Group selection! - maybe not so blasphemous after all

Group selection has long been a taboo topic just like the study of biological or genetic differences between human "races" had been a taboo topic. Several papers that have come out recently have acknowledged that group selection likely plays at least some kind of role in the process of natural selection.(here, here, here, here, here, here)
But finally, D.S. Wilson and E.O. Wilson have written up a paper that attempts to breathe even more life into this unjustly ignored and ridiculed idea.
I had read it a few months ago and was meaning to blog on it, but never got around to it, but I just saw a story about the paper which is supposed to be out now, but I couldn't find it on the website. It's available online from D.S. Wilson's website (link on title below). See further below abstract for a few more comments, and a great quote at the very end of this post.

Rethinking the Theoretical Foundation of Sociobiology

The Quarterly Review of Biology December 2007 v.82, no.4

Abstract: Current sociobiology is in theoretical disarray, with a diversity of frameworks that are poorly related to each other. Part of the problem is a reluctance to revisit the pivotal events that took place during the 1960s, including the rejection of group selection and the development of alternative theoretical frame- works to explain the evolution of cooperative and altruistic behaviors. In this article, we take a “back to basics” approach, explaining what group selection is, why its rejection was regarded as so important, and how it has been revived based on a more careful formulation and subsequent research. Multilevel selection theory (including group selection) provides an elegant theoretical foundation for sociobiology in the future, once its turbulent past is appropriately understood

This paper goes through the arguments behind the battering and quasi-elimination of group selection as a viable possibility, and then they go through the evidence for instances of group selection. I don't have time to go into all the arguments now but I highly recommend this paper to anyone interested in this topic. I'll just put the last witty paragraph here:

When Rabbi Hillel was asked to explain the Torah in the time that he could stand on one foot, he famously replied: “Do not do unto others that which is repugnant to you. Everything else is commentary.” Darwin’s original insight and the developments reviewed in this article enable us to offer the following one foot summary of sociobiology’s new theoretical foundation: “Selfishness beats altruism within groups. Altruistic groups beat selfish groups. Everything else is commentary."

.”

Chalk another one up for "environment"

What contributes to the disparities in health between ethnic groups in the US: genetic or environmental differences between groups? ... well, both probably, but we have a long way to go in identifying all the specific genetic and environmental variants that contribute to these disparities, and to understand the relative contribution of each, for specific diseases and for specific groups. The paper below, newly published in PLoS Medicine gives us insight into another potential environmental contributor to health disparities between majority and minority groups in England. Doctors are more likely to be of a different ethnicity than their minority patients, and this can create problems in communication and optimal health care delivery to ethnic minorities

Professional Uncertainty and Disempowerment Responding to Ethnic Diversity in Health Care: A Qualitative Study

Joe Kai, Jackie Beavan, Christina Faull, Lynne Dodson, Paramjit Gill, Angela Beighton

PLoS Medicine 4(11): e323

Background While ethnic disparities in health and health care are increasing, evidence on how to enhance quality of care and reduce inequalities remains limited. Despite growth in the scope and application of guidelines on “cultural competence,” remarkably little is known about how practising health professionals experience and perceive their work with patients from diverse ethnic communities. Using cancer care as a clinical context, we aimed to explore this with a range of health professionals to inform interventions to enhance quality of care.

Methods and Findings We conducted a qualitative study involving 18 focus groups with a purposeful sample of 106 health professionals of differing disciplines, in primary and secondary care settings, working with patient populations of varying ethnic diversity in the Midlands of the UK. Data were analysed by constant comparison and we undertook processes for validation of analysis. We found that, as they sought to offer appropriate care, health professionals wrestled with considerable uncertainty and apprehension in responding to the needs of patients of ethnicities different from their own. They emphasised their perceived ignorance about cultural difference and were anxious about being culturally inappropriate, causing affront, or appearing discriminatory or racist. Professionals' ability to think and act flexibly or creatively faltered. Although trying to do their best, professionals' uncertainty was disempowering, creating a disabling hesitancy and inertia in their practice. Most professionals sought and applied a knowledge-based cultural expertise approach to patients, though some identified the risk of engendering stereotypical expectations of patients. Professionals' uncertainty and disempowerment had the potential to perpetuate each other, to the detriment of patient care.

Conclusions This study suggests potential mechanisms by which health professionals may inadvertently contribute to ethnic disparities in health care. It identifies critical opportunities to empower health professionals to respond more effectively. Interventions should help professionals acknowledge their uncertainty and its potential to create inertia in their practice. A shift away from a cultural expertise model toward a greater focus on each patient as an individual may help.

Huge study on the population genetics of Native Americans

This is a pretty impressive study. They analyzed "678 autosomal microsatellite markers genotyped in 422 individuals" spread across the Americas. They also compare it to the CEPH panel of worldwide populations
Interestingly, or ironically, there are no samples from populations living in the United States. The authors claim that their study "represents the largest continent-wide Native American population-genetic study performed to date". I like the fact that they use the data to examine several of the main hypotheses regarding Native American population genetics. They include 2o figures and 30 or so tables in the supplementary material!! They don't seem to find anything too surprising...

