вторник, 24 декабря 2019 г.

Study explores the density of the tectonic plates and why they sink in the Earth's mantle

A fast collision rate between tectonic plates and a young age (millions of years) are two factors that favour the sinking of the lithosphere in the mantle, according to a new study made by researchers at the Institute of Earth Sciences Jaume Almera of the Spanish National Research Council (ICTJA-CSIC). The study has been published recently in Scientific Reports.

Study explores the density of the tectonic plates and why they sink in the Earth's mantle
A schematic summary of the effect of the convergence rate. Upper image shows a slow convergence rate allows
thermal difussion and a derived reduction of slab's density (positive buoyancy). Lower image shows
how a faster convergence rate increases the slab's density promoting the negative buoyancy
[Credit: Kittiphon Boonma]
The authors of the study developed a new numerical model to study the effects of the convergence rate between tectonic plates and its composition on the lithospheric mantle density promoting or avoiding its sinking during subduction or delaminating processes.

"The model designed in this study provides a methodological framework for understanding the stability of the lithosphere during the convergence of the tectonic plates," said Kittiphon Boonma, Ph.D. student of the SUBITOP project at ICTJA-CSIC and first author of the study.

The lithosphere is the Earth's rigid outermost layer that comprises the crust and uppermost mantle, forming the tectonic plates. These plates float and move over the asthenosphere, a denser and more viscous layer of the sublithospheric mantle. In the areas where plates converge, one of the plates sinks below the other, thrusting into the sublithospheric mantle. This would be the typical case of the oceanic lithosphere subduction zones.

Another possibility is that, in continental collision zones, the lithospheric mantle of one of the plates separates from ("peels off") the crust and sinks into the asthenosphere in a process known as delamination. Both processes are sensitive to the lithospheric mantle density which, at the same time, depends on the pressure, temperature and chemical composition or, which is the same, of the convergence rate and the age of the lithosphere.

"Our simulations combine lithospheric composition for different plate ages with a wide spectrum of plate collision rates to understand what determines the positive or negative buoyancy of the lithosphere," said Daniel Garcia-Castellanos, researcher at ICTJA-CSIC and co-author of the study.

"The main advance of our work is the analysis of the dependence of lithospheric mantle buoyancy on density variations resulting from the advection-diffusion balance considering a wide range of tectonic convergence rates and different lithospheric mantle chemical compositions," said Kittiphon Boonma.

Researchers performed several simulations with the new model considering three different types of continental lithosphere, with an age range between 2.5 Ga and 1 Ga year, and two oceanic lithospheres aged 120 and 30 milion year old. They considered six different convergence rates between 1 and 80 mm/year. Simulations were aimed to observe the effect of the different collision rates and compositions on the lithospheric mantle density.

"In subduction or continental collision processes, there are two opposite effects that affect the mantle density. Density increases due to pressure increases but, at the same time, it tends to decrease due to the temperature increase produced by the depth. The predominance of one of these two effects will depend on the convergence velocity. Moreover, the mantle density depends also on its own chemical composition and it has been observed that it decreases with the age," explains Manel Fernandez, co-author of the study.

The model outcomes showed that the oldest and thickest continental lithospheric mantle (Archon) was less dense than the asthenosphere and avoided the sinking. At low and moderate convergence rates, researchers found that the two other types of continental lithospheric mantle shifted from sinking to stay stables due to their thinner thicknesses and to the loss of density induced by the temperature increases due to the depth. Last, the two different types oceanic lithosphere always sank, whatever the applied convergence rate was, due to their bigger density derived from it composition.

"According to these results, the faster the convergence rate between two continents, the bigger the probability that one of them delaminates or sinks towards the mantle," explains Daniel Garcia-Castellanos.

"Results suggest an explanation on why the young plates often sinks easily into the mantle, being recycled in the mantle while cratons (oldest continental regions) seem to resist better the changes in tectonic forces during Earth's evolution and they are less prone to subduct or delaminate," said Garcia-Castellanos.

Source: Institue of Earth Sciences Jaume Almera [December 19, 2019]

* This article was originally published here

New insights into the formation of Earth's crust

New research from Mauricio Ibanez-Mejia, an assistant professor of Earth and environmental sciences at the University of Rochester, and Francois Tissot, an assistant professor of geochemistry at the California Institute of Technology, gives scientists better insight into the geological processes responsible for the formation of Earth's crust.

New insights into the formation of Earth's crust
Zircon crystals, composed of silicon, oxygen and zirconium
[Credit: Parent Gery/WikiCommons]
In a paper published in the journal Science Advances, Ibanez-Mejia and Tissot studied the isotopes of the element zirconium. Most elements in the periodic table have multiple isotopes; that is, different atoms of the same element can have different masses due to the varying number of sub-atomic particles in their nuclei.

