maestro R, Agnihotri S, Gajadhar A, Wolf A, Mischel PM, Hawkins C, Guha A, Guan X, Chance MR, Barnholtz-Sloan JS, Larson JD, Rodriguez FJ, Demer AM, Sarver AL, Dubac A, Jenkins RB, Dupuy AJ, Copeland NG, Jenkins NA, Taylor MD, Largaespada DA, Lusis EA, Stuart JE, Scheck AC, Coons SW, Lal A, Perry A, Gutmann DH, Barnholtz-Sloan JS, Adams MD, Cohen M, Devine K, Wolinsky Y, Bambakidis N, Selman W, Miller R, Sloan AE, Suchorska B, Mehrkens JH, Eigenbrod S, Eroes CA, Tonn JC, Kretzschmar HA, Kreth FW, Buczkowicz P, Bartels U, Morrison A, Zarghooni M, Bouffet E, Hawkins C, Kollmeyer TM, Wrensch M, Decker PA, Xiao Y, Rynearson AL, Fink S, Kosel ML, Johnson DR, Lachance DH, Yang P, Fridley BL, Wiemels J, Wiencke J, Jenkins RB, Zhou YH, Hess KR, Yu L, Raj VR, Liu L, Alfred Yung WK, Hutchins LF, Linskey ME, Roldan G, Kachra R, McIntyre JB, Magliocco A, Easaw J, Hamilton M, Northcott PA, Van Meter T, Eberhart C, Weiss W, Rutka JT, Gupta N, Korshunov A, French P, Kros J, Michiels E, Kloosterhof N, Hauser P, Montange MF, Jouvet A, Bouffet E, Jung S, Kim SK, Wang KC, Cho BK, Di Rocco C, Massimi L, Leonard J, Scheurlen W, Pfister S, Robinson S, Yang SH, Yoo JY, Cho DG, Kim HK, Kim SW, Lee SW, Fink S, Kollmeyer T, Rynearson A, Decker P, Sicotte H, Yang P, Jenkins R, Lai A, Kharbanda S, Tran A, Pope W, Solis O, Peale F, Forrest W, Purjara K, Carrillo J, Pandita A, Ellingson B, Bowers C, Soriano R, Mohan S, Yong W, Aldape K, Mischel P, Liau L, Nghiemphu P, James CD, Prados M, Westphal M, Lamszus K, Cloughesy T, Phillips H, Thon N, Kreth S, Eigenbrod S, Lutz J, Ledderose C, Tonn JC, Kretzschmar H, Kreth FW, Mokhtari K, Ducray F, Kros JM, Gorlia T, Idbaih A, Marie Y, Taphoorn M, Wesseling P, Brandes AA, Hoang-Xuan K, Delattre JY, Van den Bent M, Sanson M, Lavon I, Shahar T, Granit A, Smith Y, Nossek E, Siegal T, Ram Z, Marko NF, Quackenbush J, Weil RJ, Ducray F, Criniere E, Idbaih A, Paris S, Marie Y, Carpentier C, Houillier C, Dieme M, Adam C, Hoang-Xuan K, Delattre JY, Duyckaerts C, Sanson M, Mokhtari K, Zinn PO, Kozono D, Kasper EM, Warnke PC, Chin L, Chen CC, Saito K, Mukasa A, Saito N, Stieber D, Lenkiewicz E, Evers L, Vallar L, Bjerkvig R, Barrett M, Niclou SP, Gorlia T, Brandes A, Stupp R, Rampling R, Fumoleau P, Dittrich C, Campone M, Twelves C, Raymond E, Lacombe D, van den Bent MJ, Potter N, Ashmore S, Karakoula K, Ward S, Suarez-Merino B, Luxsuwong M, Thomas DG, Darling J, Warr T, Gutman DA, Cooper L, Kong J, Chisolm C, Van Meir EG, Saltz JH, Moreno CS, Brat DJ, Brennan CW, Brat DJ, Aldape KD, Cohen M, Lehman NL, McLendon RE, Miller R, Schniederjan M, Vandenberg SR, Weaver K, Phillips S, Pierce L, Christensen B, Smith A, Zheng S, Koestler D, Houseman EA, Marsit CJ, Wiemels JL, Nelson HH, Karagas MR, Wrensch MR, Kelsey KT, Wiencke JK, Al-Nedawi K, Meehan B, Micallef J, Guha A, Rak J. -Omics and Prognostic Markers. Neuro Oncol 2010. [DOI: 10.1093/neuonc/noq116.s8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
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Rocke DM, Ideker T, Troyanskaya O, Quackenbush J, Dopazo J. Papers on normalization, variable selection, classification or clustering of microarray data. Bioinformatics 2009. [DOI: 10.1093/bioinformatics/btp038] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Abstract
Technologies that have emerged from the genome project have dramatically increased our ability to generate data on the way in which organisms respond to their environments, how they execute their programmes of development and growth, and how these are altered in the development of disease states. However, our ability to analyse these large datasets has not kept pace with our ability to generate them and consequently new strategies must be developed to address the issues associated with their analysis. One approach that we have employed quite successfully is to look at data from microarrays (or proteomics or metabolomics experiments) not as independent datasets, but rather as elements of a much larger body of biological information across various scales that must be integrated with, and interpreted within, the context of such ancillary data. Here we outline the general approach and provide three examples from published studies of the way in which we have applied this strategy.
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Affiliation(s)
- J Quackenbush
- Dana-Farber Cancer Institute and Harvard School of Public Health, Boston, MA 02115, USA.
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Quackenbush J. Computational approaches to analysis of DNA microarray data. Yearb Med Inform 2006:91-103. [PMID: 17051302] [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: 05/12/2023] Open
Abstract
OBJECTIVES To review the current state of the art in computational methods for the analysis of DNA microarray data. METHODS The review considers methods of microarray data collection, transformation and representation, comparisons and predictions of gene expression from the data, their mechanistic analysis, related systems biology, and the application of clustering techniques. RESULTS Functional genomics approaches have greatly increased the rate at which data on biological systems is generated, leading to corresponding challenges in analyzing the data through advanced computational techniques. The paper compares and contrasts the application of computational clustering for discovery, comparison, and prediction of gene expression classes, together with their evaluation and relation to mechanistic analyses of biological systems. CONCLUSION Methods for assaying gene expression levels by DNA microarray experiments produce considerably more data than other techniques, and require a wide variety of computational techniques for identifying patterns of expression that may be biologically significant. These will have to be verified and validated by comparison to results from other methods, integrated with other systems data, and provide the feedback for further experimentation for testing mechanistic or other biological hypotheses.
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Affiliation(s)
- J Quackenbush
- Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Department of Biostatistics, Harvard School of Public Health, Boston, MA, USA.
