Causes and consequences of parental age effects on offspring quality

How ageing occurs, why it varies across individuals, and what determines its pace, pattern, and form are crucial questions for understanding life-history diversity. Genomic variation accounts for a low proportion of phenotypic variation in ageing trajectories, highlighting the role of environmental and other non-genetic factors [1], but these factors remain relatively understudied. Albert Lansing discovered that parental age negatively affects the longevity of descendants, indicating the transgenerational transmission of parental state at breeding. Subsequent research suggests this “Lansing effect” is common [3] and may be ubiquitous in insects [4]. The Lansing effect has important consequences as it means the transitory aspects of the environment affecting parents can also affect their offspring. However, most research focusses on processes occurring within generations; how parental age affects lifespan and fitness of descendants across generations requires urgent attention [5]. Insects provide powerful models for this type of question because of their short generation time and conduciveness to performing both manipulative experiments and field studies. Using the field cricket Gryllus bimaculatus as the ideal model, we will for the first time uncover these aspects of the Lansing effect:

Form: The Lansing effect has mainly been studied in ectotherms and is understood in terms of their age. However, physiological processes are dependent on temperature, so the biological age of an ectothermic individual will also depend on the temperature it has experienced [6–9]. Therefore, it is unclear whether the parents chronological or biological age at breeding causes the Lansing effect. We will establish the independent effects of chronological age (time since birth) and biological age (temperature-dependent deterioration in an individual’s condition, expressed as time until death) on offspring longevity. We will also unravel how, and in what form, offspring longevity is affected. Offspring from older parents may be in poor condition at birth, exhibiting increased baseline mortality risk, or they could age faster, with no differences in condition at birth. These contrasting causes of mortality have important implications. The Lansing effect is assumed to negatively affect offspring fitness, but the negative effect on longevity could covary with increased early-life performance through a switch to a fast life-pace strategy, limiting the net effect on fitness.

Mechanism: It remains unclear how parental age affects offspring quality. The germline is separated from the soma by the Weismann barrier, but this barrier could be leaky, meaning age related damage can accumulate in the germline [10]. We will determine whether parental age at breeding causes oxidative damage in the germline, reducing DNA integrity. We will also determine if DNA-methylation state of the germline could underpin parental age effects on offspring quality.

Function: Experimental field studies of the Lansing effect are lacking, meaning their fitness consequences remain unclear. We will conduct a novel field study, exploiting our extensive experience with a highly suitable field system in Spain (www.wildcrickets.org), to estimate the fitness consequences of the Lansing effect across multiple generations, assessing its importance for adaptation/evolution.

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Image Captions

Fig. 1 High altitude meadow in Asturias, Spain,Fig 2. Tagged Gryllus campestris adults outside burrow


1. Form: To test the hypothesis that the biological age of parents affects offspring quality we will expose 200 adult genetic siblings to cool (22°C) and warm (32°C) temperatures, enabling within genotype estimation of treatment effects. The optimal temperature for G. bimaculatus is ~27°C and cooler and warmer temperatures decelerate and accelerate biological age, respectively [15]). We will source outbred G. bimaculatus from S. Spain. Adults will be mated at equal chronological, but differing biological ages, or equal biological, but differing chronological ages. We will measure parental age effects on offspring quality by transferring half of the offspring eggs to an intermediate temperature environment (27°C) where they are allowed to develop. We will measure offspring size, growth rate, age-dependent mortality, age at reproductive maturity, fecundity, and longevity. We will determine if the Lansing effect arises through increased offspring frailty after hatching or through their accelerated ageing using the age-specific mortality data. We will test the critical prediction that the Lansing effect is a consequence of a switch to a fast “pace of life” and hence that the negative effect on longevity covaries with increased growth rate, body size, and early life fecundity. We will estimate the net treatment effect of manipulated parental biological age on offspring performance.

2. Mechanism: Manipulating biological age as before, we will measure common biomarkers of oxidative stress (MDA, AOPPs), DNA damage (8-OHdG, telomere length), and altered methylation state in the germline, to for the first time determine the inter- and transgenerational transmission of parental somatic ageing affecting offspring quality.

