Darwinian Time

Darwinian Time Does adaptation to an environment act as a speed bump for evolutionary change? By Andrea Gawrylewski Illustrations by JT Morrow Photos by Stephen Kennedy n a windowless room, three researchers hunker over a waist-high lab table. Dressed in white coats and latex gloves, the investigators, all members of the Washington University School of Medicine in St. Louis, get down to the business at hand: skinning frozen mice. Related Ar

Andrea Gawrylewski
Dec 31, 2008

Darwinian Time

Does adaptation to an environment act as a speed bump for evolutionary change?

By Andrea Gawrylewski

Illustrations by JT Morrow

Photos by Stephen Kennedy

n a windowless room, three researchers hunker over a waist-high lab table. Dressed in white coats and latex gloves, the investigators, all members of the Washington University School of Medicine in St. Louis, get down to the business at hand: skinning frozen mice.

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Quantitative Trait Loci (QTL) detection in inbred mouse strain crosses. Two inbred strains (small body size and large body size) are crossed to form the F1 progeny, which is intercrossed to form the F2 generation where the genes are recombined. QTLs from the F2 generation are then correlated to the mouse phenotype.

Of course, estimating the speed of evolution even in simple organisms is anything but simple. Viruses can evolve in a matter of generations, but, as always, the strength of the selective pressure in an environment affects how fast organisms adapt, so individuals of the same species in different environments will evolve at different rates.

The key assumption in Orr's (and Fisher's) analysis is that a single mutation can potentially alter any and all traits in an organism, including the advantageous ones, changes which likely won't become fixed in the population. This concept—that a mutation can affect most traits—is referred to as "universal pleiotropy." But it remains unclear how extensive pleiotropy really is. If mutations affect just a small percentage of traits, rather than the majority, then complexity would act as less of a speed bump for evolutionary change than Orr and Fisher propose. "We need to collect data on how common pleiotropy is, and what percent of characters in an organism are affected by random mutation," says Orr. "We need more of that."

In 2004, Cheverud's lab, one of the few groups collecting empirical evidence related to the speed of evolution, teamed up with evolutionary biologist Günter Wagner, at Yale University, to get a handle on exactly how many traits pleiotropy affects. The answer, they hoped, would help determine whether complexity serves as a brake on the speed at which evolution can occur.

At Wagner's suggestion, Jane Kenney-Hunt, a postdoc in Cheverud's lab, began an enormous study to correlate the effect of mutations on physiological traits in mice. She started with two already-established mouse strains that had been inbred for 100 generations for either small or large body size. Then she let the two strains inter-mate for two generations and, once the animals were necropsied and skinned, began measuring their bones. When all was said and done, Kenney-Hunt evaluated 1,000 mice for 70 different traits, including the size of individual mouse vertebrae, measuring each trait three times (a total of 210,000 measurements).

"The findings mean that the basic assumption, through the whole 20th century, that mutations are highly pleiotropic and affect many characters at the same time, is just not true." —Günter Wagner

She and other lab members then examined each mouse genome, looking at molecular markers flanking gene regions—called Quantitative Trait Loci, or QTL—for any changes in genes that were statistically associated with variations in phenotype. (See figure)

The group found 102 QTLs that were correlated with specific phenotypic changes in bone size. On average, QTLs affected about seven traits out of the 70 traits they were looking at. And 50% of QTLs affected fewer than 10% of the 70 measured characters. (The remaining QTLs affected more traits, some up to 30.) "The surprise," says Cheverud, "is the fact that a given QTL affected an average of only seven traits;" they were expecting mutations to affect larger groups of at least 15 or 20 at a time. "The findings mean that the basic assumption, through the whole 20th century, that mutations are highly pleiotropic and affect many characters at the same time, is just not true," says Wagner. The resulting paper was published in Nature last March.2 Without extensive pleiotropy, a mutation will only affect certain traits, making it less likely to derail the overall fitness of the complex organism that is fine-tuned to its environment.

