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Cell-type-specific analysis of alternative polyadenylation using single-cell transcriptomics data.

Eldad David Shulman | Ran Elkon
Nucleic acids research | 2019

Alternative polyadenylation (APA) is emerging as an important layer of gene regulation because the majority of mammalian protein-coding genes contain multiple polyadenylation (pA) sites in their 3' UTR. By alteration of 3' UTR length, APA can considerably affect post-transcriptional gene regulation. Yet, our understanding of APA remains rudimentary. Novel single-cell RNA sequencing (scRNA-seq) techniques allow molecular characterization of different cell types to an unprecedented degree. Notably, the most popular scRNA-seq protocols specifically sequence the 3' end of transcripts. Building on this property, we implemented a method for analysing patterns of APA regulation from such data. Analyzing multiple datasets from diverse tissues, we identified widespread modulation of APA in different cell types resulting in global 3' UTR shortening/lengthening and enhanced cleavage at intronic pA sites. Our results provide a proof-of-concept demonstration that the huge volume of scRNA-seq data that accumulates in the public domain offers a unique resource for the exploration of APA based on a very broad collection of cell types and biological conditions.

Pubmed ID: 31501864

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ArrayExpress (tool)

RRID:SCR_002964

International functional genomics data collection generated from microarray or next-generation sequencing (NGS) platforms. Repository of functional genomics data supporting publications. Provides genes expression data for reuse to the research community where they can be queried and downloaded. Integrated with the Gene Expression Atlas and the sequence databases at the European Bioinformatics Institute. Contains a subset of curated and re-annotated Archive data which can be queried for individual gene expression under different biological conditions across experiments. Data collected to MIAME and MINSEQE standards. Data are submitted by users or are imported directly from the NCBI Gene Expression Omnibus.

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featureCounts (tool)

RRID:SCR_012919

A read summarization program, which counts mapped reads for the genomic features such as genes and exons.

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ggplot2 (tool)

RRID:SCR_014601

Open source software package for statistical programming language R to create plots based on grammar of graphics. Used for data visualization to break up graphs into semantic components such as scales and layers.

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GENCODE (tool)

RRID:SCR_014966

Human and mouse genome annotation project which aims to identify all gene features in the human genome using computational analysis, manual annotation, and experimental validation.

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Drop-seq tools (tool)

RRID:SCR_018142

Software Java tools for analyzing Drop-seq data. Used to analyze gene expression from thousands of individual cells simultaneously. Analyzes mRNA transcripts while remembering origin cell transcript.

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