Four Stone Hearth, the Anthropology Carnival, starts at Anthropology.net today.

Pelicans eat fish, right? Don’t count on it, especially if you are a pigeon…

US author offers ‘Vedic alternative’ to evolution theory:

Offering a “Vedic alternative” to Darwin’s Theory of Evolution, an American author has claimed that human beings devolved from the “realm of pure consciousness”, as testified by archaeological evidence discovered over the past 150 years.
“We did not evolve up from matter. Instead, we devolved, or came down, from the realm of pure consciousness, spirit,” author Michael A Cremo, said, citing many archaeological, psychological and genetic examples.

I have stated before that Creationism might be most prominent in American fundamentalist Christianity, but it is not limited to it. The reality is that I suspect that a “Creationist” bent is the default human mode, ready to kick in sans science. Note that this “theorist” uses similar talking points to convential Christian Creationists, replace “matter” with “monkeys,” and instead of coming down from a “realm of spirit” we are endowed with souls.

Salamander Candy has a post attempting to use the heuristic of the adaptive landscape in relation to Iraq and its political organization. These analogies of course have resonance in direct proportion to familiarity. Myself, I tend to imagine sociological systems like the boat vs. chair conformation.

Note: Download file here (it has more precise percentages on blue eyes in Norway, someone could try their hand at some game theoretic modeling if they were inclined, I lack the time right now).
Ruchira Paul brought this article to my attention:

Before you request a paternity test, spend a few minutes looking at your child’s eye color. It may just give you the answer you’re looking for…Their studies…show that blue-eyed men find blue-eyed women more attractive than brown-eyed women. According to the researchers, it is because there could be an unconscious male adaptation for the detection of paternity, based on eye color.
Both blue-eyed and brown-eyed women showed no difference in their preferences for male models of either eye color. Similarly, brown-eyed men showed no preference for either blue-eyed or brown-eyed female models. However, blue-eyed men rated blue-eyed female models as more attractive than brown-eyed models.

First, it is debatable whether a single locus Mendelian model of one biallelic gene is appropriate for eye color (see this review [PDF], or this introduction). Though it does seem that the majority of the population level variance in eye color is due to OCA2, there is a residual and non-trivial affect from other loci, some of which act independently. This is obviously clear insofar as blue and brown eye colors are typologies which compress a range of shades which span greens and hazels, the latter of which reflect quantitative variation in melanin within the iris. The short of it is that it is genetically possible without mutation for two blue eyed parents to have brown eyed offspring, and there is quantitative variance between siblings in many families in regards to eye color because more than one locus is at work here.
That being said, there is a difference between skin color and eye color in that the latter is dominated by one locus which seems to be responsible for 0.7 – 0.8 of the variance across populations, so as a first approximation one may hold to a simple Mendelian model without too much distortion of the nature of the system. So, from this moment on I will neglect the reality that the inheritance of eye color is not as simple as the authors of the paper seem to present it, and look at some other issues. The authors use the one-locus Mendelian model to posit that the recessive character of blue eyes serve as paternity confidence markers. Fair enough. But there is a problem with this narrative: large swaths of Europe have very low frequencies of individuals with dark eyes. In other words, the potential lovers are likely to have blue eyes as well, making this trait useless as a distinctive marker! Consider a population where 90% of the individuals have blue eyes (e.g., Estonia or Finland might be good candidates). Assume a Hardy-Weinberg system, so

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One of the many hypotheses in palaeoanthropology is homonids shifted to meat eating because it was metabolically rich and allowed the increase in our brain sizes. Well, there might now be some support from primate analogs finally, Study suggests evolutionary link between diet, brain size in orangutans:

In a study of orangutans living on the Indonesian islands of Borneo and Sumatra, scientists from Duke University and the University of Zurich have found what they say is the first demonstration in primates of an evolutionary connection between available food supplies and brain size.
Based on their comparative study, the scientists say orangutans confined to part of Borneo where food supplies are frequently depleted may have evolved through the process of natural selection comparatively smaller brains than orangs inhabiting the more bounteous Sumatra.

I’m sure by now you’ve seen Nick Matzke’s chart of fossil hominid cranial capacities. Between 3 million and 200,000 years BP there was consistent long term growth in our brains (with a few possible spurts within the general trend). Brain genes have also been selected for. 25% of our caloric intake is reserved just for our expensive grey and white matter, so not only do we service it, it better serve us!

