Evolutionary genomics: new perspectives and novel medical applications

Informations projet

EvoGenMed

N° de convention de subvention: 669207

DOI

10.3030/669207

Projet clôturé

Date de signature de la CE 18 Novembre 2015

Date de début 1 Janvier 2016

Date de fin 30 Juin 2021

Financé au titre de

• EXCELLENT SCIENCE - European Research Council (ERC)

Coût total

€ 2 497 996,00

Contribution de l’UE

€ 2 497 996,00

Coordonné par

UNIVERSITY OF BATH
United Kingdom

Periodic Reporting for period 4 - EvoGenMed (Evolutionary genomics: new perspectives and novel medical applications)

Période du rapport: 2020-07-01 au 2021-06-30

Résumé du contexte et des objectifs généraux du projet

Why is our genome the way it is? Why, for example, is it so very large? In understanding the answers to questions like these we hope to understand which parts of our genome are functional and why. Knowing which parts are functional can in turn could lead to improved diagnostics and to improved gene -based therapies.

We are particularly interested in a core idea in evolutionary genomics, namely that selection should be less efficient when populations are small. This has been hypothesised to explain why our genome is so large - selection is too weak in large bodied organisms to be able to prevent the spread - by chance - of insertions that are just a little bit bad for us. We want to see if this idea can be extended: if selection is weak and leads to a bloated genome, might our genome also be prone to errors and if so, does this mean that selection in us is commonly on error mitigation devices?

One result of such selection to mitigate errors could be an increased role for what have been thought to be largely irrelevant parts of our genome. We focus on so-called silent sites - silent because it is thought that mutations at these sites have no impact on us. We have however shown that there is selection on such sites/mutations. Why is this? In understanding this can we make better new genes to help disease-bearing patients and can we improve diagnosis?

The objectives of the project are thus
- to examine the role of error in evolution - both as a means to cause selection to prevent it and as a means to the evolution of novelty.
- to go from understanding the relationship between error prevention and selection on synonymous sites and so as to improve both diagnostics and the etiology of disease
- to go from understanding of errors and innocuous mutations to improve therapeutics both by improving new genes and by defining sites in the genome where these new genes are less likely to cause knock-on errors by affecting the expression of neighbours.

This work is of societal relevance not just because has the potential to impact on medicine directly, but because we are also asking fundamental questions about how evolution works and, philosophically, what it is to be human. Are we are perfect genetic machine or a barely adequate error prone product of inefficient selection?

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

Classical population genetical theory predicts that selection will be less efficient when population sizes are small as in these cases random events play a more important role. We noticed however that if selection is less effective error rates (meaning mutation rates, errors in gene processing) also go up. As such we might expect selection for control of errors to be stronger in small populations. We have found evidence that population size is indeed associated with genome bloating and high errors rates but also in turn that for some errors selection appeared to be stronger when populations are small.

One of these errors is missplicing – the way we cut up our RNAs before making proteins. One curiosity of our genes is that we have lots more sequence that helps the system to stop making errors than species with larger populations. A consequence of this is that some mutations that are often assumed to be irrelevant are, as we showed, under strong selection. This strong selection against what otherwise are innocuous mutations when populations are small is what the novel framework predicted but was counter to the classical model.

We have also used this same information to predict new disease-causing mutations, improve artificial genes used in gene therapy and to make vaccines, while all the time preserving the protein product. We also redirected our efforts to understand mutation and selection on these “silent” changes in SARS-CoV-2. In addition, in understanding how control of when a gene is turned on and off, affected by the on/off switches of neighbouring genes we have understood both how much gene expression evolves and where in the genome to put artificial genes for gene therapy where they are least likely to be subject to such errors. The same analyses allowed us to extract what have been called the holy grail of human stem cells, naïve cells.

But errors aren’t always bad: they can also make the raw material for novelty. We have looked at several cases of this looking at how new genes evolve and in the process discovered a new type of cell in the human early embryo that is a waste-bin for error laden cells.

The project has resulted, to date, in 32 publications, one patent and one web resource.

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

This project interfaces both fundamental evolutionary genetics and medicine. We have provided the first robust evidence that the correct view of the human genome is that it is bloated owing to weak selection, but in addition that this weak selection has led to more errors and in turn more error mitigation. Thus in contradiction to classical theory, selection - at least for error mitigation - can be stronger when populations are small. These results have a direct societal impact in reforming the notion of human perfection.

We have demonstrated the existence of a species with error prone translation owing to the presence of two tRNAs for the same codon. This breaks the last rule of genetic codes: in this species we cannot predict the proteome just knowing the genome as translation of one codon is stochastic.

As regards applications to medicine, the first application of our novel protocol to design new genes for gene therapy outperformed the commercially available alternative.

Our research into the evolution of error prone gene expression has led to us being able to isolate naive human stem cells and provide an improved growth medium for them (patented).

Errors in gene processing pathways