How does a cell process information? Unlike computers, with CPUs to carry out calculations, and animals, which have brains that process sensory information, cells have no centralized device for processing the many internal and external signals with which they are constantly bombarded. And yet they somehow manage just fine. The single-celled brewers's yeast, for example, can know what kind of food source is available, tell when it's hot or cold, and even find a mate.

One key way that cells sense and respond to their environment is via genetic circuits.

What has the ENOCODE project done, and how do their results change our understanding of the human genome? In Time to Rethink the Gene? I put this project into perspective by briefly outlining some past concepts of the gene and highlighting some of the ENCODE findings.

Now it's time to take a closer look at the results of the ENCODE project and their significance for our understanding of the human genome.

ENCODE's genome snapshot is unquestionably fascinating, and it suggests that some features of genome regulation that were previously viewed as exceptions to the norm are really quite common. But are these results revolutionary? Do they overturn any long-cherished notions about genes that scientists have heavily relied on in their understanding of gene regulation, as some have suggested? And do they support intelligent design? I don't think so.

What ENCODE Did

In one sense, the ENCODE project can be thought of as the third big Human Genome Project - the first project being the actual genome sequencing, and the second being the HapMap Project to extensively study genome variation in different human populations. The ENCODE project is an effort to find and study, on an encyclopedic scale, all of the functional elements in the human genome.

After the tremendous discoveries in basic biology of the last 100 years, you might think that we would understand by now what a gene is. But the big news in genome biology this week is the publication of the results of the ENCODE project, a large scale experimental (as opposed to just computational) survey of the human genome. The leaders of the ENCODE project suggest that we need to, yet again, rethink just what exactly a gene is.

Genome-wide association studies (GWAs) have received a lot of media attention in the last several months as various research groups have released over a half-dozen such studies, all focused on some of the most widespread Western diseases, including heart disease, type II diabetes, and breast cancer. (See here, here, and here for some examples.) These studies have the potential to substantially change how we understand, diagnose and treat these diseases, and they possibly signal the near-arrival of at least some of the long-promised health benefits of the Human Genome Project, although new cures are probably still many years in the future.

This week's issue of Science has a book review (subscription required unfortunately) of Michael's Behe's latest effort to defend Intelligent Design Creationism. Michael Behe's latest book, The Edge of Evolution, contains Behe's latest incarnation of his idea of irreducible complexity. A few years ago he put forward this latest argument in a paper in Protein Science (a journal which one of my mentors dismissed, maybe a little unfairly, as a "junk journal"), and he elaborates on this argument more extensively in his new book. (See a response to Behe's Protein Science paper here.)

The argument is this: Any novel function in a protein that requires two simultaneous amino acid changes is so unlikely to occur by chance that the novel function must have been designed. Since most beneficial changes in protein function would require a change of two or more amino acids, most of the varied functional proteins we see in nature must have been designed and not evolved. So for example, if a receptor for a certain hormone were, over the course of evolution, to evolve a new specificity for a different hormone, and if that new specificity required at least two amino acid changes, then such change is incredibly unlikely to occur under just natural selection and random mutation.

About two months ago I was in Steamboat Springs, Colorado, attending the Keystone Symposium on Systems Biology and Regulatory Networks. I went hoping to hear about forward-looking research that deals with some of the most fundamental outstanding questions in biology - fundamental in the sense of being relevant not just to a particular cell type or organism, but to most cells, developmental systems, or biological systems in general.

What I find most exciting about basic molecular biology today is the prospect of building a quantitative understanding of how a cell works. Many other scientists are excited about this as well, leading to the current popularity of what's being called 'systems biology.' The idea is that maybe we can understand the design principles behind a cellular process - how the behavior of a cell emerges from all of those detailed physical interactions among proteins, nucleic acids and other components of the cell. If that sounds vague to you, well, that's because it is vague. It's a nice sentiment, but I think biologists still have a hard time defining just what it is we want to learn.

I gripe about the poverty of postdoctoral scientists, but I'd rather be poor and keep my professional integrity than be lavishly paid by drug makers and lose my conscience. The NY Times has a story about psychiatrists who receive payments from drug makers, and who also just happen to have a tendency to frequently prescribe 'atypical drugs' for children with psychiatric problems.

One third of the Republican presidential candidates, when asked in their recent debate whether they believed evolution, admitted that they don't buy it. The blogosphere has already said much about this, and today the NY Times picks up the story.

According to the NIH, you can't be a systems biologist and an experimental geneticist at the same time. The NIH has issued a call for applications to:

"use systems biology approaches to investigate the mechanisms that underlie genetic determination of complex phenotypes.  These projects will combine computational modeling approaches and experimental validation of predictive models."

Last fall I had a chance to hear a presentation by Doug Berg, a microbiologist here at Washington University. Berg's work is a great combination of new technology, genomics and evolution, and it happens to also have potential medical relevance. He's studying the evolution of drug resistance in Helicobacter pylori, a usually benign bacterium that is responsible for stomach ulcers. (Recall that the Nobel Prize in medicine was awarded in 2005 to Barry Marshall and Robin Warren for their discovery of the link between H. pylori and ulcers.)

Tom Friedman, in his Friday's NY Times column (subscription required) comments on Walter Isaacson's new biography of Einstein and asks:

"If Einstein were alive today and learned science the boring way it is taught in so many U.S. schools, wouldn’t he have ended up at a Wall Street hedge fund rather than developing theories of relativity for a Nobel Prize?"

Just recently Science published the paper describing the latest primate genome - the rhesus macaque genome. (Check out Science's macaque website for some good (and free) articles on the subject.) Sequencing a large genome like this one is resource intensive (unlike microbial genomes, which are now easily and routinely sequenced), so why did scientists sequence yet another primate genome? In addition to the human genome we already have the chimp genome, and we also have several non-primate mammalian genomes - the mouse, rat, cow, dog, and opossum genomes. Is this a good use of our money? Why put in so much effort just to study evolution?