Deep learning‐enabled discovery and characterization of HKT genes in Spartina alterniflora DOI Creative Commons

Maogeng Yang,

Shoukun Chen,

Zhangping Huang

et al.

The Plant Journal, Journal Year: 2023, Volume and Issue: 116(3), P. 690 - 705

Published: July 26, 2023

Spartina alterniflora is a halophyte that can survive in high-salinity environments, and it phylogenetically close to important cereal crops, such as maize rice. It of scientific interest understand why S. live under extremely stressful conditions. The molecular mechanism underlying its high-saline tolerance still largely unknown. Here we investigated the possibility high-affinity K+ transporters (HKTs), which function salt maintenance ion homeostasis plants, are responsible for alterniflora. To overcome imprecision unstable gene screening method caused by conventional sequence alignment, used deep learning method, DeepGOPlus, automatically extract protein characteristics from our newly assemble genome identify SaHKTs. Results showed total 16 HKT genes were identified. number HKTs (SaHKTs) larger than all other plant species except wheat. Phylogenetically related SaHKT members had similar structures, conserved domains cis-elements. Expression profiling most expressed specific tissues differentially stress. Yeast complementation expression analysis type I SaHKT1;2, SaHKT1;3 SaHKT1;8 II SaHKT2;1, SaHKT2;3 SaHKT2;4 low-affinity uptake ability stronger affinity rice Arabidopsis HKTs, well SaHKTs preference Na+ transport. We believe learning-based methods powerful approaches uncovering new functional genes, identified resources breeding varieties salt-tolerant crops.

Language: Английский

In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs DOI Creative Commons
Lei Sun, Pan Li, Xiaohui Ju

et al.

Cell, Journal Year: 2021, Volume and Issue: 184(7), P. 1865 - 1883.e20

Published: Feb. 9, 2021

Language: Английский

Citations

216
Advances and opportunities in RNA structure experimental determination and computational modeling DOI Open Access
Jinsong Zhang, Yuhan Fei, Lei Sun

et al.

Nature Methods, Journal Year: 2022, Volume and Issue: 19(10), P. 1193 - 1207

Published: Oct. 1, 2022

Language: Английский

Citations

100
Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions DOI Creative Commons
Jiayang Chen, Zhihang Hu, Siqi Sun

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Aug. 7, 2022

Abstract Non-coding RNA structure and function are essential to understanding various biological processes, such as cell signaling, gene expression, post-transcriptional regulations. These all among the core problems in field. With rapid growth of sequencing technology, we have accumulated a massive amount unannotated sequences. On other hand, expensive experimental observatory results only limited numbers annotated data 3D structures. Hence, it is still challenging design computational methods for predicting their structures functions. The lack systematic study causes inferior performance. To resolve issue, propose novel foundation model (RNA-FM) take advantage 23 million non-coding sequences through self-supervised learning. Within this approach, discover that pre-trained RNA-FM could infer sequential evolutionary information RNAs without using any labels. Furthermore, demonstrate RNA-FM’s effectiveness by applying downstream secondary/3D prediction, SARS-CoV-2 genome evolution protein-RNA binding preference modeling, expression regulation modeling. comprehensive experiments show proposed method improves structural functional modelling significantly consistently. Despite being trained with unlabelled data, can serve foundational

Language: Английский

Citations

87
Transformer Architecture and Attention Mechanisms in Genome Data Analysis: A Comprehensive Review DOI Creative Commons
Sanghyuk Roy Choi, Minhyeok Lee

Biology, Journal Year: 2023, Volume and Issue: 12(7), P. 1033 - 1033

Published: July 22, 2023

The emergence and rapid development of deep learning, specifically transformer-based architectures attention mechanisms, have had transformative implications across several domains, including bioinformatics genome data analysis. analogous nature sequences to language texts has enabled the application techniques that exhibited success in fields ranging from natural processing genomic data. This review provides a comprehensive analysis most recent advancements transformer mechanisms transcriptome focus this is on critical evaluation these techniques, discussing their advantages limitations context With swift pace learning methodologies, it becomes vital continually assess reflect current standing future direction research. Therefore, aims serve as timely resource for both seasoned researchers newcomers, offering panoramic view elucidating state-of-the-art applications field. Furthermore, paper serves highlight potential areas investigation by critically evaluating studies 2019 2023, thereby acting stepping-stone further research endeavors.