Researchers have traditionally assumed that processes occurring within the solid Earth, particularly in high-temperature environments such as those found in volcanoes and magma chambers, do not have the ability to 'fractionate'--distribute unevenly--isotopes of the heavy elements amongst solids and liquids because of the isotopes' minute differences in mass.

In the study, the researchers showed that stable isotopes of the element zirconium, a heavy transition metal, can be fractionated by magnitudes much larger than those previously thought and predicted by theory.

"This changes our view of how this element behaves in the solid Earth," Ibanez-Mejia says. "By recognizing this variability, we developed a tool that can help us gain further insights into the changing chemistry of magmas as they crystallize within Earth's crust."

Author: Lindsey Valich | Source: University of Rochester [December 18, 2019]

* This article was originally published here

Why some planets eat their own skies

For many years, for all we knew, our solar system was alone in the universe. Then better telescopes began to reveal a treasure trove of planets circling distant stars.

Why some planets eat their own skies
Artist's impression of an exoplanet smaller than Neptune. A new study suggests a reason why such planets rarely grow
larger than Neptune: the planet’s magma oceans begin to eat the sky [Credit: NASA/ESA/G. Bacon (STScI)/
L. Kreidberg; J. Bean (U. Chicago)/H. Knutson (Caltech)]
In 2014, NASA's Kepler Space Telescope handed scientists a smorgasbord of more than 700 brand-new distant planets to study—many of them unlike what we had previously seen. Instead of gas giants like Jupiter, which earlier surveys had picked up first because they are easier to see, these planets were smaller and mostly rock by mass.

Scientists noticed that there were lots of these planets about the size of or just larger than Earth, but there was a steep cutoff before planets reached the size of Neptune. "This is a cliff edge in the data, and it's quite dramatic," said University of Chicago planetary scientist Edwin Kite. "What we have been puzzling over is why planets would tend to stop growing beyond about three times Earth's size."

In a paper published in Astrophysical Journal Letters, Kite and colleagues at Washington University, Stanford University, and Penn State University offer an innovative explanation for this drop-off: The oceans of magma on the surface of these planets readily absorb their atmospheres once planets reach about three times the size of Earth.

Kite, who studies the history of Mars and the climates of other worlds, was well-positioned to study the question. He thought the answer might hinge on a little-studied aspect of such exoplanets. Most of the planets slightly smaller than the drop-off size are thought to have oceans of magma on their surfaces—great seas of molten rock like the ones that once covered Earth. But instead of solidifying as ours did, these are kept hot by a thick blanket of hydrogen-rich atmosphere.

"So far, almost all models we have ignore this magma, treating it as chemically inert, but liquid rock is almost as runny as water and very reactive," said Kite, an assistant professor in the Department of Geophysical Sciences.

The question Kite and his colleagues considered was whether, as the planets acquired more hydrogen, the ocean might begin to "eat" the sky. In this scenario, as the planet acquires more gas, it piles up in the atmosphere, and the pressure at the bottom where the atmosphere meets the magma starts to build. At first, the magma takes up the added gas at a steady rate, but as the pressure rises, the hydrogen starts to dissolve much more readily into the magma.

"Not only that, but the little bit of the added gas that stays in the atmosphere raises the atmospheric pressure, and thus an even greater fraction of later-arriving gas will dissolve into the magma," Kite said.

Thus the planet's growth stalls out before it reaches the size of Neptune. (Because the majority of the volume of these planets is in the atmosphere, shrinking the atmosphere shrinks the planets.)

The authors call this the "fugacity crisis," after the term that measures how much more readily a gas dissolves into a mixture than what would be expected based on pressure.

The theory fits well with existing observations, Kite said. There are also several markers that astronomers could look for in future. For example, if the theory is correct, planets with magma oceans that are cold enough to have crystallized on the surface should display different profiles, since this would prevent the ocean from absorbing so much hydrogen. Ongoing and future surveys from TESS and other telescopes should give astronomers more data with which to work.

"Nothing like these worlds exists in our solar system," said Kite. "Although our work suggests a solution to one of the puzzles posed by sub-Neptune exoplanets, they still have a lot to teach us!"

Author: Louise Lerner | Source: University of Chicago [December 18, 2019]

* This article was originally published here

Sunhoney Prehistoric Recumbent Stone Circle, Aberdeenshire, Scotland, 20.12.19.

Sunhoney Prehistoric Recumbent Stone Circle, Aberdeenshire, Scotland, 20.12.19.

* This article was originally published here

So who's the most (indigenous) European of us all?

