Methylation-based markers for the estimation of age in African cheetah, Acinonyx jubatus.

Age is a key demographic in conservation where age classes show differences in important population metrics such as morbidity and mortality. Several traits, including reproductive potential, also show senescence with ageing. Thus, the ability to estimate age of individuals in a population is critical in understanding the current structure as well as their future fitness. Many methods exist to determine age in wildlife, with most using morphological features that show inherent variability with age. These methods require significant expertise and become less accurate in adult age classes, often the most critical groups to model. Molecular methods have been applied to measuring key population attributes, and more recently epigenetic attributes such as methylation have been explored as biomarkers for age. There are, however, several factors such as permits, sample sovereignty, and costs that may preclude the use of extant methods in a conservation context. This study explored the utility of measuring age-related changes in methylation in candidate genes using mass array technology. Novel methods are described for using gene orthologues to identify and assay regions for differential methylation. To illustrate the potential application, African cheetah was used as a case study. Correlation analyses identified six methylation sites with an age relationship, used to develop a model with sufficient predictive power for most conservation contexts. This model was more accurate than previous attempts using PCR and performed similarly to candidate gene studies in other mammal species. Mass array presents an accurate and cost-effective method for age estimation in wildlife of conservation concern.

Birds of a feather flock together: a dataset for Clock and Adcyap1 genes from migration genetics studies.

Birds in seasonal habitats rely on intricate strategies for optimal timing of migrations. This is governed by environmental cues, including photoperiod. Genetic factors affecting intrinsic timekeeping mechanisms, such as circadian clock genes, have been explored, yielding inconsistent findings with potential lineage-dependency. To clarify this evidence, a systematic review and phylogenetic reanalysis was done. This descriptor outlines the methodology for sourcing, screening, and processing relevant literature and data. PRISMA guidelines were followed, ultimately including 66 studies, with 34 focusing on candidate genes at the genotype-phenotype interface. Studies were clustered using bibliographic coupling and citation network analysis, alongside scientometric analyses by publication year and location. Data was retrieved for allele data from databases, article supplements, and direct author communications. The dataset, version 1.0.2, encompasses data from 52 species, with 46 species for the Clock gene and 43 for the Adcyap1 gene. This dataset, featuring data from over 8000 birds, constitutes the most extensive cross-species collection for these candidate genes, used in studies investigating gene polymorphisms and seasonal bird migration.

Dataset generated in a systematic review and meta-analysis of biological clocks as age estimation markers in animal ecology.

The dataset comprises a comprehensive systematic review and meta-analysis exploring the utility of biological clocks as age estimation markers in the context of animal ecology. The systematic review adhered to PRISMA guidelines and employed optimized Boolean search strings to retrieve relevant studies from Scopus and Dimensions databases. A total of 78 methylation studies and 108 telomere studies were included after rigorous screening. Effect sizes were computed, and statistical transformations were applied when necessary, ensuring compatibility for meta-analysis. Data from these studies were meticulously collected, encompassing statistical measures, study attributes, and additional biological information. The dataset comprises several folders, carefully organized to facilitate access and understanding. It contains raw and processed data used in the systematic review and meta-analysis, including Boolean search strings, database search results, citation network analysis data, PRISMA statements, extracted study data, and input data for meta-analysis. Each folder's contents are described in detail, ensuring clarity and reusability. This dataset aggregates primary research studies spanning diverse ecosystems and taxa, providing a valuable resource for researchers, biodiversity managers and policymakers. This dataset offers a wealth of information and analysis potential for researchers studying age estimation markers in animal ecology, serving as a robust foundation for future investigations and reviews in this evolving field.

Biological clocks as age estimation markers in animals: a systematic review and meta-analysis.

