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Servellita V, Sotomayor Gonzalez A, Lamson DM, Foresythe A, Huh HJ, Bazinet AL, Bergman NH, Bull RL, Garcia KY, Goodrich JS, Lovett SP, Parker K, Radune D, Hatada A, Pan CY, Rizzo K, Bertumen JB, Morales C, Oluniyi PE, Nguyen J, Tan J, Stryke D, Jaber R, Leslie MT, Lyons Z, Hedman HD, Parashar U, Sullivan M, Wroblewski K, Oberste MS, Tate JE, Baker JM, Sugerman D, Potts C, Lu X, Chhabra P, Ingram LA, Shiau H, Britt W, Gutierrez Sanchez LH, Ciric C, Rostad CA, Vinjé J, Kirking HL, Wadford DA, Raborn RT, St George K, Chiu CY. Adeno-associated virus type 2 in US children with acute severe hepatitis. Nature 2023; 617:574-580. [PMID: 36996871 PMCID: PMC10170441 DOI: 10.1038/s41586-023-05949-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [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: 09/11/2022] [Accepted: 03/10/2023] [Indexed: 04/01/2023]
Abstract
As of August 2022, clusters of acute severe hepatitis of unknown aetiology in children have been reported from 35 countries, including the USA1,2. Previous studies have found human adenoviruses (HAdVs) in the blood from patients in Europe and the USA3-7, although it is unclear whether this virus is causative. Here we used PCR testing, viral enrichment-based sequencing and agnostic metagenomic sequencing to analyse samples from 16 HAdV-positive cases from 1 October 2021 to 22 May 2022, in parallel with 113 controls. In blood from 14 cases, adeno-associated virus type 2 (AAV2) sequences were detected in 93% (13 of 14), compared to 4 (3.5%) of 113 controls (P < 0.001) and to 0 of 30 patients with hepatitis of defined aetiology (P < 0.001). In controls, HAdV type 41 was detected in blood from 9 (39.1%) of the 23 patients with acute gastroenteritis (without hepatitis), including 8 of 9 patients with positive stool HAdV testing, but co-infection with AAV2 was observed in only 3 (13.0%) of these 23 patients versus 93% of cases (P < 0.001). Co-infections by Epstein-Barr virus, human herpesvirus 6 and/or enterovirus A71 were also detected in 12 (85.7%) of 14 cases, with higher herpesvirus detection in cases versus controls (P < 0.001). Our findings suggest that the severity of the disease is related to co-infections involving AAV2 and one or more helper viruses.
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Affiliation(s)
- Venice Servellita
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - Daryl M Lamson
- Wadsworth Center, New York State Department of Health, David Axelrod Institute, Albany, NY, USA
| | - Abiodun Foresythe
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Hee Jae Huh
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Adam L Bazinet
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Nicholas H Bergman
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Robert L Bull
- Federal Bureau of Investigation Laboratory Division/Scientific Response and Analysis Unit, Quantico, VA, USA
| | - Karla Y Garcia
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Jennifer S Goodrich
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Sean P Lovett
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Kisha Parker
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Diana Radune
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - April Hatada
- California Department of Public Health, Richmond, CA, USA
| | - Chao-Yang Pan
- California Department of Public Health, Richmond, CA, USA
| | - Kyle Rizzo
- California Department of Public Health, Richmond, CA, USA
| | - J Bradford Bertumen
- California Department of Public Health, Richmond, CA, USA
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | | | - Paul E Oluniyi
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jenny Nguyen
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jessica Tan
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Doug Stryke
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Rayah Jaber
- Florida Department of Health, Tallahassee, FL, USA
| | | | - Zin Lyons
- North Carolina Department of Health and Human Services, Raleigh, NC, USA
| | - Hayden D Hedman
- Centers for Disease Control and Prevention, Atlanta, CA, USA
- South Dakota Department of Health, Pierre, SD, USA
| | - Umesh Parashar
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | - Maureen Sullivan
- Association for Public Health Laboratories, Silver Spring, MD, USA
| | - Kelly Wroblewski
- Association for Public Health Laboratories, Silver Spring, MD, USA
| | | | | | - Julia M Baker
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | - David Sugerman
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | - Caelin Potts
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | - Xiaoyan Lu
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | - Preeti Chhabra
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | | | - Henry Shiau
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - William Britt
- University of Alabama at Birmingham, Birmingham, AL, USA
| | | | - Caroline Ciric
- Department of Pediatrics, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Christina A Rostad
- Department of Pediatrics, Emory University School of Medicine and Children's Healthcare of Atlanta, Atlanta, GA, USA
| | - Jan Vinjé
- Centers for Disease Control and Prevention, Atlanta, CA, USA
| | | | | | - R Taylor Raborn
- National Biodefense Analysis and Countermeasures Center (NBACC), Frederick, MD, USA
| | - Kirsten St George
- Wadsworth Center, New York State Department of Health, David Axelrod Institute, Albany, NY, USA
- Department of Biomedical Science, University at Albany, SUNY, Albany, NY, USA
| | - Charles Y Chiu
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Department of Medicine, Division of Infectious Diseases, University of California, San Francisco, San Francisco, CA, USA.
