Evolution Runs Faster on Short Timescales
Carrie Arnold has an interesting article in Quanta:
the 1950s, the Finnish biologist Björn Kurtén noticed something unusual in the fossilized horses he was studying. When he compared the shapes of the bones of species separated by only a few generations, he could detect lots of small but significant changes. Horse species separated by millions of years, however, showed far fewer differences in their morphology. Subsequent studies over the next half century found similar effects — organisms appeared to evolve more quickly when biologists tracked them over shorter timescales.
Then, in the mid-2000s, Simon Ho, an evolutionary biologist at the University of Sydney, encountered a similar phenomenon in the genomes he was analyzing. When he calculated how quickly DNA mutations accumulated in birds and primates over just a few thousand years, Ho found the genomes chock-full of small mutations. This indicated a briskly ticking evolutionary clock. But when he zoomed out and compared DNA sequences separated by millions of years, he found something very different. The evolutionary clock had slowed to a crawl.
Baffled by his results, Ho set to work trying to figure out what was going on. He stumbled upon Kurtén’s 1959 work and realized that the differences in rates of physical change Kurtén saw also appeared in genetic sequences.
His instincts as an evolutionary biologist told him that the mutation rates he was seeing in the short term were the correct ones. The genomes varied at only a few locations, and each change was as obvious as a splash of paint on a white wall.
But if more splashes of paint appear on a wall, they will gradually conceal some of the original color beneath new layers. Similarly, evolution and natural selection write over the initial mutations that appear over short timescales. Over millions of years, an A in the DNA may become a T, but in the intervening time it may be a C or a G for a while. Ho believes that this mutational saturation is a major cause of what he calls the time-dependent rate phenomenon.
“Think of it like the stock market,” he said. Look at the hourly or daily fluctuations of Standard & Poor’s 500 index, and it will appear wildly unstable, swinging this way and that. Zoom out, however, and the market appears much more stable as the daily shifts start to average out. In the same way, the forces of natural selection weed out the less advantageous and more deleterious mutations over time.
Ho’s discovery of the time-dependent rate phenomenon in the genome had major implications for biologists. It meant that many of the dates they used as bookmarks when reading life’s saga — everything from the first split between eukaryotes and prokaryotesbillions of years ago to the re-emergence of the Ebola virus in 2014 — could be wrong. “When this work came out, everyone went ‘Oh. Oh, dear,’” said Rob Lanfear, an evolutionary biologist at the Australian National University in Canberra.
The time-dependent rate phenomenon wasn’t fully appreciated at first. For one thing, it is such a large and consequential concept that biologists needed time to wrap their heads around it. But there’s a bigger stumbling block: The concept has been all but impossible to use. Biologists have not been able to quantify exactly how much they should change their estimates of when things happened over the course of evolutionary history. Without a concrete way to calculate the shifts in evolutionary rates over time, scientists couldn’t compare dates.
Recently, Aris Katzourakis, a paleovirologist at the University of Oxford, has taken the time-dependent rate phenomenon and applied it to the evolution of viruses. In doing so, he has not only pushed back the origin of certain classes of retroviruses to around half a billion years ago — long before the first animals moved from the seas to terra firma — he has also developed a mathematical model that can be used to account for the time-dependent rate phenomenon, providing biologists with much more accurate dates for evolutionary events.
Other scientists are excited by the prospect. “It’s like Einstein’s theory of relativity, but for viruses,” said Sebastián Duchêne, a computational evolutionary biologist at the University of Melbourne. The time-dependent rate phenomenon says that the speed of an organism’s evolution will depend on the time frame over which the observer is looking at it. And as with relativity, researchers can now calculate by how much.
Viral Fossil Hunting
Katzourakis has spent his career trying to pin down the origin of HIV and other so-called “retroviruses,” which are made out of single strings of RNA.
When he looked at the mutation rates of HIV, he found that it is among the fastest-evolving viruses ever studied. The speedy mutation rate makes sense: Double-stranded molecules like DNA have molecular proofreaders that can often correct errors made during replication, but HIV and other single-strand RNA viruses don’t. Spelling errors occur on top of spelling errors.
Because of this, virologists can directly study only the recent history of viruses like this. Older samples have reached mutation saturation, with so many accumulated spelling errors that scientists can’t account for them all. Taking the history of retroviruses back thousands or millions of years would require a different way to measure mutation rates.
Katzourakis turned to another technique. . .