scholarly journals Root System Architecture Plasticity of Bread Wheat in Response to Oxidative Burst under Extended Osmotic Stress

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 939
Author(s):  
Omar Azab ◽  
Abdullah Al-Doss ◽  
Thobayet Alshahrani ◽  
Salah El-Hendawy ◽  
Adel M. Zakri ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Membrane Potential ◽  
Osmotic Stress ◽  
Root System ◽  
Bread Wheat ◽  
System Architecture ◽  
Mitochondrial Membrane ◽  
Root System Architecture ◽  
Root Tips ◽  
Scavenging Capacity

There is a demand for an increase in crop production because of the growing population, but water shortage hinders the expansion of wheat cultivation, one of the most important crops worldwide. Polyethylene glycol (PEG) was used to mimic drought stress due to its high osmotic potentials generated in plants subjected to it. This study aimed to determine the root system architecture (RSA) plasticity of eight bread wheat genotypes under osmotic stress in relation to the oxidative status and mitochondrial membrane potential of their root tips. Osmotic stress application resulted in differences in the RSA between the eight genotypes, where genotypes were divided into adapted genotypes that have non-significant decreased values in lateral roots number (LRN) and total root length (TRL), while non-adapted genotypes have a significant decrease in LRN, TRL, root volume (RV), and root surface area (SA). Accumulation of intracellular ROS formation in root tips and elongation zone was observed in the non-adapted genotypes due to PEG-induced oxidative stress. Mitochondrial membrane potential (∆Ψm) was measured for both stress and non-stress treatments in the eight genotypes as a biomarker for programmed cell death as a result of induced osmotic stress, in correlation with RSA traits. PEG treatment increased scavenging capacity of the genotypes from 1.4-fold in the sensitive genotype Gemmiza 7 to 14.3-fold in the adapted genotype Sakha 94. The adapted genotypes showed greater root trait values, ∆Ψm plasticity correlated with high scavenging capacity, and less ROS accumulation in the root tissue, while the non-adapted genotypes showed little scavenging capacity in both treatments, accompanied by mitochondrial membrane permeability, suggesting mitochondrial dysfunction as a result of oxidative stress.

scholarly journals Genomic prediction and QTL mapping of root system architecture and above-ground agronomic traits in rice (Oryza sativa L.) with a multi-trait index and Bayesian networks

2021 ◽  
Author(s):  
Santosh Sharma ◽  
Shannon R M Pinson ◽  
David R Gealy ◽  
Jeremy D Edwards
Keyword(s):  
Oryza Sativa ◽  
Root System ◽  
System Architecture ◽  
Genomic Prediction ◽  
Agronomic Traits ◽  
Oryza Sativa L ◽  
Root System Architecture ◽  
Root Tips ◽  
Phenotypic Data ◽  
Genomic Predictions

Abstract Root system architecture (RSA) is a crucial factor in resource acquisition and plant productivity. Roots are difficult to phenotype in the field, thus new tools for predicting phenotype from genotype are particularly valuable for plant breeders aiming to improve RSA. This study identifies quantitative trait loci (QTLs) for RSA and agronomic traits in a rice (Oryza sativa) recombinant inbred line (RIL) population derived from parents with contrasting RSA traits (PI312777 x Katy). The lines were phenotyped for agronomic traits in the field, and separately grown as seedlings on agar plates which were imaged to extract RSA trait measurements. QTLs were discovered from conventional linkage analysis and from a machine learning approach using a Bayesian network (BN) consisting of genome-wide SNP data and phenotypic data. The genomic prediction abilities (GPAs) of multi-QTL models and the BN analysis were compared with the several standard genomic prediction methods. We found GPAs were improved using multi-trait (BN) compared to single trait genomic prediction in traits with low to moderate heritability. Two groups of individuals were selected based on genomic predictions and a modified rank sum index (GSRI) indicating their divergence across multiple RSA traits. Selections made on genomic predictions did result in differences between the group means for numerous RSA. The ranking accuracy across RSA traits among the individual selected RILs ranged from 0.14 for root volume to 0.59 for lateral root tips. We conclude that the multi-trait genomic prediction model using BN can in some cases improve the GPA of RSA and agronomic traits, and the GSRI approach is useful to simultaneously select for a desired set of RSA traits in a segregating population.

scholarly journals Early Evaluation of Root System Architecture in Maize Using X-ray Microscopy of Root Tips

2020 ◽  
Vol 26 (S2) ◽  
pp. 1056-1057
Author(s):  
Keith Duncan ◽  
Ni Jiang ◽  
Tyler Dowd ◽  
Christopher Topp
Keyword(s):  
Root System ◽  
System Architecture ◽  
Root System Architecture ◽  
Root Tips ◽  
X Ray ◽  
Early Evaluation

scholarly journals Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

2020 ◽  
Vol 11 ◽  
Author(s):  
Waldiodio Seck ◽  
Davoud Torkamaneh ◽  
François Belzile
Keyword(s):  
Root System ◽  
System Architecture ◽  
Phenotypic Variation ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Primary Root ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

scholarly journals Genome-wide association analysis unveils novel QTLs for seminal root system architecture traits in Ethiopian durum wheat

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Admas Alemu ◽  
Tileye Feyissa ◽  
Marco Maccaferri ◽  
Giuseppe Sciara ◽  
Roberto Tuberosa ◽  
...  
Keyword(s):  
Durum Wheat ◽  
Root System ◽  
System Architecture ◽  
Root Length ◽  
Dry Weight ◽  
Root System Architecture ◽  
High Density ◽  
Soil Conditions ◽  
Root Dry Weight ◽  
Seminal Roots

Abstract Background Genetic improvement of root system architecture is essential to improve water and nutrient use efficiency of crops or to boost their productivity under stress or non-optimal soil conditions. One hundred ninety-two Ethiopian durum wheat accessions comprising 167 historical landraces and 25 modern cultivars were assembled for GWAS analysis to identify QTLs for root system architecture (RSA) traits and genotyped with a high-density 90 K wheat SNP array by Illumina. Results Using a non-roll, paper-based root phenotyping platform, a total of 2880 seedlings and 14,947 seminal roots were measured at the three-leaf stage to collect data for total root length (TRL), total root number (TRN), root growth angle (RGA), average root length (ARL), bulk root dry weight (RDW), individual root dry weight (IRW), bulk shoot dry weight (SDW), presence of six seminal roots per seedling (RT6) and root shoot ratio (RSR). Analysis of variance revealed highly significant differences between accessions for all RSA traits. Four major (− log10P ≥ 4) and 34 nominal (− log10P ≥ 3) QTLs were identified and grouped in 16 RSA QTL clusters across chromosomes. A higher number of significant RSA QTL were identified on chromosome 4B particularly for root vigor traits (root length, number and/or weight). Conclusions After projecting the identified QTLs on to a high-density tetraploid consensus map along with previously reported RSA QTL in both durum and bread wheat, fourteen nominal QTLs were found to be novel and could potentially be used to tailor RSA in elite lines. The major RGA QTLs on chromosome 6AL detected in the current study and reported in previous studies is a good candidate for cloning the causative underlining sequence and identifying the beneficial haplotypes able to positively affect yield under water- or nutrient-limited conditions.

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