From lab to field, new approaches to phenotyping root system architecture

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Plant root system architecture (RSA) is plastic and dynamic, allowing plants to respond to their environment in order to optimize acquisition of important soil resources. A number of RSA traits are known to be correlated with improved crop performance. There is increasing recognition that future gains in productivity, especially under low input conditions, can be achieved through optimization of RSA. However, realization of this goal has been hampered by low resolution and low throughput approaches for characterizing RSA. To overcome these limitations, new methods are being developed to facilitate high throughput and high content RSA phenotyping. Here we summarize laboratory and field approaches for phenotyping RSA, drawing particular attention to recent advances in plant imaging and analysis. Improvements in phenotyping will facilitate the genetic analysis of RSA and aid in the identification of the genetic loci underlying useful agronomic traits.

Highlights

► Several root system architecture (RSA) traits are correlated with agronomic performance. ► Optimizing RSA may increase crop productivity. ► Historically, methods to characterize RSA have lacked resolution and throughput. ► New methods to characterize RSA in three dimensions are being developed. ► Future challenges include correlating lab RSA traits with crop productivity.

Introduction

Roots play a vital role in plant growth, development, and fitness. They provide anchorage and support for the shoot, they are responsible for the uptake of water and nutrients, they act as storage organs for carbohydrates and other reserves, they are a site of biosynthesis of important hormones necessary for development, and they are involved in interactions with the rhizosphere. Therefore, it is not surprising that the study of roots remains a central theme in plant biology.

Plants typically produce only one or few roots during embryogenesis, with the vast majority of the root system developing as the plant grows [2, 3]. The spatial distribution, age, and identity of all roots from a single plant are collectively termed the plant's root system architecture (RSA) [4•, 5, 6]. RSA is plastic and dynamic, allowing plants to incorporate information about the environment into decisions on root growth and development [7•, 8, 9, 10]. Of particular note, plants typically increase allocation of biomass to roots under nutrient limiting conditions [11, 12, 13]. Not surprisingly, it is well established that RSA is correlated with agronomic productivity under limiting conditions. For example, deep rooting is associated with drought-tolerance in bean [14, 15], wheat [16] and maize [17]. Furthermore, narrower and deeper root systems may be primarily responsible for the historical increases in maize yields associated with higher planting densities [18]. By contrast, dense shallow roots leading to increased topsoil foraging are associated with improved performance under low P conditions in bean, soybean [19] and maize [20].

Despite the importance of roots, direct selection for optimal RSA characteristics in the field has not been routine. For practical reasons, breeding efforts have typically focused on improving above-ground traits with an obvious emphasis on yield. While these efforts have been instrumental for increasing crop production to present capacity, future yield increases are likely to be constrained by lower water and fertilizer inputs, and the use of marginal lands containing nutrient-poor soils [21••, 22•, 23]. Because the heritability of yield tends to decrease under stress conditions [24, 25], directed modification of RSA holds particular promise for improving agricultural productivity under low input conditions [21••].

The genetic basis of RSA in crops is poorly understood although it is clear that RSA is a complex trait controlled by many genes. Numerous quantitative trait loci (QTL) that regulate RSA, particularly in response to environmental cues, have been identified (e.g. [26, 27, 28, 29, 30, 31]). However, high throughput phenotyping remains a bottleneck for genetic analysis of RSA. Here we summarize new approaches to phenotyping RSA that are being developed to address this bottleneck. When combined with genetic and genomic analyses, improved RSA phenotyping should not only advance our understanding of RSA regulation, but lead to the development of crops with improved agronomic performance.

Section snippets

Plant growth methods

The analysis of RSA in field-grown plants provides a true representation of root growth in an agriculturally relevant context. However, soil obscures root system visualization in situ, and roots can form extensive networks in the soil, which prevents their easy extraction for observation. Therefore, complementary laboratory and greenhouse approaches have been devised to overcome these limitations. For example, to better access the root system, plants can be grown in mesocosms such as soil or

RSA phenotyping in the field

While laboratory RSA phenotyping methods provide controlled environments, allow increased throughput, and require fewer resources, they may not accurately reflect RSA under field conditions. Therefore, high-throughput RSA phenotyping in the field is needed to complement and validate laboratory studies. Historically, RSA has been observed in the field by excavation of soil around the root system [1], or excavation of the plant from the field followed by separation of roots from the soil stratum

Conclusions

There is increasing recognition that advances in agronomic productivity, particularly under nutrient limiting conditions, may be achieved through directed modification of RSA. To meet this goal, improved phenotyping approaches are needed that can capture and quantify complex features of RSA. Although the ultimate target is the ability to monitor RSA in the field, current methods for phenotyping RSA in field-grown plants lack resolution and throughput (Figure 1). The most promising approaches

Competing interests

GrassRoots Biotechnology is a for-profit company that conducts research to enhance agricultural and biofuel crops. We apologize to any colleagues whose work was excluded because of space constraints.

References and recommended reading

Papers of particular interest, published within the annual period of review, have been highlighted as:

  • • of special interest

  • •• of outstanding interest

Acknowledgements

We thank Jenn To, Allen Sessions, and Ai-Jiuan Wu for comments on the manuscript. Research at GrassRoots on improving root architecture in energy crops is supported by the Small Business Innovation Research (SBIR) program of the USDA National Institute for Food and Agriculture (NIFA), Grant Number 2010-33610-21633. Research on root system architecture in PNB's academic lab is supported by a grant from the NSF Plant Genome Research Program.

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