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Artikel ; Online: Making the most of genomic data with OMA.

Glover, Natasha M

2020 Band 9, Seite(n) 665

Abstract: The OMA Collection is a resource for users of Orthologous Matrix. In this collection, we provide tutorials and protocols on how to leverage the tools provided by OMA to analyse your data. Here, I explain the motivation for this collection and its ... ...

Abstract	The OMA Collection is a resource for users of Orthologous Matrix. In this collection, we provide tutorials and protocols on how to leverage the tools provided by OMA to analyse your data. Here, I explain the motivation for this collection and its published works thus far.
Mesh-Begriff(e)	Databases, Genetic ; Genomics ; Software
Sprache	Englisch
Erscheinungsdatum	2020-07-01
Erscheinungsland	England
Dokumenttyp	Editorial ; Research Support, Non-U.S. Gov't
ZDB-ID	2699932-8
ISSN	2046-1402 ; 2046-1402
ISSN (online)	2046-1402
ISSN	2046-1402
DOI	10.12688/f1000research.24904.1
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: DrosOMA: the

Thiébaut, Antonin / Altenhoff, Adrian M / Campli, Giulia / Glover, Natasha / Dessimoz, Christophe / Waterhouse, Robert M

F1000Research

2024 Band 12, Seite(n) 936

Abstract: Background: Comparative genomic analyses to delineate gene evolutionary histories inform the understanding of organismal biology by characterising gene and gene family origins, trajectories, and dynamics, as well as enabling the tracing of speciation, ... ...

Abstract	Background: Comparative genomic analyses to delineate gene evolutionary histories inform the understanding of organismal biology by characterising gene and gene family origins, trajectories, and dynamics, as well as enabling the tracing of speciation, duplication, and loss events, and facilitating the transfer of gene functional information across species. Genomic data are available for an increasing number of species from the genus Drosophila, however, a dedicated resource exploiting these data to provide the research community with browsable results from genus-wide orthology delineation has been lacking. Methods: Using the OMA Orthologous Matrix orthology inference approach and browser deployment framework, we catalogued orthologues across a selected set of Drosophila species with high-quality annotated genomes. We developed and deployed a dedicated instance of the OMA browser to facilitate intuitive exploration, visualisation, and downloading of the genus-wide orthology delineation results. Results: DrosOMA - the Drosophila Orthologous Matrix browser, accessible from https://drosoma.dcsr.unil.ch/ - presents the results of orthology delineation for 36 drosophilids from across the genus and four outgroup dipterans. It enables querying and browsing of the orthology data through a feature-rich web interface, with gene-view, orthologous group-view, and genome-view pages, including comprehensive gene name and identifier cross-references together with available functional annotations and protein domain architectures, as well as tools to visualise local and global synteny conservation. Conclusions: The DrosOMA browser demonstrates the deployability of the OMA browser framework for building user-friendly orthology databases with dense sampling of a selected taxonomic group. It provides the Drosophila research community with a tailored resource of browsable results from genus-wide orthology delineation.
Mesh-Begriff(e)	Animals ; Drosophila/genetics ; Comparative Genomic Hybridization ; Databases, Factual ; Evolution, Molecular ; Genomics
Sprache	Englisch
Erscheinungsdatum	2024-01-16
Erscheinungsland	England
Dokumenttyp	Journal Article
ZDB-ID	2699932-8
ISSN	2046-1402 ; 2046-1402
ISSN (online)	2046-1402
ISSN	2046-1402
DOI	10.12688/f1000research.135250.2
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Protein length distribution is remarkably uniform across the tree of life.

Nevers, Yannis / Glover, Natasha M / Dessimoz, Christophe / Lecompte, Odile

Genome biology

2023 Band 24, Heft 1, Seite(n) 135

Abstract: Background: In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the ... ...

Abstract	Background: In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species but has so far been scarcely studied. Results: Here we evaluate this diversity by comparing protein length distribution across 2326 species (1688 bacteria, 153 archaea, and 485 eukaryotes). We find that proteins tend to be on average slightly longer in eukaryotes than in bacteria or archaea, but that the variation of length distribution across species is low, especially compared to the variation of other genomic features (genome size, number of proteins, gene length, GC content, isoelectric points of proteins). Moreover, most cases of atypical protein length distribution appear to be due to artifactual gene annotation, suggesting the actual variation of protein length distribution across species is even smaller. Conclusions: These results open the way for developing a genome annotation quality metric based on protein length distribution to complement conventional quality measures. Overall, our findings show that protein length distribution between living species is more uniform than previously thought. Furthermore, we also provide evidence for a universal selection on protein length, yet its mechanism and fitness effect remain intriguing open questions.
Mesh-Begriff(e)	Amino Acid Sequence ; Molecular Sequence Annotation/methods ; Proteins/chemistry ; Proteins/classification ; Proteome ; Sequence Analysis, Protein/methods ; Eukaryota ; Bacteria ; Archaea
Chemische Substanzen	Proteins ; Proteome
Sprache	Englisch
Erscheinungsdatum	2023-06-08
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/s13059-023-02973-2
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Protein length distribution is remarkably uniform across the tree of life

Yannis Nevers / Natasha M. Glover / Christophe Dessimoz / Odile Lecompte

Genome Biology, Vol 24, Iss 1, Pp 1-

2023 Band 20

Abstract: Abstract Background In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, ... ...

