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July 15, 2018

India vs. China, genetically diverse vs. homogeneous

Filed under: China,China genetics,Human Population Genetics,India,India Genetics — Razib Khan @ 1:50 pm

About 36% of the world’s population are citizens of the Peoples’ Republic of China and the Republic of India. Including the other nations of South Asia (Pakistan, Bangladesh, etc.), 43% of the population lives in China and/or South Asia.

But, as David Reich mentions in Who We Are and How We Got Here China is dominated by one ethnicity, the Han, while India is a constellation of ethnicities. And this is reflected in the genetics. The relatively diversity of India stands in contrast to the homogeneity of China.

At the current time, the best research on population genetic variation within China is probably the preprint A comprehensive map of genetic variation in the world’s largest ethnic group – Han Chinese. The author used low-coverage sequencing of over 10,000 women to get a huge sample size of variation all across China. The PCA analysis recapitulated earlier work. Genetic relatedness among the Han of China is geographically structured. The largest component of variance is north-south, but a smaller component is also east-west. The north-south element explains more than 4.5 times the variance as the east-west.

Click to enlarge

Another dimension of the of the variation is that different parts of China are character by different levels of admixture between the Han and other groups. In Northwest China, there is gene flow from West Eurasian sources. In all likelihood, this is through proxy populations, such as Mongols, who are about ~10% West Eurasian. Also, during the period between the fall of the Han Dynasty and the rise of the Sui-Tang Dynasty much of northern China was dominated by barbarian groups from the steppe, and these groups settled down and were absorbed. In Northeast China, the source of admixture is from Siberian and Tungusic group. Again, this makes geographical sense.

In contrast in South China, the gene flow is from indigenous Chinese national groups, such as Dai. This is in keeping with the historical record, whereby South China became Han in the period between 0 and 1000 AD through migration, intermarriage, and acculturation.

Click to enlarge

I have my own small private dataset of Chinese individuals. Some with provenance. Some without. But using known populations I was able to divide China along the north to south cline.  Individuals from Guangdong in the south, those from Shaanxi in the north, and from Zhejiang to Sichuan in the center.

Using Punjabis as a West Eurasian outgroup I was able to plot these individuals on a PCA. If you click to enlarge you will see that a substantial minority of the Han_N sample is shifted to the left of the plot. This is toward the Punjabis. This is not because they have Punjabi ancestry, but because Punjabis are reasonable proxies for West Eurasians.

Click to enlarge

More importantly, I want to compare South Asia to China. To do that I created a small dataset that merged the Han with representative South Asian groups. The first PC, 1 and 2, illustrate the contrast. All three Chinese groups, sampled from the north to the south, occupy a very tight cluster, while the South Asians span PC 2. The Bengalis are shifted a bit to the Chinese, but most of the variance is due to within-South Asian genetic differences.

Click to enlarge

I ran PCA to 10 dimensions. Only at PC 10 did the Han Chinese separate along the north-south access. Most of the earlier PC’s separated out specific castes (e.g, Patels because if their large number in the Gujurati sample were PC 3). Here are the eigenvalues: 53.0682, 2.5641, 2.31876
1.97058, 1.90652, 1.88879, 1.7935, 1.69375, 1.61516, and 1.54207. The large value for PC 1 is what you’d expect, it’s a continental scale difference. PC 2 differentiates South Asia from north to south. It’s much more modest. The other PCs get progressively smaller, but within the data, it’s clear that the continental size difference is the big one. The variance between north and south China is a small one in a South Asian scale.

Click to enlarge

Pairwise Fst is more ambiguous. That’s probably because most of the South Asian samples have structure within them. Merging them into one pooled population just confuses the issue.

Using a South Asian dataset where groups are disaggregated makes a lot more sense, and you see the structure between the different groups.

Click to enlarge

Running Treemix gives similar results. The South Asian groups exhibit a fan-shaped topology, where the Han cluster tightly together. Since I removed Bengalis from Treemix adding migration edges doesn’t do anything between the two clusters, so I omitted those results.

Click to enlarge

Finally, of course I ran some admixture analysis. Using South Asians + Han Chinese, I thought K = 4 would be reasonable. Even if you don’t enlarge, the results are straightforward: the Han Chinese have very little diversity in unsupervised mode. A small South Asian-like component, which has affinities with Punjabis, is found in northern Han. This confirms other results with other methods that the northern Han have some West Eurasian gene flow.  Some of the southern and central Han have an affinity with one of the South Indian clusters. I think is artifactual, due to deep structure within Eastern Eurasian populations and affinities between those groups that the Han absorbed as they moved south.

This post doesn’t really shed new light on anything we didn’t know. Rather, it’s just a review of what jumps out at anyone who works with genotype data: there is not very much genetic diversity in China and there is a great deal of genetic diversity in India. Why? These are not questions genetics can really answer directly, though it can give us clues and support certain models over others.

Anyone who has read much about Chinese history knows that the cultural ideal of meritocracy is deeply ingrained, even if it is honored in the breach quite often. Chinese civilizations has been characterized by the domination of extended pedigrees (e.g., the Xianbei-Han ruling faction among the Tang), but those pedigrees never become ethno-religious castes. The exception occurred during the Yuan (Mongol) period where Kublai Khan entered into a divide-and-rule policy. But that was a short period which had no longer term cultural consequences.

In contrast, South Asia is characterized by long-term endogamy. This is not surprising to anyone who knows anything about South Asian history. The genetic evidence suggests that modern jati-barriers emerged around ~2,000 years ago. Not only do South Asian groups differ a great deal in biogeographic ancestry (deep ancestry), but historical endogamy has resulted in further drift between these groups.

July 13, 2018

Tutorial to run supervised admixture analyses

Filed under: Admixture,Data Analysis,Population genetics — Razib Khan @ 11:03 pm
ID Dai Gujrati Lithuanians Sardinian Tamil
razib_23andMe 0.14 0.26 0.02 0.00 0.58
razib_ancestry 0.14 0.26 0.02 0.00 0.58
razib_ftdna 0.14 0.26 0.02 0.00 0.57
razib_daughter 0.05 0.14 0.29 0.18 0.34
razib_son 0.07 0.17 0.28 0.19 0.30
razib_son_2 0.06 0.19 0.29 0.19 0.27
razib_wife 0.00 0.07 0.55 0.38 0.00

This is a follow-up to my earlier post, Tutorial To Run PCA, Admixture, Treemix And Pairwise Fst In One Command. Hopefully you’ll be able to run supervised admixture analysis with less hassle after reading this.

The above results are from a supervised admixture analysis of my family and myself. The fact that there are three replicates of me is due to the fact that I converted my 23andMe, Ancestry, and Family Tree DNA raw data into plink files. Notice that the results are broadly consistent. This emphasizes that discrepancies between DTC companies in their results are due to their analytic pipeline, not because of data quality.

The results for my family are not surprising. I’m about ~14% “Dai”, reflecting East Asian admixture into Bengalis. My wife is ~0% “Dai”. My children are somewhere in between. At the low fraction you expect some variance in the F1.

Now below are results for three Swedes with the sample reference panel:

Group ID Dai Gujrati Lithuanians Sardinian Tamil
Sweden Sweden17 0.00 0.09 0.63 0.28 0.00
Sweden Sweden18 0.00 0.08 0.62 0.31 0.00
Sweden Sweden20 0.00 0.05 0.72 0.23 0.00

All these were run on supervised admixture frameworks where I used Dai, Gujrati, Lithuanians, Sardinians, and Tamils, as the reference “ancestral” populations. Another way to think about it is: taking the genetic variation of these input groups, what fractions does a given test focal individual shake out at?

The commands are rather simple. For my family:
bash rawFile_To_Supervised_Results.sh TestScript

For the Swedes:
bash supervisedTest.sh Sweden TestScript

The commands need to be run in a folder: ancestry_supervised/.

You can download the zip file.

Here is what the scripts do in two different situations. Imagine you have raw genotype files downloaded from 23andMe, Ancestry, and Family Tree DNA.

Download the files as usual. Rename them in an intelligible way, because the file names are going to be used for generating IDs. So above, I renamed them “razib_23andMe.txt” and such. Leave the extensions as they are. You need to make sure they are not compressed obviously. Then place them all in ancestry_supervised/RAWINPUT.

