Molecular biomarkers for chronological age in animal ecology

An epigenetic toolbox for conservation biologists

Ongoing climatic shifts and increasing anthropogenic pressures demand an efficient delineation of conservation units and accurate predictions of populations' resilience and adaptive potential. Molecular tools involving DNA sequencing are nowadays routinely used for these purposes. Yet, most of the existing tools focusing on sequence-level information have shortcomings in detecting signals of short-term ecological relevance. Epigenetic modifications carry valuable information to better link individuals, populations, and species to their environment. Here, we discuss a series of epigenetic monitoring tools that can be directly applied to various conservation contexts, complementing already existing molecular monitoring frameworks. Focusing on DNA sequence-based methods (e.g. DNA methylation, for which the applications are readily available), we demonstrate how (a) the identification of epi-biomarkers associated with age or infection can facilitate the determination of an individual's health status in wild populations; (b) whole epigenome analyses can identify signatures of selection linked to environmental conditions and facilitate estimating the adaptive potential of populations; and (c) epi-eDNA (epigenetic environmental DNA), an epigenetic-based conservation tool, presents a non-invasive sampling method to monitor biological information beyond the mere presence of individuals. Overall, our framework refines conservation strategies, ensuring a comprehensive understanding of species' adaptive potential and persistence on ecologically relevant timescales.

Epigenetic age estimation of wild mice using faecal samples

Age is a key parameter in population ecology, with a myriad of biological processes changing with age as organisms develop in early life then later senesce. As age is often hard to accurately measure with non-lethal methods, epigenetic methods of age estimation (epigenetic clocks) have become a popular tool in animal ecology and are often developed or calibrated using captive animals of known age. However, studies typically rely on invasive blood or tissue samples, which limit their application in more sensitive or elusive species. Moreover, few studies have directly assessed how methylation patterns and epigenetic age estimates compare across environmental contexts (e.g. captive or laboratory-based vs. wild animals). Here, we built a targeted epigenetic clock from laboratory house mice (strain C57BL/6, Mus musculus) using DNA from non-invasive faecal samples, and then used it to estimate age in a population of wild mice (Mus musculus domesticus) of unknown age. This laboratory mouse-derived epigenetic clock accurately predicted adult wild mice to be older than juveniles and showed that wild mice typically increased in epigenetic age over time, but with wide variation in epigenetic ageing rate among individuals. Our results also suggested that, for a given body mass, wild mice had higher methylation across targeted CpG sites than laboratory mice (and consistently higher epigenetic age estimates as a result), even among the smallest, juvenile mice. This suggests wild and laboratory mice may display different CpG methylation levels from very early in life and indicates caution is needed when developing epigenetic clocks on laboratory animals and applying them in the wild.

Seasonal Changes in Hemolymph Protein Level and Hypopharyngeal Gland Size Depending on Age and In-Nest Location of Honeybee Workers

A honeybee colony, as a super-organism, is regulated through age-polyethism. A honeybee worker's age is considered by means of a chronological and biological approach. The biological age is estimated with physiologically related biological markers, e.g., total hemolymph protein content (THP) and hypopharyngeal gland size (HGs), which also vary seasonally. Contemporary insights into the age-related spatial workers' distribution within the hive nest space regarding biological age are insufficiently clarified. This study aimed to monitor changes in selected physiological markers during the entire season in relation to worker age and their spatial position in the hive nest. THP content and HG size analysis was performed in nine colonies for the entire season to compare the physiological markers within and among the groups of the workers whose ages were known and sampled in different hive parts. Seasonal impact on the biomarkers' development was confirmed in known-age workers. In the case of HGs, this impact was the most apparent in 4- and 5-week-old workers. For THP, the seasonal impact was the most obvious in 2-week-old workers. The highest THP was found in 1- and 2-week-old workers during the entire season. Biologically younger workers of the same age were located predominantly in upper hive parts consistently throughout the year and vice versa. These workers showed significantly higher THP in comparison with those sampled below. Regarding the chronological age, the downwards, spatially shifting mechanism of workers within the hive nest while they aged was characterized. We recommend storage of diluted hemolymph samples up to one month before performing an assay if necessary. The physiological context, relation to division of labor and benefits for beekeeping practices are discussed.

