I have long been on the record as a skeptic of the of the proposition that democratization in the Arab world will usher in liberalism. To a great extent I think that my skepticism has been vindicated, though these are early times yet. But looking at the events as they are playing out in Egypt and Tunisia reminds me of the rock-paper-scissors games.
In The New York Times, DNA Turning Human Story Into a Tell-All:
The tip of a girl’s 40,000-year-old pinky finger found in a cold Siberian cave, paired with faster and cheaper genetic sequencing technology, is helping scientists draw a surprisingly complex new picture of human origins.
The new view is fast supplanting the traditional idea that modern humans triumphantly marched out of Africa about 50,000 years ago, replacing all other types that had gone before.
Instead, the genetic analysis shows, modern humans encountered and bred with at least two groups of ancient humans in relatively recent times: the Neanderthals, who lived in Europe and Asia, dying out roughly 30,000 years ago, and a mysterious group known as the Denisovans, who lived in Asia and most likely vanished around the same time.
Their DNA lives on in us even though they are extinct. “In a sense, we are a hybrid species,” Chris Stringer, a paleoanthropologist who is the research leader in human origins at the Natural History Museum in London, said in an interview.
First, for reasons of novelty we are emphasizing the exotic tendrils of the human family tree. Even Chris Stringer, the modern paleontological father of “Out of Africa,” is claiming we’re hybrids! But let’s not forget that non-Africans are the product of a very rapid radiation out of the margins of the Afrotropic ecozone within the last ~50-100,000 years. I am not entirely sure that this is as true of Africans (recall how extremely basal Bushmen are to the rest of humanity; they seem to have diverge well before the “Out of Africa” pulse).
The title is rather loud and non-objective. But that seems to me to be the upshot of Henrich et al.’s The puzzle of monogamous marriage (open access). In the abstract they declare that “normative monogamy reduces crime rates, including rape, murder, assault, robbery and fraud, as well as decreasing personal abuses.” Seems superior to me. As a friend of mine once observed, “If polygamy is awesome, how come polygamous societies suck so much?” Case in point is Saudi Arabia. Everyone assumes that if it didn’t sit on a pile of hydrocarbons Saudi Arabia would be dirt poor and suck. As it is, it sucks, but with an oil subsidy. The founder of modern Saudi Arabia was a polygamist, as are many of his male descendants (out of ~2,000). The total number of children he fathered is unknown! (the major sons are accounted for, but if you look at the genealogies of these Arab noble families the number of daughters is always vague and flexible, because no one seems to have cared much)
According to the reader survey 88 percent said they understood what heritability was. But only 34 percent understood the concept of additive genetic variance. For the purposes of this weblog it highlights that most people don’t understand heritability, but rather heritability. The former is the technical definition of heritability which I use on this weblog, the latter is heritability in the colloquial sense of a synonym for inheritance, biological and cultural. Almost everyone who understands the technical definition of heritability will know what heritability in the ‘narrow sense’ is, often just informally termed heritability itself. It is the proportion of phenotype variability that can be attributed to additive genetic variation. Those who understand additive genetic variance and heritability in the survey were 32 percent of readers. If you understand heritability in the technical manner you have to understand additive genetic variance. This sets the floor for the number who truly understand the concept in the way I use on this weblog (I suspect some people who were exceedingly modest who basically understand the concept for ‘government purposes’ put themselves in the ‘maybe’ category’). After nearly 10 years of blogging (the first year or so of which I myself wasn’t totally clear on the issue!) that’s actually a pretty impressive proportion. You take what you can get.
My own working assumption is that the demand side impulse toward mass adoption of human genomic technology in the USA is going to be dampened by fear of downside consequences, GINA notwithstanding. Rather, I assume that the more deregulated consumer environment in parts of Asia with very low fertility rates, as well as European states with more thorough socialized medical systems, will “punch above their weight” in this domain. It looks likes a genuine socialized medical system (i.e., the doctors are state employees), that of the UK, is preparing to step up to the plate, Genomic innovation will better target treatment in the NHS:
The independent cross-government advisory group was set up in response to the 2009 House of Lords report on genomic medicine. It draws on expertise from across Government and research institutes and makes six recommendations to Government:
The recommendations are:
• to develop a cross-cutting strategic document, to set out the direction on genomic technology adoption in the NHS;
• to develop a national central genomic data storage facility;
• that the NHS Commissioning Board should lead on developing genomic technology adoption;
• to work to develop a service delivery model for genomic technologies;
• that the NHS should continue to develop genomics education and training; and
• to raise public awareness of genomic technology and its benefits.
Many researchers believe that personal genomics will really not hit the biomedical sweet spot until you have on the order of a million people sequenced. But even then in the American system how to get a hold of all that information is going to be problematic, since it will likely be decentralized. In contrast in Britain tens of millions of people have one primary healthcare provider, their national government.
You can read the full report online (PDF). Like the “rise of China,” the “rise of genomics,” was one of those futurist predictions. Until now. It’s ridiculous to talk about the rise of something which has risen. Now it’s about maturity and ripening.
The Pith: New software which gives you a more fine-grained understanding of relationships between populations and individuals.
