Anthropology.net

In 2010 the draft genome for Neandertals was released by Svante Pääbo and colleagues. It was reported that European and Asian populations are between 1-4% Neandertal—but what percentage Neandertal are you?

The company known as 23andMe recently released an analysis that claims to answer precisely this question. While personal genome sequencing has not yet hit the mainstream market, 23andMe looks at SNPs, or variations in single nucleotide pairs. Through a comparison between your SNPs and those found in the Neandertal genome draft, for a couple hundred dollars you will be given a percentage. The service has been given the name “Neanderthal Ancestry Estimator.”

Computational biologist Eric Durand developed the project, and has previously worked on both the Neandertal genome draft and Denisova genetics.

I encourage you to take a look at an outline of the methodology, online in a white paper. Are we really at the point where a private company can tell us a likely percentage of our Neandertal ancestry for $207? I’ll let you be the judge.

By Matthew Magnani

Today’s big anthropological headline is based upon this brand new open access PLoS One paper, “Evidence of Authentic DNA from Danish Viking Age Skeletons Untouched by Humans for 1,000 Years.” The paper is written well, has lots of controls, and establishes some protocols on how to recovery ancient DNA. Despite these good things, I think I have found some minor holes in this paper, which I’ll address in this blog post.

The above photo is of the excavation of the skeletal remains sampled in this current study. The remains come from the Gladegil burial site near Otterup, Denmark. Gladegil has yielded 3 males, 4 females, and 3 other individuals whose sex can’t be determined. Carbon-14 dating has revealed that the site is approximately 1,000 years old and is a Christian burial site. As you can see the excavators are in sterile bunny-suits, worn to prevent contamination of modern DNA during the exhuming process. I wonder if this new image of archaeologist will replace the dusty-rugged Indiana Jones type-caricature?

The authors of this paper extracted only mtDNA only from the teeth and associated artifacts, so the title of this paper is misleading, it should have been rewritten “Evidence of Authentic mtDNA…” You may not see this as a significant issue, but I think it is. Other researchers and editors have made sure titles are as accurate as possible, so why then did this one get the green light? While mtDNA is DNA, mtDNA is different from nuclear DNA. First of, there are a lot more copies of the mitochondrial genome compared to the nuclear genome, that’s because cells have one nucleus (for the most part) but many mitochondrion. The mitochondrial genome is much smaller and also is a completely different entity from the nuclear one. It is circular, whereas the nuclear genome is linear. Lastly, the nuclear genome is less stable and that makes extracting and sequencing it from any sample, ancient or not, a much more challenging task.

Anyways, mtDNA was isolated in a clean room by grinding the teeth and what not into a pulp. The highest quality reagents and kits were used, according to the authors. Another misleading aspect of this study is that the entire mtDNA genome was not sequenced, only a portion of the genome, the hyper-variable region 1 (HVR-1) was amplified by quantitative PCR. The HVR-1 is a pretty informative region of the mitochondrial genome, some haplogroups can be identified but it is by no means a high-resolution indicator. If the authors extracted the HVR-2, a region with a lot more haplogroups, the analysis woulda been much more thorough.

I didn’t find any discussion on how the samples were sequenced. Given that the HVR-1 is small, roughly 560 base pairs, I’m thinking a standard dideoxy chain terminated method was used. I guess it is so common nowadays that people don’t even write it in their preliminary publication. I didn’t check the supporting materials. The HVR-1 sequences from the skeletal were aligned based upon known Inuit mtDNA.

The DNA of everyone who was involved with the excavation, extraction, sequencing was also sequenced, to screen for any possible contamination. I give the team kudos for including that in their study. It is critical for anyone doing ancient DNA work, also forensic DNA work, to not only keep track of everyone that handled the samples but also include their DNA in the sequence analysis.

