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Update: Please do not take the labels below (e.g., “Baloch”) as literal ancestral elements. The most informative way to read them is that they indicate populations where this element is common, and, the relationship of proportions can tell us something. The literal proportion does not usually tell us much.

End Update

I was browsing the Harappa results, and two new things jumped out at me. Zack now has enough St. Thomas Christian samples from Kerala that I think we need to accept as the likely model that this community does not derive from the Brahmins of Kerala, as some of them claim. Their genetic profile is rather like many non-Brahmin South Indians, except the Nair, who have a peculiar attested history with the Brahmins of their region.

But that’s not the really interesting finding. Below is a table I constructed from Zack’s data.

Ethnicity Language S.Indian Baloch Caucasian NE.Euro
Karnataka Brahmin Dravidian 47% 38% 4% 6%
Karnataka Hebbar Iyengar Brahmin Dravidian 49% 36% 5% 5%
Karnataka Iyengar Dravidian 48% 39% 3% 5%
Karnataka Iyengar Brahmin Dravidian 48% 37% 3% 7%
Karnataka Kannada Brahmin Dravidian 51% 35% 3% 5%
Karnataka Konkani Brahmin Dravidian 47% 37% 2% 6%
Kerala Brahmin Dravidian 43% 39% 4% 6%
Tamil Brahmin Dravidian 46% 40% 3% 6%
Tamil Brahmin Dravidian 47% 40% 3% 5%
Tamil Brahmin Dravidian 48% 39% 9% 4%
Tamil Brahmin Dravidian 47% 38% 6% 4%
Tamil Brahmin Dravidian 48% 37% 6% 5%
Tamil Brahmin Dravidian 48% 37% 3% 5%
Tamil Brahmin Dravidian 48% 35% 5% 6%
Tamil Brahmin Iyengar Dravidian 47% 38% 6% 4%
Tamil Brahmin Iyengar Dravidian 47% 35% 6% 6%
Tamil Brahmin Iyengar Dravidian 50% 35% 2% 8%
Tamil Brahmin iyer/iyengar Dravidian 48% 38% 2% 5%
Tamil Brahmin iyer/iyengar Dravidian 48% 38% 4% 5%
Tamil Brahmin iyer/iyengar Dravidian 47% 37% 2% 5%
Tamil Brahmin iyer/iyengar Dravidian 47% 37% 6% 8%
Bengali Brahmin IE 43% 35% 4% 10%
Bengali Brahmin IE 45% 35% 2% 11%
Bengali Brahmin IE 44% 35% 5% 11%
Bihari Brahmin IE 39% 38% 5% 11%
Maharashtra/Madhya Pradesh Saraswat Brahmin IE 47% 39% 1% 6%
Mahrashtrian Desastha Brahmin IE 46% 38% 8% 5%
Oriya Brahmin IE 47% 36% 0% 9%
Punjabi Brahmin IE 33% 41% 13% 10%
Punjabi Brahmin IE 35% 40% 8% 11%
Rajasthani Brahmin IE 32% 38% 9% 15%
Sindhi Pushtikar/Pushkarna Brahmin IE 31% 36% 12% 10%
UP Brahmin IE 37% 38% 2% 14%
UP Brahmin IE 41% 37% 7% 11%

I was curious about the distribution of the “Northeast European” component in South Asia. This element is almost entirely lacking in non-Brahmin South Indians (except for the Nair), but, it is present in non-Brahmin Indo-European speaking Indians, including Biharis and Bengalis. And interestingly, it is present in the same rough fraction in North Indian and South Indian Brahmins regardless of locale, ~5 percent in the former case, and ~10-15 percent in the latter. I initially divided them into two language classes, but noticed that the Maharashtra samples were more like the South Indians.

Then I remembered something random: there is a tradition dividing Indian’s Brahmin communities in two, on a north-south split. The above partition does not perfectly reflect the oral history and custom, but it is very close. The Brahmins of South India are a particularly homogeneous lot. I’d bet that their diversity is a function of cultural evolution and adaptation to local circumstances, not disparate origins. Rather, they derive from some initial migration from a specific North Indian Brahmin community, and then admixed somewhat with another South Indian population (explaining their profiles being closer to the Southern average than that of Northern Brahmins).

