CALANGO: A phylogeny-aware comparative genomics tool for discovering quantitative genotype-phenotype associations across species
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https://hdl.handle.net/10037/30408Date
2023-06-09Type
Journal articleTidsskriftartikkel
Peer reviewed
Author
Hongo, Jorge Augusto; de Castro, Giovanni Marques; Albuquerque Menezes, Alison Pelri; Rios Picorelli, Agnello César; Martins da Silva, Thieres Tayroni; Imada, Eddie Luidy; Marchionni, Luigi; Del-Bem, Luiz-Eduardo; Vieira Chaves, Anderson; de Freitas Almeida, Gabriel Magno; Campelo, Felipe; Lobo, Francisco PereiraAbstract
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.
Publisher
ElsevierCitation
Hongo, de Castro, Albuquerque Menezes, Rios Picorelli, Martins da Silva, Imada, Marchionni, Del-Bem, Vieira Chaves, de Freitas Almeida, Campelo, Lobo. CALANGO: A phylogeny-aware comparative genomics tool for discovering quantitative genotype-phenotype associations across species. Patterns. 2023Metadata
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