EBM 2016, Marseille

In September, I went to the 20th Evolutionary Biology Meeting in Marseille. This is a very nice little meeting. I listened to a lot of talks, had some very good conversations, met some people, and presented our effort to map domestication traits in the chicken with quantitative trait locus mapping and gene expression (Johnsson & al 2015, 2016, and some unpublished stuff).

Time for a little conference report. Late, but this time less than a year from the actual conference. Here are some of my highlights:

Richard Cordaux on pill bugs, Wolbachia and sex manipulation — I did not know that Wolbachia, the intracellular parasite superstar of arthropods, had feminization of hosts in its repertoire (Cordaux & al 2004). Not only that, but in some populations of pill bugs, a large chunk of the genome of the feminizing Wolbachia has inserted into the pill bug genome, thus forming a new W chromosome (Leclercq & al 2016, published since the conference). He also told me how this is an example of the importance of preserving genetic resources — the lines of pill bugs have been maintained for a long time, and now they’re able to return to them with genomics tools and continue old lines of research. I think that is seriously cool.

Olaya Rendueles Garcia on positive frequency-dependent selection maintaining diversity in social bacterium Myxococcus xanthus (Rendueles, Amherd & Velicer 2015) — In my opinion, this was the best talk of the conference. It had everything: an interesting phenomenon, a compelling study system, good visuals and presentation. In short: M. xanthus of the same genotype tend to cooperate, inhabit their own little turfs in the soil, and exclude other genotypes. So it seems positive frequency-dependent selection maintains diversity in this case — diversity across patches, that is.

A very nice thing about this kind of meetings is that one gets a look into the amazing diversity of organisms. Or as someone put it: the complete and utter mess. In this department, I was particularly struck by … Sally Leys — sponges; Marie-Claude Marsolier-Kergoat — bison; Richard Dorrell — stramenopile chloroplasts.

I am by no means a transposable elements person. In fact, one might believe I was actively avoiding transposable elements by my choice of study species. But transposable elements are really quite interesting, and seem quite important to genome evolution, both to neutrally evolving and occasionally adaptive sequences. This meeting had a good transposon session, with several interesting talks.

Anton Crombach presented models the gap gene network in Drosophila melanogaster and Megaselia abdita, with some evolutionary perspectives (Crombach & al 2016). A couple of years ago, Marjoram, Zubair & Nuzhdin used the gap gene network as their example model to illustrate the suggestion to combine systems biology models with genetic mapping. I very much doubt (though I may be wrong; it happens a lot) that there is much meaningful variation within populations in the gap gene network. A between-species analysis seems much more fruitful, and leads to the interesting result where the outcome, in terms of gap gene expression along the embryo, is pretty similar but the way that the system gets there is quite different.

If you’ve had a beer with me and talked about the future of quantitative genetics, you’re pretty likely to have heard me talk about how in the bright future, we will not just map variation in phenotypes, but in the parameters of dynamical models. (I also think that the mapping will take place through fully Bayesian hierarchical models where the same posterior can be variously summarized for doing genomic prediction or for mapping the major quantitative trait genes, interactions etc. Of course, setting up and running whole-genome long read sequencing will be as convenient and cheap as an overnight PCR. And generally, there will be pie in the sky etc.) At any rate, what Anton Crombach showed was an example of combining systems biology modelling with variation (between clades). I thought it was exciting.

It was fun to hear Didier Raoult, one of the discoverers of giant viruses, speak. He was somewhat of a quotation machine.

”One of the major problems in biology is that people believe what they’ve learned.”

(About viruses being alive or not) ”People ask: are they alive, are they alive? I don’t care, and they don’t care either”

Very entertaining, and quite fascinating stuff about giant viruses.

If there are any readers out there who worry about social media ruining science by spilling the beans about unpublished results presented at meetings, do not worry. There were a few more cool unpublished things. Conference participants, you probably don’t know who you are, but I eagerly await your papers.

I think this will be the last evolution-themed conference for me in a while. The EBM definitely has a different range of themes than the others I’ve been to: ESEB, or rather: the subset of ESEB I see choosing my adventure through the multiple-session programme, and the Swedish evolution meetings. There was more molecular evolution, more microorganisms and even some orgin of life research.

