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A study of Alternative Polyadenylation in developing cortical neurons (timepoints: 0, 4, 30 days) in bulk RNA-seq data. Several lengthening events over time were identified.

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Alternative Polyadenylation Quantification

This repository contains information for the quantification of Alternative Polyadenylation (APA) in RNA-seq datasets over neurodevelopment time This project uses the QAPA and DEXseq methods to identify 3'UTR lengthening or shortening by comparing two timepoints in neuron differentiation (day 30 with day 0).

Abstract: The role of post-transcriptional regulation in neurodevelopment is quite pervasive, activating gene programs that give rise to specialized cell features and functions. In this context, 3’ untranslated regions (3’UTRs) play a significant role in regulating mRNA translation, stability, and subcellular localization. This is mediated by factors such as miRNAs, lncRNAs and RNA-binding proteins (RBPs) that bind regions at the 3’UTR. Longer 3’UTRs present multiple such regions, leading to complex regulation patterns, while shorter ones are characterized by simpler patterns. The process through which one gene can have transcripts with longer or shorter 3’UTRs is known as alternative polyadenylation (APA). This study aims to characterize APA events in an RNA-seq dataset of iPSCs differentiating into cortical neurons.

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Figure description: Certain RNA transcripts can contain only 1 site for cleavage and polyadenylation, which we call single. When there are multiple cleavage and polyadenylation sites, we name the one closest to the coding sequence (CDS) Proximal (P), while the sites downstream are called Distal (D).

Quantification Process

Step 1: Data alignment to the reference transcriptome (hg38) using Salmon https://salmon.readthedocs.io/en/latest/salmon.html

Step 2: Quantification of APA using QAPA https://github.com/morrislab/qapa

Step 3: Data preprocessing

Step 4: Identifying lengthening and shortening events

Step 5: Visualizing reads using Gviz

Step 6: Quantification of APA using DEXseq

Step 7: Comparison of QAPA and DEXseq (Venn Diagram to identify common genes)

Step 8: Analysis of Proteomic data and comparison with APA events

-- Contact --

Author: Maria Eleni Fafouti

Email: marlen.fafouti@outlook.com

LinkedIn: linkedin.com/in/maria-eleni-fafouti-72950920b

Feel free to reach out if you have any questions or need further assistance!

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A study of Alternative Polyadenylation in developing cortical neurons (timepoints: 0, 4, 30 days) in bulk RNA-seq data. Several lengthening events over time were identified.

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