Folate Polyglutamylation is Required for Rice Seed Development

Anukul, Nampeung; Ramos, Riza Abilgos; Mehrshahi, Payam; Castelazo, Anahi Santoyo; Parker, Helen L.; Diévart, Anne; Lanau, Nadège; Mieulet, Delphine; Tucker, Gregory A.; Guiderdoni, Emmanuel; Bennett, Malcolm J.

doi:10.1007/s12284-010-9040-0

Cited by 11 publications

(6 citation statements)

References 32 publications

(28 reference statements)

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“…FPGS has been shown to play multiple roles in plants. The two known isoforms of FPGS of Oryza sativa appear to play roles in seed development (Anukul et al, 2010). The three isoforms of FPGS of Arabidopsis thaliana accumulate in the mitochondria, chloroplast, and cytosol (Ravanel et al, 2001).…”

Section: Discussionmentioning

confidence: 99%

The maize brown midrib4 (bm4) gene encodes a functional folylpolyglutamate synthase

Hill‐Skinner

Liu

et al. 2015

The Plant Journal

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Mutations in the brown midrib4 (bm4) gene affect the accumulation and composition of lignin in maize. Fine-mapping analysis of bm4 narrowed the candidate region to an approximately 105 kb interval on chromosome 9 containing six genes. Only one of these six genes, GRMZM2G393334, showed decreased expression in mutants. At least four of 10 Mu-induced bm4 mutant alleles contain a Mu insertion in the GRMZM2G393334 gene. Based on these results, we concluded that GRMZM2G393334 is the bm4 gene. GRMZM2G393334 encodes a putative folylpolyglutamate synthase (FPGS), which functions in one-carbon (C1) metabolism to polyglutamylate substrates of folate-dependent enzymes. Yeast complementation experiments demonstrated that expression of the maize bm4 gene in FPGS-deficient met7 yeast is able to rescue the yeast mutant phenotype, thus demonstrating that bm4 encodes a functional FPGS. Consistent with earlier studies, bm4 mutants exhibit a modest decrease in lignin concentration and an overall increase in the S:G lignin ratio relative to wild-type. Orthologs of bm4 include at least one paralogous gene in maize and various homologs in other grasses and dicots. Discovery of the gene underlying the bm4 maize phenotype illustrates a role for FPGS in lignin biosynthesis.

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Section: Discussionmentioning

confidence: 99%

The maize brown midrib4 (bm4) gene encodes a functional folylpolyglutamate synthase

Hill‐Skinner

Liu

et al. 2015

The Plant Journal

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“…In order to understand the possible genetic basis of the observed increased susceptibility in the high nitrogen environment, the 126 genes annotated at NIS3 were investigated (Additional file 15 ). We considered as good candidates genes either involved in biotic stress response (twenty-nine pathogenesis-related genes), abiotic stress response ( OsTIP3; 1, [ 63 ] and RIPER6 [ 64 ]), the regulation of both stresses ( OsGRXS17, [ 65 ] and OsTPR1 [ 66 ]), or nitrogen metabolism ( OsPORB, [ 67 ] and a polylpolyglutamate synthetase [ 68 ]). The possible modulation of the M. oryzae pathogenicity program in response to a high nitrogen environment was also a hypothesis based on our previous results [ 26 ].…”

Section: Resultsmentioning

confidence: 99%

Genome-wide association of rice response to blast fungus identifies loci for robust resistance under high nitrogen

et al. 2021

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Background Nitrogen fertilization is known to increase disease susceptibility, a phenomenon called Nitrogen-Induced Susceptibility (NIS). In rice, this phenomenon has been observed in infections with the blast fungus Magnaporthe oryzae. A previous classical genetic study revealed a locus (NIS1) that enhances susceptibility to rice blast under high nitrogen fertilization. In order to further address the underlying genetics of plasticity in susceptibility to rice blast after fertilization, we analyzed NIS under greenhouse-controlled conditions in a panel of 139 temperate japonica rice strains. A genome-wide association analysis was conducted to identify loci potentially involved in NIS by comparing susceptibility loci identified under high and low nitrogen conditions, an approach allowing for the identification of loci validated across different nitrogen environments. We also used a novel NIS Index to identify loci potentially contributing to plasticity in susceptibility under different nitrogen fertilization regimes. Results A global NIS effect was observed in the population, with the density of lesions increasing by 8%, on average, under high nitrogen fertilization. Three new QTL, other than NIS1, were identified. A rare allele of the RRobN1 locus on chromosome 6 provides robust resistance in high and low nitrogen environments. A frequent allele of the NIS2 locus, on chromosome 5, exacerbates blast susceptibility under the high nitrogen condition. Finally, an allele of NIS3, on chromosome 10, buffers the increase of susceptibility arising from nitrogen fertilization but increases global levels of susceptibility. This allele is almost fixed in temperate japonicas, as a probable consequence of genetic hitchhiking with a locus involved in cold stress adaptation. Conclusions Our results extend to an entire rice subspecies the initial finding that nitrogen increases rice blast susceptibility. We demonstrate the usefulness of estimating plasticity for the identification of novel loci involved in the response of rice to the blast fungus under different nitrogen regimes.

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“…High protein [1], carotenoid [2], micronutrients [3] and antioxidant content [4] are among the preferred nutritional contents improved in rice varieties. Rice breeding for high nutritional content has been carried out extensively by bio-fortification [5,6] and/or genetic engineering [7]. The improvement of nutritional content in rice is essential due to their benefits for human health.…”

Section: Overview Of Flavonoids In Omics and Rice Breeding Improvementmentioning

confidence: 99%

Computational Analysis of Rice Transcriptomic and Genomic Datasets in Search for SNPs Involved in Flavonoid Biosynthesis

Zainal-Abidin¹,

Mohamed‐Hussein²

2021

Recent Advances in Rice Research

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This chapter describes the computational approach used in analyzing rice transcriptomics and genomics data to identify and annotate potential single nucleotide polymorphism (SNPs) as potential biomarker in the production of flavonoid. SNPs play a role in the accumulation of nutritional components (e.g. antioxidants), and flavonoid is one of them. However, the number of identified SNPs associated with flavonoid nutritional trait is still limited. We develop a knowledge-based bioinformatic workflow to search for specific SNPs and integration analysis on the SNPs and their co-expressed genes to investigate their influence on the gain/loss of functional genes that are involved in the production of flavonoids. Raw files obtained from the functional genomics studies can be analyzed in details to obtain a useful biological insight. Different tools, algorithms and databases are available to analyze the ontology, metabolic and pathway at the molecular level in order to observe the effects of gene and protein expression. The usage of different tools, algorithms and databases allows the integration, interpretation and the inference of analysis to provide better understanding of the biological meaning of the resutls. This chapter illustrates how to select and bring together several software to develop a specific bioinformatic workflow that processes and analyses omics data. The implementation of this bioinformatic workflow revealed the identification of potential flavonoid biosynthetic genes that can be used as guided-gene to screen the single nucleotide polymorphisms (SNPs) in the flavonoid biosynthetic genes from genome and transcriptomics data.

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Folate Polyglutamylation is Required for Rice Seed Development

Cited by 11 publications

References 32 publications

The maize brown midrib4 (bm4) gene encodes a functional folylpolyglutamate synthase

The maize brown midrib4 (bm4) gene encodes a functional folylpolyglutamate synthase

Genome-wide association of rice response to blast fungus identifies loci for robust resistance under high nitrogen

Computational Analysis of Rice Transcriptomic and Genomic Datasets in Search for SNPs Involved in Flavonoid Biosynthesis

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