Abstract	Abstract Background In every living species, the function of a protein depends on its organization of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species but has so far been scarcely studied. Results Here we evaluate this diversity by comparing protein length distribution across 2326 species (1688 bacteria, 153 archaea, and 485 eukaryotes). We find that proteins tend to be on average slightly longer in eukaryotes than in bacteria or archaea, but that the variation of length distribution across species is low, especially compared to the variation of other genomic features (genome size, number of proteins, gene length, GC content, isoelectric points of proteins). Moreover, most cases of atypical protein length distribution appear to be due to artifactual gene annotation, suggesting the actual variation of protein length distribution across species is even smaller. Conclusions These results open the way for developing a genome annotation quality metric based on protein length distribution to complement conventional quality measures. Overall, our findings show that protein length distribution between living species is more uniform than previously thought. Furthermore, we also provide evidence for a universal selection on protein length, yet its mechanism and fitness effect remain intriguing open questions.
Schlagwörter	Genome evolution ; Comparative genomics ; Protein length ; Genome annotation ; Biology (General) ; QH301-705.5 ; Genetics ; QH426-470
Thema/Rubrik (Code)	612
Sprache	Englisch
Erscheinungsdatum	2023-06-01T00:00:00Z
Verlag	BMC
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel ; Online: Quality assessment of gene repertoire annotations with OMArk.

Nevers, Yannis / Warwick Vesztrocy, Alex / Rossier, Victor / Train, Clément-Marie / Altenhoff, Adrian / Dessimoz, Christophe / Glover, Natasha M

Nature biotechnology

2024

Abstract: In the era of biodiversity genomics, it is crucial to ensure that annotations of protein-coding gene repertoires are accurate. State-of-the-art tools to assess genome annotations measure the completeness of a gene repertoire but are blind to other errors, ...

Abstract	In the era of biodiversity genomics, it is crucial to ensure that annotations of protein-coding gene repertoires are accurate. State-of-the-art tools to assess genome annotations measure the completeness of a gene repertoire but are blind to other errors, such as gene overprediction or contamination. We introduce OMArk, a software package that relies on fast, alignment-free sequence comparisons between a query proteome and precomputed gene families across the tree of life. OMArk assesses not only the completeness but also the consistency of the gene repertoire as a whole relative to closely related species and reports likely contamination events. Analysis of 1,805 UniProt Eukaryotic Reference Proteomes with OMArk demonstrated strong evidence of contamination in 73 proteomes and identified error propagation in avian gene annotation resulting from the use of a fragmented zebra finch proteome as a reference. This study illustrates the importance of comparing and prioritizing proteomes based on their quality measures.
Sprache	Englisch
Erscheinungsdatum	2024-02-21
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	1311932-1
ISSN	1546-1696 ; 1087-0156
ISSN (online)	1546-1696
ISSN	1087-0156
DOI	10.1038/s41587-024-02147-w
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Identifying orthologs with OMA: A primer.

Zahn-Zabal, Monique / Dessimoz, Christophe / Glover, Natasha M

F1000Research

2020 Band 9, Seite(n) 27

Abstract: The Orthologous Matrix (OMA) is a method and database that allows users to identify orthologs among many genomes. OMA provides three different types of orthologs: pairwise orthologs, OMA Groups and Hierarchical Orthologous Groups (HOGs). This Primer is ... ...

Abstract	The Orthologous Matrix (OMA) is a method and database that allows users to identify orthologs among many genomes. OMA provides three different types of orthologs: pairwise orthologs, OMA Groups and Hierarchical Orthologous Groups (HOGs). This Primer is organized in two parts. In the first part, we provide all the necessary background information to understand the concepts of orthology, how we infer them and the different subtypes of orthology in OMA, as well as what types of analyses they should be used for. In the second part, we describe protocols for using the OMA browser to find a specific gene and its various types of orthologs. By the end of the Primer, readers should be able to (i) understand homology and the different types of orthologs reported in OMA, (ii) understand the best type of orthologs to use for a particular analysis; (iii) find particular genes of interest in the OMA browser; and (iv) identify orthologs for a given gene. The data can be freely accessed from the OMA browser at https://omabrowser.org.
Mesh-Begriff(e)	Computational Biology ; Genome ; Genomics/methods ; Software
Sprache	Englisch
Erscheinungsdatum	2020-01-17
Erscheinungsland	England
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2699932-8
ISSN	2046-1402 ; 2046-1402
ISSN (online)	2046-1402
ISSN	2046-1402
DOI	10.12688/f1000research.21508.1
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel: Assigning confidence scores to homoeologs using fuzzy logic.

