scholarly journals Transcriptomic Analysis Reveals the Contribution of QMrl-7B to Wheat Root Growth and Development

2020 ◽  
Author(s):  
Jiajia Liu ◽  
Hanwen Li ◽  
Na Zhang ◽  
Deyuan Meng ◽  
Liya Zhi ◽  
...  
Keyword(s):  
Root Growth ◽  
Root System ◽  
Root Traits ◽  
Wheat Root ◽  
Root System Architecture ◽  
Transcriptomic Analysis ◽  
Differentially Expressed ◽  
Yield Potential ◽  
Trait Locus ◽  
Normal Nitrogen

Abstract Backgound: Roots are the major organs for water and nutrient acquisition and substantially affect plant growth, development and reproduction. Improvements to root system architecture are highly important for increasing yield potential of bread wheat. QMrl-7B, a major stable quantitative trait locus (QTL) that controls maximum root length (MRL), strongly contributes to an improved root system in wheat. Results: To further analyse the biological functions of QMrl-7B in root development, two types of Triticum aestivum near isogenic lines (NILs), one with superior QMrl-7B alleles from cultivar Kenong 9204 (KN9204) and another with inferior QMrl-7B alleles from cultivar Jing 411 (J411), were subjected to transcriptomic analysis. Among all the mapped genes analysed, 4871 genes were identified as being differentially expressed between the pairwise NILs under different nitrogen (N) conditions, with 3543 genes expressed under normal-nitrogen (NN) condition and 2689 genes expressed under low-nitrogen (LN) condition. These genes encode proteins that include mainly NO3- transporters, phytohormone signalling components and transcription factors (TFs), indicating the presence of a complex regulatory network involved in root determination. In addition, among the 13524 LN-induced differentially expressed genes (DEGs) detected in this assay, 4308 were specifically expressed in the A-NIL which brings superior alleles, and 2463 were expressed specifically in the B-NIL which brings inferior alleles. These DEGs reflect different responses of the two types of NILs to varying N supplies, which likely involve LN-induced root growth. Conclusions: These results explain the better-developed root system and increased root vitality provided by the superior alleles of QMrl-7B and provide a deeper understanding of the genetic underpinnings of root traits, pointing to a valuable locus suitable for future breeding efforts for sustainable agriculture.

scholarly journals Modeling root system growth around obstacles

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Wencheng Jin ◽  
Jayde Aufrecht ◽  
Fernando Patino-Ramirez ◽  
Heidy Cabral ◽  
Chloé Arson ◽  
...  
Keyword(s):  
Root Growth ◽  
Root System ◽  
Time Lapse ◽  
Wheat Root ◽  
Root System Architecture ◽  
Main Axis ◽  
Wheat Roots ◽  
Wheat Seedlings ◽  
Proposed Model ◽  
3D Printed

Abstract State-of-the-Art models of Root System Architecture (RSA) do not allow simulating root growth around rigid obstacles. Yet, the presence of obstacles can be highly disruptive to the root system. We grew wheat seedlings in sealed petri dishes without obstacle and in custom 3D-printed rhizoboxes containing obstacles. Time-lapse photography was used to reconstruct the wheat root morphology network. We used the reconstructed wheat root network without obstacle to calibrate an RSA model implemented in the R-SWMS software. The root network with obstacles allowed calibrating the parameters of a new function that models the influence of rigid obstacles on wheat root growth. Experimental results show that the presence of a rigid obstacle does not affect the growth rate of the wheat root axes, but that it does influence the root trajectory after the main axis has passed the obstacle. The growth recovery time, i.e. the time for the main root axis to recover its geotropism-driven growth, is proportional to the time during which the main axis grows along the obstacle. Qualitative and quantitative comparisons between experimental and numerical results show that the proposed model successfully simulates wheat RSA growth around obstacles. Our results suggest that wheat roots follow patterns that could inspire the design of adaptive engineering flow networks.

scholarly journals ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture

2020 ◽  
Author(s):  
Nicolás Gaggion ◽  
Federico Ariel ◽  
Vladimir Daric ◽  
Éric Lambert ◽  
Simon Legendre ◽  
...  
Keyword(s):  
Deep Learning ◽  
Root System ◽  
High Throughput ◽  
System Architecture ◽  
Root Traits ◽  
Root System Architecture ◽  
Machine Intelligence ◽  
Reconstruction Process ◽  
High Throughput Phenotyping ◽  
3D Printed