Genetic variation and Population Structure in Native Americans

Sijia Wang, Cecil M. Lewis Jr., et al.

PLoS Genetics 3(11): e185

Abstract: We examined genetic diversity and population structure in the American landmass using 678 autosomal microsatellite markers genotyped in 422 individuals representing 24 Native American populations sampled from North, Central, and South America. These data were analyzed jointly with similar data available in 54 other indigenous populations worldwide, including an additional five Native American groups. The Native American populations have lower genetic diversity and greater differentiation than populations from other continental regions. We observe gradients both of decreasing genetic diversity as a function of geographic distance from the Bering Strait and of decreasing genetic similarity to Siberians—signals of the southward dispersal of human populations from the northwestern tip of the Americas. We also observe evidence of: (1) a higher level of diversity and lower level of population structure in western South America compared to eastern South America, (2) a relative lack of differentiation between Mesoamerican and Andean populations, (3) a scenario in which coastal routes were easier for migrating peoples to traverse in comparison with inland routes, and (4) a partial agreement on a local scale between genetic similarity and the linguistic classification of populations. These findings offer new insights into the process of population dispersal and differentiation during the peopling of the Americas.

Genetic Admixture, and SES in Venezuela

They use very few markers, but they find some interesting, albeit expected differences in admixture between high and low SES groups.

Admixture estimates for Caracas, Venezuela, based on autosomal, Y-chromosome, and mtDNA markers.

Martínez H, Rodríguez-Larralde A, Izaguirre MH, De Guerra DC

Hum Biol. 2007 Apr;79(2):201-13.

Abstract: The present Venezuelan population is the product of admixture of Amerindians, Europeans, and Africans, a process that was not homogeneous throughout the country. Blood groups, short tandem repeats (STRs), mtDNA, and Y-chromosome markers have been used successfully in admixture studies, but few such studies have been conducted in Venezuela. In this study we aim to estimate the admixture components of samples from two different socioeconomic levels from Caracas, Venezuela's capital city, compare their differences, and infer sexual asymmetry in the European Amerindian union patterns. Gene frequencies for blood groups ABO and Rh (CDE) and for the STRs VWA, F13A01, and FES/FPS and mtDNA and Y-chromosome haplogroups were studied in a sample of 60 individuals living in Caracas, taken from a private clinic (high socioeconomic level), and 50 individuals, also living in Caracas, drawn from a public maternity clinic (low socioeconomic level). The admixture analysis for the five autosomal markers gives a high European component (0.78) and an almost negligible African sub-Saharan component (0.06) for the high socioeconomic level, whereas for the low socioeconomic level the sub-Saharan, European, and Amerindian components were 0.21, 0.42, and 0.36, respectively. Estimates of admixture based on mtDNA and Y-chromosome markers reveal that the Amerindian contribution to these Caracas samples is almost entirely through females, because the Y-chromosome Amerindian and African sub-Saharan chromosomes found in this study were scarce. Our study reveals that the identification of the grandparents' geographic origin is an important methodological aspect to take into account in genetic studies related to the reconstruction of historical events.

The sickle cell gene's recent introgression into East Africa

This is a "Short Report" and it is indeed very short! It seems like they assume that patterns of mt-DNA and Y-chromosome diversity are not subject to forces of selection and just represent neutral "population-level forces". I wonder how safe this assumption is? Here is the basis of their test:

By typing both the haploid Y chromosome and the S gene in the same samples it should be possible to test for common demography as well as detect affinities of particular S variants observed in Sudan to other regions of Africa.

their conclusion:

Our results suggest that the sickle cell gene may have been preferentially introduced through males of migrating west African tribes (Figure 1), particularly Hausa-Fulani, and Bagara in the large migrations that began in the eighteenth century and escalated during the nineteenth and early twentieth century. The estimates of a recent figure of 1–3 generations for the introduction of the gene and associated haplotypes to eastern Sahel, is consistent with demography during the past 100 years and with a hypothesis of a recent origin of malaria as a major human infection.

"recent origin of malaria as a major human infection" - hmm...interesting!

Co-introgression of Y-chromosome haplogroups and the sickle cell gene across Africa's Sahel

Rihab E Bereir, Hisham Y Hassan, Niven A Salih, Peter A Underhill, Luigi L Cavalli-Sforza, Ayman A Hussain, Dominic Kwiatkowski and Muntaser E Ibrahim

European Journal of Human Genetics (2007) 15, 1183–1185;

Abstract: The Sahel that extends from the Atlantic Ocean to the Ethiopian highland is a historical reservoir of Africa's cultures and grandest populations and a known arena of ancient and recent migrations. We are interested in the issue whether such migrations were also carriers of genetic traits and whether this introgression could be associated with population genetic markers. Based on analysis of Y-chromosome haplogroups, we present evidence that the sickle gene, one of the major protective polymorphisms known in malaria, has in fact found its way only recently to the gene pool of the populations in eastern Sahel. We discuss the possible dynamics of the process and give estimates of the age of the introduction of the S allele into eastern Sahel.

