PhD Project

Background

Each year, several species of birds take to the sky to make their annual journey from nonbreeding to breeding grounds. This event is carefully timed, and the repeated occurrence of this behaviour has led to the field of chronobiology with emphasis on both intrinsic as well as environmental cues contributing to timekeeping. One proposed mechanism is the circadian clock, which regulates daily activity in almost all organisms. The circadian clock comprises several genes which have a central axis with a positive feedback loop, which promotes transcription; and a negative feedback loop, which prevents transcription. The molecular clock is tied to environmental cues such as photoperiod, changing temperatures, and availability of food sources. As the photoperiod (length of sunlight) changes, the internal phase of the circadian clock adjusts to maintain appropriate sleep-wake cycles known as entrainment. This partially explains how environmental changes modulate the circadian clock on a circannual basis. It has, however, been noted that many species persistently exhibit migration-related behaviour (such as migratory restlessness and moulting) when kept under constant conditions in captivity. Therefore, the intrinsic clock can function in isolation of environmental factors, raising the question as to why differential patterns of migration exist within a species. Several studies compared migratory phenology to putative variation within clock genes. Two clock genes have since been identified: clock and Adcyap1. The former showed variability within a series of poly-glutamine residues which differs both between and within species; the latter shows variation within the 5’-UTR of the gene. A significant correlation between variability and migration patterns has been illustrated in blue tits, pied flycatcher and warblers; whilst some studies failed to show a significant correlation. Thus, some species are fine-tuned to environmental cues to initiate migration whilst others are not, and some species have significant variability in key clock genes that partially contribute to differences in migration phenology. Some species, such as the Streaky-breasted flufftail, show two distinct populations of resident and migratory birds, the exact mechanisms responsible for such differences in migratory phenology remains to be elucidated. Further studies are thus warranted to assess the degree of variability in candidate genes, their relation to migration phenology, and utility in answering important questions regarding breeding phenology.

Age is another key factor in animal ecology as it can be used to assign animals to important age classes ranging from reproductive success to old age and fragility. Morphological features of internal structures, such as tooth cementum annulation are used to provide accurate age estimation of dead animals. Age determination in live animals is generally more cumbersome and may rely upon either natural markings, such as those on the flukes of whales, or artificial markings, such as uniquely numbered bands attached to the legs of birds. Molecular methods to determine age in wildlife however remains elusive. Many aspects of the natural aging process are under genetic control. Epigenetics is a collective term for mechanisms that modify DNA and DNA packaging, independent of genetic sequence. One widely studied epigenetic feature is DNA methylation; a process that adds a methyl group to the 5’ cytosine of Cytosine-Guanine pairs (CpG’s). Studies have revealed that within genes, nearly a third of all CpG sites are influenced by age. Given its consistency, the epigenetic clock is a promising avenue of chronological age prediction that has been illustrated in several studies15. Another promising epigenetic feature is telomeres, stretches of noncoding nucleotide repeats that cap the 3’ terminals of chromosomes. These caps present as single stranded ‘TTAGGG’ overhangs that fold back upon themselves to form telomere loops. As DNA polymerase would not be able to replicate the segment of DNA to which it binds, telomeres serve as barriers protecting coding sequences located towards the end of chromosomes. However, telomeres are also subject to the gradual loss of sequence and telomere length has since become a well studied attribute of cellular aging. This has increased interest in its ability to determine age and many studies have been conducted in human models to investigate the potential of using this process to estimate chronological age using biological age. Such correlations have been illustrated in several species. These methods therefore present a novel and promising method of age estimation in diverse animal populations where age is unknown but plays an important role in their ecology.

Aims

Use genetic methods to investigate two biological clock measures: migration phenology and age, by:

•  Investigating the relationship between genetic variance in circadian clock genes and their potential role in differential migration phenology.

• Investigating the potential of age-related changes in the methylation of genes under epigenetic clock control, as well as telomere length, to be used to establish an accurate age estimation model in yet unexplored wildlife.

Objectives

• Sample from various African avian species that show diverse migratory phenology such as resident versus migrant status, migration to two different sites, as well as early migration and nesting birds versus late arrivals.

• Amplify and sequence a region of the poly-Q repeat residue of the Clock gene and the 3’-UTR of the Adcyap1 gene to determine if there is a correlation between gene variation and migration phenology (migratory distance, time of departure and arrival, and sex).

• Obtain samples from both long- and short-lived species with distinct, relevant, age classes across their lifespan.

• Identify the best candidate genes from the literature to screen for differential CpG methylation in animals and screen for significant changes in methylation patterns, using Mass Array technology.

• Assay absolute telomere length and test for a significant decrease in absolute telomere length with age.

• Compare the utility of either assay, independently or in conjunction and develop and validate a model for accurate age estimation for both methods.

Methods

DNA will be extracted from whole blood. PCR of clock genes will be performed with novel/modified primers and amplification monitored by gel electrophoresis. PCR products for Clock and Adcyap1 will be purified by Exonuclease I (Exo) and Shrimp Alkaline Phosphatase (SAP) digestion. Samples will be sequenced with the BigDye™ Terminator v3.1 Cycle Sequencing Kit and analyzed on the ABI 3130 Genetic Analyzer. Methylation analysis will be done of CpG’s in 8 genes, identified from the literature, with EpiTYPER® Mass array bisulfite sequencing (Inqaba Biotechnical Industries (Pty) Ltd. Hatfield, Pretoria). New primers will be designed (www.epidesigner.com) using available sequence data from Genbank for cheetah genes analogous to those from human studies. EpiTYPER® biochemistry starts with bisulfite treatment of DNA, followed by PCR amplification. The reverse primers contain a T-7 promoter tag. In vitro RNA transcription will be performed, followed by base-specific RNA cleavage. Cleaved products will be analysed using MALDI-TOF (MassARRAY® Analyzer), where fragment length indicates the fragmentation sites, which cleave differently based on methylation status. Those CpG’s showing a significant relationship (α = 0.05, p ≤ 0.05, r2 ≥ 0.75) between methylation percentage and age will be selected for further linear or quadratic modelling in varied combinations, to establish a model with the least Standard Error of the Mean (SEM) for predicting age. Telomere length will be assayed using a quantitative real-time PCR method for the absolute telomere length (aTL). This establishes the total telomere repeats per reaction by comparison to a serially diluted telomere standard for which the number of repeats is known. This value is normalized using a single copy gene, 36B4, as control for genome copy number. The absolute telomere length values will be used in modelling their age, as for methylation. Statistical analyses will be performed with R.