The script looks for the files in there. You don’t need to specify names, it will find them. In plink the family ID and individual ID will be taken from the text before the extension in the file name. Output files will also have the file name.

Aside from the raw genotype files, you need to determine a reference file. In REFERENCESFILES/ you see the binary pedigree/plink file Est1000HGDP. The same file from the earlier post. It would be crazy to run supervised admixture on the dozens of populations in this file. You need to create a subset.

For the above I did this:
grep "Dai|Guj|Lithua|Sardi|Tamil" Est1000HGDP.fam > ../keep.keep

Then:
./plink --bfile REFERENCEFILES/Est1000HGDP --keep keep.keep --make-bed --out REFERENCEFILES/TestScript

When the script runs, it converts the raw genotype files into plink files, puts them in INDIVPLINKFILES/. Then it takes each plink file and uses it as a test against the reference population file. That file has a preprend on group/family IDs of the form AA_Ref_. This is essential for the script to understand that this is a reference population. The .pop files are automatically generated, and the script inputs in the correct K by looking for unique population numbers.

The admixture is going to be slow. I recommend you modify runadmixture.pl by adding the number of cores parameters so it can go multi-threaded.

When the script is done it will put the results in RESULTFILES/. They will be .csv files with strange names (they will have the original filename you provided, but there are timestamps in there so that if you run the files with a different reference and such it won’t overwrite everything). Each individual is run separately and has a separate output file (a .csv).

But this is not always convenient. Sometimes you want to test a larger batch of individuals. Perhaps you want to use the reference file I provided? For the Swedes I did this:
grep "Swede" REFERENCEFILES/Est1000HGDP.fam > ../keep.keep

Then:
./plink --bfile REFERENCEFILES/Est1000HGDP --keep keep.keep --make-bed --out INDIVPLINKFILES/Sweden

Please note the folder. There are modifications you can make, but the script assumes that the test files inINDIVPLINKFILES/. The next part is important. The Swedish individuals will have AA_Ref_ preprended on each row since you got them out of Est1000HGDP. You need to remove this. If you don’t remove it, it won’t work. In my case, I modified using the vim editor:
vim Sweden.fam

You can do it with a text editor too. It doesn’t matter. Though it has to be the .fam file.

After the script is done, it will put the .csv file in RESULTFILES/. It will be a single .csv with multiple rows. Each individual is tested separately though, so what the script does is append each result to the file. If you have 100 individuals, it will take a long time. You may want to look in the .csv file as the individuals are being added to make sure it looks right.

The convenience of these scripts is that it does some merging/flipping/cleaning for you. And, it formats the output so you don’t have to.

I originally developed these scripts on a Mac, but to get it to work on Ubuntu I made a few small modifications. I don’t know if it still works on Mac, but you should be able to make the modifications if not. Remember for a Mac you will need the make versions of plink and admixture.

For supervised analysis, the reference populations need to make sense and be coherent. Please check the earlier tutorial and use the PCA functions to remove outliers.

July 12, 2018

Running your own analyses

Filed under: Genetics,Population genetics,Scripts — Razib Khan @ 8:25 am

For the technically inclined people here: Tutorial To Run PCA, Admixture, Treemix And Pairwise Fst In One Command.

The Insight show notes: episode 28, Violence & Warfare

Filed under: History,violence,War — Razib Khan @ 12:28 am
Scottish cavalry charging during the Battle of Waterloo

This week Razib and Spencer discussed violence and warfare on The Insight (iTunes, Stitcher and Google Play).

Spencer’s book, Pandora’s Seed, was mentioned. As was John Horgan’s The End of War and Steven Pinker’s The Better Angels of Our Nature. Both Jean-Jacques Rousseau and Thomas Hobbes were presented as giving opposite views of human nature and its relationship to conflict: the peaceful noble savage and the brute engaged in a war of all-against-all. Spencer expressed a sympathy with Rousseau’s views due to his earlier research as well as field work with indigenous people.

Transitions between various cultural stages were extensively discussed. From the Paleolithic to the Neolithic, to the Bronze Age and the Iron Age. Karl Jaspers’ idea of an Axial Age was introduced in the context for the transition from the Bronze Age to the Iron Age, and the fall of Mycenaean Greece and the rise of the Classical World.

The difference between the brutal warlike Bronze Age, defined by a charioteer, and the more genteel Iron Age, with the rise of ethical and religious prophets, was presented in the context of cultural evolution. The theorist Peter Turchin argues that rising violence due to more effective weapons may have resulted in the emergence of countervailing ideologies. In short, ideologies which favored peace evolved as social stabilizers in the face of war and inequality, which had been ramping up since the adoption of farming.

Spencer and Razib also talk about the biological corollaries and causes of war. Men are much more violent and warlike than women, especially young men. Some aspect of this is likely “hard-wired.”

But classical Malthusian theory familiar to anyone who has studied ecological carrying capacity was suggested to be the primary driver of war, as opposed to reflexive instinct or ideology. In Pandora’s Seed Spencer presented the thesis that increased conflict during the Neolithic was a consequence of Malthusian sedentarism, and the rapid rise of extremely of non-egalitarian societies (which today may include sex-biased societies with “bare branches”).

Finally, in the modern era was presented as one which has been defined by the decline of violence, mortality, and the development of a more peaceful lifestyle, and what that tells us about the potentialities of human nature.

Interested in learning where your ancestors came from? Check out Regional Ancestry by Insitome to discover various regional migration stories and more!


The Insight show notes: episode 28, Violence & Warfare was originally published in Insitome on Medium, where people are continuing the conversation by highlighting and responding to this story.

July 11, 2018

Tutorial to run PCA, Admixture, Treemix and pairwise Fst in one command

Filed under: Admixture,data,Fst,PCA,PLINK,Population genetics,TreeMix — Razib Khan @ 11:50 pm


Today on Twitter I stated that “if the average person knew how to run PCA with plink and visualize with R they wouldn’t need to ask me anything.” What I meant by this is that the average person often asks me “Razib, is population X closer to population Y than Z?” To answer this sort of question I dig through my datasets and run a few exploratory analyses, and get back to them.

I’ve been meaning to write up and distribute a “quickstart” for a while to help people do their own analyses. So here I go.

The audience of this post is probably two-fold:

  1. “Trainees” who are starting graduate school and want to dig in quickly into empirical data sets while they’re really getting a handle on things. This tutorial will probably suffice for a week. You should quickly move on to three population and four population tests, and Eigensoft and AdmixTools. As well fineStructure
  2. The larger audience is technically oriented readers who are not, and never will be, geneticists professionally. 

What do you need? First, you need to be able to work in a Linux or environment. I work both in Ubuntu and on a Mac, but this tutorial and these scripts were tested on Ubuntu. They should work OK on a Mac, but there may need to be some modifications on the bash scripts and such.

Assuming you have a Linux environment, you need to download this zip or tar.xz file. Once you open this file it should decompress a folderancestry/.

There are a bunch of files in there. Some of them are scripts I wrote. Some of them are output files that aren’t cleaned up. Some of them are packages that you’ve heard of. Of the latter:

  • admixture
  • plink
  • treemix

You can find these online too, though these versions should work out of the box on Ubuntu. If you have a Mac, you need the Mac versions. Just replace the Mac versions into the folderancestry/. You may need some libraries installed into Ubuntu too if you recompile yourselfs. Check the errors and make search engines your friends.

You will need to install R (or R Studio). If you are running Mac or Ubuntu on the command line you know how to get R. If not, Google it.

I also put some data in the file. In particular, a plink set of files Est1000HGDP. These are merged from the Estonian Biocentre, HGDP, and 1000 Genomes. There are 4,899 individuals in the data, with 135,000 high quality SNPs (very low missingness).

