While many lines of criticism have
been leveled against evolution theory over the years, one of the most ironic
reoccurring criticisms focuses in one of its greatest strengths --
flexibility. Frequently the theory is alternatively blasted for being too
rigid and an incomplete picture and then later for changing and revising.
Flexibility is a key strength of evolution theory. DailyTech
recently chronicled a major evolution observed by American researchers,
believed to be the first of its magnitude to be observed. Now
evolutionary biologists have made critical steps in revising the genetic side
of evolutionary theory to help explain one of the most daunting questions of
evolutionary history -- how prehistoric fish evolved over hundreds of millions
of years into amphibians, then reptiles, and finally mammals, and eventually
how apes evolved into humans.
European Molecular Biology Laboratory's European Bioinformatics Institute
[EMBL-EBI] researchers have discovered and fixed critical errors in genetic comparisons
between species. Genetic comparisons are frequently used to draw
evolutionary conclusions about heredity and common ancestors. However,
according to the EMBL-EBI researchers, these methods have been suffering
silently under systematic errors.
Their findings are detailed in the journal Science this
month. They don't just point out the problem either -- they provide a
solution. The researchers have developed a computational tool which
avoids the errors and offers key insight into how DNA and protein sequences
have evolved over time.
The results suggest that sequence turnover, thought to be a key component of
major evolutions, is discovered to be much more common than previously
thought. Nick Goldman, group leader at EMBL-EBI explains that while evolution
may be occurring faster, it still occurs at a maddeningly slow pace by human
standards.
Says Goldman, "Evolution is happening so slowly that we cannot study it by
simply watching it. That's why we learn about the relationships between species
and the course and mechanism of evolution by comparing genetic sequences."
Evolution is driven by changes in living organisms' DNA. DNA code
consists of sets of four "letter" bases, which code a sequence for a
specific amino acid. Mutation and thus evolution can occur when the DNA
gets "messed up" during copying with individual or several letters
incorrectly copied [substitution], lost [deletion] or gained [insertion].
The rather complex error is explained well in the researchers’
publications. They detail genetic comparison and how they go awry,
stating:
A comparison of multiple sequences
starts with their alignment. Characters in different sequences that share
common ancestry are matched and gains and losses of characters are marked as
gaps. Since this procedure is computationally heavy, multiple alignments are
often built progressively from several pairwise alignments. It is impossible,
however, to judge if a length difference between two sequences is a deletion in
one or an insertion in the other sequence. For correct alignment of multiple
sequences, distinguishing between these two events is crucial. Existing
methods, that fail to do that, lead to a flawed understanding of the course of
evolution.
Ari
Löytynoja, who developed the tool to correct these errors, states, "Our
new method gets around these errors by taking into account what we already know
about evolutionary relationships. Say we are comparing the DNA of human
and chimp and can't tell if a deletion or an insertion happened. To solve this,
our tool automatically invokes information about the corresponding sequences in
closely related species, such as gorilla or macaque. If they show the same gap
as the chimp, this suggests an insertion in humans."
Researchers have thus discovered that insertions are much more prevalent than
previously believed, while deletions are less common than previously believed.
The researchers believe that the errors came from adapting protein recognition
tools to genetics, which is broader in scope. They believe that for this
reason, additional errors in current computational methods are likely to be
found. Fortunately for evolutionary theory, it has the flexibility to
correct these errors, and some of the world's brightest minds to help with the
corrections.