Anthropology.net

That is what University of Liverpool’s Emma Nelson probably would have said if she were to meet our hominan ancestors in person. Known to hold true in anthropoids (humans, apes and monkeys), the index (second digit) to ring (fourth digit) fingers ratio or 2D:4D is an indication of how much an individual were exposed to androgen (such as testosterone) in the womb. The more androgen you are exposed to, the longer the ring fingers are (and the shorter the index fingers are compared to the index fingers).

Nelson et al. believe that a high ratio (longer index finger, shorter ring finger) suggests monogamy (or pair-bonded) while a low ratio (shorter index finger, longer ring finger) suggests polygamy (or non pair-bonded). Simply put, individuals with high androgen level is likely to be non pair-bonded and the telltale sign is in the index and ring fingers. Also, some controversial studies had suggested that both men and women who receive high levels of androgen in the womb are more likely to be stronger, faster, and more sexually competitive.

Nelson and her researchers recently looked at the fossils of two Neandertals and one Australopithecus afarensis with complete index and ring fingers to determine their 2D:4D. They found that Neandertals had long ring fingers, suggesting that they were polygamous just like modern day primates that live in groups. A. afarensis on the other hand, had long index fingers. Nelson is puzzled by this discovery. “These were small creatures that probably lived in groups and were being eaten by predators. How do you keep from mating with different members of the group?”, she said.

Indeed it does not make sense for A. afarensis to be monogamous if they live in groups. Notice that Nelson et al. only used one A. afarensis fossil to get the 2D:4D. Perhaps it is not their fault that only one A. afarensis specimen had complete index and ring fingers but such are the dilemma of using fossil specimens to generalize a whole species.The result might just be a statistical outlier. However, I can’t speculate the result or the implications but anyone that are familiar with statistical data knows that a small sample size leads to a higher sampling error. Also what would a 2D:4D = 1 (same index and ring finger length) be?

Interesting enough, John Hawks at John Hawk’s Weblog mentioned the correlation of 2D:4D with male homosexuality (Robinson and Manning, 2000). I would know about this. In fact, my 2D:4D is indeed low.  Robinson and Manning predicted right! Maybe …

I do find both Nelson et al. and Robinson and Manning (2000) research interesting but I would like to stress that the results are mere predictors and correlations. Take it with a grain of salt. Don’t go measuring 2D:4D of your future spouse, boyfriend or girlfriend and accuse them of not being monogamous or a homosexual.

Emma Nelson and her team presented their research at this year’s Society for Vertebrate Paleontology meeting held in Bristol, United Kingdom. Read more about Emma Nelson’s research.

References:

Reilly M. 2009. Human Ancestors Conflicted on Monogamy. Discovery News. Retrieved September 25, 2009, from http://dsc.discovery.com/news/2009/09/24/human-monogamy.html

Robinson SJ. Manning JT. 2000. The ratio of 2nd to 4th digit length and male homosexuality. Evolution and Human Behavior 21(5): 333-345. [doi:10.1016/S1090-5138(00)00052-0]

Originally posted on The Prancing Papio

A summary of Yoel Rak’s talk at the last month meeting of the Paleoanthropology Society in Vancouver, Canada has surfaced in a National Geographic news article from several days ago. Yoel Rak and William Hylander analyzed the anatomy of the Neandertal face and inferred what that coulda meant as far as Neandertal dietary behavior. Did they take quaint bites like a sophisticated aristocrat or were they ruthless wide mouth ogres? If you read the title of this post you’d know the answer to that.

Rak presented his findings, specifically focusing on how the forward-positioned molars and an unusually large mandibular notches allowed Neandertals to gape widely. I’ve put up a photo of La Ferrassie 1 to you right. La Ferrassie 1 is a Neandertal skull found in 1909 in France that shows both traits.

“The scientists believe the large space behind Neandertals’ molars created a geometry that allowed them to take extremely large bites… perhaps an adaptation to the size of the food Neandertals ate, the researchers said.”

This sort of conclusion reeks of adaptionist story telling. I remember reading a similar study that analyzed the form of a horse’s mouth and concluded that it is perfectly adapted to eat apples. Just silly to think of selection and adaptation this way. Anyone one else who shares this sentiment will also appreciate Alan Mann‘s snarky commentary, which really drives home the ridiculous nature behind this study. Mann said,

“They didn’t have to put a whole [animal] leg in their mouths.”