If you look in the “family” file you will see an important part of the structure. So do:

less Est1000HGDP.fam

You’ll see something like this:
Abhkasians abh154 0 0 1 -9
Abhkasians abh165 0 0 1 -9
Abkhazian abkhazian1_1m 0 0 2 -9
Abkhazian abkhazian5_1m 0 0 1 -9
Abkhazian abkhazian6_1m 0 0 1 -9
AfricanBarbados HG01879 0 0 0 -9
AfricanBarbados HG01880 0 0 0 -9

There are 4,899 rows corresponding to each individual. I have used the first column to label the ethnic/group identity. The second column is the individual ID. You can ignore the last 4 columns.

There is no way you want to analyze all the different ethnic groups. Usually, you want to look at a few. For that, you can use lots of commands, but what you need is a subset of the rows above. The grep command matches and returns rows with particular patterns. It’s handy. Let’s say I want just Yoruba, British (who are in the group GreatBritain), Gujurati, Han Chinese, and Druze. The command below will work (note that Han matches HanBeijing, Han_S, Han_N, etc.).

grep "Yoruba|Great|Guj|Han|Druze" Est1000HGDP.fam > keep.txt

The file keep.txt has the individuals you want. Now you put it through plink to generate a new file:

./plink --bfile Est1000HGDP --keep keep.txt --make-bed --out EstSubset

This new file has only 634 individuals. That’s more manageable. But more important is that there are far fewer groups for visualization and analysis.

As for that analysis, I have a Perl script with a bash script within it (and some system commands). Here is what they do:

1) they perform PCA to 10 dimensions
2) then they run admixture on the number of K clusters you want (unsupervised), and generate a .csv file you can look at
3) then I wrote a script to do pairwise Fst between populations, and output the data into a text file
4) finally, I create the input file necessary for the treemix package and then run treemix with the number of migrations you want

There are lots of parameters and specifications for these packages. You don’t get those unless you to edit the scripts or make them more extensible (I have versions that are more flexible but I think newbies will just get confused so I’m keeping it simple).

Assuming I create the plink file above, running the following commands mean that admixture does K = 2 and treemix does 1 migration edge (that is, -m 1). The PCA and pairwise Fst automatically runs.

perl pairwise.perl EstSubset 2 1

Just walk away from your box for a while. The admixture will take the longest. If you want to speed it up, figure out how many cores you have, and edit the file makecluster.sh, go to line 16 where you see admixture. If you have 4 cores, then type -j4 as a parameter. It will speed admixture up and hog all your cores.

There is as .csv that has the admixture output. EstSubset.admix.csv. If you open it you see something like this:
Druze HGDP00603 0.550210 0.449790
Druze HGDP00604 0.569070 0.430930
Druze HGDP00605 0.562854 0.437146
Druze HGDP00606 0.555205 0.444795
GreatBritain HG00096 0.598871 0.401129
GreatBritain HG00097 0.590040 0.409960
GreatBritain HG00099 0.592654 0.407346
GreatBritain HG00100 0.590847 0.409153

Column 1 will always be the group, column 2 the individual, and all subsequent columns will be the K’s. Since K = 2, there are two columns. Space separated. You should be able to open the .csv or process it however you want to process it.

You’ll also see two other files: plink.eigenval plink.eigenvec. These are generic output files for the PCA. The .eigenvec file has the individuals along with the values for each PC. The .eigenval file shows the magnitude of the dimension. It looks like this:
68.7974
38.4125
7.16859
3.3837
2.05858
1.85725
1.73196
1.63946
1.56449
1.53666

Basically, this means that PC 1 explains twice as much of the variance as PC 2. Beyond PC 4 it looks like they’re really bunched together. You can open up this file as a .csv and visualize it however you like. But I gave you an R script. It’s RPCA.R.

You need to install some packages. First, open R or R studio. If you want to go command line at the terminal, type R. Then type:
install.packages("ggplot2")
install.packages("reshape2")
install.packages("plyr")
install.packages("ape")
install.packages("igraph")
install.packages("ggplot2")

Once those packages are loaded you can use the script:
source("RPCA.R")

Then, to generate the plot at the top of this post:
plinkPCA()

There are some useful parameters in this function. The plot to the left adds some shape labels to highlight two populations. A third population I label by individual ID. This second is important if you want to do outlier pruning, since there are mislabels, or just plain outlier individuals, in a lot of data (including in this). I also zoomed in.

Here’s how I did that:
plinkPCA(subVec = c("Druze","GreatBritain"),labelPlot = c("Lithuanians"),xLim=c(-0.01,0.0125),yLim=c(0.05,0.062))

To look at stuff besides PC 1 and PC 2 you can do plinkPCA(PC=c("PC3","PC6")).

I put the PCA function in the script, but to remove individuals you will want to run the PCA manually:

./plink --bfile EstSubset --pca 10

You can remove individuals manually by creating a remove file. What I like to do though is something like this:
grep "randomID27 " EstSubset.fam >> remove.txt

The double-carat appends to the remove.txt file, so you can add individuals in the terminal in one window while running PCA and visualizing with R in the other (Eigensoft has an automatic outlier removal feature). Once you have the individuals you want to remove, then:

./plink --bfile EstSubset --remove remove.txt --make-bed --out EstSubset
./plink --bfile EstSubset --pca 10

Then visualize!

To make use of the pairwise Fst you need the fst.R script. If everything is set up right, all you need to do is type:
source("fst.R")

It will load the file and generate the tree. You can modify the script so you have an unrooted tree too.

The R script is what generates the FstMatrix.csv file, which has the matrix you know and love.

So now you have the PCA, Fst and admixture. What else? Well, there’s treemix.

I set the number of SNPs for the blocks to be 1000. So -k 1000. As well as global rearrangement. You can change the details in the perl script itself. Look to the bottom. I think the main utility of my script is that it generates the input files. The treemix package isn’t hard to run once you have those input files.

Also, as you know treemix comes with R plotting functions. So run treemix with however many migration edges (you can have 0), and then when the script is done, load R.

Then:
>source("src/plotting_funcs.R")
>plot_tree("TreeMix")

But actually, you don’t need to do the above. I added a script to generate a .png file with the treemix plot in pairwise.perl. It’s called TreeMix.TreeMix.Tree.png.

OK, so that’s it.

To review:

Download zip or tar.xz file. Decompress. All the packages and scripts should be in there, along with a pretty big dataset of modern populations. If you are on a non-Mac Linux you are good to go. If you are on a Mac, you need the Mac versions of admixture, plink, and treemix. I’m going to warn you compiling treemix can be kind of a pain. I’ve done it on Linux and Mac machines, and gotten it to work, but sometimes it took time.

You need R and/or R Studio (or something like R Studio). Make sure to install the packages or the scripts for visualizing results from PCA and pairwiseFst won’t work.*

There is already a .csv output from admixture. The PCA also generates expected output files. You may want to sort, so open it in a spreadsheet.

This is potentially just the start. But if you are a laypersonwith a nagging question and can’t wait for me, this should be you where you need to go!

* I wrote a lot of these things piecemeal and often a long time ago. It may be that not all the packages are even used. Don’t bother to tell me.

Drawing on the slate of human nature

Some of you have been reading me since 2002. Therefore, you’ve seen a lot of changes in my interests (and to a lesser extent, my life…no more cat pictures because my cats died). Whereas today I incessantly flog Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past, in 2002 I would talk about Steven Pinker’s The Blank Slate: The Modern Denial of Human Nature quite a bit. The reason I don’t talk much about The Blank Slate is that some point in the 2000s I realized my future deep interests were going to be in population genetics, rather than behavior genetics and cognitive psychology. If you are not a specialist who doesn’t follow the literature. Who doesn’t “read the supplements”. You’re going to stop gaining anything more from books at a certain point.

Similarly, after I read In Gods We Trust: The Evolutionary Landscape of Religion, I read a lot of books on the cognitive anthropology of religion. Until I didn’t. Now that Harvey Whitehouse has teamed up with Peter Turchin, I suspect I’ll check in on this literature again.

But life comes at you fast. Today I think the broad thesis of The Blank Slate seems so correct, that we are not a “blank slate”, that no one would argue with that. Rather, the implications of that thesis are highly “problematic,” and social and cultural constructionism has really gone much further on the Left operationally than they were in the early 2000s. To give a concrete example, you can admit that sex differences are real and significant, but you have to be very careful in mentioning or highlighting specific instances or cases where they matter.