- Chan-Zuckerberg Biohub, San Francisco, CA, USA.
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Meisel JS, Nasko DJ, Brubach B, Cepeda-Espinoza V, Chopyk J, Corrada-Bravo H, Fedarko M, Ghurye J, Javkar K, Olson ND, Shah N, Allard SM, Bazinet AL, Bergman NH, Brown A, Caporaso JG, Conlan S, DiRuggiero J, Forry SP, Hasan NA, Kralj J, Luethy PM, Milton DK, Ondov BD, Preheim S, Ratnayake S, Rogers SM, Rosovitz MJ, Sakowski EG, Schliebs NO, Sommer DD, Ternus KL, Uritskiy G, Zhang SX, Pop M, Treangen TJ. Current progress and future opportunities in applications of bioinformatics for biodefense and pathogen detection: report from the Winter Mid-Atlantic Microbiome Meet-up, College Park, MD, January 10, 2018. Microbiome 2018; 6:197. [PMID: 30396371 PMCID: PMC6219074 DOI: 10.1186/s40168-018-0582-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 10/18/2018] [Indexed: 06/08/2023]
Abstract
The Mid-Atlantic Microbiome Meet-up (M3) organization brings together academic, government, and industry groups to share ideas and develop best practices for microbiome research. In January of 2018, M3 held its fourth meeting, which focused on recent advances in biodefense, specifically those relating to infectious disease, and the use of metagenomic methods for pathogen detection. Presentations highlighted the utility of next-generation sequencing technologies for identifying and tracking microbial community members across space and time. However, they also stressed the current limitations of genomic approaches for biodefense, including insufficient sensitivity to detect low-abundance pathogens and the inability to quantify viable organisms. Participants discussed ways in which the community can improve software usability and shared new computational tools for metagenomic processing, assembly, annotation, and visualization. Looking to the future, they identified the need for better bioinformatics toolkits for longitudinal analyses, improved sample processing approaches for characterizing viruses and fungi, and more consistent maintenance of database resources. Finally, they addressed the necessity of improving data standards to incentivize data sharing. Here, we summarize the presentations and discussions from the meeting, identifying the areas where microbiome analyses have improved our ability to detect and manage biological threats and infectious disease, as well as gaps of knowledge in the field that require future funding and focus.
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Affiliation(s)
- Jacquelyn S Meisel
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Daniel J Nasko
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Brian Brubach
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Victoria Cepeda-Espinoza
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Jessica Chopyk
- School of Public Health, University of Maryland, College Park, College Park, MD, USA
| | - Héctor Corrada-Bravo
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Marcus Fedarko
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Jay Ghurye
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Kiran Javkar
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Nathan D Olson
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nidhi Shah
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Sarah M Allard
- School of Public Health, University of Maryland, College Park, College Park, MD, USA
| | - Adam L Bazinet
- National Biodefense Analysis and Countermeasures Center, Frederick, MD, USA
| | - Nicholas H Bergman
- National Biodefense Analysis and Countermeasures Center, Frederick, MD, USA
| | - Alexis Brown
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - J Gregory Caporaso
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA
| | - Sean Conlan
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Samuel P Forry
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nur A Hasan
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
- CosmosID, Inc., Rockville, MD, USA
| | - Jason Kralj
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Paul M Luethy
- Department of Pathology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Donald K Milton
- Maryland Institute for Applied Environmental Health, School of Public Health, University of Maryland, College Park, College Park, MD, USA
| | - Brian D Ondov
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sarah Preheim
- Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | | | - M J Rosovitz
- National Biodefense Analysis and Countermeasures Center, Frederick, MD, USA
| | - Eric G Sakowski
- Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA
| | | | - Daniel D Sommer
- National Biodefense Analysis and Countermeasures Center, Frederick, MD, USA
| | | | - Gherman Uritskiy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Sean X Zhang
- Division of Medical Microbiology, Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Mihai Pop
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | - Todd J Treangen
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA.
- Present address: Department of Computer Science - MS-132, Rice University, P.O. Box 1892, Houston, TX, 77005-1892, USA.
