How do cells know what they should
become as the body develops? Biological development depends crucially on
spatial patterns: the lines that eventually give rise to segments, organs, or
markings like stripes and spots. Yet despite the variation in form, shape and
structure in the animal kingdom, the mechanisms that generate these body plans
are surprisingly similar across species.
For decades, scientists have known
that webs of genes controlling other genes, known as "gene regulatory networks," play a central role in shaping these patterns. But how these
networks evolve to create new patterns is less understood.
This question is being explored by
Zena Hadjivasiliou, Group Leader of the Crick's Mathematical and Physical
Biology Laboratory. Her team are aiming to unpick how the same genes and
molecules produce life in all its diverse forms.
"We have an incomplete picture
of how these patterning mechanisms evolve," Hadjivasiliou says. "When
a new type of marking appears in a species, such as a new eye spot in a
butterfly wing, it doesn't come from scratch. It emerges from subtle rewiring
of the underlying genetic architecture. But what kind of mutations make this
possible? And are there rules that govern which new patterns are possible, and
which remain out of reach?"
Evolving gene networks: A well-trodden path?
The lab's latest research, published today in PRX Life, explores whether
specific types of mutations in patterning networks accelerate the evolution of
new patterns, and if any of these changes yield predictable evolutionary
outcomes.
Hadjivasiliou explains that the
idea of predicting evolution has been pondered by biologists and philosophers
alike over many years.
"There's a classic thought experiment from the paleontologist and evolutionary biologist Stephen Jay Gould: if we were able to replay the 'tape of life,' would we end up with the same diversity in the animal kingdom that we see today?" says Hadjivasiliou. "For Gould, the answer is no—seemingly inconsequential and random events in history pushed us down an evolutionary path which was therefore unlikely to ever happen again."
Changes that happen together stay together
Answering these questions
experimentally is nearly impossible. Real embryos are complex, mutations are
hard to track, and evolution plays out over immense timescales. To begin to
tackle this challenge, Harry Booth, mathematician and computer scientist in the
lab and first author of the study, built a virtual version of the process: a
computer simulation that models how small networks of genes evolve under
natural selection.
"Our system models gene
networks that instruct cells to commit to a specific fate, depending on where
they are in a tissue," says Booth. "Small changes within these
networks can drive large differences in the spatial patterns they produce."
He continues, "By running the
simulation not just once, but more than 100,000 times, we were able to build a
statistical picture of how evolution tends to proceed in the search for new
patterns. Once you reach this kind of scale, all the random features of
evolution start to disappear and what you are left with represents general
properties of these types of processes."
Using the computer simulation
allowed Booth and Hadjivasiliou to uncover rules about the types of mutations
that matter most. Adjusting an existing boundary—for example, shifting where a
stripe begins or ends—needed only small tweaks to the strengths of existing
gene interactions. But creating new boundaries was far more difficult. It
usually demanded multiple changes at once: for example, adding entirely new
regulatory links and flipping a gene's role from activation to inhibition
simultaneously.
Booth summarizes, "In short, fine-tuning is easy, but genuine innovation takes a bigger shake-up of the network."
History makes its mark
And what about Gould's 'tape of
life'? Booth took a novel approach to this question. Using the massive dataset
of evolutionary trajectories, he trained a machine learning model that could forecast which network design a
trajectory was heading towards, finding that, surprisingly, aspects of
evolution could be predicted.
"History does make its
mark," he concludes. "We found that certain mutations radically shift
the predicted evolutionary outcome. This suggests that the mutation introduces
a fork in the road early in the journey of evolution, which, despite
evolution's inherent randomness, reliably redirects evolution to a specific
destination."
This finding lends evidence to the
hypothesis that chance events in history shape the future of a species'
evolution. As Hadjivasiliou puts it, "the model makes headway in
explaining how small, seemingly unimportant events in evolutionary history can have lasting impacts on the development and
diversity of animal forms."
And what's next? Booth explains
that they're hoping to pick up signals of the principles they identified in
their virtual evolution experiment in genetic data from organisms such as fruit
flies.
He concludes, "We've laid the groundwork for some really interesting experiments, now that we know a bit more about the types of evolutionary processes required to evolve these networks and how they can produce new patterns."
Source: How evolution rewires gene circuits to build new patterns
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