Moving to a more controversial topic, for a long while I’ve pretty much ignored the genomic study of the normal variation of cognition. The reason is that until recently all the studies were very underpowered to detect much of anything. The sample sizes were too small in relation to the genetic architecture of the trait because of the “Fourth Law of Behavior Genetics.”

As 2018 proceeds I think we can say that we are now in new territory. On Twitter, Steve Hsu seems positively ecstatic over a paper that just came out in PNAS. His blog post, Game Over: Genomic Prediction of Social Mobility summarizes it pretty well, but you should read the open access paper.

Genetic analysis of social-class mobility in five longitudinal studies:

Genome-wide association study (GWAS) discoveries about educational attainment have raised questions about the meaning of the genetics of success. These discoveries could offer clues about biological mechanisms or, because children inherit genetics and social class from parents, education-linked genetics could be spurious correlates of socially transmitted advantages. To distinguish between these hypotheses, we studied social mobility in five cohorts from three countries. We found that people with more education-linked genetics were more successful compared with parents and siblings. We also found mothers’ education-linked genetics predicted their children’s attainment over and above the children’s own genetics, indicating an environmentally mediated genetic effect. Findings reject pure social-transmission explanations of education GWAS discoveries. Instead, genetics influences attainment directly through social mobility and indirectly through family environments.

Why does this matter? I’m assuming most of you have seen charts like the ones below, which “prove” how the game is rigged against the poor:

The problem that most behavior geneticists immediately have with these popular analyses, which now suffuse our public culture (e.g., the “representation” argument in academic science often takes as a cartoonish model that all groups will have equal representation in all fields given no discrimination; substantively almost everyone believes this isn’t true in some way, but for the sake of argumentation this is a bullet-proof line of attack which every white male academic is going to retreat away from), is that they ignore genetic confounds. This paper is an attempt to address that. Measure it. Quantify it. Characterize it.

The two most interesting results for me have to do with siblings and mothers. Unsurprisingly siblings who have a higher predicted educational attainment score genetically tend to have higher educational attainments. As you know, siblings vary in relatedness. They vary in the segregation of alleles from their parents. Some siblings are tall. Some are short. This is due to variation in genetics across the pedigree. People within a family are related to each other, but unless you are talking Targaryens they aren’t exactly alike. Similarly, some siblings are smart and some are not so smart, because they’re “born that way.”

We knew that. Soon we’ll understand that genomically I suspect.

Second, we see again the importance of maternal effects and non-transmitted alleles. Mothers who have a higher predicted level of education have children with more education even if those children don’t inherit those alleles.* One natural conclusion here is mothers with a particular disposition shaped by genes are creating particular environments for their children, and those environments let them flourish even if they do not have their mother’s genetic endowments. This actually has “news you can use” implications in life choices people make in relation to their partners.

The study ends on a cautionary note. Residual population substructure can cause issues, correcting which can attenuate or eliminate such subtle and small signals. The sample sizes could always get bigger. And ethnically diverse panels have to come into the picture at some point.

But Razib abides. This study had a combined sample size of >20,000 individuals. Then you have the other recent paper with 270,000 individuals, Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. All well and good, but I wait for greater things. There is no shame in waiting for better things. And I prophesy that a greater sample size shall come to pass before this year turns into the new.

And you know what’s better than 1 million samples? How about 1 billion samples!

* Note that the models are controlling for a lot of background socioeconomic variables.

July 10, 2018

How Donald Trump is like Marxism and Psychoanalysis

Filed under: Donald Trump,Politics,race — David Hume @ 11:46 pm

Recently my Twitter and Facebook timelines have been littered with references to this story: Man, 92, Allegedly Beaten With a Brick & Told ‘Go Back to Mexico’ by a Mom in Front of Her Child. Terrible. It was posted on Twitter, and Facebook, as evidence that Donald Trump’s America was horrible. Some of the Twitter reactions also talked about white privilege and that sort of thing.

When I saw that this occurred in the Los Angeles area though I grew skeptical. There are conservative parts of California. Much of the Central Valley, the far North, some of the trans-Sierra counties and even much of San Diego. But Los Angeles? Here’s Willowbrook, California‘s demographics (took me 30 seconds to find):

The 2010 United States Census reported that Willowbrook had a population of 35,983. The population density was 9,544.1 people per square mile (3,685.0/km²). The racial makeup of Willowbrook was 8,245 (22.9%) White (0.9% Non-Hispanic White), 12,387 (34.4%) African American, 273 (0.8%) Native American, 119 (0.3%) Asian, 49 (0.1%) Pacific Islander, 13,858 (38.5%) from other races, and 1,052 (2.9%) from two or more races. Hispanic or Latino of any race were 22,979 persons (63.9%).

1% of Willowbrooks’ residents were non-Hispanic whites. 64% were Hispanic. Just based on nativity my assumption then was that the attack was going to be a black American since Hispanic Americans are the less likely to engage in nativist tinged attacks since so many are either immigrants, the children of immigrants, or are in communities where immigrants are common.

And yes, the attacker was a black woman.

Additionally, you can get precinct level election results. 5% of the people in Willowbrook who voted in 2016 voted for Donald Trump for President of the United States of America.

So what you have here is that a black woman who lives in one of the most cosmopolitan metropolitan areas of the United States, in a community that has almost no non-Hispanic whites, and where only 5% of people voted for Donald J. Trump, has engaged in nativist violence. This is evidence for what is happening in “Donald Trump’s America.” As someone who is a nonwhite immigrant I do have to say that I experienced plenty of racism and prejudice, and sometimes bullying, from native born Americans over my whole life. From white people, and black people. Under Republican and Democratic administrations. In Red America and Blue America. I’m not saying it’s all the same. But it’s not new. And it’s not limited to one race or political faction.

There are some arguments for Marxist social and economic systems where everything seems to support the theory. The theory is unfalsifiable. Similarly, the same occurs with Freudian psychoanalysis. These are theories just too good to give way in the face of facts. Facts are secondary.

Often I feel the same way about the current partisan debates in the United States. If a single immigrant kills someone, it’s an immigrant crime wave. Similarly, if there is violence against a nonwhite person somewhere, it’s because of the climate that Donald Trump is creating. There have been instances where racial events have occurred and Trump’s came has come up as a justification. But if America is becoming polarized it seems very unlikely that this crime has anything to do with Trump, seeing as how this is an area with almost no white people, and very few Trump supporters.

You might say I’m kind of being a nerd about this. That’s fine. But not being nerdy about details is how we get in a post-fact world.

Ancient Ancestral South “Indians” may have roots in Southeast Asia

Filed under: Genetics — Razib Khan @ 10:51 pm


At the Society for Molecular Biology and Evolution conference in Japan there is a presentation which reports evidence for gene flow from Pleistocene Southeast Asians into South Asia. I have long suggested this was possible for several reasons.

During the Last Glacial Maximum ~20,000 years ago Southeast Asia would have been a relatively protected and well-watered region in comparison to South Asia. My understanding is that moist savanna has higher population densities of hunter-gatherers than dry scrubland. Southeast Asia would have had a great deal of the former, and almost none of the latter (the LGM was drier, and the rainforest zone in Southeast Asia would have been smaller, and Sundaland was probably mostly savanna). The Thar desert zone would have been much more expansive, pushing south and east. The summer monsoons were far weaker.

All this indicates Southeast Asia would have had larger populations than South Asia during this period. And large populations tend to impact smaller populations genetically.

Additionally, looking closely at haplogroup M, which is highly diverse in South Asia, some of them look to be intrusive and related to branches in Southeast Asia. Though I do believe some of the M branches in South Asia are very old and probably native, others may have been brought by Southeast Asian people related to the Hoabinhian culture (which was mostly absorbed by rice farmers from the north during the Holocene).

During the Pleistocene Southeast Asia and Southern Asia were probably part of the same biogeographic zone, just as they are today. The ancestors and relatives of the Negrito peoples of Southeast Asia probably displayed a continuity from South Asia down toward Oceania. The preponderant gene flow at some points from the east to the was probably just a function of population size and climate.

