The current study is based upon a somewhat disappointingly smalll sample consisting of "75 human head lice [that] were collected from different individuals at 10 localities throughout the world. Clothing lice came from two sites: Canada and Nepal. Canadian clothing lice (N = 16) were collected from a single homeless person. The two clothing lice from Nepal (N = 2) were collected from two persons." This small sample size and the paper's comparison in the paper to divergent results from another, even smaller louse genetics study by Leo et al. (2005) of louse genetics in eleven double clothing-head lice infections designed to determine if they consitute one or two species, suggest that neither study nor the two studies combined, have secured a sample comprehensive enough to capture something close to the complete global genetic diversity in human head and clothing lice.
The ten locations were a Western Canadian City, New York City, San Francisco, two locations in Florida, Hondurus, Thailand, Nepal, Cambodia, Norway and the United States. The mtDNA clade analysis was also informed by five previously published studies of louse genetics. As a result, the geographic descriptions below convey the impression that they are more complete than they is actually the case. Fore example, the fact that some regions, like South America, aren't specifically described, appears to be a function of the lack of a sample from that location rather than necessarily constituting evidence of a population genetic barried between Central America and South America that played a role in human louse genetics.
Human Head Louse mtDNA genetics
There are four main clades in the mtDNA population genetics of lice (open access) based on their mtDNA. Clade A is found worldwide, but has two internal geographic clusters, one containing all the Clade A lice outside Africa, and the other including African lice Clade B is found in Europe, Australia, Central America and North America. Clade C is found in Nepal and Ethiopia. The analysis was conducted using the essentially the same cluster analysis analytical tools used in human population genetics studies.
Clade A is estimated to have diverged from the common ancestor of Clades A and B about 110,000 to 540,000 years ago. No date is suggested in the study for the internal clustering within Clade A, although presumably, it was later than the divergence date for the entire clade. Clade B is estimate to have diverged 150,000 years ago. Clade C also diverges something on the order of 150,000 years ago. The chimp louse diverged from the common ancestor of Clades A, B and C about 2,000,000 years ago.
The dates for Clade B and C are consistent with divergences associated with the original Out of Africa migration. Clade A could be consistent with either Out of Africa, or with the appearance of the common ancestor of Neanderthals and modern humans, or with an intermediate date such as the emergence of the first modern humans.
The ABC divergence date from the chimp louse takes place right around the time that Homo erectus evolved and became the first hominin to leave Africa.
[P]revious studies suggested that louse mtDNA haplogroup A has had a long history associated with the host lineage that led to anatomically modern humans, Homo sapiens. Studies of modern human expansion out of Africa show the footprint of serial founder effects on the genetic diversity of human populations as revealed by the human pattern of increased genetic distance and decreased diversity with distance from Africa. The microsatellite loci developed in this study are ideal markers to measure louse genetic diversity and how it parallels to human diversity. Louse mitochondrial haplogroup B is found in the New World, Europe and Australia but not in Africa. Reed et al. suggested that its evolutionary origins might lie with archaic hominids from Eurasia (i.e., Homo neanderthalensis) and that they became associated with modern humans via a host switch during periods of overlap.Autosomal Louse Genetics
Autosomal louse genetics were also considered and in a step that far too few studies of human genetics take, correlated with the mtDNA data.
Population structure was inferred with a Bayesian clustering approach implemented in the STRUCTURE software. In all the three STRUCTURE analysis, all worldwide human lice were assigned to four genetic clusters (K = 4), one defined by clothing lice from Canada, the other head lice from North America and Europe, a third cluster was composed of head lice from Honduras, and the fourth cluster included Asian lice (both head and clothing lice). . . .
In another STRUCTURE analysis, we incorporated the mitochondrial haplogroup data for each louse. . . . there is no correlation between mitochondrial haplogroups (A and B) and nuclear genetic clusters, at least among the current samples.
We also employed the multivariate technique Principal Coordinate Analysis (PCA) . . . We found similar results as the STRUCTURE analyses, where one cluster included head lice from North America and Europe, while all Asian and Central American lice comprised a second cluster with the exception of the clothing louse from Nepal that showed an intermediate position between this group and clothing lice from Canada. . . .
For Canada, New York, Honduras, and Cambodia populations we further analyzed their genetic substructure by analyzing each population individually using STRUCTURE. These results revealed an increase in the number of regional genetic clusters in New York (K = 3), and in Cambodia (K = 3). Although Evanno's method cannot evaluate K = 1 as the most likely number of clusters, we found that populations from Canada and Honduras showed admixture for all individuals when K = 2. This can be interpreted as evidence supporting Canada and Honduras as a single genetic cluster, respectively, at least with the current number of microsatellite markers analyzed.
[T]he clothing lice (Canada and Nepal) grouped more closely with the Central America-Asia cluster probably because of close ancestry. These results are consistent with the idea that clothing lice evolved from head louse ancestors, invading the body region only recently with the advent of clothing use in modern humans. Further, studies have shown that clothing lice emerged from only one of the three mitochondrial haplogroups (Clade A) roughly 83,000 years ago. Although clothing lice belong to a single mtDNA clade, they appear to have evolved locally (in situ) throughout the world from head louse populations.
They do not seem to "parallel" human clades, right? Just to have some regional structure, like we do, but different in many aspects.
ReplyDeleteClade A's subgroups are suggestive of a non-African mtDNA N and a mixed Africa and non-African mtDNA L3(xN) which would include mtDNA M and its descendants, or of Y-DNA CT (xE) and Y-DNA E respectively.
ReplyDeleteClade B's non-African distribution is suggestive of mtDNA N and all descendants, and of Y-DNA F and all descendants.
Clade C found only in Ethiopia and Nepal is parallel to Y-DNA DE which is found in Tibet and Africa but not in between. Given the mysteries surround the weird distribution of D and DE with little data to explain them, this is a tempting hint that is worth a follow up. I can't think of any mtDNA fits for that kind of discontinuous distribution.
The absence of any pure East Eurasian clade of lice is particularly disappointing as that is the second most basal split in human population genetics after African-Nonafrican, although some of that may be buried by backmigration (in the same way that mtDNA M1 is an African back migration of what is otherwise exclusively an Asian clade - this could be going on in Clade C and be hidden back lack of intermediate data since Ethiopia is a place where there is M1 back migration).
In general, there definitely does seem to be at least a parallel at the first order division betweeen Africans and non-Africans found in humans. But, the parallels are less clear, particularly in light of the incomplete sampling that could be creating deceptive gaps in distributions, than the headline of the press release or a first glance at the data showed.
So, I actually edited out my observations on the parallels that I did see from my post. I do think that better sampling could show parallels.