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August 30, 2008

How does gene duplication allow evolutionary innovation?

Genes with new functions do not magically appear from nowhere, or so most scientists assume. (If I thought that evolution, perhaps especially human evolution, was being guided by some supernatural individual or group, I would be looking for such “genes from nowhere� rather than whining that theories with no evidence should get equal time. Not that they want schools to teach all theories that lack evidence, of course, just ones favored by their particular religion or short-term economic interests.)

Random duplication of existing genes is often a key step, but there are at least two different ways in which gene duplication could facilitate evolutionary innovation. Once there are two copies of a gene, one could evolve a new function without interfering with the old gene’s function. Or, a single gene could evolve two different functions, doing neither of them particularly well. Then, gene duplication would allow the two copies to evolve separately, each being optimized for a different function. This week’s paper shows that evolution has followed this second pathway at least once, and perhaps often. The paper also provides yet another example of how molecular methods are providing new details on how evolution works.

“Escape from adaptive conflict after duplication in an anthocyanin pathway gene� was published in Nature by David L. des Marais – apparently not the the David J. des Marais who has published on evolution of photosynthesis – and Mark Rausher, at Duke University in North Carolina. They looked at genes whose enzyme products make pigments for flower colors.

They started by making a family tree for these genes, based on their DNA sequences. Different methods of doing this sometimes give slightly different trees, but in this case the three standard methods all gave the same result: the common ancestor of morning glories and potatoes had only one DFR gene (coding for the enzyme dihydroflavonol-4-reductases; aren’t you glad you asked?) as does potato. But, somewhere on the pathway to morning glories, this gene was duplicated.

What happened next? The methods used to develop the tree can also predict the DNA sequence of ancestors along each branch. So they could compare the DNA sequences of the duplicated genes, in modern morning glories, with the DNA sequence of the last ancestor before the duplication. The authors reasoned that, if only one gene was evolving a new function, that copy would change more than the other. Furthermore, they could distinguish random changes from those driven by selection for a particular function. There are often two or more DNA triplets that code for the same amino acid. If DNA changes that actually change amino acids in the DFR enzyme are more common than expected by random chance, that suggests natural selection for a particular function, not random drift. (This is a widely used method for detecting natural selection.) The authors reasoned that, if only one copy was evolving a new function, they would see this pattern in only one copy. Instead, they saw clear evidence that both copies were evolving, but differently, under natural selection. This suggests that the ancestral enzyme was doing two jobs, neither of them particularly well. But, once there were two copies, they could evolve separately, each specializing in a different function.

But why speculate about function, when you can measure it? Using the DNA sequence of the ancestral gene, determined from the family tree, they made some of the ancestral enzyme. (See my earlier post about using similar methods to “resurrect� proteins from ancient bacteria, measuring their optimum temperatures, and thereby inferring ancient temperatures.) Then they tested the resulting enzymes. Consistent with their hypothesis of two diverging functions, one copy works better than the ancestral version, while the other is worse.

The copy that got worse at one function (related making flower colors) presumably got better at something else. We know this because the DNA changes changed amino acids, and therefore actual enzyme function, more often than random. But we don’t know what the new function is, yet. Stay tuned!

August 28, 2008

Bias in science vs. honest errors

Some comments attached to the previous post discuss cases where scientists made statements or drew conclusions that turned out to be wrong. When should we suspect bias, as opposed to honest errors? Some scientists, of course, may have financial conflicts of interest, such as stock in tobacco or biotech companies. But strong opinions can be a source of bias even without a direct conflict of interest.

Here's an example from my own past research. For ten years, I directed the Long-Term Research on Agricultural Systems project at UC Davis. This huge field experiment included comparisons of organic and conventional farming methods. (LTRAS also compared irrigated and nonirrigated systems, which you might think would generate more interest, given how much of California's limited water supply is used by agriculture. But these comparisons never generated as much controversy, for some reason.)

The simplest way to compare conventional and organic systems would be to have the organic system exactly like the conventional one, only without the synthetic fertilizers and pesticides. But no serious organic farmer would farm that way.