Today the genetic differences on the border between South and Southeast Asia are striking. Though Pathans and Punjabis are quite different, they are far closer genetically than Bengalis and Burmese (notably, linguistically the chasm is also far greater). I think that has partly to do with agricultural and sedentarism. The mountainous zones in northeast India and western Burma are far harder for farmers to traverse than small groups of hunter-gatherers.

Open Thread

Filed under: Open Thread — Razib Khan @ 11:58 am

Please keep the other posts on topic. Use this for talking about whatever you want to talk about.

The coming end of 150 years of the USA as the largest economy

Filed under: Economic History — Razib Khan @ 2:44 am


Most projections usually predict that China will be the largest economy by the year 2030. This got me thinking: when exactly did the USA surpass other nations? I knew it was in the 19th century, but I wasn’t sure exactly when.

As I’m sure you know, GDP estimates are always somewhat dicey, and they were even more so in the past. But the above plot* is representative of what you can find online: the USA became #1 in the decade or so after the Civil War. What surprised me is that the nation it surpassed was China! Around 1880 the USA overtook China, and around 2030 China will overtake the USA. That’s 150 years of American singular economic dominance. Curiously, for a period India was #3, just as it will be in 2030 (though it’s GDP will be far lower than #2 USA by most estimates).

I am aware that on a per capita basis America will be the most affluent large society in the world for decades beyond the point when it’s economy is not the largest. My only observation is that we are living to see the end of a particular phase in world history.

One aspect of this that I wonder about is that it is a fact that to some extent in the late 19th and early 20th century America refused to take over the role of the world’s preeminent power from the United Kingdom long after it had become the most consequential economic power. To be frank, it was clear in the early 20th century that the UK was simply longer up to the task, and arguably a great deal of suffering might have been alleviated if the United States had stepped earlier into its natural role. Now I wouldn’t be surprised if the inverse occurred in the second quarter of the 21st century: the USA, like Britain, continues to play the role of hyperpower hegemon longer after it’s able to carry out that role credibly. I hope I’m wrong.

* Data from Barry Ritholtz’s blog.

The hegemon and world-citizen

Filed under: Diplomacy,International Affairs,international relations — Razib Khan @ 1:16 am

On occasion, I read a book…and forget it’s title. I usually manage to recall the title at some point. For the past five years or so I’ve been trying to recall a book I read on Asian diplomatic history written by a Korean American scholar. Today I finally recalled that book: East Asia Before the West: Five Centuries of Trade and Tribute.

The reason I’ve been trying to remember this book is that I’ve felt it told a story which is more relevant today than in the late 2000s, when the book was written. From the summary:

Focusing on the role of the “tribute system” in maintaining stability in East Asia and in fostering diplomatic and commercial exchange, Kang contrasts this history against the example of Europe and the East Asian states’ skirmishes with nomadic peoples to the north and west. Although China has been the unquestioned hegemon in the region, with other political units always considered secondary, the tributary order entailed military, cultural, and economic dimensions that afforded its participants immense latitude. Europe’s “Westphalian” system, on the other hand, was based on formal equality among states and balance-of-power politics, resulting in incessant interstate conflict.

Here’s my not-so-counterintuitive prediction: as China flexes its geopolitical muscles, it will revert back to form in substance, forging a foreign policy predicated hierarchical relationships between states, while maintaining an external adherence to the system of European diplomacy which crystallized between the Peace of Westphalia and the Congress of Vienna. “Diplomacy with Chinese characteristics” if you will.

2019 isn’t 1999: the unipolar moment is over

Filed under: History — Razib Khan @ 1:02 am

I just finished reading War! What Is It Good For?: Conflict and the Progress of Civilization from Primates to Robots where the author argues that hegemonic Leviathans are actually good for average human well-being because they maintain order and peace. In other words, a multipolar balance-of-powers situation is dangerous. Unipolarity is less dangerous.

For various personal normative reasons, I’m not entirely happy with this conclusion. But, this book and others have convinced me that this is probably correct (for others, see The Fall of Rome).  So on some level, the Claire Berlinksi thread post below reflects a lot of truth. But I think it is wrong to get overly exorcised over Donald Trump’s acceleration of American involution.

The reason is that is that inevitable forces of economic determinism mean that the American unipolar world is not going to be maintained into the 21st century. In the late 1990s, with Japanese somnolescence, Russia as a supine post-superpower, and China only starting to get its footing as a capitalist nation, the vision of eternal American hegemony in our time was not a simple fantasy. It was an extension of the world that we saw around us.

That world is gone.

A quick check of GDP (PPP) by nation(s) tells us that China + India is now already ~75% of the USA + European Union. On a nominal basis, all the forecasts seem to put China and India #1 and #3 in GDP by 2030. On a per capita basis, these nations are going to be poorer than the West for a while longer. But in terms of power projection that may not matter so much. The fact that Czarist Russia and the Soviet Union were poorer per capita and had less human capital per unit didn’t prevent them from grinding superior western and central European powers down through sheer size.*

As a man in his 70s Donald Trump doesn’t seem to grasp that America cannot dictate as much by force of will as it could in the second half of the 20th century when he came into the fullness of manhood. But he’ll learn. And America will learn.

Our society is rich and wealthy. We are powerful. Our armed forces are the sharpest and longest blades on the face of the earth. But aside from the inexorable heaving emergence of the Asian nations the United States, and the West more generally, seems to be gripped by alternating fluxes of anomie and ennui. Trump’s election is a reflection of this.

* I refer here to the Napoleonic Wars and World War II. The Czarist collapse of World War I strikes me in some ways a collapse in morale and national spirit.

July 9, 2018

Bangladeshis are very East Asian, Sri Lankan Tamils are not quite as structured

Filed under: Genetics — Razib Khan @ 11:38 pm
Click to enlarge

A very long post as my other weblog where I reiterate how East Asian Bengalis, and in particular East Bengalis, are. Aside from the existence of a Dalit/scheduled caste subcommunity, very little has surprised me about Bangladeshi genetics in the last 5 years or so. Rather than a novelty, some simple truths seem to be reinforced over and over. Two major takeaways:

1) the only “exotic” aspect of Bengali ancestry is that Bengalis are substantially East Asian (with the exception that this is sharply attenuated in Brahmins).

2) Though there is some evidence of West Asian admixture in a few Bengali Muslims, you have to look really close to see evidence of it. Though I can believe and do believe, that many Bengali Muslims have a genealogical connection to Iran and Turan through a distinct paternal lineage, that has left a minimal genetic impact.

But one thing I did not emphasize in the post: looking closely at the 1000 Genomes Sri Lankan Tamil samples from the UK I think it is clear that they are less structured than an Indian sample would be. The proportion of Dalits is far lower than in the Indian Telugu sample obtained from the UK. So I will have to update my assertion that the Sri Lanka Tamil sample is as structured as Indians. It isn’t. This is contrast to the Lahore Punjabi samples, which are highly structured. More so than the Sri Lanka Tamils.

The main interesting thing about Bangladeshi genetics is how East Asian Bangladeshis are

Filed under: Bangladeshi Genetics,South Asian Genetics — Razib Khan @ 11:29 pm
Click to enlarge

 

I got a question about endogamy and Bangladeshis on of my other weblogs, as well as their relatedness to western (e.g., Iranian) and eastern (e.g., Southeast Asian) populations. Instead of talking, what do the data say? Most of you have probably seen me write about this before, but I think it might be useful to post again for Google (or Quora, as Quora seems to like my blog posts as references).

The 1000 Genomes project collected samples a whole lot of Bangladeshis in Dhaka. The figure at the top shows that the Bangladeshis overwhelmingly form a relatively tight cluster that is strongly shifted toward East Asians. There is one exception: about five individuals, several of which were collected right after each other (their sample IDs are sequential) who show almost no East Asian shift.

This to me is very strange.

Looking at other Bengali samples, whether it be a Kayastha and/or Brahmins from West Bengal, there tends to be a noticeable East Asian shift. The Brahmins though are mostly genetically similar to Brahmins from further north and west, with a minority of their ancestry probably indigenous Bengali, judging by the fact that they usually have less than 5% East Asian ancestry (depending on your metric). I have one Bengali Brahmin in the sample. You can see it as the outlier shifted to the Northwest Indian/Pakistani populations. This individual has very little East Asian shift. In contrast, the West Bengal Kayasthas, a typical “middle caste”, look similar to the Bangladeshi samples, except they have a lot less East Asian ancestry. In other words, they would plot between the Bangladeshi cluster and the other South Asian populations.

