From laboratory to field: yield stability and shade avoidance genes are massively differentially expressed in the field

Nelissen, Hilde; Sprenger, Heike; Demuynck, Kirin; Block, Jolien De; Hautegem, Tom Van; Vliegher, A. de; Inzé, Dirk

doi:10.1111/pbi.13269

Cited by 12 publications

(16 citation statements)

References 8 publications

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“…These differences were much bigger for six of the genes expressed in 7 DAP spikes growing in the field compared to GC. This is consistent with the observation that stress inducible genes were expressed more strongly in field than in laboratory conditions [ 33 ]. These differences in expression might be the result of allelic variation among the tested genes, their genetic background and cross-talk with environments.…”

Section: Discussionsupporting

confidence: 92%

“…It was already documented that constant irradiance during the day in controlled environments and lack of light-day transitions may significantly influence plant phenotype [ 27 ]. Consequently, many group of genes determining yield in normal and stress conditions, genes encoding chloroplast located proteins or shade avoidance (including genes involved in hormonal regulation, light and flowering) are differentially expressed in growth chamber versus field conditions [ 33 , 39 ]. Expression of CKX as well as biosynthetic IPT genes might also be regulated by the levels of available macronutrients, such as nitrate and phosphate [ 40 ], and biotic/abiotic stress conditions in the field.…”

Section: Discussionmentioning

confidence: 99%

“…It was previously indicated that yield stability genes are differentially expressed in the field compared to growth chambers [ 33 ]. These differences might mean that many genetically modified plants carrying single, agronomically important genes cannot be applied in practice [ 5 , 50 ].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, plant hormones differently regulated grain development in normal and under abiotic stress conditions [ 29 – 32 ]. It was also reported that yield stability genes are differentially expressed in the field compared to laboratory conditions [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

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Different sets of TaCKX genes affect yield-related traits in wheat plants grown in a controlled environment and in field conditions

et al. 2020

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Background TaCKX wheat gene family members (GFMs) encode the enzyme cytokinin oxidase/dehydrogenase (CKX), which irreversibly degrades cytokinins. The genes are important regulators of cytokinin content and take part in growth and development, with a major impact on yield-related traits. The goal of this research was to test whether these genes might be differentially expressed in the field compared to laboratory conditions and consequently differently affect plant development and yield. Results We compared expression and crosstalk of the TaCKX GFMs and TaNAC2-5A gene in modern varieties grown in a growth chamber (GC) and in the field and looked for differences in their impact on yield-related traits. The TaNAC2-5A gene was included in the research since it was expected to play an important role in co-regulation of these genes. The range of relative expression levels of TaCKX GFMs and TaNAC2-5A gene among tested cultivars was from 5 for TaCKX8 to more than 100 for TaCKX9 in the GC and from 6 for TaCKX8 to 275 for TaCKX10 in the field. The range was similar for four of them in the GC, but was much higher for seven others and TaNAC2-5A in the field. The TaCKX GFMs and TaNAC2-5A form co-expression groups, which differ depending on growth conditions. Consequently, the genes also differently regulate yield-related traits in the GC and in the field. TaNAC2-5A took part in negative regulation of tiller number and CKX activity in seedling roots only in controlled GC conditions. Grain number and grain yield were negatively regulated by TaCKX10 in the GC but positively by TaCKX8 and others in the field. Some of the genes, which were expressed in seedling roots, negatively influenced tiller number and positively regulated seedling root weight, CKX activity in the spikes, thousand grain weight (TGW) as well as formation of semi-empty spikes. Conclusions We have documented that: 1) natural variation in expression levels of tested genes in both environments is very high, indicating the possibility of selection of beneficial genotypes for breeding purposes, 2) to create a model of an ideotype for breeding, we need to take into consideration the natural environment.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Different sets of TaCKX genes affect yield-related traits in wheat plants grown in a controlled environment and in field conditions

et al. 2020

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“…Increasing evidence is pointing toward the unique character of plant molecular responses to combinations of stresses, which often have non‐additive effects on the molecular and phenotypic level (Atkinson & Urwin, 2012; Barah et al , 2016; Cabello et al , 2014; Davila Olivas et al , 2017; Johnson et al , 2014; Rasmussen et al , 2013; Suzuki et al , 2014; Thoen et al , 2017). As a result, perturbation studies performed under controlled laboratory conditions are often of limited predictive value for phenotypes in the field (Atkinson & Urwin, 2012; Mittler, 2006; Nelissen et al , 2014; Nelissen et al , 2019; Oh et al , 2009). It has been advocated that to close this lab‐field gap, more ‐omics data and associated phenotypic data should be generated on field‐grown plants (Alexandersson et al , 2014; Nelissen et al , 2019; Zaidem et al , 2019).…”

Section: Introductionmentioning

confidence: 99%

Using single‐plant‐omics in the field to link maize genes to functions and phenotypes

Cruz

Meyer

Ampe

et al. 2020

Molecular Systems Biology

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Most of our current knowledge on plant molecular biology is based on experiments in controlled laboratory environments. However, translating this knowledge from the laboratory to the field is often not straightforward, in part because field growth conditions are very different from laboratory conditions. Here, we test a new experimental design to unravel the molecular wiring of plants and study gene–phenotype relationships directly in the field. We molecularly profiled a set of individual maize plants of the same inbred background grown in the same field and used the resulting data to predict the phenotypes of individual plants and the function of maize genes. We show that the field transcriptomes of individual plants contain as much information on maize gene function as traditional laboratory‐generated transcriptomes of pooled plant samples subject to controlled perturbations. Moreover, we show that field‐generated transcriptome and metabolome data can be used to quantitatively predict individual plant phenotypes. Our results show that profiling individual plants in the field is a promising experimental design that could help narrow the lab‐field gap.

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Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass

et al. 2022

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The growing demand for food and feed crops in the world because of growing population and more extreme weather events requires high-yielding and resilient crops. Many agriculturally important traits are polygenic, controlled by multiple regulatory layers, and with a strong interaction with the environment. In this study, 120 F 2 families of perennial ryegrass (Lolium perenne L.) were grown across a water gradient in a semifield facility with subsoil irrigation. Genomic (single-nucleotide polymorphism [SNP]), transcriptomic (gene expression [GE]), and DNA methylomic (MET) data were integrated with feed quality trait data collected from control and drought sections in the semifield facility, providing a treatment effect. Deep root length (DRL) below 110 cm was assessed with convolutional neural network image analysis. Bayesian prediction models were used to partition phenotypic variance into its components and evaluated the proportion of phenotypic variance in all traits captured by different regulatory layers (SNP, GE, and MET). The spatial effects and effects of SNP, GE, MET, the interaction between GE and MET (GE × MET) and GE × treatment (GE Control and GE Drought ) interaction were investigated. Gene expression explained a substantial part of the genetic and spatial variance for all the investigated phenotypes, whereas MET explained residual variance not accounted for by SNPs or GE. For DRL, MET also contributed to explaining spatial variance. The study provides a statistically elegant analytical paradigm that integrates genomic, transcriptomic, and MET information to understand the regulatory mechanisms of polygenic effects for complex traits.

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From laboratory to field: yield stability and shade avoidance genes are massively differentially expressed in the field

Cited by 12 publications

References 8 publications

Different sets of TaCKX genes affect yield-related traits in wheat plants grown in a controlled environment and in field conditions

Different sets of TaCKX genes affect yield-related traits in wheat plants grown in a controlled environment and in field conditions

Using single‐plant‐omics in the field to link maize genes to functions and phenotypes

Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass

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