Via Hit and Run, a Wired article: Battle of the New Atheism. The author talks with Dawkins and Dennett.

One poster at the SFN conference last week described a microRNA (miR132) discovered using a novel screening technique for learning related genes that controls dendrite growth and production of new synapses. The method is called Serial Analysis of Chromatin Occupancy (SACO). The team that first produced SACO in 2004 focused on a transcription factor called CREB (CyclicAMP Response Element Binding Protein, this is NOT CPEB). Part of CREB’s popularity stems from the emphasis it has received as a sort of final common path for long-term memory processes in the scheme presented by Eric Kandel in his Nobel work. In that view, CREB is activated by signaling pathways initiated during learning, such as the cyclic-AMP dependent protein kinase (PKA). Activated CREB then goes to the nucleus and sits next to parts of the genome that it wants to regulate up or down. Soren Impey and Daniel Storm showed a few years ago that mice carrying a reporter gene (lacZ) with 6 places for CREB to sit (CREs) in front of it showed more reporter expression in the hippocampus following learning than following simple stimulus exposure. There are many questions as to why you would want to bother to regulate genes at the transcriptional level in response to learning. It seems slow and clunky compared to translating a pre-existing RNA near the affected synapses, but the level of many transcripts does change in the minutes to hours following learning or induction of synaptic plasticity. One assumes it is not for nothing.

When a transcription factor like CREB settles down on the DNA you can play a dirty trick and glue it to its seat using formaldehyde. In the initial SACO study, they activated CREB using a drug that activates PKA and then glued it to all the different parts of the DNA that it lighted upon. They then pulled CREB and whatever DNA would come with it out of solution and sequenced 21 nucleotide strings of it. 21 nucleotides turns out to be just enough to uniquely identify a region in a large genome. These segments represent candidate CREB binding sites, especially if the same segment comes up multiple time. So they sorted through all these potential CREB binding sites and found that most of them were either in genes or near them, so that was nice. Some of the SACO-identified sites were near microRNAs. One of those microRNAs is miR132 and (I guess because it has such a pretty name) Impey and co decided to follow it up.

In the SFN poster, they showed an increase in miR132 with neuronal activity. Activity in cell cultures (where most of this work was done) can lead to dendritic growth and production of new synapses, but not if miR132 isn’t around. The straightforward story then is that activity activates CREB which goes to the nucleus and causes transcription of miR132 which then must come out and inhibit the translation of some protein? They used several predictoin algorithms to try and pick out what neuronal gene miR132 might antagonize and came up with a protein called p250GAP. We’d have to get involved in a whole other signaling pathway to explain what p250GAP does, but let’s just say that it is in prime position to regulate the cytoskeleton and therefore dendritic and synaptic morphology. Note that miR132 works in the opposite direction from miR134 in terms of synapse growth (although they could be active at different times and in different areas). Reports in Drosophila that RNA interference associated machinery is degraded in response to activity raised the possibility that RNAs that promote synaptic growth and strength could be regulated as a group by RNAi and released from inhibition in concert. But alas, with microRNAs having opposite functional effects the appealing idea of coordinated regulation seems less plausible now.

In case you were asleep. Dawkins may be right, but Colbert won anyway.

Update from Razib: Dawkins on the radio.

I just came across another argument for why the regulatory changes vs. protein coding changes argument is inane— sometimes protein-coding changes are regulatory changes. Ok, maybe RPM made that point in the comments on that post I linked, but here’s a great example, from a recent paper:

The authors looked for local regulatory variation in a number of genes, and found one instance where the putative regulatory variant mapped to a protein-coding SNP inside the gene. On a little further study, they found the story goes like this– the gene itself (AMN1) is a regulator of two other genes (DSE1 and DSE2) in a network, and those genes, in turn, regulate AMN1. The coding change in the gene keeps it from playing its proper role in the network, so DSE1 and DSE2 are upregulated and, in turn, up-regulate AMN1. I’m sure there’s an easier way to explain this, but the take-home message is that a protein-coding change in AMN1 leads, indirectly, to it’s own regulation.

So the genetics underlying gene expression can be rather complex. And just think, it’s networks of interacting genes that lead to phenotypes–the complexity is rather daunting, and I feel like first understanding gene expression is certainly a great first step towards getting at phenotypic complexity itself (there’s another great first step, but no one seems to have taken it…yet). For those who simply must know more, here‘s a great review of the current knowledge on the genetics of gene expression.