Accounting for unobserved population dynamics and aging error in close-kin mark-recapture assessments

Obtaining robust estimates of population abundance is a central challenge hindering the conservation and management of many threatened and exploited species. Close-kin mark-recapture (CKMR) is a genetics-based approach that has strong potential to improve the monitoring of data-limited species by enabling estimates of abundance, survival, and other parameters for populations that are challenging to assess. However, CKMR models have received limited sensitivity testing under realistic population dynamics and sampling scenarios, impeding the application of the method in population monitoring programs and stock assessments. Here, we use individual-based simulation to examine how unmodeled population dynamics and aging uncertainty affect the accuracy and precision of CKMR parameter estimates under different sampling strategies. We then present adapted models that correct the biases that arise from model misspecification. Our results demonstrate that a simple base-case CKMR model produces robust estimates of population abundance with stable populations that breed annually; however, if a population trend or non-annual breeding dynamics are present, or if year-specific estimates of abundance are desired, a more complex CKMR model must be constructed. In addition, we show that CKMR can generate reliable abundance estimates for adults from a variety of sampling strategies, including juvenile-focused sampling where adults are never directly observed (and aging error is minimal). Finally, we apply a CKMR model that has been adapted for population growth and intermittent breeding to two decades of genetic data from juvenile lemon sharks (Negaprion brevirostris) in Bimini, Bahamas, to demonstrate how application of CKMR to samples drawn solely from juveniles can contribute to monitoring efforts for highly mobile populations. Overall, this study expands our understanding of the biological factors and sampling decisions that cause bias in CKMR models, identifies key areas for future inquiry, and provides recommendations that can aid biologists in planning and implementing an effective CKMR study, particularly for long-lived data-limited species.

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

Telomeres are short repetitive DNA sequences capping the ends of chromosomes. Telomere shortening occurs during cell division and may be accelerated by oxidative damage or ameliorated by telomere maintenance mechanisms. Consequently, telomere length changes with age, which was recently confirmed in a large meta-analysis across vertebrates. However, based on the correlation between telomere length and age, it was concluded that telomere length can be used as a tool for chronological age estimation in animals. Correlation should not be confused with predictability, and the current data and studies suggest that telomeres cannot be used to reliably predict individual chronological age. There are biological reasons for why there is large individual variation in telomere dynamics, which is mainly due to high susceptibility to a wide range of environmental, but also genetic factors, rendering telomeres unfeasible as a tool for age estimation. The use of telomeres for chronological age estimation is largely a misguided effort, but its occasional reappearance in the literature raises concerns that it will mislead resources in wildlife conservation.

Age estimation of captive Asian elephants (Elephas maximus) based on DNA methylation: An exploratory analysis using methylation-sensitive high-resolution melting (MS-HRM)

Age is an important parameter for bettering the understanding of biodemographic trends-development, survival, reproduction and environmental effects-critical for conservation. However, current age estimation methods are challenging to apply to many species, and no standardised technique has been adopted yet. This study examined the potential use of methylation-sensitive high-resolution melting (MS-HRM), a labour-, time-, and cost-effective method to estimate chronological age from DNA methylation in Asian elephants (Elephas maximus). The objective of this study was to investigate the accuracy and validation of MS-HRM use for age determination in long-lived species, such as Asian elephants. The average lifespan of Asian elephants is between 50-70 years but some have been known to survive for more than 80 years. DNA was extracted from 53 blood samples of captive Asian elephants across 11 zoos in Japan, with known ages ranging from a few months to 65 years. Methylation rates of two candidate age-related epigenetic genes, RALYL and TET2, were significantly correlated with chronological age. Finally, we established a linear, unisex age estimation model with a mean absolute error (MAE) of 7.36 years. This exploratory study suggests an avenue to further explore MS-HRM as an alternative method to estimate the chronological age of Asian elephants.

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.

