ADMIXTURE on African HapMap populations

Here is the result of running ADMIXTURE on the three African HapMap-3 populations, using about 440K SNPs, including Tuscans as a non-African group.

The Tuscans are in purple and show no trace of African admixture. All the other populations are separated: red: Luhya (Bantu); green: Maasai (Nilotes); Yoruba (Niger-Congo).

The two east African groups show asymmetrical affinities: the Maasai have some Luhya red, while the Luhya have little Maasai green, while they have substantial West African turqoise, consistent with the origin of their Bantu language.

Related: ADMIXTURE on HapMap-3 populations

Utah Whites vs. Tuscans with 1.5 millions SNPs

This time I took the full ~1.5M SNPs and ran ADMIXTURE on two HapMap-3 European populations, CEU Utah Whites and Tuscan Italians. I sorted the individuals based on their ancestral proportions, but still the cutoff is quite obvious, and the separation is perfect.

CEU belong to the blue cluster with 93.7%, and TSI in the red one with 94.9%.

The most red Utah White has 31.4% "southern" ancestry, while the most blue Tuscan has 21.2% "northern" ancestry. Thus, the cutoff "jump" between the two populations, at the middle of the figure, is 47.4%.

The standard deviation of the "southern" component among CEU individuals is 6.9%, and the standard deviation of the "northern" component among Tuscans is 5.7%.

How real is this "admixture"?

As I have mentioned before in the blog, apparent "mixedness" between populations decreases as the number of markers increases. Thus, the question arises: is the apparent "admixture" between Tuscans and Utahns a real effect of individuals diverging toward a population other than their own, or an artefact of a limited number of markers?

We should note that increasing the number of markers has diminishing returns: most new markers are in linkage disequilibrium with existing markers, and hence provide little additional information: going from 10 to 110 markers has a huge effect, but going from 1000 to 1100 a trivial one.

To study this question I took a 1/5 random sample of the markers, or about 300K SNPs and repeated the ADMIXTURE run:

Now, CEU are 93.9% in the blue cluster (vs. 93.7% in the 1.5M run) and the variance of the red component in CEU individuals is 6.8% (vs. 6.9% in the 1.5M run).

Tuscans are 94.0% in the red cluster (vs. 94.9% in the 1.5M run) and the variance of the blue component in TSI individuals is 6.5% (vs. 5.7% in the 1.5M run).

The conclusion is obvious that the 5-fold increase in markers from 300K to 1.5M had no noticeable effect in the apparent mixedness of populations and individuals.

ADMIXTURE in the New World

Here is the result of running ADMIXTURE on ~450K markers on six HapMap-3 populations; left-to-right: African Americans from the Southwest (ASW), Utah Whites (CEU), Beijing Chinese (CHB), Mexicans from Los Angeles (MEX), Toscans (TSI), and Yoruban from Nigeria (YRI).

Here are the admixture proportions (in %):

It is obvious, however, from the ADMIXTURE plot above, and the triangle plots below (for ASW and MEX), that the admixture is not uniformly distributed.

Notice the two African American individuals with substantial Amerindian admixture (14 and 29%), while the rest are a simple 2-way mix of Europeans and Sub-Saharans with minor Amerindian admixture in some of them. The standard deviation of European admixture is 8.3%, lower than in Mexicans.

Mexicans are variable in terms of their European-Amerindian mix, but with less variable tiny Sub-Saharan component (0.6% with a standard deviation of 1.2%). This is probably due to the fact that blacks were absorbed earlier in Mexico, while European-Amerindian social stratification and continued European immigration has fueled the retention of considerable variation. European admixture in Mexicans is 27.7% on average, but with a standard deviation of 24.0% and minimum/maximum value of 0.0 to 90.5% in the sample I am considering.

Eva Longoria, for example, who recently learned that she is 70% European in "Faces of America" belongs to the top-5% of Mexican American "European-ness", although there is probably considerable variation of Mexican Americans within the country.

