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@ARTICLE{Millet:826912,
author = {Millet, Emilie and Welcker, Claude and Kruijer, Willem and
Negro, Sandra and Nicolas, Stephane and Praud, Sebastien and
Ranc, Nicolas and Presterl, Thomas and Tuberosa, Roberto and
Bedo, Zoltan and Draye, Xavier and Usadel, Björn and
Charcosset, Alain and van Eeuwijk, Fred and Tardieu,
Francois and Coupel-Ledru, Aude and Bauland, Cyril},
title = {{G}enome-wide analysis of yield in {E}urope: allelic
effects as functions of drought and heat scenarios},
journal = {Plant physiology},
volume = {172},
number = {2},
issn = {1532-2548},
address = {Rockville, Md.},
publisher = {Soc.},
reportid = {FZJ-2017-01128},
pages = {749-764},
year = {2016},
abstract = {Assessing the genetic variability of plant performance
under heat and drought scenarios can contribute to reduce
the negative effects of climate change. We propose here an
approach that consisted of (1) clustering time courses of
environmental variables simulated by a crop model in current
(35 years × 55 sites) and future conditions into six
scenarios of temperature and water deficit as experienced by
maize (Zea mays L.) plants; (2) performing 29 field
experiments in contrasting conditions across Europe with 244
maize hybrids; (3) assigning individual experiments to
scenarios based on environmental conditions as measured in
each field experiment; frequencies of temperature scenarios
in our experiments corresponded to future heat scenarios
(+5°C); (4) analyzing the genetic variation of plant
performance for each environmental scenario. Forty-eight
quantitative trait loci (QTLs) of yield were identified by
association genetics using a multi-environment multi-locus
model. Eight and twelve QTLs were associated to tolerances
to heat and drought stresses because they were specific to
hot and dry scenarios, respectively, with low or even
negative allelic effects in favorable scenarios. Twenty-four
QTLs improved yield in favorable conditions but showed
nonsignificant effects under stress; they were therefore
associated with higher sensitivity. Our approach showed a
pattern of QTL effects expressed as functions of
environmental variables and scenarios, allowing us to
suggest hypotheses for mechanisms and candidate genes
underlying each QTL. It can be used for assessing the
performance of genotypes and the contribution of genomic
regions under current and future stress situations and to
accelerate breeding for drought-prone environments.},
cin = {IBG-2},
ddc = {580},
cid = {I:(DE-Juel1)IBG-2-20101118},
pnm = {582 - Plant Science (POF3-582)},
pid = {G:(DE-HGF)POF3-582},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000391147700011},
pubmed = {pmid:27436830},
doi = {10.1104/pp.16.00621},
url = {https://juser.fz-juelich.de/record/826912},
}