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12
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Carninci P, Kasukawa T, Katayama S, Gough J, Frith MC, Maeda N, Oyama R, Ravasi T, Lenhard B, Wells C, Kodzius R, Shimokawa K, Bajic VB, Brenner SE, Batalov S, Forrest ARR, Zavolan M, Davis MJ, Wilming LG, Aidinis V, Allen JE, Ambesi-Impiombato A, Apweiler R, Aturaliya RN, Bailey TL, Bansal M, Baxter L, Beisel KW, Bersano T, Bono H, Chalk AM, Chiu KP, Choudhary V, Christoffels A, Clutterbuck DR, Crowe ML, Dalla E, Dalrymple BP, de Bono B, Della Gatta G, di Bernardo D, Down T, Engstrom P, Fagiolini M, Faulkner G, Fletcher CF, Fukushima T, Furuno M, Futaki S, Gariboldi M, Georgii-Hemming P, Gingeras TR, Gojobori T, Green RE, Gustincich S, Harbers M, Hayashi Y, Hensch TK, Hirokawa N, Hill D, Huminiecki L, Iacono M, Ikeo K, Iwama A, Ishikawa T, Jakt M, Kanapin A, Katoh M, Kawasawa Y, Kelso J, Kitamura H, Kitano H, Kollias G, Krishnan SPT, Kruger A, Kummerfeld SK, Kurochkin IV, Lareau LF, Lazarevic D, Lipovich L, Liu J, Liuni S, McWilliam S, Madan Babu M, Madera M, Marchionni L, Matsuda H, Matsuzawa S, Miki H, Mignone F, Miyake S, Morris K, Mottagui-Tabar S, Mulder N, Nakano N, Nakauchi H, Ng P, Nilsson R, Nishiguchi S, Nishikawa S, Nori F, Ohara O, Okazaki Y, Orlando V, Pang KC, Pavan WJ, Pavesi G, Pesole G, Petrovsky N, Piazza S, Reed J, Reid JF, Ring BZ, Ringwald M, Rost B, Ruan Y, Salzberg SL, Sandelin A, Schneider C, Schönbach C, Sekiguchi K, Semple CAM, Seno S, Sessa L, Sheng Y, Shibata Y, Shimada H, Shimada K, Silva D, Sinclair B, Sperling S, Stupka E, Sugiura K, Sultana R, Takenaka Y, Taki K, Tammoja K, Tan SL, Tang S, Taylor MS, Tegner J, Teichmann SA, Ueda HR, van Nimwegen E, Verardo R, Wei CL, Yagi K, Yamanishi H, Zabarovsky E, Zhu S, Zimmer A, Hide W, Bult C, Grimmond SM, Teasdale RD, Liu ET, Brusic V, Quackenbush J, Wahlestedt C, Mattick JS, Hume DA, Kai C, Sasaki D, Tomaru Y, Fukuda S, Kanamori-Katayama M, Suzuki M, Aoki J, Arakawa T, Iida J, Imamura K, Itoh M, Kato T, Kawaji H, Kawagashira N, Kawashima T, Kojima M, Kondo S, Konno H, Nakano K, Ninomiya N, Nishio T, Okada M, Plessy C, Shibata K, Shiraki T, Suzuki S, Tagami M, Waki K, Watahiki A, Okamura-Oho Y, Suzuki H, Kawai J, Hayashizaki Y. The transcriptional landscape of the mammalian genome. Science 2005; 309:1559-63. [PMID: 16141072 DOI: 10.1126/science.1112014] [Citation(s) in RCA: 2607] [Impact Index Per Article: 137.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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Guerrero FD, Miller RJ, Rousseau ME, Sunkara S, Quackenbush J, Lee Y, Nene V. BmiGI: a database of cDNAs expressed in Boophilus microplus, the tropical/southern cattle tick. Insect Biochem Mol Biol 2005; 35:585-595. [PMID: 15857764 DOI: 10.1016/j.ibmb.2005.01.020] [Citation(s) in RCA: 48] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2004] [Revised: 01/26/2005] [Accepted: 01/26/2005] [Indexed: 05/24/2023]
Abstract
We used an expressed sequence tag approach to initiate a study of the genome of the southern cattle tick, Boophilus microplus. A normalized cDNA library was synthesized from pooled RNA purified from tick larvae which had been subjected to different treatments, including acaricide exposure, heat shock, cold shock, host odor, and infection with Babesia bovis. For the acaricide exposure experiments, we used several strains of ticks, which varied in their levels of susceptibility to pyrethroid, organophosphate and amitraz. We also included RNA purified from samples of eggs, nymphs and adult ticks and dissected tick organs. Plasmid DNA was prepared from 11,520 cDNA clones and both 5' and 3' sequencing performed on each clone. The sequence data was used to search public protein databases and a B. microplus gene index was constructed, consisting of 8270 unique sequences whose associated putative functional assignments, when available, can be viewed at the TIGR website (http://www.tigr.org/tdb/tgi). A number of novel sequences were identified which possessed significant sequence similarity to genes, which might be involved in resistance to acaricides.
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Affiliation(s)
- F D Guerrero
- USDA-ARS, Knipling Bushland US Livestock Insect Research Laboratory, 2700 Fredericksburg Road, Kerrville, TX 78028, USA.
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Pinent M, Bladé MC, Salvadó MJ, Arola L, Hackl H, Quackenbush J, Trajanoski Z, Ardévol A. Grape-seed derived procyanidins interfere with adipogenesis of 3T3-L1 cells at the onset of differentiation. Int J Obes (Lond) 2005; 29:934-41. [PMID: 15917849 DOI: 10.1038/sj.ijo.0802988] [Citation(s) in RCA: 66] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Our group's previous results on the effects of a grape seed procyanidin extract (GSPE) on adipose metabolism showed that peroxisome proliferator-activated receptor-gamma (PPARgamma) plays a central role in the lipolytic effects of GSPE on adipocytes. Since PPARgamma2 is a main regulator of the differentiation process of adipocytes, we investigated whether GSPE affects the adipogenesis of 3T3-L1 cells. DESIGN We performed a time point screening by treating 3T3-L1 cells with GSPE during the differentiation process for 24 h. MEASUREMENTS Differentiation markers and differential gene expression due to GSPE treatment (using the microarray technique). RESULTS Twenty four hour-GSPE treatment at the onset of differentiation reduces adipose-specific markers and maintains the expression of preadipocyte marker preadipocyte factor-1 (Pref-1) significantly elevated. These effects were not found in other time points. Microarray analysis of gene expression after GSPE treatment at the early stage of differentiation showed a modified gene expression profile in which cell cycle and growth-related genes were downregulated by GSPE. CONCLUSION These results suggest that GSPE affects adipogenesis, mainly at the induction of differentiation, and that procyanidins may have a new role in which they impede the formation of adipose cells.
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Affiliation(s)
- M Pinent
- Department of Biochemistry and Biotechnology, Rovira i Virgili University, Tarragona, Spain
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Lee Y, Tsai J, Sunkara S, Karamycheva S, Pertea G, Sultana R, Antonescu V, Chan A, Cheung F, Quackenbush J. The TIGR Gene Indices: clustering and assembling EST and known genes and integration with eukaryotic genomes. Nucleic Acids Res 2005; 33:D71-4. [PMID: 15608288 PMCID: PMC540018 DOI: 10.1093/nar/gki064] [Citation(s) in RCA: 159] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Although the list of completed genome sequencing projects has expanded rapidly, sequencing and analysis of expressed sequence tags (ESTs) remain a primary tool for discovery of novel genes in many eukaryotes and a key element in genome annotation. The TIGR Gene Indices (http://www.tigr.org/tdb/tgi) are a collection of 77 species-specific databases that use a highly refined protocol to analyze gene and EST sequences in an attempt to identify and characterize expressed transcripts and to present them on the Web in a user-friendly, consistent fashion. A Gene Index database is constructed for each selected organism by first clustering, then assembling EST and annotated cDNA and gene sequences from GenBank. This process produces a set of unique, high-fidelity virtual transcripts, or tentative consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to genetic and physical maps, to provide links to orthologous and paralogous genes, and as a resource for comparative and functional genomic analysis.
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Affiliation(s)
- Y Lee
- The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.