ADMIXTURE on HapMap 3 populations

Here is the result of running ADMIXTURE on about ~50K markers from the HapMap 3 populations. I'll annotate the final K=9 run; the rest are given at the end:

I list the distinctive colors for the populations, Left-to-Right. The minor components are easy enough to pick up and as expected:

ASW (A): African ancestry in Southwest USA [Sub-Saharan blue]

CEU (C): Utah residents with Northern and Western European ancestry from the CEPH collection [European yellow]

CHB (H): Han Chinese in Beijing, China [East Asian orange]
CHD (D): Chinese in Metropolitan Denver, Colorado [East Asian orange]

GIH (G): Gujarati Indians in Houston, Texas [South Asian purple]

JPT (J): Japanese in Tokyo, Japan [East Asian light green]

LWK (L): Luhya in Webuye, Kenya [East African bright green]

MEX (M): Mexican ancestry in Los Angeles, California [Amerindian pink]

MKK (K): Maasai in Kinyawa, Kenya [East African light blue]

TSI (T): Tuscan in Italy [European yellow]

YRI (Y): Yoruban in Ibadan, Nigeria (West Africa) [Sub-Saharan blue]

The rest of the runs for K=3 to K=8 are below:

K=3: Notice: Asian red+Caucasoid blue on Gujarati Indians and Mexicans. At this level of resolution, these two populations look similar. Notice presence of blue in East Africans but not Yorubans (green at the end).

K=4: East Africans get their own (yellow) cluster. Notice the diminution of the Sub-Saharan (purple) element, relative to the previous figure. This is due to the fact that the East African element is intermediate between Caucasoids and Sub-Saharans and "eats up" the other two elements, although residual Caucasoid red and Sub-Saharan purple remains. The tripartite origin of Mexicans is especially visible in this plot, with components being in order of European, East Eurasian, Sub-Saharan.
K=5: Gujarati Indians now get their own (purple) cluster. Here the difference between Luhya (mostly Sub-Saharan blue + East African yellow) and Maasai (the reverse) is quite striking. The former are Bantu speakers and thus not indigenous to east Africa.
K=6: Mexicans get their own cluster (blue) reflecting their Amerindian, rather than East Asian ancestry which could not be resolved in the previous figures.
K=7: the Luhya get their own cluster, splitting off from the Maasai. There are now 3 components in Africa centered on Yorubans (light blue), Luhya (very light green) and Maasai (red).
K=8: A low-frequency element appears in Maasai that is hard to interpret; it is preserved in the next and final K=9 run (shown at the beginning of the post), in which the Japanese and Chinese are split off.

Eurasian ADMIXTURE (a precursor to Eurasian-DNA-Calc?)

(Last Update: Oct 8; K=7 added)

I took the 540,814 markers from the HGDP dataset that are also included in the 23andMe personal genomics test, and that have less than 1% no-call rate.

I ran ADMIXTURE on all the West- (and some mainly Caucasoid Central-) Eurasian populations, including Yoruba and Han Chinese to account for non-Caucasoid admixture in parts of Eurasia.

The populations are (left-to-right): Tuscan, North Italian, Sardinian, French, French Basque, Orcadian, Russian, Adygei, Palestinian, Bedouin, Druze, Mozabite, Pathan, Sindhi, Balochi, Brahui, Burusho, Yoruba, Han Chinese.

Here are the admixture proportions corresponding to this experiment:

This seems like a good starting point for the new EURASIAN-DNA-CALC I have in the works.

Relative to the existing EURO-DNA-CALC, doubling the number of ancestral populations (from 3 to 6), and increasing the number of SNPs (by 3 orders of magnitude) introduces some obvious computational problems. I have some ideas on how to resolve them, so stay tuned.

APPENDIX

For the sake of completeness here are the ADMIXTURE runs for K=3 to K=5.

At K=3, the three major races (Caucasoid: green, Mongoloid: red, Negroid: blue) emerge.

At K=4, the Caucasoids are split into West Eurasians (red) and Central Asians (purple)
At K=5, the West Eurasians are split into Europeans (yellow) and West Asians (blue)

PS: I will probably do some ADMIXTURE runs for K=7 and higher in the next few days; the results will be posted in this blog post as an update.

