Guo Weijun, Wang Fanhua, Lv Jianyue, Yu Jia, Wu Yue, Wuriyanghan Hada, Le Liang, Pu Li
Biotechnology Research Institute Chinese Academy of Agricultural Sciences Beijing China.
School of Life Science Inner Mongolia University Hohhot China.
Imeta. 2025 Mar 13;4(2):e70015. doi: 10.1002/imt2.70015. eCollection 2025 Apr.
Root System Architecture (RSA) plays an essential role in influencing maize yield by enhancing anchorage and nutrient uptake. Analyzing maize RSA dynamics holds potential for ideotype-based breeding and prediction, given the limited understanding of the genetic basis of RSA in maize. Here, we obtained 16 root morphology-related traits (R-traits), 7 weight-related traits (W-traits), and 108 slice-related microphenotypic traits (S-traits) from the meristem, elongation, and mature zones by cross-sectioning primary, crown, and lateral roots from 316 maize lines. Significant differences were observed in some root traits between tropical/subtropical and temperate lines, such as primary and total root diameters, root lengths, and root area. Additionally, root anatomy data were integrated with genome-wide association study (GWAS) to elucidate the genetic architecture of complex root traits. GWAS identified 809 genes associated with R-traits, 261 genes linked to W-traits, and 2577 key genes related to 108 slice-related traits. We confirm the function of a candidate gene, (), in regulating root development and heat tolerance in maize. The different haplotypes found in tropical/subtropical and temperate lines are associated with primary root features and hold promising applications in molecular breeding. Furthermore, we performed machine learning prediction models of RSA using root slice traits, achieving high prediction accuracy. Collectively, our study offers a valuable tool for dissecting the genetic architecture of RSA, along with resources and predictive models beneficial for molecular design breeding and genetic enhancement.
根系结构(RSA)通过增强固着能力和养分吸收对玉米产量起着至关重要的作用。鉴于对玉米RSA遗传基础的了解有限,分析玉米RSA动态对于基于理想型的育种和预测具有潜力。在这里,我们通过对316个玉米品系的初生根、冠根和侧根进行切片,从分生区、伸长区和成熟区获得了16个与根形态相关的性状(R性状)、7个与重量相关的性状(W性状)和108个与切片相关的微表型性状(S性状)。在热带/亚热带品系和温带品系之间的一些根性状上观察到显著差异,如初生根和总根直径、根长度和根面积。此外,将根解剖数据与全基因组关联研究(GWAS)相结合,以阐明复杂根性状的遗传结构。GWAS鉴定出809个与R性状相关的基因、261个与W性状相关的基因以及2577个与108个切片相关性状相关的关键基因。我们证实了一个候选基因()在调节玉米根发育和耐热性方面的功能。在热带/亚热带品系和温带品系中发现的不同单倍型与初生根特征相关,在分子育种中具有广阔的应用前景。此外,我们使用根切片性状进行了RSA的机器学习预测模型,取得了较高的预测准确性。总的来说,我们的研究为剖析RSA的遗传结构提供了一个有价值的工具,以及有利于分子设计育种和遗传改良的资源和预测模型。