Basically, the first map below reveals the answer. It shows the spread of a European specific cluster from a global-wide ADMIXTURE analysis at K=8 (eight ancestral populations assumed), which I call "North European". Thus, genetically, the most European populations are found around the Baltic Sea, and in particular in the East Baltic region. In my genome collection, samples from Lithuania clearly and consistently score the highest percentages in ADMIXTURE clusters specific to Europe. However, I suspect that if I had Latvians with no known foreign ancestry going back more than four generations, they'd come out the "most European". Hopefully we can test that in the near future.

Below are the fifteen Eurogenes sample sets that scored the highest levels of membership in the North European cluster. The list only includes groups with five or more individuals present in the analysis, so some populations, like Estonians or Danes, weren't included, even though they easily made the cut. The spreadsheet with all the results from this run can be seen here. A table of Fst (genetic) distances between the eight clusters is available here.

Lithuanians 77%
Finns 74%
Belorussians 70%
Swedes 69%
Norwegians 68%
Kargopol Russians 68%
Russians 68%
Poles 68%
Erzya 66%
Ukrainians 66%
Moksha 66%
Orcadians 63%
HapMap Utah Americans (CEU) 63%
Irish 63%
British 62%

So why did I pick the results from K=8, and not some other K, like 2, 10, or 25? Well, it's not possible to evaluate who is more European without a European-specific cluster (ie. modal in Europeans, with a low frequency outside of Europe). Provided that a decent number and range of global and West Eurasian samples are used in the analysis, such clusters begin appearing at around K=5 or K=6, and start breaking up into local clusters from about K=9. I found that runs below K=8 produced European clusters that spilled too generously outside of the borders of Europe. On the other hand, runs above K=8 produced European clusters that weren't representative of enough European groups (ie. too localized). But the European cluster from K=8 was pretty much perfect, and I think that's obvious from the map. In fact, I can hardly believe how well it fits the modern geographic concept of Europe - north of the Mediterranean and west of the Urals. Amazing stuff.

There are two other clusters that show up across Europe in non-trivial amounts - Mediterranean and Caucasus (see maps below). These can also be thought of as native European clusters, since they've been on the continent for thousands of years. However, their peak frequencies are found in West Asia, so they're not particularly useful signals of European-specific ancestry.

So what do these three clusters show exactly? They represent certain allele frequencies in modern populations, and in fact, these can change fairly rapidly due to admixture, selection, and genetic drift. So claiming that such clusters represent pure ancient populations is unlikely to be true in most cases, if ever. However, I don't think there's anything wrong in saying that, when robust enough, they can be thought of as signals of ancestry from relatively distinct ancestral groups.

Indeed, anyone who's read up on the prehistory of Europe, knows that there are three general Neolithic archeological waves to consider when trying to untangle the story of the peopling of Europe. These are Mediterranean Neolithic, Anatolian Neolithic and Forest Neolithic (for example, see here).

Mediterranean Neolithic refers to a series of migrations from West Asia via the Mediterranean and its coasts. The areas most profoundly affected by these movements include the islands of Sardinia and Corsica, and the Southwest European mainland. Anatolian Neolithic describes migrations into Europe from modern day Turkey, mostly into the Balkans, but also as far as Germany and France. At the moment, Forest Neolithic of Northeastern Europe is something of a mystery. However, the general opinion is that it was largely the result of native Mesolithic hunter-gatherers adopting agriculture.

Obviously, it's very difficult to dismiss the correlations between these three broad archeological groups and the European and two European/West Asian clusters produced in my K=8 ADMIXTURE analysis. Is it a coincidence that the Mediterranean cluster today peaks in Sardinia, which has been largely shielded from foreign admixture since the Neolithic, and today forms a very distinct Southern European isolate? Why does the North European cluster show the highest peaks in classic Forest Neolithic territory? And why does the Caucasus cluster radiate in Europe from the southeast, which is where Anatolian farmers had the greatest impact? These can't all be coincidences, and I'm willing to bet that none of them are. I'm convinced that the three clusters from my K=8 run are strong signals from the Neolithic, and the North European cluster also from the Mesolithic.

Eventually, these issues will be settled with ancient DNA data, in a much more comprehensive way than ever possible using modern genomes. We've already seen some preliminary results, mostly from Mesolithic, Neolithic and Bronze Age sites around Europe, so perhaps it's useful to ask whether my ADMIXTURE analysis and commentary here mirror these early findings? I think they do. For instance, here's an interesting conclusion regarding the East Baltic area from a study on ancient Scandinavian mtDNA by Malmström et al.

Through analysis of DNA extracted from ancient Scandinavian human remains, we show that people of the Pitted Ware culture were not the direct ancestors of modern Scandinavians (including the Saami people of northern Scandinavia) but are more closely related to contemporary populations of the eastern Baltic region. Our findings support hypotheses arising from archaeological analyses that propose a Neolithic or post-Neolithic population replacement in Scandinavia [7]. Furthermore, our data are consistent with the view that the eastern Baltic represents a genetic refugia for some of the European hunter-gatherer populations.

