When analogies go bad

August 5, 2011 § 5 Comments

Lots has been written about the scientific method (and even I have written about it in a minor way in the past).  The cycle of “make hypothesis, make predictions, test predictions, revise hypothesis, repeat” is the main thing people focus on when talking about how scientific progress happens.  What’s less talked about is where the hypothesis comes from in the first place, which starts with someone (maybe you, dear reader) noticing something that needs to be explained.  This is harder than it may sound, because in order to see something that needs to be explained, you need to be able to see past the existing explanations.  You need to notice that what the textbook says should happen isn’t quite correct, instead of falling prey to the temptation to edit what you’re seeing to match what you expected to see.  You need, in short, to creatively ignore dogma.  And so it’s always interesting to me to watch what happens as a dogma begins to shift.  The shift may be of earthquake proportions, as when a new way of looking at a problem causes you to doubt everything you ever knew — what people talk about (but far too often) as a paradigm shift.  Or it may be more of an evolution of your understanding — the new idea conflicts with dogma, but there’s no fundamental reason why it should.  Your world view can accommodate the new idea without major changes; it’s just that you didn’t think it had to.

Today’s dynamic dogma has to do with the ribosome, and the shift is of the latter type.  As you all know (and if you don’t, Wikipedia will tell you) the ribosome is responsible for reading the information carried in messenger RNAs and translating it to produce proteins.  It’s a big, complicated protein/RNA complex, and we think of it as both homogeneous and hidebound, a stereotyped machine with a single job: take RNA as input, produce protein as output.  We don’t think about the ribosome as exerting any control over which RNAs get translated — or, at least, we haven’t until quite recently.  But evidence is accumulating that it can. The most recent chapter in this story is some rather dramatic evidence that mutations in a specific ribosomal subunit can cause substantial changes in the vertebrate body plan (Kondrashov et al., 2011 Ribosome-mediated specificity in Hox mRNA translation and vertebrate tissue patterning.  Cell 145 383-397).  It looks to me as if we’re going to have to start thinking about the ribosome as an active participant in the regulation of gene expression.

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What is the difference between a buffalo and a bison?*

May 5, 2011 § Leave a comment

The question of how a genotype (the arrangement of letters in DNA) maps to a phenotype (the shape and behavior of an organism) can be examined at many levels.  On the one hand, we’d like to know how small differences in DNA sequence determine differences between individual humans, such as susceptibility to disease, height, IQ, maybe musical talent… the list is long.  On the other hand, we’d like to know which DNA differences determine the crucial differences between species.  What makes the beak short or long or pointy, what makes the neck short or long, what determines the size of the average member of the species?  Many of these factors can vary significantly within a species, too: take, for example, the enormous range of size that we see in dogs, from Elwood the 9cm-high Jack Russell to Giant George the 110cm-tall Great Dane.  While some of these differences are at least partly understood — size variation in dogs has been traced to a polymorphism in the gene for the growth hormone IGF-1, for example — there are many many others that we simply don’t understand.

One of the surprising findings of the molecular age, which has become even clearer as genome sequence becomes more available, is that changes in protein coding sequences are less prevalent than changes in sequences that may affect the regulation of a gene.  This is rather irritating because (as we’ve discussed before) it’s not easy to use sequence information to predict how the expression of a gene might change.  So there’s not a great deal of information on whether and when different species use the same gene (or set of genes) at different times, or whether and when a gene is expressed to a higher level in one species relative to another.  But some of the differences between species are almost certainly encoded in the genome in this way.  There’s been particular interest in changes in timing, called heterochrony, going back to seminal discoveries in the 1980’s about heterochronic genes in C. elegans that affect the timing of developmental events.  But we don’t know how frequent such changes are.

A recent paper (Yanai et al. 2011. Mapping gene expression in two Xenopus species: Evolutionary constraints and developmental flexibility.  Developmental Cell PMID: 21497761) sets out to survey differences in gene expression between two different species of frog, Xenopus laevis and Xenopus tropicalis.  These frogs are similar in some ways — they have fat little back legs and an egg-shaped body, for example — but very different in others.  X. laevis is about twice the size of X. tropicalis, and takes about 4x as long to grow to maturity.  X. tropicalis prefers higher temperatures than X. laevis for development (28° C vs. 22°C).  On the molecular level, the largest difference is that X. laevis is tetraploid, with more or less 4 copies of every gene (presumably because two diploid cells accidentally fused), while X. tropicalis is diploid.  This makes X. tropicalis a better model for genetic studies, while X. laevis is the favored organism for biochemical studies due to the large size of its eggs (1 mm).   The most recent common ancestor for the two species lived at least 30 million years ago, so the genome sequences have undoubtedly diverged significantly: the X. tropicalis genome came out last year, but the X. laevis genome is not yet complete, so we don’t know the details of the sequence differences.