Morning coffee: against validation and optimization

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It appears like I’m accumulating pet peeves at an alarming rate. In all probability, I am guilty of most of them myself, but that is no reason not to complain about them on the internet. For example: Spend some time in a genetics lab, and you will probably hear talk of ”validation” and ”optimization”. But those things rarely happen in a lab.

According to a dictionary, to ”optimize” means to make something as good as possible. That is almost never possible, nor desirable. What we really do is change things until they work according to some accepted standard. That is not optimization; that is tweaking.

To ”validate” means to confirm to that something is true, which is rarely possible. Occasionally we have something to compare to that you are really sure about, so that if a method agrees with it, we can be pretty certain that it works. But a lot of time, we don’t know the answer. The best we can do is to gather additional evidence.

Additional evidence, ideally from some other method with very different assumptions, is great. So is adjusting a protocol until it performs sufficiently well. So why not just say what we mean?

”You keep using that word. I do not think that it means what you think it means.”

A year ago in Lund: the panel discussion at Evolution in Sweden 2016

This meeting took place on the 13th and 14th of January 2016 in Lund. It feels a bit odd to write about it now, but my blog is clearly in a state of anachronistic anarchy as well as ett upphöjt tillstånd av språklig förvirring, so that’s okay. It was a nice meeting, spanning quite a lot of things, from mosasaurs to retroviruses. It ended with a panel discussion of sorts that made me want to see more panel discussions at meetings.

The panel consisted of Anna-Liisa Laine, Sergey Gavrilets, Per Lundberg, Niklas Wahlberg, and Charlie Cornwallis, and a lot of people joined in with comments. I don’t know how the participants were chosen (Anna-Liisa Laine and Sergey Gavrilets were the invited speakers, so they seem like obvious choices), or how they were briefed; Per Lundberg served as a moderator and asked the other participants about their predictions about the future of the field (if memory serves me right).

I thought some of the points were interesting. One of Sergey Gavrilets’ three anticipated future developments was links between different levels of organisation; he mentioned systems biology and community ecology in the same breath. This sounded interesting to me, who not so secretly dreams of the day when systems biology, quantitative genetics, and populations genetics can all be brought to bear on the same phenotypes. (The other two directions of research he brought up were cliodynamics and human evolution.) He himself had, earlier in his talk, provided an example where a model of human behaviour shows the possibility of something interesting — that a kind of cooperation or drive for equality can be favoured without anything like kin or group selection. That is, in some circumstances it pays to protect the weak, and thus make sure that they bullies do not get too much ahead. He said something to the effect that now is the time to apply evolutionary biology to humans. I would disagree with that. On the one hand, if you are interested in studying humans, any time is the time. On the other hand, if the claim is that now, evolutionary biology is mature and solid, so one can go out and apply it to help other disciplines to sort out their problems … I think that would be overly optimistic.

A lot of the discussion was about Mats Björklund‘s talk about predicting evolution, or failing to do so. Unfortunately, I think he had already left, and this was the one talk of the conference that I missed (due to dull practical circumstances stemming from a misplaced wallet), so this part of the discussion mostly passed me by.

A commonplace that recurred a few times was jokes about sequencing … this or that will not be solved by sequencing thousands of genomes, or by big data — you know the kind. This is true, of course; massively parallel sequencing is good when you want to 1) make a new reference genome sequence; 2) get lots and lots of genetic markers or 3) quantify sequences in some library. That certainly doesn’t cover all of evolutionary biology, but it is still quite useful. Every time this came up part of me felt like putting my hand up to declare that I do in fact think that sequencing thousands of individuals is a good idea. But I didn’t, so I write it here where even fewer people will read it.

This is (according to my notes) what the whiteboard said at the end of the session:

”It’s complicated …”
”We need more data …”
”Predictions are difficult/impossible”
”We need more models”

Business as usual
Eventually we’ll get there (where?)
Revise assumptions, models, theories, methods, what to measure

Nothing in evolutionary biology makes sense except in the light of ecology phylogeny disease

Everything in evolution makes sense in the light of mangled Dobzhansky quotes.

