DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates.

IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences Genome Biology Pub Date : 2024-09-06 DOI:10.1186/s13059-024-03367-8
Chikara Mizukoshi, Yasuhiro Kojima, Satoshi Nomura, Shuto Hayashi, Ko Abe, Teppei Shimamura
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引用次数: 0

Abstract

Messenger RNA splicing and degradation are critical for gene expression regulation, the abnormality of which leads to diseases. Previous methods for estimating kinetic rates have limitations, assuming uniform rates across cells. DeepKINET is a deep generative model that estimates splicing and degradation rates at single-cell resolution from scRNA-seq data. DeepKINET outperforms existing methods on simulated and metabolic labeling datasets. Applied to forebrain and breast cancer data, it identifies RNA-binding proteins responsible for kinetic rate diversity. DeepKINET also analyzes the effects of splicing factor mutations on target genes in erythroid lineage cells. DeepKINET effectively reveals cellular heterogeneity in post-transcriptional regulation.

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DeepKINET:用于估计单细胞 RNA 剪接和降解率的深度生成模型。
信使 RNA 的剪接和降解对基因表达调控至关重要,其异常会导致疾病。以往估算动力学速率的方法有其局限性,即假设整个细胞的速率是一致的。DeepKINET 是一种深度生成模型,能根据 scRNA-seq 数据以单细胞分辨率估算剪接和降解率。DeepKINET 在模拟和代谢标记数据集上的表现优于现有方法。在应用于前脑和乳腺癌数据时,它能识别导致动力学速率多样性的 RNA 结合蛋白。DeepKINET 还分析了红系细胞中剪接因子突变对靶基因的影响。DeepKINET 能有效揭示转录后调控的细胞异质性。
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来源期刊
Genome Biology
Genome Biology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-GENETICS & HEREDITY
CiteScore
25.50
自引率
3.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Genome Biology is a leading research journal that focuses on the study of biology and biomedicine from a genomic and post-genomic standpoint. The journal consistently publishes outstanding research across various areas within these fields. With an impressive impact factor of 12.3 (2022), Genome Biology has earned its place as the 3rd highest-ranked research journal in the Genetics and Heredity category, according to Thomson Reuters. Additionally, it is ranked 2nd among research journals in the Biotechnology and Applied Microbiology category. It is important to note that Genome Biology is the top-ranking open access journal in this category. In summary, Genome Biology sets a high standard for scientific publications in the field, showcasing cutting-edge research and earning recognition among its peers.
期刊最新文献
DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates. Seqrutinator: scrutiny of large protein superfamily sequence datasets for the identification and elimination of non-functional homologues. Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans. TaqTth-hpRNA: a novel compact RNA-targeting tool for specific silencing of pathogenic mRNA. Benchmarking computational variant effect predictors by their ability to infer human traits.
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