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Abstract
When performing bioforensic casework, it is important to be able to reliably detect the presence of a particular organism in a metagenomic sample, even if the organism is only present in a trace amount. For this task, it is common to use a sequence classification program that determines the taxonomic affiliation of individual sequence reads by comparing them to reference database sequences. As metagenomic data sets often consist of millions or billions of reads that need to be compared to reference databases containing millions of sequences, such sequence classification programs typically use search heuristics and databases with reduced sequence diversity to speed up the analysis, which can lead to incorrect assignments. Thus, in a bioforensic setting where correct assignments are paramount, assignments of interest made by "first-pass" classifiers should be confirmed using the most precise methods and comprehensive databases available. In this study we present a BLAST-based method for validating the assignments made by less precise sequence classification programs, with optimal parameters for filtering of BLAST results determined via simulation of sequence reads from genomes of interest, and we apply the method to the detection of four pathogenic organisms. The software implementing the method is open source and freely available.
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Affiliation(s)
- Adam L. Bazinet
- National Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA
| | - Brian D. Ondov
- National Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA
- National Human Genome Research Institute, Bethesda, MD, USA
| | - Daniel D. Sommer
- National Biodefense Analysis and Countermeasures Center, Fort Detrick, MD, USA
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Loreille O, Ratnayake S, Bazinet AL, Stockwell TB, Sommer DD, Rohland N, Mallick S, Johnson PLF, Skoglund P, Onorato AJ, Bergman NH, Reich D, Irwin JA. Biological Sexing of a 4000-Year-Old Egyptian Mummy Head to Assess the Potential of Nuclear DNA Recovery from the Most Damaged and Limited Forensic Specimens. Genes (Basel) 2018; 9:genes9030135. [PMID: 29494531 PMCID: PMC5867856 DOI: 10.3390/genes9030135] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 02/06/2018] [Accepted: 02/06/2018] [Indexed: 12/17/2022] Open
Abstract
High throughput sequencing (HTS) has been used for a number of years in the field of paleogenomics to facilitate the recovery of small DNA fragments from ancient specimens. Recently, these techniques have also been applied in forensics, where they have been used for the recovery of mitochondrial DNA sequences from samples where traditional PCR-based assays fail because of the very short length of endogenous DNA molecules. Here, we describe the biological sexing of a ~4000-year-old Egyptian mummy using shotgun sequencing and two established methods of biological sex determination (RX and RY), by way of mitochondrial genome analysis as a means of sequence data authentication. This particular case of historical interest increases the potential utility of HTS techniques for forensic purposes by demonstrating that data from the more discriminatory nuclear genome can be recovered from the most damaged specimens, even in cases where mitochondrial DNA cannot be recovered with current PCR-based forensic technologies. Although additional work remains to be done before nuclear DNA recovered via these methods can be used routinely in operational casework for individual identification purposes, these results indicate substantial promise for the retrieval of probative individually identifying DNA data from the most limited and degraded forensic specimens.
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Affiliation(s)
- Odile Loreille
- DNA Support Unit, FBI Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA.
| | - Shashikala Ratnayake
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
| | - Adam L Bazinet
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
| | - Timothy B Stockwell
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
| | - Daniel D Sommer
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
| | - Nadin Rohland
- Department of Genetics Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
| | - Swapan Mallick
- Department of Genetics Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
| | - Philip L F Johnson
- Department of Biology, University of Maryland, 1210 Biology-Psychology Building, 4094 Campus Drive, College Park, MD 20742, USA.
| | - Pontus Skoglund
- The Francis Crick Institute, 1 Midland Rd, London NW1 1AT, UK.
| | - Anthony J Onorato
- DNA Support Unit, FBI Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA.
| | - Nicholas H Bergman
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD 21702, USA.
| | - David Reich
- Department of Genetics Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA.
- Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA.
| | - Jodi A Irwin
- DNA Support Unit, FBI Laboratory, 2501 Investigation Parkway, Quantico, VA 22135, USA.
