Working on non-model organisms comes with both challenges and rewards. While the joy and satisfaction of uncovering knowledge in wild populations drives many scientists, the lack of genomic resources can be a roadblock for many important research themes, such as determining the extent of evolutionary potential and response to selection. In this paper from Molecular Ecology Resources, Laura Gervais and co-authors demonstrate the potential for RAD-sequencing to overcome these challenges and estimate heritability and evolutionary potential in wild populations, even for non-model organisms without many existing genomic resources. Read below for a behind-the-scenes look at their paper!
Link to the study: https://onlinelibrary.wiley.com/doi/full/10.1111/1755-0998.13031
What led to your interest in this topic / what was the motivation for this study?
We are interested in how natural populations adapt to environmental changes. These changes occur rapidly and there is an urge to accumulate results on wild populations’ capacity of adaption for a wide range of species. Traditionally, measuring the evolutionary potential of a trait required long-term field surveys of phenotypic data and genetic relatedness obtained from a multi-generational pedigree. This is challenging to obtain because many free-ranging populations are hard to sample with the intensity required for pedigree reconstruction. We believe that genome-wide data and in particular RAD-sequencing data might be an opportunity to overcome this issue but we still lack an accessible practical framework to go from genomic data to the estimation of a population’s evolutionary potential.
What difficulties did you run into along the way?
We had to overcome two main methodological difficulties. First, to investigate the effects of the sequencing strategy and the SNP calling/filtering procedure ultimately on GRM-based heritability, we had to run a considerable amount of bioinformatic and quantitative genetic analyses, which both proved to be time consuming. Secondly, there was not much methodology available on how to implement genomic relatedness matrix in a quantitative genetic linear mixed model. We hope that our work will make this approach more easily accessible.
What is the biggest or most surprising finding from this study?
When we started the study, we did not expect that it would be possible to run genomic quantitative genetic analyses with only a few hundred individuals. Most of our colleagues were skeptical when we mentioned that we found significant heritability (at the beginning with only 170 genotyped individuals). Our results give hope that evolutionary potential studies in the wild might be virtually accessible for any natural population when using the appropriate sampling and sequencing design.
Moving forward, what are the next steps for this research?
We are working to combine genome-wide data with intensive bio-logging technology (data on animal movement) and high-resolution habitat information. The synergy between these three high-density data technologies offers a great opportunity to understand how species adapt to environmental changes across complex landscapes.
What would your message be for students about to start their first research projects in this topic?
Our message would be to never hesitate to contact people and surround yourself with all the necessary help. This is a domain that evolves rapidly and that is very exciting but may be quite disconcerting. It seems essential to remain informed and open-minded. Lastly, I would say that self-learning is really rewarding but that there is always the opportunity to ask for help to learn and get over a problem efficiently.
What have you learned about science over the course of this project?
We have learned that more interdisciplinary exchanges between ecologists, molecular biologists and bioinformaticians are useful and can help to build such an integrative approach. This may be challenging as they often have different views on different issues that need to be conciliated. There is a need to meet and exchange ideas to get the most out of this type of projects.
Describe the significance of this research for the general scientific community in one sentence.
This study sheds light on a unique opportunity to evaluate whether species have the genetic potential to adapt to environmental changes, and this for virtually any non-model organism.
Gervais, L., Perrier, C., Bernard, M., Merlet, J., Pemberton, J. M., Pujol, B., & Quéméré, E. RAD‐sequencing for estimating genomic relatedness matrix‐based heritability in the wild: A case study in roe deer. Molecular Ecology Resources. 19(5). 1205-1217. https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.13031