Time trees and clock genes: a systematic review and comparative analysis of contemporary avian migration genetics

Abstract

Timing is a crucial aspect for survival and reproduction in seasonal environments leading to carefully scheduled annual programs of migration in many species. But what are the exact mechanisms through which birds (class: Aves) can keep track of time, anticipate seasonal changes, and adapt their behaviour? One proposed mechanism regulating annual behaviour is the circadian clock, controlled by a highly conserved set of genes, collectively called 'clock genes' which

Candidate gene polymorphisms are linked to dispersive and migratory behaviour: Searching for a mechanism behind the “paradox of the great speciators”

“…These behaviours often have significant narrow sense heritability, often greater than 0.4 (Dochtermann et al, 2019). Additionally, at the molecular level, genetic variation for migration, dispersive behaviour and personality traits are well documented (Bubac et al, 2020), including the identification of a number of candidate genes underlying personality traits such as tendency for boldness or exploratory behaviour (Canestrelli et al, 2016; Fidler et al, 2007; Ruegg et al, 2014; Steinmeyer et al, 2009), and migratory behaviour (Bazzi et al, 2015; Johnsen et al, 2007; Peterson et al, 2013; see Le Clercq et al, 2023 for an extensive review). Changes in genetic variation at these candidate genes may act as a genetic switch catalysing population‐level shifts in dispersive behaviour.…”

Telomere length is not a useful tool for chronological age estimation in animals

“…[14] The individual variation in TL, TL change and maintenance is consequently very large, which is mainly because of differences in individual experiences (e.g., reproduction, activity level, growth [15,16] ) and exposure to various environmental factors and stressors (e.g., disease, food availability, abiotic conditions [16][17][18][19] ), but also due to biological differences (e.g., sex [20,21] ) and genetic [22][23][24][25] and epigenetic variation. [26,27] Accordingly, Le Clercq et al [1] found that most of the variation (69%) in TL within species could not be explained by age. The great individual heterogeneity in telomere dynamics is what makes the area interesting to a broad range of fields from ecophysiology, conservation biology, and evolutionary ecology to life-history theory, [28][29][30] but TL does not predictably track time as a clock.…”

“…Telomeres are not currently among the targets being developed as biomarkers for chronological age determination in wild animals. Fortynine of the 69 studies included in the meta-analysis by Le Clercq et al [1] did not consider using telomere dynamics to estimate age (see Table S1 in the Supporting Information). Twelve studies concluded that telomeres should not be used for age estimation in their focal species, four studies suggested it may be used given future developments, and four studies suggested that TL could be used for age estimation thus sharing the conclusions of Le Clercq et al [1] Of the latter studies, Hatase et al [87] paradoxically found no correlation between TL and age in loggerhead sea turtle (Caretta caretta); Haussmann et al [69] found that TL could classify common terns (Sterna hirundo) into three age classes with 80% accuracy; Cherdsukjai et al [88] found that TL could assess whether dugongs (Dugong dugon) were below 20 years, after which there was no TL change; and Pauli et al [89] used TL together with information on body size, sex, population density, and age class (juvenile or adult) to assign martens (Martes spp.)…”

“…In a recent study, Le Clercq et al. [ 1 ] conducted a comprehensive meta‐analysis of the correlation between age and average telomere length (TL). They found a moderate statistically significant correlation between TL and age in 60 vertebrate species ( R 2 = 0.31, 95% confidence interval (CI): [0.25, 0.37], p < 0.01, 95% prediction interval: [−0.23, 0.71]), or in 51 bird species ( R 2 = 0.43, 95% CI: [0.35, 0.51], p < 0.01, 95% prediction interval: [−0.23, 0.82]), suggesting that age explains some of the variation in TL, but with no or little prediction capabilities to estimate age from TL.…”

“…This is contrary to epigenetic clocks which routinely have R 2 > 90, suggesting that they explain over twice as much variation in chronological age as TL. [ 1,2 ] However, Le Clercq et al. concluded that TL estimation is “an accurate method of age prediction,” that it is a “biological clock with sufficient age prediction capabilities to measure age in animals,” that was “able to classify individuals into young, middle, or old age classes with high accuracy,” and that although “[DNA] methylation may be superior to telomere length in terms of accuracy and cross‐taxa portability; however, costs may be higher.” Such conclusions may direct resources in conservation biology to continue attempting to use telomere dynamics as a tool for age estimation in wildlife, despite two decades of mainly failed attempts to do so.…”