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RNA Splicing

RNA Splicing

Splicing is the process by which eukaryotic RNA is edited before its translation into protein. The RNA strand transcribed from eukaryotic DNA is called the primary transcript. The primary transcripts that become mRNAs are called precursor messenger RNAs (pre-mRNAs). Eukaryotic pre-mRNA contains alternating sequences of exons and introns. Exons are nucleotide sequences that code for proteins, whereas introns are the non-coding regions. In RNA splicing, introns are removed and exons are bonded...

Pre-mRNA Processing: RNA Splicing

Pre-mRNA Processing: RNA Splicing

Alternative RNA Splicing

Alternative RNA Splicing

Chromatin Structure and RNA Splicing

Chromatin Structure and RNA Splicing

Pre-mRNA Processing: Modification of pre-mRNA Ends

Pre-mRNA Processing: Modification of pre-mRNA Ends

In eukaryotic cells, transcripts made by RNA polymerase are modified and processed before exiting the nucleus. Unprocessed RNA is called precursor mRNA or pre-mRNA to distinguish it from mature mRNA.
Once about 20-40 ribonucleotides have been joined together by RNA polymerase, a group of enzymes adds a cap to the 5' end of the growing transcript. In this process, a 5' phosphate is replaced by modified guanosine that has a methyl group attached (7-methyl guanosine). This 5' cap helps...

Long-patch Base Excision Repair

Long-patch Base Excision Repair

Since the discovery of the two BER pathways, there has been a debate about how a cell chooses one pathway over the other and the factors determining this selection. Numerous in vitro experiments have pointed out multiple determinants for the sub-pathway selection. These are:

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Related Experiment Video

Updated: Jul 19, 2025

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

Published on: December 9, 2016

Splam: a deep-learning-based splice site predictor that improves spliced alignments.

Kuan-Hao Chao^1,2, Alan Mao^1,2,3, Steven L Salzberg^1,2,3,4

¹Department of Computer Science, Johns Hopkins University, Baltimore, MD 21218, USA.

Biorxiv : the Preprint Server for Biology

|August 7, 2023

Summary

This summary is machine-generated.

Splam, a novel deep learning method, accurately predicts splice junctions in DNA by analyzing flanking sequences and training on donor-acceptor pairs. This approach improves RNA sequencing data analysis and gene variant identification.

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Last Updated: Jul 19, 2025

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models

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Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

RNA splicing is crucial for gene expression and creating gene variants.
Accurate splice junction prediction is essential for understanding gene function and disease.

Approach:

Developed Splam, a deep residual convolutional neural network for splice junction prediction.
Utilized a limited 400 base pair window and trained on donor-acceptor pairs simultaneously.
Compared Splam against state-of-the-art methods like SpliceAI.

Key Points:

Splam achieved 96% accuracy in predicting human splice junctions, outperforming SpliceAI.
Demonstrated generalization to non-human species, including *Arabidopsis thaliana*.
Applied Splam to RNA-seq data, improving transcriptome analysis accuracy and error correction.

Conclusions:

Splam provides a faster, more accurate method for splice junction detection.
Offers a reliable solution for cleaning erroneous spliced alignments in RNA-seq data.
Enhances downstream transcriptome analysis for poly(A) and ribo-depleted libraries.