論文 - 詳細
| RRC ID | 81565 |
|---|---|
| 著者 | Takashi Akagi, Kanae Masuda, Eriko Kuwada, Kouki Takeshita, Taiji Kawakatsu, Tohru Ariizumi, Yasutaka Kubo, Koichiro Ushijima, Seiichi Uchida |
| タイトル | Genome-wide cis-decoding for expression design in tomato using cistrome data and explainable deep learning |
| ジャーナル | The Plant Cell |
| Abstract |
In the evolutionary history of plants, variation in cis-regulatory elements (CREs) resulting in diversification of gene expression has played a central role in driving the evolution of lineage-specific traits. However, it is difficult to predict expression behaviors from CRE patterns to properly harness them, mainly because the biological processes are complex. In this study, we used cistrome datasets and explainable convolutional neural network (CNN) frameworks to predict genome-wide expression patterns in tomato (Solanum lycopersicum) fruit from the DNA sequences in gene regulatory regions. By fixing the effects of trans-acting factors using single cell-type spatiotemporal transcriptome data for the response variables, we developed a prediction model for crucial expression patterns in the initiation of tomato fruit ripening. Feature visualization of the CNNs identified nucleotide residues critical to the objective expression pattern in each gene, and their effects were validated experimentally in ripening tomato fruit. This cis-decoding framework will not only contribute to the understanding of the regulatory networks derived from CREs and transcription factor interactions, but also provides a flexible means of designing alleles for optimized expression. |
| 巻・号 | 34 |
| ページ | 2174-2187 |
| 公開日 | 2022-5-24 |
| DOI | 10.1093/plcell/koac079 |
| PMID | 35258588 |
| PMC | PMC9134063 |
| MeSH | Deep Learning* Fruit / genetics Fruit / metabolism Gene Expression Regulation, Plant / genetics Plant Proteins / genetics Plant Proteins / metabolism Regulatory Sequences, Nucleic Acid Solanum lycopersicum* / genetics Solanum lycopersicum* / metabolism Transcription Factors / genetics Transcription Factors / metabolism |
| IF | 9.618 |
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| 最多言及媒体 | X(Twitter) |
| 各媒体での言及数の合計 | 22 |
| 過去6か月間でのオルトメトリクス指標の変動値 | 0.0 |
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