The news article goes on to express Mann’s opinion, on how the gape size expanded as a function of brain expansion.

“What has changed is the architecture that we begin to see in modern humans, where the face and the braincase have different kinds of structural relationships…This has produced a change in our ability to open our mouths.”

Recently, I introduced related studies that showed how Neandertals may have eaten plants and how form may not equal function in regards to hominin mastication anatomy. I have some concerns with both studies, but that doesn’t mean they don’t provide applicable criticisms towards Rak and Hylander’s conclusions on Neandertal dietary behavior.

I really want the following paper that was just published in Nature, “Neanderthals in central Asia and Siberia.” The paper seems really interesting. Why? It pushes how far east Neandertals ventured, by using sequence comparisons. From the abstract,

“we determined mitochondrial DNA (mtDNA) sequences from hominid remains found in Uzbekistan and in the Altai region of southern Siberia. Here we show that the DNA sequences from these fossils fall within the European Neanderthal mtDNA variation. Thus, the geographic range of Neanderthals is likely to have extended at least 2,000 km further to the east than commonly assumed.”

If anyone has a copy of it, please send me a copy, I’d appreciate it a lot.

In exchange, I’ll preemptively offer you a tutorial to using public sequence databases to compare Neandertals. This relates to the above paper. Specifically, I’m gonna outline how similar two sequences of mitochondrial DNA extracted from Neandertals from Spain and Italy are.

If you’re interested in the intersection of bioinformatics, genomics, and paleoanthropology but haven’t really wondered how to apply these disciplines together, this should wet your appetite. All the tools I will be using are freely accessible to everyone. After this tutorial, you can basically begin to do some of the comparative research that Svante Pääbo et al. did… and you don’t need really any preface, other than DNA is made up of nucleotides and one can compare two or more sets of nucleotides to trace relationships.

If you’re an instructor, feel free to use or adapt this in one of your classes or lectures. It is a quick and easy way to introduce physical anthropology students to tools many molecular biologists have been using to compare species and genomes. So, what are we waiting for? Fire up a new browser window or tab, and follow along. I’m gonna keep it simple.

Perhaps the best bioinformatic resource out there is the NCBI’s GenBank. Lots of information can be harvested out from the free, public databases housed there. Today, we’re gonna focus on the Entrez Nucleotide database, so click the following link to jump on over there: http://www.ncbi.nlm.nih.gov/

At the top of the page you’ll see a text box. Locate where it says, “Search” and from the pull down menu, to the right, select, “Nucleotide.” Type or copy and paste in “Homo neanderthalensis” in the empty text box. Hit the ‘Go’ button.

You’ll find yourself at a landing page which says there are 1,335 nucleotide sequences in GenBank at this time, of which only 9 are core nucleotide records, for Neandertal genes. The remainder of the records are genome survey sequence records which are way beyond our needs. We’ll just keep it at the 9 core nucleotide records for now. So, if you click the 9 core nucleotide link, you should be at this rather foreign summary page.

You ask, “What the hell am I looking at? What does DQ859014 stand for?” You’re looking at GenBank’s record for Neandertal sequences and things like DQ859014 are accession numbers, a fancy word that basically means GenBank’s dewey decimal system. Each sequence that gets submitted to GenBank gets a unique catalogue number called the accession number.

For today’s purposes, I want us to be looking at the top two records, DQ859014 and DQ836132, which are both control, partial sequences of mitochondrial DNA from Neandertals found in Spain and Italy.