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5
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Goodheart JA, Bazinet AL, Valdés Á, Collins AG, Cummings MP. Prey preference follows phylogeny: evolutionary dietary patterns within the marine gastropod group Cladobranchia (Gastropoda: Heterobranchia: Nudibranchia). BMC Evol Biol 2017; 17:221. [PMID: 29073890 PMCID: PMC5659023 DOI: 10.1186/s12862-017-1066-0] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [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: 05/05/2017] [Accepted: 10/15/2017] [Indexed: 12/03/2022] Open
Abstract
Background The impact of predator-prey interactions on the evolution of many marine invertebrates is poorly understood. Since barriers to genetic exchange are less obvious in the marine realm than in terrestrial or freshwater systems, non-allopatric divergence may play a fundamental role in the generation of biodiversity. In this context, shifts between major prey types could constitute important factors explaining the biodiversity of marine taxa, particularly in groups with highly specialized diets. However, the scarcity of marine specialized consumers for which reliable phylogenies exist hampers attempts to test the role of trophic specialization in evolution. In this study, RNA-Seq data is used to produce a phylogeny of Cladobranchia, a group of marine invertebrates that feed on a diverse array of prey taxa but mostly specialize on cnidarians. The broad range of prey type preferences allegedly present in two major groups within Cladobranchia suggest that prey type shifts are relatively common over evolutionary timescales. Results In the present study, we generated a well-supported phylogeny of the major lineages within Cladobranchia using RNA-Seq data, and used ancestral state reconstruction analyses to better understand the evolution of prey preference. These analyses answered several fundamental questions regarding the evolutionary relationships within Cladobranchia, including support for a clade of species from Arminidae as sister to Tritoniidae (which both preferentially prey on Octocorallia). Ancestral state reconstruction analyses supported a cladobranchian ancestor with a preference for Hydrozoa and show that the few transitions identified only occur from lineages that prey on Hydrozoa to those that feed on other types of prey. Conclusions There is strong phylogenetic correlation with prey preference within Cladobranchia, suggesting that prey type specialization within this group has inertia. Shifts between different types of prey have occurred rarely throughout the evolution of Cladobranchia, indicating that this may not have been an important driver of the diversity within this group. Electronic supplementary material The online version of this article (10.1186/s12862-017-1066-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Jessica A Goodheart
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742, USA. .,NMFS, National Systematics Laboratory, National Museum of Natural History, Smithsonian Institution, MRC-153, PO Box 37012, Washington, DC, 20013, USA.
| | - Adam L Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742, USA.,Present address: National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, MD, 21702, USA
| | - Ángel Valdés
- Department of Biological Sciences, California State Polytechnic University, 3801 W Temple Ave, Pomona, CA, 91768, USA
| | - Allen G Collins
- NMFS, National Systematics Laboratory, National Museum of Natural History, Smithsonian Institution, MRC-153, PO Box 37012, Washington, DC, 20013, USA
| | - Michael P Cummings
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742, USA
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Abstract
BACKGROUND Bacillus cereus sensu lato (s. l.) is an ecologically diverse bacterial group of medical and agricultural significance. In this study, I use publicly available genomes and novel bioinformatic workflows to characterize the B. cereus s. l. pan-genome and perform the largest phylogenetic and population genetic analyses of this group to date in terms of the number of genes and taxa included. With these fundamental data in hand, I identify genes associated with particular phenotypic traits (i.e., "pan-GWAS" analysis), and quantify the degree to which taxa sharing common attributes are phylogenetically clustered. METHODS A rapid k-mer based approach (Mash) was used to create reduced representations of selected Bacillus genomes, and a fast distance-based phylogenetic analysis of this data (FastME) was performed to determine which species should be included in B. cereus s. l. The complete genomes of eight B. cereus s. l. species were annotated de novo with Prokka, and these annotations were used by Roary to produce the B. cereus s. l. pan-genome. Scoary was used to associate gene presence and absence patterns with various phenotypes. The orthologous protein sequence clusters produced by Roary were filtered and used to build HaMStR databases of gene models that were used in turn to construct phylogenetic data matrices. Phylogenetic analyses used RAxML, DendroPy, ClonalFrameML, PAUP*, and SplitsTree. Bayesian model-based population genetic analysis assigned taxa to clusters using hierBAPS. The genealogical sorting index was used to quantify the phylogenetic clustering of taxa sharing common attributes. RESULTS The B. cereus s. l. pan-genome currently consists of ≈60,000 genes, ≈600 of which are "core" (common to at least 99% of taxa sampled). Pan-GWAS analysis revealed genes associated with phenotypes such as isolation source, oxygen requirement, and ability to cause diseases such as anthrax or food poisoning. Extensive phylogenetic analyses using an unprecedented amount of data produced phylogenies that were largely concordant with each other and with previous studies. Phylogenetic support as measured by bootstrap probabilities increased markedly when all suitable pan-genome data was included in phylogenetic analyses, as opposed to when only core genes were used. Bayesian population genetic analysis recommended subdividing the three major clades of B. cereus s. l. into nine clusters. Taxa sharing common traits and species designations exhibited varying degrees of phylogenetic clustering. CONCLUSIONS All phylogenetic analyses recapitulated two previously used classification systems, and taxa were consistently assigned to the same major clade and group. By including accessory genes from the pan-genome in the phylogenetic analyses, I produced an exceptionally well-supported phylogeny of 114 complete B. cereus s. l. genomes. The best-performing methods were used to produce a phylogeny of all 498 publicly available B. cereus s. l. genomes, which was in turn used to compare three different classification systems and to test the monophyly status of various B. cereus s. l. species. The majority of the methodology used in this study is generic and could be leveraged to produce pan-genome estimates and similarly robust phylogenetic hypotheses for other bacterial groups.