Genetic influence on hypertension differences between African and European Americans

In this large scale admixture scan, they don't find evidence for an effect of genetic differences between Africans and Europeans on hypertension risk. They discuss the implications in that the incidence disparity between African Americans and European Americans may be due more to the effects of the environment, but they also discuss some of the limitations of their study.
Interestingly they look at the effects of loci that were proposed to have an effect in an earlier study:

We also examined five candidate genes that were highlighted by Young et al. [3], who proposed that HTN may arise from the interaction of salt-availability in humans populations with heat-adapted alleles that vary widely in frequency across populations. None of the five genes produced an admixture signal, suggesting that the underlying alleles do not explain a substantial amount of differential HTN risk across these populations.

This earlier study, also in PLoS Genetics, suggests that:

... the current epidemic of hypertension is due to exposures of the modern period interacting with ancestral susceptibility. Modern populations differ in susceptibility to these new exposures, however, such that those from hot environments are more susceptible to hypertension than populations from cold environments. This differential susceptibility is likely due to our history of adaptation to climate.

High-Density Admixture Scan in 1,670 African Americans with Hypertension

Rahul C. Deo, Nick Patterson, Arti Tandon, Gavin J. McDonald, Christopher A. Haiman, Kristin Ardlie, Brian E. Henderson, Sean O. Henderson, David Reich

PLoS Genetics 3(11): e196

Author Summary: Hypertension (HTN) is a devastating disease with a higher incidence in African Americans than European Americans, inspiring searches for genetic variants that contribute to this difference. We report the results of a large-scale admixture scan for genes contributing HTN risk, in which we screened 1,670 African Americans with HTN and 387 control individuals for regions of the genome with elevated proportion of African or European ancestry. No loci were identified that were significantly associated with HTN. We also searched for evidence of an admixture signal at 40 candidate genes and eight previously reported linkage peaks, but none appears to contribute substantially to the differential HTN risk between African and European Americans. Finally, we observed nominal association at one of the loci detected in the admixture scan of Zhu et al. 2005 (p = 0.016 at 6q24.3 correcting for four hypotheses tested), although we caution that the significance is marginal and the estimated odds ratio of 1.19 per African allele is less than what would be expected from the original report; thus, further work is needed to follow up this locus.

Disease associations differ between ethnic groups - within Europe?

The finding here is that Germans and Serbs differ in the association between a haplotype in the MAPT gene and Parkinson's disease. Previous studies had shown different associations within this gene with PD between Norwegians and Greeks. Here they look at whether there's a difference along a similar North vs. South European geographical spectrum - Germans and Serbs - a much narrower spectrum, at that.
One annoying thing about this paper is their use of the term "ethnical".
It's surprising to me that they find this difference between groups that are geographically so close, and I'm not too sure how to interpret their statement that their power is 80%.

Role of ethnicity on the association of MAPT H1 haplotypes and subhaplotypes in Parkinson's disease

Susan Winkler, Inke R König, Katja Lohmann-Hedrich, Peter Vieregge, Vladimir Kostic and Christine Klein

European Journal of Human Genetics (2007) 15, 1163–1168

Abstract: An association of the H1 haplotype and subhaplotypes in the microtubule-associated protein Tau (MAPT) gene with Parkinson's disease (PD) has been reported. To further evaluate their role in PD, we genotyped a sample set of 765 cases and controls consisting of two large European subgroups of German (n=418) and Serbian (n=347) origin for the MAPT haplotypes H1 and H2. The H1/H1 carriers were tested for three additional MAPT polymorphisms. In the Serbian sample, there was significant evidence (P=0.0108) of an association of the H1/H1 genotype and PD. Surprisingly, in the German sample, we did not find significant differences in genotype or haplotype frequencies between patients and controls. These results suggest that the role of H1 haplotypes in the etiology of PD may be ethnically dependent.

Recent revisions regarding how the genome works

Via TAMU Anthropology in the News, I found this article from the Washington Post by David Brown called How Science is Rewriting the Book on Genes that gives an update on why things that were once thought to be rules in genetics are turning out not to be so cut and dry. Many of these are pretty well known.

• A gene can code for many proteins, not just one, through alternative splicing

• The regulation of genes might contribute more than previously thought to evolutionary change than the actual content of the genes:

"Nearly 1 in 10 (genes) code for transcription factors, proteins that help turn genes on and off at the right time."

