2023 journal article

Cellular clarity: a logistic regression approach to identify root epidermal regulators of iron deficiency response

BMC GENOMICS, 24(1).

By: S. Schmittling n, D. Muhammad *, S. Haque *, T. Long n  & C. Williams n 

author keywords: Iron deficiency; Epidermis; Arabidopsis; Logistic regression; Gene regulatory network; RNA-seq
topics (OpenAlex): Plant Micronutrient Interactions and Effects; Plant Stress Responses and Tolerance; Plant nutrient uptake and metabolism
TL;DR: Machine learning approaches combined with additional static data identified putative regulators of -Fe response that would not have been identified solely through transcriptomic profiles and reveal how developmental and general stress responses within the epidermis may act upstream of more specialized -Fe responses for Fe uptake. (via Semantic Scholar)
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Plants respond to stress through highly tuned regulatory networks. While prior works identified master regulators of iron deficiency responses in A. thaliana from whole-root data, identifying regulators that act at the cellular level is critical to a more comprehensive understanding of iron homeostasis. Within the root epidermis complex molecular mechanisms that facilitate iron reduction and uptake from the rhizosphere are known to be regulated by bHLH transcriptional regulators. However, many questions remain about the regulatory mechanisms that control these responses, and how they may integrate with developmental processes within the epidermis. Here, we use transcriptional profiling to gain insight into root epidermis-specific regulatory processes.