Calibrating epigenetic clocks with training data error

Animal age data are valuable for management of wildlife populations. Yet, for most species, there is no practical method for determining the age of unknown individuals. However, epigenetic clocks, a molecular-based method, are capable of age prediction by sampling specific tissue types and measuring DNA methylation levels at specific loci. Developing an epigenetic clock requires a large number of samples from animals of known ages. For most species, there are no individuals whose exact ages are known, making epigenetic clock calibration inaccurate or impossible. For many epigenetic clocks, calibration samples with inaccurate age estimates introduce a degree of error to epigenetic clock calibration. In this study, we investigated how much error in the training data set of an epigenetic clock can be tolerated before it resulted in an unacceptable increase in error for age prediction. Using four publicly available data sets, we artificially increased the training data age error by iterations of 1% and then tested the model against an independent set of known ages. A small effect size increase (Cohen's d >0.2) was detected when the error in age was higher than 22%. The effect size increased linearly with age error. This threshold was independent of sample size. Downstream applications for age data may have a more important role in deciding how much error can be tolerated for age prediction. If highly precise age estimates are required, then it may be futile to embark on the development of an epigenetic clock when there is no accurately aged calibration population to work with. However, for other problems, such as determining the relative age order of pairs of individuals, a lower-quality calibration data set may be adequate.

Identification and Characterization of Small RNA Markers of Age in the Blow Fly Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae)

Blow fly development is important in decomposition ecology, agriculture, and forensics. Much of the impact of these species is from immature samples, thus knowledge of their development is important to enhance or ameliorate their effects. One application of this information is the estimation of immature insect age to provide temporal information for death investigations. While traditional markers of age such as stage and size are generally accurate, they lack precision in later developmental stages. We used miRNA sequencing to measure miRNA expression, throughout development, of the secondary screwworm, Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae) and identified 217 miRNAs present across the samples. Ten were identified to be significantly differentially expressed in larval samples and seventeen were found to be significantly differentially expressed in intrapuparial samples. Twenty-eight miRNAs were identified to be differentially expressed between sexes. Expression patterns of two miRNAs, miR-92b and bantam, were qPCR-validated in intrapuparial samples; these and likely food-derived miRNAs appear to be stable markers of age in C. macellaria. Our results support the use of miRNAs for developmental markers of age and suggest further investigations across species and under a range of abiotic and biotic conditions.

Epigenetic models developed for plains zebras predict age in domestic horses and endangered equids

Effective conservation and management of threatened wildlife populations require an accurate assessment of age structure to estimate demographic trends and population viability. Epigenetic aging models are promising developments because they estimate individual age with high accuracy, accurately predict age in related species, and do not require invasive sampling or intensive long-term studies. Using blood and biopsy samples from known age plains zebras (Equus quagga), we model epigenetic aging using two approaches: the epigenetic clock (EC) and the epigenetic pacemaker (EPM). The plains zebra EC has the potential for broad application within the genus Equus given that five of the seven extant wild species of the genus are threatened. We test the EC's ability to predict age in sister taxa, including two endangered species and the more distantly related domestic horse, demonstrating high accuracy in all cases. By comparing chronological and estimated age in plains zebras, we investigate age acceleration as a proxy of health status. An interaction between chronological age and inbreeding is associated with age acceleration estimated by the EPM, suggesting a cumulative effect of inbreeding on biological aging throughout life.

Epigenetic Measurement of Key Vertebrate Population Biology Parameters

The age, sex, and sexual maturity of individual animals are key parameters in assessing wild populations and informing conservation management strategies. These parameters represent the reproductive potential of a population and can indicate recovery rates or vulnerabilities. Natural populations of wild animals are difficult to study; logistically, economically, and due to the impacts of invasive biomonitoring. Genetic and epigenetic analyses offer a low impact, low cost, and information-rich alternative. As epigenetic mechanisms are intrinsically linked with both biological aging and reproductive processes, DNA methylation can be used as a suitable biomarker for population biology study. This review assesses published research utilizing DNA methylation analysis in relation to three key population parameters: age, sex, and sexual maturity. We review studies on wild vertebrates that investigate epigenetic age relationships, with successful age estimation assays designed for mammals, birds, and fish. For both determination of sex and identification of sexual maturity, very little has been explored regarding DNA methylation-based assays. Related research, however, confirms the links between DNA methylation and these processes. Future development of age estimation assays for underrepresented and key conservation taxa is suggested, as is the experimental development and design of DNA methylation-based assays for both sex and sexual maturity identification, further expanding the genomics toolkit for population biology studies.

