Multi-Layered Screening Method Identification of Flavonoid-Specific Genes, using Transgenic Rice

Kim, Chang-Kug; Lim, Hyemin; Park, Sung-Han; Kim, Aram; Lee, Gang-Seob; Yoon, Ung-Han; Park, Soo-Kwon; Park, Dong-Soo; Kim, Yong-Kab; Kim, Sang Woo

doi:10.5504/bbeq.2013.0037

Cited by 5 publications

(6 citation statements)

References 26 publications

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“…The first report of SRG1 showed that SRG1 gene was expressed in senescing organs of Arabidopsis ( Callard et al, 1996 ). Recently, the SRG1 was found to have flavonoid-related functions in rice ( Kim et al, 2013 ). In our study, the SRG1 was mapped on the same position of FLS in KEGG pathway analysis.…”

Section: Discussionmentioning

confidence: 99%

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

Song

Zou

et al. 2017

Front. Plant Sci.

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‘Huangjinya’ is an excellent albino tea germplasm cultivated in China because of its bright color and high amino acid content. It is light sensitive, with yellow leaves under intense light while green leaves under weak light. As well, the flavonoid and carotenoid levels increased after moderate shading treatment. However, the mechanism underlying this interesting phenomenon remains unclear. In this study, the transcriptome of ‘Huangjinya’ plants exposed to sunlight and shade were analyzed by high-throughput sequencing followed by de novo assembly. Shading ‘Huangjinya’ made its leaf color turn green. De novo assembly showed that the transcriptome of ‘Huangjinya’ leaves comprises of 127,253 unigenes, with an average length of 914 nt. Among the 81,128 functionally annotated unigenes, 207 differentially expressed genes were identified, including 110 up-regulated and 97 down-regulated genes under moderate shading compared to full light. Gene ontology (GO) indicated that the differentially expressed genes are mainly involved in protein and ion binding and oxidoreductase activity. Antioxidation-related pathways, including flavonoid and carotenoid biosynthesis, were highly enriched in these functions. Shading inhibited the expression of flavonoid biosynthesis-associated genes and induced carotenoid biosynthesis-related genes. This would suggest that decreased flavonoid biosynthetic gene expression coincides with increased flavonoids (e.g., catechin) content upon moderate shading, while carotenoid levels and biosynthetic gene expression are positively correlated in ‘Huangjinya.’ In conclusion, the leaf color changes in ‘Huangjinya’ are largely determined by the combined effects of flavonoid and carotenoid biosynthesis.

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Section: Discussionmentioning

confidence: 99%

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

Song

Zou

et al. 2017

Front. Plant Sci.

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“…TBGI130922 controls the metabolism, including the cytokinin metabolism 75 , to support rice coleoptile growth 84 . One product of this gene is flavonoid-biosynthesis networks 85 , 86 . These flavonoid compounds have many roles in plants, including the reproduction process 87 and specialized metabolite pathways 88 in rice.…”

Section: Discussionmentioning

confidence: 99%

Deep polygenic neural network for predicting and identifying yield-associated genes in Indonesian rice accessions

Dominic

Cenggoro

Budiarto

et al. 2022

Sci Rep

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As the fourth most populous country in the world, Indonesia must increase the annual rice production rate to achieve national food security by 2050. One possible solution comes from the nanoscopic level: a genetic variant called Single Nucleotide Polymorphism (SNP), which can express significant yield-associated genes. The prior benchmark of this study utilized a statistical genetics model where no SNP position information and attention mechanism were involved. Hence, we developed a novel deep polygenic neural network, named the NucleoNet model, to address these obstacles. The NucleoNets were constructed with the combination of prominent components that include positional SNP encoding, the context vector, wide models, Elastic Net, and Shannon’s entropy loss. This polygenic modeling obtained up to 2.779 of Mean Squared Error (MSE) with 47.156% of Symmetric Mean Absolute Percentage Error (SMAPE), while revealing 15 new important SNPs. Furthermore, the NucleoNets reduced the MSE score up to 32.28% compared to the Ordinary Least Squares (OLS) model. Through the ablation study, we learned that the combination of Xavier distribution for weights initialization and Normal distribution for biases initialization sparked more various important SNPs throughout 12 chromosomes. Our findings confirmed that the NucleoNet model was successfully outperformed the OLS model and identified important SNPs to Indonesian rice yields.

