RKUL: Time Well Spent 08/08/2023

poolside edition

Aug 08, 2023

Your time is finite. Your phone and the internet stand ready to help you squander it. Here are my latest picks for spending it well instead. Feel free to add more in the comments.

Books, what else?

This week’s podcast was a two-hour-long discussion with statistical geneticists Alex Young and James Lee and quantitative and polygenic traits, their prediction and architecture. The goal was to clarify issues and questions that regularly crop up in the public conversation on these topics, ideally at length and in some depth. But a two-hour discussion has limitations. There’s a lot we didn’t get to. Nevertheless, I see the topics as relatively accessible to someone who is both interested and willing to put in the legwork.

To say that I learned population genetics by reading the 3rd edition of the Principles of Populations Genetics is nearly correct. As a comprehensive survey of the major topics of the field as they coalesced in the late 20th century, this book approaches bible status in this field to me. Working through the problems in Principles of Populations Genetics will take you much of the way to being able to think about population genetic questions analytically. Countless details have changed due to genomics in the last generation, but not the fundamentals.

Built atop the foundations of Principles of Populations Genetics, D. S. Falconer and Trudy Mackay’s Introduction to Quantitative Genetics takes you the next step in grasping the nature of polygenic characteristics, the estimation of heritability and how quantitative characteristics respond to selection. It builds on population genetics but extends it specifically to apply to domains like the selection and breeding of animals.

One of the benefits of Principles of Populations Genetics and Introduction to Quantitative Genetics is their relative accessibility. The two volumes often referred to as “Lynch and Walsh” (after their co-authors, Genetics and Analysis of Quantitative Traits and Evolution and Selection of Quantitative Traits are not introductory, and probably should not be read without the earlier two books under your belt. Encyclopedic and exhaustive works by extremely eminent scientists in the field, these works are less the read-front-to-back variety than invaluable resources for ruminating upon a particular chapter at a given moment.

Over the course of my discussion with Young and Lee we alluded to some historical figures and the origins of statistical genetics in the early 20th century. If there was ever a historian of population and evolutionary genetics, it was probably the late Will Provine. The Origins of Theoretical Population Genetics is a slim volume that begins with Charles Darwin, and ends with R.A Fisher, J. B. S. Haldane and Sewall Wright, outlining how the theory of evolution, early statistics and Mendelianism fused into population genetics by the 1920’s and 1930’s. Sewall Wright and Evolution Biology take Provine’s project deep into the 20th century via an intellectual biography of one of population genetics’ three founders in the English-speaking world. Young, Lee and I talk about the shifting balance theory, but Provine’s biography clarifies that Wright’s own views of the model evolved over the decades, from the importance of drift vs. gene-gene interaction, making it difficult to understand the dominant insights offered.

Of course, theoretical population genetics did not stop with Wright, Fisher and Haldane. One of the major advances in the late 20th century was coalescent theory, and John Wakeley’s text of that name, Coalescent Theory, is an excellent introduction to the topic. After the the understanding of the coalescence of DNA genealogies back to a common ancestor, probably the last generation’s most important development in population genetics has been the massive influx of data enabled by genomics. Michael Lynch’s The Origins of Genome Architecture was written over 15 years ago, so it should not be taken as gospel, but it is a useful work that illustrates how minds trained in 20th-century population genetics began tackling the first wave of the ongoing flood of 21st-century genomic data.

Thought

Tracing the genetic histories of ghost apes: The footprints of extinct lineages are the closest we have to a fossil record of the African apes. This John Hawks piece is a “must-read” because it contextualizes a lot of what we’re going to see in many animals, including humans. The idea of “ghost lineages” is really a useful shorthand for imperfect species definitions, but it gets at the overall dynamics of evolutionary genetics which don’t fit neatly into our tidy concept of species.

Europeans Are Becoming Poorer. ‘Yes, We’re All Worse Off’. Or see How the U.K. Became One of the Poorest Countries in Western Europe. By some estimates, Slovenians are now better off than Britons. The underlying reasons, structural-demographic and policy-wise, are interesting, but the not-so-slow-fade of Europe is pretty incredible from a world-historical perspective. The continent that once ruled the world is shifting into genteel decline and relative poverty (compared to the US, for example).

Harvard will never be an engine of social mobility. Read with Making What Harvard Is About Transparent. Harvard and the other Ivies remind me of those super-rich, sybaritic mega-church pastors; total hypocrites papering over their naked self-interest with noble-sounding rhetoric.

A Room-Temperature Superconductor? New Developments. If this works, it might lead to a ‘post-scarcity society.’ Also, check Manifold Markets on this issue. And here’s a piece about some of the new tech room-temperature superconductors would allow.

Why America’s Largest Tool Company Couldn’t Make a Wrench in America. This is demoralizing but unsurprising. Deindustrialization can’t just be reversed on a dime (also see Samo Burja’s The End of Industrial Society).

Brian Frezza: scaling experimental science and the art of entrepreneurship. A podcast I did with the CEO of Emerald Cloud Labs, whose facility I got to check out here in Austin. Frezza is excited about science and has charted an interesting trajectory from academia to industry. The Guardian did a story on his company last year. The basic idea is to scale and decentralize scientific experimentation with automation and remote facilities.

