Nitrogen response and growth trajectory of sorghum CRISPR-Cas9 mutants using high-throughput phenotyping

Abstract

ABSTRACT Inorganic nitrogen (N) fertilizer has emerged as one of the key factors driving increased crop yields in the past several decades; however, the overuse of chemical N fertilizer has led to severe ecological and environmental burdens. Understanding how crops respond to N fertilizer has become a central topic in plant science and plant genetics, with the ultimate goal of enhancing N use efficiency (NUE) in crop production. As one of the most essential macronutrients, N significantly influences crop performance across different developmental stages of plant, phenotypic traits result from the accumulative effects of genetic factors, prevailing environmental conditions (specifically N availability), and their complex interactions. To characterize the targeting N-responsiveness and growth trajectory, we employed CRISPR-Cas9 technique to generate sorghum mutants using CRISPR technology. Using a LemnaTec plant imaging system, we obtained time series imagery data from 29 to 130 days after sowing (DAS) for these CRISPR-edited mutants under high N and low N greenhouse conditions. After imagery data analysis, we extracted a number of morphological and greenness index traits as a proxy of plant growth and N responses. Subsequently, we employed two different methods to model the temporal N-responsive traits, allowing us to estimate seven key parameters from the growth curve. Our findings revealed that the wildtype and the edited sorghum lines exhibited differences in N responses for several of the key growth-related parameters. The high-throughput N phenotyping pipeline paves the way for a better understanding of the N responses of edited lines in a dynamic manner and sheds light on further improvements in crop NUE.

Plant phenotyping relevance

LemnaTec画像による時系列形質取得と成長曲線モデリングを組み合わせた高スループット表現型解析パイプラインが、研究の主要な技術的要素として記述されています。

Code and data availability

The paper's Supporting Information section links four public GitHub-hosted supplementary data files containing the paper-specific phenotypic values (fitted pixel count and ExG curve parameters) and statistical contrasts, directly reproducing this study's sorghum N-response phenotyping measurements and analysis outputs.