I suppose there will be people wondering why I didn't take Sub-Saharan African, East Asian, and South Asian admixtures into account in my analysis. The reason is that I wasn't looking at which group was most West Eurasian, or Caucasoid. Based on everything I've seen to date, in my own work as well as elsewhere, the most West Eurasian group would probably be the French Basques from the HGDP. However, the differences between them, and certain groups from Northeastern Europe, like Northern Poles and Lithuanians, really wouldn't be that great anyway. I might do a write up about that at some point.


- Maps by Eurogenes project member FR7

- Additional stats by Eurogenes project member DESEUK1


Helena Malmström et al., Ancient DNA Reveals Lack of Continuity between Neolithic Hunter-Gatherers and Contemporary Scandinavians, Current Biology, 24 September 2009, doi:10.1016/j.cub.2009.09.017

Noreen von Cramon-Taubadel and Ron Pinhasi, Craniometric data support a mosaic model of demic and cultural Neolithic diffusion to outlying regions of Europe, Proc. R. Soc. B published online 23 February 2011, doi: 10.1098/rspb.2010.2678

* This article was originally published here

2019 December 24 A Northern Winter Sky Panorama Image Credit...

2019 December 24

A Northern Winter Sky Panorama
Image Credit & Copyright: Tomas Slovinsky

Explanation: What stars shine in Earth’s northern hemisphere during winter? The featured image highlights a number of bright stars visible earlier this month. The image is a 360-degree horizontal-composite panorama of 66 vertical frames taken consecutively with the same camera and from the same location at about 2:30 am. Famous stars visible in the picture include Castor & Pollux toward the southeast on the left, Sirius just over the horizon toward the south, Capella just over the arch of the Milky Way Galaxy toward the west, and Polaris toward the north on the right. Captured by coincidence is a meteor on the far left. In the foreground is the Museum of the Orava Village in Zuberec, Slovakia. This village recreates rural life in the region hundreds of years ago, while the image captures a timeless sky surely familar to village residents, a sky also shared with northern residents around the world.

∞ Source: apod.nasa.gov/apod/ap191224.html

* This article was originally published here

Origin story: Rewriting human history through DNA

For most of our evolutionary history—for most of the time anatomically modern humans have been on Earth—we've shared the planet with other species of humans. It's only been in the last 30,000 years, the mere blink of an evolutionary eye, that modern humans have occupied the planet as the sole representative of the hominin lineage.

Origin story: Rewriting human history through DNA
Joshua Akey, a professor in the Lewis-Sigler Institute for Integrative Genomics, uses a research method he calls
genetic archaeology to transform how we’re learning about our past. Fossil evidence illustrates the spread
of two long-extinct hominin species, Neanderthals and Denisovans. Modern humans carry genes from
these species, indicating that our direct ancestors encountered and mated with archaic humans
[Credit: Michael Francis Reagan]
But we carry evidence of these other species with us. Lurking within our genome are traces of genetic material from a variety of ancient humans that no longer exist. These traces reveal a long history of intermingling, as our direct ancestors encountered—and mated with—archaic humans. As we use increasingly complex technologies to study these genetic connections, we are learning not only about these extinct humans but also about the larger picture of how we evolved as a species.

Joshua Akey, a professor in the Lewis-Sigler Institute for Integrative Genomics, is spearheading efforts to understand this larger picture. He calls his research method genetic archaeology, and it's transforming how we're learning about our past. "We can excavate different types of humans not from dirt and fossils but directly from DNA," he said.

Combining his expertise in biology and Darwinian evolution with computational and statistical methods, Akey studies the genetic connections between modern humans and two species of extinct hominins: Neanderthals, the classical "cave men" of paleoanthropology; and Denisovans, a recently discovered archaic human. Akey's research divulges a complex history of the intermixing of early humans, indicative of several millennia of population movements across the globe.

"There's often a divide between the researchers who go out and collect exotic samples and the researchers who do really creative theory and data analysis, and he's done both," said Kelley Harris, a former colleague of Akey's who is now an assistant professor of genome sciences at the University of Washington.

Like many of us, Akey has long been interested in how the human species evolved. "People want to learn about their past," he said. "But even more than that, we want to know what it means to be human."

This curiosity followed Akey throughout his schooling. During his graduate work at the University of Texas Health Science Center at Houston in the late 1990s, he looked at how contemporary humans in different parts of the world were genetically related to one another, and used early gene sequencing methods to try to understand these relationships.