Based upon the haplogroup distribution, the samples were attributed to be of Viking ancestry. To clarify, the presence of haplogroup I and G6 have also been seen relatively higher frequencies in other Viking populations. Hg I is not observed in any ancient Italian, Spanish, British, and central European populations. Again, if HVR-2 was included, this woulda been a more robust association of ancestry…

In general this was a graceful little paper. But after reading it, I don’t see what and where the big umph of this paper is to warrant so much play in the press. There have been much more challenging successes in ancient DNA work that didn’t get as much attention as this paper has gotten. And like I said, it is ultimately a report of an isolation and sequence comparison of only 500 base pairs… which is much easier to do than a nuclear one. I’d like to have seen at least the HVR-2, that woulda given me more of a meal-deal. Perhaps more will be done is a good template for ancient DNA work? At the very least it is an effective template for how to excavated ancient-but-recent DNA and what controls to include in the analysis.

Melchior, L., Kivisild, T., Lynnerup, N., Dissing, J., Ahmed, N. (2008). Evidence of Authentic DNA from Danish Viking Age Skeletons Untouched by Humans for 1,000 Years. PLoS ONE, 3(5), e2214. DOI: 10.1371/journal.pone.0002214

PLoS Genetics has published a new population genetics paper. It summarizes the order by which the world was peopled through the use of a new statistical model. This has been a big question in anthropology, and has often relied on archaeology, linguistics, and ethnography to supplement the genetic and physical data. I don’t mean to imply that the question has been completely answered with this new paper — but it is a new approach to asking a very critical question.

The paper is titled, “Inferring Human Colonization History Using a Copying Model.” This study is based off of inheritance patterns of 2,000 SNPs from the Human Genome Diversity Project (HGDP) dataset from 2006. The dataset comes from 927 individuals from 53 different populations. Not all populations are included in this dataset, so there are gaps… But for any anthropologist out there who is interested with the tempo certain human populations radiated as well as their ancestry patterns, this open access paper is a must read.

The new “copy model” resolves much finer details because it compares the structure of chromosomes — i.e. how the haplotypes spread on a chromosome are inherited. This makes it possible to delve further back in time and identify smaller genetic contributions. You may know that other models have resorted to single loci, such as the Y-chromosome or mtDNA. It has been argued that these models oversimplify heredity. By analyzing shared parts of chromosomes across the entire human genome, the researchers believe their method can cope with much larger datasets, suggesting that over 500,000 genetic markers can be compared and contrasted in the future.

This paper has yielded both consistent and surprising results. For starters, the results are right inline with the Out of Africa model. In the video clips below, you can see that for yourself

Inferred history of the peopling of the world.

Donors are listed at the bottom in order according to the mean number of individuals that are used. Click to see the original movie in high res.

Did you noticed that the San are the beginning population? That’s obviously because the San of Southern Africa are the first population in the ordering of chromosomes. According to Spencer Wells, the San are one of the oldest, if not the oldest, peoples in the world based upon the Y-chromosome. Exactly one month ago, a study of mitochondrial genetic diversity within Africa kinda challenged this claim. But because this study used the HGDP dataset from 2006, the results are restricted to the populations included in the sample. The San gave rise to the Biaka, Bantu, and Mbuti populations which are all below the Sahara.

The last lineage to arise in Africa are the Mozabites, and based upon the 2,000 SNPs they have less in common with other African populations than the others African populations have with themselves. The authors suggest that this observation is because there was a bottleneck in the Mozabites that is not shared by any other African population.

The Mozabites gave rise to all the Central Eurasian populations in the HGDP sample. The Mozabites also gave rise to the Central European populations. The first three populations to arise in Europe are the French, Tuscans, and Italians. Several Near Eastern and Central Asian populations also contributed to the peopling of Central Europe.