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Affiliation(s)
- Adam L Bazinet
- National Biodefense Analysis and Countermeasures Center, Fort Detrick, 21702, MD, USA.
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7
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White WT, Corrigan S, Yang L, Henderson AC, Bazinet AL, Swofford DL, Naylor GJP. Phylogeny of the manta and devilrays (Chondrichthyes: mobulidae), with an updated taxonomic arrangement for the family. Zool J Linn Soc 2017. [DOI: 10.1093/zoolinnean/zlx018] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
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8
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Corrigan S, Maisano Delser P, Eddy C, Duffy C, Yang L, Li C, Bazinet AL, Mona S, Naylor GJ. Historical introgression drives pervasive mitochondrial admixture between two species of pelagic sharks. Mol Phylogenet Evol 2017; 110:122-126. [DOI: 10.1016/j.ympev.2017.03.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Revised: 02/16/2017] [Accepted: 03/08/2017] [Indexed: 11/26/2022]
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9
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Huson DH, Tappu R, Bazinet AL, Xie C, Cummings MP, Nieselt K, Williams R. Fast and simple protein-alignment-guided assembly of orthologous gene families from microbiome sequencing reads. Microbiome 2017; 5:11. [PMID: 28122610 PMCID: PMC5267372 DOI: 10.1186/s40168-017-0233-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2016] [Accepted: 01/17/2017] [Indexed: 05/03/2023]
Abstract
BACKGROUND Microbiome sequencing projects typically collect tens of millions of short reads per sample. Depending on the goals of the project, the short reads can either be subjected to direct sequence analysis or be assembled into longer contigs. The assembly of whole genomes from metagenomic sequencing reads is a very difficult problem. However, for some questions, only specific genes of interest need to be assembled. This is then a gene-centric assembly where the goal is to assemble reads into contigs for a family of orthologous genes. METHODS We present a new method for performing gene-centric assembly, called protein-alignment-guided assembly, and provide an implementation in our metagenome analysis tool MEGAN. Genes are assembled on the fly, based on the alignment of all reads against a protein reference database such as NCBI-nr. Specifically, the user selects a gene family based on a classification such as KEGG and all reads binned to that gene family are assembled. RESULTS Using published synthetic community metagenome sequencing reads and a set of 41 gene families, we show that the performance of this approach compares favorably with that of full-featured assemblers and that of a recently published HMM-based gene-centric assembler, both in terms of the number of reference genes detected and of the percentage of reference sequence covered. CONCLUSIONS Protein-alignment-guided assembly of orthologous gene families complements whole-metagenome assembly in a new and very useful way.
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Affiliation(s)
- Daniel H Huson
- Center for Bioinformatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany.
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore.
| | - Rewati Tappu
- Center for Bioinformatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany
| | - Adam L Bazinet
- Center for Bioinformatics and Computational Biology, University of Maryland, 8314 Paint Branch Drive, College Park, MD, 20742, USA
- National Biodefense Analysis and Countermeasures Center, 8300 Research Plaza, Fort Detrick, Frederick, MD, 21702, USA
| | - Chao Xie
- Human Longevity Inc., Singapore, Singapore
| | - Michael P Cummings
- Center for Bioinformatics and Computational Biology, University of Maryland, 8314 Paint Branch Drive, College Park, MD, 20742, USA
| | - Kay Nieselt
- Center for Bioinformatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany
| | - Rohan Williams
- Life Sciences Institute, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
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Goodheart JA, Bazinet AL, Collins AG, Cummings MP. Relationships within Cladobranchia (Gastropoda: Nudibranchia) based on RNA-Seq data: an initial investigation. R Soc Open Sci 2015; 2:150196. [PMID: 26473045 PMCID: PMC4593679 DOI: 10.1098/rsos.150196] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2015] [Accepted: 08/26/2015] [Indexed: 05/28/2023]
Abstract
Cladobranchia (Gastropoda: Nudibranchia) is a diverse (approx. 1000 species) but understudied group of sea slug molluscs. In order to fully comprehend the diversity of nudibranchs and the evolution of character traits within Cladobranchia, a solid understanding of evolutionary relationships is necessary. To date, only two direct attempts have been made to understand the evolutionary relationships within Cladobranchia, neither of which resulted in well-supported phylogenetic hypotheses. In addition to these studies, several others have addressed some of the relationships within this clade while investigating the evolutionary history of more inclusive groups (Nudibranchia and Euthyneura). However, all of the resulting phylogenetic hypotheses contain conflicting topologies within Cladobranchia. In this study, we address some of these long-standing issues regarding the evolutionary history of Cladobranchia using RNA-Seq data (transcriptomes). We sequenced 16 transcriptomes and combined these with four transcriptomes from the NCBI Sequence Read Archive. Transcript assembly using Trinity and orthology determination using HaMStR yielded 839 orthologous groups for analysis. These data provide a well-supported and almost fully resolved phylogenetic hypothesis for Cladobranchia. Our results support the monophyly of Cladobranchia and the sub-clade Aeolidida, but reject the monophyly of Dendronotida.
