A central tenet of
evolutionary biology is the notion of common ancestry. The theory of descent
with modification ultimately connects all organisms to a single common
ancestor. Humans, butterflies, lettuce, and bacteria all trace their lineages
back to the same primordial stock. The crucial evidence for universal common
ancestry includes homology.
Why Common Ancestry
Matters
Common ancestry is
the conceptual foundation upon which all of modern biology, including
biomedical science, is built. Because we are descended from the same ancestral
lineage as monkeys, mice, baker’s yeast, and even bacteria, we share with these
organisms numerous homologies in the internal machinery of our cells. This is
why studies of other organisms can teach us about ourselves.
Consider work on mice and yeast by Kriston McGary and colleagues (2010) in the lab of Edward Marcotte. The researchers knew that because mice and yeast are derived from a common ancestor, we find not only many of the same genes in both creatures, but many of the same groups of genes working together to carry out biological functions—what we might call gene teams. The scientists thus guessed that a good place to look for genes associated with mammalian diseases would be on mouse gene teams whose members are also teammates in yeast. Using a database of genes known to occur in both mice and yeast, McGary and colleagues first identified gene teams as sets of genes associated with a particular phenotype. In mice the phenotype might be a disease. In yeast it might be sensitivity to a particular drug. The researchers then looked for mouse and yeast gene teams with overlapping membership.
Consider work on mice and yeast by Kriston McGary and colleagues (2010) in the lab of Edward Marcotte. The researchers knew that because mice and yeast are derived from a common ancestor, we find not only many of the same genes in both creatures, but many of the same groups of genes working together to carry out biological functions—what we might call gene teams. The scientists thus guessed that a good place to look for genes associated with mammalian diseases would be on mouse gene teams whose members are also teammates in yeast. Using a database of genes known to occur in both mice and yeast, McGary and colleagues first identified gene teams as sets of genes associated with a particular phenotype. In mice the phenotype might be a disease. In yeast it might be sensitivity to a particular drug. The researchers then looked for mouse and yeast gene teams with overlapping membership.
Among the pairs of
overlapping teams they found was a mouse team of eight genes known to be
involved in the development of blood vessels (angiogenesis) and a yeast team of
67 genes known to influence sensitivity to the drug lovastatin. These teams formed
a pair because of the five genes that belonged to both. The connection between
the two teams suggested that both might be larger than previously suspected,
and that more than just five genes might play for both. In particular, the 62
genes from the yeast lovastatin team not already known to belong to the mouse
angiogenesis team might, in fact, be members. Starting with this list of 62
candidates, the researchers conducted experiments in frogs revealing a role in
angiogenesis for at least five of the genes. Three more genes on the list
turned out to have been identified already as angiogenesis genes, but had not
been flagged as such in the researchers’ database. Eight hits in 62 tries is a
much higher success rate
than would have been expected had the researchers simply chosen genes at random
and tested their influence on angiogenesis. In other words, McGary and
colleagues used genetic data from yeast, an organism with neither blood nor
blood vessels, to identify genes in mammals that influence blood vessel growth.
Researchers in Marcotte’s lab have since exploited the overlap between the
yeast lovastatin team and the mouse angiogenesis team to identify an antifungal
drug as an angiogenesis inhibitor that may be useful
in treating cancer
(Cha et al. 2012). That the theory of descent with modification is such a
powerful research tool indicates that it has a thing or two going for it.
Homology
As the fields of
comparative anatomy and comparative embryology developed in the early 1800s,
one of the most striking results to emerge was that fundamental similarities
underlie the obvious physical differences among species. Early researchers
called the phenomenon homology—literally, the study of likeness.
Richard Owen, Britain’s leading anatomist, defined homology as “the same organ
in different animals under every variety of form and function.”
Structural Homology
A famous example of
homology comes from work by Owen and by Georges Cuvier, the founder of
comparative anatomy. They described extensive similarities among vertebrate
skeletons and organs. Referring to Owen and Cuvier’s work, Darwin (1859, p.
434) wrote:
What could be more
curious than that the hand of a man, formed for grasping, that of a mole for
digging, the leg of the horse, the paddle of the porpoise, and the wing of the
bat, should all be constructed on the same pattern, and should include the same
bones, in the same relative positions?
