Understanding the influence of relatedness on fine-scale social interactions within a population is fundamental to understanding the role of kinship in animal societies. In this study, Foroughirad et al provide insight into the quality of Single Nucleotide Polymorphism (SNP) data required to obtain accurate and precise parentage assignments and relatedness coefficients using data from a long‐term behavioural study on bottlenose dolphins with a known partial pedigree. They then go on to explore how the quality of these estimates influence post-hoc analyses exploring the relationship between relatedness and social structure. Again, they provide important practical guidance about the quality of data needed for these types of analyses. This article was published in Molecular Ecology Resources: read the full article here, and read our interview with Vivienne Foroughirad, lead author of the study, below.
What led to your interest in this topic / what was the motivation for this study?
In the broadest sense my research interests concern the evolution of sociality and complex social behaviors such as cooperation. To that end, I was interested in our ability to parcel out contexts in which cooperation occurs between kin versus between unrelated individuals. Non-kin cooperation is rare is animal societies, and a common way to search for examples is to first investigate the link between the strength of social relationships and the genetic relatedness of pairs. Since genotyping-by-sequencing is now cheaper and more accessible than ever, I wanted to explore the effects this increased resolution would have on our power to test the relationship between social structure and relatedness, especially in viscous populations with strong philopatry.
What difficulties did you run into along the way?
In our case, the greatest challenges centered around maintaining a longitudinal study on a wild marine mammal with a large enough sample size to make answering these types of questions feasible. We were lucky to have over 30 years of data available from the Shark Bay Dolphin Project which allowed us to verify some of the reconstructed pedigree relationships, as well as measure detailed home range usage and social associations. An analytical difficulty we encountered is how to account for the confounding effect of philopatry or limited dispersal on social relationships with kin if you want to distinguish kin discrimination from more passive kin associations that are a byproduct of shared space use.
What is the biggest or most surprising finding from this study?
We provided evidence that genotyping-by-sequencing methods could produce more precise relatedness values than typical microsatellite analyses, which isn’t surprising. What was less well-understood was the effect this would have for downstream analyses, such as those testing whether relatedness correlated with social affiliation. We found that even though our study species exhibits strong, life-long affiliative relationships between maternal kin, there were a surprising number of scenarios under which our analysis failed to detect a significant correlation between genetic relatedness and social associations. We also found surprisingly diminishing returns in relatedness resolution with increasing sample size (number of individuals) when small numbers of markers were used.
Moving forward, what are the next steps for this research?
Pedigree reconstruction is rapidly improving, especially where there is access to new genetic resources such as chromosome-level assemblies for non-model organisms. Improved kin assignment methods will allow us to investigate the function of these relationships at the level of the individual, which will help us to tease out how both intra- and inter-specific variation in ecology and demography affect social behavior. Within my own study site, I’m using these data to look at the effect of family size on social network position and reproductive success, as well as the demographic conditions that facilitate the formation of non-kin bonds. We’re also working on ways to better discriminate between maternal and paternal kin, which will be important for investigating the mechanisms of kin recognition.
What would your message be for students about to start their first research projects in this topic?
That this is a great idea! Rapid advances in technology will open up new avenues of inquiry and there is lots of work to be done. Nevertheless, as with any field, you also need to know when to stop and submit. There will always be a new higher coverage genome or updated version of the software you’re using that’s about to be released, but if you keep reanalyzing your data with each advance, you’ll never finish a project. My second piece of advice would be to practice simulating data and analyzing it. Building simulated datasets, tweaking parameters, and testing different software has really deepened my understanding of methodologies- plus you can start before you even get your first sequencing results and be ready with a tested pipeline when you do get results in hand.
What have you learned about science over the course of this project?
That building a robust, reproducible, and well-documented pipeline for analysis is crucial. It might take a bit more work to set up, but it’s always worth it. I also benefitted a lot from the opportunity to present my work to audiences from different disciplines which helped me keep the big picture in mind since I’m the kind of person that gets easily caught up in minutiae. Biologically, I’m always reminded that there’s so much individual variation that gets masked by conducting analyses at the population level, and that rather than being discounted as noise, that variation could be leveraged to ask really interesting questions about how ecology and demography affect behavior.
Describe the significance of this research for the general scientific community in one sentence.
The correlation between genetic relatedness and the strength of social relationships can be masked by the limited power of typical published sample sizes.
Describe the significance of this research for your scientific community in one sentence.
We provide practical guidance for how sample sizes and sequencing methods might interact to improve precision of relatedness estimates and their effect on the analysis of social structure, using wild bottlenose dolphins as a case study.
Foroughirad, V., Levengood, A. L., Mann, J., & Frère, C. H. (2019). Quality and quantity of genetic relatedness data affect the analysis of social structure. Molecular Ecology Resources, 1181–1194. https://doi.org/10.1111/1755-0998.