East Asians have an entirely distinct source of ancestry from European peoples. The Uygurs and Hazara gave rise to Cambodian, Mongolian, Oroquen, Xibo, Yi, Tu, Daur, and Naxi people of East Asia. The Han also received their ancestry from the Xibo and other populations. Just how distinct is this cut-off? Well, less than 10% of Europeans show ancestry from the Uygurs. Almost no Europeans show ancestry from the Hazara. The authors suggest that this observation is because the East Asian populations were established independently from Europeans and only relatively recent admixture has affected the 10% Uygur-ness in European populations.

Many populations in Europe have exhibited distinct genetic, cultural, and linguistic traits such as the Basque. This study has shown that the Sardianians, Russians, Orcadians, and the Basque show strong similarities to other Europeans — but have a lot more Near Eastern and Central Asian ancestry markers than other Europeans. For example, the Basque show some of their ancestry come from the Hezhen, a far Eastern population.

The Pacific Islanders receive ancestry from the Melanesians and Cambodians — not surprising. The first Native American populations (the Colombians) share ancestry to the Hazara, Han, and Xibo, also not surprising. But since modern people were screened, the Colombians show European ancestry — it is most likely because of the outstanding European occupation of the Americas in the last 500 or so years.

The somewhat surprising finding (at least surprising to the authors, editors of the paper, and apparently the bloggers at the Spittoon) is that there’s strong Mongolian ancestry signal in the Pima people. This is distinctly differently from the Colombians, who have a much different ancestry. The authors write that this suggest independent waves of migration in the Americas which contradicts ‘the current consensus.’

I believe that this statement should be revised because a more recent paper, published after this current paper was submitted, suggests that the Americas was peopled in multiple waves. I’m kinda surprised the editors didn’t catch this. I’m also surprised the the bloggers behind the Spittoon, the 23andMe blog, didn’t catch this. They are in the population genetics and personal genomics business, I expect them to keep current on their literature. Anyways, I was talking to Razib about this and he suggested if some sort of Na-Dene phenomenon could be happening. Definitely possibly… what do you think?

Inferred history of chromosomes for individual populations

Each frame shows the path that chromosomes took from their origin in Southern Africa in reaching the population labelled in each frame. The width of each line indicates the proportion of the chromosomes that travelled by that route, with the diameter of the circle indicating the total proportion of chromosomes that went via that location (diameter of San = 1.0). Values were estimated recursively, working backwards from the labelled population to the first by assuming that the amount of genetic material passed on by each population was proportional to the number of donor individuals it contributed. Click to see the original movie in high res.

This paper is not the first to work around the single loci comparison critique, but it is successful and provides a template for others to work on. I’m really interested to see this same model applied to more SNPs and more populations.

Hellenthal, G., Auton, A., Falush, D., Przeworski, M. (2008). Inferring Human Colonization History Using a Copying Model. PLoS Genetics, 4(5), e1000078. DOI: 10.1371/journal.pgen.1000078

In 1999, hunters looking for sheep stumbled upon the remains of a man in Tatshenshini-Alsek Park, British Columbia, Canada. The man was found at the foot of a glacier. After reporting the discovery, a team of archaeologists and forensic anthropologists worked with the Champagne and Aishihik First Nations to recover the remains. His affiliation wasn’t really well known.

Several months later, carbon dating on the hat and robe found on the man was completed. The remains of the man, named Kwaday Dän Ts’inchi, was calculated to be at least 340 years old. The closer interval of Kwaday was calculated to be 160 years old. That puts his death somewhere between 1670 and 1850 AD. Because many of these indigenous people in modern day Yukon and Alaska practice an oral tradition, this date didn’t help figure out which tribe Kwaday Dän Ts’inchi belongs too.

Since 1999, not much was heard from Kwaday. But, a symposium dedicated to Kwaday Dän Ts’inchi just wrapped up this weekend in Victoria. All sorts of research has been done on Kwaday, such as analysis of the clothing, tools associated, migratory patterns, even the contents of his stomach. People shared their studies at this symposium. The most interesting research shared was an analysis of the genealogy of Kwaday Dän Ts’inchi.