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Rexroad CE, Lee Y, Keele JW, Karamycheva S, Brown G, Koop B, Gahr SA, Palti Y, Quackenbush J. Sequence analysis of a rainbow trout cDNA library and creation of a gene index. Cytogenet Genome Res 2004; 102:347-54. [PMID: 14970727 DOI: 10.1159/000075773] [Citation(s) in RCA: 79] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2003] [Accepted: 07/30/2003] [Indexed: 11/19/2022] Open
Abstract
Expressed sequence tag (EST) projects have produced extremely valuable resources for identifying genes affecting phenotypes of interest. A large-scale EST sequencing project for rainbow trout was initiated to identify and functionally annotate as many unique transcripts as possible. Over 45,000 5' ESTs were obtained by sequencing clones from a single normalized library constructed using mRNA from six tissues. The production of this sequence data and creation of a rainbow trout Gene Index eliminating redundancy and providing annotation for these sequences will facilitate research in this species.
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Affiliation(s)
- C E Rexroad
- USDA/ARS National Center for Cool and Cold Water Aquaculture, Kearneysville, West Virginia 25430, USA.
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Yang I, Eschrich S, Bloom G, Quackenbush J, Yeatman TJ. Molecular profiling predicts colon cancer survival better than dukes staging. Ann Surg Oncol 2004. [DOI: 10.1007/bf02523978] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Whitelaw CA, Barbazuk WB, Pertea G, Chan AP, Cheung F, Lee Y, Zheng L, van Heeringen S, Karamycheva S, Bennetzen JL, SanMiguel P, Lakey N, Bedell J, Yuan Y, Budiman MA, Resnick A, Van Aken S, Utterback T, Riedmuller S, Williams M, Feldblyum T, Schubert K, Beachy R, Fraser CM, Quackenbush J. Enrichment of gene-coding sequences in maize by genome filtration. Science 2004; 302:2118-20. [PMID: 14684821 DOI: 10.1126/science.1090047] [Citation(s) in RCA: 171] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Approximately 80% of the maize genome comprises highly repetitive sequences interspersed with single-copy, gene-rich sequences, and standard genome sequencing strategies are not readily adaptable to this type of genome. Methodologies that enrich for genic sequences might more rapidly generate useful results from complex genomes. Equivalent numbers of clones from maize selected by techniques called methylation filtering and High C0t selection were sequenced to generate approximately 200,000 reads (approximately 132 megabases), which were assembled into contigs. Combination of the two techniques resulted in a sixfold reduction in the effective genome size and a fourfold increase in the gene identification rate in comparison to a nonenriched library.
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Affiliation(s)
- C A Whitelaw
- The Institute for Genomic Research (TIGR), 9712 Medical Center Drive, Rockville, MD 20850, USA
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Saeed AI, Sharov V, White J, Li J, Liang W, Bhagabati N, Braisted J, Klapa M, Currier T, Thiagarajan M, Sturn A, Snuffin M, Rezantsev A, Popov D, Ryltsov A, Kostukovich E, Borisovsky I, Liu Z, Vinsavich A, Trush V, Quackenbush J. TM4: a free, open-source system for microarray data management and analysis. Biotechniques 2003; 34:374-8. [PMID: 12613259 DOI: 10.2144/03342mt01] [Citation(s) in RCA: 3681] [Impact Index Per Article: 175.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Affiliation(s)
- A I Saeed
- Institute for Genomic Research, Rockville, MD, USA
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20
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Okazaki Y, Furuno M, Kasukawa T, Adachi J, Bono H, Kondo S, Nikaido I, Osato N, Saito R, Suzuki H, Yamanaka I, Kiyosawa H, Yagi K, Tomaru Y, Hasegawa Y, Nogami A, Schönbach C, Gojobori T, Baldarelli R, Hill DP, Bult C, Hume DA, Quackenbush J, Schriml LM, Kanapin A, Matsuda H, Batalov S, Beisel KW, Blake JA, Bradt D, Brusic V, Chothia C, Corbani LE, Cousins S, Dalla E, Dragani TA, Fletcher CF, Forrest A, Frazer KS, Gaasterland T, Gariboldi M, Gissi C, Godzik A, Gough J, Grimmond S, Gustincich S, Hirokawa N, Jackson IJ, Jarvis ED, Kanai A, Kawaji H, Kawasawa Y, Kedzierski RM, King BL, Konagaya A, Kurochkin IV, Lee Y, Lenhard B, Lyons PA, Maglott DR, Maltais L, Marchionni L, McKenzie L, Miki H, Nagashima T, Numata K, Okido T, Pavan WJ, Pertea G, Pesole G, Petrovsky N, Pillai R, Pontius JU, Qi D, Ramachandran S, Ravasi T, Reed JC, Reed DJ, Reid J, Ring BZ, Ringwald M, Sandelin A, Schneider C, Semple CAM, Setou M, Shimada K, Sultana R, Takenaka Y, Taylor MS, Teasdale RD, Tomita M, Verardo R, Wagner L, Wahlestedt C, Wang Y, Watanabe Y, Wells C, Wilming LG, Wynshaw-Boris A, Yanagisawa M, Yang I, Yang L, Yuan Z, Zavolan M, Zhu Y, Zimmer A, Carninci P, Hayatsu N, Hirozane-Kishikawa T, Konno H, Nakamura M, Sakazume N, Sato K, Shiraki T, Waki K, Kawai J, Aizawa K, Arakawa T, Fukuda S, Hara A, Hashizume W, Imotani K, Ishii Y, Itoh M, Kagawa I, Miyazaki A, Sakai K, Sasaki D, Shibata K, Shinagawa A, Yasunishi A, Yoshino M, Waterston R, Lander ES, Rogers J, Birney E, Hayashizaki Y. Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs. Nature 2002; 420:563-73. [PMID: 12466851 DOI: 10.1038/nature01266] [Citation(s) in RCA: 1226] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2002] [Accepted: 10/28/2002] [Indexed: 01/10/2023]
Abstract
Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.
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MESH Headings
- Alternative Splicing/genetics
- Amino Acid Motifs
- Animals
- Chromosomes, Mammalian/genetics
- Cloning, Molecular
- DNA, Complementary/genetics
- Databases, Genetic
- Expressed Sequence Tags
- Genes/genetics
- Genomics/methods
- Humans
- Membrane Proteins/genetics
- Mice/genetics
- Physical Chromosome Mapping
- Protein Structure, Tertiary
- Proteome/chemistry
- Proteome/genetics
- RNA, Antisense/genetics
- RNA, Messenger/analysis
- RNA, Messenger/genetics
- RNA, Untranslated/analysis
- RNA, Untranslated/genetics
- Transcription Initiation Site
- Transcription, Genetic/genetics
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Affiliation(s)
- Y Okazaki
- [1] Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center, RIKEN Yokohama Institute 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, 230-0045, Japan
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21
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Kim H, Zhao B, Snesrud EC, Haas BJ, Town CD, Quackenbush J. Use of RNA and genomic DNA references for inferred comparisons in DNA microarray analyses. Biotechniques 2002; 33:924-30. [PMID: 12398202 DOI: 10.2144/02334mt06] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
In most microarray assays, labeled cDNA molecules derived from reference and query RNA samples are co-hybridized to probes arrayed on a glass surface. Gene expression profiles are then calculated for each gene based on the relative hybridization intensities measured between the two samples. The most commonly used reference samples are typically isolates from a single representative RNA source (RNA-0) or pooled mixtures of RNA derived from a plurality of sources (RNA-p). Genomic DNA offers an alternative reference nucleic acid with a number of potential advantages, including stability, reproducibility, and a potentially uniform representation of all genes, as each unique gene should have equal representation in a haploid genome. Using hydrogen peroxide-treated Arabidopsis thaliana plants as a model, we evaluated genomic DNA and RNA-p as reference samples and compared expression levels inferred through the reference relative to unexposed plants with expression levels measured directly using an RNA-0 reference. Our analysis demonstrates that while genomic DNA can serve as a reasonable reference source for microarray assays, a much greater correlation with direct measurements can be achieved using an RNA-based reference sample.
