Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA Splicing01:32

RNA Splicing

59.8K
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...
59.8K
Exon Recombination02:32

Exon Recombination

3.9K
The evolution of new genes is critical for speciation. Exon recombination, also known as exon shuffling or domain shuffling, is an important means of new gene formation. It is observed across vertebrates, invertebrates, and in some plants such as potatoes and sunflowers. During exon recombination, exons from the same or different genes recombine and produce new exon-intron combinations, which might evolve into new genes. 
Exon shuffling follows “splice frame rules.” Each exon...
3.9K
Alternative RNA Splicing02:18

Alternative RNA Splicing

24.2K
Alternative RNA splicing is the regulated splicing of exons and introns to produce different mature mRNAs from a single pre-mRNA. Unlike in constitutive splicing where a single gene produces a single type of mRNA, alternative splicing allows an organism to produce multiple proteins from a single gene and plays an important role in protein diversity.
There are five types of alternative RNA splicing that vary in the ways the pre-mRNA segments are removed or retained in the mature mRNA. The first...
24.2K
Alternative RNA Splicing02:18

Alternative RNA Splicing

4.6K
4.6K
Pre-mRNA Processing: RNA Splicing01:36

Pre-mRNA Processing: RNA Splicing

6.3K
6.3K
Organization of Genes02:07

Organization of Genes

72.6K
Overview
72.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Functional gut microbiota dynamics of generalist and specialist bacteria in association with chicken growth.

ISME communications·2026
Same author

Contrasting recovery of metagenome‑assembled genomes and derived bacterial communities and functional profiles from lizard fecal and cloacal samples.

Animal microbiome·2025
Same author

Stress Response to Climate Change and Postharvest Handling in Two Differently Pigmented Lettuce Genotypes: Impact on <i>Alternaria alternata</i> Invasion and Mycotoxin Production.

Plants (Basel, Switzerland)·2023
Same author

Recovering High-Quality Host Genomes from Gut Metagenomic Data through Genotype Imputation.

Advanced genetics (Hoboken, N.J.)·2023
Same author

Publisher Correction: A short exposure to a semi-natural habitat alleviates the honey bee hive microbial imbalance caused by agricultural stress.

Scientific reports·2022
Same author

A short exposure to a semi-natural habitat alleviates the honey bee hive microbial imbalance caused by agricultural stress.

Scientific reports·2022

Related Experiment Video

Updated: Dec 10, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.1K

EXFI: Exon and splice graph prediction without a reference genome.

Jorge Langa1, Andone Estonba1, Darrell Conklin2,3

  • 1Department of Genetics, Physical Anthropology and Animal Physiology Faculty of Science and Technology University of the Basque Country Leioa Spain.

Ecology and Evolution
|September 5, 2020
PubMed
Summary
This summary is machine-generated.

EXFI is a new Python pipeline that predicts exon sequences and splice graphs from genomic data. This tool aids population genetic studies in nonmodel organisms by leveraging transcriptomes and raw sequencing reads.

Keywords:
SNP discoveryexome sequencingexonsequence capturesplice graphtranscriptome

More Related Videos

Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

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

Published on: December 9, 2016

14.1K
A Reporter Based Cellular Assay for Monitoring Splicing Efficiency
08:53

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

Published on: September 15, 2021

3.1K

Related Experiment Videos

Last Updated: Dec 10, 2025

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data
08:35

Identification of Alternative Splicing and Polyadenylation in RNA-seq Data

Published on: June 24, 2021

6.1K
Using RNA-sequencing to Detect Novel Splice Variants Related to Drug Resistance in In Vitro Cancer Models
09:58

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

Published on: December 9, 2016

14.1K
A Reporter Based Cellular Assay for Monitoring Splicing Efficiency
08:53

A Reporter Based Cellular Assay for Monitoring Splicing Efficiency

Published on: September 15, 2021

3.1K

Area of Science:

  • Genomics
  • Bioinformatics
  • Population Genetics

Background:

  • Accurate genomic information is crucial for population genetic studies, especially in nonmodel organisms.
  • Existing methods may not fully utilize all available genomic data sources.

Purpose of the Study:

  • To present EXFI, a novel Python pipeline for predicting splice graphs and exon sequences.
  • To enable comprehensive genomic analysis in nonmodel organisms by integrating transcriptomic and whole-genome sequencing data.

Main Methods:

  • EXFI utilizes Bloom filters to identify and filter reads belonging to the transcriptome.
  • The pipeline predicts intron-exon boundaries and calls exons from the assembled transcriptome.
  • It generates a splice graph representing transcript structures.

Main Results:

  • EXFI successfully predicts exon sequences and their connections, forming a splice graph.
  • The output is provided in GFA1 format, detailing exon sequences and transcript assembly.
  • The pipeline is implemented in Python and tested on Linux systems.

Conclusions:

  • EXFI offers a valuable tool for population geneticists studying nonmodel organisms.
  • The pipeline enhances the utilization of genomic information for understanding genetic diversity and structure.