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Affiliation(s)
- Jessica A. Goodheart
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
- NMFS, National Systematics Laboratory, National Museum of Natural History, Smithsonian Institution, MRC-153, PO Box 37012, Washington, DC 20013, USA
| | - Adam L. Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
| | - Allen G. Collins
- NMFS, National Systematics Laboratory, National Museum of Natural History, Smithsonian Institution, MRC-153, PO Box 37012, Washington, DC 20013, USA
| | - Michael P. Cummings
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
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Abstract
We introduce molecularevolution.org, a publicly available gateway for high-throughput, maximum-likelihood phylogenetic analysis powered by grid computing. The gateway features a garli 2.0 web service that enables a user to quickly and easily submit thousands of maximum likelihood tree searches or bootstrap searches that are executed in parallel on distributed computing resources. The garli web service allows one to easily specify partitioned substitution models using a graphical interface, and it performs sophisticated post-processing of phylogenetic results. Although the garli web service has been used by the research community for over three years, here we formally announce the availability of the service, describe its capabilities, highlight new features and recent improvements, and provide details about how the grid system efficiently delivers high-quality phylogenetic results. [garli, gateway, grid computing, maximum likelihood, molecular evolution portal, phylogenetics, web service.]
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Affiliation(s)
- Adam L Bazinet
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA
| | - Derrick J Zwickl
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA
| | - Michael P Cummings
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, 20742-3360, USA, and Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721-0088, USA
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Bazinet AL, Cummings MP, Mitter KT, Mitter CW. Can RNA-Seq resolve the rapid radiation of advanced moths and butterflies (Hexapoda: Lepidoptera: Apoditrysia)? An exploratory study. PLoS One 2013; 8:e82615. [PMID: 24324810 PMCID: PMC3853519 DOI: 10.1371/journal.pone.0082615] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2013] [Accepted: 10/23/2013] [Indexed: 11/19/2022] Open
Abstract
Recent molecular phylogenetic studies of the insect order Lepidoptera have robustly resolved family-level divergences within most superfamilies, and most divergences among the relatively species-poor early-arising superfamilies. In sharp contrast, relationships among the superfamilies of more advanced moths and butterflies that comprise the mega-diverse clade Apoditrysia (ca. 145,000 spp.) remain mostly poorly supported. This uncertainty, in turn, limits our ability to discern the origins, ages and evolutionary consequences of traits hypothesized to promote the spectacular diversification of Apoditrysia. Low support along the apoditrysian "backbone" probably reflects rapid diversification. If so, it may be feasible to strengthen resolution by radically increasing the gene sample, but case studies have been few. We explored the potential of next-generation sequencing to conclusively resolve apoditrysian relationships. We used transcriptome RNA-Seq to generate 1579 putatively orthologous gene sequences across a broad sample of 40 apoditrysians plus four outgroups, to which we added two taxa from previously published data. Phylogenetic analysis of a 46-taxon, 741-gene matrix, resulting from a strict filter that eliminated ortholog groups containing any apparent paralogs, yielded dramatic overall increase in bootstrap support for deeper nodes within Apoditrysia as compared to results from previous and concurrent 19-gene analyses. High support was restricted mainly to the huge subclade Obtectomera broadly defined, in which 11 of 12 nodes subtending multiple superfamilies had bootstrap support of 100%. The strongly supported nodes showed little conflict with groupings from previous studies, and were little affected by changes in taxon sampling, suggesting that they reflect true signal rather than artifacts of massive gene sampling. In contrast, strong support was seen at only 2 of 11 deeper nodes among the "lower", non-obtectomeran apoditrysians. These represent a much harder phylogenetic problem, for which one path to resolution might include further increase in gene sampling, together with improved orthology assignments.