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Affiliation(s)
- H Kim
- The Institute for Genomic Research, Rockville, MD 20850, USA
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22
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Andersson T, Unneberg P, Nilsson P, Odeberg J, Quackenbush J, Lundeberg J. Monitoring of representational difference analysis subtraction procedures by global microarrays. Biotechniques 2002; 32:1348-50, 1352, 1354-6, 1358. [PMID: 12074166 DOI: 10.2144/02326mt06] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Various approaches to the study of differential gene expression are applied to compare cell lines and tissue samples in a wide range of biological contexts. The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). The subtraction of ubiquitous gene fragments from the two samples was demonstrated using cDNA microarrays including more than 32 000 spotted, PCR-amplified human clones. Hybridizations indicated the expression of 9100 of the microarray elements in a macrophage/foam cell atherosclerosis model system, of which many were removed during the RDA process. The stepwise subtraction procedure was demonstrated to yield an efficient enrichment of gene fragments overrepresented in either sample (18% in the representations, 86% after the first subtraction, and 88% after the second subtraction), many of which were impossible to detect in the starting material. Interestingly, the method allowed for the observation of the differential expression of several members of the low-abundant nuclear receptor gene family. We also observed a certain background level in the difference products of nondifferentially expressed gene fragments, warranting a verification strategy for selected candidate genes. The differential expression of several genes was verified by real-time PCR.
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Affiliation(s)
- T Andersson
- Royal Institute of Technology (KTH), Stockholm, Sweden
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23
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Litwin CM, Quackenbush J. Characterization of a Vibrio vulnificus LysR homologue, HupR, which regulates expression of the haem uptake outer membrane protein, HupA. Microb Pathog 2001; 31:295-307. [PMID: 11747377 DOI: 10.1006/mpat.2001.0472] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.4] [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: 11/22/2022]
Abstract
In Vibrio vulnificus, the ability to acquire iron from the host has been shown to correlate with virulence. Here, we show that the DNA upstream of hupA (haem uptake receptor) in V. vulnificus encodes a protein in the inverse orientation to hupA (named hupR). HupR shares homology with the LysR family of positive transcriptional activators. A hupA-lacZ fusion contained on a plasmid was transformed into Fur(-), Fur(+)and HupR(-)strains of V. vulnificus. The beta-galactosidase assays and Northern blot analysis showed that transcription of hupA is negatively regulated by iron and the Fur repressor in V. vulnificus. Under low-iron conditions with added haemin, the expression of hupA in the hupR mutant was significantly lower than in the wild-type. This diminished response to haem was detected by both Northern blot and hupA-lacZ fusion analysis. The haem response of hupA in the hupR mutant was restored to wild-type levels when complemented with hupR in trans. These studies suggest that HupR may act as a positive regulator of hupA transcription under low-iron conditions in the presence of haemin.
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MESH Headings
- Amino Acid Sequence
- Bacterial Outer Membrane Proteins/analysis
- Bacterial Outer Membrane Proteins/chemistry
- Bacterial Outer Membrane Proteins/genetics
- Bacterial Proteins/analysis
- Bacterial Proteins/chemistry
- Bacterial Proteins/genetics
- Base Sequence
- Blotting, Northern
- Carrier Proteins/chemistry
- Carrier Proteins/genetics
- DNA-Binding Proteins
- Dose-Response Relationship, Drug
- Electrophoresis, Polyacrylamide Gel
- Gene Expression Regulation, Bacterial/drug effects
- Gene Expression Regulation, Bacterial/genetics
- Genes, Bacterial
- Hemin/pharmacology
- Molecular Sequence Data
- Promoter Regions, Genetic
- RNA, Bacterial/analysis
- Sequence Homology, Amino Acid
- Transcription Factors/analysis
- Transcription Factors/chemistry
- Transcription Factors/genetics
- Transcription, Genetic/drug effects
- Vibrio/genetics
- Vibrio/growth & development
- Vibrio/metabolism
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Affiliation(s)
- C M Litwin
- Section of Clinical Immunology, Microbiology and Virology, Salt Lake City, Utah, 84132, USA.
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24
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Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FC, Kim IF, Markowitz V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S, Stewart J, Taylor R, Vilo J, Vingron M. Minimum information about a microarray experiment (MIAME)-toward standards for microarray data. Nat Genet 2001; 29:365-71. [PMID: 11726920 DOI: 10.1038/ng1201-365] [Citation(s) in RCA: 2652] [Impact Index Per Article: 115.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Microarray analysis has become a widely used tool for the generation of gene expression data on a genomic scale. Although many significant results have been derived from microarray studies, one limitation has been the lack of standards for presenting and exchanging such data. Here we present a proposal, the Minimum Information About a Microarray Experiment (MIAME), that describes the minimum information required to ensure that microarray data can be easily interpreted and that results derived from its analysis can be independently verified. The ultimate goal of this work is to establish a standard for recording and reporting microarray-based gene expression data, which will in turn facilitate the establishment of databases and public repositories and enable the development of data analysis tools. With respect to MIAME, we concentrate on defining the content and structure of the necessary information rather than the technical format for capturing it.
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Affiliation(s)
- A Brazma
- European Bioinformatics Institute, EMBL outstation, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
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25
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Hegde P, Qi R, Gaspard R, Abernathy K, Dharap S, Earle-Hughes J, Gay C, Nwokekeh NU, Chen T, Saeed AI, Sharov V, Lee NH, Yeatman TJ, Quackenbush J. Identification of tumor markers in models of human colorectal cancer using a 19,200-element complementary DNA microarray. Cancer Res 2001; 61:7792-7. [PMID: 11691794] [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] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2023]
Abstract
Metastasis represents a crucial transition in disease development and progression and has a profound impact on survival for a wide variety of cancers. Cell line models of metastasis have played an important role in developing our understanding of the metastatic process. We used a 19,200-element human cDNA microarray to profile transcription in three paired cell-line models of colorectal tumor metastasis. By correlating expression patterns across these cell lines, we have identified 176 genes that appear to be differentially expressed (greater than 2-fold) in all highly metastatic cell lines relative to their reference. An analysis of these genes reiterates much of our understanding of the metastatic process and suggests additional genes, many of previously uncharacterized function, that may be causatively involved in, or at least prognostic of, metastasis. Northern analysis of a limited number of these genes validates the observed pattern of expression and suggests that further investigation and functional characterization of the identified genes is warranted.
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Affiliation(s)
- P Hegde
- The Institute for Genomic Research, Rockville, Maryland 20850, USA
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26
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Abstract
The scientific process, and scientific progress, require a critical examination of all published reports. Recent publications detailing errors in the draft human genome sequence are an integral part of our quest to better understand nature and demonstrate the value of free access to scientific data.