The genealogy was constructed by sampling some DNA from Kwaday’s remains. The results linked Kwaday Dän Ts’inchi to 17 living people. 15 of these people self-identify with the Wolf Clan, meaning the young man was may have been a member of the Wolf Clam as well. I don’t know which genetic loci was screened, I’m guessing a basic STR marker screen, the ones used in criminology, was done. I’d like to know what was done, because the thoroughness and robusticity of the test greatly effect the results. So does the comparison pool. Who were the outgroups? And how many people was the DNA compared too?

The news article reporting this doesn’t drop names about who did this study. A shame really, the author, Murray Langdon, discusses the ethics of working on and with Native Americans, but no mention was made to who did the genetic study. If you’re out there, mystery researcher, please comment and let us know how you analyzed and compared Kwaday Dän Ts’inchi ancestry.

Here is Meredith Small, an anthropologist at Cornell University and a primatologist, who has focused her life work on observing behavior, writing a slam on DNA testing over at LiveScience. I don’t know how she gets the authority to call genetic ancestry testing a scam if she specializes in behavior.

But that’s really not the case, cause she has clearly shown, she doesn’t fully understand DNA testing. Blain Bettinger, the Genetic Genealogist, points this out to us. Here’s an example, where she sides with the opinions of Jonathan Marks,

“But, [anthropologist Jonathan] Marks points out, these companies are preying on the public because they simply don’t have enough comparative information to pinpoint a gene on a world map.”

Marks and Small, these genetic ancestry tests don’t isolate specific genes in populations. Instead, these tests mostly focus identifying haplotypes in the mitochondrial DNA which we inherit from our maternal lineage and, if we are male, our Y chromosomal DNA. Haplotypes are the unique composition of single nucleotide polymorphisms that we inherit as large fragments from our parents. They help classify us into our haplogroups. Once again, haplotypes are inherited as blocks. For example you can see how your segments of mtDNA matches up with other people who have similar haplotypes. If a population has a similar set of haplotypes, they are grouped in a haplogroup. This is how population genetics helps trace ancestry.

Some tests offer more resolution, in other words, they screen for more haplotypes, where as others are more general and can only identify down to a region of the Earth. Recently, in my PCR class, I sequenced part of my mitochondrial DNA. In the following post, I’m gonna describe to you what we can do with with this sequence and how we can tell where I came from. I hope Small and Marks will check this out.

After spitting in a tube, I isolated my DNA from my cells. Commonly, what happens next, is that a mix of primers, nucleotides, and polymerase enzyme is mixed into another tube with a small fraction of the DNA I isolated. The primers help polymerase identify and target the regions where haplogroups are, to amplify them. After running PCR, a chemical reaction where polymerase is activated and deactivated in multiple cycles, what I end up with is multiple copies of a set of haplotypes.

This is then sequenced. The sequence I get can be compared to a whole lot of other known sequences from people. If my sequence matches up with other people, we are more related than different. People from the same ethnicity tend to have similar sequences in sets of haplotypes. Here’s my sequence that I plucked out of the dLoop part of my mitochondrial DNA:

CAGATGTCGGATACAGTTCACTTTAGCTACCCCCAAGTGTTATGGGCCCGGAGCGAGGAGAGTAGCACTCTTGTGCGGGATATTGATTTCACGGAGGATGGTGGTCAAGGGACCCCTATCTGAGGGGGGTCATCCATGGGGACGAGAAGGGATTTGACTGTAATGTGCTATGTACGGTAAATGGCTTTATGTACTATGTACTGTTAAGGGTGGGTAGGTTTGTTGGTATCCTAGTGGGTGAGGGGTGGCTTTGGAGTTGCAGTTGATGTGTGATAGTTGAGGGTTGATTGCTGTACTTGCTTGTAAGCATGGGGAGGGGGTTTTGATGTGGATTGGGTTTTTATGTACTACAGGTGGTCAAGTATTTATGGTACCGTACAATATTCATGGTGGCTGGCAGTAATGTACGAAATACATAGCGGTTGTTGATGGGTGAGTCAATACTTGGGTGGG