Finally, most readers will be aware that I broadly accept the outline in Reconstructing Indian History. But, I do think there were multiple waves of northwest population intrusions into South Asia. In particular, I think the demographically preponderant wave was probably West Asian, while a later group brought some Eastern European ancestry into the mix as well. I think this explains nicely the fact that North Indian Brahmins have a “South Indian” cline but not a Northeast European cline (compare Bengali Brahmins to Punjabi Brahmins, and you’ll see what I mean). One possible model is that a very rapid sweep of an Indo-European speaking population may have occurred across the North Indian plain, overlain upon a local set of populations which had an ANI-ASI cline. The Genographic Project reportedly is going to present results which suggest that the Indian caste system pre-dates the arrival of the Aryans. That would comport well with this model, where earlier groups of northwesterners established a caste-like system, which the Aryans, who later formed the core of the twice-born castes, simply suited to their own needs upon arrival. If you look at Zack’s results using public data sets a very low proportion of “Northeastern European,” equivalent to what you see in South India, is found in a few groups:

- The Dravidian Brahui and Baloch

- Tribes and Dalits

- Austro-Asiatic populations

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Anthropology, India, Indian 
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The term “BRICs” gets thrown around a lot these days. At least it gets thrown around by people who perceive themselves to be savvy and worldly. In case you aren’t savvy and worldly, BRICs just means Brazil, Russia, India and China. The huge rising economies of the past generation, and next generation. Here’s a summary from Wikipedia:

The BRIC thesis recognizes that Brazil, Russia, India and China…have changed their political systems to embrace global capitalism. Goldman Sachs predicts that China and India, respectively, will become the dominant global suppliers of manufactured goods and services, while Brazil and Russia will become similarly dominant as suppliers of raw materials. It should be noted that of the four countries, Brazil remains the only nation that has the capacity to continue all elements, meaning manufacturing, services, and resource supplying simultaneously. Cooperation is thus hypothesized to be a logical next step among the BRICs because Brazil and Russia together form the logical commodity suppliers to India and China. Thus, the BRICs have the potential to form a powerful economic bloc to the exclusion of the modern-day states currently of “Group of Eight” status. Brazil is dominant in soy and iron ore while Russia has enormous supplies of oil and natural gas. Goldman Sachs’ thesis thus documents how commodities, work, technology, and companies have diffused outward from the United States across the world.

But there are big quantitative differences between these nations as well. Below the fold are some charts which I think illustrate those differences.

(Republished from Discover/GNXP by permission of author or representative)
 
• Category: Science • Tags: Brazil, BRICs, China, Data Analysis, Indian, Russia 
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price_fig1I have put up a few posts warning readers to be careful of confusing PCA plots with real genetic variation. PCA plots are just ways to capture variation in large data sets and extract out the independent dimensions. Its great at detecting population substructure because the largest components of variation often track between population differences, which consist of sets of correlated allele frequencies. Remeber that PCA plots usually are constructed from the two largest dimensions of variation, so they will be drawn from just these correlated allele frequency differences between populations which emerge from historical separation and evolutionary events. Observe that African Americans are distributed along an axis between Europeans and West Africans. Since we know that these are the two parental populations this makes total sense; the between population differences (e.g., SLC24A5 and Duffy) are the raw material from which independent dimensions can pop out. But on a finer scale one has to be cautious because the distribution of elements on the plot as a function of principal components is sensitive to the variation you input to generate the dimensions in the first place.

I can give you a concrete example: me. I showed you my 23andMe ancestry painting yesterday. I didn’t show you my position on the HGDP data set because I’ve shared genes with others and I don’t want to take the step of displaying other peoples’ genetic data, even if at a remove. But, I have reedited some “demo” screenshots and placed where I am on the plot to illustrate what I’m talking about above. The first shot is my position on the two-dimensional plot of first and second principal components of genetic variation from the HGDP data set.


gsa-lillymendel-worldNo surprise that I’m in the Central/South Asian cluster. But what may surprise you is that I’m not in the South Asian cluster, I’m in the Central Asian cluster. In the Central Asian cluster are Uyghurs and Hazaras. These are two hybrid populations, a mixture of West and East Eurasian elements. The Uyghurs are likely the outcome of a process of admixture between the Iranian and Tocharian Indo-European populations of the cities of the Tarim basin, and later Turkic speaking settlers who arrived in the wake of the expansion and later collapse of the first Uyghur Empire (the historical connection between the current Uyghurs and ancient Uyghurs is tenuous at best, and complicated). The Hazaras are a more recent population, likely emerging as the product of intermarriages between Mongol soldiers who arrived in the 13th century, and indigenous women, Persians, Turks, and assorted Indo-Iranian groups between the Zagros and Khyber Pass. It is somewhat ironic that I’m on the edge of the Hazara cluster since they are almost certainly in part descended from Genghis Khan’s family, and my own surname is Khan. But I know that my Y chromosomal lineage is R1a1, very common across Central and Southern Eurasia, and not a Mongolian one at all.