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27
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Kappe SH, Gardner MJ, Brown SM, Ross J, Matuschewski K, Ribeiro JM, Adams JH, Quackenbush J, Cho J, Carucci DJ, Hoffman SL, Nussenzweig V. Exploring the transcriptome of the malaria sporozoite stage. Proc Natl Acad Sci U S A 2001; 98:9895-900. [PMID: 11493695 PMCID: PMC55549 DOI: 10.1073/pnas.171185198] [Citation(s) in RCA: 105] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2001] [Indexed: 11/18/2022] Open
Abstract
Most studies of gene expression in Plasmodium have been concerned with asexual and/or sexual erythrocytic stages. Identification and cloning of genes expressed in the preerythrocytic stages lag far behind. We have constructed a high quality cDNA library of the Plasmodium sporozoite stage by using the rodent malaria parasite P. yoelii, an important model for malaria vaccine development. The technical obstacles associated with limited amounts of RNA material were overcome by PCR-amplifying the transcriptome before cloning. Contamination with mosquito RNA was negligible. Generation of 1,972 expressed sequence tags (EST) resulted in a total of 1,547 unique sequences, allowing insight into sporozoite gene expression. The circumsporozoite protein (CS) and the sporozoite surface protein 2 (SSP2) are well represented in the data set. A BLASTX search with all tags of the nonredundant protein database gave only 161 unique significant matches (P(N) < or = 10(-4)), whereas 1,386 of the unique sequences represented novel sporozoite-expressed genes. We identified ESTs for three proteins that may be involved in host cell invasion and documented their expression in sporozoites. These data should facilitate our understanding of the preerythrocytic Plasmodium life cycle stages and the development of preerythrocytic vaccines.
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Affiliation(s)
- S H Kappe
- Michael Heidelberger Division, Department of Pathology, Kaplan Cancer Center, New York University School of Medicine, New York, NY 10016, USA.
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28
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Abstract
Microarray gene expression technology has recently made it feasible to characterize the RNA expression of thousands of genes across numerous tissue samples. We hypothesized that the warm ischemia commonly associated with the surgical extirpation of human tissue would have significant effects on gene expression profiles. To quantitate the effects of warm ischemia on human tissue, we rapidly dissected normal mucosa from a human colon cancer specimen. The specimen was divided and maintained at room temperature until snap-frozen in liquid nitrogen. Aliquots of tissue were frozen at times 5, 10, 15, 20, 40, and 60 min after extirpation. Spotted microarrays composed of 2400 distinct elements were used to assay mRNA derived from each time point in triplicate. Eisen's hierarchical clustering methodology and Bayesean statistical methods were then used to assay the effects of warm ischemia on gene expression. Application of time-course statistical models suggest that three patterns were induced by ischemia, accounting for 68.2, 17.8, and 13.4% of the evaluable genes, respectively. Pattern I corresponds to an average change of 27% over 60 min from 5 min baseline level of expression and 63.8% of the genes with at least 80% probability of membership in this pattern show average increases in expression over 60 min. The remainder decrease on average. Pattern II genes show the least ischemia-related effects, demonstrating an average change of only 12% over 60 min. In contrast to pattern I, we find that 67.5% of the genes with at least 80% probability of membership in this pattern are decreasing in expression on average over time. The remaining 32.5% in this pattern increase an average of 12% over 60 min. Finally, pattern III genes (13.4% of the sample) show the greatest sensitivity to ischemia, changing an average of 50% over 60 min, with about the same number increasing as are decreasing. Fold changes in RNA over- or under-expression were observed up to greater than 20-fold. Warm ischemia associated with the surgical extirpation of human tissues has significant effects on gene expression. These data support the careful monitoring of ischemic time for tissues harvested for the purpose of gene profiling.
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Affiliation(s)
- J Huang
- Department of Surgery and Biostatistics, H. Lee Moffitt Cancer Center, University of South Florida, 12902 Magnolia Drive, Tampa, FL 33647, USA
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29
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Gaspard R, Dharap S, Malek J, Qi R, Quackenbush J. Optimized growth conditions for direct amplification of cDNA clone inserts from culture. Biotechniques 2001; 31:35-6. [PMID: 11464517 DOI: 10.2144/01311bm04] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Affiliation(s)
- R Gaspard
- Institute for Genomic Research, 9712 Medical Center Dr., Rockville, MD 20850, USA
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30
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Flores-Morales A, Ståhlberg N, Tollet-Egnell P, Lundeberg J, Malek RL, Quackenbush J, Lee NH, Norstedt G. Microarray analysis of the in vivo effects of hypophysectomy and growth hormone treatment on gene expression in the rat. Endocrinology 2001; 142:3163-76. [PMID: 11416039 DOI: 10.1210/endo.142.7.8235] [Citation(s) in RCA: 62] [Impact Index Per Article: 2.7] [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: 11/19/2022]
Abstract
Complementary DNA microarrays containing 3000 different rat genes were used to study the consequences of severe hormonal deficiency (hypophysectomy) on the gene expression patterns in heart, liver, and kidney. Hybridization signals were seen from a majority of the arrayed complementary DNAs; nonetheless, tissue-specific expression patterns could be delineated. Hypophysectomy affected the expression of genes involved in a variety of cellular functions. Between 16-29% of the detected transcripts from each tissue changed expression level as a reaction to this condition. Chronic treatment of hypophysectomized animals with human GH also caused significant changes in gene expression patterns. The study confirms previous knowledge concerning certain gene expression changes in the above-mentioned situations and provides new information regarding hypophysectomy and chronic human GH effects in the rat. Furthermore, we have identified several new genes that respond to GH treatment. Our results represent a first step toward a more global understanding of gene expression changes in states of hormonal deficiency.
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Affiliation(s)
- A Flores-Morales
- Department of Molecular Medicine, Karolinska Institute, 17176 Stockholm, Sweden
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31
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Abstract
Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns. Although this technique has been enthusiastically developed and applied in many biological contexts, the management and analysis of the millions of data points that result from these experiments has received less attention. Sophisticated computational tools are available, but the methods that are used to analyse the data can have a profound influence on the interpretation of the results. A basic understanding of these computational tools is therefore required for optimal experimental design and meaningful data analysis.
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Affiliation(s)
- J Quackenbush
- The Institute for Genomic Research, 9,712 Medical Center Drive, Rockville, Maryland 20850, USA.
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32
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Smith TP, Grosse WM, Freking BA, Roberts AJ, Stone RT, Casas E, Wray JE, White J, Cho J, Fahrenkrug SC, Bennett GL, Heaton MP, Laegreid WW, Rohrer GA, Chitko-McKown CG, Pertea G, Holt I, Karamycheva S, Liang F, Quackenbush J, Keele JW. Sequence evaluation of four pooled-tissue normalized bovine cDNA libraries and construction of a gene index for cattle. Genome Res 2001; 11:626-30. [PMID: 11282978 PMCID: PMC311058 DOI: 10.1101/gr.170101] [Citation(s) in RCA: 76] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
An essential component of functional genomics studies is the sequence of DNA expressed in tissues of interest. To provide a resource of bovine-specific expressed sequence data and facilitate this powerful approach in cattle research, four normalized cDNA libraries were produced and arrayed for high-throughput sequencing. The libraries were made with RNA pooled from multiple tissues to increase efficiency of normalization and maximize the number of independent genes for which sequence data were obtained. Target tissues included those with highest likelihood to have impact on production parameters of animal health, growth, reproductive efficiency, and carcass merit. Success of normalization and inter- and intralibrary redundancy were assessed by collecting 6000-23,000 sequences from each of the libraries (68,520 total sequences deposited in GenBank). Sequence comparison and assembly of these sequences was performed in combination with 56,500 other bovine EST sequences present in the GenBank dbEST database to construct a cattle Gene Index (available from The Institute for Genomic Research at http://www.tigr.org/tdb/tgi.shtml). The 124,381 bovine ESTs present in GenBank at the time of the analysis form 16,740 assemblies that are listed and annotated on the Web site. Analysis of individual library sequence data indicates that the pooled-tissue approach was highly effective in preparing libraries for efficient deep sequencing.
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Affiliation(s)
- T P Smith
- United States Department of Agriculture, Agricultural Research Service, United States Meat Animal Research Center, Clay Center, Nebraska 68933, USA.
