Literature DB >> 19658522

Accuracy of positional information provided by multiple morphogen gradients with correlated noise.

Yoshihiro Morishita1, Yoh Iwasa.   

Abstract

Normal development of multicellular organisms requires cells to respond properly according to their positions. Positional information is often provided to cells as concentrations of diffusive chemicals called morphogens with spatial gradients. However, the spatial profiles of their concentrations include various kinds of noises, making positional information unreliable. In many developmental systems, multiple morphogen gradients are adopted to specify the spatial position along a single axis, presumably to achieve a sufficiently high precision of information on the location of each cell. In this paper, we ask how the precision of positional information depends on the number of morphogens. We derive a formula for the limit of precision when each cell adopts the maximum-likelihood estimation of the "true" position from noisy inputs. The precision increases with the number of morphogens and interestingly it also depends on the correlation of noises. The positional specification can be made more precisely if their gradients are of the opposite (same) direction when noises of the two morphogens are positively (negatively) correlated. The formula also tells us a minimum number of morphogens needed to achieve a given precision of positional information. We illustrate the theory by analyzing experimental data for the gradients of two diffusive chemicals, Bicoid and Caudal, in the early development of Drosophila embryo. The analysis suggests that combined information provided by the two chemicals is able to give accurate positional information in the middle part of the embryo, where the embryo segmentation occurs in later stages, much more than near both ends.

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Year:  2009        PMID: 19658522     DOI: 10.1103/PhysRevE.79.061905

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  11 in total

1.  Coding design of positional information for robust morphogenesis.

Authors:  Yoshihiro Morishita; Yoh Iwasa
Journal:  Biophys J       Date:  2011-11-15       Impact factor: 4.033

2.  Shaping a morphogen gradient for positional precision.

Authors:  Feng He; Timothy E Saunders; Ying Wen; David Cheung; Renjie Jiao; Pieter Rein ten Wolde; Martin Howard; Jun Ma
Journal:  Biophys J       Date:  2010-08-04       Impact factor: 4.033

Review 3.  The developmental-genetics of canalization.

Authors:  Benedikt Hallgrimsson; Rebecca M Green; David C Katz; Jennifer L Fish; Francois P Bernier; Charles C Roseman; Nathan M Young; James M Cheverud; Ralph S Marcucio
Journal:  Semin Cell Dev Biol       Date:  2018-05-24       Impact factor: 7.727

4.  A two-dimensional simulation model of the bicoid gradient in Drosophila.

Authors:  Jingyuan Deng; Wei Wang; Long Jason Lu; Jun Ma
Journal:  PLoS One       Date:  2010-04-21       Impact factor: 3.240

5.  Decoding of position in the developing neural tube from antiparallel morphogen gradients.

Authors:  Marcin Zagorski; Yoji Tabata; Nathalie Brandenberg; Matthias P Lutolf; Gašper Tkačik; Tobias Bollenbach; James Briscoe; Anna Kicheva
Journal:  Science       Date:  2017-06-30       Impact factor: 47.728

Review 6.  Systems approach to developmental biology--designs for robust patterning.

Authors:  Yoshihiro Morishita; Ken-Ichi Hironaka
Journal:  IET Syst Biol       Date:  2013-04       Impact factor: 1.615

Review 7.  The many bits of positional information.

Authors:  Gašper Tkačik; Thomas Gregor
Journal:  Development       Date:  2021-02-01       Impact factor: 6.868

8.  Noise and robustness in phyllotaxis.

Authors:  Vincent Mirabet; Fabrice Besnard; Teva Vernoux; Arezki Boudaoud
Journal:  PLoS Comput Biol       Date:  2012-02-16       Impact factor: 4.475

Review 9.  The organelle of differentiation in embryos: the cell state splitter.

Authors:  Natalie K Gordon; Richard Gordon
Journal:  Theor Biol Med Model       Date:  2016-03-10       Impact factor: 2.432

10.  Mutual repression enhances the steepness and precision of gene expression boundaries.

Authors:  Thomas R Sokolowski; Thorsten Erdmann; Pieter Rein ten Wolde
Journal:  PLoS Comput Biol       Date:  2012-08-30       Impact factor: 4.475

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