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“…One white rice accession Dongjin and two black rice accessions Heugjinju and Heugseol were acquired from the RDA-Genebank (http://www.genebank.go.kr/) and were cultivated in a standard manner in an experimental field of the National Academy of Agricultural Science (NAAS, http://www.naas.go.kr) [7]. In addition, we analyzed the microarray data from three Ac/Ds gene trapped lines (Ds40112, Ds22978 and Ds97389) expressing high levels of anthocyanins in Dongjin genetic background [8,9].…”

Section: Rice Accessionsmentioning

confidence: 99%

“…Microarray data were collected from the agricultural crops research project of the NAAS. In total, we investigated gene expression in six accessions (i.e., one white and five black rice cultivars) at three developmental stages based on microarray expression intensity [7,8]. Microarray analysis was performed using the 135K Oryza sativa microarray, which is referenced to the annotation data on the Os-Nipponbare-Reference-IRGSP-1.0 at the Rice Annotation Project (http://rapdb.dna.affrc.go.jp/).…”

Section: Microarray Data Collectionmentioning

confidence: 99%

“…In order to elucidate genes responsible for anthocyanin biosynthesis in rice grains, microarray analysis was previously performed on six rice accessions (i.e., white and black rice) expressing different levels of anthocyanins by using the 135K Oryza sativa array [7,8]. Comparison among three cultivars (Dongjin, Heugjinju and Heugseol) identified 12,673 candidates, while analysis of three Ac/Ds gene-trapped lines and their wild-type Dongjin identified 6,739 genes for flavonoid pathway [7,8]. With an aim to further narrow down to the potential genes in anthocyanin pathway, we integrated these two sets of data and found that 3,728 genes were shown to be either up-or down-regulated with more than 2-fold changes in the five black rice accessions at all three developmental stages, compared to the white rice Dongjin.…”

Section: Identification Of Differentially Expressed Genes (Degs) In Amentioning

confidence: 99%

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Computational Identification of Anthocyanin-Related Genes Using Transcriptome Data from Black Rice Plants

Oh¹,

Won²,

Lee³

et al. 2015

Cell Dev Biol

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Anthocyanins are a group of secondary metabolite that is responsible for the color in plant and their antioxidant activity has been noticed as a health-promoting material. To identify the genes responsible for anthocyaninenrichment in the black rice grains, we assessed the expression of transcripts in both black and white rice cultivars using the 135K Oryza sativa microarray and found that the 3,728 genes were associated with the production of anthocyanin pigment. Among them, the 573 conserved orthologous genes were identified using the COGs analyses and were compared with the existing flavonoid-pathway network. Enriched-pathway analysis finally resulted in 53 candidates for anthocyanin biosynthesis. These genes were anchored to the chromosomes of the rice genome to identify their genetic-map positions and were subjected to the phylogenetic construction together with their 31 homologous proteins sequences from A. thaliana, using the maximum-likelihood method. Our candidate genes seem to either play a regulatory role in anthocyanin biosynthesis or be related to anthocyanin metabolism.

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Multi-Layered Screening Method Identification of Flavonoid-Specific Genes, using Transgenic Rice

Cited by 5 publications

References 26 publications

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

Molecular Link between Leaf Coloration and Gene Expression of Flavonoid and Carotenoid Biosynthesis in Camellia sinensis Cultivar ‘Huangjinya’

Deep polygenic neural network for predicting and identifying yield-associated genes in Indonesian rice accessions

Computational Identification of Anthocyanin-Related Genes Using Transcriptome Data from Black Rice Plants

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