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Integrating molecular and physiological approaches to quantify genetic controls for wheat development and improve phenotyping

12 Sept 2025 · 10.1101/2025.09.11.675709

Abstract

Summary Disentangling genotype × environment (G×E) effects is critical to understand the performance of wheat across different environments. A framework for doing this was previously presented in a model that integrated knowledge of crop physiology and the Vrn gene feedback loop to explain and predict the time of anthesis. The aims of this study were: 1) provide an updated description of the Cereal Anthesis Molecular Phenology (CAMP) model; 2) to verify the model’s assumptions regarding the relationship between Vrn gene expression and the timing of phenological stages in a set of diverse genotypes and environments; 3) to use the CAMP model to establish a phenotyping strategy for use in genetic studies and model parameterisation. Six wheat genotypes with a range of cool temperature and photoperiod sensitivities were evaluated. Apical development, final leaf number (FLN) and temporal expression of Vrn1, Vrn2 and Vrn3 were compared with model predictions. There was a clear relationship between FLN responses to cool temperature and photoperiod, the timing of phenological events and the patterns of Vrn gene expression for all genotypes. There was general agreement between the temporal patterns of foliar gene expression observed with those assumed by CAMP, but some obvious discrepancies. These may be related to differences between gene expression in foliar (observed) and apical (assumed by the model) parts of the plant, or differences in the way observed and modelled gene expression are scaled. Overall, the model described all the observed development responses to environment and provides a basis for building quantitative predictions of field-based development from genotypic and environmental data. A protocol is presented for phenotyping wheat using FLN measured in specific combinations of temperature and photoperiod. It allows easy and unconfounded measure of key developmental phenotypes that clearly relate to the genetic make-up of the plants and underlying gene expression profiles.

Plant phenotyping relevance

CAMPモデルの更新・検証と、FLNを用いた小麦発育形質のフェノタイピングプロトコル提示が研究の中心であり、単なる生物学的測定ではない。

abstractto use the CAMP model to establish a phenotyping strategy for use in genetic studies and model parameterisation.
abstractA protocol is presented for phenotyping wheat using FLN measured in specific combinations of temperature and photoperiod.
abstractOverall, the model described all the observed development responses to environment and provides a basis for building quantitative predictions of field-based development from genotypic and environmental data.

Code and data availability

The paper's CAMP model code, analysis scripts, and data are explicitly stated as publicly available on the authors' GitHub repository, with specific URLs for the model notebook and the test/plotting script.

Codepublic

were also validated and the best-performing sets selected. A 347 description of each of the primers used in this study is given in the supplementary material 348 (Table SA1). 349 2.9 Verification of CAMP predictions 350 2.9.1 Model set-up and operation. 351 The CAMP model was coded into a Python script which is available at 352 https://github.com/HamishBrownPFR/CAMP/blob/master/CAMP.ipynb. A formal 353 description of the code and parameterisation scheme is given in the supplementary material. 354 The FLN developmental phenotypes measured for each genotype (Section 3.1) were used to 355 derive the Vrn expression parameters needed for CAMP. Each of the treatments was 356 simulated using CAMP w

Open resource ↗https://github.com/HamishBrownPFR/CAMP/ · pdf-raw-page:14 lines:1-70
Codepublic

pression parameters needed for CAMP. Each of the treatments was 356 simulated using CAMP with its corresponding daily temperature and Pp, so its predictions of 357 Vrn gene expression could be compared with those observed. The script running the CAMP 358 code and producing the graphs displayed in this paper can be viewed at 359 https://github.com/HamishBrownPFR/CAMP/blob/master/Tests/CAMPCETests.py.360 . CC-BY-NC 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made The copyright holder for this preprint this version posted September 12, 2025. ; https://doi

Open resource ↗https://github.com/HamishBrownPFR/CAMP/ · pdf-raw-page:14 lines:1-70
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nd testing of the model in 689 broader contexts. EW contributed substantially to the improvement of model concepts and the 690 manuscript and all authors provided final checking. 691 8. Data Availability 692 All the data and scripts used to analyse data and produce graphs as well as CAMP model code are 693 publicly available at https://github.com/HamishBrownPFR/CAMP/694 9. References 695 Allard V, Otto V, Bela K, Rousset M, Le Gouis J, Martre P. 2012. The quantitative 696 response of wheat vernalization to environmental variables indicates that vernalization is not 697 a response to cold temperature. Journal of Experimental Botany 63: 847–857. 698 Baumont M, Parent B, Manceau L, Brown HE, D

Open resource ↗https://github.com/HamishBrownPFR/CAMP/ · pdf-raw-page:31 lines:1-68

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