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33
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Yuan Q, Quackenbush J, Sultana R, Pertea M, Salzberg SL, Buell CR. Rice bioinformatics. analysis of rice sequence data and leveraging the data to other plant species. Plant Physiol 2001; 125:1166-74. [PMID: 11244096 PMCID: PMC1539370 DOI: 10.1104/pp.125.3.1166] [Citation(s) in RCA: 20] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Rice (Oryza sativa) is a model species for monocotyledonous plants, especially for members in the grass family. Several attributes such as small genome size, diploid nature, transformability, and establishment of genetic and molecular resources make it a tractable organism for plant biologists. With an estimated genome size of 430 Mb (Arumuganathan and Earle, 1991), it is feasible to obtain the complete genome sequence of rice using current technologies. An international effort has been established and is in the process of sequencing O. sativa spp. japonica var "Nipponbare" using a bacterial artificial chromosome/P1 artificial chromosome shotgun sequencing strategy. Annotation of the rice genome is performed using prediction-based and homology-based searches to identify genes. Annotation tools such as optimized gene prediction programs are being developed for rice to improve the quality of annotation. Resources are also being developed to leverage the rice genome sequence to partial genome projects such as expressed sequence tag projects, thereby maximizing the output from the rice genome project. To provide a low level of annotation for rice genomic sequences, we have aligned all rice bacterial artificial chromosome/P1 artificial chromosome sequences with The Institute of Genomic Research Gene Indices that are a set of nonredundant transcripts that are generated from nine public plant expressed sequence tag projects (rice, wheat, sorghum, maize, barley, Arabidopsis, tomato, potato, and barrel medic). In addition, we have used data from The Institute of Genomic Research Gene Indices and the Arabidopsis and Rice Genome Projects to identify putative orthologues and paralogues among these nine genomes.
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Affiliation(s)
- Q Yuan
- The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, Maryland 20850, USA
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Kawai J, Shinagawa A, Shibata K, Yoshino M, Itoh M, Ishii Y, Arakawa T, Hara A, Fukunishi Y, Konno H, Adachi J, Fukuda S, Aizawa K, Izawa M, Nishi K, Kiyosawa H, Kondo S, Yamanaka I, Saito T, Okazaki Y, Gojobori T, Bono H, Kasukawa T, Saito R, Kadota K, Matsuda H, Ashburner M, Batalov S, Casavant T, Fleischmann W, Gaasterland T, Gissi C, King B, Kochiwa H, Kuehl P, Lewis S, Matsuo Y, Nikaido I, Pesole G, Quackenbush J, Schriml LM, Staubli F, Suzuki R, Tomita M, Wagner L, Washio T, Sakai K, Okido T, Furuno M, Aono H, Baldarelli R, Barsh G, Blake J, Boffelli D, Bojunga N, Carninci P, de Bonaldo MF, Brownstein MJ, Bult C, Fletcher C, Fujita M, Gariboldi M, Gustincich S, Hill D, Hofmann M, Hume DA, Kamiya M, Lee NH, Lyons P, Marchionni L, Mashima J, Mazzarelli J, Mombaerts P, Nordone P, Ring B, Ringwald M, Rodriguez I, Sakamoto N, Sasaki H, Sato K, Schönbach C, Seya T, Shibata Y, Storch KF, Suzuki H, Toyo-oka K, Wang KH, Weitz C, Whittaker C, Wilming L, Wynshaw-Boris A, Yoshida K, Hasegawa Y, Kawaji H, Kohtsuki S, Hayashizaki Y. Functional annotation of a full-length mouse cDNA collection. Nature 2001; 409:685-90. [PMID: 11217851 DOI: 10.1038/35055500] [Citation(s) in RCA: 487] [Impact Index Per Article: 21.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
The RIKEN Mouse Gene Encyclopaedia Project, a systematic approach to determining the full coding potential of the mouse genome, involves collection and sequencing of full-length complementary DNAs and physical mapping of the corresponding genes to the mouse genome. We organized an international functional annotation meeting (FANTOM) to annotate the first 21,076 cDNAs to be analysed in this project. Here we describe the first RIKEN clone collection, which is one of the largest described for any organism. Analysis of these cDNAs extends known gene families and identifies new ones.
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Affiliation(s)
- J Kawai
- Laboratory for Genome Exploration Research Group, RIKEN Genomic Sciences Center, Yokohama Institute, Kanagawa, Japan
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Quackenbush J, Cho J, Lee D, Liang F, Holt I, Karamycheva S, Parvizi B, Pertea G, Sultana R, White J. The TIGR Gene Indices: analysis of gene transcript sequences in highly sampled eukaryotic species. Nucleic Acids Res 2001; 29:159-64. [PMID: 11125077 PMCID: PMC29813 DOI: 10.1093/nar/29.1.159] [Citation(s) in RCA: 318] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
While genome sequencing projects are advancing rapidly, EST sequencing and analysis remains a primary research tool for the identification and categorization of gene sequences in a wide variety of species and an important resource for annotation of genomic sequence. The TIGR Gene Indices (http://www.tigr.org/tdb/tgi. shtml) are a collection of species-specific databases that use a highly refined protocol to analyze EST sequences in an attempt to identify the genes represented by that data and to provide additional information regarding those genes. Gene Indices are constructed by first clustering, then assembling EST and annotated gene sequences from GenBank for the targeted species. This process produces a set of unique, high-fidelity virtual transcripts, or Tentative Consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to mapping and genomic sequence data, to provide links between orthologous and paralogous genes and as a resource for comparative sequence analysis.
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Affiliation(s)
- J Quackenbush
- The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA.
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Yuan Q, Liang F, Hsiao J, Zismann V, Benito MI, Quackenbush J, Wing R, Buell R. Anchoring of rice BAC clones to the rice genetic map in silico. Nucleic Acids Res 2000; 28:3636-41. [PMID: 10982886 PMCID: PMC110739 DOI: 10.1093/nar/28.18.3636] [Citation(s) in RCA: 35] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
A wealth of molecular resources have been developed for rice genomics, including dense genetic maps, expressed sequence tags (ESTs), yeast artificial chromosome maps, bacterial artificial chromosome (BAC) libraries and BAC end sequence databases. Integration of genetic and physical maps involves labor-intensive empirical experiments. To accelerate the integration of the bacterial clone resources with the genetic map for the International Rice Genome Sequencing Project, we cleaned and filtered the available EST and BAC end sequences for repetitive sequences and then searched all available rice genetic markers with our filtered databases. We identified 418 genetic markers that aligned with at least one BAC end sequence with >95% sequence identity, providing a set of large insert clones with an average separation of 1 Mb that can serve as nucleation points for the sequencing phase of the International Rice Genome Sequencing Project.
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Affiliation(s)
- Q Yuan
- The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA
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39
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Abstract
The vast body of Expressed Sequence Tag (EST) data in the public databases provide an important resource for comparative and functional genomics studies and an invaluable tool for the annotation of genomic sequences. We have developed a rigorous protocol for reconstructing the sequences of transcribed genes from EST and gene sequence fragments. A key element in developing this protocol has been the evaluation of a number of sequence assembly programs to determine which most faithfully reproduce transcript sequences from EST data. The TIGR Gene Indices constructed using this protocol for human, mouse, rat and a variety of other plant and animal models have demonstrated their utility in a variety of applications and are freely available to the scientific research community.
