The global human population is expected to reach 10 billion within the next 30 years [1]. Current yield increases for major crops will likely not be able to satisfy the future demand. Improving plant architecture, both above and below ground, is one of the most effective ways to increase crop productivity. During the Green Revolution, the manipulation of above-ground plant features resulted in substantial increases in cereal yields [2]. The roots, which serve as the interface between the plant and the dynamic soil environment, have crucial functions affecting plant productivity and tolerance to environmental stresses [3]. Research regarding plant roots has been limited by the complexity of phenotyping the underground plant parts and because there is relatively little relevant genetic information available to breeders. However, a recent study confirmed that modifying the root architecture can increase resource use efficiency and yields [4], which has prompted plant scientists to focus more of their attention on plant roots. Clarifying the genetic mechanism regulating root development is critical for enhancing crop performance and increasing food security.
To characterise the effects of root traits on crop performance, several phenotyping methods involving artificial conditions (e.g., on germination paper) and natural conditions (e.g., field trials) have been developed to evaluate genotypic variations and the utility of root traits [5]. Moreover, shovelomics-based experiments have been widely used to investigate soil resource acquisition by maize crown roots [6]. Furthermore, maize crown root traits, including crown root number [7], diameter [8], and growth angle [4], are associated with the above-ground performance of plants as well as the nutrient content and grain yield. Another study proved that decreasing the number of roots in maize inbred lines may lead to deeper root growth and enhanced acquisition of water in dry soils [7]. Decreasing the number of crown roots can enhance nitrogen acquisition from low-nitrogen soils [9]. The root angle is a crucial factor influencing how deep roots can grow in the soil to obtain water and nutrients. RSA that are narrow and vertically oriented are typically associated with increased drought tolerance [10]. In maize and wheat, root growth depth is positively associated with yield under drought conditions. Relatively steep root angles increase rooting depth and drought tolerance in rice [4] and common bean [11]. The root angle also affects nitrogen capture, with steep maize root angles under low-nitrogen conditions potentially increasing nitrogen acquisition by 15–50% as the soil nitrogen content decreases [12; 13]. Compared with thin roots, thick roots have greater mechanical strength, leading to better anchorage and lodging resistance, protection against herbivory, and enhanced soil penetration [8]. Inbred lines exhibiting high nitrogen use efficiency (NUE) reportedly have larger root diameters than lines with a lower NUE under low-nitrogen conditions [8]. An exposure to nitrogen stress induces several maize genotypes to increase their root diameter. Thus, the root diameter can influence adaptive stress responses. Accordingly, breeding maize lines with modified crown roots may lead to the development of new cultivars suitable for various stress conditions.
Exploring the natural variations in crown root traits may lead to new insights into root development, while also revealing elite allelic variations that can enhance root performance. Many recent quantitative trait locus (QTL) mapping studies regarding the number of maize crown roots have been conducted [14]. For example, QTL analyses in single and multiple environments have been performed for the crown root angle (CRA), the crown root diameter (CRD), and the crown root number (CRN) in a recombinant inbred line population. A total of 46 QTL were detected in a single environment and 25 QTL were identified in multiple environments, with most loci confirmed as minor-effect QTL for crown root traits [15]. Two major QTL for the total brace root number were identified by Ku et al. [16], and the largest additive effect was 16.4–17.9%. Cai et al. detected five QTL for CRN at three maize growth stages, including one consensus QTL in chromosome bin 10.4 [17]. There have been relatively few studies on the maize CRA. Only 10 root angle-related QTL were identified in two maize–teosinte F2 populations [18]. In rice, six major QTL for root angle (DRO1, DRO2, DRO3, DRO4, DRO5, and qSOR1) have been identified, and DRO1 and qSOR1 have been cloned [19; 20]. Additionally, DRO1 is the first cloned gene associated with the root growth angle. Its expression is negatively regulated by auxin and the encoded protein helps mediate root tip cell elongations related to asymmetrical root growth and the downward bending of the root in response to gravity [4]. A previous study confirmed that qSOR1, which is a DRO1 homologue, is also negatively regulated by auxin, and is predominantly expressed in root columella cells to influence root gravitropic responses [20]. All of these genes are potential targets for root system architecture (RSA)-related breeding. Regarding the root diameter, only one QTL associated with CRD has been detected under well-watered and water stress conditions [21]. Moreover, 21 root architecture traits were evaluated in three recombinant inbred populations, but only one root diameter-related QTL was identified [22].
To date, only a few maize studies have identified QTL and allelic variations associated with RSA development in the field. As an alternative to traditional QTL mapping and map-based cloning, a genome-wide association study (GWAS) can identify the genes and allelic variations responsible for natural phenotypic diversity. In this study, the CRN, CRA, and CRD of 348 maize inbred lines were evaluated in three field trials. The objectives of this study were (i) to study phenotypic variation of crown root traits within a maize association panel, (ii) to identify significant SNPs associated with CRA, CRD and CRN, and (iii) to detected potential candidate genes and natural variations for crown root development.