Regulator proteins or symphonies of genes: Statistical modeling points
way toward unified theory for DNA folding

Date:
September 21, 2021
Source:
American Institute of Physics
Summary:
Researchers seek to point a way toward a unified theory for how DNA
changes shape when expressing genes. The scientists use an approach
called statistical mechanics to explore the phenomenon of so-called
expression waves of gene regulation. The group hopes to reconcile a
long- standing gulf between the two scientific fields most involved
in the topic, using concepts common to biology and physics.



FULL STORY ==========================================================================
At more than 2 meters long, the human DNA molecule uses intricate
folding patterns to fit into cells while locally unfolding to express
genes. Such phenomena, however, are difficult to measure in experiments,
and theoretical frameworks explaining them continue to be at odds with
one another.


========================================================================== Researchers in Italy, Japan, and Poland seek to point a way toward a
unified theory for how DNA changes shape when expressing genes. Presenting their work in Biophysics Reviews, published by AIP Publishing, the
scientists use an approach called statistical mechanics to explore the phenomenon of so-called expression waves of gene regulation.

The group hopes to reconcile a long-standing gulf between the two
scientific fields most involved in the topic.

"Many scholars at the crossroad between physics and biology are now
approaching what is probably the most crucial puzzle of biology," said co-author Alessandro Giuliani. "How is it possible that, starting from
the same genetic background in the fertilized egg, around 400 highly differentiated cell types can arise, each endowed with a specific
physiological role?" Biology-based theories often center on regulator proteins, called transcription factors, that biochemically conduct a
symphony of genes to be expressed together. By contrast, many physicists
have focused on expression waves, the rhythmic changes in expression
levels across the genome, driven by relaxation and condensing of the
DNA molecule itself.

"It is something like the so-called hola, common in soccer and in other
sport events, in which the spectators stand up simultaneously giving
rise to a 'wave' spreading all over the stadium," Giuliani said.

To get at the heart of the issue, the group focuses on a specific type
of cell found in breast cancer with a proven track record of consistently behaving the same way to stimuli.

They used statistical mechanics to make sense of how DNA molecules fold by assessing the collective behavior of a huge number of microscopic players
in terms of ensemble properties, unlike classical top-down perspectives,
like Newton's laws.

Ultimately, the researchers landed in favor of expression waves,
acknowledging that while transcription factors play a vital role, they
are second fiddle to the changing shape of DNA.

To unify these two perspectives, the authors present their conclusion
using concepts common to biology and physics, limiting the use of
mathematics to intuitive approaches such as recurrence quantification
analysis and the classical statistical method of principal component
analysis.

Next, they look to apply the same approach to identify ecological tipping points based on the makeup of species in particular habitats.

========================================================================== Story Source: Materials provided by American_Institute_of_Physics. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Giovanna Zimatore, Masa Tsuchiya, Midori Hashimoto, Andrzej
Kasperski,
Alessandro Giuliani. Self-organization of whole-gene expression
through coordinated chromatin structural transition. Biophysics
Reviews, 2021; 2 (3): 031303 DOI: 10.1063/5.0058511 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2021/09/210921172713.htm

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