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Affiliation(s)
- Adam L. Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America
| | - Michael P. Cummings
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America
| | - Kim T. Mitter
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
| | - Charles W. Mitter
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
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Regier JC, Mitter C, Zwick A, Bazinet AL, Cummings MP, Kawahara AY, Sohn JC, Zwickl DJ, Cho S, Davis DR, Baixeras J, Brown J, Parr C, Weller S, Lees DC, Mitter KT. A large-scale, higher-level, molecular phylogenetic study of the insect order Lepidoptera (moths and butterflies). PLoS One 2013; 8:e58568. [PMID: 23554903 PMCID: PMC3595289 DOI: 10.1371/journal.pone.0058568] [Citation(s) in RCA: 166] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2012] [Accepted: 02/05/2013] [Indexed: 01/22/2023] Open
Abstract
Background Higher-level relationships within the Lepidoptera, and particularly within the species-rich subclade Ditrysia, are generally not well understood, although recent studies have yielded progress. We present the most comprehensive molecular analysis of lepidopteran phylogeny to date, focusing on relationships among superfamilies. Methodology / Principal Findings 483 taxa spanning 115 of 124 families were sampled for 19 protein-coding nuclear genes, from which maximum likelihood tree estimates and bootstrap percentages were obtained using GARLI. Assessment of heuristic search effectiveness showed that better trees and higher bootstrap percentages probably remain to be discovered even after 1000 or more search replicates, but further search proved impractical even with grid computing. Other analyses explored the effects of sampling nonsynonymous change only versus partitioned and unpartitioned total nucleotide change; deletion of rogue taxa; and compositional heterogeneity. Relationships among the non-ditrysian lineages previously inferred from morphology were largely confirmed, plus some new ones, with strong support. Robust support was also found for divergences among non-apoditrysian lineages of Ditrysia, but only rarely so within Apoditrysia. Paraphyly for Tineoidea is strongly supported by analysis of nonsynonymous-only signal; conflicting, strong support for tineoid monophyly when synonymous signal was added back is shown to result from compositional heterogeneity. Conclusions / Significance Support for among-superfamily relationships outside the Apoditrysia is now generally strong. Comparable support is mostly lacking within Apoditrysia, but dramatically increased bootstrap percentages for some nodes after rogue taxon removal, and concordance with other evidence, strongly suggest that our picture of apoditrysian phylogeny is approximately correct. This study highlights the challenge of finding optimal topologies when analyzing hundreds of taxa. It also shows that some nodes get strong support only when analysis is restricted to nonsynonymous change, while total change is necessary for strong support of others. Thus, multiple types of analyses will be necessary to fully resolve lepidopteran phylogeny.
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Affiliation(s)
- Jerome C. Regier
- Institute for Bioscience and Biotechnology Research, University of Maryland, College Park, Maryland, United States of America
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
- * E-mail: (JCR); (CM)
| | - Charles Mitter
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
- * E-mail: (JCR); (CM)
| | - Andreas Zwick
- Entomology, State Museum of Natural History, Stuttgart, Germany
| | - Adam L. Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America
| | - Michael P. Cummings
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, United States of America
| | - Akito Y. Kawahara
- Florida Museum of Natural History, Gainesville, Florida, United States of America
| | - Jae-Cheon Sohn
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
| | - Derrick J. Zwickl
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona, United States of America
| | - Soowon Cho
- Department of Plant Medicine, Chungbuk National University, Cheongju, Korea
| | - Donald R. Davis
- Department of Entomology, Smithsonian Institution, Washington, District of Columbia, United States of America
| | - Joaquin Baixeras
- Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Valencia, Spain
| | - John Brown
- Systematic Entomology Lab, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America
| | - Cynthia Parr
- Encyclopedia of Life, Smithsonian Institution, Washington, District of Columbia, United States of America
| | - Susan Weller
- Department of Entomology, University of Minnesota, Saint Paul, Minnesota, United States of America
| | - David C. Lees
- Department of Life Sciences, Natural History Museum, London, England
| | - Kim T. Mitter
- Department of Entomology, University of Maryland, College Park, Maryland, United States of America
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Abstract
Background A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics). Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for ’barcoding genes’ like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis. Results We divided the very large number of programs that have been released in recent years for solving the sequence classification problem into three main categories based on the general algorithm they use to compare a query sequence against a database of sequences. We also evaluated the performance of the leading programs in each category on data sets whose taxonomic and functional composition is known. Conclusions We found significant variability in classification accuracy, precision, and resource consumption of sequence classification programs when used to analyze various metagenomics data sets. However, we observe some general trends and patterns that will be useful to researchers who use sequence classification programs.
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Affiliation(s)
- Adam L Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20874, USA.