Ageing European lobsters (Homarus gammarus) using DNA methylation of evolutionarily conserved ribosomal DNA

Crustaceans are notoriously difficult to age because of their indeterminate growth and the moulting of their exoskeleton throughout life. The poor knowledge of population age structure in crustaceans therefore hampers accurate assessment of population dynamics and consequently sustainable fisheries management. Quantification of DNA methylation of the evolutionarily conserved ribosomal DNA (rDNA) may allow for age prediction across diverse species. However, the rDNA epigenetic clock remains to be tested in crustaceans, despite its potential to inform both ecological and evolutionary understanding, as well as conservation and management practices. Here, patterns of rDNA methylation with age were measured across 5154 bp of rDNA corresponding to 355 quality-filtered loci in the economically important European lobster (Homarus gammarus). Across 0- to 51-month-old lobsters (n = 155), there was a significant linear relationship between age and percentage rDNA methylation in claw tissue at 60% of quality-filtered loci (n = 214). An Elastic Net regression model using 46 loci allowed for the accurate and precise age estimation of individuals (R 2 = 0.98; standard deviation = 1.6 months). Applying this ageing model to antennal DNA from wild lobsters of unknown age (n = 38) resulted in predicted ages that are concordant with estimates of minimum size at age in the wild (mean estimated age = 40.1 months; range 32.8-55.7 months). Overall, the rDNA epigenetic clock shows potential as a novel, nonlethal ageing technique for European lobsters. However, further validation is required across a wider range of known-age individuals and tissue types before the model can be used in fisheries management.

An epigenetic clock to estimate the age of living beluga whales

DNA methylation data facilitate the development of accurate molecular estimators of chronological age or "epigenetic clocks." We present a robust epigenetic clock for the beluga whale, Delphinapterus leucas, developed for an endangered population in Cook Inlet, Alaska, USA. We used a custom methylation array to measure methylation levels at 37,491 cytosine-guanine sites (CpGs) from skin samples of dead whales (n = 67) whose chronological ages were estimated based on tooth growth layer groups. Using these calibration data, a penalized regression model selected 23 CpGs, providing an R 2 = 0.92 for the training data; and an R 2 = 0.74 and median absolute age error = 2.9 years for the leave one out cross-validation. We applied the epigenetic clock to an independent dataset of 38 skin samples collected with a biopsy dart from living whales between 2016 and 2018. Age estimates ranged from 11 to 27 years. We also report sex correlations in CpG data and describe an approach of identifying the sex of an animal using DNA methylation. The epigenetic estimators of age and sex presented here have broad applications for conservation and management of Cook Inlet beluga whales and potentially other cetaceans.

Ambiguities in using telomere length for age determination in two North American bat species

The age of an animal, determined by time (chronological age) as well as genetic and environmental factors (biological age), influences the likelihood of mortality and reproduction and thus the animal’s contribution to population growth. For many long-lived species, such as bats, a lack of external and morphological indicators has made determining age a challenge, leading researchers to examine genetic markers of age for application to demographic studies. One widely studied biomarker of age is telomere length, which has been related both to chronological and biological age across taxa, but only recently has begun to be studied in bats. We assessed telomere length from the DNA of known-age and minimum known-age individuals of two bat species using a quantitative PCR assay. We determined that telomere length was quadratically related to chronological age in big brown bats (Eptesicus fuscus), although it had little predictive power for accurate age determination of unknown-age individuals. The relationship was different in little brown bats (Myotis lucifugus), where telomere length instead was correlated with biological age, apparently due to infection and wing damage associated with white-nose syndrome. Furthermore, we showed that wing biopsies currently are a better tissue source for studying telomere length in bats than guano and buccal swabs; the results from the latter group were more variable and potentially influenced by storage time. Refinement of collection and assessment methods for different non-lethally collected tissues will be important for longitudinal sampling to better understand telomere dynamics in these long-lived species. Although further work is needed to develop a biomarker capable of determining chronological age in bats, our results suggest that biological age, as reflected in telomere length, may be influenced by extrinsic stressors such as disease.

Parallel Progress in Perceived Age and Life Expectancy

BACKGROUND

Human life expectancy continues to rise in most populations. This rise not only leads to longer lives but also is accompanied by improved health at a given age, that is, recent cohorts show a reduction of biological age for a given chronological age. Despite or even because of the diversity of biomarkers of aging, an accurate quantification of a general shift in biological age across time has been challenging.

METHODS

Here, we compared age perception of facial images taken in 2001 over a decade and related these changes in age perception to changes in life expectancy.