23andmepcazoomZoom! Now we’ve constrained the input data set to the Central/South Asian groups. First, look at the Kalash. They’re strange, which is no surprise, they’re an inbred mountain group in Pakistan who have not adopted Islam. The Pakistani Taliban looks to be ending them as we speak. I really would prefer that they were just thrown out of the data set for this zoom view, because on this fine grained scale I don’t think they add much at all. They’re just an example of what long term endogamy can do to your allele frequencies. The bigger picture is the axis between the populations of Pakistan, and those of Central Asia. Observe that I’ve changed position. Whereas when taking world wide genetic variation into account I clustered with Central Asians, now I’m 2/3 of the way to the South Asian cluster. I will tell you that I’ve shared “genes” with around 50 South Asians now, from various parts of the subcontinent, and in the 23andMe plot they overlay the South Asians nearly perfectly. I’ve put labels at the approximate ethno-linguistic position. I’m an outlier. 23andMe tells me that I’m 43% “East Asian.” The typical South Asian is in the 10-30% range. My first assumption was that I have a lot of ancient South Indian, which just shows up as East Asian in their algorithm. With this in mind I tried sharing with a lot of South and East Indians, and found out two interesting points. First, South Indians seem no higher than 30-35% East Asian. Bengalis on the other hand are more East Asian, with Bangladeshis more East Asian than West Bengalis. My sample size for Bengalis is small, so take that with caution. Second, the PCA plots put the South Indians firmly in the South Asian cluster, but the Bengalis trail out toward my own position. This indicates again that different methods are telling you slightly different things. The PCA is only a thin slice of variation, but it’s highly informative of between population differences. A Bengali and a South Indian with the same “East Asian” fraction in the ancestry painting nevertheless have consistently different positions on the PCA, with Bengalis closer to the East Asians. Additionally, there’s an ethnic Persian in this zoom plot that I’m describing, and they are positioned near the Balochi. But on the world wide plot they’re on the margins of the European cluster. Another illustration that position of an element is sensitive to the input data because of how the dimensions are generated.

Blaine Bettinger, who inspired me to post this, told a story with his ancestry painting which was plausible. What can I say? First, I have less than 1% African ancestry. This could be noise. But, I do observe that the South Asians with Muslim names are enriched in the set of those who I’ve shared genes with and who have less than 1%, but not 0%, African ancestry. Just as Muslim South Asians have non-trivial West Asian ancestry, I suspect that many of us have Sub-Saharan African ancestry through the same dynamic. Sub-Saharan African soldiers were prominent across South Asia with the arrival of Muslims. Bengal even has a period of rule by Abyssinian rulers. But the bigger issue for me is the East Asian component. Here is a figure from a paper published 4 years ago:

journal.pgen.0020215.g005

The figure is showing Fst value comparing Indian Americans with Europeans and East Asians. Fst measures between population differences in allele frequency, in this case the alleles being 207 indels. Take a look at the Bengalis. These are West Bengalis, who I believe have a lesser East Asian component, but even there the allele frequency difference to East Asians is near that of Europeans. The Assamese, who speak a language very close to Bengali, are similar. Assam was ruled by a Tibeto-Burman people for nearly 600 years. The Oriya speakers, from the southwest of Bengal, are more distant from East Asians. As one goes south and east, and west and north, the distance from East Asians increases. This shouldn’t be that surprising, but nice to confirm. The fact that the genetic distance increases as one goes south means that for northeast South Asia you need to complexify the model from a two-way admixture with “ancient North Indians” and “ancient South Indians.” Set next to these two is an East Asian element, which is also clear in the Indo-Aryan peoples of Nepal.

Sheikh Hasina, Khaleda ZiaOf course anyone who knows Bengalis won’t be totally surprised by an East Asian component to their ancestry. To the left are head shots of the two women who have dominated Bangladeshi politics for the past two decades, Khaleda Zia and Sheik Hasina. They’re both Bengalis, but they do look different, and I know many people who look like one or the other (or a combination). My family is from one of most easternmost districts of Bengali, next to Tripura. In fact my late maternal grandmother lived in Tripura for some of her childhood (she was almost trampled to death by the Maharani of Tripura’s insane elephant as a young girl!). When I was a young child I once saw a black and white photo from my father’s college days, and I was curious who the Asiatic looking young man in the middle of the photograph was. Turns out it was my father! Sometimes our expectations affect how we perceive people. I have never perceived my father to have an Asian cast to his features as a more mature man, but others have told me that he does still exhibit them.

There is still the question of how Bengalis came to have this particular admixture. I think the most plausible scenario probably synthesizes conventional village-to-village intermarriage and isolation-by-distance, along with some component of migrationism. Tribes such as the Chakma have left Burma in historical time. The Chakma of Bangladesh now speak a dialect of Bengali, not their ancestral Sino-Tibetan tongue. I believe that a non-trivial portion of Bengalis have ancestors who were tribal people who shifted their religious identity to that of Hinduism or Islam (from Theravada Buddhism in the case of the Chakma, or animism in the case of the Garos before their Christianization). But eastern South Asia is adjacent to mainland Southeast Asia, and it stands to reason that continuous gene flow would over time would also have introduced East Asian alleles into the Bengali gene pool.

Image Credit: TopNews.in

(Republished from Discover/GNXP by permission of author or representative)
 
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Razib Khan
About Razib Khan

"I have degrees in biology and biochemistry, a passion for genetics, history, and philosophy, and shrimp is my favorite food. If you want to know more, see the links at http://www.razib.com"