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Guest post: A new link between ontogeny and phylogeny

December 17, 2010 § Leave a comment

Jeremy Purvis writes: I once had an English professor in college who began class by writing the phrase “ontogeny recapitulates phylogeny” on the blackboard. He then began to explain—in English-professor terms—how embryos pass through stages of development that closely resemble successive stages in their own evolution. Though I can’t remember exactly, I believe this introduction was used as some sort of cross-disciplinary metaphor for one of Shakespeare’s plays, in which a certain scene in the play recapitulated the entire plotline. Obviously, I learned very little biology or literature from that experience.

I did learn a little biology, however, from a recent paper (Kalinka et al. 2010.  Gene expression divergence recapitulates the developmental hourglass model.  Nature 468, 811-4, PMID 21150996). In this paper, the authors provide some hard evidence to support a longstanding observation in developmental biology: organisms in the same phylum tend to look remarkably similar during mid-development. This interval of morphological conservation is known as the phylotypic period, and can be thought of as the waist of an hourglass: embryos of different species look most different from each other during early and late development, and — oddly — least different in the middle. The notion that ontogeny recapitulates phylogeny was discredited decades ago  — though the compelling rhythm of the phrase keeps it alive in English classes —  but the idea that there is some deep similarity (on a morphological level) between embryos of related species remains.  But how could it be true that the morphologies of embryos are more similar in the middle of development than at either end? Could it be that this stage of embryonic development is particularly complex and hard to change for some reason?  Or, is the phylotypic period some kind of mass hallucination — are the similarities superficial and unimportant?

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Eve and the tree of knowledge

June 30, 2010 § 3 Comments

Zeba Wunderlich (DePace lab) pointed me to this paper about the even-skipped (eve) stripe 2 enhancer in Drosophila. (Arnosti DN, Barolo S, Levine M, Small S. 1996. The eve stripe 2 enhancer employs multiple modes of transcriptional synergy. Development 122 205-14 PMID: 8565831), which apparently sparked a lively discussion in journal club last week.  It’s an interesting paper that seems to indicate something of a transition point for Drosophila work, namely the point at which Drosophilologists got serious about trying to understand not only which DNA sequences in an enhancer are important, but also why this particular combination of DNA sequences, in this order, produces the quantitative output that it does.  And the question is still there for the answering.  The bottom line for me, after reading this paper, is that if you had any hope that your personal genome sequence would tell you much about protein levels in the cells of your body, you should give up that hope right now. (Except in extreme cases, of course.)  This is an extraordinarily well-studied system where all the important inputs are known, and how the input levels vary from cell to cell in the wild type is also known.   Even so, a heroic amount of work produced little in the way of principles that could be used to predict how individual gene sequences (say, in individual humans) might differ in expression patterns.  And yet, there are hints in this paper that with better quantitation and the ability to detect multiple inputs and outputs at once, the problem may be tractable.  In other words, it’s a great paper to read for background on why the DePace lab, and other labs, are doing what they’re doing.

Don’t misunderstand me — your personal genome sequence, when you shell out $1000 to get it, will certainly tell you some important things.  Correlations between specific genotypes and certain types of risks, or drug responsiveness, will be increasingly easy to identify, and increasingly important.  And polymorphisms in coding sequences should be relatively easy to interpret, for the most part.  But before we can make the kinds of quantitative predictions that you might imagine as the ultimate goal of post-genomic medicine — oh look, this person has a polymorphism in one of the activator sites in the enhancer region for Bid, she’s going to have a 30% reduction in Bid expression in her breast tissue, that means that she’s right on the borderline for efficacy of cytotoxic drug X, probably better not to subject her to the nasty side-effects of drug X, let’s try drug Y instead — we’ll need a better understanding of many biological processes, transcriptional control being high on the list. « Read the rest of this entry »

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