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Systems analysis of lateral root development: an emerging story…

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Food security represents a major global issue. Significant improvements in crop yields are urgently required to meet the 50% increase in world population by 2050. The degree of root branching determines the efficiency of water uptake and acquisition of nutrients in crops. Understanding the regulation of root branching is therefore of vital agronomic importance. Lateral root branching can be divided into 2 distinct, yet inter-connected, developmental processes; primordium initiation and emergence. To date, research has focused largely on lateral root (LR) initiation. However, recent evidence suggests that LR emergence is an important checkpoint for root branching which is regulated by nutrients such as nitrate and phosphate and hormone signals such as auxin.

Lateral root primordia (LRP) originate exclusively from pericycle cells located deep within the parental root, necessitating that new primordia emerge through several overlaying tissues. In a recent article published in Nature Cell Biology (Swarup et al [2008] 10:625-628) we described how LRP emergence is a highly regulated process involving the active participation of cells in both new lateral root primordia and the parental root. The hormone auxin originating from the developing lateral root appears to act as a local inductive signal which reprograms adjacent cells. Auxin induces the expression of a previously uncharacterized auxin influx carrier LAX3 in cortical and epidermal cells directly overlaying new primordia. Increased LAX3 activity reinforces the auxin-dependent induction of a selection of cell wall remodelling enzymes, promoting cell separation in advance of developing lateral root primordia.

I will describe how we are employing a systems approach to study the gene regulatory networks and biomechanics associated with lateral root emergence. Our systems approach involves creating increasingly sophisticated multi-cellular models of the lateral root emergence network, populating them with experimental data, and then testing the in-silico models predictive ability.

This talk is part of the Plant Sciences Departmental Seminars series.

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