RESULTS

We show that age perception changes substantially across time and parallels the progress in life expectancy. In 2012, people aged more than 70 years needed to look 2.3 years younger to be rated the same age as in 2002.

CONCLUSIONS

Our results suggest that age perception reflects the past life events better than predicts future length of life, that is, it is written in your face how much you have aged so far. We draw this conclusion as age perception among elderly individuals paralleled changes in life expectancy at birth but not changes in remaining life expectancies. We suggest that changes in age perception should be explored for younger age classes to inform on aging processes, including whether aging is delayed or slowed with increasing life expectancy.

Foot web pentosidine does not covary strongly with age in four species of wild seabirds

Age is an important parameter for a variety of ecological applications, including population viability analyses, contaminants monitoring and targeting of individuals for conservation. While many organisms can be aged by annual rings, dentition and other techniques (i.e., fish otoliths, clam growth rings, mammal tooth wear), there are no minimally invasive biomarkers for accurately aging birds in the wild. For the past century, banding has been the only way to identify a bird of known age, which requires continuous effort on a large scale with possibly low return rates. Recent studies have identified pentosidine as a potential biomarker of chronological aging in several bird species. To test this idea in four species of long-lived seabirds, we collected skin biopsies from the foot webs of previously banded, known-age seabirds: black-legged kittiwakes (Rissa tridactyla; 0-19 y old), Atlantic puffins (Fratercula arctica; 5-26 y old), razorbills (Alca torda; 0-15 d old) and thick-billed murres (Uria lomvia; 0-35 y old). Foot web samples were specifically chosen because this was the least invasive site for substantial skin biopsy. Samples were analysed with high performance liquid chromatography to quantify pentosidine levels. Collagen levels were estimated through hydroxyproline assays to normalize pentosidine content across individuals. Kittiwakes displayed a weak correlation (r² = 0.20) between age and pentosidine/collagen. Puffins (adults only, r² = 0.02), razorbills (chicks only, r² = 0.08), and murres (adults, r² = 0.04) did not show any associations with age. We concluded that pentosidine content in the foot web does not appear to be a reliable method for aging seabirds in the wild. An absence of change in pentosidine in the foot web with age is further evidence that long-lived seabirds may maintain physiological performance into old age.

Accuracy, precision, and error in age estimation of Florida manatees using growth layer groups in earbones

Ages of Florida manatees (Trichechus manatus latirostris) can be estimated by counting annual growth layer groups (GLGs) in the periotic dome portion of the tympanoperiotic complex of their earbones. The Florida Fish and Wildlife Conservation Commission manages an archive of more than 8,700 Florida manatee earbones collected from salvaged carcasses from 1989 to 2017. Our goal was to comprehensively evaluate techniques used to estimate age, given this large sample size and changes to processing protocols and earbone readers over time. We developed new standards for estimating ages from earbones, involving two independent readers to obtain measurements of within- and between-reader precision. To quantify accuracy, precision, and error, 111 earbones from manatees with approximately known ages (first known as calves: “KAC”) and 69 earbones from manatees with minimum known ages (“MKA,” based on photo-identification sighting histories) were processed, and their ages were estimated. There was greater precision within readers (coefficient of variation, CV: 2.4–8.5%) than between readers (CV: 13.1–13.3%). The median of age estimates fell within the true age range for 63.1% of KAC cases and was at least the sighting duration for 75.0% of MKA cases. Age estimates were generally unbiased, as indicated by an average raw error ± SD of −0.05 ± 3.05 years for the KAC group. The absolute error (i.e., absolute value of raw error) of the KAC data set averaged 1.75 ± 2.50 years. Accuracy decreased and error increased with increasing known age, especially for animals over 15 years old, whose ages were mostly underestimated due to increasing levels of resorption (the process of bone turnover that obscures GLGs). Understanding the degree of uncertainty in age estimates will help us assess the utility of age data in manatee population models. We emphasize the importance of standardizing and routinely reviewing age estimation and processing protocols to ensure that age data remain consistent and reliable.

