PNAS: 'Gaps' in DNA datasets should not be ignored

A simple statistical test shows that, contrary to current practice, "gaps" in DNA protein and sequence alignments commonly used in evolutionary biology can provide important information about changes in nucleotides and amino acids over tim.

Evolutionary biologists do this by looking at how DNA and protein sequences change over tim.

"Imagine a DNA sequence and its evolution as a sentence, replicated by different people over time," said Jeff Thorne, professor of biological sciences and statistics at NC State and co-corresponding author of the stud.

When analysts look at evolutionary DNA changes, the usual first step is to construct sequence alignment.

"Typically, when using sequence alignments for analysis, gaps within aligned columns are considered missing data and provide no information about substitutions," Thorne sai.

Thorne and colleagues created a simple statistical test to assess whether gap positions are independent of the amino acid substitution proces.

"One possibility is that the gap position provides useful information about the amino acid substitution process," Thorne sai.

The study also shows that there can be problems with the approach that typically constructs sequence alignments and then draws evolutionary conclusions based on a single optimal alignmen.

For example, if substitutions occur more frequently than gaps, researchers tend to repeatedly select substitutions over gaps when building sequence alignments, and the resulting alignment may contain too few gap.

"Sometimes our best guesses are biased," said Tae-Kun Seo, chief research scientist at the Korea Polar Research Institute and co-corresponding author of the stud.

The research, published in the Proceedings of the National Academy of Sciences, was supported by the National Science Foundation and the Korea Polar Research Institut.

Original title:

Correlations between alignment gaps and nucleotide substitution or amino acid replacement