ABSTRACTDeep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence approaches have been hampered by the inaccessibility of the rhizosphere. Here we present ChronoRoot, a system which combines 3D printed open-hardware with deep segmentation networks for high temporal resolution phenotyping of plant roots in agarized medium. We developed a novel deep learning based root extraction method which leverages the latest advances in convolutional neural networks for image segmentation, and incorporates temporal consistency into the root system architecture reconstruction process. Automatic extraction of phenotypic parameters from sequences of images allowed a comprehensive characterization of the root system growth dynamics. Furthermore, novel time-associated parameters emerged from the analysis of spectral features derived from temporal signals. Altogether, our work shows that the combination of machine intelligence methods and a 3D-printed device expands the possibilities of root high-throughput phenotyping for genetics and natural variation studies as well as the screening of clock-related mutants, revealing novel root traits.

scholarly journals Two Wheat Cultivars with Contrasting Post-Embryonic Root Biomass Differ in Shoot Re-Growth after Defoliation: Implications for Breeding Grazing Resilient Forages

Plants ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 470
Author(s):  
Paez-Garcia ◽  
Liao ◽  
Blancaflor
Keyword(s):  
Winter Wheat ◽  
Root Growth ◽  
Root System ◽  
Aboveground Biomass ◽  
Root Traits ◽  
Shoot Biomass ◽  
Wheat Cultivars ◽  
Leaf Clipping ◽  
The Impact ◽  
Embryonic Root

The ability of forages to quickly resume aboveground growth after grazing is a trait that enables farmers to better manage their livestock for maximum profitability. Leaf removal impairs root growth. As a consequence of a deficient root system, shoot re-growth is inhibited leading to poor pasture performance. Despite the importance of roots for forage productivity, they have not been considered as breeding targets for improving grazing resilience due in large part to the lack of knowledge on the relationship between roots and aboveground biomass re-growth. Winter wheat (Triticum aestivum) is extensively used as forage source in temperate climates worldwide. Here, we investigated the impact of leaf clipping on specific root traits, and how these influence shoot re-growth in two winter wheat cultivars (i.e., Duster and Cheyenne) with contrasting root and shoot biomass. We found that root growth angle and post-embryonic root growth in both cultivars are strongly influenced by defoliation. We discovered that Duster, which had less post-embryonic roots before defoliation, reestablished its root system faster after leaf cutting compared with Cheyenne, which had a more extensive pre-defoliation post-embryonic root system. Rapid resumption of root growth in Duster after leaf clipping was associated with faster aboveground biomass re-growth even after shoot overcutting. Taken together, our results suggest that lower investments in the production of post-embryonic roots presents an important ideotype to consider when breeding for shoot re-growth vigor in dual purpose wheat.

scholarly journals Trait-Based Root Phenotyping as a Necessary Tool for Crop Selection and Improvement

Agronomy ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1328
Author(s):  
Rebecca K. McGrail ◽  
David A. Van Sanford ◽  
David H. McNear
Keyword(s):  
Root System ◽  
System Architecture ◽  
Production Systems ◽  
Root Traits ◽  
Root System Architecture ◽  
Root Decomposition ◽  
Crop Breeding ◽  
Organic Acid Production ◽  
Nutritional Qualities ◽  
Chemical Traits

Most of the effort of crop breeding has focused on the expression of aboveground traits with the goals of increasing yield and disease resistance, decreasing height in grains, and improvement of nutritional qualities. The role of roots in supporting these goals has been largely ignored. With the increasing need to produce more food, feed, fiber, and fuel on less land and with fewer inputs, the next advance in plant breeding must include greater consideration of roots. Root traits are an untapped source of phenotypic variation that will prove essential for breeders working to increase yields and the provisioning of ecosystem services. Roots are dynamic, and their structure and the composition of metabolites introduced to the rhizosphere change as the plant develops and in response to environmental, biotic, and edaphic factors. The assessment of physical qualities of root system architecture will allow breeding for desired root placement in the soil profile, such as deeper roots in no-till production systems plagued with drought or shallow roots systems for accessing nutrients. Combining the assessment of physical characteristics with chemical traits, including enzymes and organic acid production, will provide a better understanding of biogeochemical mechanisms by which roots acquire resources. Lastly, information on the structural and elemental composition of the roots will help better predict root decomposition, their contribution to soil organic carbon pools, and the subsequent benefits provided to the following crop. Breeding can no longer continue with a narrow focus on aboveground traits, and breeding for belowground traits cannot only focus on root system architecture. Incorporation of root biogeochemical traits into breeding will permit the creation of germplasm with the required traits to meet production needs in a variety of soil types and projected climate scenarios.