(Seriously, I get why pastiches of this particular quote are so common: It’s a very good turn of phrase, and one can easily substitute the scientific field and the concept one thinks is particularly important. Nothing in behavioural ecology makes sense except in the light of Zahavi’s handicap principle etc. It is a fun internal joke, but at the same time sounds properly authoritative. Michael Lynch’s version sometimes seems to be quoted in the latter way.)

Linköping–Edinburgh–Uppsala

If you are the kind of person who reads the lists of decisions from Formas, you may already know this. In March, I’m starting a new postdoc position, in collaboration with John Hickey’s AlphaGenes group at the Roslin Institute in Edinburgh and Dirk-Jan de Koning’s group at the Swedish University of Agriculture in Uppsala, funded by a mobility starting grant for young researchers from the research council Formas. Hurrah!

The project involves using huge datasets from livestock animals to search for genes and variants underlying quantitative traits. In that sense, for me, this is both a new direction (animal breeding research) and a natural continuation (the genetic basis of quantitative traits). So, in the coming years I anticipate, among other things, learning a ton about computational quantitative genetics; meeting and working with great people; travelling more than ever (relative to my relatively low baseline); writing a poem or two about the scenic environs of Edinburgh and the Royal Mounds of Uppsala; figuring out the across-borders relationship thing; discovering new and useful things about quantitative traits; and hopefully picking up a bit of a Scottish tone in my otherwise Swenglish accent.

Linköping has been very good to me, and so have my colleagues in the Wright lab and AVIAN Behavioural Genetics and Physiology group. So, naturally, I’m both happy and sad to leave. Friends in Linköping, we will meet again.

Also, happy new year!

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(Me holding a sign that says (in Swedish): ”Thank you, Formas! I will do my very best.”)

Reviewing, postscript

Later the same day as the post on reviewing was published, I saw the paper by Kovanis and coworkers on the burden of peer review in biomedical literature. It’s silly of me that it didn’t occur to me to look for data on how many papers researchers review. Their first figure shows data on the number of reviews performed 2015 by Publons users:

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Figure 1B from Kovanis & al (2016) PLOS ONE (cc:by 4.0).

If we take these numbers at face value (but we probably shouldn’t, because Publons users seem likely to be a bised sample of researchers), my 4-6 reviews in a year fall somewhere in the middle: on the one hand, more than half of the researchers review fewer papers, but it’s a lot less than those who review the most.

This paper estimates the supply and demand of reviews in biomedical literature. The conclusion is lot like the above graph: reviewer effort is unevenly distributed. In their discussion, the authors write:

Besides, some researchers may be willing to contribute but are never invited. An automated method to improve the matching between submitted articles and the most appropriate candidate peer reviewers may be valuable to the scientific publication system. Such a system could track the number of reviews performed by each author to avoid overburdening them.

This seems right to me. There may be free riders who refuse to pull their weight. But there are probably a lot more of people like me, who could and would review more if they were asked to. A way for editors to find them (us) more easily would probably be a good thing.

Morning coffee: reviewing

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(It was a long time since I did one of these posts. I’d better get going!)

One fun thing that happened after I received my PhD is that I started getting requests to review papers, four so far. Four papers (plus re-reviews of revised versions) in about a year probably isn’t that much, but it is strictly greater than zero. I’m sure the entertainment value in reviewing wears off quite fast, but so far it’s been fun, and feels good to pay off some of the sizeable review debt I’ve accumulated while publishing papers from my PhD. Maybe I’m just too naïve and haven’t seen the worst parts of the system yet, but I don’t feel that I’ve had any upsetting revelations from seeing the process from the reviewer’s perspective.

Of course, peer review, like any human endeavour, has components of politics, ego and irrationality. Maybe one could do more to quell those tendencies. I note that different journals have quite different instructions to reviewers. Some provide detailed directions, laying out things that the reviewer should and shouldn’t do, while others just tell you how to use their web form. I’m sure editorial practices also differ.