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Affiliation(s)
- F Liang
- The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20850, USA
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40
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Hegde P, Qi R, Abernathy K, Gay C, Dharap S, Gaspard R, Hughes JE, Snesrud E, Lee N, Quackenbush J. A concise guide to cDNA microarray analysis. Biotechniques 2000; 29:548-50, 552-4, 556 passim. [PMID: 10997270 DOI: 10.2144/00293bi01] [Citation(s) in RCA: 668] [Impact Index Per Article: 27.8] [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: 11/23/2022] Open
Abstract
Microarray expression analysis has become one of the most widely used functional genomics tools. Efficient application of this technique requires the development of robust and reproducible protocols. We have optimized all aspects of the process, including PCR amplification of target cDNA clones, microarray printing, probe labeling and hybridization, and have developed strategies for data normalization and analysis.
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Affiliation(s)
- P Hegde
- Institute for Genomic Research, Rockville, MD, USA
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41
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Liang F, Holt I, Pertea G, Karamycheva S, Salzberg SL, Quackenbush J. Gene index analysis of the human genome estimates approximately 120,000 genes. Nat Genet 2000; 25:239-40. [PMID: 10835646 DOI: 10.1038/76126] [Citation(s) in RCA: 195] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Although sequencing of the human genome will soon be completed, gene identification and annotation remains a challenge. Early estimates suggested that there might be 60,000-100,000 (ref. 1) human genes, but recent analyses of the available data from EST sequencing projects have estimated as few as 45,000 (ref. 2) or as many as 140, 000 (ref. 3) distinct genes. The Chromosome 22 Sequencing Consortium estimated a minimum of 45,000 genes based on their annotation of the complete chromosome, although their data suggests there may be additional genes. The nearly 2,000,000 human ESTs in dbEST provide an important resource for gene identification and genome annotation, but these single-pass sequences must be carefully analysed to remove contaminating sequences, including those from genomic DNA, spurious transcription, and vector and bacterial sequences. We have developed a highly refined and rigorously tested protocol for cleaning, clustering and assembling EST sequences to produce high-fidelity consensus sequences for the represented genes (F.L. et al., manuscript submitted) and used this to create the TIGR Gene Indices-databases of expressed genes for human, mouse, rat and other species (http://www.tigr.org/tdb/tgi.html). Using highly refined and tested algorithms for EST analysis, we have arrived at two independent estimates indicating the human genome contains approximately 120,000 genes.
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Affiliation(s)
- F Liang
- The Institute for Genomic Research, Rockville, Maryland, USA
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Abstract
The haploid nuclear genome of the African trypanosome, Trypanosoma brucei, is about 35 Mb and varies in size among different trypanosome isolates by as much as 25%. The nuclear DNA of this diploid organism is distributed among three size classes of chromosomes: the megabase chromosomes of which there are at least 11 pairs ranging from 1 Mb to more than 6 Mb (numbered I-XI from smallest to largest); several intermediate chromosomes of 200-900 kb and uncertain ploidy; and about 100 linear minichromosomes of 50-150 kb. Size differences of as much as four-fold can occur, both between the two homologues of a megabase chromosome pair in a specific trypanosome isolate and among chromosome pairs in different isolates. The genomic DNA sequences determined to date indicated that about 50% of the genome is coding sequence. The chromosomal telomeres possess TTAGGG repeats and many, if not all, of the telomeres of the megabase and intermediate chromosomes are linked to expression sites for genes encoding variant surface glycoproteins (VSGs). The minichromosomes serve as repositories for VSG genes since some but not all of their telomeres are linked to unexpressed VSG genes. A gene discovery program, based on sequencing the ends of cloned genomic DNA fragments, has generated more than 20 Mb of discontinuous single-pass genomic sequence data during the past year, and the complete sequences of chromosomes I and II (about 1 Mb each) in T. brucei GUTat 10.1 are currently being determined. It is anticipated that the entire genomic sequence of this organism will be known in a few years. Analysis of a test microarray of 400 cDNAs and small random genomic DNA fragments probed with RNAs from two developmental stages of T. brucei demonstrates that the microarray technology can be used to identify batteries of genes differentially expressed during the various life cycle stages of this parasite.
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Affiliation(s)
- N M El-Sayed
- The Institute for Genomic Research (TIGR), 9712 Medical Center Drive, Rockville, MD 20850, USA.
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43
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Abstract
Expressed sequence tags (ESTs) have provided a first glimpse of the collection of transcribed sequences in a variety of organisms. However, a careful analysis of this sequence data can provide significant additional functional, structural and evolutionary information. Our analysis of the public EST sequences, available through the TIGR Gene Indices (TGI; http://www.tigr.org/tdb/tdb.html ), is an attempt to identify the genes represented by that data and to provide additional information regarding those genes. Gene Indices are constructed for selected organisms by first clustering, then assembling EST and annotated gene sequences from GenBank. This process produces a set of unique, high-fidelity virtual transcripts, or tentative consensus (TC) sequences. The TC sequences can be used to provide putative genes with functional annotation, to link the transcripts to mapping and genomic sequence data, and to provide links between orthologous and paralogous genes.
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Affiliation(s)
- J Quackenbush
- The Institute for Genomic Research, Rockville, MD 20850, USA.
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Doyle DJ, Quackenbush J. Symposium on Genomic Medicine, University of Maryland, Shady Grove Campus, Rockville, Maryland, March 17-18, 1997. Microb Comp Genomics 1998; 2:99-102. [PMID: 9689218 DOI: 10.1089/omi.1.1997.2.99] [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] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- D J Doyle
- Institute for Genomic Research, Rockville, Maryland, USA
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45
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Korenberg JR, Aaltonen J, Brahe C, Cabin D, Creau N, Delabar JM, Doering J, Gardiner K, Hubert RS, Ives J, Kessling A, Kudoh J, Lafrenière R, Murakami Y, Ohira M, Ohki M, Patterson D, Potier MC, Quackenbush J, Reeves RH, Sakaki Y, Shimizu N, Soeda E, Van Broeckhoven C, Yaspo ML. Report and abstracts of the Sixth International Workshop on Human Chromosome 21 Mapping 1996. Cold Spring Harbor, New York, USA. May 6-8,1996. Cytogenet Cell Genet 1998; 79:21-52. [PMID: 9533011 DOI: 10.1159/000134681] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
- J R Korenberg
- Medical Genetics Birth Defects Center, UCLA School of Medicine 90048, USA.
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46
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Fraser CM, Casjens S, Huang WM, Sutton GG, Clayton R, Lathigra R, White O, Ketchum KA, Dodson R, Hickey EK, Gwinn M, Dougherty B, Tomb JF, Fleischmann RD, Richardson D, Peterson J, Kerlavage AR, Quackenbush J, Salzberg S, Hanson M, van Vugt R, Palmer N, Adams MD, Gocayne J, Weidman J, Utterback T, Watthey L, McDonald L, Artiach P, Bowman C, Garland S, Fuji C, Cotton MD, Horst K, Roberts K, Hatch B, Smith HO, Venter JC. Genomic sequence of a Lyme disease spirochaete, Borrelia burgdorferi. Nature 1997; 390:580-6. [PMID: 9403685 DOI: 10.1038/37551] [Citation(s) in RCA: 1498] [Impact Index Per Article: 55.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The genome of the bacterium Borrelia burgdorferi B31, the aetiologic agent of Lyme disease, contains a linear chromosome of 910,725 base pairs and at least 17 linear and circular plasmids with a combined size of more than 533,000 base pairs. The chromosome contains 853 genes encoding a basic set of proteins for DNA replication, transcription, translation, solute transport and energy metabolism, but, like Mycoplasma genitalium, it contains no genes for cellular biosynthetic reactions. Because B. burgdorferi and M. genitalium are distantly related eubacteria, we suggest that their limited metabolic capacities reflect convergent evolution by gene loss from more metabolically competent progenitors. Of 430 genes on 11 plasmids, most have no known biological function; 39% of plasmid genes are paralogues that form 47 gene families. The biological significance of the multiple plasmid-encoded genes is not clear, although they may be involved in antigenic variation or immune evasion.