He discusses conserved, non-coding elements and says this:

"A study in the journal Science in August found that these elements are less tolerant of mutation than protein-coding genes. That means they are more likely to be identical among people, mice, fruit flies and worms than are the genes coding for proteins. It turns out that more of evolution's survival-of-the-fittest battles occurred in writing the instruction manual for running the genes than in designing the genes themselves."

However, as a side note, there was another recent study (see here) that found little effect of removing ultraconserved non-coding elements from mice, in that it did not visibly or immediately affect their viability, suggesting as the authors put it "...that extreme sequence constraint does not necessarily reflect crucial functions required for viability"

• Synonymous mutations are not as inconsequential as previously thought (see here)

• There is a premium placed on an organisms being able to quickly and efficiently mitigate the effects of an unpredictable environment:

"When a cell is translating a piece of mRNA into a protein, it stops when it reaches a three-nucleotide segment called a termination codon that causes the just-built protein chain to separate from the construction machinery -- like a car rolling off the assembly line. It now turns out that the mRNA instructions for a few proteins have a termination codon in the middle of the chain, not just at the end.

The protein-building machinery can sometimes "read through" this instruction and complete the protein. (How it does that is complicated and only partially understood). But most of the time, construction just stops. The half-finished protein is broken down, and all the effort goes for naught.

Why would an organism have an assembly line that builds a product partway and then tears it up time after time? This may be another strategy that allows the body to handle certain problems at a moment's notice."

I guess the bottom line here is that we're making slow progress towards understanding the genome,... or that "the more we know, the less we know".

"Racial" Self Classification, African genetic ancestry, and GST polymorphisms

First, using about 40 AIMs (ancestry informative markers) and the STRUCTURE program, they come up with AF, EU, and NA admixture proportions. They look at how these proportions differ based on self-classification (White, Black, Intermediate). They also type some GST polymorphisms. These are known to be pharmacologically important in that they encode the phase 2 drug metabolizing enzymes, and are known to differ in frequency between populations.

Most interestingly, when they analyze the association of AF ancestry (ACA) and the different polymorphisms they find a threshold effect for some of them:

This approach disclosed significant associations of the GSTM1-null and the GSTM3*B polymorphisms with the proportion in African ancestry, throughout the range of ACAs observed in the study population (0.13–0.95). Importantly, a threshold proportion of the African component of ancestry was detected at approximately 0.4, above which the frequency of the polymorphisms shows a monotonic dependence on the ACA. This range encompasses 61% of the overall population sample, representing 87.5% of Blacks, 70.3% of Intermediates but only 8.8% of self-identified Whites.

I wish they would have discussed or interpreted this finding a bit more.

Self-reported skin color, genomic ancestry and the distribution of GST polymorphisms.

Suarez-Kurtz G, Vargens DD, Struchiner CJ, Bastos-Rodrigues L, Pena SD.

Pharmacogenet Genomics. 2007 Sep;17(9):765-71.

Background and objective: Skin color and self-reported ethnicity have systematically been used in the pharmacogenetic/-genomic literature as phenotypic proxies for geographical ancestry. Population admixture, however, challenges the appropriateness of this approach. We compared the effectiveness of color-based and marker-based biogeographical ancestry classifications in typing polymorphisms in GSTM1, GSTM3 and GSTT1 in the heterogeneous Brazilian population.

Methods: Individual DNA from 335 healthy Brazilians was typed for a set of insertion/deletion polymorphisms, previously validated as ancestry informative markers. GSTM1-null and GSTT1-null polymorphisms were detected by multiplex PCR and the GSTM3*B polymorphism by restriction-fragment length polymorphism. Nonlinear logistic regression modeling was developed to describe the association between the GST polymorphisms and ancestry estimated by the ancestry informative markers.

Results: Analysis of the ancestry informative markers data with the Structure software revealed the existence of only two significant clusters, one of which was inferred to be an estimate of the African component of ancestry. Nonlinear logistic regression showed that the odds of having the GSTM1-null genotype decreases (P less than 0.0004, Wald statistics), whereas the odds of having the GSTM3*B allele increases (P less than 0.0001) with the increase of the African component of ancestry, throughout the range (0.13-0.95) observed in the population sample. The African component of ancestry proportion was not associated with GSTT1-null frequency. Within the self-reported Black and Intermediate groups, there were significant differences in ancestry informative markers between GSTM1-null and non-null individuals, and between carriers and noncarriers of the GSTM3*B allele.

Conclusions: Interethnic admixture is a source of cryptic population structure that may lead to spurious genotype-phenotype associations in pharmacogenetic/-genomic studies. Logistic regression modeling of GST polymorphisms shows that admixture must be dealt with as a continuous variable, rather than proportioned in arbitrary subcategories for the convenience of data quantification and analysis.

Out of Africa with or without assimilation?

This one finds more evidence for Out of Africa, with replacement and no funny business. This debate seems endless, but it is interesting. I'd have to say that the overall picture of the evidence so far points mostly to Out of Africa with little to very little assimilation. The scenario presented in this paper seems a bit extreme, but nonetheless important to consider.