So, for example, we substituted compost and nitrogen-fixing cover crops for fertilizers in the organic system (and in several alternative systems that were not strictly organic). OK, but which cover crops? A scientist biased against organic methods could tilt the balance in favor of the conventional system just be choosing a bad cover crop. A lazy scientist, or one pressed for time or money, could choose a cover crop based on published data (trying to match local conditions) or by asking a nearby organic farmer for a recommendation. Ideally, one would start with such sources but then test various alternatives before making a final decision. At LTRAS, Martha Jimenez tested four cover crop species, each at two seeding rates, and two combinations. Woollypod vetch or a mixture of vetch and peas did best in her one-year experiment, so Dennis Bryant and his crew tested these options over three years before deciding. (Vetch+peas proved to be the least risky, even though vetch-only did slightly better under ideal conditions.) Similarly, we tested Farm Advisor Tom Kearney's suggestion that we should use a different corn cultivar in systems without nitrogen fertilizer. (These tests and other results for the first nine years of this 100-year experiment have been published: see Field Crops Research 86:267; email me if you want a PDF). Without this "tuning", the organic system would have done worse than it did. Similarly, we tried to optimize each of the nine other systems at LTRAS within its particular system-specific constraints. For example, irrigating the nonirrigated system was not an option, but we did choose a wheat cultivar suited to nonirrigated conditions.

Here's where concerns about bias come in. For each system, someone who suspected us of bias could claim that we should have done more to optimize their favorite system. For example, if timing of cultivation is important in all systems, but especially in organic ones, should we always have given the organic systems priority when scheduling, even if that meant neglecting conventional ones in ways no conventional farmer would do? I know that we were committed to finding out which methods are best, rather than trying to prove preconceived ideas. But that doesn't mean we always made perfect decisions. And why should you believe me? After all, my brother Tom Denison is an organic farmer; I could be biased by that or by a graduate education and postdoctoral work in Crop Science that those not familiar with my advisers Tom Sinclair and Bob Loomis might assume was "brainwashing." (It would be more accurate to call their efforts "brain-building.")

If individual scientists or groups of scientists have conscious or unconscious biases, that may influence their conclusions and even their results. Fortunately, two solutions to this problem are built right into the fabric of science today. The first is peer review. Before a paper is published in any reputable scientific journal, it is reviewed by at least two experts with no direct connection to the authors of the paper. (We may know each other, however.) These reviewers look for problems such as unreliable methods, inconsistency between results and conclusions, and inconsistency with previously published results. The latter should not lead to rejection, but reviewers should insist the discrepancy be discussed. Note that most books, web sites, pamphlets, popular magazines, television program, and even certain "junk journals" (low citation impact is a clue) have little or no peer review. As I result, I have usually found reading such sources to be a waste of time. For example, critical details needed to assess the reliability of results are often left out.

Second, and more important, any really important conclusions need to be based on results confirmed by at least two independent groups. This is the best way to detect fraudulent or biased results: do other research groups, who may have different biases, nonetheless get the same results? This is one reason society would benefit from investing more in research. When research money is scarce, studies needed to confirm or refute important results may not get done.

With peer review and independent testing of important results, the biases and errors of individual scientists do not prevent the scientific community from reaching reliable conclusions, sooner or later.

August 21, 2008

Ask the right experts

A book review titled "Redefining 'natural' in agriculture" makes some interesting points. I haven't read the book, which is about organic farming and transgenic crops, although I know both authors slightly from my years as a professor at UC Davis. The review notes that many people have strong opinions about agricultural issues even though they lack relevant expertise. Anthony Trewavas, the author of the review, suggests that even "being a scientist doesn't qualify you to advise on any subject except your specialty."

So what is his own specialty?

A quick check of Web of Science finds he has published substantial scientific papers on "Dynamic localization of calmodulin domain protein kinase (CDPK) and its relationship to calcium signaling in growing pollen tubes" and so on, so if I ever want advice on those topics, I'll know where to turn.

When he wanders from his field of expertise things get interesting, but not necessarily credible. For example, his recent paper on "Green plants as intelligent organisms" claims that

When provided with water only once a year, young trees learn to predict when water will be provided in the future and synchronize their growth and metabolism with this period only

How exciting! Learning in plants! Except that I looked up the cited book chapter and it doesn't show that. All of the trees in the experiment described were
watered to field capacity (27% vb/v) once per year, at the beginning of the growing season, to simulate natural patterns of water availability

In other words, the trees got water at the same time of year as their ancestors, so they didn't have to learn anything new. Instead, they just executed their DNA-based programs, shaped by past natural selection.