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Affiliation(s)
- C M Fraser
- Institute for Genomic Research, Rockville, Maryland 20850, USA
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47
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Klenk HP, Clayton RA, Tomb JF, White O, Nelson KE, Ketchum KA, Dodson RJ, Gwinn M, Hickey EK, Peterson JD, Richardson DL, Kerlavage AR, Graham DE, Kyrpides NC, Fleischmann RD, Quackenbush J, Lee NH, Sutton GG, Gill S, Kirkness EF, Dougherty BA, McKenney K, Adams MD, Loftus B, Peterson S, Reich CI, McNeil LK, Badger JH, Glodek A, Zhou L, Overbeek R, Gocayne JD, Weidman JF, McDonald L, Utterback T, Cotton MD, Spriggs T, Artiach P, Kaine BP, Sykes SM, Sadow PW, D'Andrea KP, Bowman C, Fujii C, Garland SA, Mason TM, Olsen GJ, Fraser CM, Smith HO, Woese CR, Venter JC. The complete genome sequence of the hyperthermophilic, sulphate-reducing archaeon Archaeoglobus fulgidus. Nature 1997; 390:364-70. [PMID: 9389475 DOI: 10.1038/37052] [Citation(s) in RCA: 990] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Archaeoglobus fulgidus is the first sulphur-metabolizing organism to have its genome sequence determined. Its genome of 2,178,400 base pairs contains 2,436 open reading frames (ORFs). The information processing systems and the biosynthetic pathways for essential components (nucleotides, amino acids and cofactors) have extensive correlation with their counterparts in the archaeon Methanococcus jannaschii. The genomes of these two Archaea indicate dramatic differences in the way these organisms sense their environment, perform regulatory and transport functions, and gain energy. In contrast to M. jannaschii, A. fulgidus has fewer restriction-modification systems, and none of its genes appears to contain inteins. A quarter (651 ORFs) of the A. fulgidus genome encodes functionally uncharacterized yet conserved proteins, two-thirds of which are shared with M. jannaschii (428 ORFs). Another quarter of the genome encodes new proteins indicating substantial archaeal gene diversity.
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Affiliation(s)
- H P Klenk
- Institute for Genomic Research, Rockville, Maryland 20850, USA
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48
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Tomb JF, White O, Kerlavage AR, Clayton RA, Sutton GG, Fleischmann RD, Ketchum KA, Klenk HP, Gill S, Dougherty BA, Nelson K, Quackenbush J, Zhou L, Kirkness EF, Peterson S, Loftus B, Richardson D, Dodson R, Khalak HG, Glodek A, McKenney K, Fitzegerald LM, Lee N, Adams MD, Hickey EK, Berg DE, Gocayne JD, Utterback TR, Peterson JD, Kelley JM, Cotton MD, Weidman JM, Fujii C, Bowman C, Watthey L, Wallin E, Hayes WS, Borodovsky M, Karp PD, Smith HO, Fraser CM, Venter JC. The complete genome sequence of the gastric pathogen Helicobacter pylori. Nature 1997; 388:539-47. [PMID: 9252185 DOI: 10.1038/41483] [Citation(s) in RCA: 2543] [Impact Index Per Article: 94.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Helicobacter pylori, strain 26695, has a circular genome of 1,667,867 base pairs and 1,590 predicted coding sequences. Sequence analysis indicates that H. pylori has well-developed systems for motility, for scavenging iron, and for DNA restriction and modification. Many putative adhesins, lipoproteins and other outer membrane proteins were identified, underscoring the potential complexity of host-pathogen interaction. Based on the large number of sequence-related genes encoding outer membrane proteins and the presence of homopolymeric tracts and dinucleotide repeats in coding sequences, H. pylori, like several other mucosal pathogens, probably uses recombination and slipped-strand mispairing within repeats as mechanisms for antigenic variation and adaptive evolution. Consistent with its restricted niche, H. pylori has a few regulatory networks, and a limited metabolic repertoire and biosynthetic capacity. Its survival in acid conditions depends, in part, on its ability to establish a positive inside-membrane potential in low pH.
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Affiliation(s)
- J F Tomb
- Institute for Genomic Research, Rockville, Maryland 20850, USA.
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49
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Stewart EA, McKusick KB, Aggarwal A, Bajorek E, Brady S, Chu A, Fang N, Hadley D, Harris M, Hussain S, Lee R, Maratukulam A, O'Connor K, Perkins S, Piercy M, Qin F, Reif T, Sanders C, She X, Sun WL, Tabar P, Voyticky S, Cowles S, Fan JB, Mader C, Quackenbush J, Myers RM, Cox DR. An STS-based radiation hybrid map of the human genome. Genome Res 1997; 7:422-33. [PMID: 9149939 DOI: 10.1101/gr.7.5.422] [Citation(s) in RCA: 239] [Impact Index Per Article: 8.9] [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: 02/04/2023]
Abstract
We have constructed a physical map of the human genome by using a panel of 83 whole genome radiation hybrids (the Stanford G3 panel) in conjunction with 10,478 sequence-tagged sites (STSs) derived from random genomic DNA sequences, previously mapped genetic markers, and expressed sequences. Of these STSs, 5049 are framework markers that fall into 1766 high-confidence bins. An additional 945 STSs are indistinguishable in their map location from one or more of the framework markers. These 5994 mapped STSs have an average spacing of 500 kb. An additional 4484 STSs are positioned with respect to the framework markers. Comparison of the orders of markers on this map with orders derived from independent meiotic and YAC STS-content maps indicates that the error rate in defining high-confidence bins is < 5%. Analysis of 322 random cDNAs indicates that the map covers the vast majority of the human genome. This STS-based radiation hybrid map of the human genome brings us one step closer to the goal of a physical map containing 30,000 unique ordered landmarks with an average marker spacing of 100 kb.
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Affiliation(s)
- E A Stewart
- Stanford Human Genome Center, Palo Alto, California, USA
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50
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Inoue I, Nakajima T, Williams CS, Quackenbush J, Puryear R, Powers M, Cheng T, Ludwig EH, Sharma AM, Hata A, Jeunemaitre X, Lalouel JM. A nucleotide substitution in the promoter of human angiotensinogen is associated with essential hypertension and affects basal transcription in vitro. J Clin Invest 1997; 99:1786-97. [PMID: 9120024 PMCID: PMC508000 DOI: 10.1172/jci119343] [Citation(s) in RCA: 396] [Impact Index Per Article: 14.7] [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: 02/04/2023] Open
Abstract
In earlier studies, we provided statistical evidence that individual differences in the angiotensinogen gene, the precursor of the vasoactive hormone angiotensin II, constitute inherited predispositions to essential hypertension in humans. We have now identified a common variant in the proximal promoter, the presence of an adenine, instead of a guanine, 6 bp upstream from the initiation site of transcription, in significant association with the disorder. Tests of promoter activity and DNA binding studies with nuclear proteins suggest that this nucleotide substitution affects the basal transcription rate of the gene. These observations provide some biological insight about the possible mechanism of a genetic predisposition to essential hypertension; they may also have important evolutionary implications.
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Affiliation(s)
- I Inoue
- Department of Human Genetics, University of Utah Health Sciences Center, Salt Lake City 84112, USA
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