Gene sequencers are devices that determine the order of the four chemical bases (A, T, C and G) that make up the DNA molecule. By determining the order of these bases, analysts can identify the genetic information encoded in a strand of DNA.

Since the 1990s, however, gene sequencing technology has progressed dramatically. A new technology known as next-generation sequencing came into use around 2010 and allowed researchers to study a very large number of genetic sequences in the human genome. It took 10 years to sequence the first human genome, but these new machines get whole genome sequence data from thousands of individuals in only a matter of hours. "When next-generation sequencing technology started to become the dominant force in genetics," Akey said, "that completely changed the entire field. It's hard to overstate how dramatic this technology has been."

Origin story: Rewriting human history through DNA
Joshua Akey and his team use gene-sequencing technologies to reveal new information about archaic human
lineages as well as our own evolutionary history [Credit: Sameer A. Khan/Fotobuddy]
The scale of the data that now can be analyzed has allowed researchers to address a whole slew of new questions that would not have been possible with the previous technology.

One of these questions is the relationship between modern humans and archaic humans, such as Neanderthals. In fact, this question fostered a vigorous debate about whether modern humans carried genes from Neanderthals. For many years, the opinions of researchers—both pro and con—ticked back and forth like a metronome.

Gradually, however, a few researchers—including geneticists Svante Paabo of the Max Planck Institute in Germany and his colleague Richard (Ed) Green of the University of California-Santa Cruz—began to demonstrate strong evidence that, indeed, there had been gene flow from Neanderthals to modern humans. In a 2010 paper, these researchers estimated that people of non-African ancestry had about 2% Neanderthal ancestry.

Neanderthals lived in a wide geographical swath across Europe, the Near East and Central Asia before dying out around 30,000 years ago. They lived alongside anatomically modern humans, who evolved in Africa some 200,000 years ago. The archaeological record shows that Neanderthals were adept at making stone tools and developed a number of physical traits that uniquely adapted them to cold, dark climates, such as broad noses, thick body hair and large eyes.

Following on the heels of Paabo and Green's Neanderthal research, Akey and a colleague, Benjamin Vernot, published a paper in Science looking at recovering Neanderthal sequences from the genome of modern humans. Geneticist David Reich of Harvard University published a similar paper in Nature, and, together, the two papers provided the first data employing the modern genome to investigate our link with Neanderthals.

Using the genetic variation in contemporary populations to learn about things that happened in the past involves scrutinizing the modern human genome for gene sequences that display traits expected to have been inherited from a different type of human. Akey and his colleagues then take those sequences and compare them to the Neanderthal genome, looking for a match.

Using this technique, Akey has been able to uncover a rich human legacy of genetic interconnections on a scale previously unconceived. As stated, while the available evidence suggests that non-Africans carry about 2% of Neanderthal genes, Africans, who were once believed not to have any connections with Neanderthals, actually have approximately 0.5% Neanderthal genes. Researchers have further discovered that the Neanderthal genome has contributed to several diseases seen in modern human populations, such as diabetes, arthritis and celiac disease. By the same token, some genes inherited from Neanderthals have proven beneficial or neutral, such as genes for hair and skin color, sleep patterns and even mood.

Akey has also discovered genetic fingerprints that suggest our human ancestry contains species about which we know nothing or very little. The Denisovans are a case in point. An archaic form of human, they coexisted with anatomically modern humans and Neanderthals and interbred with both before going extinct. The first evidence of their existence came in 2008 when a finger bone was discovered in Denisova Cave in the remote Altai Mountains of southern Siberia. At first the bone was assumed to be Neanderthal because the cave contained evidence of these species. Consequently, it sat in a museum drawer in Leipzig, Germany, for many years before it was analyzed. But when it was, the researchers were dumbfounded. It wasn't a Neanderthal—it was a hitherto unknown type of ancient human. "The Denisovans are the first species ever identified directly from their DNA and not from fossil data," Akey said.

Since that time, continued genetic work—much of it conducted by Akey and his colleagues—has established that the closest living relatives of Denisovans are modern Melanesians, the inhabitants of the Melanesian islands of the western Pacific—places such as New Guinea, Vanuatu, the Solomon Islands and Fiji. These populations carry between 4% and 6% of Denisovan genes, though they also carry Neanderthal genes.

Examples like this highlight one of the main features of our human lineage, Akey said, that admixture has been a defining feature of our history. "Throughout human history there's always been admixture," Akey said. "Populations split and they come back together."

While there remains a lot of debate about the Denisovans, Akey believes they most likely were closely related to Neanderthals, perhaps an eastern version who split off from the latter sometime around 300,000 or 400,000 years ago. Recently, genetic analysis of fossils from Denisova Cave has uncovered evidence of an offspring between a Neanderthal woman and a Denisovan male. The offspring was a female who lived approximately 90,000 years ago. By looking at this genetic trail, Akey and other researchers have been able to piece together a fascinating story of human evolution—one that is promising to rewrite our understanding of early human origins.

