CALANGO: a phylogeny-aware comparative genomics tool for discovering quantitative genotype-phenotype associations across species


Living species vary significantly in phenotype and genomic content. Sophisticated statistical methods linking genes with phenotypes within a species have led to breakthroughs in complex genetic diseases and genetic breeding. Despite the abundance of genomic and phenotypic data available for thousands of species, finding genotype-phenotype associations across species is challenging due to the non-independence of species data resulting from common ancestry. To address this, we present CALANGO (comparative analysis with annotation-based genomic components), a phylogeny-aware comparative genomics tool to find homologous regions and biological roles associated with quantitative phenotypes across species. In two case studies, CALANGO identified both known and previously unidentified genotype-phenotype associations. The first study revealed unknown aspects of the ecological interaction between Escherichia coli, its integrated bacteriophages, and the pathogenicity phenotype. The second identified an association between maximum height in angiosperms and the expansion of a reproductive mechanism that prevents inbreeding and increases genetic diversity, with implications for conservation biology and agriculture.

Publication DOI:
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies > Applied AI & Robotics
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
College of Engineering & Physical Sciences > Aston Centre for Artifical Intelligence Research and Application
Additional Information: Copyright © 2023 The Author(s). This is an open access article under the CC BY-NC-ND license ( Acknowledgements & Funding: The authors would like to thank the artists that shared the images used in our graphical abstract and in Figure 1 (Creative Commons Zero 1.0 Public Domain License, original images available at,, and This work was supported by the Coordenacao de Aperfeicoamento de Pessoal de Nı ́vel Superior (CAPES)/Brazil Finance Code 001, the Graduate Program in Genetics/UFMG, and the Graduate Program in Bioinformatics/UFMG.
Uncontrolled Keywords: species data,comparative genomics,evolution of quantitative phenotypes,genotype-phenotype association,comparative methods,molecular function convergence,quantitative trait,Genetics,Computer Science Applications
Publication ISSN: 2666-3899
Last Modified: 11 Jul 2024 07:18
Date Deposited: 28 Apr 2023 07:47
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Related URLs: https://www.cel ... 3899(23)00068-5 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2023-04-14
Accepted Date: 2023-02-23
Authors: Hongo, Jorge Augusto
Marques de Castro, Giovanni
Menezes, Alison
Picorelli, Agnello
Martins da Silva, Thieres
Imada, Eddie Luidy
Marchionni, Luigi
Del-Bem, Luiz Eduardo
Chaves, Anderson
Almeida, Gabriel
Campelo, Felipe (ORCID Profile 0000-0001-8432-4325)
Lobo, Francisco

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