TY - JOUR
T1 - Functional physiological phenotyping with functional mapping
T2 - A general framework to bridge the phenotype-genotype gap in plant physiology
AU - Pandey, Arun K.
AU - Jiang, Libo
AU - Moshelion, Menachem
AU - Gosa, Sanbon Chaka
AU - Sun, Ting
AU - Lin, Qin
AU - Wu, Rongling
AU - Xu, Pei
N1 - Funding Information:
This study is supported by the joined Chinese-Israeli grant (NSFC-ISF joint grant No. 31861143044 and 2436/18), the National Natural Science Foundation of China (grant No. 31772299), and the Key Research Program of Zhejiang Province (2021C02041). M.M. wishes to also thank the Israel Science Foundations (grant No. 878/16). P.X, M.M, and R.W conceived the idea. P.X, L.J, A.K.P, M.M. and R.W designed the experiments and developed statistical algorithms. A.K.P, L.J, S.C.G, and Q.L performed the experiment. L.J, P.X, S. C.G and M.M analyzed and interpreted the data. A.K.P and P.X. wrote the manuscript. All authors read and approved the final manuscript. The authors declare that they have no competing interests.
Funding Information:
This study is supported by the joined Chinese-Israeli grant ( NSFC -ISF joint grant No. 31861143044 and 2436/18 ), the National Natural Science Foundation of China (grant No. 31772299 ), and the Key Research Program of Zhejiang Province ( 2021C02041 ). M.M. wishes to also thank the Israel Science Foundations (grant No. 878/16 ).
Publisher Copyright:
© 2021 The Author(s)
PY - 2021/8/20
Y1 - 2021/8/20
N2 - The recent years have witnessed the emergence of high-throughput phenotyping techniques. In particular, these techniques can characterize a comprehensive landscape of physiological traits of plants responding to dynamic changes in the environment. These innovations, along with the next-generation genomic technologies, have brought plant science into the big-data era. However, a general framework that links multifaceted physiological traits to DNA variants is still lacking. Here, we developed a general framework that integrates functional physiological phenotyping (FPP) with functional mapping (FM). This integration, implemented with high-dimensional statistical reasoning, can aid in our understanding of how genotype is translated toward phenotype. As a demonstration of method, we implemented the transpiration and soil-plant-atmosphere measurements of a tomato introgression line population into the FPP-FM framework, facilitating the identification of quantitative trait loci (QTLs) that mediate the spatiotemporal change of transpiration rate and the test of how these QTLs control, through their interaction networks, phenotypic plasticity under drought stress.
AB - The recent years have witnessed the emergence of high-throughput phenotyping techniques. In particular, these techniques can characterize a comprehensive landscape of physiological traits of plants responding to dynamic changes in the environment. These innovations, along with the next-generation genomic technologies, have brought plant science into the big-data era. However, a general framework that links multifaceted physiological traits to DNA variants is still lacking. Here, we developed a general framework that integrates functional physiological phenotyping (FPP) with functional mapping (FM). This integration, implemented with high-dimensional statistical reasoning, can aid in our understanding of how genotype is translated toward phenotype. As a demonstration of method, we implemented the transpiration and soil-plant-atmosphere measurements of a tomato introgression line population into the FPP-FM framework, facilitating the identification of quantitative trait loci (QTLs) that mediate the spatiotemporal change of transpiration rate and the test of how these QTLs control, through their interaction networks, phenotypic plasticity under drought stress.
UR - http://www.scopus.com/inward/record.url?scp=85111206492&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111206492&partnerID=8YFLogxK
U2 - 10.1016/j.isci.2021.102846
DO - 10.1016/j.isci.2021.102846
M3 - Article
C2 - 34381971
AN - SCOPUS:85111206492
SN - 2589-0042
VL - 24
JO - iScience
JF - iScience
IS - 8
M1 - 102846
ER -