A bunch of cool things

From the weeks during which I failed to check my RSS reader…

1. The coolest ribozyme ever. (In more than one sense.)

I’ve made no secret of my fandom of the RNA world hypothesis, according to which early life forms used RNA both as genetic material and as enzymes, before DNA took over the former role and proteins (mostly) took over the latter. RNA is truly an amazing molecule, capable of doing all kinds of stuff that we traditionally imagined as the job of proteins. However, coaxing it into carrying out the most important function of a primordial RNA genome – copying itself – has proven pretty difficult.

To my knowledge, the previous record holder in the field of RNA copying ribozymes (Wochner et al., 2011) ran out of steam after making RNA strands only half of its own length. (Which is still really impressive compared to its predecessors!) In a recent study, the same team turned to an alternative RNA world hypothesis for inspiration. According to the “icy RNA world” scenario, pockets of cold liquid in ice could have helped stabilise the otherwise pretty easily degraded RNA as well as concentrate and isolate it in a weird inorganic precursor to cells.

Using experimental evolution in an icy setting, they found a variation related to the aforementioned ribozyme that was much quicker and generally much better at copying RNA than its ancestors. Engineering a few previously known performance-enhancing mutations into this molecule finally gave a ribozyme that could copy an RNA molecule longer than itself! It still wouldn’t be able to self-replicate, since this particular guy can only copy sequences with certain properties it doesn’t have itself, but we’ve got the necessary endurance now. Only two words can properly describe how amazing that is. Holy. Shit. :-O

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Attwater J et al. (2013) In-ice evolution of RNA polymerase ribozyme activity. Nature Chemistry, published online 20/10/2013, doi: 10.1038/nchem.1781

Wochner A et al. (2011) Ribozyme-catalyzed transcription of an active ribozyme. Science 332:209-212

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2. Cambrian explosion: evolution on steroids.

This one’s for those people who say there is nothing special about evolution during the Cambrian – and also for those who say it was too special. (Creationists, I’m looking at you.) It is also very much for me, because Cambrian! (How did I not spot this paper before? Theoretically, it came out before I stopped checking RSS…)

Lee et al. (2013) used phylogenetic trees of living arthropods to estimate how fast they evolved at different points in their history. They looked at both morphology and genomes, because the two can behave very differently. It’s basically a molecular clock study, and I’m still not sure I trust molecular clocks, but let’s just see what it says and leave lengthy ruminations about its validity to my dark and lonely hours 🙂

They used living arthropods because, obviously, you can’t look at genome evolution in fossils, but the timing of branching events in the tree was calibrated with fossils. With several different methods, they inferred evolutionary trees telling them how much change probably happened during different periods in arthropod history. They tweaked things like the estimated time of origin of arthropods, or details of the phylogeny, but always got similar results.

On average, arthropod genomes, development and anatomy evolved several times faster during the Cambrian than at any later point in time. Including the aftermath of the biggest mass extinctions. Mind you, not faster than modern animals can evolve under strong selection – they just kept up those rates for longer, and everyone did it.

(I’m jumping up and down a little, and at the same time I feel like there must be something wrong with this study, the damned thing is too good to be true. And I’d still prefer to see evolutionary rates measured on actual fossils, but there’s no way on earth the fossil record of any animal group is going to be good enough for that sort of thing. Conflicted much?)

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Lee MSY et al. (2013) Rates of phenotypic and genomic evolution during the Cambrian explosion. Current Biology 23:1889-1895

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3. Chitons to sausages

Aplacophorans are probably not what you think of when someone mentions molluscs. They are worm-like and shell-less, although they do have tiny mineralised scales or spines. Although they look like one might imagine an ancestral mollusc before the invention of shells, transitional fossils and molecular phylogenies have linked them to chitons, which have a more conventional “sluggy” body plan with a wide foot suitable for crawling and an armoured back with seven shell plates.

Scherholz et al. (2013) compared the musculature of a living aplacophoran to that of a chiton and found it to support the idea that aplacophorans are simplified from a chiton-like ancestor rather than simple from the start. As adults, aplacophorans and chitons are very different – chitons have a much more complex set of muscles that includes muscles associated with their shell plates. However, the missing muscles appear to be present in baby aplacophorans, who only lose them when they metamorphose. (As a caveat, this study only focused on one group of aplacophorans, and it’s not entirely certain whether the two main groups of these creatures should even be together.)

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Scherholz M et al. (2013) Aplacophoran molluscs evolved from ancestors with polyplacophoran-like features. Current Biology in press, available online 17/10/2013, doi: 10.1016/j.cub.2013.08.056

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4. Does adaptation constrain mammalian spines?

Mammals are pretty rigid when it comes to the differentiation of the vertebral column. We nearly all have seven neck vertebrae, for example. This kind of conservatism is surprising when you look at other vertebrates – which include not only fairly moderate groups like birds with their variable necks, but also extremists like snakes with their lack of legs and practically body-long ribcages. Mammalian necks are evolutionarily constrained, and have been that way for a long time.

