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Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression

Sam De Meyer (UGent) , Daniel Felipe Cruz Galvis (UGent) , Tom De Swaef (UGent) , Peter Lootens, Jolien De Block (UGent) , Kevin Bird, Heike Sprenger (UGent) , Michael Van de Voorde (UGent) , Stijn Hawinkel (UGent) , Tom Van Hautegem (UGent) , et al.
(2023) PLOS COMPUTATIONAL BIOLOGY. 19(5).
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Abstract
In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.
Keywords
Computational Theory and Mathematics, Cellular and Molecular Neuroscience, Genetics, Molecular Biology, Ecology, Modeling and Simulation, Ecology, Evolution, Behavior and Systematics, TRANSCRIPTION FACTOR, ARABIDOPSIS-THALIANA, SEEDLING EMERGENCE, REGULATORY NETWORK, FLORAL TRANSITION, MERISTEM FUNCTION, ABIOTIC STRESS, SINGLE, PROTEIN, GENOME

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Citation

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MLA
De Meyer, Sam, et al. “Predicting Yield of Individual Field-Grown Rapeseed Plants from Rosette-Stage Leaf Gene Expression.” PLOS COMPUTATIONAL BIOLOGY, edited by Kiran Raosaheb Patil, vol. 19, no. 5, 2023, doi:10.1371/journal.pcbi.1011161.
APA
De Meyer, S., Cruz Galvis, D. F., De Swaef, T., Lootens, P., De Block, J., Bird, K., … Maere, S. (2023). Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression. PLOS COMPUTATIONAL BIOLOGY, 19(5). https://doi.org/10.1371/journal.pcbi.1011161
Chicago author-date
De Meyer, Sam, Daniel Felipe Cruz Galvis, Tom De Swaef, Peter Lootens, Jolien De Block, Kevin Bird, Heike Sprenger, et al. 2023. “Predicting Yield of Individual Field-Grown Rapeseed Plants from Rosette-Stage Leaf Gene Expression.” Edited by Kiran Raosaheb Patil. PLOS COMPUTATIONAL BIOLOGY 19 (5). https://doi.org/10.1371/journal.pcbi.1011161.
Chicago author-date (all authors)
De Meyer, Sam, Daniel Felipe Cruz Galvis, Tom De Swaef, Peter Lootens, Jolien De Block, Kevin Bird, Heike Sprenger, Michael Van de Voorde, Stijn Hawinkel, Tom Van Hautegem, Dirk Inzé, Hilde Nelissen, Isabel Roldán-Ruiz, and Steven Maere. 2023. “Predicting Yield of Individual Field-Grown Rapeseed Plants from Rosette-Stage Leaf Gene Expression.” Ed by. Kiran Raosaheb Patil. PLOS COMPUTATIONAL BIOLOGY 19 (5). doi:10.1371/journal.pcbi.1011161.
Vancouver
1.
De Meyer S, Cruz Galvis DF, De Swaef T, Lootens P, De Block J, Bird K, et al. Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression. Patil KR, editor. PLOS COMPUTATIONAL BIOLOGY. 2023;19(5).
IEEE
[1]
S. De Meyer et al., “Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression,” PLOS COMPUTATIONAL BIOLOGY, vol. 19, no. 5, 2023.
@article{01H5HS6DW7HADD92VKGS2K208S,
  abstract     = {{In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.}},
  articleno    = {{e1011161}},
  author       = {{De Meyer, Sam and Cruz Galvis, Daniel Felipe and De Swaef, Tom and Lootens, Peter and De Block, Jolien and Bird, Kevin and Sprenger, Heike and Van de Voorde, Michael and Hawinkel, Stijn and Van Hautegem, Tom and Inzé, Dirk and Nelissen, Hilde and Roldán-Ruiz, Isabel and Maere, Steven}},
  editor       = {{Patil, Kiran Raosaheb}},
  issn         = {{1553-734X}},
  journal      = {{PLOS COMPUTATIONAL BIOLOGY}},
  keywords     = {{Computational Theory and Mathematics,Cellular and Molecular Neuroscience,Genetics,Molecular Biology,Ecology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,TRANSCRIPTION FACTOR,ARABIDOPSIS-THALIANA,SEEDLING EMERGENCE,REGULATORY NETWORK,FLORAL TRANSITION,MERISTEM FUNCTION,ABIOTIC STRESS,SINGLE,PROTEIN,GENOME}},
  language     = {{eng}},
  number       = {{5}},
  pages        = {{42}},
  title        = {{Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression}},
  url          = {{http://doi.org/10.1371/journal.pcbi.1011161}},
  volume       = {{19}},
  year         = {{2023}},
}
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