Cross-species functional modules link proteostasis to human normal aging

The evolutionarily conserved nature of the few well-known anti-aging interventions that affect lifespan, such as caloric restriction, suggests that aging-related research in model organisms is directly relevant to human aging. Since human lifespan is a complex trait, a systems-level approach will contribute to a more comprehensive understanding of the underlying aging landscape. Here, we integrate evolutionary and functional information of normal aging across human and model organisms at three levels: gene-level, process-level, and network-level. We identify evolutionarily conserved modules of normal aging across diverse taxa, and notably show proteostasis to be conserved in normal aging. Additionally, we find that mechanisms related to protein quality control network are enriched for genes harboring genetic variants associated with 22 age-related human traits and associated to caloric restriction. These results demonstrate that a systems-level approach, combined with evolutionary conservation, allows the detection of candidate aging genes and pathways relevant to human normal aging.

Measuring biological age to assess colony demographics in honeybees

Honeybee colonies are increasingly exposed to environmental stress factors, which can lead to their decline or failure. However, there are major gaps in stressor risk assessment due to the difficulty of assessing the honeybee colony state and detecting abnormal events. Since stress factors usually induce a demographic disturbance in the colony (e.g. loss of foragers, early transition from nurse to forager state), we suggest that disturbances could be revealed indirectly by measuring the age- and task-related physiological state of bees, which can be referred to as biological age (an indicator of the changes in physiological state that occur throughout an individual lifespan). We therefore estimated the biological age of bees from the relationship between age and biomarkers of task specialization (vitellogenin and the adipokinetic hormone receptor). This relationship was determined from a calibrated sample set of known-age bees and mathematically modelled for biological age prediction. Then, we determined throughout the foraging season the evolution of the biological age of bees from colonies with low (conventional apiary) or high Varroa destructor infestation rates (organic apiary). We found that the biological age of bees from the conventional apiary progressively decreased from the spring (17 days) to the fall (6 days). However, in colonies from the organic apiary, the population aged from spring (13 days) to summer (18.5 days) and then rejuvenated in the fall (13 days) after Varroa treatment. Biological age was positively correlated with the amount of brood (open and closed cells) in the apiary with low Varroa pressure, and negatively correlated with Varroa infestation level in the apiary with high Varroa pressure. Altogether, these results show that the estimation of biological age is a useful and effective method for assessing colony demographic state and likely detrimental effects of stress factors.

A Tale of Two Concepts: Harmonizing the Free Radical and Antagonistic Pleiotropy Theories of Aging

SIGNIFICANCE

The two foremost concepts of aging are the mechanistic free radical theory (FRT) of how we age and the evolutionary antagonistic pleiotropy theory (APT) of why we age. Both date from the late 1950s. The FRT holds that reactive oxygen species (ROS) are the principal contributors to the lifelong cumulative damage suffered by cells, whereas the APT is generally understood as positing that genes that are good for young organisms can take over a population even if they are bad for the old organisms. Recent Advances: Here, we provide a common ground for the two theories by showing how aging can result from the inherent chemical reactivity of many biomolecules, not just ROS, which imposes a fundamental constraint on biological evolution. Chemically reactive metabolites spontaneously modify slowly renewable macromolecules in a continuous way over time; the resulting buildup of damage wrought by the genes coding for enzymes that generate such small molecules eventually masquerades as late-acting pleiotropic effects. In aerobic organisms, ROS are major agents of this damage but they are far from alone.

CRITICAL ISSUES

Being related to two sides of the same phenomenon, these theories should be compatible. However, the interface between them is obscured by the FRT mistaking a subset of damaging processes for the whole, and the APT mistaking a cumulative quantitative process for a qualitative switch.

FUTURE DIRECTIONS

The manifestations of ROS-mediated cumulative chemical damage at the population level may include the often-observed negative correlation between fitness and the rate of its decline with increasing age, further linking FRT and APT. Antioxid. Redox Signal. 29, 1003-1017.

Genetic and genomic monitoring with minimally invasive sampling methods

The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high-quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low-quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next-generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

Estimation of chimpanzee age based on DNA methylation

In wild animal conservation, knowing the age of an individual animal is extremely beneficial. However, estimating the age is difficult for many species. Recently, epigenetics-based methods of estimating age have been reported. These studies were predominantly on humans with few reports on other animals, especially wild animals. In the present study, a chimpanzee (Pan troglodytes) age prediction model was developed based on the ELOVL2, CCDC102B, and ZNF423 genes that may also have application in human age prediction. Pyrosequencing was used to measure methylation in 20 chimpanzee blood samples and correlation between age and methylation status was calculated. Age and methylation of sites in ELOVL2 and CCDC102B were significantly correlated and an age prediction model was created using these genes. In the regression equation using only ELOVL2, the highest correlation coefficient was 0.741, with a mean absolute deviation (MAD) of 5.41, compared with the combination of ELOVL2 and CCDC102B, where the highest correlation coefficient was 0.742 and the MAD was 5.41. Although larger MADs were observed in chimpanzees than in humans based on these genes, the results indicate the feasibility of estimating chimpanzee age using DNA methylation, and can have implications in understanding the ecology of chimpanzees and chimpanzee conservation.