UPDATE (K=7)

The Druze get their own cluster (pink) with an average membership of 65.4% of Druze individuals

Y chromosomes of Vlax Roma

From the paper:

The Gypsies arrived in Europe 900–1100 years ago, when they first appeared in the Balkans. The present-day Gypsy population groups in Europe are the compound product of the early migrations from the Balkans into Europe [1]. The Gypsies came to Hungary from the Balkans in two large migrations. The Carpathian Romanies arrived in the 15th century and the Vlax Romanies came in the 19th century. The Carpathian Gypsies speak Hungarian and the Vlax Romanies speak Hungarian and Romani languages.

Interesting:

A median-joining (MJ) network of haplogroup H1a-M82 has demonstrated the sharing of identical Indian specific Y-chromosomal lineages between all Romani populations including Malaysian Indians as well as the Vlax Romanies (Fig. 2A and B). This common lineage of haplogroup H1a-M82 represents a common descent from a single ancestor providing a strong genetic link to the ancestral geographical origin of the proto-Gypsies [1]. According to Sengupta et al. [24] the age of microsatellite variation within haplogroup H1 in Indian populations is more than 9.7 +/- 4.4 ky. This time was estimated to be 992 years (95%CI 425–3472) in the Romani populations investigated by Gresham et al. [1] suggesting the Indian H1 haplogroup is the ancestral one.

Gresham et al. (pdf) used the genealogical mutation rate. Hence, the discrepancy between the Sengupta et al. age estimates and their own is partly due to the choice of mutation rate. Nonetheless, it's obvious that the Balkan H1 is still 3 times younger than the Indian one, and obviously of South Asian origin. Notice also how the Gresham et al. paper gives a large confidence interval for its estimate, in agreement with my observations about the inadequacy of a limited number of Y-STRs, and Y-STRs in general to couple tightly with historical events.

Nonetheless, if one uses an order-of-magnitude approach, the Gresham et al. estimate is quite compatible with historical knowledge about the arrival of Gypsy founders to the Balkans, just as was the case for Serbian Roma.

The ~1ky estimate for Balkan Gypsy H1 is similar to the ~1ky estimate for the updated J1 Cohen Modal Haplotype. For reasons explained in that post, this is probably an overestimate, and I can envision a scenario according to which the tribal descendants of an H1-man who lived in the 1st millennium AD made their way to Europe at the turn of the millennium, proliferating into the Gypsy communities of today.

Related:

• Y-chromosome study of Serbian Roma
• Y chromosomes of Iberian Gypsies
• Y chromosomes of Bayash Romani
• Y-chromosomes of Albanian populations (Ferri et al. 2010)

Forensic Science International: Genetics doi:10.1016/j.fsigen.2010.08.017

Paternal genetic history of the Vlax Roma

Andrea Zalán et al.

Romanies constitute the largest minority group belonging to different subgroups in Hungary. Vlax Romanies are one of these Romani subgroups. The Gypsies came to Hungary from the Balkans in two large migrations. The Carpathian Romanies arrived in the 15th century and the Vlax Romanies came in the 19th century. The Carpathian Gypsies speak Hungarian and the Vlax Romanies speak Hungarian and Romani languages.
Only a limited number of genetic studies of Y-chromosomal haplotypes/haplogroups have been done before, moreover most studies did not contain information regarding the investigated Roma populations which subgroups belong to.
In the present study, we analyzed a wide set of Y-chromosomal markers to do comparable studies of the Vlax Roma in eastern Hungarian regions. The results can be compared in the context of previously published data on other Romani groups, Indian and Hungarian reference populations.
Haplogroups H1a-M82 and J2a2-M67 were most common in the investigated population groups. A median-joining network of haplogroup H1a-M82 has demonstrated the sharing of identical Indian specific Y-chromosomal lineages between all Romani populations including Malaysian Indians as well as the Vlax Romanies. This common lineage of haplogroup H1a-M82 represents a common descent from a single ancestor provides a strong genetic link to the ancestral geographical origin of the proto-Gypsies.
The detected haplogroups in the Vlax Romani population groups can be classified into two different Y-chromosomal lineages based on their putative origin. These lineages include ancestral Indian (H1a-M82), present-day Eurasian (J2a2-M67, J2*-M172, E1b1b1a-M78, I1-M253, R1a1-M198 and R1b1-P25) Y-chromosome lineages. Presence of these lineages in the paternal gene pool of the Roma people is illustrative of the Gypsy migration route from India through the Balkan to the Carpathian Basin.