According to the reader survey >50 percent of you don’t know how to interpret PCA or model-based (e.g., ADMIXTURE) genetic plots, so I am a little hesitant to point to this new paper in PLoS Genetics, Inference of Population Structure using Dense Haplotype Data, as it extends the results of those earlier methods. But it’s an important paper, and at some point I’ll starting using their software. The “big picture” is that earlier methods left “some information on the table.” That’s partly due to the fact that they were developed (or in the case of PCA leveraged, as it’s a very general technique) in an era where very dense marker data sets were not available (today we’re shifting to full genome sequences in many cases!). The information left on the table would be haplotype structure. Genetic variation in a concrete form manifests as sequences along a line, many of them physically connected. These correlations of nearby variant markers represent haplotypes of great interest, because they are excellent clues to admixture or divergence events across populations. In contrast the older methods, were looking at variation from marker to marker, each in turn independently, which collapses some of the important genomic structure that we can now inspect (in fact, linkage disequilibrium due to these correlations can distort some of the results in the older methods, so you want to “thin” your marker set).
Let me make this concrete for you. On 23andMe you can see where your friends shake out on a PCA plot using the HGDP data set as a reference. What this means is that the HGDP data set is used to generate independent dimensions of genetic variation. As is the usual case in these analyses the largest dimension separates Africans from everyone else, and the second largest dimension separates Asians from Europeans and Africans. 23andMe customers are then projected upon this variation, so you can get a sense where you are positioned in the clusters. To the left is a zoom in on the section for Central/South Asians. You can see that one of my friends, highlighted with a green color, falls almost perfectly in the Uygur cluster. According to ancestry estimates my friend is 50 percent Asian and 50 percent European. The “representative” Uygur in the 23andMe chromosome painting gives about the same results. But these are total genome estimates. The historical nature of my friend’s admixture and that of the Uygur woman is very different, as one can see in the below figure.
In light of my previous posts on GRE scores and educational interests (by the way, Education Realist points out that the low GRE verbal scores are only marginally affected by international students) I was amused to see this write-up at LiveScience, Low IQ & Conservative Beliefs Linked to Prejudice. Naturally over at Jezebel there is a respectful treatment of this research. This is rather like the fact that people who would otherwise be skeptical of the predictive power of I.Q. tests become convinced of their precision of measurement when it comes to assessing whether a criminal facing the death penalty is mentally retarded or not! (also see this thread over at DailyKos). You can see some of the conservative response too.
The latest edition of The American Journal of Human Genetics has two papers using “old fashioned” uniparental markers to trace human migration out of Africa and Siberia respectively. I say old fashioned because the peak novelty of these techniques was around 10 years ago, before dense autosomal SNP marker analyses, let alone whole genome sequencing. But mtDNA, passed down the maternal line, and Y chromosomes, passed from father to son, are still useful. Prosaically they’re useful because the data sets are now so large for these sets of markers after nearly 20 years of surveying populations. More technically because these two regions of the genome do not recombine they lend themselves to excellent representation as a tree phylogeny. Finally, mtDNA in particular is particularly amenable to estimates via molecular clock methodologies (it has a region with a higher mutational rate, so you can sample a larger range of variation over a given number of base pairs; you can use STRs, which mutate rapidly, for Y chromosomes, but there seems to be a lot of controversy in dating).
The papers are The Arabian Cradle: Mitochondrial Relicts of the First Steps along the Southern Route out of Africa and Mitochondrial DNA and Y Chromosome Variation Provides Evidence for a Recent Common Ancestry between Native Americans and Indigenous Altaians. Dienekes has already commented on the first paper. I am not going to take a detailed position on either, but I have to add that we need to be very careful of extrapolating from maternal or paternal lineages, and, assuming that population turn over is low enough that we can make phylogeographic inferences about the past from the present. For example, if you look at mtDNA South Asians as a whole strongly cluster with East Asians and not Europeans, while if you look at Y chromosomes you see the reverse. The whole genome gives a more mixed picture. Additionally, ancient DNA analyses in Northern Eurasia are showing strong discontinuities between past and present populations. So coalescence back to last common ancestor between two different lineages in two different regions may actually be due to diversity in a common source population more recently, which entered into demographic expansion and replaced other groups.
If you need the papers, email me. Some of you know the alphabet soup of haplogroups better than I do. Below are two figures which I think give the top line results.
In the survey below I asked if you knew about how many migrants per generation were needed to prevent divergence between populations. About ~80 percent of you stated you did not know the answer. That was not totally surprising to me. The reason I asked is that the result is moderately obscure, but also rather surprisingly simple and fruitful. The rule of thumb is that 1 migrant per generation is needed to prevent divergence.*
It doesn’t tell you much in and of itself of course. But if you think about it you can inject that fact into all sorts of other population genetic phenomena. For example, to have selection across two populations which is not reducible to selection within those populations (i.e., inter-demic selection) you need group-level genetic differences. These differences can be measured by the Fst statistic. In short the value of Fst tells you the proportion of variation which can be attributed to between-group differences (e.g., Fst across human races is ~0.15). For natural selection to have any adaptive effect you also need heritable variation. If you have lots of heritable variation selection can be weaker, while if you have little heritable variation selection has to be very strong (see response to selection). Fst is a rough gauge of heritable variation when you are evaluating group level differences. An Fst of 1.0 would imply that the groups are nearly perfectly distinct at the loci of interest, while an Fst of 0.0 would imply that the groups are not genetically distinct at all. With no distinction selection would have no efficacy in terms of driving adaptation. All this is a long way to saying that the 1 migrant rule is one reason that evolutionary biologists take a skeptical position in relation to group selection. It tends to quickly erase the variation which group selection depends upon.