But there's so much more to discover, Akey said. "Even though we have sequenced probably 100,000 genomes already, and we have pretty sophisticated tools for looking at that variation, the more we think about how to interpret genetic variation, the more we find these hidden stories in our DNA," he said.

Author: Tom Garlinghouse | Source: Princeton University [December 19, 2019]

* This article was originally published here

Brandsbutt Decorated Pictish Symbol Stone, Aberdeenshire, Scotland, 20.12.19.

Brandsbutt Decorated Pictish Symbol Stone, Aberdeenshire, Scotland, 20.12.19.

* This article was originally published here

Fossil expands ancient fish family tree

A second ancient lungfish has been discovered in Africa, adding another piece to the jigsaw of evolving aquatic life forms more than 400 million years ago.

Fossil expands ancient fish family tree
Illustration of the newly described lungfish Isityumzi (lower right) and other Late Devonian freshwater
ecosystem creatures including an early tetrapod (Unzantsia) [Credit: Maggie Newman]
The new fossil lungfish genus (Isityumzi mlomomde) was found about 10,000km from a previous species described in Morocco, and is of interest because it existed in a high latitude (70 degrees south) or polar environment at the time.

Flinders University researcher Dr Alice Clement says the "scrappy" fossil remains including tooth plates and scales were found in the Famennian Witpoort Formation off the western cape of South Africa.

"This lungfish material is significant for a number of reasons," Dr Clement says. "Firstly it represents the only Late Devonian lungfish known from Western Gondwana (when South America and Africa were one continent). During this period, about 372-359 million years ago, South Africa was situated next to the South Pole. Secondly, the new taxa from the Waterloo Farm Formation seems to have lived in a thriving ecosystem, indicating this region was not as cold as the polar regions of today."

Dr Clement says the animal would still have been subject to long periods of winter darkness, very different to the freshwater habitats that lungfish live in today when there are only six known species of lungfish living only in Africa, South America and Australia.

Isityumzi mlomomde means "a long-mouthed device for crushing" in isiXhosa, one of the official languages of South Africa.

Around 100 kinds of primitive lungfish (Dipnoi) evolved from the early Devonian period more than 410 million years ago. More than 25 originated in Australian (Gondwanan) and others are known to have lived in temperate tropical and subtropical waters of China and Morocco in the Northern Hemisphere.

Lungfish are a group of fish most closely related to all tetrapods - all terrestrial vertebrates including amphibians, reptiles, birds and mammals.

"In this way, a lungfish is more closely related to humans than it is to a goldfish!" says Dr Clement, who has been involved in naming three other new ancient lungfish.

The paper has been published in PeerJ.

Source: Flinders University [December 19, 2019]

* This article was originally published here

Cullerlie Prehistoric Stone Circle and Cist Cairns, Aberdeenshire, Scotland, 20.12.19.

Cullerlie Prehistoric Stone Circle and Cist Cairns, Aberdeenshire, Scotland, 20.12.19.

* This article was originally published here

Beware of the "calculator effect"

Many people are getting skewed results from so called DIY admixture calculators. For instance, users from the UK often come out much more continental European than they should. Some of them actually believe that this is because they're genetically more Norman or Saxon than the average Brit.

No, the real reason is what I call the "calculator effect". This is when the algorithm gives different results to people who are part of the ADMIXTURE runs that produced the allele frequencies used by the calculators, than to those who aren't, even though both sets of users are of exactly the same origin, and should expect basically identical results.

So, is it possible to get around this calculator effect? Yes, people who aren't included in the datasets that produce the allele frequencies used by the calculators shouldn't compare their results to those who are, including the academic references used. They should only compare results to those of other calculator users. On the other hand, members of the various projects who are run as references, should only compare their results to other project members and relevant academic references.

I've put together a quick experiment to show the "calculator effect" in full force. I ran two intra-North European ADMIXTURE analyses at K=3, Test1 and Test2, and included myself (PL1) only in the former. These tests were almost identical, except for the fact that I wasn't part of the second run. I then tested my genome with calculators made from the allele frequencies from the two runs.

My calculator results for Test1 were very similar to the results I received from ADMIXTURE, and made perfect sense based on my ancestry. However, the calculator results for Test2 were way off, and basically made me look like a different sample from some other part of Europe. I even managed to score above noise level Far Eastern ancestry in the calculator version of Test2. Please note, however, that all the other individuals received almost identical scores in both tests. The results from the experiment can be seen in the spreadsheet below.

