Precision of morphogen gradients in neural tube development

Roman Vetter () and Dagmar Iber ()
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Roman Vetter: ETH Zürich
Dagmar Iber: ETH Zürich

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: Abstract Morphogen gradients encode positional information during development. How high patterning precision is achieved despite natural variation in both the morphogen gradients and in the readout process, is still largely elusive. Here, we show that the positional error of gradients in the mouse neural tube has previously been overestimated, and that the reported accuracy of the central progenitor domain boundaries in the mouse neural tube can be achieved with a single gradient, rather than requiring the simultaneous readout of opposing gradients. Consistently and independently, numerical simulations based on measured molecular noise levels likewise result in lower gradient variabilities than reported. Finally, we show that the patterning mechanism yields progenitor cell numbers with even greater precision than boundary positions, as gradient amplitude changes do not affect interior progenitor domain sizes. We conclude that single gradients can yield the observed developmental precision, which provides prospects for tissue engineering.

Date: 2022
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DOI: 10.1038/s41467-022-28834-3

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