Can concentrations of steroid hormones in brown bear hair reveal age class?

Although combining genetic and endocrine data from non-invasively collected hair samples has potential to improve the conservation of threatened mammals, few studies have evaluated this opportunity. In this study, we determined if steroid hormone (testosterone, progesterone, estradiol and cortisol) concentration profiles in 169 hair samples collected from free-ranging brown bears (Ursus arctos) could be used to accurately discriminate between immature and adult bears within each sex. Because hair samples were acquired opportunistically, we also needed to establish if interactions between hormones and several non-hormone factors (ordinal day, year, contact method, study area) were associated with age class. For each sex, we first compared a suite of candidate models by Akaike Information Criteria model selection, using different adult-age thresholds (3, 4 and 5 years), to determine the most supported adult age. Because hair hormone levels better reflect the endocrine state at an earlier time, possibly during the previous year, then at the time of sampling, we re-analysed the data, excluding the records for bears at the adult-age threshold, to establish if classification accuracy improved. For both sexes, candidate models were most supported based on a 3-year-old adult-age threshold. Classification accuracy did not improve with the 3-year-old bear data excluded. Male age class was predicted with a high degree of accuracy (88.4%) based on the concomitant concentrations of all four hormones. Female age class was predicted with less accuracy (77.1%) based only on testosterone and cortisol. Accuracy was reduced for females, primarily because we had poor success in correctly classifying immature bears (60%) whereas classification success for adult females was similar to that for males (84.5%). Given the small and unbalanced sample used in this study, our findings should be viewed as preliminary, but they should also provide a basis for more comprehensive future studies.

DNA methylation levels in candidate genes associated with chronological age in mammals are not conserved in a long-lived seabird

Most seabirds do not have any outward identifiers of their chronological age, so estimation of seabird population age structure generally requires expensive, long-term banding studies. We investigated the potential to use a molecular age biomarker to estimate age in short-tailed shearwaters (Ardenna tenuirostris). We quantified DNA methylation in several A. tenuirostris genes that have shown age-related methylation changes in mammals. In birds ranging from chicks to 21 years of age, bisulphite treated blood and feather DNA was sequenced and methylation levels analysed in 67 CpG sites in 13 target gene regions. From blood samples, five of the top relationships with age were identified in KCNC3 loci (CpG66: R² = 0.325, p = 0.019). In feather samples ELOVL2 (CpG42: R² = 0.285, p = 0.00048) and EDARADD (CpG46: R² = 0.168, p = 0.0067) were also weakly correlated with age. However, the majority of markers had no clear association with age (of 131 comparisons only 12 had a p-value < 0.05) and statistical analysis using a penalised lasso approach did not produce an accurate ageing model. Our data indicate that some age-related signatures identified in orthologous mammalian genes are not conserved in the long-lived short tailed shearwater. Alternative molecular approaches will be required to identify a reliable biomarker of chronological age in these seabirds.

Measuring Animal Age with DNA Methylation: From Humans to Wild Animals

DNA methylation (DNAm) is a key mechanism for regulating gene expression in animals and levels are known to change with age. Recent studies have used DNAm changes as a biomarker to estimate chronological age in humans and these techniques are now also being applied to domestic and wild animals. Animal age is widely used to track ongoing changes in ecosystems, however chronological age information is often unavailable for wild animals. An ability to estimate age would lead to improved monitoring of (i) population trends and status and (ii) demographic properties such as age structure and reproductive performance. Recent studies have revealed new examples of DNAm age association in several new species increasing the potential for developing DNAm age biomarkers for a broad range of wild animals. Emerging technologies for measuring DNAm will also enhance our ability to study age-related DNAm changes and to develop new molecular age biomarkers.