首页|stAPAminer:Mining Spatial Patterns of Alternative Polyadenylation for Spatially Resolved Transcriptomic Studies

stAPAminer:Mining Spatial Patterns of Alternative Polyadenylation for Spatially Resolved Transcriptomic Studies

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Alternative polyadenylation(APA)contributes to transcriptome complexity and gene expression regulation and has been implicated in various cellular processes and diseases.Single-cell RNA sequencing(scRNA-seq)has enabled the profiling of APA at the single-cell level;however,the spatial information of cells is not preserved in scRNA-seq.Alternatively,spatial transcriptomics(ST)technologies provide opportunities to decipher the spatial context of the transcriptomic land-scape.Pioneering studies have revealed potential spatially variable genes and/or splice isoforms;however,the pattern of APA usage in spatial contexts remains unappreciated.In this study,we developed a toolkit called stAPAminer for mining spatial patterns of APA from spatially barcoded ST data.APA sites were identified and quantified from the ST data.In particular,an imputation model based on the k-nearest neighbors algorithm was designed to recover APA signals,and then APA genes with spatial patterns of APA usage variation were identified.By analyzing well-established ST data of the mouse olfactory bulb(MOB),we presented a detailed view of spatial APA usage across morphological layers of the MOB.We compiled a comprehensive list of genes with spatial APA dynamics and obtained several major spatial expression patterns that represent spatial APA dynamics in different morphological layers.By extending this analysis to two addi-tional replicates of the MOB ST data,we observed that the spatial APA patterns of several genes were reproducible among replicates.stAPAminer employs the power of ST to explore the transcrip-tional atlas of spatial APA patterns with spatial resolution.This toolkit is available at https://github.com/BMILAB/stAPAminer and https://ngdc.cncb.ac.cn/biocode/tools/BT007320.

Alternative polyadenylationSpatial transcriptomicsSingle-cell RNA sequencingSpatial patternImputation

Guoli Ji、Qi Tang、Sheng Zhu、Junyi Zhu、Pengchao Ye、Shuting Xia、Xiaohui Wu

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Pasteurien College,Suzhou Medical College of Soochow University,Soochow University,Suzhou 215000,China

Department of Automation,Xiamen University,Xiamen 361005,China

Institute of Neuroscience,Soochow University,Suzhou 215000,China

National Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaSuzhou City People's Livelihood Science and Technology Project,China

T22220076157329681901287SYS2020086

2023

10.1016/j.gpb.2023.01.003

基因组蛋白质组与生物信息学报(英文版)
中国科学院北京基因组研究所

基因组蛋白质组与生物信息学报(英文版)

CSTPCDCSCD
影响因子：0.495
ISSN：1672-0229
年,卷(期)：2023.21(3)
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