scholarly journals Root plasticity under abiotic stress

2021 ◽  
Author(s):  
Rumyana Karlova ◽  
Damian Boer ◽  
Scott Hayes ◽  
Christa Testerink
Keyword(s):  
Abiotic Stress ◽  
Root Growth ◽  
Root System ◽  
System Architecture ◽  
Root System Architecture ◽  
Root Anatomy ◽  
Soil Conditions ◽  
Root Plasticity ◽  
Cellular Mechanisms ◽  
Aerenchyma Formation

Abstract Abiotic stresses increasingly threaten existing ecological and agricultural systems across the globe. Plant roots perceive these stresses in the soil and adapt their architecture accordingly. This review provides insights into recent discoveries showing the importance of root system architecture and plasticity for the survival and development of plants under heat, cold, drought, salt, and flooding stress. In addition, we review the molecular regulation and hormonal pathways involved in controlling root system architecture plasticity, main root growth, branching and lateral root growth, root hair development and formation of adventitious roots. Several stresses affect root anatomy by causing aerenchyma formation, lignin and suberin deposition, and Casparian strip modulation. Roots can also actively grow towards favourable soil conditions and avoid environments detrimental to their development. Recent advances in understanding the cellular mechanisms behind these different root tropisms are discussed. Understanding root plasticity will be instrumental for the development of crops that are resilient in the face of abiotic stress.

scholarly journals Chickpea (Cicer arietinum L.) root system architecture adaptation to initial soil moisture improves seed development in dry-down conditions

2020 ◽  
Author(s):  
Thibaut Bontpart ◽  
Ingrid Robertson ◽  
Valerio Giuffrida ◽  
Cristobal Concha ◽  
Livia C. T. Scorza ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Root Growth ◽  
Root System ◽  
Seed Development ◽  
Water Use ◽  
System Architecture ◽  
Adaptive Strategies ◽  
Root System Architecture ◽  
Initial Soil Moisture ◽  
Initial Soil

AbstractSoil water deficit (WD) impacts vascular plant phenology, morpho-physiology, and reproduction. Chickpea, which is mainly grown in semi-arid areas, is a good model plant to dissect mechanisms involved in drought resistance.We used a rhizobox-based phenotyping system to simultaneously and non-destructively characterise root system architecture (RSA) dynamics and water use (WU) patterns. We compared the drought-adaptive strategies of ‘Teketay’ to the drought-sensitive genotype ICC 1882 in high and low initial soil moisture without subsequent irrigation.WD restricted vegetative and reproductive organ biomass for both genotypes. Teketay displayed greater adaptability for RSA dynamics and WU patterns and revealed different drought adaptive strategies depending on initial soil moisture: escape when high, postponement when low. These strategies were manifested in distinct RSA dynamics: in low initial soil moisture, its reduced root growth at the end of the vegetative phase was followed by increased root growth in deeper, wetter soil strata, which facilitated timely WU for seed development and produced better-developed seeds.We demonstrate that RSA adaptation to initial soil moisture is one mechanism by which plants can tolerate WD conditions and ensure reproduction by producing well-developed seeds. Our approach will help in identifying the genetic basis for large plasticity of RSA dynamics which enhances the resilience with which crops can optimally adapt to various drought scenarios.HighlightRoot system architecture and water use patterns change dynamically for distinct drought adaptation strategies in chickpea.