PopAffiliator: estimating origin with forensic autosomal STRs

Anders Pålsen alerts me to PopAffiliator, a neat little tool that guesses the origin of a sample from one of several major population groups:

The STR collection database used to train and evaluate the machine learning model encompasses data gathered from more than 40 different studies and contains a total of 56,222 individuals, distributed by 7 major geographical locations: East Asia, Eurasia, sub-Saharan Africa, North Africa, Near East, Central-South America and North America. The data is available here.

The tool uses 17 forensic autosomal STR markers. This may seem like too little in this day and age, but it is sufficient for the purpose at hand.

A few years ago someone had posted at the dna-forums site -I can't seem to find the topic today- a STRUCTURE-based calculator on mostly the same markers. That calculator contained 500 German/500 Chinese/500 African individuals:

• Group 3=Africans
• Group 2=Chinese
• Group 1=Germans

Back then, I ran STRUCTURE on the data yielding the following results:

1: 0.041 0.025 0.934 500
2: 0.949 0.012 0.039 500
3: 0.019 0.955 0.026 500

If we look at the 1,500 individuals, it turns out that correct "guess" of a person's origin (i.e., his maximum inferred cluster membership coefficient corresponding to the real one) occurred in 497/500 Africans, 491/500 Chinese, and 490/500 Germans.

Pretty good! Typing hundreds of thousands of SNPs to guess if someone is East Asian, European, or Sub-Saharan African is overkill, and there is already widespread forensic profiling of numerous human populations, so why not amortize all this data?

The problem with using so few numbers isn't that they are insufficient to guess one's origin, but that they are insufficient to estimate admixture, if present. Here is the triangle plot from my aforementioned mini-experiment:

If hundreds of thousands of SNPs had been used, the red, green, and blue dots would be gathered in tight clusters in the three corners, with the occasional individual deviating in a different direction. Nonetheless it's also clear that very few individuals deviate beyond the 50% cutoff from their true origin, which might fool one into assigning them to the wrong population.

Since I have some autosomal test data of my own, I decided to give PopAffiliator a try.

The link to PopAffiliator will go to the right sidebar of the blog.

INTERNATIONAL JOURNAL OF LEGAL MEDICINE
DOI: 10.1007/s00414-010-0472-2

PopAffiliator: online calculator for individual affiliation to a major population group based on 17 autosomal short tandem repeat genotype profile

Luísa Pereira et al.

Because of their sensitivity and high level of discrimination, short tandem repeat (STR) maker systems are currently the method of choice in routine forensic casework and data banking, usually in multiplexes up to 15–17 loci. Constraints related to sample amount and quality, frequently encountered in forensic casework, will not allow to change this picture in the near future, notwithstanding the technological developments. In this study, we present a free online calculator named PopAffiliator (http://cracs.fc.up.pt/popaffiliator) for individual population affiliation in the three main population groups, Eurasian, East Asian and sub-Saharan African, based on genotype profiles for the common set of STRs used in forensics. This calculator performs affiliation based on a model constructed using machine learning techniques. The model was constructed using a data set of approximately fifteen thousand individuals collected for this work. The accuracy of individual population affiliation is approximately 86%, showing that the common set of STRs routinely used in forensics provide a considerable amount of information for population assignment, in addition to being excellent for individual identification.

Link

French cattle in global genomic context

The congruence of cattle breeds with inferred clusters is remarkable. K=47 frappe analysis is probably testing the limits of human visual perception...

PLoS ONE 5(9): e13038. doi:10.1371/journal.pone.0013038

Insights into the Genetic History of French Cattle from Dense SNP Data on 47 Worldwide Breeds

Mathieu Gautier et al.

Abstract
Background
Modern cattle originate from populations of the wild extinct aurochs through a few domestication events which occurred about 8,000 years ago. Newly domesticated populations subsequently spread worldwide following breeder migration routes. The resulting complex historical origins associated with both natural and artificial selection have led to the differentiation of numerous different cattle breeds displaying a broad phenotypic variety over a short period of time.