But this paper is by no means the last word. Using QTL studies, researchers can attribute most traits to a broad region of the genome. But these regions can contain hundreds of genes, making it impossible to tease out the individual effects of individual mutations. Sequencing could provide a picture of what's happening at the gene level, but with a mouse experiment on a scale as large as Cheverud's, the cost and difficulty of such a project would likely be enormous, says Charles Baer, evolutionary geneticist at the University of Florida.

In response, Cheverud's team has continued breeding successive generations of mice used in the Nature paper. By allowing the mice to breed for more than 35 generations—some 10,000 animals when all is said and done—the DNA has been spliced and recombined over and over. With such slicing and dicing, the chance increases that genes which originally got transmitted together in one region are, in later generations, split up and transmitted separately. And indeed, that's what's happened: The team is now able to map traits down to a region about 1 megabase long, containing just five to 10 genes. Although they haven't finished their analysis, preliminary results are indicating that the number of traits affected by a single mutation is even smaller than was published in the Nature paper, in some cases by half.

The results in the original Nature paper are certainly suggestive, says Orr, but not conclusive in light of other empirical studies. Findings in Drosophila from the early 1990's show that two-thirds of all genes are involved in correct development and neural connectivity of the eye.3 So mutations, even in indirectly related genes, can affect a broad range of traits. "It is clear that there's a lot of pleiotropy out there; the open question is how many characters are affected," says Orr. He says he still believes pleiotropy acts as a speed limit on evolution in some capacity, but whether it's a strong limit, or weak one, is still unanswered.

James Cheverud in his office.

And can Cheverud's experiments really grasp the full effect of mutations on traits, as one would see in nature? For an organism to evolve, a mutation must become fixed in a population and that will only happen if it confers upon the organism some advantage—something that scientists can't measure in a lab. Plus, "what we call a mutation in the lab tends not to be subtle," says Leonid Kruglyak, evolutionary biologist at Princeton University, "versus what evolution sees—it could easily be that the difference in effects of a mutation on something important for survival could be on order of 1% or one-tenth of a percent" in nature—and how can we possibly account for that, even with 35 generations of lab mice?

Even if researchers achieve optimal lab conditions, they likely won't find that pleiotropy is either universal or minimal. The view that genes relate to specific characters and don't affect others is "largely defunct," says University of California, Irvine, evolutionary biologist Michael Rose. Alternatively, some biologists see the organism as totally interconnected, creating strong limits on what can change. "But neither view is true," says Rose. "Pleiotropy is extensive, but not paralyzing." In Rose's mind, evolution is neither infinitely nor negligibly flexible, creating an intermediate state where the ability of an organism, whether simple or complex, to evolve is kept in moderate check by the effect of mutations.

On a brisk day in September at Yale University, Brendan Ogbungafor, a grad student in Paul Turner's lab, fills a dozen mini-vials with RNA virus phi6. He walks across the high-ceilinged lab room to a PCR machine and inserts the vials, cranking the temperature on the machine down to just above freezing, well below the virus' comfort levels, since they are normally cultivated at 25°C. After a few minutes in the PCR he pulls out the vials, walks them back to his lab bench and begins to pour the contents onto an agar plate seeded with bacterial cells. Once the plates have been left to rest for a few days, Ogbungafor will count how many viruses have survived by counting the number of plaques on the plate, and add these data to observations that Turner's group has been making on how well viruses survive extreme temperatures. Eventually, they hope to gather enough information to support their theory that certain genotypes are able to adapt quicker to new environments than other genotypes of the same species.

In 2005, Turner's group allowed single viruses to infect a cell, multiply, and release progeny. In another treatment they let multiple viruses of the same genetic lineage simultaneously infect a single cell. The researchers let both populations replicate for 100 generations, hypothesizing that viruses that infected cells together had an advantage, because if one virus starts coding lousy proteins, it can capitalize on good proteins brought in by coinfecting viruses.

