My talk at the ChickenStress Genomics and Bioinformatics Workshop

A few months ago I gave a talk at the ChickenStress Genomics and Bioinformatics Workshop about genetic mapping of traits and gene expression.

ChickenStress is a European training network of researchers who study stress in chickens, as you might expect. It brings together people who work with (according to the work package names) environmental factors, early life experiences and genetics. The network is centered on a group of projects by early stage researchers — by the way, I think that’s a really good way to describe the work of a PhD student — and organises activities like this workshop.

I was asked to talk about our work from my PhD on gene expression and behaviour in the chicken (Johnsson & al. 2018, Johnsson & al. 2016), concentrating on concepts and methods rather than results. If I have any recurring readers, they will already know that brief is exactly what I like to do. I talked about the basis of genetic mapping of traits and gene expression, what data one needs to do it, and gave a quick demo for a flavour of an analysis workflow (linear mixed model genome-wide association in GEMMA).

Here are slides, and the git repository of the demo:

Journal club of one: ”Give one species the task to come up with a theory that spans them all: what good can come out of that?”

This paper by Hanna Kokko on human biases in evolutionary biology and behavioural biology is wonderful. The style is great, and it’s full of ideas. The paper asks, pretty much, the question in the title. How much do particularities of human nature limit our thinking when we try to understand other species?

Here are some of the points Kokko comes up with:

The use of introspection and perspective-taking in invention of hypotheses. The paper starts out with a quote from Robert Trivers advocating introspection in hypothesis generation. This is interesting, because I’m sure researchers do this all the time, but to celebrate it in public is another thing. To understand evolutionary hypotheses one often has to take the perspective of an animal, or some other entity like an allele of an enhancer or a transposable element, and imagine what its interests are, or how its situation resembles a social situation such as competition or a conflict of interest.

If this sounds fuzzy or unscientific, we try to justify it by saying that such language is a short-hand, and what we really mean is some impersonal, mechanistic account of variation and natural selection. This is true to some extent; population genetics and behavioural ecology make heavy use of mathematical models that are free of such fuzzy terms. However, the intuitive and allegorical parts of the theory really do play an important role both in invention and in understanding of the research.

While scientists avoid using such anthropomorphizing language (to an extent; see [18,19] for critical views), it would be dishonest to deny that such thoughts are essential for the ease with which we grasp the many dilemmas that individuals of other species face. If the rules of the game change from A to B, the expected behaviours or life-history traits change too, and unless a mathematical model forces us to reconsider, we accept the implicit ‘what would I do if…’ as a powerful hypothesis generation tool. Finding out whether the hypothesized causation is strong enough to leave a trace in the phylogenetic pattern then necessitates much more work. Being forced to examine whether our initial predictions hold water when looking at the circumstances of many species is definitely part of what makes evolutionary and behavioural ecology so exciting.

Bias against hermaphrodites and inbreeding. There is a downside, of course. Two of the examples Kokko gives of human biases possibly hampering evolutionary thought are hermaphroditism and inbreeding — two things that may seem quite strange and surprising from a mammalian perspective, but are the norm in a substantial number of taxa.

Null models and default assumptions. One passage clashes with how I like to think. Kokko brings up null models, or default assumptions, and identifies a correct null assumption with being ”simpler, i.e. more parsimonious”. I tend to think that null models may be occasionally useful for statistical inference, but are a bit suspect in scientific reasoning. Both because there’s an asymmetry in defaulting to one model and putting the burden of proof on any alternative, and because parsimony is quite often in the eye of the beholder, or in the structure of the theories you’ve already accepted. But I may be wrong, at least in this case. If you want to formulate an evolutionary hypothesis about a particular behaviour (in this case, female multiple mating), it really does seem to matter for what needs explaining if the behaviour could be explained by a simple model (bumping into mates randomly and not discriminating between them).

However, I think that in this case, what needs explaining is not actually a question about scope and explanatory power, but about phylogeny. There is an ancestral state and what needs explaining is how it evolved from there.

Group-level and individual-level selection. The most fun part, I think, is the speculation that our human biases may make us particularly prone to think of group-level benefits. I’ll just leave this quote here:

Although I cannot possibly prove the following claim, I consider it an interesting conjecture to think about how living in human societies makes us unusually strongly aware of the group-level consequences of our actions. Whether innate, or frequently enough drilled during upbringing to become part of our psyche, the outcome is clear. By the time a biology student enters university, there is a belief in place that evolution in general produces traits because they benefit entire species. /…/ What follows, then, is that teachers need to point out the flaws in one set of ideas (e.g. ‘individuals die to avoid overpopulation’) much more strongly than the other. After the necessary training, students then graduate with the lesson not only learnt but also generalized, at which point it takes the form ‘as soon as someone evokes group-level thinking, we’ve entered “bad logic territory”’.

Literature

Kokko, Hanna. (2017) ”Give one species the task to come up with a theory that spans them all: what good can come out of that?” Proc. R. Soc. B. Vol. 284. No. 1867.

Morning coffee: the selfish gene versus the world

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The distinction between ”gene” in the sense of an allele at some locus and ”gene” in the sense of a dna sequence with a name and some function seems easy enough, but still causes a lot of confusion, both in popular and scientific literature.

This was very clear a few months ago when science journalist David Dobbs published his ”Die selfish gene, die” and a few weeks of debate broke out. In my opinion it’s not a particularly good piece, but I agree with Dobbs that the ”selfish gene” metaphor sometimes invites misunderstandings. The article itself displays a few of them, when it suggests that evolution and genetics as understood before the age of microarrays are somehow at odds with the importance of gene regulation or phenotypic plasticity. I suspect that many of these problems stem from the double meaning of the word gene. Other examples are found in headlines claiming that researchers have found the gene for something or the confusion about the word pleiotropy (Paaby & Rockman 2012).

When Dawkins wrote about the selfish gene, he did not mean the selfish dna sequence encoding a protein; he meant the selfish genetic variant causing differences in fitness between individuals. (Or rather, a set of genetic variants in sufficiently close linkage to seldom be separated by recombination.) The book is not about molecular genes. As anyone who actually read it knows, it deals mostly with behaviour using game theory approaches. This does not mean that Dawkins denied that there are actual molecular genes doing the mechanistic work, but that he analysed the situation mostly on a different level. And had he chosen to write only about known sequence variants with adaptive effects on behaviour it would have been a very short book.

Of course the word ”selfish”, while I agree that it is the proper word in the sense that Dawkins intended, is great for those who want to point to instances where people are horrible to each other and tell you that it’s all because of evolution. But I think that is a bigger issue that will not be solved by tweaking popular science metaphors. By the way, that is completely contrary to Dawkins’ intentions, which were to popularise the evolutionary models that explain why animals are not always horrible to each other, even though their behaviour is shaped by natural selection.