Advances and Applications in the Quest for Orthologs.
- Glover N Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Dessimoz C Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.
- Ebersberger I Applied Bioinformatics Group, Institute of Cell Biology and Neuroscience, Goethe University Frankfurt, Frankfurt, Germany.
- Forslund SK Experimental and Clinical Research Center, A Cooperation of Charité-Universitätsmedizin Berlin and Max Delbruck Center for Molecular Medicine, Berlin, Germany.
- Gabaldón T Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Spain.
- Huerta-Cepas J Structural and Computational Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany.
- Martin MJ European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
- Muffato M European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
- Patricio M European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
- Pereira C Eura Nova, Marseille, France.
- da Silva AS European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom.
- Wang Y Department of Microbiology and Plant Pathology, Institute for Integrative Genome Biology, University of California-Riverside, Riverside, CA.
- Sonnhammer E Science for Life Laboratory, Department of Biochemistry and Biophysics, Stockholm University, Solna, Sweden.
- Thomas PD Division of Bioinformatics, Department of Preventive Medicine, University of Southern California, Los Angeles, CA.
- 2019-06-27
Published in:
- Molecular biology and evolution. - 2019
gene family
genome evolution
orthology
Algorithms
Animals
Evolution, Molecular
Genomics
Humans
Multigene Family
English
Gene families evolve by the processes of speciation (creating orthologs), gene duplication (paralogs), and horizontal gene transfer (xenologs), in addition to sequence divergence and gene loss. Orthologs in particular play an essential role in comparative genomics and phylogenomic analyses. With the continued sequencing of organisms across the tree of life, the data are available to reconstruct the unique evolutionary histories of tens of thousands of gene families. Accurate reconstruction of these histories, however, is a challenging computational problem, and the focus of the Quest for Orthologs Consortium. We review the recent advances and outstanding challenges in this field, as revealed at a symposium and meeting held at the University of Southern California in 2017. Key advances have been made both at the level of orthology algorithm development and with respect to coordination across the community of algorithm developers and orthology end-users. Applications spanned a broad range, including gene function prediction, phylostratigraphy, genome evolution, and phylogenomics. The meetings highlighted the increasing use of meta-analyses integrating results from multiple different algorithms, and discussed ongoing challenges in orthology inference as well as the next steps toward improvement and integration of orthology resources.
- Language
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- English
- Open access status
- hybrid
- Identifiers
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- DOI 10.1093/molbev/msz150
- PMID 31241141
- Persistent URL
- https://sonar.ch/global/documents/161345
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