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@ARTICLE{Sonnewald:878722,
author = {Sonnewald, Uwe and Fernie, Alisdair R. and Gruissem,
Wilhelm and Schläpfer, Pascal and Anjanappa, Ravi B. and
Chang, Shu‐Heng and Ludewig, Frank and Rascher, Uwe and
Muller, Onno and Doorn, Anna M. and Rabbi, Ismail Y. and
Zierer, Wolfgang},
title = {{T}he {C}assava {S}ource–{S}ink project: opportunities
and challenges for crop improvement by metabolic
engineering},
journal = {The plant journal},
volume = {103},
number = {5},
issn = {1365-313X},
address = {Oxford [u.a.]},
publisher = {Wiley-Blackwell},
reportid = {FZJ-2020-03022},
pages = {1655 - 1665},
year = {2020},
abstract = {Cassava (Manihot esculenta Crantz) is one of the important
staple foods in Sub‐Saharan Africa. It produces starchy
storage roots that provide food and income for several
hundred million people, mainly in tropical agriculture
zones. Increasing cassava storage root and starch yield is
one of the major breeding targets with respect to securing
the future food supply for the growing population of
Sub‐Saharan Africa. The Cassava Source–Sink (CASS)
project aims to increase cassava storage root and starch
yield by strategically integrating approaches from different
disciplines. We present our perspective and progress on
cassava as an applied research organism and provide insight
into the CASS strategy, which can serve as a blueprint for
the improvement of other root and tuber crops. Extensive
profiling of different field‐grown cassava genotypes
generates information for leaf, phloem, and root metabolic
and physiological processes that are relevant for
biotechnological improvements. A multi‐national pipeline
for genetic engineering of cassava plants covers all steps
from gene discovery, cloning, transformation, molecular and
biochemical characterization, confined field trials, and
phenotyping of the seasonal dynamics of shoot traits under
field conditions. Together, the CASS project generates
comprehensive data to facilitate conventional breeding
strategies for high‐yielding cassava genotypes. It also
builds the foundation for genome‐scale metabolic modelling
aiming to predict targets and bottlenecks in metabolic
pathways. This information is used to engineer cassava
genotypes with improved source–sink relations and
increased yield potential.},
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},
pubmed = {pmid:32502321},
UT = {WOS:000543137600001},
doi = {10.1111/tpj.14865},
url = {https://juser.fz-juelich.de/record/878722},
}