Figure 1 |
Figure 2 |
What causes these
similarities in construction despite differences in form and function? Darwin
argued that descent from a common ancestor is the most logical explanation. He
argued that the orchids in Figure are similar because they share a common
ancestor. Likewise, the tetrapods in Figure 1 have similar forelimbs because
they are descended from a single lineage, from which they inherited the
fundamental design of their appendages.
Using Homology to
Test the Hypothesis of Common Ancestry
We can use homologous
traits shared among species to test Darwin’s hypothesis of common ancestry. We
will show the logic using evolutionary novelties shared among imaginary snail
species derived with modification from a single lineage. shows the evolutionary
history. The common ancestor is the lineage of squat-shelled blue snails at far
left. This lineage underwent speciation (1). One of the daughter lineages
persisted to the present with no further changes in its shell (2). The other
lineage evolved elongated shells (3). The lineage with elongated shells
underwent speciation (4). One daughter lineage evolved bands on its shell (5),
then persisted to the present with no further changes (6). The other daughter
evolved pink shells (7), then split (8). One daughter lineage evolved
high-spired shells (9). The other persisted with no further changes (10). The
high-spired lineage split (11). One daughter lineage persisted with no further
changes (12). The other evolved spikes on its shell (13), then persisted with no
further changes (14). These events yielded the five extant species at far
right. shows the novel shell traits shared by the four species that exhibit them.
Note that these traits are shared in a nested pattern. The species with spikes is
nested within the set of species with high spires. The set of species with high
spires is nested within the set of species with pink shells. And the set of
species with pink shells is nested within the set of species with elongated
shells
Figure 3 |
Our hypothetical
snails demonstrate that the theory of descent with modification from common
ancestors makes a prediction. Extant organisms should share nested sets of
novel traits. And, indeed, they do. For example, humans are nested within the
apes—a group of species that have large brains and no tails. The apes, in turn,
are nested within the primates—which have grasping hands, and feet, with flat
nails instead of claws. The primates are nested within the mammals—defined by
hair and feeding milk to their young. The mammals are nested within the
tetrapods, the tetrapods within the vertebrates, and so on. The nested pattern
of traits shared among extant species thus confirms a prediction of Darwin’s
theory. But we can go further. Look again at Figure 3 and compare part (b)
to part (a). Notice that the most deeply nested sets are defined by traits,
such as spikes, that evolved relatively late. If we start with one of these
sets and work our way out across the progressively larger sets that enclose it,
we encounter additional traits that evolved ever earlier in time. Spikes were
preceded by high spires. High spires, in turn, were preceded by pink shells.
And pink shells were preceded by elongated shells. Even if we had only the five
extant species and did not know their evolutionary history, we could still use
the nesting of the traits they share to predict the order in
which the traits should appear in the fossil record. We could then check the
fossil record to see if our prediction is correct. Mark Norell and Michael
Novacek (1992) performed such tests on two dozengroups of vertebrates.
Representative results appear in. In six cases, such as the duck-billed dinosaurs,
there was no significant correlation between the predicted order in which
traits arose versus the actual order. However, in the other 18
cases, including the reptiles and the elephants and kin, the correlation was
significant or strongly so.
More sophisticated
methods of assessing the correspondence between traitbased reconstructions of
evolutionary history versus the order traits appear in the fossil record have
since been developed (see Wills et al. 2008). The correspondence is generally
high, at least for well-studied groups of organisms that fossilize readily.
This pattern is consistent with descent from common ancestors.
Molecular Homology
Figure 4 |
A Predictive Test of
Common Ancestry Using Molecular Homologies
Our second example of molecular homology concerns another
kind of genetic quirk that might be considered a flaw: processed pseudogenes. Before we explain what
processed pseudogenes are, note that most genes in the human genome consist of
small coding bits, or exons, separated by noncoding intervening sequences, or introns. After a gene is transcribed
into messenger RNA, the introns have to be spliced out before the message can
be translated into protein. Note also that the human genome is littered with retrotransposons, retroviruslike genetic
elements that jump from place to place in the genome via transcription to RNA,
reverse transcription to DNA, and insertion at a new site (see Luning Prak and
Kazazian 2000). Some of the retrotransposons in our genome are active and
encode functional reverse transcriptase. Now we can explain that processed
pseudogenes are nonfunctional copies of normal genes that originate when
processed mRNAs are accidentally reverse transcribed to DNA by reverse
transcriptase, then inserted back into the genome
Universal Molecular
Homologies
Universal Triplet Code |
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