Skype a scientist

Skype a scientist is a programme that connects classrooms to scientists for question and answer sessions. I have done it a few times now, and from the scientist’s perspective, it has a lot of reward for not that much work.

It works like this: the Skype a scientist team makes matches based on what kind of scientist the teacher asks for; the scientist writes a letter (or it could be a video or something else) about what they work on; the students prepare questions; and the scientist tries to answer.

One thing I like about the format is how it is driven by student questions, turning the conversation to things students actually want to know, and not just what the the scientist (me) believes there’s a need to ‘explain’ (scare quotes used to imply scepticism). Of course, the framing as a classroom exercise, the priming by the letter, and the fact that the questions pass through the teacher influence the content, but still. I also like how some students ask questions that I suspect are not entirely serious, but that still turn out to be interesting. Something I like less is how each session still is kind of a monologue with little interactivity.

I think it has gone reasonably well. I hope my answers will get more polished with time. Another thing I need to get better at is extracting useful feedback from the teachers to improve what I do. They’ve all said positive things (of course, how else could they respond?), but I’m sure there are all kinds of things I could improve.

Here, enjoy some of the questions I’ve gotten! I won’t answer them here; you will have to sign up your classroom for that. I have organised them into categories that I think reflect the most common types of questions.

Pig and chicken genetics

What are some mutations in pigs that you see?

Have you ever encountered a chicken that had something about it that surprised you?

What kinds of chickens live the longest?

What is significant about the DNA of pigs and chickens?

What is the most pervasive genetic disorders in pigs and chickens?

Which genes have the highest demand from industry?

Evolution

If certain traits are dominant and humans have been around for 6 million years, how do we not have all those dominant traits?

What came first, the chicken or the egg?

Does the DNA of chickens and pigs have any similarity to humans — if so, what percent is common?

When were pigs domesticated and what were they domesticated from?

Hard questions

Are science and religion compatible?

Can genetic engineering lead to the creation of a super-race?

Do you think that, if extra-terrestrial life was found, a breeding program between humans and aliens could exist to create hybrids?

Do you think you could genetically modify pigs to create the perfect bacon?

Can you genetically modify an organism to make it more clever?

Will we be able to genetically modify humans with features from other organisms such as gills, not just single gene traits?

What do you think is the next big genetically modified breakthrough on the horizon?

How far away are we from being able to clone a human (like Dolly)?

Have you researched genes designed to protect chickens or pigs from super bacteria resistant to antibiotics?

Personal stuff

Do you ever get to dissect anything?

What is the most exciting part of your job?

What is your favourite complex trait?

Have you always been interested in science?

What makes your job so important that you are willing to move countries?

Why did you choose to study genetics?

Do you prefer group or solo work?

Are you under intense pressure in your job?

What are you looking forward to working on in the future?

The practice of science

What materials do you use in your research?

Who decides what you research?

How do you use computers to research genes and DNA?

What kind of technology/equipment do you use?

Why do you research pigs and chickens?

Different ways to cite papers

The journals Genetics and Nature Genetics seem to take opposite views on citations. See first this editorial from Nature Genetics: ”Neutral citation is poor scholarship”. It is strongly worded in a way that is surprising and entertaining:

The journal deplores and will decline to consider manuscripts that fail to identify the key findings of published articles and that—deliberately or inadvertently—omit the reason the prior work is cited.

(All the emphasis in all the quotes was added by me.)

The passage that suggests a difference in citation policy occurs at the end:

Authors are of course free to select the literature that is relevant to their current work and to cite in their arguments only those publications that meet their standards of evidence and quality.

Genetics, on the other hand, says this in the instructions for preparing a manuscript:

Authors are encouraged to:

  • cite the supporting literature completely rather than select a subset of citations;
  • provide important background citations, including relevant review papers (to help orient the non-specialist reader);
  • to cite similar work in other organisms.

I’m sure the editors of Genetics also don’t support scattershot citation of tangentially related papers (as in ”This field exists [1-20]”), but they seem to take a different stance on how to choose what to cite.

I wonder what the writers of the respective recommendations would make of these, in my opinion delightful, opening sentences (from Yun & Agrawal 2014). Note the absence of hundreds of citations.

Inbreeding depression has been estimated hundreds of times in a wide variety of taxa. From this body [of] work, it is clear that inbreeding depression is common but also that it is highly variable in magnitude.

