Genomic-based root plasticity to enhance abiotic stress adaptation and edible yield in grain crops

Dwivedi, Sangam L.; Stoddard, Frederick L.; Ortíz, Rodomiro

doi:10.1016/j.plantsci.2019.110365

Cited by 12 publications

(10 citation statements)

References 124 publications

(136 reference statements)

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“…A variety of tradeoff exists, inter alia , source-sink, growth-defense, or yield-nutrition nexus. Plants under biotic stress divert more resources to expression of defense related traits at the expense of growth and reproduction ( Herms and Matsson, 1992 ) and plasticity ( Dwivedi et al., 2020 ) which typically implies tradeoffs-is the way plants adapt to their physical environment. A better understanding of mechanisms that drive this antagonism may provide opportunities to refine breeding strategies that ensure such tradeoffs favor crop productivity.…”

Section: Introductionmentioning

confidence: 99%

Mitigating tradeoffs in plant breeding

Dwivedi¹,

Reynolds

Ortíz

2021

iScience

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Summary Tradeoffs among plant traits help maintain relative fitness under unpredictable conditions and maximize reproductive success. However, modifying tradeoffs is a breeding challenge since many genes of minor effect are involved. The intensive crosstalk and fine-tuning between growth and defense responsive phytohormones via transcription factors optimizes growth, reproduction, and stress tolerance. There are regulating genes in grain crops that deploy diverse functions to overcome tradeoffs, e.g., miR-156- IPA1 regulates crosstalk between growth and defense to achieve high disease resistance and yield, while OsALDH2B1 loss of function causes imbalance among defense, growth, and reproduction in rice. GNI-A1 regulates seed number and weight in wheat by suppressing distal florets and altering assimilate distribution of proximal seeds in spikelets. Knocking out ABA-induced transcription repressors (AITRs) enhances abiotic stress adaptation without fitness cost in Arabidopsis . Deploying AITRs homologs in grain crops may facilitate breeding. This knowledge suggests overcoming tradeoffs through breeding may expose new ones.

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Section: Introductionmentioning

confidence: 99%

Mitigating tradeoffs in plant breeding

Dwivedi¹,

Reynolds

Ortíz

2021

iScience

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“…Rice is one of the major abiotic stress-sensitive sources of food. Backcrossing and induced mutation methods have led to the development of rice drought-tolerant varieties that include important traits such as root architectural plasticity [ 411 , 412 , 413 , 414 , 415 , 416 ]. Gamma rays irradiated rice varieties or landraces have rendered at least 16 drought-tolerant lines, for example, MK-D-2, MK-D-3, MR219-9, and MR219-4 [ 411 , 412 , 413 , 414 ].…”

Section: Cropsmentioning

confidence: 99%

“…qDTY12.1 and qDTY3.1 drought yield QTL loci) [ 440 ] and resistance to biotic and abiotic stress [ 441 ] has been identified in this crop. It is worth noting that root architectural plasticity QTLs are closely linked to drought and submergence adaptation in rice [ 416 ]. Haplotype analysis combined with GWAS led to the identification of the SEMIDWARF1 gene involved in rice adaptation to flooding [ 442 ] ( Table 2 ).…”

Section: Cropsmentioning

confidence: 99%

“…GWAS has identified gene variants and markers for maize abiotic stress-tolerance improvement [ 543 ]. Importantly, root architecture plasticity QTLs as well as genes identified by transcriptomic approaches under water-deficit conditions are closely related, as most of them are specific and most regulated in the cortex of the mature root zone and the elongation zone changes in the root tip, comprising functions associated with cell wall reorganization, allowing continued root growth in water-deficit conditions [ 416 ]. These pieces of evidence show clear root-plasticity and stress-tolerance productivity relationships with multiple identified QTLs and promising candidate genes to increase stress tolerance in crops.…”

Section: Cropsmentioning

confidence: 99%

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Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops

Villalobos-López

Arroyo-Becerra

Quintero-Jiménez

et al. 2022

IJMS

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The major challenges that agriculture is facing in the twenty-first century are increasing droughts, water scarcity, flooding, poorer soils, and extreme temperatures due to climate change. However, most crops are not tolerant to extreme climatic environments. The aim in the near future, in a world with hunger and an increasing population, is to breed and/or engineer crops to tolerate abiotic stress with a higher yield. Some crop varieties display a certain degree of tolerance, which has been exploited by plant breeders to develop varieties that thrive under stress conditions. Moreover, a long list of genes involved in abiotic stress tolerance have been identified and characterized by molecular techniques and overexpressed individually in plant transformation experiments. Nevertheless, stress tolerance phenotypes are polygenetic traits, which current genomic tools are dissecting to exploit their use by accelerating genetic introgression using molecular markers or site-directed mutagenesis such as CRISPR-Cas9. In this review, we describe plant mechanisms to sense and tolerate adverse climate conditions and examine and discuss classic and new molecular tools to select and improve abiotic stress tolerance in major crops.

