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Brůna T, Lomsadze A, Borodovsky M. GeneMark-ETP significantly improves the accuracy of automatic annotation of large eukaryotic genomes. Genome Res 2024; 34:757-768. [PMID: 38866548 PMCID: PMC11216313 DOI: 10.1101/gr.278373.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Accepted: 05/02/2024] [Indexed: 06/14/2024]
Abstract
Large-scale genomic initiatives, such as the Earth BioGenome Project, require efficient methods for eukaryotic genome annotation. Here we present an automatic gene finder, GeneMark-ETP, integrating genomic-, transcriptomic-, and protein-derived evidence that has been developed with a focus on large plant and animal genomes. GeneMark-ETP first identifies genomic loci where extrinsic data are sufficient for making gene predictions with "high confidence." The genes situated in the genomic space between the high-confidence genes are predicted in the next stage. The set of high-confidence genes serves as an initial training set for the statistical model. Further on, the model parameters are iteratively updated in the rounds of gene prediction and parameter re-estimation. Upon reaching convergence, GeneMark-ETP makes the final predictions and delivers the whole complement of predicted genes. GeneMark-ETP outperforms gene finders using a single type of extrinsic evidence. Comparisons with gene finders MAKER2 and TSEBRA, those that use both transcript- and protein-derived extrinsic evidence, show that GeneMark-ETP delivers state-of-the-art gene-prediction accuracy, with the margin of outperforming existing approaches increasing in its application to larger and more complex eukaryotic genomes.
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Affiliation(s)
- Tomáš Brůna
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Alexandre Lomsadze
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
| | - Mark Borodovsky
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA;
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, USA
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Cleary AM, Farmer AD. Genome Context Viewer (GCV) version 2: enhanced visual exploration of multiple annotated genomes. Nucleic Acids Res 2023:7173788. [PMID: 37207325 DOI: 10.1093/nar/gkad391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/21/2023] [Accepted: 05/08/2023] [Indexed: 05/21/2023] Open
Abstract
The Genome Context Viewer is a web application for identifying, aligning, and visualizing genomic regions based on their micro and macrosyntenic structures. By using functional elements such as gene annotations as the unit of search and comparison, the Genome Context Viewer can compute and display relationships between regions across many assemblies from federated data sources in real-time, enabling users to rapidly explore multiple annotated genomes and identify divergence and structural events that can help provide insight into evolutionary mechanisms associated with functional consequences. In this work, we introduce version 2 of the Genome Context Viewer and highlight new features that enhance usability, performance, and ease of deployment.
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Affiliation(s)
- Alan M Cleary
- National Center for Genome Resources, 2935 Rodeo Park Dr E, Santa Fe, NM 87505, USA
| | - Andrew D Farmer
- National Center for Genome Resources, 2935 Rodeo Park Dr E, Santa Fe, NM 87505, USA
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Dong Y, Li C, Kim K, Cui L, Liu X. Genome annotation of disease-causing microorganisms. Brief Bioinform 2021; 22:845-854. [PMID: 33537706 PMCID: PMC7986607 DOI: 10.1093/bib/bbab004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 12/23/2020] [Accepted: 01/03/2021] [Indexed: 11/13/2022] Open
Abstract
Humans have coexisted with pathogenic microorganisms throughout its history of evolution. We have never halted the exploration of pathogenic microorganisms. With the improvement of genome-sequencing technology and the continuous reduction of sequencing costs, an increasing number of complete genome sequences of pathogenic microorganisms have become available. Genome annotation of this massive sequence information has become a daunting task in biological research. This paper summarizes the approaches to the genome annotation of pathogenic microorganisms and the available popular genome annotation tools for prokaryotes, eukaryotes and viruses. Furthermore, real-world comparisons of different annotation tools using 12 genomes from prokaryotes, eukaryotes and viruses were conducted. Current challenges and problems were also discussed.
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Affiliation(s)
- Yibo Dong
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Chang Li
- College of Public Health, University of South Florida, Tampa, FL, USA
| | - Kami Kim
- Division of Infectious Disease and International Medicine, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Liwang Cui
- Division of Infectious Disease and International Medicine, Department of Internal Medicine, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Xiaoming Liu
- College of Public Health, University of South Florida, Tampa, FL, USA
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Khan AK, Kausar H, Jaferi SS, Drouet S, Hano C, Abbasi BH, Anjum S. An Insight into the Algal Evolution and Genomics. Biomolecules 2020; 10:E1524. [PMID: 33172219 PMCID: PMC7694994 DOI: 10.3390/biom10111524] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 11/02/2020] [Accepted: 11/05/2020] [Indexed: 01/06/2023] Open
Abstract
With the increase in biotechnological, environmental, and nutraceutical importance of algae, about 100 whole genomic sequences of algae have been published, and this figure is expected to double in the coming years. The phenotypic and ecological diversity among algae hints at the range of functional capabilities encoded by algal genomes. In order to explore the biodiversity of algae and fully exploit their commercial potential, understanding their evolutionary, structural, functional, and developmental aspects at genomic level is a pre-requisite. So forth, the algal genomic analysis revealed us that algae evolved through endosymbiotic gene transfer, giving rise to around eight phyla. Amongst the diverse algal species, the unicellular green algae Chlamydomonas reinhardtii has attained the status of model organism as it is an ideal organism to elucidate the biological processes critical to plants and animals, as well as commercialized to produce range of bio-products. For this review, an overview of evolutionary process of algae through endosymbiosis in the light of genomics, as well as the phylogenomic, studies supporting the evolutionary process of algae was reviewed. Algal genomics not only helped us to understand the evolutionary history of algae but also may have an impact on our future by helping to create algae-based products and future biotechnological approaches.