If you click on the first, DQ859014 you’ll find yourself at an information sheet with a lot of data displayed. The most important things I look for when I see this page are the title of the publication, the authors, the date, and then the sequence…. which is all the way at the bottom. For DQ859014, here is the sequence that was submitted in the most current revision:

ORIGIN
1 agcaaccgct atgtatttcg tacattactg ccagccacca tgaatattgt acagtaccat
61 aattacttga ctacctgcag tacataaaaa cctaatccac accaaccccc cccccccatg
121 cttacaagca agcacagcaa tcaaccttca actgtcatac atcaactaca actccaaaga
181 cgcccttaca cccactagga tatcaacaaa cctacccacc cttgacagta catagcacat
241 aaagtcattt accgtacata gcacattaca gtcaaatccc ttctcgcccc catggatgac
301 ccc
//

These 300 or so A’s, T’s, C’s, and G’s represent the order of nucleotides, or bases, that make up this sequence of Neandertal mitochondrial DNA. But the format that sequence is provided to us isn’t too useful. A more versatile and widely used format is the FASTA format. Other databases and tools use FASTA format.

No worries though, using GenBank, we can easily convert this sequence to the FASTA format by scrolling to the top of the information sheet for DQ859014. Under the Search prompt, at the top, you should see “Display.” Select that pull down menu and look for FASTA. GenBank will automatically restructure the sequence data, to the more concise FASTA format. Here’s what you should be seeing for DQ859014 in FASTA format:

>gi|111146900|gb|DQ859014.1| Homo sapiens neanderthalensis from Spain control region, partial sequence; mitochondrial
AGCAACCGCTATGTATTTCGTACATTACTGCCAGCCACCATGAATATTGTACAGTACCATAATTACTTGA
CTACCTGCAGTACATAAAAACCTAATCCACACCAACCCCCCCCCCCCATGCTTACAAGCAAGCACAGCAA
TCAACCTTCAACTGTCATACATCAACTACAACTCCAAAGACGCCCTTACACCCACTAGGATATCAACAAA
CCTACCCACCCTTGACAGTACATAGCACATAAAGTCATTTACCGTACATAGCACATTACAGTCAAATCCC
TTCTCGCCCCCATGGATGACCCC

See how the FASTA format cuts out both the spaces between every 10 nucleotides as well as the 1, 61, 121 markers? That’s much easier to work with for what I have planned. But before we jump to the next step, let’s not forget about our other sequence we wanna compare, DQ836132. If you repeat the steps to convert DQ836132 to FASTA, just like we did for DQ859014… you should get this output:

>gi|111035029|gb|DQ836132.1| Homo sapiens neanderthalensis from Italy control region, partial sequence; mitochondrial
TTCTTTCATGGGGGAGCAGATTTGGGTACCACCCAAGTATTGACTCACCCATCAACAACCGCTATGTATT
TCGTACATTACTGCCAGCCACCATGAATATTGTACAGTACCATAATTACTTGACTACCTGTAGTACATAA
AAACCTAATCCACATCAACCCCCCCCCCCCATGCTTACAAGCAAGCACAGCAATCAACCTTCAACTGTCA
TACATCAACTACAACTCCAAAGACGCCCTTACACCCACTAGGATACCAACAAACCTACCCACCCTTAACA
GTACATAGCACATAAAGCCATTTACCGTACATAGCACATTACAGTCAAATCCCTTCTCATCCCCATAGAT
GACCCCCCTCAAATAGGGGTCCCTTGAT

Cool, we now have our two sequences from Spain and Italy to compare. Let’s see how similar these two sets are by using a tool called LALIGN, which compares these two nucleotide sequences.

I didn’t bother to title both query sequences. It is up to you if you’d like to do that. Instead, I just copied the entire FASTA sequence from the Spanish Neandertal and pasted it in the first sequence query box and then repeated the same thing for the Italian but this time pasted it in the second query box. I then pressed the “Run lalign” and didn’t futz with any other settings.

The results the LALIGN spews out are the best local alignments between two sequences. In our example, DQ859014 and DQ836132, are 97.0% similar in 303 overlapping nucleotides. That’s a pretty remarkable similarity between two Neandertals from different locations… and especially remarkable since the samples were sequenced by different labs. Now, we don’t know if the sequences were from the same part of the mitochondrial genome, but since they share such a remarkable similarity, it is very probable they came from the same region.

In this miniexperiment, we see how related Neandertals from Spain and Italy were, at least in 300 or so base pairs of their mtDNA. We did that all, in about 5 minutes, without any prior bioinformatic knowledge. Pretty sweet, right? Anyways, I hope you enjoyed that. I can write up more more of these type bioinformatic and anthropology tutorials, if you’d like me to. Just let me know.