Language: Английский

Citations

77
tRNA renovatio: Rebirth through fragmentation DOI Creative Commons
Bernhard Kuhle, Qi Chen, Paul Schimmel

et al.

Molecular Cell, Journal Year: 2023, Volume and Issue: 83(22), P. 3953 - 3971

Published: Oct. 5, 2023

tRNA function is based on unique structures that enable mRNA decoding using anticodon trinucleotides. These interact with specific aminoacyl-tRNA synthetases and ribosomes 3D shape sequence signatures. Beyond translation, tRNAs serve as versatile signaling molecules interacting other RNAs proteins. Through evolutionary processes, fragmentation emerges not merely random degradation but an act of recreation, generating shorter called tRNA-derived small (tsRNAs). tsRNAs exploit their linear sequences newly arranged for unexpected biological functions, epitomizing the "renovatio" (from Latin, meaning renewal, renovation, rebirth). Emerging methods to uncover full tRNA/tsRNA modifications, combined techniques study RNA integrate AI-powered predictions, will comprehensive investigations products new interaction potentials in relation functions. We anticipate these directions herald a era understanding complexity advancing pharmaceutical engineering.

Language: Английский

Citations

45
Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states DOI Creative Commons

Ritwika Bose,

Irfana Saleem,

Anthony M. Mustoe

et al.

Cell chemical biology, Journal Year: 2024, Volume and Issue: 31(1), P. 17 - 35

Published: Jan. 1, 2024

Language: Английский

Citations

18
RNA structure probing uncovers RNA structure-dependent biological functions DOI
Xiwen Wang,

Chu‐Xiao Liu,

Ling‐Ling Chen

et al.

Nature Chemical Biology, Journal Year: 2021, Volume and Issue: 17(7), P. 755 - 766

Published: June 25, 2021

Language: Английский

Citations

94
Comparison of viral RNA–host protein interactomes across pathogenic RNA viruses informs rapid antiviral drug discovery for SARS-CoV-2 DOI Creative Commons
Shaojun Zhang, Wenze Huang, Lili Ren

et al.

Cell Research, Journal Year: 2021, Volume and Issue: 32(1), P. 9 - 23

Published: Nov. 4, 2021

Abstract In contrast to the extensive research about viral protein–host protein interactions that has revealed major insights how RNA viruses engage with host cells during infection, few studies have examined between factors and RNAs (vRNAs). Here, we profiled vRNA–host interactomes for three virus pathogens (SARS-CoV-2, Zika, Ebola viruses) using ChIRP-MS. Comparative interactome analyses discovered both common virus-specific responses vRNA-associated proteins variously promote or restrict infection. particular, SARS-CoV-2 binds hijacks factor IGF2BP1 stabilize vRNA augment translation. Our interactome-informed drug repurposing efforts identified several FDA-approved drugs (e.g., Cepharanthine) as broad-spectrum antivirals in hACE2 transgenic mice. A co-treatment comprising Cepharanthine Trifluoperazine was highly potent against newly emerged B.1.351 variant. Thus, our study illustrates scientific medical discovery utility of adopting a comparative perspective.

Language: Английский

Citations

83
Computer-aided design of RNA-targeted small molecules: A growing need in drug discovery DOI Creative Commons
Jacopo Manigrasso, Marco Marcia, Marco De Vivo

et al.

Chem, Journal Year: 2021, Volume and Issue: 7(11), P. 2965 - 2988

Published: June 23, 2021

Language: Английский

Citations

67
Recent advances in RNA structurome DOI Open Access
Bingbing Xu, Yanda Zhu, Changchang Cao

et al.

Science China Life Sciences, Journal Year: 2022, Volume and Issue: 65(7), P. 1285 - 1324

Published: June 14, 2022

Language: Английский

Citations

43