Razib Khan One-stop-shopping for all of my content

December 11, 2017

Endless Tigers Most Beautiful

Filed under: Evolutionary Biology — Razib Khan @ 11:55 pm

The Thylacine, or the Tasmanian Tiger, is a tragic story that we all know (or should know!). Too late did humans realize how precious it was, a large(ish) marsupial carnivore endemic to Tasmania. Hunted to extinction, the last one died because it was not properly taken care of.

The Tasmanian Tiger is an example of why science is not just instrumental. That is, science is not simply the handmaid of engineering. Most people with an interest in biology have some instinctive reaction to the Tasmanian Tiger and what happened. There’s a natural pathos in it.

If you read The Monkey’s Voyage you know that the marsupials of South America probably derive from a single dispersal event. Genetics has determined that the South American Monito del monte is the most basal of the superorder Australidelphia, which includes all Australasian marsupials. That means instead of the single South American marsupial of this superorder being due to a migration from Australia, the Australian lineages diversified from a single South American ancestor. The Monito del monte is the last living descendent of this once extensive clade.

This means that all of the vareigated marsupials of Australia probably diversified during the Cenozoic, even though the divergence between marsupials and placental mammals dates deep into the Mesozoic. The Koala, the Kangaro, and the Tasmania Devil, all derive from the same source.

Well, a new paper in Nature: Ecology & Evolution does something quite neat, they sequence the whole genome of a Tasmanian Tiger! Genome of the Tasmanian tiger provides insights into the evolution and demography of an extinct marsupial carnivore:

The Tasmanian tiger or thylacine (Thylacinus cynocephalus) was the largest carnivorous Australian marsupial to survive into the modern era. Despite last sharing a common ancestor with the eutherian canids ~160 million years ago, their phenotypic resemblance is considered the most striking example of convergent evolution in mammals. The last known thylacine died in captivity in 1936 and many aspects of the evolutionary history of this unique marsupial apex predator remain unknown. Here we have sequenced the genome of a preserved thylacine pouch young specimen to clarify the phylogenetic position of the thylacine within the carnivorous marsupials, reconstruct its historical demography and examine the genetic basis of its convergence with canids. Retroposon insertion patterns placed the thylacine as the basal lineage in Dasyuromorphia and suggest incomplete lineage sorting in early dasyuromorphs. Demographic analysis indicated a long-term decline in genetic diversity starting well before the arrival of humans in Australia. In spite of their extraordinary phenotypic convergence, comparative genomic analyses demonstrated that amino acid homoplasies between the thylacine and canids are largely consistent with neutral evolution. Furthermore, the genes and pathways targeted by positive selection differ markedly between these species. Together, these findings support models of adaptive convergence driven primarily by cis-regulatory evolution.

The authors are saying that the clear morphological convergences between Tasmania Tigers and canids, which are obvious to anyone with eyes, aren’t detectable in similar sequence identity in regions of the genome known to be functional relevant to the characteristics of interest. Instead of sequence identity they suggest that rather the morphology is being controlled by evoutionary genetic process of cis-regulatory adaptation.

In the Mike Lynch vs. Sean Carroll debate of about ten years back, they’re saying that Sean Carroll was right (see this Hoekstra & Coyne paper for a different take).

Part of the issue here is probably the sort of traits they’re focused on. There seems to be something about the gross morphological characteristics humans find salient that make them the target of cis-regulatory mediated evolutionary processes.

Finally, they suggest with a PSMC plot that Tasmanian Tiger populations crashed around 70,000 years ago, well before Australian Aboriginals arrived. First, I’m not sure that I trust the 70,000 number to be precise enough that we can say it doesn’t overalp with human arrival. But second, is it me, or does every PSMC look like the pot above? It’s probably some sort of publication bias, as you don’t put in PSMC figures if they don’t show a bottleneck. But I’m kind of getting tired of it.

November 6, 2017

Our time in the sun

Filed under: Evolutionary Biology — Razib Khan @ 9:14 pm

The New York Times has a story up, After the Dinosaurs’ Demise, Many Mammals Seized the Day. It’s a write-up of a new paper that is open access, Temporal niche expansion in mammals from a nocturnal ancestor after dinosaur extinction.

This research illustrates how computational power has changed evolutionary biology. There has long been an intuitive verbal model that mammals were ancestrally night-adapted creatures based on aspects of their biology, as well as the evolutionary reality that for most of the lineages’ existence they were overshadowed by dinosaurs (remember, more than half of our evolutionary history predates the Cenozoic).

But today we do more than posit models which match and predict the fossil (or genetic) data. Computationally intensive phylogenetic frameworks are tested using extant lineages to generate probabilities of given scenarios generating the data we see given particular models. Something like the Reversible-jump Markov chain Monte Carlo (which is used in this paper) could actually be done manually…if a phylogeneticist had thousands of slaves to do all the computations. Obviously, the emergence of powerful computers accessible to all really changed the game in terms of analytic power.