I suspect that the individuals with no East Asian ancestry may be from one of the Telugu migrant Dalit communities which settled in Dhaka during the British period.

There are some other East Bengalis on the plot that I added from the SAGP. Four of them are from Comilla. Though now a city, traditionally this region encompassed the area to the south and east of Dhaka, to the border with Tripura. Two of these individuals are my parents. I also added several from Sylhet, which borders Assam to the north (Syhlet people speak an unintelligible language to standard Bengali, similar to the people of Chittagong and the Rohingya). Two things to note.

click to enlarge

First the Comilla individuals are found in the most East Asian shifted portion of the distribution. This suggests, along with the position of West Bengalis, that the eastern ancestry in Bengalis exhibits a west to east cline. My father is somewhat atypical, in that he is shifted out of the main Bangladesh cluster ever so slightly. A genealogical fact though is that his maternal grandfather was reputedly from a Bengali Brahmin family (more likely looking at the attenuated extent of the skew, his mother’s paternal grandfather was a Brahmin).

Second, the Syhlet individuals seem to have something of a shift to Northwest Indians and Pakistanis. But the individual who sent me these data noted that several of the individuals have family records and memory of partial descent from Muslims from Afghanistan and such. That seems likely looking at their position.

Using Treemix, it is notable to me that both the Syhlet and Comilla groups show gene flow more directly from the Dai than the Bangladeshis more generally. I think this is likely an artifact…but there is some slight structure in the Bangladesh population which is probably being missed. The eastern ancestry in Bengalis probably comes from both Austro-Asiatic and Tibeto-Burman people, and this fraction must vary across the region (or normal variation as part of Mendelian segregation).

click to enlarge

Earlier I said the Bangladeshi population is relatively unstructured. Click the Treemix plot above. Or check this Admixture run at K = 5. The Bangladeshi sample has only modest quantitative differences in comparison to most of the other South Asians. To the left are plots of Telugus sampled in the UK, along with South Indian Brahmins. Notice the relatively large range of variance. This is not atypical in sampling from South Asian populations. You see the same pattern in the Gujuratis sampled from Houston, and the Punjabis sampled from Lahore. The partial exception here at the Tamils from Sri Lanka sampled in the UK. There are a small number of individuals who cluster with Dalit groups, but far less than the Telugus. Why? I suspect that panmixia is somewhat along the way in Sri Lankan Tamil populations.

So what’s going on in eastern Bengal? One thing to note is that Muslim Punjabi populations seem to have a huge amount of genetic variation. On par with what you see in Indian populations. The relatively well-mixed character of eastern Bengalis isn’t just a function of caste-less Islam. Bengali Muslims are no more strictly Muslim than Muslims from Punjab. In fact, the stereotype arguably goes in the other direction. Additionally, the variation in East Asian ancestry in Bangladeshis is significant, but aside from what are likely scheduled caste (Dalit) groups which may descend from Indian colonial migrants, I suspect that range in quantum is probably mostly due to geography. The only group of Bangladeshi genotypes where I’ve seen a higher East Asian fraction than my own is of individuals from Chittagong, which is entirely expected from on history and geography.

Based on LD decay the admixture between the East and South Asian components in modern Bangladeshis dates to about 52 generations ago. That’s 1,300 years ago assuming 25 year generation times. A single pulse admixture is a better fit than two distinct events. Because of the range of physical appearance in my family, from mildly East Asian looking (I have family members who can easily pass for Malay or Filipino, at least judging by the languages people speak to them in cosmopolitan areas) to not very East Asian looking, I had assumed that a great deal of the admixture was recent due to proximity (several branches of my family lived in the princely state of Tripura; my grandmother almost killed by a rampaging elephant owned by the Maharani of Tripura). So, I was surprised that my parents both had about the same amount of East Asian ancestry (~15%). This is not entirely shocking, but consider that my mental model of the admixture process was similar to that of African Americans. So if you are a black American, and our parents both turn out to be ~15% European, rather than say 12% vs. 18%, you have to start wondering. So when the LD decay estimate suggested an older, but singular, admixture I was not entirely surprised.

In The Rise Of Islam And The Bengal Frontier 1204-1760 the author presents a model whereby the collapse of Hindu rule in Bengal in the 13th century was coincident with the emergence of a frontier society which expanded the zone of intensive agriculture through reclamation projects. Though the expansion and settlement was directed by Muslims of originally West Asian provenance (Turanian Turks and Afghans), the settlers themselves were peasants who spoke the proto-Bengali language. Curiously, both West Bengalis and Burmese individuals have told me that there is a belief that the indigenous people of Bengal were of East Asian character. The LD decay statistics indicate that most of the admixture occurred well before the arrival of Islam to South Asia, but if settlers were drawn already from the eastern fringe of Indo-Aryan speech, then they would be more enriched to East Asian ancestry. That still leaves one to explain the west-to-east cline of East Asian ancestry even within Bangladesh (East Bengal). That is probably due to secondary  admixture, combined with further gene flow from the west diluting the original admixture signal.

Going back the original question in terms of affinities to western and eastern population and Bengalis. There is a northwest to southeast gradient of “Ancestral North Indian” (Iranian farmer + Indo-Aryan) ancestry in South Asia, and that is evident in Bengal. But, Bengalis clearly have a substantial minority ancestral component from Eastern Eurasia, probably via Austro-Asiatic and Tibeto-Burmans tribes. Though some Bengalis have a small proportion of distinct West Asian ancestry that is distinct from what is found typically in South Asians, that’s about one order of less magnitude significant than the East Asian ancestry.

All of this was pretty clear about five years ago. The more genotypes I get, the more clear and obvious the above assertions are.

Open Thread, 07/09/2018

Filed under: Open Thread — Razib Khan @ 6:31 pm

My review of The University We Need: Reforming American Higher Education is up at National Review Online (it’s already posted to my total content feed). The book’s publication date is tomorrow.

A  review can only pack in so many things. So if there is something missing that seems obvious, it’s probably something that I cut in the interests of space (e.g., the author is not a fan of the emphasis on football and such at many universities, but I didn’t touch on that in the review). The University We Need is a short book, but it’s very dense in ideas and suggestions. Unfortunately, comments on NRO and Twitter indicate many people haven’t really read the review, so they won’t read the book.

Surely one reason I enjoyed the book is that the author is someone who I’m coincidently on the same wavelength. I first encountered his work nearly twenty years ago, when I read A History of the Byzantine State and Society, a ~1,000 survey of the topic. In many ways a scholarly “core dump”, it has served me in good stead all these years. But at the time I was totally unaware that the author, Warren Treadgold, and I shared broadly similar politics in the grand scheme of things. That is, we were intellectually oriented people who were also not on the Left.

I don’t consider myself a conservative intellectual. I’m just an intellectual happens to be conservative because the Left terrifies me (I have real personal reasons!). Treadgold’s work similarly is not informed by him being a conservative intellectual. Rather, he’s a scholar whose views default to the Right as opposed to the center or Left because of where the dominant tendency in academia today is.

I’m currently reading A History of Japan. I think I’m getting stale and predictable. I read John Keay’s Midnight’s Descendants: A History of South Asia since Partition really quickly a few weeks ago. Need to move out beyond my tendency of reading long histories and lots of genetics papers.

I have a stack of books on cognitive psychology and cultural evolution I need to get through, though I think papers are probably more useful in the latter area, since I’ve read a fair number of books already on this topic (e.g., Cultural Evolution: How Darwinian Theory Can Explain Human Culture and Synthesize the Social Sciences).

Speaking of psychology, there are some really good podcasts in that field out. Part of it is there is so much to talk about with the replication crisis. I really enjoyed Two Psychologists Four Beers, for example. Though not surprisingly they sort of still mischaracterize the views and issues of conservatives or non-liberals in academia…there are so few who are “out” and vocal with their politically normal colleagues that people just don’t know what’s going on in their heads and it’s easy to mischaracterize.