Statistical evaluation of alternative models of human evolution

Nelson J. R. Fagundes, Nicolas Ray, Mark Beaumont, Samuel Neuenschwander, Francisco M. Salzano, Sandro L. Bonatto, and Laurent Excoffier

PNAS Published online before print October 31, 2007

Abstract: An appropriate model of recent human evolution is not only important to understand our own history, but it is necessary to disentangle the effects of demography and selection on genome diversity. Although most genetic data support the view that our species originated recently in Africa, it is still unclear if it completely replaced former members of the Homo genus, or if some interbreeding occurred during its range expansion. Several scenarios of modern human evolution have been proposed on the basis of molecular and paleontological data, but their likelihood has never been statistically assessed. Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. A Bayesian analysis of the data under this best supported model points to an origin of our species 141 thousand years ago (Kya), an exit out-of-Africa 51 Kya, and a recent colonization of the Americas 10.5 Kya. We also find that the African replacement model explains not only the shallow ancestry of mtDNA or Y-chromosomes but also the occurrence of deep lineages at some autosomal loci, which has been formerly interpreted as a sign of interbreeding with Homo erectus.

ACTN3 in West vs. East African Athletes

It's nice to see negative results like this one published. Some studies have found associations between this ACTN3 allele and endurance vs. sprint performance (here), but only Europeans have been looked at so far (although I thought they did a study on Kenyans before). We also know that the "endurance" version of this allele (X) is at a higher frequency outside of Africa (here). In this study they look for an association between West African controls vs. "sprint" athletes and Kenyan and Ethiopian controls vs. endurance athletes.

the discussion is short and sweet, and they offer some alternative scenarios (abstract is further below):

The X allele has been observed in all human populations tested so far. The lowest X allele frequencies occur in Kenyan, Nigerian and South African populations (8-11%), resulting in approximately 1% XX genotype frequency. Australian Caucasian and Spanish with European origin, Japanese in northeast Asia, and Javanese in southeast Asia have the highest frequencies of the X allele (44-54%), resulting in XX genotype frequencies from 18 to 25%. The X allele frequencies in the Japanese and Javanese populations are higher than 50%. Papua New Guinea highlanders and Aboriginal Australians display intermediate X allele frequencies (29-36%), resulting in XX genotype frequencies of 10-15% (11).

This study does not support the hypothesis that the ACTN3 null X allele contributes to the success of the East African endurance runners relative to their source populations. In addition, the extremely low XX genotype frequency in the Nigerian control population (0% in this study) rules out the possibility of detecting a lower frequency of the XX genotype in Nigerian power athletes.

There are several possible explanations for the discrepancy between these results and previously published associations seen in athletes of European descent. The low baseline allele frequency of 577X in the three surveyed African populations reduces the effective power of our study, potentially obscuring any genetic association with performance. Alternately, it is possible that the effect of ACTN3 genotype on muscle performance is dependent on other genetic influences, or on environmental variables, that differ between African and non-African populations. For example, many East Africans are subject to environmental influences, such as living and training at altitude and high levels of incidental running during childhood, which play major roles in shaping athletes from this region (12,15) and differ substantially from the childhood experiences of most potential non-African athletes. Such factors may reduce the impact of [alpha]-actinin-3 deficiency on the muscle performance of African individuals.

In conclusion, the results of this study extend our knowledge of the distribution of the 577X null allele of the ACTN3 gene to three previously unexamined African populations. We have shown that the frequency of the 577X allele is substantially lower in Kenyan and Nigerian populations than in any non-African population sampled to date, and it is similar to that seen previously in a South African Bantu-speaking cohort (Table 1) (7). The 577X allele frequency seen in the Ethiopian group is substantially higher, probably reflecting population admixture with non-African groups. We have found no evidence for an association between the R577X polymorphism and endurance performance in East African athletes. The absence of 577XX ([alpha]-actinin-3 deficiency) in controls and athletes from Nigeria would mask any association between the presence of [alpha]-actinin-3 and sprint/power performance. Our data suggest that [alpha]-actinin-3 deficiency is not a major influence on performance in African athletes.

The ACTN3 R577X Polymorphism in East and West African Athletes

YANG, NAN; MACARTHUR, DANIEL G.; WOLDE, BEZABHE; ONYWERA, VINCENT O.; BOIT, MICHAEL K.; LAU, SAU YIN MARY-ANN; WILSON, RICHARD H.; SCOTT, ROBERT A.; PITSILADIS, YANNIS P.; NORTH, KATHRYN

Medicine & Science in Sports & Exercise. 39(11):1985-1988, November 2007.

Purpose: To determine the frequency of the ACTN3 R577X polymorphism (functional R allele and nonfunctional X allele) in a variety of African populations and to examine its influence on the success of elite East African endurance runners and West African sprinters.