Methodology/Principal Findings
This study gives a detailed assessment of cattle genetic diversity based on 1,121 individuals sampled in 47 populations from different parts of the world (with a special focus on French cattle) genotyped for 44,706 autosomal SNPs. The analyzed data set consisted of new genotypes for 296 individuals representing 14 French cattle breeds which were combined to those available from three previously published studies. After characterizing SNP polymorphism in the different populations, we performed a detailed analysis of genetic structure at both the individual and population levels. We further searched for spatial patterns of genetic diversity among 23 European populations, most of them being of French origin, under the recently developed spatial Principal Component analysis framework.

Conclusions/Significance
Overall, such high throughput genotyping data confirmed a clear partitioning of the cattle genetic diversity into distinct breeds. In addition, patterns of differentiation among the three main groups of populations—the African taurine, the European taurine and zebus—may provide some additional support for three distinct domestication centres. Finally, among the European cattle breeds investigated, spatial patterns of genetic diversity were found in good agreement with the two main migration routes towards France, initially postulated based on archeological evidence.

Link

Turks to destroy the archaeological site of Allianoi

Ancient Roman spa awaits flooding in Turkey

By Nicolas Cheviron (AFP) – 15 hours ago

ALLIANOI, Turkey [correct: occupied Asia Minor] — Under a mild autumn sun, workers bustle about like bees at a Roman bath complex sprawling over a green plain in western Turkey in what looks like a regular excavation site.

But the fate awaiting the impressive ancient spa of Allianoi is dark: the workers here are tasked with burying the site and not digging it out to reveal its secrets.

Much to the consternation of archaeologists and civic bodies, the Turkish government has said it will go ahead with flooding the valley the site sits in to serve as a dam reservoir with a capacity to irrigate 8,000 hectares (19,760 acres) of farmland.

The work now underway is an effort to preserve the complex for future generations, before officials allow water to accumulate in the reservoir for the Yorganli dam before the end of the year.

As archaeologists -- denied entry to the site -- mourn the loss of a significant treasure, workers dump wheelbarrows of sand over the foundations of the hospital of Galen, a prominent Roman physician born in the 2nd century AD in the nearby city of Pergamon, or modern-day Bergama.

Soon the thermal bath -- with its five metre-high (17 feet-high) walls and a pool still powered by a hot spring -- will disappear under the sand, after being covered with a pinkish protective coating, along with buildings looking out over a columned courtyard, rooms covered with mosaics and paved walkways.

It is a sad sight for Professor Ahmet Yaras who excavated Allianoi for nine years and who says 80 percent of the site has yet to see the daylight.

"Normally, cultural treasures need to be examined and registered before any action is taken on a site. Here, flooding the site before the excavation is complete is a massacre," lamented the archaeologist.

"There is no other warm bath, health center in the world as well preserved as this... Unfortunately, all this will be abandoned forever," he said.

Furthermore, Yasar expressed doubt that the sand will be enough to preserve the site under 30 metres of water.

"Even if the site were protected, the sedimentation brought by the dam will reach 15 or 16 meters in 50 years time. It would be crazy to try to excavate the complex again at such a depth," he added.

But the fate of the site is not much of a concern for the farmers at the nearby village, who see the Yorganli dam -- completed in 2007 -- as the answer to their irrigation problems.

"They exaggerate, I do not think there is much of the ancient there. It is just a hot spring," said Mehmet Aydin, 52, who grows cotton, tomatoes and corn on his plot.

His remarks almost echo the views of Environment Minister Veysel Eroglu who said in late August: "Allianoi does not exist, it is an invention... There is just a hot spring like many others across Turkey."

His remarks were roundly criticized while the International Council on Monuments and Sites (ICOMOS), the European non-governmental preservation organization Europa Nostra and archaeologists from the European Union urged the Turkish government in a letter to preserve the "common [correct: Greco-Roman] heritage" at Allianoi.

But the game seems to be over: Culture Minister Ertugrul Gunay quashed hope of saving Allianoi last week when he dismissed the idea of questioning the local archaeological commission's decision in late August to bury the site for preservation.

