Skip to Content

How Neandertal DNA Will Shed Light on Human Genes

Michael Egholm of 454 Life Sciences talks about his company’s ambitious project to sequence the Neandertal genome.
September 27, 2006

Neandertals, our most closely related cousins, vanished approximately 30,000 years ago, leaving only traces of their existence. Now scientists in Germany and Connecticut plan to resurrect their DNA, potentially shedding light on our own unique evolutionary path.

Collecting and analyzing DNA from fossilized bones has been notoriously difficult–ancient genetic material is often degraded and contaminated with other types of DNA. But new sequencing technologies promise to extract volumes of genetic information from this molecular stew. A unique sequencing method developed by Connecticut-based 454 Life Sciences can analyze the sequence of thousands of DNA fragments in parallel, allowing the high volume of sequencing needed for the ambitious project to sequence the Neandertal genome.

Michael Egholm, vice president of 454 Life Sciences, and a speaker at Technology Review’s Emerging Technology Conference this week, promises that the results will be exciting. Egholm and collaborators will compare the Neandertal sequence to that of humans and chimpanzees to identify uniquely human genes. The project could shed light on the evolution of human traits, such as language and complex thought. Here, Egholm tells us how researchers plan to complete the project and what they hope to find.

Technology Review: Will this be the first attempt to sequence Neandertal DNA?

Michael Egholm: Svante Pääbo of the Max Planck Institute, our collaborator on the current project, has analyzed mitochondrial DNA from Neandertal samples. He was able to infer that Neandertals and homo sapiens came from a common ancestor and split approximately half a million years ago.

For the last several years, Pääbo, who more or less invented analysis of ancient DNA, had been trying to find a way to sequence the rest of the genome. He was on the verge of abandoning the research when he got a call from 454’s founder, Jonathan Rothberg, who had always been interested in ancient DNA and was looking for the best people in the field to do an ancient DNA project.

TR: What are the biggest challenges in sequencing Neandertal DNA?

ME: There is almost none of it around–so Neandertal DNA is incredibly precious. The biggest challenge in actually sequencing the DNA is the fact that 95 percent of the genetic material in a Neandertal bone is microbial–from ancient bacteria. So when we sequence, we use brute force [running thousands of sequencing experiments in parallel to generate enough DNA sequences to separate the bacterial from the Neandertal DNA –TR]. In order to generate three billion bases of Neandertal DNA [about the length of the genome] we’ll need to generate 20 times more bases of sequence, for a total of 60 billion bases for this project.

Another big challenge is that ancient DNA is so degraded–the DNA we use comes from a 38,000-year-old bone found in a cave in Croatia. The pieces are mostly 80 to 100 bases long, which is just enough for us to make sense of it. In order to piece together the genome, we take the DNA sequence we generate and map it against the human sequence.

We also worry about contamination from human DNA. Because we’re working with a sample that is genetically so similar to us, it could be easily mixed up. We’ve spent a lot of time devising analysis to make sure we have ancient DNA. In that sense, DNA degradation is actually our friend: it gives a signature of old DNA.

TR: How will 454’s sequencing technology make this ambitious project possible?

ME: It’s simply a numbers game. Because you have to throw out 19 out of 20 of your reads [due to the presence of so much bacterial DNA], you need to be able to do a lot of sequencing. We generate a quarter of a million reads per run, while standard capillary sequencing only generates 96 reads at a time. [A “read” refers to the number of DNA fragments that can be sequenced, or read, in a single sequencing reaction.]

We have already generated a few test-runs of a million bases of Neandertal DNA. Before then, only a few hundred bases of sequence were known, so we’ve increased the knowledge of Neandertal DNA dramatically. We hope to have a paper on this published soon.

TR: What do you expect to learn from the Neandertal genome?

ME: We know something dramatic happened in modern man within the last 200,000 years, which is a long time after we split from the Neandertal genome. So we’re trying to find the so-called “human genes,” possibly the genes involved in the evolution of language, abstract thinking, and planning.

The chimp genome was recently sequenced, so scientists have been able to compare chimp and human DNA to try to figure out what makes us different–there are about 35 million base pairs that are different. Chimps and humans diverged about five million years ago, while Neandertals split only half a million years ago. So you could say they are 10 times closer to us than chimps and therefore make a better comparison.

We believe we can use the Neandertal genome as a signpost for our own genome. Our approach is to look at the 35 million base pair differences between chimp and man. Then we ask a simple question: Is Neandertal like chimp or human on those sites?

TR: How far along are you? Any early results?

ME: We’ve sequenced about seven million bases so far. Based on analysis from the first million bases, Neandertals were like humans about 96 percent of the time [meaning: at the sites of the genome where modern humans and chimps differ, the Neandertal sequence was much more likely to resemble modern humans, while it was the same as the chimp only four percent of the time.]

The parts we’re really interested in are the four percent where Neandertals are like chimps rather than humans. We hope those genes will be those that confer higher executive function. Genes for talking, cognition, or brain development would be most exciting. We imagine that as people find new genes they suspect are unique to humans and are involved in higher-order cognition, we’ll be able to compare to them the Neandertal genome and see if they are different.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.