Glover, Natasha M / Altenhoff, Adrian / Dessimoz, Christophe

PeerJ

2019 Band 6, Seite(n) e6231

Abstract: In polyploid genomes, homoeologs are a specific subtype of homologs, and can be thought of as orthologs between subgenomes. In Orthologous MAtrix, we infer homoeologs in three polyploid plant species: upland cotton ( ...

Abstract	In polyploid genomes, homoeologs are a specific subtype of homologs, and can be thought of as orthologs between subgenomes. In Orthologous MAtrix, we infer homoeologs in three polyploid plant species: upland cotton (
Sprache	Englisch
Erscheinungsdatum	2019-01-11
Erscheinungsland	United States
Dokumenttyp	Journal Article
ZDB-ID	2703241-3
ISSN	2167-8359
ISSN	2167-8359
DOI	10.7717/peerj.6231
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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Artikel ; Online: Identifying orthologs with OMA

Monique Zahn-Zabal / Christophe Dessimoz / Natasha M. Glover

F1000Research, Vol

A primer [version 1; peer review: 2 approved]

2020 Band 9

Abstract	The Orthologous Matrix (OMA) is a method and database that allows users to identify orthologs among many genomes. OMA provides three different types of orthologs: pairwise orthologs, OMA Groups and Hierarchical Orthologous Groups (HOGs). This Primer is organized in two parts. In the first part, we provide all the necessary background information to understand the concepts of orthology, how we infer them and the different subtypes of orthology in OMA, as well as what types of analyses they should be used for. In the second part, we describe protocols for using the OMA browser to find a specific gene and its various types of orthologs. By the end of the Primer, readers should be able to (i) understand homology and the different types of orthologs reported in OMA, (ii) understand the best type of orthologs to use for a particular analysis; (iii) find particular genes of interest in the OMA browser; and (iv) identify orthologs for a given gene. The data can be freely accessed from the OMA browser at https://omabrowser.org.
Schlagwörter	Medicine ; R ; Science ; Q
Thema/Rubrik (Code)	028
Sprache	Englisch
Erscheinungsdatum	2020-01-01T00:00:00Z
Verlag	F1000 Research Ltd
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel ; Online: How to build phylogenetic species trees with OMA [version 2; peer review

Yannis Nevers / David Dylus / Natasha M. Glover / Antoine Gürtler / Christophe Dessimoz / Adrian M. Altenhoff

F1000Research, Vol

2 approved]

2022 Band 9

Abstract: Knowledge of species phylogeny is critical to many fields of biology. In an era of genome data availability, the most common way to make a phylogenetic species tree is by using multiple protein-coding genes, conserved in multiple species. This ... ...

Abstract	Knowledge of species phylogeny is critical to many fields of biology. In an era of genome data availability, the most common way to make a phylogenetic species tree is by using multiple protein-coding genes, conserved in multiple species. This methodology is composed of several steps: orthology inference, multiple sequence alignment and inference of the phylogeny with dedicated tools. This can be a difficult task, and orthology inference, in particular, is usually computationally intensive and error prone if done ad hoc. This tutorial provides protocols to make use of OMA Orthologous Groups, a set of genes all orthologous to each other, to infer a phylogenetic species tree. It is designed to be user-friendly and computationally inexpensive, by providing two options: (1) Using only precomputed groups with species available on the OMA Browser, or (2) Computing orthologs using OMA Standalone for additional species, with the option of using precomputed orthology relations for those present in OMA. A protocol for downstream analyses is provided as well, including creating a supermatrix, tree inference, and visualization. All protocols use publicly available software, and we provide scripts and code snippets to facilitate data handling. The protocols are accompanied with practical examples.
Schlagwörter	phylogenetics ; phylogenomics ; species tree ; OMA ; Orthologous Matrix ; eng ; Medicine ; R ; Science ; Q
Thema/Rubrik (Code)	590 ; 580
Sprache	Englisch
Erscheinungsdatum	2022-02-01T00:00:00Z
Verlag	F1000 Research Ltd
Dokumenttyp	Artikel ; Online
Datenquelle	BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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Artikel ; Online: Inferring Orthology and Paralogy.

Altenhoff, Adrian M / Glover, Natasha M / Dessimoz, Christophe

Methods in molecular biology (Clifton, N.J.)

2019 Band 1910, Seite(n) 149–175

Abstract: The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide ... ...

Abstract	The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments.
Mesh-Begriff(e)	Algorithms ; Animals ; Computational Biology/methods ; Evolution, Molecular ; Genome ; Genomics/methods ; Humans ; Multigene Family ; Phylogeny
Sprache	Englisch
Erscheinungsdatum	2019-07-05
Erscheinungsland	United States
Dokumenttyp	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1940-6029
ISSN (online)	1940-6029
DOI	10.1007/978-1-4939-9074-0_5
Datenquelle	MEDical Literature Analysis and Retrieval System OnLINE

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