"After all, Allianoi remained underground for a long time and it surfaced only during drilling works," he said.

Some ADMIXURE estimates on Eurafricans

Here is an ADMIXTURE run on the Xing et al. (2010) dataset using markers with less than 1% genotyping no-calls. Populations (left-to-right) are: Alur, Hema, Luhya (from Africa), and CEU, Tuscan, Slovenian, Urkarah, and Kurdish (from Western Eurasia).

Most West Eurasians have no trace of Sub-Saharan ancestry, except Kurds (estimated here at 2.3% overall, range: 1-3.6%), and a couple of Slovenians (4.5% and 1.6%, overall 0.2%). The fairly uniform distribution in Kurds suggests to me that this is an ancient phenomenon reflecting gene flow between the Near East and Africa and not a recent phenomenon.

The Hema are an African population exhibiting West Eurasian affinities (11.0%, range: 4.2-15.2%). Consult my comments on the original Xing et al. article on some information on these Nilo-Saharan pastoralists from the Democratic Republic of Congo.

Collective intelligence in groups

The press release has more info. Not sure why the proportion of women resulted in higher "collective intelligence". The authors suggest that it is because of women's higher "social sensitivity". Personally, I think it may be because men (and women) tend to try to impress members of the opposite sex for obvious evolutionary reasons.

Science DOI: 10.1126/science.1193147

Evidence for a Collective Intelligence Factor in the Performance of Human Groups

Anita Williams Woolley et al.

Psychologists have repeatedly shown that a single statistical factor—often called "general intelligence"— emerges from the correlations among people's performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of "collective intelligence" exists for groups of people. In two studies with 699 individuals, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group's performance on a wide variety of tasks. This "c factor" is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group.

Link

More ADMIXTURE estimates in Eurasia

This time, I removed SNPs with more than 1% genotyping no-call from the Xing et al. (2010) dataset, and ran ADMIXTURE on the following populations (left-to-right): Slovenian, Kyrgyzstani, Buryat, and HapMap Chinese. For K=2:

The results are as expected, with Slovenians and Chinese forming opposite poles, and Kyrgyzstanis and Buryat showing a preponderence of Mongoloid ancestry, but with variable Caucasoid admixture. Notice a single Slovenian showing eastern influence.

For K=3:

The Buryat get their own cluster (blue). Some Chinese are seen as having "Buryat" influence, which makes sense as there have been incursion of Mongols into China in historical times. Some Buryat too seem to be "Chinese"-influenced.

Kyrgyzstanis show mixed affiliations. The presence of both a Buryat and a "Chinese" cluster is interesting. The Kyrgyz live at a lower latitude than the Buryat, so this may be a reason behind the "Chinese" cluster, while the Buryat are a more purely northern Mongoloid population.

Notice too, how the lone Slovenian becomes "blue" indicating Mongol rather than Chinese origins. This also makes sense as the Chinese people did not migrate to Europe, while Mongoloids of the steppe and forest zones did.

Interesting is also the emergence of a 2-3 Buryat with some "European" admixture. These may not stem from the centuries old mix between Sakas and Mongols, but may represent a more recent (e.g., Slavic) European element.

Y-chromosomes of Filipino Negritos and non-Negritos

European Journal of Human Genetics (29 September 2010) | doi:10.1038/ejhg.2010.162

The Y-chromosome landscape of the Philippines: extensive heterogeneity and varying genetic affinities of Negrito and non-Negrito groups

Frederick Delfin et al.


The Philippines exhibits a rich diversity of people, languages, and culture, including so-called ‘Negrito’ groups that have for long fascinated anthropologists, yet little is known about their genetic diversity. We report here, a survey of Y-chromosome variation in 390 individuals from 16 Filipino ethnolinguistic groups, including six Negrito groups, from across the archipelago. We find extreme diversity in the Y-chromosome lineages of Filipino groups with heterogeneity seen in both Negrito and non-Negrito groups, which does not support a simple dichotomy of Filipino groups as Negrito vs non-Negrito. Filipino non-recombining region of the human Y chromosome lineages reflect a chronology that extends from after the initial colonization of the Asia-Pacific region, to the time frame of the Austronesian expansion. Filipino groups appear to have diverse genetic affinities with different populations in the Asia-Pacific region. In particular, some Negrito groups are associated with indigenous Australians, with a potential time for the association ranging from the initial colonization of the region to more recent (after colonization) times. Overall, our results indicate extensive heterogeneity contributing to a complex genetic history for Filipino groups, with varying roles for migrations from outside the Philippines, genetic drift, and admixture among neighboring groups.