Root growth and root system architecture of field-grown maize in response to high planting density

2018 ◽  
Vol 430 (1-2) ◽  
pp. 395-411 ◽  
Author(s):  
Hui Shao ◽  
Tingting Xia ◽  
Dali Wu ◽  
Fanjun Chen ◽  
Guohua Mi
Keyword(s):  
Root Growth ◽  
Root System ◽  
System Architecture ◽  
Root System Architecture ◽  
Planting Density

Pinpointing Genomic Regions Associated with Root System Architecture in Rice Through an Integrative Meta-Analysis Approach

2021 ◽  
Author(s):  
Parisa Daryani ◽  
Hadi Darzi Ramandi ◽  
Sara Dezhsetan ◽  
Raheleh Mirdar Mansuri ◽  
Ghasem Hosseini Salekdeh ◽  
...  
Keyword(s):  
Drought Stress ◽  
Root System ◽  
Candidate Genes ◽  
System Architecture ◽  
Meta Analysis ◽  
Root System Architecture ◽  
Stress Conditions ◽  
Yield Potential ◽  
Analysis Approach ◽  
Genomic Regions

Abstract Root system architecture (RSA) is an important factor for facilitating water and nutrient uptake from deep soils and adaptation to drought stress conditions. In the present research, an integrated meta-analysis approach was employed to find candidate genes and genomic regions involved in rice RSA traits. A whole-genome meta-analysis was performed for 425 initial QTLs reported in 34 independent experiments controlling RSA traits under control and drought stress conditions in the previous twenty years. Sixty-four consensus meta-QTLs (MQTLs) were detected, unevenly distributed on twelve rice chromosomes. The confidence interval (CI) of the identified MQTLs was obtained as 0.11-14.23 cM with an average of 3.79 cM, which was 3.88 times narrower than the mean CI of the original QTLs. Interestingly, 52 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The genes located in these RSA related MQTLs were detected, and explored to find the drought-responsive genes in the rice root based on the RNA-seq and microarray data. Multiple RSA and drought tolerance associated genes were found in the MQTLs including the genes involved in auxin biosynthesis or signaling (e.g. YUCCA, WOX, AUX/IAA, ARF), root angle (DRO1-related genes), lateral root development (e.g. DSR, WRKY), root diameter (e.g. OsNAC5), plant cell wall (e.g. EXPA) and lignification (e.g. C4H, PAL, PRX and CAD). The genes located both in the SNP peak positions and in the high-overview-index MQTLs for root architecture traits are suggested as novel candidate genes for further functional analysis.. The promising candidate genes and MQTLs would be applicable to genetic engineering and MQTL-assisted breeding of root phenotypes aimed at improving yield potential, stability and performance in a water-stressed environment.

scholarly journals Genetic Dissection of the Seminal Root System Architecture in Mediterranean Durum Wheat Landraces by Genome-Wide Association Study

Agronomy ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 364 ◽  
Author(s):  
Martina Roselló ◽  
Conxita Royo ◽  
Miguel Sanchez-Garcia ◽  
Jose Miguel Soriano
Keyword(s):  
Durum Wheat ◽  
Root System ◽  
System Architecture ◽  
Eastern Mediterranean Region ◽  
Root Traits ◽  
Root System Architecture ◽  
Seminal Root ◽  
Large Variability ◽  
Wheat Landraces ◽  
Durum Wheat Landraces

Roots are crucial for adaptation to drought stress. However, phenotyping root systems is a difficult and time-consuming task due to the special feature of the traits in the process of being analyzed. Correlations between root system architecture (RSA) at the early stages of development and in adult plants have been reported. In this study, the seminal RSA was analysed on a collection of 160 durum wheat landraces from 21 Mediterranean countries and 18 modern cultivars. The landraces showed large variability in RSA, and differences in root traits were found between previously identified genetic subpopulations. Landraces from the eastern Mediterranean region, which is the driest and warmest within the Mediterranean Basin, showed the largest seminal root size in terms of root length, surface, and volume and the widest root angle, whereas landraces from eastern Balkan countries showed the lowest values. Correlations were found between RSA and yield-related traits in a very dry environment. The identification of molecular markers linked to the traits of interest detected 233 marker-trait associations for 10 RSA traits and grouped them in 82 genome regions named marker-train association quantitative trait loci (MTA-QTLs). Our results support the use of ancient local germplasm to widen the genetic background for root traits in breeding programs.

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