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“…This universal coping mechanism has been reported across all taxa, from humans (Feinberg, 2007), to animals (Laurila & Kujasalo, 1999;Miranda, 2017), plants (Sultan, 2000), and fungi (Slepecky & Starmer, 2009). It occurs in various aspects of an individual's life, including ontogeny (Gunter et al, 2013;Sultan, 2000), lifespan (Borges, 2009), response to biotic (Agrawal, 2001;Leal et al, 2017) or abiotic factors (Dwivedi et al, 2019;Tollrian & Heibl, 2004), pathogens or disease susceptibility (Agrawal, 1999;Feinberg, 2007), and animal behaviour (Laurila & Kujasalo, 1999;Miranda, 2017).…”

Section: Phenotypic Plasticitymentioning

confidence: 98%

Big fish, little fish: a multi-omics investigation of growth traits in silver trevally (Pseudocaranx georgianus – araara)

Valenza-Troubat

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Understanding the relationship between DNA sequence variation and the diversity of observable traits across the tree of life is a central research theme in biology. In all organisms, most traits vary continuously between individuals. Explaining the genetic basis of this quantitative variation requires disentangling genetic from non-genetic factors, as well as their interactions. The identification of causal genetic variants yields fundamental insights into how evolution creates diversity across the tree of life. Ultimately, this information can be used for medical, environmental and agricultural applications. Aquaculture is an industry that is experiencing significant global growth and is benefiting from the advances of genomic research. Genomic information helps to improve complex commercial phenotypes such as growth traits, which are easily quantified visually, but influenced by polygenes and multiple environmental factors, such as temperature. In the context of a global food crisis and environmental change, there is an urgent need not only to understand which genetic variants are potential candidates for selection gains, but also how the architecture of these traits are composed (e.g. monogenes, polygenes) and how they are influenced by and interact with the environment. The overall goal of this thesis research was to generate a genome-wide multi-omics dataset matched with exhaustive phenotypic information derived from a F0-F1 pedigree to investigate the quantitative genetic basis of growth in the New Zealand silver trevally (Pseudocaranx georgianus). These data were used to identify genomic regions that co-segregate with growth traits, and to describe the regulation of the genes involved in response to temperature fluctuations. The findings of this research helped gain fundamental insights into the genotype–phenotype map in an important teleost species and understand its ability to dynamically respond to temperature variations. This will ultimately support the establishment of a genomics-informed New Zealand aquaculture breeding programme. Chapter 1 of this thesis provides an overview of how genes interact with the environment to produce various growth phenotypes and how an understanding of this is important in aquaculture. This first chapter provides the deeper context for the research in subsequent data chapters. Chapter 2 describes the study population, the collection of phenotypic and genotypic data, and a first description of the genetic parameters of growth traits in trevally. A combination of Whole Genome Sequencing (WGS) and Genotyping-By-Sequencing (GBS) techniques were used to generate 60 thousand Single Nucleotide Polymorphism (SNP) markers for individuals in a two-generation pedigree. Together with phenotypic data, the genotyping data were used to reconstruct the pedigree, measure inbreeding levels, and estimate heritability for 10 growth traits. Parents were identified for 63% of the offspring and successful pedigree reconstruction indicated highly uneven contributions of each parent, and between the sexes, to the subsequent generation. The average inbreeding levels did not change between generations, but were significantly different between families. Growth patterns were found to be similar to that of other carangids and subject to seasonal variations. Heritability as well as genetic and phenotypic correlations were estimated using both a pedigree and a genomic relatedness matrix. All growth trait heritability estimates and correlations were found to be consistently high and positively correlated to each other. In Chapter 3, genotypic and phenotypic data were used to carry out linkage mapping and a genome-wide association study (GWAS) to map quantitative trait loci (QTLs) associated with growth differences in the F1 population. A linkage map was generated using the largest family, which allowed to scan for rare variants associated with the traits. The linkage map reported in this thesis is the first one for the Pseudocaranx genus and one of the densest for the carangid family. It included 19,861 SNPs contained in 24 linkage groups, which correspond to the 24 trevally chromosomes. Eight significant QTLs associated with height, length and weight were discovered on three linkage groups. Using GWAS, 113 SNPs associated with nine traits were identified and 29 genetic growth hot spots were uncovered. Two of the GWAS markers co-located with the QTLs discovered with the linkage mapping analysis. This demonstrates that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex phenotypes, such as growth, and provides important insights into the genetic architecture of these traits. Chapter 4, the last data chapter, investigates plasticity in gene expression patterns and growth of juvenile trevally, in response to different temperatures. Temperature conditions were experimentally manipulated for 1 month to mimic seasonal extremes. Phenotypic differences in growth were measured in 400 individuals, and the gene expression patterns of the pituitary gland and the liver were compared across treatments in a subset of 100 individuals, using RNA sequencing. Results showed that growth increased 50% more in the warmer compared with the colder condition, suggesting that temperature has a large impact on the metabolic activity associated with growth. We were able to annotate 27,887 gene models and found 39 differentially expressed genes (DEGs) in the pituitary, and 238 in the liver. Of these, 6 DEGs showed a common expression pattern between the tissues. Annotated blast matches of all DEGs revealed genes linked to major pathways affecting metabolism and reproduction. Our results indicate that native New Zealand trevally exhibit predictable plastic regulatory responses to temperature stress and the genes identified provide excellent for selective breeding objectives and studied how populations may adapt to increasing temperatures. Finally, Chapter 5 discusses the implications, future directions, and application of this research for trevally and other breeding programmes. It more broadly highlights the insights that were gained on the genetic architecture of growth, and the role of temperature in interacting and modulating genes involved in plastic growth responses.

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Genomic-based root plasticity to enhance abiotic stress adaptation and edible yield in grain crops

Cited by 12 publications

References 124 publications

Mitigating tradeoffs in plant breeding

Mitigating tradeoffs in plant breeding

Biotechnological Advances to Improve Abiotic Stress Tolerance in Crops

Big fish, little fish: a multi-omics investigation of growth traits in silver trevally (Pseudocaranx georgianus – araara)

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