Progress in science depends on new technologies, new discoveries and new ideas, probably in that order.
– Sydney Brenner (attributed to, at least)
It is a good time to study adaptation. With new technologies, new data, and new ideas proving just how little Nature appreciates the rules we’ve written for her, we are quickly learning a great deal about the process of adaptation: its causes, its mechanics, and its effects. I want to treat each of these topics, and how they surfaced in the conference, individually. But first:
The larger themes of this conference come with some pretty specific language, so I’ll make an attempt at clarification before I dive in. Adaptation (verb) refers to the change in the genetic makeup of a population that improves its fit to the environment, making it more likely that any individual critter with in that population survives to reproduce. Broadly speaking (or narrowly, depending on your point-of-view), a single organism doesn’t adapt during its lifetime because it can’t change its genetic code – those non-genetic changes in response to a new environment are collectively called plasticity – more on that in a later post. An adaptation (noun) is a physical characteristic of an organism (think behavior, development, chemistry, body shape — collectively termed phenotypes) that improves its chance of survival and reproduction. To make things more nuanced, I want to also bring to your attention both genetic architecture and genomic architecture. Genetic architecture refers to the number of genes involved in producing a phenotype (from one to many hundreds), to what degree any one of these affects said phenotype, and how the products of these genes interact with one another. In contrast, to understand genomic architecture we need to remember that ‘genes’ are physical things – stretches of DNA organized into chromosomes. Genomic architecture describes how these genes are organized relative to one another within our genomes. With any luck, this amount of jargon will suffice for now. Further jargon will with luck come with a convenient Wikipedia page to which I will conveniently link.
Nature doesn’t like to give up her secrets easily, and it’s clear that one our main impediments to understanding evolution is now a technological one. Over 150 years of study has given us a none-too-shabby idea about how evolution occurs generally; this has resulted from a lot of theory and math and other unpleasantness that, if you can get past them, give you an elegant, if somewhat pixelated, view of how living systems come to be. What is also clear is that advancements in DNA sequencing are revolutionizing how we think about evolution and adaptation at a rate that makes a peregrine falcon just seem lazy. If you’ve blinked at some point in the past five years or so, you’ve probably missed something important (for a quick refresher, try here). Given enough cash and computer-savvy, the world of DNA is now your oyster. And sequencing is now coming to the masses. Even while sequencing costs are decreasing faster than predicted by Moore’s Law, a little handiwork at the lab bench, much of it pioneered at the University of Oregon, makes sequencing your critter of choice even more accessible and informative. More on that later.
When it comes to new data, two themes come to mind. First, due to technological advances, focused study of multiple branches of the tree of life, from E. coli to fruitflies to flowers to fish, has greatly improved our understanding of both the overarching themes of evolution and adaptation and how specific branches stubbornly refuse to recognize them. From Rich Lenski’s to-hell-with-sugar adaptation in 30,000-generations-old E. coli cultures to the stickleback’s insistence that adaptation needn’t take nearly that long, our ability to use sequencing to understand the genetic and genomic architectures of adaptation was on display throughout Evolution 2013. On the flip side of this coin is the fact that some of our greatest examples of adaptation come from the ‘simplest’ of experiments; 50- or 100-year-old techniques combined with genuine ingenuity still have the potential to generate new ideas and turn grad student minds to mush. Again, Rich Lenski sets the standard, but up-and-comers like Robin Hopkins and Rowan Barrett aren’t shying away from brute-force field work and experimentation, either.
To finish this post, I’ll touch on new ideas (note that ‘new ideas’ should, in these posts, always come with the prefix ‘sort of’). In my totally biased opinion, I’ll say that the biggest idea I noted at Evolution this year is the interaction between the genetic and genomic architectures of adaptation. I was genuinely shocked to see how often this interplay appeared in talks throughout the conference*. Is the genetic architecture of adaptation simple or complex? How might genomic architecture blur this line, organizing tens to hundreds (or thousands?) of genes into manageable genomic units on which selection can act? When one population must adapt to two different environments, why does this sometimes, but only sometimes, result in speciation? These are all questions I encountered at Evolution this year and are all questions to which we only sort of know the answer. It is at once inspiring how far we’ve come in our understanding of how evolution has shaped our world and humbling that we are still struggling to answer some of the same questions that Darwin and Wallace asked a century-and-a-half ago – before DNA, before biochemistry, before genetics or inheritance**.
We should really get on that.
* I should note here that this was my first time attending Evolution. Ask me in a couple years if this is still that surprising.
** All of these existed well before Darwin or Wallace, of course. We were just hopelessly ignorant of them.