Integrated Phenomics and Genomics reveals genetic loci associated with inflorescence growth in Brassica napus

Abstract

A fundamental challenge to the production of climate-resilient crops is how to measure dynamic yield-relevant responses to the environment, such as growth rate, at a scale which informs mechanistic understanding and accelerates breeding. The timing, duration and architectural characteristics of inflorescence growth are crucial for optimising crop productivity and have been targets of selection during domestication. We report a robust and versatile procedure for computationally assessing environmentally-responsive flowering dynamics. In the oilseed crop, Brassica napus, there is wide variation in flowering response to winter cold (vernalization). We subjected a diverse set of B. napus accessions to different vernalization temperatures and monitored shoot responses using automated image acquisition. We developed methods to computationally infer multiple aspects of flowering from this dynamic data, enabling characterisation of speed, duration and peaks of inflorescence development across different crop types. We input these multiple traits to genome- and transcriptome-wide association studies, and identified potentially causative variation in a priori phenology genes (including EARLY FLOWERING3) for known traits and in uncharacterised genes for computed traits. These results could be used in marker assisted breeding to design new ideotypes for improved yield and better adaptation to changing climatic conditions.

Plant phenotyping relevance

自動画像取得と計算手法により、開花・花序成長の動態形質を推定する方法を開発しており、表現型取得・抽出が研究の中心である。

Code and data availability

The supplied blocks describe phenotyping pipelines, trait tables, and GWAS/AT analyses but contain no public dataset, image, code, or model deposit with an authors' URL. The GAGA pipeline is cited as 'in prep.' with no availability statement, and supplemental tables are referenced without public links.

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