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.

NASA and Orphan Black

A few months ago I wrote a post about the (fictitious, and also evil) clone experiment in Orphan Black. I said that comparison of complex traits between a handful of individuals isn’t, even in principle, a ”scientifically beautiful setup to learn myriad things”, but garbage. You can’t take two humans, even if they’re clones, put them in different environments, and expect to learn much of anything.

Funnily enough, it seems like NASA has been doing just that with the NASA twin study: there are two astronauts who are twins, and researchers have compared various things between them and before/after one of them went to space. Of course, those various things include headline-attracting assays like telomere length and DNA methylation (including ”epigenetic age” — something like Horvath 2013, I assume).

The news coverage has been confused — mixing up DNA methylation, gene expression and mutation. But can one blame news outlet for reporting about ”7% changes to his DNA” and ”space genes” when the press release said this:

Another interesting finding concerned what some call the “space gene”, which was alluded to in 2017. Researchers now know that 93% of Scott’s genes returned to normal after landing. However, the remaining 7% point to possible longer term changes in genes related to his immune system, DNA repair, bone formation networks, hypoxia, and hypercapnia.

Someone who knows some biology can guess that this doesn’t refer to mutation, but it’s not making things easy for the reader, and when put like that, the 7% could be DNA methylation, gene expression, or something else transient and genomic. (They’ve since clarified that it was gene expression — in some sample; my bet is on white blood cells.)

Now that we’ve made fun of NASA a little, there are some circumstances when we can learn useful things from studies of even a single individual. For example, if Chaser the Border Collie can learn the names of 1000 toys, and learn new toy names through reasoning by exclusion (Pilley & Reid 2011), then we can safely assume that this is within the realm of dog abilities. Another example is a reference genome, which in the best case is made from a single individual, ideally an individual who is as homozygous as possible. When comparing the reference genome to that of other species, we feel confident enough to publish genome papers with comparisons of gene content, gene family evolution, and selection on protein coding sequences over evolutionary timescales. But when it comes to functional genomics, many variable molecular trait measurements all along the genome? No.

The study is not out. It may be better than the advertisement. It’s seems they’ve compared the two men before and after, so they can get some handle on differences that came about in the years leading up to the study. And maybe they’ve run a crazy number of technical replicates to make sure that the value they get from each data point is as a good measurement as possible. And maybe there is data on what happens with these kinds of assays when people do other strenuous things, putting the differences into context. Maybe.

Literature

Pilley, John W., and Alliston K. Reid. ”Border collie comprehends object names as verbal referents.” Behavioural processes 86.2 (2011): 184-195.

Horvath, Steve. ”DNA methylation age of human tissues and cell types.” Genome biology 14.10 (2013): 3156.

Selected, causal, and relevant

What is ”function”? In discussions about junk DNA people often make the distinction between ”selected effects” and ”causal roles”. Doolittle & Brunet (2017) put it like this:

By the first (selected effect, or SE), the function(s) of trait T is that (those) of its effects E that was (were) selected for in previous generations. They explain why T is there. … [A]ny claim for an SE trait has an etiological justification, invoking a history of selection for its current effect.

/…/

ENCODE assumed that measurable effects of various kinds—being transcribed, having putative transcription factor binding sites, exhibiting (as chromatin) DNase hypersensitivity or histone modifications, being methylated or interacting three-dimensionally with other sites — are functions prima facie, thus embracing the second sort of definition of function, which philosophers call causal role …

In other words, their argument goes: a DNA sequence can be without a selected effect while it has, potentially several, causal roles. Therefore, junk DNA isn’t dead.

Two things about these ideas:

First, if we want to know the fraction of the genome that is functional, we’d like to talk about positions in some reference genome, but the selected effect definition really only works for alleles. Positions aren’t adaptive, but alleles can be. They use the word ”trait”, but we can think of an allele as a trait (with really simple genetics — its genetic basis its presence or absence in the genome).

Also, unfortunately for us, selection doesn’t act on alleles in isolation; there is linked selection, where alleles can be affected by selection without causally contributing anything to the adaptive trait. In fact, they may counteract the adaptive trait. It stands to reason that linked variants are not functional in the selected effect sense, but they complicate analysis of recent adaptation.

