Quantification of variability in trichome patterns
While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves gen...
Saved in:
Published in | Frontiers in plant science Vol. 5; p. 596 |
---|---|
Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
13.11.2014
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves genetic regulation and cell-to-cell communication. These processes are potentially variable due to, e.g., the abundance of cell components or environmental conditions. To elevate the understanding of regulatory processes underlying the pattern formation it is crucial to quantitatively analyze the variability in naturally occurring patterns. Here, we review recent approaches toward characterization of noise on trichome initiation. We present methods for the quantification of spatial patterns, which are the basis for data-driven mathematical modeling and enable the analysis of noise from different sources. Besides the insight gained on trichome formation, the examination of observed trichome patterns also shows that highly regulated biological processes can be substantially affected by variability. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 This article was submitted to Plant Evolution and Development, a section of the journal Frontiers in Plant Science. Edited by: Karen Alim, Harvard University, USA Reviewed by: Roeland M. H. Merks, Centrum Wiskunde and Informatica, Netherlands; John Schiefelbein, University of Michigan, USA |
ISSN: | 1664-462X 1664-462X |
DOI: | 10.3389/fpls.2014.00596 |