What is missing from Trewavas impressive publication list is original field research on environmental risks or benefits of biotechnology, pesticides, etc. If we want to know which pesticides cause cancer, we need to consult cancer researchers, not chemical engineers. Similarly, if we want to know about ecological and evolutionary risks of biotechnology, we need to consult ecologists and evolutionary biologists, not genetic engineers.

Fortunately, the Ecological Society of America, a stellar group of 8000 scientists who collectively publish a significant fraction of ecological research papers worldwide, has issued a public statement on risks and benefits of transgenic crops. Individual ecologists and evolutionary biologists have published on particular biotechnology related topics, but this statement is a balanced expert overview of issues that should be considered. They make a good case for a "cautious approach" while supporting "judicious use of biotechnology."

Trewavas suggests that risks of pesticides should be compared to risks from the natural chemicals plants make to defend themselves against insects, that wider use of organic methods could worsen food shortages, and that reduced tillage methods using herbicides can reduce erosion. I agree with each of these points, to some extent, but in each case there are other factors to consider. Watch for my book on Darwinian Agriculture, sometime in 2009. Go ahead, ask whether I have published papers with original data on both evolutionary biology and agricultural field experiments.

The bird in the mirror

This week’s paper is “Mirror-induced behavior in the magpie (Pica pica): evidence of self-recognition?, by Helmut Prior and colleagues, available online in PLoS Biology.

When confronted with mirrors, apes (including humans) react very differently from monkeys. Monkeys never seem to recognize that they are seeing a reflection of themselves rather than another monkey. Recently, dolphins and elephants have been added to the list of species that can recognize themselves in mirrors and use them for self-exploration. Most other species can not. Is this because their brains are too small? Or is the tendency to self-exploration using a mirror a side-effect of a mental ability that evolved for other reasons? If the latter is true (even if there is also some minimum brain size requirement), then more species that need to pay more attention to what others of their species are doing might be more likely to evolve this mental ability.

Some birds, for example, hide food, raid each other’s food caches, and pay attention to who was around when they were hiding food. How do these birds respond to mirrors?

Prior’s group tested five individual magpies. All initially responded to the mirror as if it were another bird, but three changed their behavior and appeared to be examining themselves, like apes, dolphins or elephants. The most convincing test involved marking the birds somewhere they could see in the mirror but not directly. Two of the three birds that examined themselves in the mirror paid increased attention to a yellow mark but not to a black control mark (invisible against their feathers). They even removed the mark, as seen a video available online.

So some magpies show behaviors previously seen only in species with larger brains. This was not true of all individuals, consistent with results for some other species. What can explain this difference among individuals? Are there genetic differences in this trait? I wouldn’t expect individuals to vary genetically in traits that are consistently beneficial, but many behavioral traits are beneficial under some conditions and not others. Or is there some difference in experience among individual birds that makes them less curious or in some sense less intelligent?

August 15, 2008

What's that smell?

I'm back from vacation, which included a closeup look at this research submarine with Q&A by an expert technician, and seeing the family of our next president in a beach park. But lots of interesting work accumulated while I was gone, so my comments on this week's paper will be brief. You can read the whole thing on line.

"MHC-correlated odour preferences in humans and the use of oral contraceptives" was published in Proceedings of the Royal Society by Craig Roberts and colleagues. This is another women-sniffing-tee-shirts paper, but with some interesting new results.

One theory to explain why many species reproduce sexually (that is, by using genes from two individuals, rather than just one) is that the resulting genetic diversity decreases the chance that a disease epidemic will kill all of an individual's offspring. So we might expect females to prefer to mate with males who are more different genetically from themselves. This is apparently true for mice, with odors playing a key role in identifying genetic differences.

Similarly, women were previously reported to prefer the odors of men who differed from themselves in a particular set of genes known as the major histocompatability complex or MHC. This week's paper repeated this work, with some additional variations. Their results:

1) On average, women did not show the same preference for the odors of tee-shirts worn by men differing in MHC, relative to those with similar MHC. Apparently other studies have had mixed results. Do we need larger sample sizes, more consistency in methods, or new theoretical advances to guide future experiments?

2) When data were split by relationship status, women in relationships tended to prefer different-MHC smells, whereas unattached women preferred similar-MHC smells (see their Figure 3a). The authors suggested that this could reflect an (unconscious?) interest in having more genetic diversity in one's offspring. But could causality go in the opposite direction, with women seeking variety being more likely to form attachments?

3) Starting birth control pills shifted female preferences in favor of similar-MHC male odors.

I expect we will be hearing more about this.