Methods: The R577X polymorphism was genotyped in 198 Ethiopian controls and 76 elite Ethiopian endurance athletes, 158 Kenyan controls and 284 elite Kenyan endurance runners, and 60 Nigerian controls and 62 elite Nigerian power athletes. Statistical analyses were performed by exact tests of population differentiation, using Arlequin, version 3. Analyses were carried out using 1 × 10⁶ Markov chain steps, and 1 × 10⁵ dememorization steps.

Results: The frequency of the X allele was extremely low among Kenyans and Nigerians (~1% homozygosity) and higher in Ethiopians (~11% homozygosity). The low baseline frequencies of the three populations tested mean that any associations with sprint performance would likely be obscured. In Ethiopians, where baseline levels of 577XX were about 11%, there was no increased frequency in the endurance athletes.

Conclusion: Our data suggest that [alpha]-actinin-3 deficiency is not a major influence on performance in African athletes.

---

PNG population genetics

First some background on the populations in PNG and the surrounding area:

The island of New Guinea is interesting for studying human genetic history because it was occupied by anatomically modern humans as long as 35–40,000 years ago (Groube et al. 1986; Pavlides and Gosden 1994; Leavesley et al. 2002; Specht 2005) representing part of the first expansion of modern humans out of Africa. Melanesia (used here as geographic term comprising mainland New Guinea and surrounding islands in the north and east, also referred to as Near Oceania together with most of the Solomon islands) is inhabited today by speakers of 2 kinds of languages. Austronesian-speaking groups have a common ancestral language, Proto-Austronesian, and mostly live on islands around New Guinea as well as on the northeast and southeast coasts of the New Guinea mainland. Non-Austronesian (=Papuan)–speaking groups lack a (recent) common ancestry and include numerous linguistically unrelated groups. Papuan speakers dominate the New Guinea mainland, living inland from Austronesian speakers where such are present, and are also found in a few places around the islands north, northeast, and east of mainland New Guinea where their languages have persisted to modern times (Wurm and Hattori 1981; Specht 2005). These 2 groups of people have a different history in Melanesia: non-Austronesian–speaking groups reflecting the ebb and flow of language that emerged out of the Pleistocene language geography, whereas Austronesian speakers arrived as migrants from East Asia not earlier than 3,500 years ago (Kirch 1997).

What is the Trans-New Guinea hypothesis?

The genetic history of the New Guinea area prior to the arrival of Austronesian speakers has only recently begun to receive attention. The Trans-New Guinea (TNG) hypothesis proposes a very large family of languages mostly spoken along the central cordillera of New Guinea and in some regions north and south of the cordillera, with outliers in the Timor area of Island Southeast Asia. The TNG hypothesis implies an expansion of people speaking TNG languages started about 6,000–7,000 (perhaps as early as 10,000) years ago in the central highlands of what is now Papua New Guinea (PNG), most likely in connection with the expansion of agriculture, and spread both eastwards and westwards (Pawley 1998; Denham et al. 2003; Pawley 2005)

What they conlcude:

It is likely that the expansion of TNG speakers starting from the highlands of what is now PNG about 6,000–7,000 (perhaps as early as 10,000) years ago, presumably in association with the expansion of agriculture, had a great impact on shaping New Guinean Y-chromosome diversity as seen today.

and

We propose that sex-biased differences in the social structure and cultural heritage of the people involved in the 2 different expansions played an important role (among other factors) in shaping the New Guinean Y-chromosome landscape.

I wish I had more time to look at this paper more closely, because it seems to highlight both the genetic and cultural aspects of population dynamics.

Patterns of Y-Chromosome Diversity Intersect with the Trans-New Guinea Hypothesis

Stefano Mona, Mila Tommaseo-Ponzetta, Silke Brauer, Herawati Sudoyo, Sangkot Marzuki and Manfred Kayser

Molecular Biology and Evolution 2007 24(11):2546-2555

The island of New Guinea received part of the first human expansion out of Africa (>40,000 years ago), but its human genetic history remains poorly understood. In this study, we examined Y-chromosome diversity in 162 samples from the Bird's Head region of northwest New Guinea (NWNG) and compared the results with previously obtained data from other parts of the island. NWNG harbors a high level of cultural and linguistic diversity and is inhabited by non-Austronesian (i.e., Papuan)–speaking groups as well as harboring most of West New Guinea's (WNG) Austronesian-speaking groups. However, 97.5% of its Y-chromosomes belong to 5 haplogroups that originated in Melanesia; hence, the Y-chromosome diversity of NWNG (and, according to available data, of New Guinea as a whole) essentially reflects a local history. The remaining 2.5% belong to 2 haplogroups (O-M119 and O-M122) of East Asian origin, which were brought to New Guinea by Austronesian-speaking migrants around 3,500 years ago. Thus, the Austronesian expansion had only a small impact on shaping Y-chromosome diversity in NWNG, although the linguistic impact of this expansion to this region was much higher. In contrast, the expansion of Trans-New Guinea (TNG) speakers (non-Austronesian) starting about 6,000–10,000 years ago from the central highlands of what is now Papua New Guinea, presumably in combination with the expansion of agriculture, played a more important role in determining the Y-chromosome diversity of New Guinea. In particular, we identified 2 haplogroups (M-P34 and K-M254) as suggestive markers for the TNG expansion, whereas 2 other haplogroups (C-M38 and K-M9) most likely reflect the earlier local Y-chromosome diversity. We propose that sex-biased differences in the social structure and cultural heritage of the people involved in the Austronesian and the TNG expansions played an important role (among other factors) in shaping the New Guinean Y-chromosome landscape.

