Genomic, Biochemical, and Modeling Analyses of Asparagine Synthetases from Wheat

Xu, Hongwei; Curtis, Tanya Y.; Powers, Stephen J.; Raffan, Sarah; Gao, Runhong; Huang, Jianhua; Heiner, Monika; Gilbert, David; Halford, Nigel G.

doi:10.3389/fpls.2017.02237

Cited by 23 publications

(37 citation statements)

References 41 publications

(63 reference statements)

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“…The enzymes encoded by these genes are very similar to each other, with molecular masses between 65 and 67 kDa. Heterologous expression and biochemical characterisation of TaASN1 and TaASN2 enzymes also showed them to have similar biochemical properties [23]. TaASN1 , TaASN2 and TaASN4 are all single copy genes, located on chromosomes 5, 3 and 4, respectively, of each genome (A, B and D), although some varieties lack a TaASN2 gene in the B genome [23].…”

Section: Resultsmentioning

confidence: 99%

“…This was despite the apparent lack of expression of a B genome TaASN2 homeologue. Some varieties lack a B genome TaASN2 homeologue [23], including Chinese Spring, which was the reference genome used in the study. Analysis of the RNA-seq reads did not reveal any single nucleotide polymorphisms to suggest that a B genome homeologue was being expressed; in other words, all the reads could be assigned to the A or D genome homeologues.…”

Section: Resultsmentioning

confidence: 99%

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Contrasting gene expression patterns in grain of high and low asparagine wheat genotypes in response to sulphur supply

et al. 2019

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Background Free asparagine is the precursor for acrylamide formation during cooking and processing of grains, tubers, beans and other crop products. In wheat grain, free asparagine, free glutamine and total free amino acids accumulate to high levels in response to sulphur deficiency. In this study, RNA-seq data were acquired for the embryo and endosperm of two genotypes of bread wheat, Spark and SR3, growing under conditions of sulphur sufficiency and deficiency, and sampled at 14 and 21 days post anthesis (dpa). The aim was to provide new knowledge and understanding of the genetic control of asparagine accumulation and breakdown in wheat grain. Results There were clear differences in gene expression patterns between the genotypes. Sulphur responses were greater at 21 dpa than 14 dpa, and more evident in SR3 than Spark. TaASN2 was the most highly expressed asparagine synthetase gene in the grain, with expression in the embryo much higher than in the endosperm, and higher in Spark than SR3 during early development. There was a trend for genes encoding enzymes of nitrogen assimilation to be more highly expressed in Spark than SR3 when sulphur was supplied. TaASN2 expression in the embryo of SR3 increased in response to sulphur deficiency at 21 dpa, although this was not observed in Spark. This increase in TaASN2 expression was accompanied by an increase in glutamine synthetase gene expression and a decrease in asparaginase gene expression. Asparagine synthetase and asparaginase gene expression in the endosperm responded in the opposite way. Genes encoding regulatory protein kinases, SnRK1 and GCN2, both implicated in regulating asparagine synthetase gene expression, also responded to sulphur deficiency. Genes encoding bZIP transcription factors, including Opaque2/bZIP9, SPA/bZIP25 and BLZ1/OHP1/bZIP63, all of which contain SnRK1 target sites, were also expressed. Homeologues of many genes showed differential expression patterns and responses, including TaASN2 . Conclusions Data on the genetic control of free asparagine accumulation in wheat grain and its response to sulphur supply showed grain asparagine levels to be determined in the embryo, and identified genes encoding signalling and metabolic proteins involved in asparagine metabolism that respond to sulphur availability. Electronic supplementary material The online version of this article (10.1186/s12864-019-5991-8) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Contrasting gene expression patterns in grain of high and low asparagine wheat genotypes in response to sulphur supply

et al. 2019

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“…In other words, the high asparagine synthetase gene expression in the grain of wheat, accounted for mainly by TaASN2, has not been observed in maize. In addition, biochemical analyses have shown the reactions catalysed by the wheat asparagine synthetases, ASN1 and ASN2, to proceed much more rapidly than has been reported for the maize enzymes (Duff et al, 2011;Xu et al, 2018).…”

