At the end of October, our paper on gene regulation in the retina was published in Cell Reports. (We paid good money for open access, so go ahead, click the link – there’s no paywall.) Our editor asked us if we wanted to try two things to help explain our work to our broader audience. The first is Figure360, a brief video guide to one figure in our paper. This is still fairly technical; it’s how I might explain our work in a conference poster presentation.
The second way we were invited to explain our work was in an informal post on the Cell Reporter blog. Here I tried to explain what we did in a way that would make sense to my mother. (Who has a bachelor’s degree in biology, so at least I had a chance) My mother’s response: “I read it 3 times to better understand it. It is a difficult topic.” In other words, I failed to make sense…
It’s not the most jargon-free thing I’ve written, but for your edification and enlightenment, I’m posting the link here. Check it out to understand massively parallel reporter gene assays and our Goldilocks theory of gene expression.
Happening at the U of Chicago today is the ASBMB meeting “Evolution and Core Processes in Gene Regulation”. The attendees here are an eclectic mix of evolutionary geneticists, systems biologists, developmental biologists, and hard core biochemists. So far the result has been fascinating, as Ian Dworkin over at Genes Gone Wild tells us.
Follow the meeting over at #genereg, where Ian has done a great job summarizing the talks in real time.
I’ll try to chime in occasionally during today’s talks (@genologos) and put up some more in depth thoughts on my favorite bits here.
The complexity of the machinery by which our cells run is so extreme that one of the key questions in biological research is, why doesn’t the whole thing just collapse like a house of cards in a tornado? Another way of phrasing this question is to ask, where does the information come from to keep everything running smoothly?
Consider this: the crucial task of gene regulation is carried out in large part by transcription factors, regulatory proteins that recognize and bind to very short, degenerate DNA sequences located somewhere in the rough (sometimes very rough) vicinity of genes. Once they bind, transcription factors recruit the machinery that activates their target genes. (You can also have transcription factors that repress target genes.) This is all good, until you consider the fact that a human transcription factor has to find its target sequences from among the 3 billion base pairs in the human genome. Some plant and fish transcription factors have to search through genomes with more than 100 billions base pairs. So the question is, why don’t transcription factors get lost? Where are they asking for directions?
On finding needles in the genomic haystack Continue reading “The genome is a huge haystack. How do you find the needle?”