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MicroRNAs Still Do Not Support an Evolutionary "Tree of Life"

kevin.j.peterson.preferred_0.jpegAs we reported here and here in 2012, biologist Kevin Peterson at Dartmouth (pictured at right) sent shock waves through the Darwin community when he studied microRNAs and found they did not track expected evolutionary relationships as expected. Thinking that microRNAs should be clear windows on evolution because they are generally well conserved, he kept "uncovering problems, from the base of the animal tree all the way up to its crown."

Now Nature News has an update on the story. The headline and subtitle read, "Flaws emerge in RNA method to build tree of life: Study finds problems with alluringly simple way to tease out evolutionary relationships through microRNA." Amy Maxmen puts the bad news up front:

Tiny molecules that seemed to provide a powerful way to construct the tree of life may not have such a strong capability after all. A team of scientists has exposed flaws in a previously celebrated method that uses molecules called microRNAs to deduce evolutionary relationships between animals.

As well as casting doubt over some specific results published in the past few years — for example, that turtles are more closely related to lizards than to birds and alligators — the latest findings pour cold water on what seemed like a hot approach to solving some big mysteries in evolutionary biology. (Emphasis added.)

The article offers some reasons why there was such a major mismatch. Robert C. Thomson at the University of Hawaii at Manoa, for instance, wondered why his phylogenetic trees based on genetic sequences were so different from Peterson’s from microRNAs. Reconstructing his own data sets, he found that there was a strong tendency for microRNAs to drop out over time: "this result seemed to violate one of the main justifications for using microRNAs to build evolutionary trees in the first place: that it is almost always conserved across generations."

Thomson re-analyzed data sets on microRNAs and found many more microRNA losses than expected (see the PNAS paper). "The way microRNAs were being analyzed probably didn’t reflect the way they evolve," he now believes. By tweaking the method, he got better results:

Thomson and his co-authors also applied an alternative method of analyzing trees, which accommodated nuances in microRNA evolution, instead of using a method that assumes microRNA conservation through the generations. Three of the five resulting trees, including the reptile tree, more closely matched those produced by other methods.

Three out of five is pretty close to ambiguity, especially using a method relying on "nuances in microRNA evolution." This sounds more than a little like question begging. For instance, Thomson decided that Bayesian analysis is more suitable for evaluating microRNA data than parsimony, which Peterson used. He also alleged there was sampling error in Peterson’s analysis. Such questions may be matters of opinion; without Peterson’s response, we cannot judge whose assumptions should prevail.

In any event, if Thomson had solved the problems, his PNAS paper would have been a vindication for standard evolutionary trees. Instead, his purpose was to caution others from using microRNAs or any other method as a "silver bullet" for resolving relationships.

Thomson offers another possible reason for the mismatch: "The discrepancy likely results from the fact that some pieces of RNA are only expressed at particular moments in an animal’s lifetime, whereas genes in the genome are steady." That’s a testable hypothesis for explaining the losses, but will it confirm the phylogenetic trees? It looks like more detailed studies will be required to answer that.

Nature News points out that Peterson was not available for comment, but his colleague Erik Sperling is tending to agree with Thomson, now believing that "MicroRNAs are not the panacea we perhaps originally hoped." Peterson and Sperling published a new paper using more comparisons than just microRNAs. It put turtles back where they belong on the evolutionary tree, to the relief of Darwinians.

Still, if that had mopped up the mess Peterson created, Nature News would not have ended on a despairing note:

For Ken Halanych, an evolutionary biologist at Auburn University in Alabama, today’s paper provides a critical analysis of a method that he has long doubted. Why did microRNAs get so much attention? "Because we are hopeful," he says. A simple tool to decode how animals have evolved over hundreds of millions of years would certainly be nice — but it is looking unlikely that one exists.

At best, this "explains away" the microRNA mismatch. But if a "simple tool to decode how animals have evolved" does not exist, evolutionists are left with a collection of methods that either disagree with one another, or rely on ad hoc fudge factors to bring the data into agreement with expectations. That’s hardly a good situation to be in for arguing the empirical reliability of any scientific theory.

Our own previous reporting did not, of course, argue that microRNA patterns support intelligent design, as if each animal were designed with specific microRNAs for its needs. Finding microRNA patterns that roughly tracked taxonomic categories would be expected, assuming that each member of a taxon had similar needs. We were more interested in how Peterson’s findings contradicted Darwinian expectations. We concluded earlier:

Intelligent-design advocates are unsurprised by any of this, because their focus is on the origins of functional information, not unobservable prehistories imagined by assuming that a universal common ancestor gave birth to a family tree via random mutation and natural selection. Design theorists also believe in following the evidence where it leads.

Ditto.

Photo source: Dartmouth College.

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Evolution News & Science Today (EN) provides original reporting and analysis about evolution, neuroscience, bioethics, intelligent design and other science-related issues, including breaking news about scientific research. It also covers the impact of science on culture and conflicts over free speech and academic freedom in science. Finally, it fact-checks and critiques media coverage of scientific issues.

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