Author: Mike White

Genomes, Books, and Science Fiction

2012 – Year of Classic Science Fiction Reprints

It’s been a little too busy to do the Sunday Science Poem or finish up the Thomas Kuhn book club (we’ll finish it soon, really). In the mean time, here are some quick sci-fi thoughts: with the recent arrival of an Amazon package at my home, I’ve realized that 2012 has been an awesome year for classic science fiction reprints. Here are my acquisitions:

1) Store of the Worlds: The Stories of Robert Sheckley (NYRB classics): Nearly 400 pages, 26 stories, and a useful intro (PDF) by Alex Abramovich – this is essential reading for fans of the SF short story, especially those who like the vintage 50’s stuff. Continue reading “2012 – Year of Classic Science Fiction Reprints”

My last thoughts on the media coverage of ENCODE

I’m interested in moving on to the science of ENCODE, and to put the media coverage behind us. My final thoughts on the subject are up at the Huffington Post: “A Genome-sized Media Failure:”

This was a fantastic opportunity for scientists and science journalists to explain to the public some of the exciting and important research findings in genome biology that are changing how we think about health, disease, and our evolutionary past. But we blew it, in a big way…

[The media] stories failed us all in three major ways: they distorted the science done before ENCODE, they obscured the real significance of the ENCODE project, and most crucially, they mislead the public on how science really works.

A few supplemental points:

1) You’ve got to read John Timmer’s excellent discussion of the media coverage, filled with more details.

2) The ENCODE consortium was well-run, produced high-quality data, and measured the right biochemical activities; and I’m very interested in seeing the results.

3) However, I’m not convinced that big science was the way to go here, nor am I convinced that this will become the one dataset to rule them all as the technology rapidly changes… which means you can justify an open-ended project that has no concrete end point.

4) My opinion in point #3 could of course be wrong, but it will take time to for that to become clear.

Keeping genomes small

We read this paper in my Eukaryotic Genomes class (more than 10 years ago…sigh). The paper suggests that you need to be proactive about getting rid of pseudogenes and transposable elements if you want to keep your genome small:

High intrinsic rate of DNA loss in Drosophila

DMITRI A. PETROV, ELENA R. LOZOVSKAYA & DANIEL L. HARTL

Nature 384, 346 – 349 (28 November 1996)

Differences in deletion rate may also contribute to the divergence in genome size among taxa, the so-called ‘C-value paradox’. Two reports find a positive correlation between genome size and intron size in a variety of taxa. In addition, the reduction in the intron size in birds, whose genome size is smaller than that of other tetrapods, has been inferred to be due to multiple separate deletions scattered along the introns. It is noteworthy that pseudogenes are much rarer in birds than in mammals. These results argue that differences in genome size among related organisms may be determined primarily by the variation in the genome-wide deletion rate, and not, for instance, by different rates of insertion of transposable elements.

Genome PR is OK

There was some criticism of this video out there, but I liked it. Given how little attention the average news reader/online browser is going to devote to genomics, I think this kind of thing is just right (except for the misleading throwaway line about junk DNA).

Sure, the video hypes ENCODE as biology’s latest, greatest, development, but nobody outside the scientific community is going to know the difference between ENCODE and all of the rest of us genome biologists anyway. So basically, the video us hyping all of us.

Random Genome, Naked Genome

On Saturday, my former Center for Genome Sciences colleague Sean Eddy brought up the idea of a Random Genome Project: let’s create a random genome to serve as a null model of genome function. With this random genome, we can determine how much supposedly functional biochemical activity do we expect to see just by chance, and, among other things, we might use a random genome to explore how new functions evolve by “repurposing” (Eddy’s great term) non-functional DNA. In the comments to that post, you can read some discussion of how you might go about making a random genome.

An easier task would be to implement the random genome computationally, an idea I’ve been exploring recently, using a genome-wide binding model along the lines of the one by Wasson and Hartemink.

Why do this? Because we could explore two kinds of null models – the random genome described by Sean Eddy, and the naked genome. Continue reading “Random Genome, Naked Genome”