Woods Patrick, Lehner Kevin R, Hein Kirsten, Mullen Jack L, McKay John K
Department of Agricultural Biology, Colorado State University, Fort Collins, CO, United States.
Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, United States.
Front Plant Sci. 2022 Apr 15;13:883209. doi: 10.3389/fpls.2022.883209. eCollection 2022.
High-throughput, field-based characterization of root systems for hundreds of genotypes in thousands of plots is necessary for breeding and identifying loci underlying variation in root traits and their plasticity. We designed a large-scale sampling of root pulling force, the vertical force required to extract the root system from the soil, in a maize diversity panel under differing irrigation levels for two growing seasons. We then characterized the root system architecture of the extracted root crowns. We found consistent patterns of phenotypic plasticity for root pulling force for a subset of genotypes under differential irrigation, suggesting that root plasticity is predictable. Using genome-wide association analysis, we identified 54 SNPs as statistically significant for six independent root pulling force measurements across two irrigation levels and four developmental timepoints. For every significant GWAS SNP for any trait in any treatment and timepoint we conducted tests for genotype-by-environment interaction, using a mixed model ANOVA. We found that 8 of the 54 SNPs showed significant GxE. Candidate genes underlying variation in root pulling force included those involved in nutrient transport. Although they are often treated separately, variation in the ability of plant roots to sense and respond to variation in environmental resources including water and nutrients may be linked by the genes and pathways underlying this variation. While functional validation of the identified genes is needed, our results expand the current knowledge of root phenotypic plasticity at the whole plant and gene levels, and further elucidate the complex genetic architecture of maize root systems.
对于育种以及鉴定根系性状变异及其可塑性背后的基因座而言,在数千个试验小区中对数百个基因型的根系进行高通量、基于田间的表征是必要的。我们设计了一项大规模采样,在两个生长季节的不同灌溉水平下,对玉米多样性群体的根系拔出力(即从土壤中拔出根系所需的垂直力)进行采样。然后,我们对提取的根冠的根系结构进行了表征。我们发现,在差异灌溉条件下,一部分基因型的根系拔出力存在一致的表型可塑性模式,这表明根系可塑性是可预测的。通过全基因组关联分析,我们在两个灌溉水平和四个发育时间点的六次独立根系拔出力测量中,确定了54个单核苷酸多态性(SNP)具有统计学意义。对于任何处理和时间点的任何性状的每一个显著的全基因组关联研究SNP,我们使用混合模型方差分析进行基因型与环境互作测试。我们发现,54个SNP中有8个显示出显著的基因型与环境互作。根系拔出力变异的潜在候选基因包括那些参与养分运输的基因。尽管植物根系感知和响应包括水和养分在内的环境资源变异的能力的变异通常被分开处理,但这种变异背后的基因和途径可能将它们联系起来。虽然需要对已鉴定的基因进行功能验证,但我们的结果扩展了目前在全株和基因水平上对根系表型可塑性的认识,并进一步阐明了玉米根系复杂的遗传结构。