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ERC

NoisyAgeing Report Summary

Project ID: 638426
Funded under: H2020-EU.1.1.

Periodic Reporting for period 1 - NoisyAgeing (Beyond genotype to phenotype: how ancestor lifestyle impacts on lifespan variation in descendants)

Reporting period: 2015-06-01 to 2016-11-30

Summary of the context and overall objectives of the project

Others and I have shown that inter-individual variability in the longevity pathways –and in particular, in stress response genes- has consequences for genetic/environmental phenotypic robustness as well as for lifespan in Caenorhabditis elegans. The main goal of this proposal is to uncover the causes that explain inter-individual variability in lifespan. The variability across individuals must include an important non-genetic component because the laboratory strains of this nematode are genetically homogeneous. I propose that lifespan variation is a by-product of non-genetic sources of variability in the pathways that control longevity.

The overall objectives of this project are:
• Aim 1: To use High Throughput (HT) techniques to survey inter-individual variability of longevity related transcripts.
• Aim 2: To find environmental triggers behind transgenerational inheritance of lifespan and study whether they introduce inter-individual variability in gene expression.
• Aim 3: To uncover the molecular causes of inter-individual variability. The output of Aims 1 and 2 are transcripts that vary across individuals.
• Aim 4: Develop a next generation Nano-fluidic device to perform longitudinal analysis and use it to test the correlation between the levels of gene expression and the probability of living a longer healthier life.

Understanding the basis of lifespan variability is crucial for personalised medicine, where not the average population but rather the individual is centre stage. It is equally crucial for the identification of new factors that may have been missed by the analysis of population averages that can have an impact for human ageing and health. More generally, I propose the inter-individual variability in the vertical transmission of transcriptional states as a unifying framework underlying a large class of adaptive phenotypes that vary among individuals.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

The main results obtained during this period are:
• We have optimised techniques that allow the quantitation of steady state levels of transcripts in single worms. First, we have developed nano-fludics based polymerase chain reaction technique as well as a statistical algorithm that provide highly accurate and reproducible quantitation of biological variance. This is the first time that such technique has been developed for a multicellular organism.
• We have for the first time surveyed the inter-individual variability landscape of stress-related genes in young adult C. elegans and found that there are two clear trends: highly-inducible genes have high levels of biological variance in the absence of stress and this is not the case for stress-related genes that are non-inducible. We have found that for both these classes of behaviours there are post-transcriptional mechanisms constraining variance.
• We have found that maternal age directly impacts the probability of the offspring in expressing the phenotypic effects of mutations. In other words, we have found that inter-generational inheritance contributes to phenotypic inter-individual variability.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

• We have found that maternal age contributes to phenotypic variability, for example by increasing the probability of the offspring of expressing the phenotype associated with a mutation. Many studies in humans and mammalian models have demonstrated maternal effects for the offspring. For example, maternal nutrition is associated with an increased risk of metabolic disease in the F1 progeny. Parental age is known to cause intergenerational effects in mammals. For example, a number of studies have linked advanced paternal age with an increased risk of neuropsychiatric diseases such as schizophrenia and autism in the offspring. Although these studies rule out age-related de novo mutations associated with increased parental age, the complexity of studying such phenotypes in mammals has precluded molecular follow up studies. Our system is very simple and our results highly reproducible and therefore we believe to be in a good position to uncover the molecular mechanisms underlying maternal age influences on the offspring.

• We have optimised for the first time techniques that allow the quantitation of steady state levels of transcripts in single worms. These techniques have allowed as to accurately measuring biological variance for the first time in a whole organism. These technologies have allowed us to uncover that post-transcriptional control mechanisms are key in the regulation of biological variance. Although formal demonstrations of their relevance for variability have been done, proper biological examples of this sort are missing, so our results go beyond the state of the art. In the next period, we will perform research that will help us uncover how such variability impact phenotypes that are important for society. For example, how this molecular variability impacts the rates of ageing across individuals.
Record Number: 196309 / Last updated on: 2017-03-28