| 研究課題/領域番号 |
18F18386
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| 研究機関 | 沖縄科学技術大学院大学 |
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研究代表者 |
佐瀬 英俊 沖縄科学技術大学院大学, 植物エピジェネティクスユニット, 准教授 (70510006)
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| 研究分担者 |
MIRYEGANEH NODEHI MATIN 沖縄科学技術大学院大学, 植物エピジェネティクスユニット, 外国人特別研究員
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| 研究期間 (年度) |
2018-11-09 – 2021-03-31
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| キーワード | Epigenetics / Plants / Environment |
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| 研究実績の概要 |
We are planning to investigate how methylation variation is distributed among individuals from different habitats in different level of stress, and how this variation is correlated with their morphological differences and gene expression.
In order to do this we first sequenced the genomes and transcriptomes of representative mangrove species using the combination of long read sequencing technology (pacbio) supplemented by the more conventional platforms (Illumina Hiseq and matepair) to correct for the error of long read sequencing. To produce a high-quality reference genome, we started to generate a de novo assembly using these sequencing data.
We have also started a de novo RNA seq analysis and complementary detailed de novo annotation of genes based on RNA sequencing data.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
The genome assembly and annotation process is ongoing. We are also doing a gene expression analysis to identify genomic characteristics that are conserved within each group of plants but differ among them and we are also building a complementary detailed annotation of genes and also trying to reveal differences in the transcriptome profiles among populations that are growing under different level of stress.
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| 今後の研究の推進方策 |
The final goal is to construct genome-wide DNA methylation maps comparing phenotypically different individuals that are growing in different distances from the coastal area and investigate how methylation variation is distributed among individuals from different habitats in different level of stress, and how this variation is correlated with their morphological differences and gene expression. In order to do this we will investigate the functional consequences of the quantified DNA methylation variation by comparing its effect on gene expression data from RNA-Seq analysis.
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