3. Function: We will conduct a field study in Spain to determine whether the Lansing effect constrains adaptation to the local climate conditions, which have shown a consistent trend of rapid warming during the past 30 years. We will manipulate parental temperature conditions, simulating likely climate warming scenarios, by applying an array of infrared heating lamps and/or artificial shade, which we have successfully trialed. This manipulation will induce parental age effects in response to conditions mimicking climate change. We will estimate selection on these parental age effects by measuring offspring fitness. This experimental field study will provide crucial insight into the role of the Lansing effect in adaptation and evolutionary change in response to environmental warming.

Project Timeline

Year 1

Y1 – Months 1-6: Core skills training. Initiate Lansing effect lab project (cricket husbandry, mating design, pedigree, phenotypic performance measures).

Y1 – Months 7-12: Collect germ line samples, DNA extractions for the characterisation of DNA-methylation and noncoding RNA landscapes. We will also measure oxidative stress and telomere length of germ cells.

Year 2

Y2 – Months 1-6: The student will join the WildCrickets field work in Spain to conduct the in situ environmental manipulations, perform matings according to a predetermined breeding design, and collect phenotypic performance measurements.

Y2 – Secondment to St Andrews to conduct bioinformatic analyses. The student will also initiate a quantitative genetic study as part of their core training.

Year 3

Y3 – Months 1-6: Data analyses to investigate parental age effects on offspring performance, germ line DNA methylation, and oxidative stress and telomere dynamics. By this time we will also obtain the fitness data from the field study to estimate the fitness consequences of the Lansing effect.

Y3 – Months 7-12: Finalising data analyses. Chapter and manuscript writing. Conference presentations.

Year 3.5

Y4 – Months 1-6: Submit thesis and work on papers.

& Skills

The studentship provides an opportunity to receive training from a diverse team of internationally recognized experts to develop skills in cutting-edge research techniques consistent with NERC’s mission. For example, numeracy will be developed through engagement with statistical quantitative genetics analyses and we will also work with the student to develop new theory to extend the quantitative genetic framework to include epigenetic modes of heritable biological variation. Best practice for lab technique plus proficiency in quantitative and epigenomic analyses will equip the student with skills that can be applied in other settings or systems during their future career. We will encourage the student to identify relevant external workshops in molecular evolution and local adaptation and enable them to pursue sub-specialities of their own interest. Fieldwork training will be facilitated by the PIs, and the student will be embedded within a highly collegiate postgraduate environment at Glasgow that offers both formal and informal mentoring, access to seminars and more informal discussion groups. The student and supervisors will take advantage of the DTP scheme to arrange for a secondment to St Andrews to facilitate knowledge exchange through institutional seminars or workshops, thus widening the network of potential contacts, colleagues and collaborators for the student.

The project will benefit from matured genomic resources including an annotated genome, gene expression data, a genome browser (www.chirpbase.org), and bioinformatic pipelines in closely-related cricket species, and includes a secondment to co-supervisor Bailey’s lab at the University of St Andrews.

References & further reading

References: 1. Eichler EE, et al. (2010) Nat Rev Genet 11, 446–450. 2. Lansing A (1947) J Gerontology 2, 228–239. 3. Campos FA et al. (2022) PNAS 119, e2117669119. 4. Ivimey-Cook E, Shorr S, Moorad J (2022) Biorxiv, 2022.04.27.489689. 5. Monaghan P, Maklakov AA, Metcalfe NB (2020) TREE 35, 927–937. 6. Mair W, et al. (2003) Science 301, 1731–1733. 7. Boonekamp JJ, Briga M, Verhulst S (2015) Exp. Gerontol. 71, 95–102. 8. Miquel J, et al. (1976) Mech Ageing Dev 5, 347–370. 9. Keil G, Cummings E, Magalhães JP de (2015) Biogerontology 16, 383–397. 10. Monaghan P, Metcalfe NB (2019) Proc R Soc B 286, 20192187

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