Section: Assignment Of All the Asparagine Synthetase Genes To Groupsmentioning

confidence: 90%

“…The bread wheat ( Triticum aestivum ; genomes AABBDD) asparagine synthetase gene family comprises five genes per genome: TaASN1 , TaASN2 , TaASN3.1 , TaASN3.2 and TaASN4 (Xu et al, 2018). Of these, TaASN3 is the most highly expressed during early grain development, but TaASN1 and TaASN2 are the most highly expressed by mid‐development, with expression of TaASN2 much higher than TaASN1 (Curtis et al, 2019; Gao et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Cereal asparagine synthetase genes

Raffan

Halford

2020

Annals of Applied Biology

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Asparagine synthetase catalyses the transfer of an amino group from glutamine to aspartate to form glutamate and asparagine. The accumulation of free (nonprotein) asparagine in crops has implications for food safety because free asparagine is the precursor for acrylamide, a carcinogenic contaminant that forms during hightemperature cooking and processing. Here we review publicly available genome data for asparagine synthetase genes from species of the Pooideae subfamily, including bread wheat and related wheat species (Triticum and Aegilops spp.), barley (Hordeum vulgare) and rye (Secale cereale) of the Triticeae tribe. Also from the Pooideae subfamily: brachypodium (Brachypodium dIstachyon) of the Brachypodiae tribe. More diverse species are also included, comprising sorghum (Sorghum bicolor) and maize (Zea mays) of the Panicoideae subfamily and rice (Oryza sativa) of the Ehrhartoideae subfamily. The asparagine synthetase gene families of the Triticeae species each comprise five genes per genome, with the genes assigned to four groups: 1, 2, 3 (subdivided into 3.1 and 3.2) and 4. Each species has a single gene per genome in each group, except that some bread wheat varieties (genomes AABBDD) and emmer wheat (Triticum dicoccoides; genomes AABB) lack a group 2 gene in the B genome. This raises questions about the ancestry of cultivated pasta wheat and the B genome donor of bread wheat, suggesting that the hybridisation event that gave rise to hexaploid bread wheat occurred more than once. In phylogenetic analyses, genes from the other species cluster with the Triticeae genes, but brachypodium, sorghum and maize lack a group 2 gene, while rice has only two genes, one group 3 and one group 4. This means that TaASN2, the most highly expressed asparagine synthetase gene in wheat grain, has no equivalent in maize, rice, sorghum or brachypodium. An evolutionary pathway is proposed in which a series of gene duplications gave rise to the five genes found in modern Triticeae species.

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“…The well-established formalism of Petri nets ( PNs ) has been shown to ideally support multidisciplinary research [1], [2], [3], [4]. By their definition, PNs allow for an intuitive representation of reaction networks including concurrency and synchronisation [5], [6].…”

Section: Introductionmentioning

confidence: 99%

BioModelKit – An Integrative Framework for Multi-Scale Biomodel-Engineering

Blätke

2018

Journal of Integrative Bioinformatics

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While high-throughput technology, advanced techniques in biochemistry and molecular biology have become increasingly powerful, the coherent interpretation of experimental results in an integrative context is still a challenge. BioModelKit (BMK) approaches this challenge by offering an integrative and versatile framework for biomodel-engineering based on a modular modelling concept with the purpose: (i) to represent knowledge about molecular mechanisms by consistent executable sub-models (modules) given as Petri nets equipped with defined interfaces facilitating their reuse and recombination; (ii) to compose complex and integrative models from an ad hoc chosen set of modules including different omic and abstraction levels with the option to integrate spatial aspects; (iii) to promote the construction of alternative models by either the exchange of competing module versions or the algorithmic mutation of the composed model; and (iv) to offer concepts for (omic) data integration and integration of existing resources, and thus facilitate their reuse. BMK is accessible through a public web interface (www.biomodelkit.org), where users can interact with the modules stored in a database, and make use of the model composition features. BMK facilitates and encourages multi-scale model-driven predictions and hypotheses supporting experimental research in a multilateral exchange.

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Genomic, Biochemical, and Modeling Analyses of Asparagine Synthetases from Wheat

Cited by 23 publications

References 41 publications

Contrasting gene expression patterns in grain of high and low asparagine wheat genotypes in response to sulphur supply

Contrasting gene expression patterns in grain of high and low asparagine wheat genotypes in response to sulphur supply

Cereal asparagine synthetase genes

BioModelKit – An Integrative Framework for Multi-Scale Biomodel-Engineering

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