Transcriptome-wide alternative mRNA splicing analysis reveals post-transcriptional regulation of neuronal differentiation
Data files
Dec 24, 2024 version files 121.62 MB
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README.md
3.51 KB
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Supplementary_tables.xlsx
121.62 MB
Abstract
Alternative splicing (AS) plays an important role in neuronal development, function, and disease. Efforts to analyze the transcriptome of AS neurons on a wide scale are currently limited. We characterized the transcriptome-wide AS changes in SH-SY5Y neuronal differentiation model, which is widely used to study neuronal function and disorders. Our analysis revealed global changes in five AS programs that drive neuronal differentiation. Motif analysis revealed the contribution of RNA binding proteins (RBPs) to the regulation of AS during neuronal development. We concentrated on the primary alternative splicing program that occurs during differentiation, specifically on events involving exon skipping (SE). Motif analysis revealed motifs for Polypyrimidine Tract Binding Protein 1 (PTB) and ELAV Like RNA Binding Protein 1 (HuR/ELAVL1) to be the top enriched in SE events, and their protein levels were downregulated after differentiation. shRNA Knockdown of either PTB and HuR was associated with enhanced neuronal differentiation and transcriptome-wide exon skipping events that drive the process of differentiation. At the level of gene expression, we observed only modest changes, indicating predominant post-transcriptional effects of PTB and HuR. We also observed that both RBPs altered cellular responses to oxidative stress, in line with the differentiated phenotype observed after either gene knockdown. Our work characterizes the AS changes in a widely used and important model of neuronal development and neuroscience research and reveals intricate post-transcriptional regulation of neuronal differentiation.
README: Transcriptome-wide alternative mRNA splicing analysis reveals post-transcriptional regulation of neuronal differentiation
https://doi.org/10.5061/dryad.k0p2ngfj3
Description of the data and file structure
Supplementary tables containing local splice variants (LSV) events generated using the rMATs pipeline. The data include 5 LSV subtypes analyzed in Differentiated vs undifferentiated SH-SY5Y cells as well as after PTB or HuR Knockdown experiments. For detailed bioinformatics analysis, please refere to the original article.
Files and variables
File: Supplementary_tables.xlsx
Description: Supplementary tables containing LSV data from RNA-seq experiments.
Variables
Supplementary table 1: exon skipping events after neural differentiation (Differentiated vs undifferentiated cells)
Supplementary table 2: mutually exclusive exon events after neural differentiation (Differentiated vs undifferentiated cells)
Supplementary table 3: retained intron events after neural differentiation (Differentiated vs undifferentiated cells)
Supplementary table 4: alternative 5’ splice site events after neural differentiation (Differentiated vs undifferentiated cells)
Supplementary table 5: alternative 3’ splice site events after neural differentiation (Differentiated vs undifferentiated cells)
Supplementary table 6: exon skipping events after PTB KD (KD vs Mock)
Supplementary table 7: mutually exclusive exon events after PTB KD (KD vs Mock)
Supplementary table 8: retained intron events after PTB KD (KD vs Mock)
Supplementary table 9: alternative 5’ splice site events after PTB KD (KD vs Mock)
Supplementary table 10: alternative 3’ splice site events after PTB KD (KD vs Mock)
Supplementary table 11: exon skipping events after HuR KD (KD vs Mock)
Supplementary table 12: mutually exclusive exon events after HuR KD (KD vs Mock)
Supplementary table 13: retained intron events after HuR KD (KD vs Mock)
Supplementary table 14: alternative 5’ splice site events after HuR KD (KD vs Mock)
Supplementary table 15: alternative 3’ splice site events after HuR KD (KD vs Mock)
Access information
Data was derived from the following sources:
- RNA sequencing data of PTB and HuR KD was deposited in the sequence read archive (PRJNA1001516). The RNA-seq data of differentiated neurons was retrieved from previous publication (Zhou et al, J Cell Phys, 2024) and is available through the sequence read archive (PRJNA779467).
- Bioinformatics analysis of RNA-seq data: Quality control for Raw Fastq was performed using FastQC. Raw reads were then trimmed with Trimmomatic and adaptor sequences and low-quality read removed. Reads were aligned to the human reference genome hg38 (GRCh38.p13) using the splice aware aligner HISAT2. Mapped reads BAM file were then counted to gene features by FeatureCounts with standard settings. Cutoff for significant gene expression was FDR < 0.05 and |Log2 FC| ≥ 1. Local splice variants (LSV) analysis was conducted using rMATs and motif analysis of RBPs was conducted using rMAPs2. Cutoff value for statistically significant splice event was FDR < 0.05 and |ΔΨ| ≥ 0.2. Pre ranked gene set enrichment analysis was conducted using eVITTA toolbox. Overrepresentation analysis (ORA) was conducted using eVITTA or Metascape.
- For datasheet structure and explanation, please refer to rMATs documentations: https://github.com/Xinglab/rmats-turbo/blob/v4.1.1/README.md