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Dryad

Parental age does not influence offspring telomeres during early life in common gulls (Larus canus)

Cite this dataset

Sepp, Tuul et al. (2021). Parental age does not influence offspring telomeres during early life in common gulls (Larus canus) [Dataset]. Dryad. https://doi.org/10.5061/dryad.2ngf1vhn5

Abstract

Parental age can affect offspring telomere length through heritable and epigenetic-like effects, but at what stage during development these effects are established is not well known. To address this, we conducted a cross-fostering experiment in common gulls (Larus canus) that enabled us distinguish between pre- and post-natal parental age effects on offspring telomere length. Whole clutches were exchanged after clutch completion within and between parental age classes (young and old) and blood samples were collected from chicks at hatching and during the fastest growth phase (11 days later) to measure telomeres. Neither the ages of the natal nor the foster parents’ predicted the telomere length or the change in telomere lengths of their chicks. Telomere length was repeatable within chicks, but increased across development (repeatability = 0.55, Intraclass Correlation Coefficient within sampling events 0.934). Telomere length and the change in telomere length were not predicted by post-natal growth rate. Taken together, these findings suggest that in common gulls, telomere length during early life is not influenced by parental age or growth rate, which may indicate that protective mechanisms buffer telomeres from external conditions during development in this relatively long-lived species.

Methods

1. Field methods.

We conducted the study between the end of May – early June 2017 on a free-living, known-age breeding population of common gulls located on Kakrarahu islet in Matsalu National Park on the west coast of Estonia (58°46' N, 23°26' E). A total of 40 nests were included in the experiment. Nests and experimental groups were chosen based on the age of the mother, but the father’s age was also known. Common gulls mates assortatively with respect to age and the ages of the parents were highly positively correlated (Spearman r=0.74, p<0.0001) Half of the breeders (n = 20 females) were young, on their 1st-3rd breeding event (age exactly 5 years). Another half (n = 20 females) were middle-aged or older (15-30 years old, average age 18 ± 3.37 (SD) years). In total, 19 males were 5-7 years old (average age 5.52 ± 0.80 (SD) years) and were grouped as “young”, 21 males were 10+ years (average age 16.29 ± 5.58 (SD) years) old and were grouped as “old”.

We cross-fostered whole clutches right after the clutch was completed both within and between maternal age classes (Table 1), so that all of the chicks included in this experiment hatched in foster-parent’s nests. Half of the clutches were cross-fostered between age classes (to test for the effects of parental age – young vs old - on offspring telomere length) and half of the clutches within age classes (to exclude the possibility that we are measuring the effect of cross-fostering). The 72 chicks that were successfully caught for second sampling were included in the study. From the nests of “old” parents, we recaptured on average 1.6 chicks, from “young” parents, 2.0 chicks (t-test t=-1.7, p=0.1). Within two days from hatching, we collected the first blood sample (10-30 µL taken, from brachial vein) for telomere measurement (average age 0.61±0.09 (SE) days), individually marked the chicks for identification, and measured chick head size (the distance from the tip of the bill to the back of the head) with a calliper to the nearest 0.1 mm. Chicks were blood sampled again near their nests sites between 5-20 days after hatching (mean age: 10.62 days ±0.35 SE). Blood samples were kept on ice in an insulated box while on the islet, and stored at -20°C until the end of the field work period, when they were transferred to -80ºC and maintained until analyses. The experimental protocol was approved by the Ministry of Rural Affairs of the Republic of Estonia (licence no. 106, issued 24.05.2017) and was performed in accordance with relevant Estonian and European guidelines and regulations.

2. Telomere measurement and molecular sexing

DNA was extracted from whole blood samples using Macherey Nagel Nucleospin Blood kits following the manufacturer’s protocol. DNA concentration was assessed with a Nanodrop 8000 (Thermo Scientific), all our samples had high purity. Relative TL was measured using qPCR (quantitative polymerase chain reaction) on an Mx3000P (Stratagene). The relative telomere length (T/S) of the samples was calculated as the ratio of the telomere repeat copy number (T) to that of a single copy control gene (S), relative to the reference sample. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) was used as the single copy control gene. We used the following gull specific GAPDH forward and reverse primers (Integrated DNA Technologies): 5’-CGGAGCACCGCTTACAATTT-3’ and 5’- GCATCTCCCCACTTGATGTTG-3’ respectively (concentration in reaction mixture 200 nM). Amplified samples were run on a 3% agarose gel to verify that the amplification was a single product, which yielded a single band at 77 bp as expected. We used the following telomere primers (Quanta Bio, with final concentration of 200 nM): TEL 1b: 5’-CGGTTTGTTTGGGTTTGGGTTTGGGTT-3’ and TEL 2b: 5’-GGCTTGCCTTACCCTTACCCTTACCCT-3. The qPCR reactions for GAPDH and telomeres were run on separate plates. The cycling parameters for telomere plate were following: 1 cycle – 10 min at 95°C, 27 cycles -15 sec at 95°C, 30 sec at 58°C, 30 sec at 72°C, 1 cycle of dissociation curve (melt curve). The cycling parameters for the GAPDH plate were following: 1 cycle -10 min at 95°C, 40 cycles – 30 sec at 95°C, 30 sec at 60°C, 1 cycle of dissociation curve (melt curve). All reactions used 20 ng of DNA in a final volume of 25 µl containing 12.5 µl of SYBR green Master Mix, 0.25 µl forward and reverse primer, 6 µl water, and 6 µl of DNA sample. A negative control of water was run on each plate. All samples were run in duplicate, and average values were used to determine the T/S ratio. Treatment groups were distributed approximately equally between plates. Technical replicates of each sample, and the first and second sample for each bird were run on the same plate. Duplicates that had a SD higher of 0.25 were rerun again as duplicates. In order to assess the efficiencies of each plate, samples were run against a standard curve of 40, 20, 10, 5, and 2.5 ng produced by serially diluting a reference sample. In all cases, plate efficiencies were in the accepted range (i.e. 100+/-15%) and all of the samples fell within the bounds of the standard curve. Average plate efficiencies and standard errors for GAPDH and telomere plates were 102.34 ± 3.00, and 98.94 ± 3.00, respectively. The average intra-plate variation of the Ct values was 0.82% for the telomere assays and 0.19% for the GAPDH assays, and the inter-plate CV-s of the Ct values for telomere and GAPDH assays were 0.64% and 0.34%, respectively. The same individual was also included on every plate and the coefficient of variation of the T/S ratio across plates was 8.12%. Standards and Golden (reference sample)  were from birds not included in the experiment. A subset of samples (45) were also run across two plates to calculate the Intraclass Correlation Coefficient (ICC) for the T/S ratio (single measurements ICC = 0.876, 95% CI 0.785 ± 0.930, p < 0.0001).

The CHD gene (Chromo Helicase DNA-binding gene) was use as a molecular marker for sexing the birds. PCR was used to amplify the CHD genes in DNA extracted from the red blood cells.  The primers used in the PCR were as follows: 2550F (5’-GTTACTGATTCGTCTACGAGA-3’) and 2718R (5’- ATTGAAATGATCCAGTGCTTG-3’). The PCR products were visualized by gel electrophoresis and a FluorChem FC2 imaging system. One band on the gel indicates a male and two bands indicates a female.

Funding

Estonian Research Council, Award: IUT21-1

European Research Council, Award: MSC grant 701747

European Commission, Award: MOBJD344

Estonian Research Council, Award: IUT34-8

Estonian Research Council, Award: PSG653

Estonian Research Council, Award: PSG458