Data

Local population structure in Cambridgeshire during the Roman occupation. More and more work on historical demography will hinge on ancient DNA. Not surprising that Roman-era peasants, presumably Celtic-speaking, in Cambridgeshire, in the east of England and near the core of where the Anglo-Saxons landed, were much more genetically similar to the Welsh than people in the modern region are.

Interpreting SNP heritability in admixed populations. The portability of these population-genetic statistics across different groups is a major open question in this decade, but a precise understanding of how variants operate against different genetic backgrounds should occur with more diverse genomic training sets.

Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases. The ultimate aim of genomics is to target real biological processes, and this is another method to do just that.

The Correlation between Relatives on the Supposition of Mendelian Inheritance. R. A. Fisher’s original paper. Still worth reading, as it helped fuse evolutionary biology with Mendelian genetics.

KoNA: Korean Nucleotide Archive as a New Data Repository for Nucleotide Sequence Data. Imagine a world where all nations did this.

My Two Cents

There’s still no free lunch, free subscribers; my most in-depth pieces for this Substack remain beyond the paywall. Since the last “Time Well Spent” I’ve released a long-requested deep dive on the Bantu (with a second, smaller addendum coming next) .

Bantu über alles: three millennia of unstoppable African farmers repeopling the vast continent - Humanity’s last great agricultural revolution:

Looking more deeply at ancient DNA from across Bantu Africa reiterates the massive demographic impact of these farmers as they spread south and east. Before the Bantu expansion, a variety of foragers occupied Africa’s entire Indian-Ocean zone, with genetic diversity running from the Khoisan in the south to the indigenous Africans of highland Ethiopia in the north. When the Bantu pushed into southern Congo 3,000 years ago, East Africa was experiencing a migration of pastoralists from the north. These nomadic goat and cattle herders had penetrated as far south as Tanzania more than five centuries before ‌the Bantu. But the genetic signal of the pastoralists was a thin veneer atop the forager substrate, ‌which remained dominant. It was the Bantu arrival that truly collapsed and ablated the bulk of the earlier genetic diversity. A deep whole-genome analysis of populations in Angola, in the west, and Mozambique, in the east, reveals that local populations today have at most roughly 5% pre-Bantu ancestry. This contrasts with figures closer to 30% Western European indigenous forager among Neolithic farmers in Northern Europe 6,000 years ago, or 25% indigenous Paleolithic Southeast Asian ancestry absorbed by rice farmers arriving from China 4,000 years ago in Vietnam. In Malawi, in Africa’s southern Great Lakes region, the indigenous hunter-gatherers left literally no descendants when we compare their ancient DNA with modern samples. Only in far southwest Africa, in Botswana, western South Africa and in Namibia, can we detect extensive mixture of the indigenous populations of Khoekhoe, on par with early European farmers’ 30% forager ancestry. The Bantu winner-take-all rise was catastrophic for the people that preceded them, one million years of Africa’s human complexity swept away at spearpoint as the continent was filled by the last human diaspora.

If you want to browse my more geographically focused pieces, Dry.io has created an interactive map of them. We’ll keep adding to that page over time. Also, Dry.io set up a nice skin for my pinboard bookmarks and a page for reader-submitted links.

Discussion

All my podcasts go ungated two weeks after their Substack release. So I encourage subscribers on the free plan who’d like to automatically get them to subscribe to that podcast stream (Apple, Stitcher, and Spotify). If you want to listen on YouTube, please subscribe.

Here are my guests (and monologue topics) since the last Time Well Spent:

For subscribers, I post transcripts (automatically generated, though I have someone going through to catch major errors).

ICYMI

Some of you follow me on my newsletter, blog, or Twitter. But my own domain also has all my links and updates: https://www.razib.com. There you’ll find links to the few different podcasts I’ve contributed to or run, my total RSS feed, links to more mainstream or print articles when I remember to post them, my Twitter, the occasional guest appearance, etc.

Email me
DM me
Facebook message me
My total feed of content
My long-time blog, GNXP
A group blog, Secular Right, vintage at this point, but worthwhile for Heather Mac Donald’s prescience
My Indian/South Asian-focused blog, Brown Pundits
Some of my past pieces for UnHerd, National Review, The Manhattan Institute, Quillette, and The New York Times
My old podcast, The Insight
This podcast, Unsupervised Learning

On the blog

Computational Linguistic Phylogenetics And Indo-Europeans:

To be entirely candid, it’s very hard for me to reconcile the ancient DNA with this typology and time-depth in a parsimonious manner that holds together in my head. This doesn’t mean the other models don’t have holes, the “Southern Arc” theory is pretty complicated too, and everything would have been “easier” if the Hittites had steppe ancestry, and they do not seem to. But there are too many things that are hard for me to understand with this new model. For example, the vast numbers of steppe Iranian people seem to be mostly descended from the CWC societies that gave rise to Europeans, but their languages diverged extremely early from their western neighbors, almost 2,000 years before the diversification of the CWC as an archaeological, demographic and genetic unit.

Over to you

Comments are open to all for this post, so if you have more reading/listening suggestions or tips on who I should be talking to or what you hope I’ll write about, lay it on us.

Razib Khan's Unsupervised Learning

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