Emily Buchholz proposes an interesting explanation with links to previous hypotheses. Mammals not only differ from other vertebrates in the less variable numbers of vertebrae in various body regions; these regions are also more differentiated. For example, mammals are the only vertebrates that lack ribs in the lower back. In Buchholz’s view, this kind of increased differentiation contributes to adaptation but costs flexibility.

Her favourite example is the muscular diaphragm unique to mammals. This helps mammals breathe while they move, and also makes breathing more powerful, which is nice for active, warm-blooded creatures that use a lot of oxygen. However, it also puts constraints on further changes. Importantly, Buccholz argues that these constraints don’t all have to work in the same way.

For example, the constraint on the neck may arise because muscle cells in the diaphragm come from the same place as muscle cells associated with specific neck vertebrae. Moving the forelimbs relative to the spine, i.e. changing the number of neck vertebrae, would mess up their migration to the right place, and we’d end up with equally messed up diaphragms.

A second possible constraint has less to do with developmental mishaps and more to do with plain old functionality. If you moved the pelvis forward, you may not screw with the development of other bits, but you’d squeeze the space behind the diaphragm, which you kind of need for your guts, especially when you’re breathing in using your lovely diaphragm.

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Buccholz E (2013) Crossing the frontier: a hypothesis for the origins of meristic constraint in mammalian axial patterning. Zoology in press, available online 28/10/2013, doi: 10.1016/j.zool.2013.09.001

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And… I think that approximately covers today’s squee moments 🙂

Phantom hourglasses

Holy ribosome, I’ve just written close to two thousand words about a paper. I… think I may have got a bit too excited. Or too bogged down in little technical details. Either way, you got lucky. The two-thousand word monster is not what you’re getting.

The reason I got excited about Piasecka et al. (2013) is that it, er, qualifies some other things I’d previously got excited about. And by “qualifies”, I mean turns inside out and performs a thorough autopsy on.

I previously touched upon the idea of the developmental hourglass – meaning that the embryos of related creatures are most similar to each other somewhere in the middle of development. The great rival of this hypothesis is that of early conservation (or the “funnel”), where embryos diverge from a similar starting point. The latter has been around as long as comparative embryology itself. The hourglass is a pretty intriguing pattern and raises all kinds of questions about what causes it – but of course, to have a cause, it has to exist in the first place.

So my previous excitement had been partly about the observation that the hourglass – originally noted in visible traits of embryos – also exists in the changing sets of genes activated throughout development (the transcriptome). According to various papers, genes expressed in mid-embryogenesis are on average older, slower-evolving and behave more similarly across species than genes active at other stages. If such observations are correct, that would certainly indicate that the hourglass is a real thing and something strange is going on with constraints and evolvability.

But, and here comes the Piasecka paper – is it?

This study is huge. There is (to use a highly technical phrase) a fucking shitload of stuff in it. Instead of looking at some big global property of the transcriptome, these authors went into all kinds of detail about various properties of specific sets of genes. They looked at – well, they say they looked at five different measures of evolutionary constraint, but actually some of those are made up of more than one thing, so really it’s quite a bit more than five.

And when they go down to that level of detail, they find that the hourglass is not a universal property of the developmental genetics of zebrafish embryos (unlike Domazet-Lošo and Tautz [2010] reported). Different measures of evolutionary constraint such as the strength of selection against protein-changing mutations, the age of the genes (which is what the original study focused on), or the conservation of their regulatory elements, show different patterns. There are hourglasses, there are a couple of funnels, and then there are parameters that just don’t exhibit much systematic change at all.

(There’s also a couple of points about potentially dodgy statistical approaches in some of these papers, which may make all the difference between an hourglass and a funnel. That’s a bit scary.)

I can’t say I’ve properly digested this paper. There’s an awful lot in it, and, my head was spinning non-stop when I finished reading. It’s definitely fascinating stuff, though, and once again, the conclusion is that things are More Complicated. (I’m kind of getting used to that at this point…) Before, you could look at a group of creatures, compare their development and ask, funnel or hourglass? Then you could ask why. Now, you can’t just make grand generalisations about anything. Taking Piasecka et al. at face value, “funnel or hourglass” is not even a valid question – it depends on exactly what you’re measuring. So much for “laws” of developmental evolution…

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References:

Domazet-Lošo T & Tautz D (2010) A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature 468:815-818

Piasecka B et al. (2013) The hourglass and the early conservation models—co-existing patterns of developmental constraints in vertebrates. PLoS Genetics 9: e1003476

Only so many ways

In a way, the limitations of evolution are more interesting to me than its possibilities. It’s cool to figure out how exquisite adaptations and fantastically complex molecular machines might have evolved, but I like my evolution the way Brandon Sanderson likes his magic. If it can do anything, then where’s the fun? Deep underlying rules and constraints are what make it really interesting.