And yet I wonder about the sense of precision that people gain from these methods. Verbal models are necessarily vague. When you give a probability of a given hypothesis being 0.71, that gives understanding a solidity. But is it warranted? Though researchers understand all the individual moving parts of the phylogenetic framework, only a computer can really bring it all together.

It’s something to consider. This is to a great extent the future of evolutionary biology. Positing models, and put it into a calculating machine like Leibniz dreamed of.

Citation: Temporal Niche Expansion In Mammals From A Nocturnal Ancestor After Dinosaur Extinction
Roi Maor, Tamar Dayan, Henry Ferguson-Gow, Kate Jones

Addendum: This is stupid of me, but only after reading the above paper did I reflect that most amniotes are diurnal and that mammals are the exception. Think about it, birds. And reptiles are probably more sluggish at night.

May 4, 2011

We, Robot & Hamilton’s Rule

The original robots

We are haunted by Hamilton. William D. Hamilton specifically, an evolutionary biologist who died before his time in 2000. We are haunted because debates about his ideas are still roiling the intellectual world over a decade after his passing. Last summer there was an enormous controversy over a paper which purported to refute the relevance of standard kin selection theory. You can find out more about the debate in this Boston Globe article, Where does good come from? If you peruse the blogosphere you’ll get a more one-sided treatment. So fair warning (I probably agree more with the loud side which dominates the blogosphere for what it’s worth on the science).

What was Hamilton’s big idea? In short he proposed to tackle the problem of altruism in social organisms. The biographical back story here is very rich. You can hear that story from the “horse’s mouth” in the autobiographical sketches which Hamilton wrote up for his series of books of collected papers, Narrow Roads of Gene Land: Evolution of Social Behaviour and Narrow Roads of Gene Land: Evolution of Sex. ...

November 24, 2010

The inevitable social brain

ResearchBlogging.orgOne of the most persistent debates about the process of evolution is whether it exhibits directionality or inevitability. This is not limited to a biological context; Marxist thinkers long promoted a model of long-term social determinism whereby human groups progressed through a sequence of modes of production. Such an assumption is not limited to Marxists. William H. McNeill observes the trend toward greater complexity and robusticity of civilization in The Human Web, while Ray Huang documents the same on a smaller scale in China: A Macrohistory. A superficial familiarity with the dynastic cycles which recurred over the history of Imperial China immediately yields the observation that the interregnums between distinct Mandates of Heaven became progressively less chaotic and lengthy. But set against this larger trend are the small cycles of rise and fall and rise. Consider the complexity and economies of scale of the late Roman Empire, whose crash in material terms is copiously documented in The Fall of Rome: And the End of Civilization. It is arguable that it took nearly eight centuries for European civilization to match the vigor and sophistication of the Roman Empire after its collapse as a unitary entity in the 5th century (though some claim that Europeans did not match Roman civilization until the early modern period, after the Renaissance).

It is natural and unsurprising that the same sort of disputes which have plagued the scholarship of human history are also endemic to a historical science like evolutionary biology. Stephen Jay Gould famously asserted that evolutionary outcomes are highly contingent. Richard Dawkins disagrees. Here is a passage from The Ancestor’s Tale:

…I have long wondered whether the hectoring orthodoxy of contingency might have gone too far. My review of Gould’s Full House (reprinted in A Devil’s Chaplain) defended the popular notion of progress in evolution: not progress towards humanity – Darwin forend! – but progress in directions that are at least predictable enough to justify the word. As I shall argue in a moment, the cumulative build-up of compelx adaptations like eyes strongly suggest a version of progress – especially when coupled in imagination with of the wonderful products of convergent evolution.

Credit: Luke Jostins
Credit: Luke Jostins

One of those wonderful products is the large and complex brains of animals. Large brains are found in a disparate range of taxa. Among the vertebrates both mammals and birds have relatively large brains. Among the invertebrates the octopus, squid and cuttlefish are rather brainy. The figure to the right is from Luke Jostins, and illustrates the loess curve of best fit with a scatter plot of brain size by time for a large number of fossils. The data set is constrained to hominins, humans and their ancestors. As you can see there is a general trend toward increase cranial capacities across all the human populations. Neandertals famously were large-brained, but they exhibited the same secular increase in cranial capacity as African Homo. On the scale of Pleistocene Homo and their brains the idea of the supreme importance of contingency seems ludicrous. Some common factor was driving the encephalization of humans and their near relations over the past two million years. This strikes me as very strange, as the brain is metabolically expensive, and there are plenty of species with barely a brain which are highly successful. H. floresiensis may be a human instance of this truism.

