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Time Series Canopy Phenotyping Enables Identification of Genetic Variants Controlling Dynamic Phenotypes in Soybean

Source: Institute of Crop Sciences

An international team of scientists co-led by Prof. Qiu Lijuan (Institute of Crop Science, Chinese Academy of Agricultural Sciences, ICS-CAAS) has recently revealed the genetic basis of soybean time series canopy. This research was published in Journal of Integrative Plant Biology.


Plants undergo dynamic changes in their phenotypes throughout their life cycle and response to environmental cues and stressors. However, most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data, because collecting quantitative plant traits had been comparatively slow and expensive. Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across time points.


The time-series phenotypic data of a large panel of soybean (Glycine max (L.) Merr.) varieties were collected by an unmanned aircraft system for identifying previously uncharacterized loci. Specifically, this study focused on the dissection of canopy coverage (CC) variation. The speed of canopy closure, an additional dimension of CC, was inferred from this rich dataset, as it may represent an important trait for weed control. Genome-wide association studies (GWASs) identified 35 loci exhibiting dynamic associations with CC across developmental stages. 10 of 35 loci were known flowering time and plant height quantitative trait loci (QTLs) detected in previous studies of adult plants. The identification of novel QTLs that act in earlier stage may explain why they were missed in previous single-time-point studies. Two novel loci showed evidence of adaptive selection during domestication, with different genotypes/haplotypes favored in different geographic regions. In summary, the time-series data, with soybean CC as an example, improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.


This study was led by groups from ICS-CASS, Prof. Qiu Lijuan, Prof. Li Yinghui, and Prof. Jin Xiuliang serving as co-corresponding authors. Prof. James Schnable from the University of Nebraska-Lincoln was also a co-corresponding author and contributed to the design of the experiment and the data analyses. Dr.Li Delin, Mr. Bai Dong and Mr. Tian Yu contributed equally to this work as co-first authors. This study was supported by the National Key Research & Development Program of China, the Agricultural Science and Technology Innovation Program (ASTIP) of the CAAS, and Hainan Yazhou Bay Seed Lab.


By Li Yinghui (liyinghui@caas.cn)

Figure 1. Soybean cultivars, unmanned aircraft system and time-series canopy coverage



Figure 2. Dynamic association of canopy coverage