Research Output:

1. Le Clercq, L.-S., Bazzi, G., Cecere, J.G., Gianfranceschi, L., Grobler, J.P., Kotzé, A., Rubolini, D., Liedvogel, M. and Dalton, D.L. (2023), Time trees and clock genes: a systematic review and comparative analysis of contemporary avian migration genetics. Biological Reviews. https://doi.org/10.1111/brv.12943  

2. Le Clercq, L.-S., Bazzi, G., Ferrer Obiol, J., Cecere, J., Gianfranceschi, L., Grobler, J.P., Kotze, A., Riutort, M., González-Solís, J., Rubolini, D., et al. (2023). Birds of a feather flock together: a dataset for Clock and Adcyap1 genes from migration genetics studies. Scientific Data. https://doi.org/10.1038/s41597-023-02717-8.

3. Le Clercq, L.-S., Kotzé, A., Grobler, J.P. and Dalton, D.L. (2023), PAReTT: a Python package for the automated retrieval and management of divergence time data from the TimeTree resource for downstream analyses. Journal of Molecular Evolution. https://doi.org/10.1007/s00239-023-10106-3 

4. Le Clercq, L.-S., Kotzé, A., Grobler, J.P., and Dalton, D.L. (2023), Biological clocks as age estimation markers in animals: a systematic review and meta-analysis. Biological Reviews. https://doi.org/10.1111/brv.12992  

5. Le Clercq, L.-S., Kotzé, A., Grobler, J.P., and Dalton, D.L. (2023), Dataset generated in a systematic review and meta-analysis of biological clocks as age estimation markers in animal ecology. Data in Brief.  https://doi.org/10.1016/j.dib.2023.109615

6. Le Clercq, L.-S. (2023), ABCal: a Python package for Author Bias Computation and Scientometric Plotting for Reviews and Meta-Analyses. Scientometrics. https://doi.org/10.1007/s11192-023-04880-6.

7. Le Clercq, L.-S., Phetla, V., Osinubi, S.T., Kotzé, A., Grobler, J.P., and Dalton, D.L. (2024), Phenotypic correlates between candidate genes for migration among races of Diederik cuckoos, Chrysococcyx caprius. Ecology and Evolution. http://dx.doi.org/10.1002/ece3.70117 

8. Le Clercq, L.-S., Kotzé, A., Grobler, J.P., and Dalton, D.L. (2024), Methylation-based markers for the estimation of age in African Cheetah, Acinonyx jubatus. Molecular Ecology Resources. https://doi.org/10.1111/1755-0998.13940

9. Le Clercq, L.-S., Dalton, D.L. & Kotzé, A. (2018). Molecular age estimation based on promotor CpG methylation using methylation sensitive PCR. In Poster Presented at: 9th Annual Research Symposium of the National Zoological Gardens of South Africa. SANBI, Pretoria. URI: http://hdl.handle.net/11660/11182 DOI: https://doi.org/10.13140/RG.2.2.11352.21768  

10. Le Clercq, L.-S. (2023). Python Automated Retrieval of TimeTree data (PAReTT), version 1.0.2. https://github.com/LSLeClercq/PAReTT 

11. Le Clercq, L.-S. (2023). Dataset of Clock and Adcyap1 alleles for Birds (AvianClocksData), version 1.0.2. https://github.com/LSLeClercq/AvianClocksData 

12. Le Clercq, L.-S. (2023). Author Bias Computation and Scientometric Plotting (ABCal), version 1.0.2. https://github.com/LSLeClercq/ABCal 

13. Le Clercq, L.-S, Dalton, D.L., Kotzé, A. & Grobler, J.P. (2023). PCR Amplification of Clock and Adcyap1 genes with EmeraldAmp® GT PCR Master Mix in Avian species for polymorphism elucidation. protocols.io. https://dx.doi.org/10.17504/protocols.io.6qpvrdwk3gmk/v1

14. Le Clercq, L.-S., Dalton, D.L., Kotzé, A. & Grobler, J.P. (2023). ABI Sanger Sequencing of Avian Clock genes to elucidate markers for Migration Phenology. protocols.io. https://dx.doi.org/10.17504/protocols.io.3byl4k6zrvo5/v1

15. Le Clercq, L.-S., Dalton, D.L., Kotzé, A. & Grobler, J.P. (2023). Designing an EpiTYPER bisulfite sequencing assay for age estimation in Acinonyx jubatus based on human orthologues. protocols.io. https://dx.doi.org/10.17504/protocols.io.j8nlk4yk1g5r/v1

16. Le Clercq, L.-S., Dalton, D.L., Kotzé, A. & Grobler, J.P. (2023). DNA extraction protocol for animal blood samples using the E.Z.N.A blood mini kit. protocols.io. https://dx.doi.org/10.17504/protocols.io.ewov141xpvr2/v1