Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet.

IF 4.7 2区生物学 Q1 BIOCHEMICAL RESEARCH METHODS

Plant Methods Pub Date : 2024-11-05 DOI:10.1186/s13007-024-01295-z

Zhenyu Wang, Jiongyu Hao, Xiaofan Shi, Qiaoqiao Wang, Wuping Zhang, Fuzhong Li, Luis A J Mur, Yuanhuai Han, Siyu Hou, Jiwan Han, Zhaoxia Sun

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引用次数: 0

Abstract

Background: Foxtail millet [Setaria italica (L.) Beauv] is a C₄ graminoid crop cultivated mainly in the arid and semiarid regions of China for more than 7000 years. Its grain highly nutritious and is rich in starch, protein, essential vitamins such as carotenoids, folate, and minerals. To expand the utilisation of foxtail millet, efficient and precise methods for dynamic phenotyping of its growth stages are needed. Traditional foxtail millet monitoring methods have high labour costs and are inefficient and inaccurate, impeding the precise evaluation of foxtail millet genotypic variation.

Results: This study introduces a high-throughput imaging system (HIS) with advanced image processing techniques to enhance monitoring efficiency and data quality. The HIS can accurately extract a range of key growth feature parameters, such as plant height (PH), convex hull area (CHA), side projected area (SPA) and colour distribution, from foxtail millet images. Compared with traditional manual measurements, this HIS improved data quality and phenotyping of the key foxtail millet growth traits. High-throughput phenotyping combined with a genome-wide association study (GWAS) revealed genetic loci associated with dynamic growth traits, particularly plant height (PH), in foxtail millet. The loci were linked to genes involved in the gibberellic acid (GA) synthesis pathway related to PH.

Conclusion: The HIS developed in this study enables the efficient and dynamic monitoring of foxtail millet phenotypic traits. It significantly improves the quality of data obtained for phenotyping key growth traits. The integration of high-throughput phenotyping with GWAS provides new insights into the genetic underpinnings of dynamic growth traits, particularly plant height, by identifying associated genetic loci in the GA synthesis pathway. This methodological advancement opens new avenues for the precise phenotyping and exploration of genetic resources in foxtail millet, potentially enhancing its utilisation.

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整合动态高通量表型和遗传分析，监测狐尾黍的生长变异。

背景：狐尾黍 [Setaria italica (L.) Beauv] 是一种 C4 禾本科作物，主要在中国干旱和半干旱地区种植，已有 7000 多年的历史。其谷物营养丰富，富含淀粉、蛋白质、胡萝卜素等必需维生素、叶酸和矿物质。为扩大狐尾粟的利用，需要高效、精确的方法对其生长阶段进行动态表型。传统的狐尾粟监测方法劳动力成本高、效率低且不准确，阻碍了对狐尾粟基因型变异的精确评估：本研究介绍了一种高通量成像系统（HIS），该系统采用先进的图像处理技术来提高监测效率和数据质量。高通量成像系统可从狐尾粟图像中精确提取一系列关键生长特征参数，如株高（PH）、凸壳面积（CHA）、侧投影面积（SPA）和颜色分布。与传统的人工测量相比，该 HIS 提高了数据质量和狐尾粟关键生长性状的表型。高通量表型分析与全基因组关联研究（GWAS）相结合，揭示了狐尾粟动态生长性状（尤其是株高（PH））的相关基因位点。这些基因位点与赤霉素（GA）合成途径中与 PH 相关的基因有关：本研究开发的 HIS 能够对狐尾粟的表型性状进行有效的动态监测。它大大提高了关键生长性状表型数据的质量。高通量表型分析与 GWAS 的整合通过确定 GA 合成途径中的相关遗传位点，为动态生长性状（尤其是株高）的遗传基础提供了新的见解。这一方法学上的进步为狐尾粟遗传资源的精确表型和探索开辟了新途径，有可能提高其利用率。

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来源期刊

Plant Methods 生物-植物科学

CiteScore

9.20

自引率

3.90%

发文量

121

审稿时长

2 months

期刊介绍： Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences. There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics. Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.