But what about the larger macroevolutionary pattern? Is there a trend toward larger brain sizes in general, of which primates, and humans in particular, are just the most extreme manifestation? Some natural historians have argued that there is such a trend. But, there is a question as to whether increased brain size is simply a function of allometry, the pattern where different body parts and organs tend to correlate together in size, but also shift in ratio with scale. The nature of physics means that very large organisms have to be more robust because their mass increases far faster than their surface area. By taking the aggregate relationship between body size and brain size, and examining the species which deviate above or below the trend line, one can generate an encephalization quotient. Humans, for example, have a brain which is inordinately large for our body size.

And yet there are immediate problems looking at relationships between body and brain size, and inferring expectations. Different species and taxa are not interchangeable in very fundamental ways, and so a summary statistic or trend may obscure many fine-grained details. A new paper in PNAS focuses specifically on various mammalian taxa, corrects for phylogenetics, and also relates encephalization quotient by taxa to the proportion of social animals within each taxon. Encephalization is not a universal macroevolutionary phenomenon in mammals but is associated with sociality:

Evolutionary encephalization, or increasing brain size relative to body size, is assumed to be a general phenomenon in mammals. However, despite extensive evidence for variation in both absolute and relative brain size in extant species, there have been no explicit tests of patterns of brain size change over evolutionary time. Instead, allometric relationships between brain size and body size have been used as a proxy for evolutionary change, despite the validity of this approach being widely questioned. Here we relate brain size to appearance time for 511 fossil and extant mammalian species to test for temporal changes in relative brain size over time. We show that there is wide variation across groups in encephalization slopes across groups and that encephalization is not universal in mammals. We also find that temporal changes in brain size are not associated with allometric relationships between brain and body size. Furthermore, encephalization trends are associated with sociality in extant species. These findings test a major underlying assumption about the pattern and process of mammalian brain evolution and highlight the role sociality may play in driving the evolution of large brains.

A key point is that the authors introduce time as an independent variable, so they are assessing encephalization over the history of the taxon. This is clearly relevant for humans, but may be so for other mammalian lineages. The table and figures below show the encephalization slope generated by using time and body size as the predictors and brain size as the dependent variable. A positive slope means that brain size is increasing over time.

Two major points:

- Note that the slope is sensitive to the level of taxon one is examining. A closer focus tends to show more variance between taxa. So, for example, humans distort the value for primates in general. Bracketing out anthropoids paints a more extreme picture of encephalization, a higher slope. In contrast, the lemurs and their relatives exhibit less encephalization over time.

- The correlation between proportion of species which exhibit sociality and encephalization of the taxon is strong. From the text:

Encephalization slopes were correlated with both the proportion of species with stable groups (order R = 0.92, P = 0.005, n = 6; suborder R = 0.767, P = 0.008, n = 9; Fig. 2 A and B) and the proportion in either facultative or stable social groups (order R = 0.804, P = 0.027, n = 6; suborder R = 0.63, P = 0.04, n = 9).

The last figure makes it is clear that the correlations are high, so the specific values should not be surprising. Don’t believe these specific figures too much, how one arranges the data set or categorizes may have a large effect on the p-value. But the overall relationship seems robust.

A highly encephalized “alien”

What to think of all of this? If you don’t know, one of the authors of the paper, Robin Dunbar, has been arguing for the prime importance of social structure in driving brain evolution among humans for nearly twenty years. The relationship is laid out in his book Grooming, Gossip, and the Evolution of Language. Robin Dunbar is also the originator of the eponymous Dunbar’s number, which argues that real human social groups bound together by interpersonal familiarity have an upper limit of 150-200. He argues that this number arises because of the computational limits of our “wetware,” our neocortex. Those limits presumably being a function of biophysical constraints.

One interesting fact though is that the median cranial capacity of our species seems to have peaked around one hundred thousand years ago. The average human today has a smaller brain than the average human alive during the Last Glacial Maximum! (see this old post from Panda’s Thumb, it’s evident in the charts) This may be simply due to smaller body sizes in general after the Ice Age. Or, it may be due to the possibility that social changes with the rise of agriculture required less brain power.

Ultimately if Dunbar and his colleagues are correct, if social structure is the most powerful variate in explaining differences in brain size when controlling for phylogenetics and body size, then in some ways it is surprising to me. After all, it does not seem that ants have particularly large brains, despite being extremely social and highly successful. Clearly the hymenoptera and other social insects operate on different principles from mammals. Instead of
developing “hive minds,” it seems as if in mammals greater social structure entails greater cognitive structure.

Citation: Susanne Shultz, & Robin Dunbar (2010). Encephalization is not a universal macroevolutionary phenomenon in mammals but is associated with sociality PNAS : 10.1073/pnas.1005246107

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