Quantification of variability in trichome patterns

• Main Authors: Bettina eGreese, Martin eHuelskamp, Christian eFleck
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2014-11-01
• Series: Frontiers in Plant Science
• Subjects: pattern formation; plant development; Spatial data analysis; trichome patterning; Data-driven Modeling; cell-to-cell variability
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fpls.2014.00596/full

While pattern formation is studied in various areas of biology, little is known about the intrinsic 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 the regulatory processes underlying the pattern formation it is crucial to quantitatively analyze the variability in naturally occurring patterns. Here, we review recent approaches towards 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.