One thing that did surprise me was when an editor changed the text of a review I wrote. It was nothing major, not a case of removing something inappropriate, but rewording a recommendation to make it stronger. I don’t mind, but I feel that the edit changed the tone of the review. I’ve also heard that this particular kind of comment (when a reviewer states that something is required for a paper to be acceptable for publication) rubs some people the wrong way, because that is up to the editor to decide. In this case, the editor must have felt that a more strongly worded review was the best way to get the author to pay attention, or something like that. I wonder how often this happens. That may be a reason to be even more apprehensive about signing reviews (I did not sign).

So far, I’ve never experienced anything else than single-blind review, but I would be curious to review double-blinded. I doubt the process would differ much: I haven’t reviewed any papers from people I know about, and I haven’t spent any time trying to learn more about them, except in some cases checking out previous work that they’ve referenced. I don’t expect that I’d feel any urge to undertake search engine detective work to figure out who the authors were.

Sometimes, there is the tendency among scientists and non-scientists alike to elevate review to something more than a couple of colleagues reading your paper and commenting on it. I’m pretty convinced peer review and editorial comments improve papers. And as such, the fact that a paper has been accepted by an editor after being reviewed is some evidence of quality. But peer review cannot be a guarantee of correctness. I’m sure I’ve missed and misunderstood things. But still, I promise that I’ll do my best, and I will not have the conscience to turn down a request for peer review for a long time. So if you need a reviewer for a paper on domestication, genetic mapping, chickens or related topics, keep me in mind.

Paper: ”Feralisation targets different genomic loci to domestication in the chicken”

It is out: Feralisation targets different genomic loci to domestication in the chicken. This is the second of our papers on the Kauai feral and admixed chicken population, and came out a few days ago.

The Kauai chicken population is kind of famous: you can find them for instance on Flickr, or on YouTube. We’ve previously looked at their plumage, listened to the roosters’ crowings, and sequenced mitochondrial DNA to investigate their origins. Based on this, we concur with the common view that the chickens of Kauai probably are a mixture of feral birds of domestic origin and wild Junglefowl. The Kauai chickens look and sound like a mix of wild and domestic, and we found mitochondrial DNA of two haplogroups, one of which (called D) is typical in ancient chicken DNA from Pacific islands (Gering et al 2015).

In this paper, we looked at the rest of the genome of the same chickens — you didn’t think we sequenced the whole thing just to look at the mitochondrion plus a subset of markers, did you? We turn to population genomics, and a family of methods called selective sweep mapping, to search for regions of their genome that show signs of being affected by natural selection. This lets us: 1) draw pretty rainbow plots such as  this one …

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(Figure 1a from the paper in question, Johnsson & al 2016. cc:by The chromosomes have been laid out on the horizontal axis with different colours, and split into windows of 40 kb. Each dot represents the heterozygosity of that windows. For all the details, see the paper.)

… 2) highlight a regions of the genome that may have been selected during feralisation on Kauai (these are the icicles in the graph, highligthed by arrows); 3) conclude that the regions that look like they’ve been selected in feralisation overlap very little with the ones that look like they’ve been selected in chicken domestication. Hence the title.

That was the main result, but of course we also look at what genes are highlighted. Mostly we have no idea how they may contribute to feralisation, but a couple of regions overlap with those that we’ve previously found in genetic mapping of comb size and egg laying in our wild-by-domestic intercross. We also compare the potentially selected regions to domestic chicken sequences.

Last year, Ewen Callaway visited Dominic Wright, Eben Gering and Rie Henriksen on the last fieldtrip to Kauai. The article, When chickens go wild, was published in Nature News in January, and it explains a lot of the ideas nicely. This paper was submitted by then, so the samples they gathered on that trip do not feature in it. But, spoiler alert: there is more to come. (I don’t know what role I personally will play, but that is less important.)

As you may have guessed if you looked at the author list, this was a collaboration between quite a lot of people in Linköping, Michigan, London, and Victoria. Thanks to all involved! This was great fun, and for those of you who like this sort of thing, I hope the paper will be an interesting read.

Literature

M. Johnsson, E. Gering, P. Willis, S. Lopez, L. Van Dorp, G. Hellenthal, R. Henriksen, U. Friberg & D. Wright. (2016) Feralisation targets different genomic loci to domestication in the chicken. Nature Communications. doi:10.1038/ncomms12950