Convergent evolution can hint at such rules. Some of them are just physics and seem pretty straightforward. If you’re a creature swimming in the sea, being streamlined is good for you, and there aren’t that many ways of being streamlined. So dolphins, squid and sharks have the same basic shape despite coming from very different ancestors. Other cases involve more subtle and probably more interesting constraints. The baggage of your ancestry, the interactions in your genome, the pool of available mutations, can all restrict the ways in which you can adapt to a particular challenge. A study I found in the huge backlog of random pdfs on my desktop probes tentatively into the importance of such intrinsic limitations.

Conte et al. (2012) asked a seemingly simple question that has apparently never been systematically investigated before: how often does convergent or parallel evolution of the same trait result from modification of the same genes?

Convergent and parallel evolution are sort of two ends of a continuum. We use parallel evolution to refer to traits that evolved in similar directions starting from the same starting point. For example, three-spine sticklebacks repeatedly lost their bony armour when they moved from the sea to rivers and lakes in various places around the world. The ancestor is the same heavily armoured marine fish in each case, and most freshwater populations underwent very similar changes (including their genetic basis) from this common beginning. At the other end of the scale you find clear instances of convergence, such as “milk” in mammals and birds. Their common ancestors not only didn’t ooze custom-made immune-boosting baby food, they likely didn’t even care for their young.

Back to the paper. Conte et al. conducted what we call a meta-analysis: collecting and analysing data from all published studies that fit their pre-determined set of criteria. Altogether, they looked at a carefully selected set of 25 studies about the genetic basis of convergent traits. Not too great, the authors acknowledge, but it’s a start.

The studies were divided into two sets, because the two main methods of looking at the genetic basis of a trait can’t easily be analysed together. The first set contained genetic mapping studies (“which parts of the genome cause X?”), and the second candidate gene studies (“does this gene cause X?”). The convergent traits in these studies were quite diverse. There was pale skin from cave fish to humans, African and European peoples’ ability to digest lactose as adults, resistance to tetrodotoxin in snakes, wing patterns in butterflies, electric organs in fish…

The comparisons span quite a long time scale. On one end, there are populations within a single species, like lactose-tolerant Europeans and Arabs, that diverged mere tens of thousands of years ago. On the other, pale-skinned cave fish and Swedes are separated by something on the order of 400 million years. This is part of what makes this an exciting study, because you can indirectly observe what happens to genetic constraints over time.

The most exciting, though, is the sheer amount of gene re-use the researchers saw. For mapping studies, they found a 32% chance that the same trait will be associated with the same gene(s) in different species. Candidate genes give an even higher estimate (55%), but that might just be the nature of the beast. When a candidate gene is not behaving as expected it’s probably less interesting and publishable, Conte et al. argue, whereas mapping studies will usually throw up something to write about.*

Within a species, the probability of the same gene being used in the same adaptation gets as high as 80% for both methods. This is despite the fact that often the traits in question are controlled by several genes, any of which could be mutated to the same effect. Where you come from clearly has a huge impact on where (and how) you can go. The impact lessens as you look at increasingly distant species; at a hundred million years of divergence, mapping data show only 10% similarity between convergent traits, and even candidate genes drop to around 40%. (Methinks 10% is still a big number considering how many genes we have, but of course we’re talking about relatively simple traits here, so the number of relevant genes isn’t nearly as high.)

There are some logical possible explanations behind both the high level of genetic convergence in close relatives and the big drop with increasing divergence. For example, it could be that populations within a species have very similar pools of genetic variation. If the same genes vary, then natural selection will “naturally” hit on the same genes when adaptation becomes handy. It’s also likely that the rest of the genome plays a part – closely related populations/species have more similar genetic backgrounds, their genes likely interact with one another in more similar ways, ergo the restrictions on what mutations can become beneficial are also similar. As lineages diverge, so do such interactions and restrictions, lowering the probability that two species evolve the same trait in the same way.

Of course, it’s at this point impossible to say which of the potential reasons actually cause the trends observed in this study, but that wasn’t the point. The authors’ stated goals were pretty modest:

“[O]ur aim here has been to stimulate thinking about these issues and to move towards a quantitative understanding of repeated genetic evolution” (p5044)

In that, I hope, they have succeeded. It’d be lovely to see more of this “big picture” discussion of convergent evolution. Big pictures make Mammals happy.

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*I’m not sure about that, myself. I think if you’ve got a gene that’s been shown to do X in species after species, a negative finding is a lot more newsworthy than yet another confirmation of the same old shit. I suppose it’s gut feeling versus intuition until someone does a study of that, though 🙂

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Reference:

Conte GL et al. (2012) The probability of genetic parallelism and convergence in natural populations. Proceedings of the Royal Society B 279:5039-5047