This is the week when you follow the #SMBE2018 hashtag on Twitter. I assume a lot of papers are going to come out in the next few weeks after people present at SMBE.

Estimating recent migration and population size surfaces. This seems important. Definitely going to read.

How eliminating the ‘kill box’ turned Mosul into a meat-grinder.

Genetic analysis of social-class mobility in five longitudinal studies.

Male homosexuality and maternal immune responsivity to the Y-linked protein NLGN4Y.

Hung out with Stuart Ritchie this week. Still recommend his book, Intelligence: All That Matters.

There was some discussion on ancient DNA and archaeology on Twitter. Has ancient DNA changed everything? Or not?

First, I think it’s important to acknowledge that many of the models which have emerged out of ancient DNA are resurrections of older anthropological, archaeological, and historical frameworks, which emphasize migration. But these were long dismissed within many of these fields. Like David Reich in Who We Are and How We Got Here I believe that there was a political rationale for this. As someone who has read deeply in paleoanthropology and history for twenty years, I reject the idea that ancient DNA is actually not that revolutionary because I remember what passed as conventional wisdom 10-20 years ago.

A University for Non-Leftists

Filed under: Books — Razib Khan @ 2:30 am
Professor Warren Treadgold has a radical proposal for higher-ed reform.

July 7, 2018

Carthage (and others) must be read

Filed under: History — Razib Khan @ 12:07 am

The first half of Richard Miles’ Carthage Must Be Destroyed: The Rise and Fall of an Ancient Civilization is useful, but there’s less of a focus on the culmination you know is coming, the Punic Wars. For a history of that, I’d actually recommend Adrian Goldsworthy’s The Fall of Carthage: The Punic Wars 265-146 BC (one of the best descriptions of Cannae).

By utilizing archaeology and generating an inferred cultural history of Carthage, Miles does a great job contrasting the Punic mercantile republic with Rome. Aside from the penchant to name their leading citizens Hanno, Hannibal, and Hamilcar (to the point it’s hard to keep track of who is who), the most notable aspect of ancient Carthage seems to be its tendency to crucify generals who fail in battle. The Carthaginians come off as cartoon villains, even setting aside the child sacrifice. This is probably partly history being written by the winners, but it’s clear that still, Rome, in particular, was unique in its public spiritedness and social cohesion.  This, despite the fact that Rome and Carthage had both converged on a system of an oligarchic republic during the height of their rivalry.

Ancient history, and reading about other cultures, is illuminating about the human condition because different peoples in different exigent circumstances seem to react mostly the same but to wildly different outcomes.

For China, I don’t know of a better treatment in survey form than John King Fairbank’s classic. I also have a very soft spot for Jaques Gernet’s A History of Chinese Civilization. Fairbank’s book is more narrative history with some cultural fat on the bones. Gernet is more a cultural history with an exoskeleton of narrative diplomatic history.

For Rome, there are many recent books. But I still really like Michael Grant’s big thick survey, History of Rome. I don’t know about Greece since I haven’t read Greek history much since I was a child. Though Grant has some books on Greece too.

Finally, Michael Axworthy’s Empire of the Mind should be on a “to read” list. It’s a little off the beaten path because it’s a history of Iran. It’s got only superficial coverage of the recent past and tries to go deep into the psyche of what makes Iran Iran. I think it is fair to say that the book ends of concluding that Iran, as we understand it today, is hard to detach from the Safavid period (when it become Shia).

I think these civilizations of the Eurasian oikoumene are good places to start to understand the human condition because so many people were peasants and those ruled by peasants over the past 10,000 years. I would recommend a book on India, but those are mostly religious books. Islam comes a little late, as does Northern Europe. Much of Eurasia and Africa had no written language. If you understand China, Persia, and Rome, you’ll understand a lot. And probably enough.

Book recommendations welcome.

July 5, 2018

Give me liberty or give me alternative history!

Filed under: Alternative history,American History,History — David Hume @ 9:33 pm

For Want of a Nail: If Burgoyne Had Won at Saratoga is one of the best alternative history science fiction novels written in the 20th century. It is literally encyclopedic. A fully realized alternative timeline, the novel takes the form of a narrative history!  I don’t know if one can say that the world depicted is better or worse than ours…it is simply different.

I think of it whenever I see pieces such as one in Vox, 3 reasons the American Revolution was a mistake. There are some people offended by the timing of the piece, July 3rd. And I can see that.

But what about the premise? The author makes three assertions:

  • Slavery would have ended sooner
  • The Native Americans would have done better under the British
  • The British system of parliamentary democracy with a constitutional monarchy is superior to the presidential republican one

The last point really isn’t about the American Revolution. It’s an argument about a presidential system vs. that of a constitutional monarchy. The second point seems the simplest and most straightforwardly defensible. The reality is that there is a consistent pattern of monarchs and authorities being more benevolent to marginalized subjects than those nearer to those subjects. The Spanish who settled the New World were brutal to the native peoples, and though the rulers of Spain could not ultimately stop them, it is clear that they did not condone or encourage the brutality. Similarly, the white settlers of Australia treated the native peoples brutally and genocidally, but this occurred because of the relatively free hand that the British Empire gave the white settler colonies. And finally, even in the United States, in the 19th century, the most pro-Native sentiment was often found in places like New England, where the local Native population was mostly gone due to earlier wars (during which Congregationalist ministers had justified the tossing of Indian children into rivers to drown).

Though it is likely that the Native Americans would have been marginalized and decimated by white settlers in North America no matter what timeline you look at, it seems plausible that if the American settlers had not taken over their government the British crown probably would have suppressed some of the more overt brutality. It is likely, for example, that the Cherokee would never have been relocated to Oklahoma, at great human cost.

But the phenomenon of slavery brings to mind a major issue when weighing the cost vs. benefit of American independence: as tacitly acknowledged in the Vox piece the very secession of the American colonies from the British Empire likely had an impact on the British themselves.

In Kevin Phillips’ The Cousins’ Wars: Religion, Politics, Civil Warfare, And The Triumph Of Anglo-America he points out that the removal of the American colonies (or the majority at least) in the late 18th century, and the mass exodus of the Catholic Irish in the 1840s, transformed the white population of the British Empire. In 1800 the population of England and Wales was about 10 million and the population of Ireland was 5 million. By 1900 there 30 million people living in England, and 3 million living in Ireland. In 1850 there were about 15 million people in England and 25 million people in the United States of America.

The removal of the Catholic Irish from the United Kingdom, often to the United States, shifted the cultural and ethnic balance in the United Kingdom to one where people who adhered to the established Anglican Church were numerically dominant. The United States itself when it had been the American colonies were dominated by dissenter Protestants. With the Second Great Awakening in the early 19th century, only a small minority of the population was affiliated with the Episcopal Church. Arguably the only part of the British Empire which could ever compete with the metropole as producers of manufactured goods would have been the New England colonies and the northern Mid-Atlantic region. The American exit probably had fortuitous long-term consequences for British cohesion and singular purpose in terms of imperial policy.

Overall I think considering the morality of the American Revolution is a good thing. In the year 2000, the film The Patriot depicted the British as proto-Nazis, committing heinous acts against the American populace. One reason that this was not plausible is that a substantial minority of the American population was pro-British, and a large number were ambivalent or neutral. By all estimates, the hardcore revolutionaries were a minority, though this varied by region and period (e.g., New England was a hotbed of revolt, while New York City and much of the Mid-Atlantic remained loyalist). And the reality is that the British treated white Americans colonials with kid gloves in part because those American colonials were seen as part of the British people in a way that nonwhites never were. The issue for the Americans is that the metropole did not see them as exact equals.

I was taught history in the United States, and so it was written and presented in a way which did depict the British as villains who were imposing unjust demands on the American colonists. As I got older I realized that though the revolutionaries had cause to be angry, the British also had a rationale for their behavior. 1776 was not 1986.

