Evolutionary insights into Felidae iris color through ancestral state reconstruction.

Evolutionary Biology Phylogeny Zoology

Journal

iScience
ISSN: 2589-0042
Titre abrégé: iScience
Pays: United States
ID NLM: 101724038

Informations de publication

Date de publication:
18 Oct 2024
Historique:
received: 01 10 2023
revised: 20 12 2023
accepted: 04 09 2024
medline: 11 10 2024
pubmed: 11 10 2024
entrez: 11 10 2024
Statut: epublish

Résumé

Few studies have explored eye (iris) color evolution beyond humans and domesticated animals. Felids exhibit significant eye color diversity, unlike their brown-eyed relatives, making them an ideal model to study the evolution of eye color in natural populations. Through machine learning analysis of public photographs, five felid eye colors were identified: brown, green, yellow, gray, and blue. The presence or absence of these colors was reconstructed on a phylogeny, as well as their specific quantitative shades. The ancestral felid population likely had brown-eyed and gray-eyed individuals, the latter color being pivotal for the diversification of eye color seen in modern felids. Additionally, yellow eyes are highly associated with and may be necessary for, the evolution of round pupils in felids. These findings enhance the understanding of eye color evolution, and the methods presented in this work are widely applicable and will facilitate future research into the phylogenetic reconstruction of color beyond irises.

Identifiants

pubmed: 39391740
doi: 10.1016/j.isci.2024.110903
pii: S2589-0042(24)02128-X
pmc: PMC11465125
doi:

Banques de données

Dryad
['10.5061/dryad.s4mw6m9b0']

Types de publication

Journal Article

Langues

eng

Pagination

110903

Informations de copyright

© 2024 The Author(s).

Déclaration de conflit d'intérêts

The authors declare no competing interests.

Auteurs

Julius A Tabin (JA)

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA.

Katherine A Chiasson (KA)

Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD 21218, USA.

Classifications MeSH