首页|A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences,Bulk RNA-seq,and Single-cell RNA-seq
A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences,Bulk RNA-seq,and Single-cell RNA-seq
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Alternative polyadenylation(APA)plays important roles in modulating mRNA stability,translation,and subcellular localization,and contributes extensively to shaping eukaryotic tran-scriptome complexity and proteome diversity.Identification of poly(A)sites(pAs)on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation.A number of established computational tools have been proposed to predict pAs from diverse genomic data.Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences,bulk RNA sequencing(RNA-seq)data,and single-cell RNA sequencing(scRNA-seq)data.Particularly,we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools.We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios.Moreover,we discussed in depth the challenges in improving the performance of pA prediction and bench-marking different methods.Additionally,we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques,and provided our perspective on how computational methodologies might evolve in the future for non-3'untranslated region,tissue-specific,cross-species,and single-cell pA prediction.
Pasteurien College,Suzhou Medical College of Soochow University,Soochow University,Suzhou 215000,China
Department of Automation,Xiamen University,Xiamen 361005,China
Key Laboratory of the Coastal and Wetland Ecosystems,Ministry of Education,College of the Environment and Ecology,Xiamen University,Xiamen 361005,China
National Natural Science Foundation of ChinaNatural Science Foundation of Fujian Province of China
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