Okay, so you’re asking, where in this string of nucleotides does it show where I’m from? This is were we must harness the comparative power of massive databases such as GenBank. Before we do, some people may think that this string is not significantly long enough to tell me about my heritage. It is… this sequence is 454 bases long, with 4 possibilities of bases per position, you can estimate that there are 4 ⁴⁵⁴ different possibilities. People who inherit this same haplotype, this set of SNPs, are related because they literally are one in 2.1638944 × 10²⁷³.

Anyways, let’s fire up GenBank, specifically BLAST, a searching algorithm to help compare an unknown sequence to known ones in the database to show you who I match up with. If you want to retrace my steps, I’m here. I pulled down the database from the choose search set, to screen all the ‘nucleotide collection.’ This will take my sequence and screen it against all nucleotides in the database. If you also optimize for megablast, a more scrutinizing algorithm, you’ll know your match had to be dead on. Now, I gotta just cut and paste my sequence and hit BLAST.

A couple seconds later, I see a list of search results. At the top of which are alignments to known haplotypes from the mtDNA. I know my primers were designed to target mtDNA, and this confirms it. And if I see correctly, my mtDNA that I inherited from my mother is a 100% match to haplotype H*, H1, H4a. Using the following map, I can see where in the world this haplotype is specific to.

So, if you look hard you can see haplotype H is prevalent in Middle Eastern and European populations. I know I’m from the middle east, born there… and my family has a long history of living there. This test confirms some of my mtDNA is from that area of the world. Of course, if I screened for my haplotypes, I suspect I’d get a stronger match to middle eastern haplotypes.

Next time you read an asinine commentary on the validity of genetic ancestry testing, please refer back to this. Sometimes the science behind it isn’t explained, and I hope that misinformation can be adjusted. This sorta stuff can be abstract even to people with a doctorate and I don’t know if I explained it well, but hell, it is a start. People, especially professional anthropologists, need to make sure they know the difference between a gene and a haplotype, before they publicize that genetic ancestry testing is a scam. It works, these same principles are used everywhere… from the law to screen for lactose tolerance in populations…. to large scale pharmacogenomic tests. And just cause some capitalizing individuals want to make a profit off of people’s innate curiosity to see where they came from, doesn’t mean it is a scam!

One last thing, this quote from Small’s piece,

“If you want to know who you are, look in the mirror. Written on your face is countless generations that have survived to reproduce, and the only thing you can realistically do at this point is thank them and then move forward.”

… makes me want to puke. Way to go, Small. You really drive home your analytical, academic nature with this example of sappiness. These tests are ‘forward’ progress. Ugh.

Coming up in the September 2007 issue of PLoS Genetics will be a unique study that reports on using a new computer algorithm to help trace the genetic ancestry of thousands of individuals in minutes, without any prior knowledge of their background. I reported on how Ancestry.com will be providing DNA tests for sale last month.

This study does not need an individual’s ancestry and background to narrow down the scope for specific DNA markers known as single nucleotide polymorphisms, or SNPs. The new algorithm needs nothing more than a DNA sample. Previous genetic data collected is used to perform and confirm the research.

Just how accurate is the study? It was 99% accurate in correctly identifying hundreds of people’s ancestry from similar and complex background, such as Chinese, Japanese, and Puerto Ricans. Petros Drineas, one of authors of the paper from the Rensselaer Polytechnic Institute discusses expanding the study,

“Now that we have found that the program works well, we hope to implement it on a much larger scale, using hundreds of thousands of SNPs and thousands of individuals.”

Algorithms are not only useful to help people understand their personal heritage, anthropologists benefit form these large scale screens to help understand where and when different populations originated and how humans evolved into such a diverse, global society.

I’ll report more on this once the paper comes out, in the mean time this was adapted from this press release.