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Affiliation(s)
- Amna Komal Khan
- Department of Biotechnology, Kinnaird College for Women, Lahore 54000, Pakistan; (A.K.K.); (H.K.); (S.S.J.)
| | - Humera Kausar
- Department of Biotechnology, Kinnaird College for Women, Lahore 54000, Pakistan; (A.K.K.); (H.K.); (S.S.J.)
| | - Syyada Samra Jaferi
- Department of Biotechnology, Kinnaird College for Women, Lahore 54000, Pakistan; (A.K.K.); (H.K.); (S.S.J.)
| | - Samantha Drouet
- Laboratoire de Biologie des Ligneux et des Grandes Cultures (LBLGC), INRAE USC1328, Université d’Orléans, 28000 Chartres, France; (S.D.); (C.H.)
| | - Christophe Hano
- Laboratoire de Biologie des Ligneux et des Grandes Cultures (LBLGC), INRAE USC1328, Université d’Orléans, 28000 Chartres, France; (S.D.); (C.H.)
| | - Bilal Haider Abbasi
- Department of Biotechnology, Quaid-i-Azam University, Islamabad 45320, Pakistan;
| | - Sumaira Anjum
- Department of Biotechnology, Kinnaird College for Women, Lahore 54000, Pakistan; (A.K.K.); (H.K.); (S.S.J.)
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Jung H, Ventura T, Chung JS, Kim WJ, Nam BH, Kong HJ, Kim YO, Jeon MS, Eyun SI. Twelve quick steps for genome assembly and annotation in the classroom. PLoS Comput Biol 2020; 16:e1008325. [PMID: 33180771 PMCID: PMC7660529 DOI: 10.1371/journal.pcbi.1008325] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Eukaryotic genome sequencing and de novo assembly, once the exclusive domain of well-funded international consortia, have become increasingly affordable, thus fitting the budgets of individual research groups. Third-generation long-read DNA sequencing technologies are increasingly used, providing extensive genomic toolkits that were once reserved for a few select model organisms. Generating high-quality genome assemblies and annotations for many aquatic species still presents significant challenges due to their large genome sizes, complexity, and high chromosome numbers. Indeed, selecting the most appropriate sequencing and software platforms and annotation pipelines for a new genome project can be daunting because tools often only work in limited contexts. In genomics, generating a high-quality genome assembly/annotation has become an indispensable tool for better understanding the biology of any species. Herein, we state 12 steps to help researchers get started in genome projects by presenting guidelines that are broadly applicable (to any species), sustainable over time, and cover all aspects of genome assembly and annotation projects from start to finish. We review some commonly used approaches, including practical methods to extract high-quality DNA and choices for the best sequencing platforms and library preparations. In addition, we discuss the range of potential bioinformatics pipelines, including structural and functional annotations (e.g., transposable elements and repetitive sequences). This paper also includes information on how to build a wide community for a genome project, the importance of data management, and how to make the data and results Findable, Accessible, Interoperable, and Reusable (FAIR) by submitting them to a public repository and sharing them with the research community.
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Affiliation(s)
- Hyungtaek Jung
- School of Biological Sciences, The University of Queensland, St Lucia, Queensland, Australia
- Centre for Agriculture and Bioeconomy, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Tomer Ventura
- Genecology Research Centre, School of Science and Engineering, University of the Sunshine Coast, Sippy Downs, Queensland, Australia
| | - J. Sook Chung
- Institute of Marine and Environmental Technology, University of Maryland Center for Environmental Science, Baltimore, Maryland, United States of America
| | - Woo-Jin Kim
- Genetics and Breeding Research Center, National Institute of Fisheries Science, Geoje, Korea
| | - Bo-Hye Nam
- Biotechnology Research Division, National Institute of Fisheries Science, Busan, Korea
| | - Hee Jeong Kong
- Biotechnology Research Division, National Institute of Fisheries Science, Busan, Korea
| | - Young-Ok Kim
- Biotechnology Research Division, National Institute of Fisheries Science, Busan, Korea
| | - Min-Seung Jeon
- Department of Life Science, Chung-Ang University, Seoul, Korea
| | - Seong-il Eyun
- Department of Life Science, Chung-Ang University, Seoul, Korea
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