Calculator Effect K=3

I have to say I'm disappointed that no one else is talking about the calculator effect, and how to remedy it. I actually designed my Eurogenes ancestry tests for Gedmatch with this problem in mind, by only using academic references to source the allele frequencies. This means that test results for Eurogenes project members and non-members are directly comparable. Perhaps other genome bloggers can eventually do the same?

See also...

Ancient genomes and the calculator effect

* This article was originally published here

Jtest K14 - the Eurogenes Ashkenazi ancestry test

Update 19/03/2018: It's come to my attention that many people are still using the Jtest and taking the results very seriously. Indeed, perhaps too seriously.

Also, some users are doing weird stuff with the Jtest output in an attempt to estimate their supposedly "true" Ashkenazi ancestry proportions, like multiplying their Ashkenazi coefficient by three, because Ashkenazi Jews "only" score around 30% Ashkenazi in this test. Ouch! Please don't do that!

Let me reiterate that this test was only supposed to be a fun experiment. It was never meant to be the definitive online Ashkenazi ancestry test. And even as fun experiments with ADMIXTURE go, it's now horribly outdated, and probably useless for anyone with less than 15-20% Ashkenazi ancestry.

So it might be time to move on. If you really want to confirm your Jewish ancestry, either or both Ashkenazi and Sephardi, then you need to look at much more powerful and sophisticated options. One of these options is the Global25 analysis (see HERE), which can pick up minor Jewish ancestry of just a few per cent. But it's not free (USD $12), and it's a DIY test that requires a bit of time and effort to get the most out of it. Also, you'd need to send me your autosomal file so that I can estimate your Global25 coordinates. But I can help you get started and even quickly check if you have any hope at all of confirming Jewish ancestry.

If, for whatever reason, you'd rather not take advantage of the Global25 offer, because, say, you don't want to share your data with me, then it might be an idea to join the Anthrogenica discussion board and ask the experienced members there about other options [LINK].

In any case, whatever you choose to do, please remember the following points, and feel free to share them with others who are still using the Jtest:

- do not multiply your Jtest Ashkenazi score by 3 in an attempt to find your "true" Ashkenazi ancestry proportion, because this won't work for the vast majority of users

- but do compare your Jtest Ashkenazi score to those of other people of the same or very similar ancestry to yours to get a rough idea whether you might have any Ashkenazi ancestry (the Jtest population averages will be useful for this, see here)

- if you're still not sure what your Jtest results mean, then just focus on your Jtest Oracle-4 output at GEDmatch, and if you don't see AJ at the top of the oracle list, then this is a strong signal that you don't have substantial Ashkenazi ancestry

I recently learned that the new Ancestry Painting at 23andMe will include an Ashkenazi reference group. To be honest, I’m not sure there’s much value in using a genetically bottlenecked population of varied biogeographical origins as a reference in such things. Indeed, the Ashkenazi mainly descend from a few hundred founders, but carry Central European, Eastern European, Middle Eastern, African and probably many other admixtures, as evidenced by their genome-wide and uniparental markers.

That’s quite a problem, because due to their relative inbreeding, they produce strong ancestral clusters in many analyses, like in ADMIXTURE runs. However, these clusters are made up of allele frequencies from a wide range of sources and, paradoxically, it’s the relatively more outbred populations which contributed to the Ashkenazi gene pool at its formative stages that often end up showing Ashkenazi admixture in such tests, despite not having any. I've seen this happen regularly in my experiments with ADMIXTURE and STRUCTURE, and I'm pretty sure I could find an example in a peer reviewed study if I tried.

That’s just how things work with the algorithms we have available to run these sorts of tests. Nevertheless, since 23andMe is incorporating an Ashkenazi cluster into its new painting, I thought I’d try and come up with an Ashkenazi ancestry test to perhaps get a rough idea of what we might expect. I'm using ADMIXTURE in supervised mode, and basically trying to recreate clusters that have shown up in a variety of fine-scale analyses, including my ChromoPainter run of Northern European samples. It’s still a work in progress, but below are links to files that many of you might find useful..

Jtest K14 files

Jtest averages for selected populations

EUtest K13 files

EUtest averages for selected populations

The Jtest folder contains files that can be used to make an Ashkenazi ancestry test/chromosome painting with 14 Eurasian and African clusters. The EUtest folder contains the same files, except that the Ashkenazi allele frequencies have been removed. It’s useful to cross check results from both tests, mainly to see what’s hiding under the Ashkenazi admixture if it shows up in the Jtest.

