This post is a guest contribution from John Stanton-Geddes, a postdoctoral associate in the Department of Plant Biology at the University of Minnesota. John currently studies the genetic architecture of legume-rhizobium symbiosis in Medicago truncatula, as part of the same lab group as NiB contributor Jeremy Yoder.
If you’d like to write a guest post for Nothing in Biology Makes Sense!, email Jeremy.
Two weeks ago I was fortunate to attend the Evolution Society Conference in Ottawa. I saw many great talks, missed even more great talks and had the opportunity to hobnob with many luminaries of evolutionary biology. One theme that emerged through the meeting was “The genetic basis for [insert trait here]. While this goal of mapping phenotype to genotype has been a primary goal of many evolutionary ecologists since the first QTL mapping studies, it has recently come under strong criticism, notably in a fantastic paper by Matthew Rockman in the journal Evolution last year, but also by Pritchard and Di Rienzo 2010 and in a forthcoming article by Ruth Shaw (full disclosure: Ruth was my PhD advisor) and Mike Travisano. Here’s my take on the current state of Genotype to Phenotype (G-P) research from Evolution 2012, and where I’m excited to see it go.
A final few propitious presentations from the Evolution meetings in Ottawa:
Kirsten Bowser is running puffin faeces through next-generation sequencing to identify what the adorable seabirds eat—and she’s already found some prey species that wouldn’t be easily identified just by watching what puffins bring back to their nests.
Brian Counterman showed that hybridization between subspecies of the South American butterlfy Heliconius erato with different wing patterns can transfer wing patterning between subspecies—mostly by transferring a single chunk of DNA that doesn’t code for any protein, but performs a regulatory function. What’s more, the same region is being moved between multiple pairs of hybridizing H. erato subspecies.
I arrived in Ottawa a day before the proper start of the Evolution 2012 meetings so as to attend the symposium hosted by the journal Molecular Ecology, which was almost entirely devoted to the joys of genome-scale data collected from wild populations of our favorite species—and what we can and can’t learn from it. This, readers of this blog will recall, is one of the biggest changes in our field in the last few years.
Yes, your NGS-Star has collected six scrillion SNPs—but do you know how to analyze them?
Alex Buerkle kicked things off with the intersting question of how much data, exactly, do we need? It’s easy (given the funding) to obtain a lot of DNA sequence fragments from next-generation sequencing (NGS) methods—but is it better to collect lots of data from a few individuals (and thereby have high confidence in the data) or collect less data from more individuals and accept that there will be some uncertainty in the data for any one individual? Buerkle argued that the second option is preferable; it’s possible to account for uncertainty in your analysis, but if you don’t sample enough individuals, you can miss rare gene variants.
There was a tension between confidence and uncertainty in these great big genetic datasets running through the whole symposium. Buerkle also noted that patterns of differentiation and diversity across the genomes of related species can be very complex—and in the question and answer session, it was pointed out that complexity and noise can be hard to differentiate.
The rise of big data is changing ecology and evolutionary biology, along with the rest of the life sciences.
This week’s post is a guest contribution by David Hembry, who recently finished his Ph.D. at the University of California, Berkeley, working on coevolution and diversification of the obligate pollination mutualism between leafflower plants (Phyllantheae) and leafflower moths (Epicephala). He will be starting a postdoctoral fellowship at Kyoto University in the fall.
Last month, I filed my PhD dissertation, bringing to an end an intellectual and personal journey that began seven years ago in the summer of 2005. I know a lot more now than I did then, and I know a lot more about the boundaries of what I don’t know, too. But not only has my knowledge changed—evolution and ecology looks a lot different now than it did seven years ago when I was planning my dissertation research. At some point, and often multiple points, in the process of getting a PhD, everybody wonders whether what they’re doing is already out of date. Some of the transformations in the field I think I could see coming. For instance, it was clear in 2005 that computational power would keep increasing, phylogenetics would be used more and more to ask interesting questions, more and more genomes would be available for analysis, and evolutionary developmental biology was on the rise. It was unfortunately also predictable that it would be possible to study climate change in real time over PhD-length timescales. And although the 2008 global financial crisis didn’t help, it was clear that funding and jobs were going to be more competitive than they had been for our predecessors.
But there were a number of things I didn’t see coming, and which have made the field look radically different than it was back in 2005. Looking back, and looking towards the future, here are the changes I think were most important (from an evolutionist’s perspective), and what I think they mean for young scientists.