Link

Preferred vs. actual mate body shape

PLoS ONE 5(9): e13010. doi:10.1371/journal.pone.0013010

From Preferred to Actual Mate Characteristics: The Case of Human Body Shape

Alexandre Courtiol et al.

The way individuals pair to produce reproductive units is a major factor determining evolution. This process is complex because it is determined not only by individual mating preferences, but also by numerous other factors such as competition between mates. Consequently, preferred and actual characteristics of mates obtained should differ, but this has rarely been addressed. We simultaneously measured mating preferences for stature, body mass, and body mass index, and recorded corresponding actual partner's characteristics for 116 human couples from France. Results show that preferred and actual partner's characteristics differ for male judges, but not for females. In addition, while the correlation between all preferred and actual partner's characteristics appeared to be weak for female judges, it was strong for males: while men prefer women slimmer than their actual partner, those who prefer the slimmest women also have partners who are slimmer than average. This study therefore suggests that the influences of preferences on pair formation can be sex-specific. It also illustrates that this process can lead to unexpected results on the real influences of mating preferences: traits considered as highly influencing attractiveness do not necessarily have a strong influence on the actual pairing, the reverse being also possible.

Link

Hundreds of variants influence human height

From the press release:

An international team of researchers, including a number from the University of North Carolina at Chapel Hill schools of medicine and public health, have discovered hundreds of genes that influence human height.

Their findings confirm that the combination of a large number of genes in any given individual, rather than a simple "tall" gene or "short" gene, helps to determine a person's stature. It also points the way to future studies exploring how these genes combine into biological pathways to impact human growth.

"While we haven't explained all of the heritability of height with this study, we have confidence that these genes play a role in height and now can begin to learn about the pathways in which these genes play a role," said study coauthor Karen L. Mohlke, PhD, associate professor of genetics in the UNC School of Medicine.

...

"These investigators had once been competing with each other to find height genes, but then realized that the next step was to combine their samples and see what else could be found," said Mohlke. "The competitors became collaborators to achieve a common scientific goal."

Large-scale collaborations like this are awesome: people get less credit in a paper with hundreds of co-authors, but they are part of something worthwhile. Plus, it's nice to see a table of authors' different contributions listed in the supplementary material :)

Nature doi:10.1038/nature09410

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Hana Lango Allen et al.

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2, 3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P less than 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Link

Bronze Age Mediterraneans may have visited Stonehenge

A DNA test on the "Boy with the Amber necklace" would be interesting.

Bronze Age Mediterraneans may have visited Stonehenge

The links between the Stonehenge area and the Mediterranean have been debated for years. Recent research by the British Geological Survey (BGS) suggests people came from both the snow of the Alps and the heat of the Mediterranean to visit Stonehenge.

However, scientific studies show that some of the people buried in the area during the Bronze Age were not local.

The analysis of the teeth from two males provides new evidence that one, dubbed ‘the Boy with the Amber necklace’, had come from the Mediterranean area, whilst the previously known ‘Amesbury Archer’ had come from the Alps.

...

The new evidence shows that ‘the Boy with the Amber necklace’ spent his childhood in a warm climate typical of Iberia or the Mediterranean. Such warm oxygen values are theoretically possible in the British Isles but are only found on the extreme west coast of South West England, western Ireland and the Outer Hebrides. These areas can be excluded as likely childhood origins of his on the basis of the strontium isotope composition of his teeth

...

‘The Boy with the Amber necklace’, whose grave was found on Boscombe Down, about 3 km south-east of Stonehenge, is from a more recent time — the end of the Early Bronze Age. His skeleton has been radiocarbon dated to around 1550 BC (dated by Wessex Archaeology). Aged 14–15 years when he died, he was buried wearing a necklace of around 90 amber beads.