Based on a few test runs today, I’d say that the noise level for the continental clusters is much less than 1%. But it rises to a few per cent for the intra-West Eurasian clusters. In other words, if you’re European, then you might score something like 0.02% in the Sub-Saharan cluster, which basically means 0%. However, you might get around 2% in the Middle Eastern cluster, even though you’re from Central Europe, and you don’t have any recent Middle Eastern ancestry. You can blame various prehistoric and historic migrations into Europe for these seemingly quirky results, and also the fact that Mesolithic Europeans were significantly Eurasian (i.e. Siberian, Amerindian and South Asian-like).

The Ashkenazi cluster is very similar to the Middle Eastern cluster in that regard. So anyone who gets an Ashkenazi score of around 2-3% either has very distant Jewish ancestry or, more likely, none at all. However, those who show more than 25% membership in that cluster are almost certainly of fully Ashkenazi ancestry, and their genomes peppered with Ashkenazi-specific chromosomal segments.

There’s really not much difference between 2% and 25%, you might say. In fact, there is if we say there is. As always, the main thing to remember is that these clusters don’t really exist, because genetic variation is clinal, so the cluster names are basically arbitrary and it’s always the relative results that matter.That’s why to really understand what your scores mean, you need to compare them with those of other users.

Obviously, it's best to compare with people from the same ethnic and/or regional groups. If the Ashkenazi + East Med scores look relatively inflated, that's a sign of recent Ashkenazi ancestry.

Feel free to use the files above for anything you want, except commercial stuff. Please note, I make no guarantees that they’ll provide accurate results for everyone. I might update this post early next week with new and/or additional files and more tips.


Update 6/10/2012: The Jtest K14 and EUtest K13 will soon be available at GEDmatch, accompanied by an "Oracle" population matching analysis and maybe even a 3D genetic map. If all goes to plan, the population matching test should be able to give a decisive yay or nay to anyone wondering whether they have recent Ashkenazi ancestry.

By the way, below is a PCA based on the Jtest averages for selected populations. It was produced by one of my project members so that we could check the reliability of the 14 "ancestral" components. The samples were classified into clusters based on their highest peaking component. So, for instance, the Scots are in the light blue Atlantic cluster, along with French Basques, because the Atlantic component dominates in both groups. However, overall, they're more similar to other samples than to each other.

As per above, the plan is that GEDmatch will soon offer a 3D genetic map based on the loadings from this PCA analysis.

Update 11/10/2012: The Jtest and EUtest are now on offer at GEDmatch. The quickest way to get there is via this link to the Ad-Mix page. Then, from the drop down menus, choose Eurogenes, followed by Jtest.

First run the Admix test to check whether your Ashkenazi admixture is significantly higher than expected for your part of the world (as per above, Jtest averages for selected populations are available here). Then move on to the Oracle analysis by pressing the relevant button at the bottom of the page.

If your Ashkenazi admixture is clearly elevated, and the top 20 single and/or mixed mode Oracle results show AJ (Ashkenazi Jews) as one of your potential matches, then it’s likely you have recent Ashkenazi ancestry.

Whether that’s the case or not, you can then move on to the Chromosome Painting feature to see where the potential Ashkenazi admixture is located in your genome. It’s useful to cross check the results with those from the Ancestry Finder at 23andMe to assess their accuracy.

As already mentioned, the EUtest is exactly the same as the Jtest, but with the Ashkenazi allele frequencies taken out. You can use this option to see what’s hiding under your Ashkenazi admixture in the Jtest. To compare your results with those of selected populations from Europe, Asia and Africa, refer to the EUtest averages sheet.

Please note: it's important to interpret the results with insight. You need to learn how the system works, pay attention to the types of populations that appear in your results, consider carefully why they might be paired with other populations, and of course study the statistics in detail. Expecting a bullseye classification at the top of the Oracle list is likely to lead to major disappointment for many people, simply because I don't have enough samples to represent all of the substructures that exist around the world, especially within countries.

I’ll try and update both tests in a few weeks, after seeing how successful the whole set up is at predicting Ashkenazi admixture and locating it in the genome. One of the main goals will be to improve the accuracy of the Oracle analysis for everyone, including New World people with Amerindian admixture.

Update 21/10/2012: Below are spatial maps of a few of the ancestral clusters from the Jtest, courtesy of project member FR7.

Update 4/12/2012: The Jtest and EUtest at GEDmatch now include a new tool called the 4-Ancestors Oracle (aka. Oracle-4), as well as the 3D PCAs I promised earlier. Oracle-4 will attempt to pinpoint your ethnic group of origin, and then also work out the most likely combinations of two, three and four ancestral populations which make up your genome. However, this doesn't mean the results will actually show your ethnic group, or those of your parents (in dual mode) or grandparents (4-way mode). They might for many people, but for others they'll reflect the best possible outcomes from the reference samples available.

Enjoy, and feel free to give feedback to John at GEDmatch if you think it might be useful (but please don't spam his account).

* This article was originally published here


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