OCA2 and eye color

OCA2 and other genes have previously been implicated in eye color (here, here, and a new paper that I haven't blogged on yet) Here, they look at more variants in OCA2 and are able to predict eye color from a "modest number of SNPs in the gene."

Multilocus OCA2 genotypes specify human iris colors

Tony Frudakis, Timothy Terravainen and Matthew Thomas

Human Genetics Volume 122, Numbers 3-4 / November, 2007

Human iris color is a quantitative, multifactorial phenotype that exhibits quasi-Mendelian inheritance. Recent studies have shown that OCA2 polymorphism underlies most of the natural variability in human iris pigmentation but to date, only a few associated polymorphisms in this gene have been described. Herein, we describe an iris color score (C) for quantifying iris melanin content in-silico and undertake a more detailed survey of the OCA2 locus (n = 271 SNPs). In 1,317 subjects, we confirmed six previously described associations and identified another 27 strongly associated with C that were not explained by continental population stratification (OR 1.5–17.9, P = 0.03 to less than 0.001). Haplotype analysis with respect to these 33 SNPs revealed six haplotype blocks and 11 hap-tags within these blocks. To identify genetic features for best-predicting iris color, we selected sets of SNPs by parsing P values among possible combinations and identified four discontinuous and non-overlapping sets across the LD blocks (p-Selected SNP sets). In a second, partially overlapping sample of 1,072, samples with matching diplotypes comprised of these p-Selected OCA2 SNPs exhibited a rate of C concordance of 96.3% (n = 82), which was significantly greater than that obtained from randomly selected samples (62.6%, n = 246, P less than 0.0001). In contrast, the rate of C concordance using diplotypes comprised of the 11 identified hap-tags was only 83.7%, and that obtained using diplotypes comprised of all 33 SNPs organized as contiguous sets along the locus (defined by the LD block structure) was only 93.3%. These results confirm that OCA2 is the major human iris color gene and suggest that using an empirical database-driven system, genotypes from a modest number of SNPs within this gene can be used to accurately predict iris melanin content from DNA.

Recombination hotspot variation across populations

They find some interesting and strong population differences in recombination rates, but don't really give any clues as to any possible explanations other than:

Differences in recombination rates and presence or absence of hotspots may follow a more complex pattern related to the genetic diversity among humans due to their evolutionary history and its impact on the DNA sequences, that may be at the base of differences in recombination rates.

Variation in estimated recombination rates across human populations

Jan Graffelman, David J. Balding, Anna Gonzalez-Neira and Jaume Bertranpetit

Human Genetics Volume 122, Numbers 3-4 / November, 2007

Abstract: Recently it has been reported that recombination hotspots appear to be highly variable between humans and chimpanzees, and there is evidence for between-person variability in hotspots, and evolutionary transience. To understand the nature of variation in human recombination rates, it is important to describe patterns of variability across populations. Direct measurement of recombination rates remains infeasible on a large scale, and population-genetic approaches can be imprecise, and are affected by demographic history. Reports to date have suggested broad similarity in recombination rates at large genomic scales and across human populations. Here, we examine recombination rate estimates at a finer population and genomic scale: 28 worldwide populations and 107 SNPs in a 1 Mb stretch of chromosome 22q. We employ analysis of variance of recombination rate estimates, corrected for differences in effective population size using genome-wide microsatellite mutation rate estimates. We find substantial variation in fine-scale rates between populations, but reduced variation within continental groups. All effects examined (SNP-pair, region, population and interactions) were highly significant. Adjustment for effective population size made little difference to the conclusions. Observed hotspots tended to be conserved across populations, albeit at varying intensities. This holds particularly for populations from the same region, and also to a considerable degree across geographical regions. However, some hotspots appear to be population-specific. Several results from studies on the population history of humans are in accordance with our analysis. Our results suggest that between-population variation in DNA sequences may underly recombination rate variation.

EDAR and thick hair in East Asians

Razib picked up on a news story in Science about a study finding an association between hair thickness and alleles of EDAR. They did this in Southeast Asia where there was some variation in hair thickness.
East Asians have hair fibers that are 30% larger than that of Africans and 50% larger than that of Europeans. I guess the publication will show up later.