The authors note that there is a problem with alleles that have not seen positive selection, but only purifying selection (that could happen in constructive neutral evolution, which is when something becomes indispensable through a series of neutral or deleterious substitutions). Imagine a sequence where most mutations are neutral, but deleterious mutations can happen rarely. A realistic example could be the causal mutation for Freidreich’s ataxia: microsatellite repeats in an intron that occasionally expand enough to prevent transcription (Bidichandani et al. 1998, Ohshima et al. 1998; I recently read about it in Nessa Carey’s ”Junk DNA”). In such cases, selection does not preserve any function of the microsatellite. That a thing can break in a dangerous way is not enough to know that it was useful when whole.

Second, these distinctions may be relevant to the junk DNA debate, but for any research into the genetic basis of traits currently or in the future, such as medical genetics or breeding, neither of these perspectives is what we need. The question is not what parts of the genome come from adaptive alleles, nor what parts of the genome have causal roles. The question is what parts of the genome have causal roles that are relevant to the traits we care about.

The same example is relevant. It seems like the Friedriech’s ataxia-associated microsatellite does not fulfill the selected effect criterion. It does, however, have a causal role, and a causal role relevant to human disease, at that.

I do not dare to guess whether the set of sequences with causal roles relevant to human health is bigger or smaller than the set of sequences with selected effects. But they are not identical. And I will dare to guess that the relevant set, like the selected effect set, is a small fraction of the genome.

Literature

Doolittle, W. Ford, and Tyler DP Brunet. ”On causal roles and selected effects: our genome is mostly junk.” BMC biology 15.1 (2017): 116.

Nessa Carey ”Junk DNA”

I read two popular science books over Christmas. The other one was in Swedish, so I’ll do that in Swedish.

Nessa Carey’s ”Junk DNA: A Journey Through the Dark Matter of the Genome” is about noncoding DNA in the human genome. ”Coding” in this context means that it serves as template for proteins. ”Noncoding” is all the rest of the genome, 98% or so.

The book is full of fun molecular genetics: X-inactivation, rather in-depth discussion of telomeres and centromeres, the mechanism of noncoding microsatellite disease mutations, splicing — some of which isn’t often discussed at such length and clarity. It gives the reader a good look at how messy genomics can be. It has wonderful metaphors — two baseball bats with magnetic paint and velcro, for example. It even has an amusing account of the ENCODE debate. I wonder if it’s true that evolutionary biologists are more emotional than other biologists?

But it really suffers from the framing as a story about how noncoding DNA used to be dismissed as pointless, and now, surprisingly, turns out to have regulatory functions. This makes me a bit hesitant to recommend the book; you may come away from reading it with a lot of neat details, but misled about the big picture. In particular, you may believe a false history of all this was thought to be junk; look how wrong they were in the 70s, and the very dubious view that most of the human genome is important for our health.

On the first page of the book, junk DNA is defined like this:

Anything that doesn’t code for protein will be described as junk, as it originally was in the old days (second half of the twentieth century). Purists will scream, and that’s OK.

We should scream, or at least shake our heads, because this definition leads, for example, to describing ribosomes and transfer-RNA as ”junk” (chapter 11), even if both of them have been known to be noncoding and functional since at least the 60s. I guess the term ”junk” sticks, and that is why the book uses it, and why biologists love to argue about it. You couldn’t call the book something unspeakably dry like ”Noncoding DNA”.

So, this is a fun a popular science book about genomics. Read it, but keep in mind that if you want to define ”junk DNA” for any other purpose than to immediately shoot it down, it should be something like this:

For most of the 50 years since Ohno’s article, many of us accepted that most of our genome is ”junk”, by which we would loosely have meant DNA that is neither protein-coding nor involved in regulating the expression of DNA that is. (Doolittle & Brunet 2017)

The point of the term is not to dismiss everything that is not coding for a protein. The point is that the bulk of DNA in the genome is neither protein coding nor regulatory. This is part of why molecular genetics is so tricky: it is hard to find the important parts among all the rest. Researchers have become much better at sifting through the noncoding parts of the genome to find the sequences that are interesting and useful. Think of lots of tricky puzzles being solved, rather than of a paradigm being overthrown by revolution.

Literature

Carey, Nessa. (2015) Junk DNA: A Journey Through the Dark Matter of the Genome. Icon Books, London.

Doolittle, W. Ford, and Tyler DP Brunet. (2017) ”On causal roles and selected effects: our genome is mostly junk.” BMC Biology.