Genomics euphoria: ramblings of a scientist on genetics, genomics and the meaning of life

Monthly Archives: November 2012

The triumph of mathematics (or how Nate Silver got drunk)

“Drunk Nate Silver stumbles through traffic on the Jersey Turnpike, screaming out what time each driver will get home.” @davelevitan

I know… I am late to the game… let’s chalk it up to a very busy schedule in the lab. But I want to write about the elections (queue eyes rolling).

I arrived in the US in 2006, so I was fortunate enough to witness the Obamania that swept this nation in 2008. I was quite fascinated with the dynamism of the elections and I was watching it VERY closely. That was the first time I came across, a blog started by a sports statistician named Nate Silver. His simple yet elegant model correctly predicted the election outcome in 49 out of 50 states. Despite his rise, the one-sided 2008 election was not a very good indicator for the supremacy of his model. In 2012, however, everyone believed the race to be a significantly close one. While pundits called the race a virtual toss-up, Nate Silver (and other statistician/bloggers like him, including Sam Wang of Princeton Election Consortium) were assigning very high chances of winning to president Obama throughout the campaign season. This made Nate Silver a punching bag for the TV hosts, and the punditry in general, in the run up to the elections… however, the accuracy of his statistical model proved to be quite impressive (it called all 50 states and all but one of the senate races). This made him the true winner of the elections… with his book becoming a best-seller and #drunknatesilver becoming a popular hashtag on twitter (where I got the quote in the beginning of this post from).

Nate Silver’s model is fairly simple and is very similar to the models used by other poll aggregators (who predicted pretty much the same outcomes). I think, anyone with an adequate knowledge of statistics would have come up with a comparable model. I really don’t want to talk about the model or why it worked so well (which I don’t think is very surprising to any scientists). What caught my attention however, was the extent to which people were shocked by the efficacy of these statistical models. This, I think, clearly indicates that people underestimate science and its ability to deliver. I think, as scientists, we should be worried about this. Why this is the case, I really don’t know… is it the successful war on science? Is it the botched PR dramas by fraudulent scientists? Is it going head-to-head with religion and losing? I don’t know… what I do know, is that Nate Silver is not an extraordinary researcher/mathematician. He has a job and he does it well, but what he’s doing is not groundbreaking. Nevertheless, in this election, science squared off against ideology and won a decisive victory. And we should take this as an opportunity and build upon this. How? I am again not sure… I just know that this opportunity should not be wasted.

DrunkNateSilver from Gawker

Dan Levitan started a game on Twitter: #DrunkNateSilver: things Nate Silver might do/say when he’s drunk.

Shut up and take my money

Probably everyone knows that science funding is not doing ok in the US (or anywhere else for that matter). The grant application success rates have dipped below 15% or even 10% for larger grants. Scientists have been reduced to grant writers: a long and seemingly futile endeavor that is taking more and more away from research time. Basically, people are spending more and more time explaining what they want to do, and less and less time actually doing it. This is not the only problem… with low success rates, the funding process becomes conservative, less imaginative and the word “feasible” transforms into an utterly subjective concept in the mind of the reviewer. Basically, as a young scientist, you need a proposal that is both conventional and innovative at the same time… which seems like a paradox. To be honest, scientists themselves are part of the problem… like any other fraction, every scientist comes with biases, convictions and unfounded belief-systems that clouds his/her judgment. And as the number of grants per researcher shrinks, these biases become an important factor in rankings and scoring applications. The funding problem needs to be dealt with, and I think it will be dealt with in one form or another in the next 4-5 years (things simply cannot go on like this). But those who have power to change anything have not felt the problem yet and like any other profession, the young and less-established investigators suffer the most. Now Ethan Perlstein and his colleagues have come up with a short term solution to fund their innovative ideas. They have started a project in Rockethub to crowd fund their project. I think this is a step forward in the right direction. At this point, they are half way there (their goal is 25,000 dollars)… if you are reading this, head to their project, read their statement and consider fueling this study.

Shut up and take my money

Shut up and take my money

Solving the directionality problem of RNA polymerase

Every now and then, a study appears that reminds us how little we know about some of the most basic subjects in molecular biology, while at the same time expanding the connotations associated with these seemingly simple mechanisms. A recent paper in Science by a multinational collaborative team was a perfect example of one such moment for me. The problem statement is relatively simple: how does RNA polymerase recognize the orientation of DNA; in other words, how does it know towards which direction it should be heading? The answer as I knew it, was two parts: (i) there are certain promoter elements that are in of themselves directional, meaning the transcription complex specifically recognizes one strand and not the other (e.g. the world famous lac promoter is one such example). (ii) in cases where there is no directionality coded in the DNA or the epigenome, the polymerase in fact does go the wrong way, which produces the myriad anti-sense RNAs in the cell. Granted, there might be functionalities associated with these anti-sense RNAs, however, established examples are few and far between.

The more important observation, however, is the fact that there are genetic components to when the anti-sense RNA is transcribed and when it isn’t. The aforementioned study starts from one such mutant (ssu72) and goes on to dissect the mechanism through which Ssu27 establishes directionality of the RNA polymerase complex. The results are very simple and elegant: Ssu27 is a part of a bridging complex that demarcates the start and end of the gene, and consequently the correct direction for transcription (below you can see the figure from the main paper).

Ssu72-mediated loop formation

Ssu72-mediated loop formation

Now one might be wondering why all promoters are not directional at the sequence level? The short answer, I think, is “regulation”. There are a variety molecular mechanisms through which promoter directionality can be used in gene regulation, both for the downstream gene as well as the upstream ones. For the immediate gene, losing half of initiation complexes to the wrong direction ensures lower expression, a fraction that can very well be modulated (e.g. through regulating ssu72 in this example). And for the upstream of genes (as well as the downstream one), the presence of anti-sense RNA spells some form of doom or desist.