Ten rules for doing your best research

PLoS likes these top ten lists. Here's one from PLoS Computational Biology, that is taken from mathematician Richard Hamming's talk some 20 years ago. I don't really understand Rule 1 (it may apply in the 80s, but not so much anymore?). Rule #3 is very interesting. Beyond that, rules # 4, 7, and 10, are my favorites.

Rule 1: Drop Modesty

To quote Hamming: “Say to yourself: ‘Yes, I would like to do first-class work.' Our society frowns on people who set out to do really good work. But you should say to yourself: ‘Yes, I would like to do something significant.'”

Rule 2: Prepare Your Mind

Many think that great science is the result of good luck, but luck is nothing but the marriage of opportunity and preparation. Hamming cites Pasteur's adage that “luck favours the prepared mind.”

Rule 3: Age Is Important

Einstein did things very early, and all the “quantum mechanic fellows,” as well as most mathematicians and astrophysicists, were, as Hamming notes, “disgustingly young” when they did their best work. On the other hand, in the fields of music, politics, and literature, the protagonists often produce what we consider their best work late in life.

Rule 4: Brains Are Not Enough, You Also Need Courage

Great scientists have more than just brainpower. To again cite Hamming: “Once you get your courage up and believe that you can do important things, then you can. If you think you can't, almost surely you are not going to. Great scientists will go forward under incredible circumstances; they think and continue to think.”

Rule 5: Make the Best of Your Working Conditions

To paraphrase Hamming, what most people think are the best working conditions clearly are not, because people are often most productive when working conditions are bad. One of the better times of the Cambridge Physical Laboratories was when they worked practically in shacks—they did some of the best physics ever. By turning the problem around a bit, great scientists often transform an apparent defect into an asset. “It is a poor workman who blames his tools—the good man gets on with the job, given what he's got, and gets the best answer he can.”

Rule 6: Work Hard and Effectively

Most great scientists have tremendous drive, and most of us would be surprised how much we would know if we worked as hard as some great scientists did for many years. As Hamming says: “Knowledge and productivity are like compound interest. Given two people with exactly the same ability, the one person who manages day in and day out to get in one more hour of thinking will be tremendously more productive over a lifetime.” But, Hamming notes, hard work alone is not enough—it must be applied sensibly.

Rule 7: Believe and Doubt Your Hypothesis at the Same Time

Great scientists tolerate ambiguity. They believe the theory enough to go ahead; they doubt it enough to notice the errors and faults so they can step forward and create the new replacement theory. As Hamming says: “When you find apparent flaws, you've got to be sensitive and keep track of those things, and keep an eye out for how they can be explained or how the theory can be changed to fit them. Those are often the great scientific contributions.”

Rule 8: Work on the Important Problems in Your Field

It is surprising but true that the average scientist spends almost all his time working on problems that he believes not to be important and not to be likely to lead to important results. By contrast, those seeking to do great work must ask: “What are the important problems of my field? What important problems am I working on?” Hamming again: “It's that simple. If you want to do great work, you clearly must work on important problems. . . . I finally adopted what I called ‘Great Thoughts Time.' When I went to lunch Friday noon, I would only discuss great thoughts after that. By great thoughts I mean ones like: ‘What will be the impact of computers on science and how can I change it?'”

Rule 9: Be Committed to Your Problem

Scientists who are not fully committed to their problem seldom produce first-class work. To a large extent, creativity comes out of the subconscious. If you are deeply immersed in and committed to a topic, day after day, your subconscious has nothing to do but work on your problem. Hamming says it best: “So the way to manage yourself is that when you have a real important problem you don't let anything else get the center of your attention—you keep your thoughts on the problem. Keep your subconscious starved so it has to work on your problem, so you can sleep peacefully and get the answer in the morning, free.”

Rule 10: Leave Your Door Open

Keeping the door to your office closed makes you more productive in the short term. But ten years later, somehow you may not quite know what problems are worth working on, and all the hard work you do will be “sort of tangential” in importance. He (or she) who leaves the door open gets all kinds of interruptions, but he (or she) also occasionally gets clues as to what the world is and what might be important. Again, Hamming deserves to be quoted verbatim: “There is a pretty good correlation between those who work with the doors open and those who ultimately do important things, although people who work with doors closed often work harder. Somehow they seem to work on slightly the wrong thing—not much, but enough that they miss fame.”

In our view, Rule 10 may be the key to getting the best research done because it will help you to obey Rules 1–9, and, most importantly, it will foster group creativity [9]. A discussion over lunch with your colleagues is often worth much more than a trip to the library. However, when choosing your lunchmates (and, by implication, your institution), be on your toes. As Hamming says: “When you talk to other people, you want to get rid of those sound absorbers who are nice people but merely say ‘Oh yes,' and to find those who will stimulate you right back.”