Various biological attributes associated with individual fitness in animals change predictably over the lifespan of an organism. Therefore, the study of animal ecology and the work of conservationists frequently relies upon the ability to assign animals to functionally relevant age classes to model population fitness. Several approaches have been applied to determining individual age and, while these methods have proved useful, they are not without limitations and often lack standardisation or are only applicable to specific species. For these reasons, scientists have explored the potential use of biological clocks towards creating a universal age-determination method. Two biological clocks, tooth layer annulation and otolith layering have found universal appeal. Both methods are highly invasive and most appropriate for post-mortem age-at-death estimation. More recently, attributes of cellular ageing previously explored in humans have been adapted to studying ageing in animals for the use of less-invasive molecular methods for determining age. Here, we review two such methods, assessment of methylation and telomere length, describing (i) what they are, (ii) how they change with age, and providing (iii) a summary and meta-analysis of studies that have explored their utility in animal age determination. We found that both attributes have been studied across multiple vertebrate classes, however, telomere studies were used before methylation studies and telomere length has been modelled in nearly twice as many studies. Telomere length studies included in the review often related changes to stress responses and illustrated that telomere length is sensitive to environmental and social stressors and, in the absence of repair mechanisms such as telomerase or alternative lengthening modes, lacks the ability to recover. Methylation studies, however, while also detecting sensitivity to stressors and toxins, illustrated the ability to recover from such stresses after a period of accelerated ageing, likely due to constitutive expression or reactivation of repair enzymes such as DNA methyl transferases. We also found that both studied attributes have parentally heritable features, but the mode of inheritance differs among taxa and may relate to heterogamy. Our meta-analysis included more than 40 species in common for methylation and telomere length, although both analyses included at least 60 age-estimation models. We found that methylation outperforms telomere length in terms of predictive power evidenced from effect sizes (more than double that observed for telomeres) and smaller prediction intervals. Both methods produced age correlation models using similar sample sizes and were able to classify individuals into young, middle, or old age classes with high accuracy. Our review and meta-analysis illustrate that both methods are well suited to studying age in animals and do not suffer significantly from variation due to differences in the lifespan of the species, genome size, karyotype, or tissue type but rather that quantitative method, patterns of inheritance, and environmental factors should be the main considerations. Thus, provided that complex factors affecting the measured trait can be accounted for, both methylation and telomere length are promising targets to develop as biomarkers for age determination in animals.

PAReTT: A Python Package for the Automated Retrieval and Management of Divergence Time Data from the TimeTree Resource for Downstream Analyses.

Evolutionary processes happen gradually over time and are, thus, considered time dependent. In addition, several evolutionary processes are either adaptations to local habitats or changing habitats, otherwise restricted thereby. Since evolutionary processes driving speciation take place within the landscape of environmental and temporal bounds, several published studies have aimed at providing accurate, fossil-calibrated, estimates of the divergence times of both extant and extinct species. Correct calibration is critical towards attributing evolutionary adaptations and speciation both to the time and paleogeography that contributed to it. Data from more than 4000 studies and nearly 1,50,000 species are available from a central TimeTree resource and provide opportunities of retrieving divergence times, evolutionary timelines, and time trees in various formats for most vertebrates. These data greatly enhance the ability of researchers to investigate evolution. However, there is limited functionality when studying lists of species that require batch retrieval. To overcome this, a PYTHON package termed Python-Automated Retrieval of TimeTree data (PAReTT) was created to facilitate a biologist-friendly interaction with the TimeTree resource. Here, we illustrate the use of the package through three examples that includes the use of timeline data, time tree data, and divergence time data. Furthermore, PAReTT was previously used in a meta-analysis of candidate genes to illustrate the relationship between divergence times and candidate genes of migration. The PAReTT package is available for download from GitHub or as a pre-compiled Windows executable, with extensive documentation on the package available on GitHub wiki pages regarding dependencies, installation, and implementation of the various functions.

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

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 are well established in controlling the daily rhythmicity of physiology and behaviour. Due to diverse migration patterns observed within and among species, in a seemingly endogenously programmed manner, the field of migration genetics has sought and tested several candidate genes within the clock circuitry that may underlie the observed differences in breeding and migration behaviour. Among others, length polymorphisms within genes such as Clock and Adcyap1 have been hypothesised to play a putative role, although association and fitness studies in various species have yielded mixed results. To contextualise the existing body of data, here we conducted a systematic review of all published studies relating polymorphisms in clock genes to seasonality in a phylogenetically and taxonomically informed manner. This was complemented by a standardised comparative re-analysis of candidate gene polymorphisms of 76 bird species, of which 58 are migrants and 18 are residents, along with population genetics analyses for 40 species with available allele data. We tested genetic diversity estimates, used Mantel tests for spatial genetic analyses, and evaluated relationships between candidate gene allele length and population averages for geographic range (breeding- and non-breeding latitude), migration distance, timing of migration, taxonomic relationships, and divergence times. Our combined analysis provided evidence (i) of a putative association between Clock gene variation and autumn migration as well as a putative association between Adcyap1 gene variation and spring migration in migratory species; (ii) that these candidate genes are not diagnostic markers to distinguish migratory from sedentary birds; and (iii) of correlated variability in both genes with divergence time, potentially reflecting ancestrally inherited genotypes rather than contemporary changes driven by selection. These findings highlight a tentative association between these candidate genes and migration attributes as well as genetic constraints on evolutionary adaptation.