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@ARTICLE{Friedel:131882,
author = {Friedel, Swetlana and Usadel, Björn and von Wirén,
Nicolaus and Sreenivasulu, Nese},
title = {{R}everse {E}ngineering: {A} {K}ey {C}omponent of {S}ystems
{B}iology to {U}nravel {G}lobal {A}biotic {S}tress
{C}ross-{T}alk},
journal = {Frontiers in Plant Physiology},
volume = {3},
number = {294},
issn = {1664-462X},
address = {Lausanne},
publisher = {Frontiers Media83580},
reportid = {FZJ-2013-01142},
pages = {1-16},
year = {2012},
abstract = {Understanding the global abiotic stress response is an
important stepping stone for the development of universal
stress tolerance in plants in the era of climate change.
Although co-occurrence of several stress factors (abiotic
and biotic) in nature is found to be frequent, current
attempts are poor to understand the complex physiological
processes impacting plant growth under combinatory factors.
In this review article, we discuss the recent advances of
reverse engineering approaches that led to seminal
discoveries of key candidate regulatory genes involved in
cross-talk of abiotic stress responses and summarized the
available tools of reverse engineering and its relevant
application. Among the universally induced regulators
involved in various abiotic stress responses, we highlight
the importance of (i) abscisic acid (ABA) and jasmonic acid
(JA) hormonal cross-talks and (ii) the central role of WRKY
transcription factors (TF), potentially mediating both
abiotic and biotic stress responses. Such interactome
networks help not only to derive hypotheses but also play a
vital role in identifying key regulatory targets and
interconnected hormonal responses. To explore the full
potential of gene network inference in the area of abiotic
stress tolerance, we need to validate hypotheses by
implementing time-dependent gene expression data from
genetically engineered plants with modulated expression of
target genes. We further propose to combine information on
gene-by-gene interactions with data from physical
interaction platforms such as protein–protein or TF-gene
networks.},
cin = {IBG-2},
ddc = {580},
cid = {I:(DE-Juel1)IBG-2-20101118},
pnm = {242 - Sustainable Bioproduction (POF2-242)},
pid = {G:(DE-HGF)POF2-242},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000208837900288},
pubmed = {pmid:23293646},
doi = {10.3389/fpls.2012.00294},
url = {https://juser.fz-juelich.de/record/131882},
}