However, when the researchers examined the clones, they saw that viruses that infected a single cell together were less fit than viruses that infected cells one-by-one; specifically, harmful mutations had a more severe effect on viruses that co-infected cells.

To see if certain robust lineages (meaning, viruses that were able to survive deleterious mutations) were better at adapting to environmental changes than others, Turner's group started changing the environmental conditions that the viruses were used to—enter the extreme temperature experiments. In 2007, his group showed that certain individual RNA viruses (about 10% of a population) could survive heat shock treatments. The survivors and clones of non-survivors were bred to about 100 generations, and raised in normal conditions. Then the scientists heat-shocked both populations again. Viruses that had survivor ancestors, called the robust strain, survived at a rate of 80%, whereas less than 10% from the non-surviving strain made it.4

These findings suggest that questions of how fast a particular species, whether complex or not, evolves will be complicated by the fact that, within species, some individuals will have an easier time adapting to their changing environment. So, among Cheverud's mouse strains there may be a genetic lineage better suited for making the most of mutations that pop up, and more quickly adapting to their environments—a factor that cannot be accounted for in his experiments. "The ability to adapt to a new environment can differ among genotypes and among species," Turner says. "Evolution itself has the ability to evolve."

1. A. Orr, "Adaptation and the cost of complexity," Evolution, 54:13-20, 2000.
2. G. Wagner et al., "Pleiotropic scaling of gene effects and the 'cost of complexity,'" Nature, 452:470-3, 2008.
3. H.M. Thaker and D.R. Kankle, " Mosaic analysis gives an estimate of the extent of genomic involvement in the development of the visual system in Drosophila melanogaster," Genetics, 131:883-94, 1992.
4. R. McBride et al., "Robustness promotes evolvability of thermotolerance in an RNA virus," BMC Evolution Biol, 8:231-44, 2008.

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An evolutionary speed limit?

As a molecular biophysicist always thinking about protein structure and protein folding, Eugene Shakhnovich at Harvard University was frustrated that researchers studied the effect of evolution on protein structure, but little about the effect that protein structure had on evolution. There must be a link, he reasoned, between the stability of proteins and the mutations (a driving force of evolution) that can alter protein structure and function. For instance, can the stability of proteins play a role in evolutionary speed?

First, Shakhnovich considered the impact that mutated proteins have on organisms. "As mutations accumulate, these mutations impact the stability of proteins." You get to a point where enough mutations become lethal, because too many proteins are not folding correctly. But is there a fixed limit on how much change a protein can withstand?

In a series of mathematical models, Shakhnovich determined that more than six mutations per essential part of the genome (i.e., the percentage of the entire genome that codes for essential proteins whose failure leads to the organism's death) per genome replication, and any given mesophilic organism cannot survive (PNAS, 104:16152-7, 2007). "Molecular evolution cannot exceed this rate—if it goes higher then the organism loses all protein stability," he says. Since mutations underlie novel traits that get selected for or against by natural selection, the mutation rate plays directly into the pace of evolution. Is this a speed limit to evolution? And might this act as an alternate "brake" to the speed of evolution, besides the theoretical cost of complexity?

It turns out that RNA viruses, which are known to rapidly mutate, operate quite near this evolutionary speed limit, at about 5.5 mutations per essential part of the genome per genomic replication cycle. Complex organisms, though, operate at a mutation rate 1000-times under the speed limit. Why? Especially when mutations can be advantageous and produce traits that infer fitness?

In further modeling studies and empirical experiments underway with bacteria, Shakhnovich is seeing that, as organisms become well adapted to their environments, individuals with high rates of mutations are selected against. In addition, proteins that get selected for show a higher rate of improving from beneficial mutations, not deleterious ones, suggesting that evolution is selecting for robust proteins. In more complex organisms "we see a lot of complexity in the way proteins interact with each other - proteins that are functional. So organisms keep their evolution rates because they've evolved a solution. It's crazy to ruin it," says Shakhnovich.