But even aside from that, the Vox piece suffers from not acknowledging the fact that history is nonlinear and the knock-on effects of a British victory may have been much more drastic and unpredictable than the movement of a few parameters here and there (e.g., slavery abolished in the USA in 1830 rather than 1860). Jay Winik’s The Great Upheaval documents just how radical the American regime was in its time. The American republic was an exotic and strange experiment and served as a model and beacon. It is quite possible that without its model of revolutionary success the French Revolution may never have occurred. As a conservative, I think that would be a good thing, but I’m not sure many progressives would agree.

Additionally, the democratic republican model of government was shown to work in the modern world at large political scale by the United States. Most Europeans were skeptical of its feasibility, as ancient republics and democracies had never been able to sustain themselves beyond a certain size. And, unlike most every other nation at the time the United States also had a federal government which eschewed the mixing of religion and state, so that the republic was not sanctified by a divine or supernatural principle.

As an exercise in historical analysis, or entertaining alternative history, wondering about the consequences of a British victory over the rebels in the war in the American colonies is interesting, and possibly important. But I’m not sure there are truly deep moral lessons across the full arc of history, because the success of the rebellion itself had consequences far outside of the American colonies.

July 4, 2018

Rule #34 for Elves

Filed under: Fantasy — Razib Khan @ 11:17 pm
Arwen Evenstar by Anna Kulisz

George R. R. Martin’s A Song of Ice and Fire was striking in the mid-1990s when the first book debuted because it combined the epic aspect which suffused J. R. R. Tolkien’s work with a gritty realism in regards to sex and violence more appropriate for HBO. So it was entirely unsurprising that Martin’s vision has translated reasonably well to HBO.

Now that Amazon has confirmed that the new Tolkien series is going to be based around the early life of Aragorn, some are highlighting what they see as a likely problem with the new series:

While Game of Thrones is often held up as grittier and more cynical than Lord of the Rings – often by people who see the latter as a simplistic, morally two-tone tale of good vs. evil – the biggest difference, when it comes down to it, is the titties (and the characters’ filthy fucking mouths). Lord of the Rings is darker than it’s often given credit for.

There is something about the mood and ambiance of Tolkien’s work which Peter Jackson captured in his first three films. This, despite the fact that the exterior scenes in lush and green New Zealand did not properly reflect the ancient decay of the landscape of the fallen civilization to which Aragorn and his companions were the heirs to.

George R. R. Martin begins A Game of Thrones in a brutal manner. Additionally, the perverted sex is frontloaded. HBO really didn’t have to do much to sensationalize the material that Martin gave them. In fact, I’ve stated many times that some characters, such as Ramsay Bolton, were cleaned up quite a bit for the small screen. Not only is the actor who plays Bolton more handsome than the character described in the book, but he’s less depraved and cruel in comparison to the one Martin sketches out.

But as highlighted in the write-up above, and suggested in my title, I think an epic television show based on the world of Tolkien will stumble in how to depict sex and romantic feelings. A scene where Arwen Evenstar is getting railed by Aragorn from behind would seem a bit out of character. And, the way Tolkien writes about them, I’m pretty sure that his elves did not have anuses, so the real kinky stuff is off the table. But if the show neglects sex altogether, I suspect many adult watchers will perceive it as a juvenile. In three films it was reasonable that due to time constraints the characters were depicted in a relatively chaste manner. But over five episodic seasons?

What Neanderthals tells us about modern humans

Filed under: Human Population Genetics,Neanderthals — Razib Khan @ 5:35 pm

In Who We Are and How We Got Here: Ancient DNA and the New Science of the Human Past David Reich spends a fair amount of time on Neanderthal admixture into modern human lineages. Reich details exactly the process of how his team arrived to analyze the data that Svante Paabo’s group had produced, and how they replicated some peculiar patterns. In short, eventually, they concluded that modern humans outside of Africa have Neanderthal ancestry, because the Neanderthal genome that Paabo’s group had recovered happened to be subtly, but distinctively, closer to all non-Africans than to Africans. At the time, the group reported that Neanderthal ancestry was relatively evenly spread across non-African populations, which lead them to suggest that it was likely a singular admixture event early on during the expansion phase of modern humans.

Nearly a decade things have changed. There is a consistent pattern of West Eurasians having less Neanderthal ancestry than East Eurasians. That is, Europeans have lower Neanderthal ancestry fractions than Chinese (South Asians are in between, in direct proportion to their West Eurasian ancestral quantum). There have been a variety of arguments and explanations for why this might be, which fall into two classes:

  1. Neanderthal ancestry was purged more efficiently from West Eurasians due to larger effective population sizes (selection is stronger in large populations).
  2. There may have been multiple admixture events into modern humans, or, gene-flow into West Eurasians diluting their Neanderthal ancestry.

But what if all these arguments are mostly wrong? That’s what a new preprint seems to suggest: The limits of long-term selection against Neandertal introgression:

Several studies have suggested that introgressed Neandertal DNA was subjected to negative selection in modern humans due to deleterious alleles that had accumulated in the Neandertals after they split from the modern human lineage. A striking observation in support of this is an apparent monotonic decline in Neandertal ancestry observed in modern humans in Europe over the past 45 thousand years. Here we show that this apparent decline is an artifact caused by gene flow between West Eurasians and Africans, which is not taken into account by statistics previously used to estimate Neandertal ancestry. When applying a more robust statistic that takes advantage of two high-coverage Neandertal genomes, we find no evidence for a change in Neandertal ancestry in Western Europe over the past 45 thousand years. We use whole-genome simulations of selection and introgression to investigate a wide range of model parameters, and find that negative selection is not expected to cause a significant long- term decline in genome-wide Neandertal ancestry. Nevertheless, these models recapitulate previously observed signals of selection against Neandertal alleles, in particular a depletion of Neandertal ancestry in conserved genomic regions that are likely to be of functional importance. Thus, we find that negative selection against Neandertal ancestry has not played as strong a role in recent human evolution as had previously been assumed.

The basic argument in the preprint is that the model assumed for the ancestry of West Eurasians and Africans was wrong. Wrong assumptions can lead to wrong inferences. Using two Neanderthal genomes which are from different populations, one of whom directly contributed to the Neanderthal ancestry in modern humans, a new statistic which was insensitive to model assumptions about modern human phylogeny was computed.

The older statistic held that West Eurasians and Africans were distinct clades which had not had gene flow in ~50,000 years. Using simulations the authors argue that the best fit to the statistics that they do see, the earlier flawed one, and the current more robust one, is a situation where a population of West Eurasian origin mixed with Africans starting about ~20,000 years ago.

This explains why there was a consistent decline in Neanderthal ancestry: the earlier statistic’s model assumption got worse and worse over time, and so began to underestimate Neanderthal ancestry more and more. There was continuous gene flow into Africa over the past 20,000 years.

Not everything that came before is wrong. It could still be that there are multiple admixtures. And, the authors do agree that some selection for Neanderthal alleles has occurred. It’s just that it’s not the primary reason for the decline of Neanderthal ancestry in West Eurasians.

As for the other explanation, that Neanderthal-less Basal Eurasian ancestry diluted the European hunter-gatherer fractions, the authors seem very skeptical of that. One point the authors make is that though an early European farmer was estimated to have ~40% Basal Eurasian, its Neanderthal estimate is still quite high. Iosif Lazaridis points out that this is an old estimate, and the Reich group now puts it closer to ~25%. Additionally, another recent preprint put the fraction closer to ~10%. With such low values, it is possible that Basal Eurasians may have had low Neanderthal fractions, but that that was a marginal effect on the aggregate West Eurasian ancestry quantum from Neanderthals.

I think the bigger thing to consider is that our understanding of the relationships of modern humans is roughly right, but there are lots of nuanced details we’re missing or misunderstanding. Ancient DNA from South Africa, for example, shows that modern Bushmen all seem to have exotic ancestry compared to samples from 2,000 years ago. But what about samples from 20,000 years ago?

We have the best temporal transect from Ice Age Europe, and in this region, there are many population turnovers and admixtures. It seems implausible that Europe is entirely exceptional. The West Eurasian gene flow event dated to ~20,000 years ago is curiously coincidental with the beginning of the recession of the Last Glacial Maximum. To get a better understanding of the relationships of Pleistocene people looking at paleoclimate data is probably useful. The ancient DNA will come online at some point…and unless you think ahead, we’re going to be surprised.

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