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15
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Regier JC, Zwick A, Cummings MP, Kawahara AY, Cho S, Weller S, Roe A, Baixeras J, Brown JW, Parr C, Davis DR, Epstein M, Hallwachs W, Hausmann A, Janzen DH, Kitching IJ, Solis MA, Yen SH, Bazinet AL, Mitter C. Toward reconstructing the evolution of advanced moths and butterflies (Lepidoptera: Ditrysia): an initial molecular study. BMC Evol Biol 2009; 9:280. [PMID: 19954545 PMCID: PMC2796670 DOI: 10.1186/1471-2148-9-280] [Citation(s) in RCA: 124] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2009] [Accepted: 12/02/2009] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In the mega-diverse insect order Lepidoptera (butterflies and moths; 165,000 described species), deeper relationships are little understood within the clade Ditrysia, to which 98% of the species belong. To begin addressing this problem, we tested the ability of five protein-coding nuclear genes (6.7 kb total), and character subsets therein, to resolve relationships among 123 species representing 27 (of 33) superfamilies and 55 (of 100) families of Ditrysia under maximum likelihood analysis. RESULTS Our trees show broad concordance with previous morphological hypotheses of ditrysian phylogeny, although most relationships among superfamilies are weakly supported. There are also notable surprises, such as a consistently closer relationship of Pyraloidea than of butterflies to most Macrolepidoptera. Monophyly is significantly rejected by one or more character sets for the putative clades Macrolepidoptera as currently defined (P < 0.05) and Macrolepidoptera excluding Noctuoidea and Bombycoidea sensu lato (P < or = 0.005), and nearly so for the superfamily Drepanoidea as currently defined (P < 0.08). Superfamilies are typically recovered or nearly so, but usually without strong support. Relationships within superfamilies and families, however, are often robustly resolved. We provide some of the first strong molecular evidence on deeper splits within Pyraloidea, Tortricoidea, Geometroidea, Noctuoidea and others.Separate analyses of mostly synonymous versus non-synonymous character sets revealed notable differences (though not strong conflict), including a marked influence of compositional heterogeneity on apparent signal in the third codon position (nt3). As available model partitioning methods cannot correct for this variation, we assessed overall phylogeny resolution through separate examination of trees from each character set. Exploration of "tree space" with GARLI, using grid computing, showed that hundreds of searches are typically needed to find the best-feasible phylogeny estimate for these data. CONCLUSION Our results (a) corroborate the broad outlines of the current working phylogenetic hypothesis for Ditrysia, (b) demonstrate that some prominent features of that hypothesis, including the position of the butterflies, need revision, and (c) resolve the majority of family and subfamily relationships within superfamilies as thus far sampled. Much further gene and taxon sampling will be needed, however, to strongly resolve individual deeper nodes.
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Affiliation(s)
- Jerome C Regier
- Center for Biosystems Research, University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA
| | - Andreas Zwick
- Center for Biosystems Research, University of Maryland Biotechnology Institute, College Park, Maryland 20742, USA
| | - Michael P Cummings
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA
| | - Akito Y Kawahara
- Department of Entomology, University of Maryland, College Park, Maryland 20742, USA
| | - Soowon Cho
- Department of Entomology, University of Maryland, College Park, Maryland 20742, USA
- Department of Plant Medicine, Chungbuk National University, Cheongju 361-763, Korea
| | - Susan Weller
- Department of Entomology, University of Minnesota, St. Paul, Minnesota 55455, USA
| | - Amanda Roe
- Department of Entomology, University of Minnesota, St. Paul, Minnesota 55455, USA
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta T6G 2E9, Canada
| | - Joaquin Baixeras
- Cavanilles Institute of Biodiversity and Evolutionary Biology, University of Valencia, Apartat de correus 2085, 46071 Valencia, Spain
| | - John W Brown
- Systematic Entomology Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland 20705, USA
| | - Cynthia Parr
- Encyclopedia of Life, Smithsonian Institution, Washington, D.C. 20013-7012, USA
| | - Donald R Davis
- Department of Entomology, Smithsonian Institution, Washington, D.C. 20013-7012, USA
| | - Marc Epstein
- Plant Pest Diagnostics Branch, California Department of Food and Agriculture, 3294 Meadowview Road, Sacramento, California 95832-1448, USA
| | - Winifred Hallwachs
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Axel Hausmann
- Bavarian State Collection of Zoology, Münchhausenstrasse 21, D-81247 München, Germany
| | - Daniel H Janzen
- Department of Biology, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Ian J Kitching
- Department of Entomology, The Natural History Museum, Cromwell Road, London SW7 5BD, UK
| | - M Alma Solis
- Systematic Entomology Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland 20705, USA
| | - Shen-Horn Yen
- Department of Biological Sciences, National Sun Yat-Sen University, Kaohsiung 804, Taiwan
| | - Adam L Bazinet
- Laboratory of Molecular Evolution, Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland 20742, USA
| | - Charles Mitter
- Department of Entomology, University of Maryland, College Park, Maryland 20742, USA
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