Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Comparing Copy Number Variations and SNPs

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

Modern Molecular Taxonomy

Modern Molecular Taxonomy

Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...

You might also read

Related Articles

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

Sort by

Same author

Complete genomes reveal a refined map of Mycobacterium tuberculosis genetic diversity across evolutionary scales.

Nature communications·2026

Same author

Rate variation and recurrent sequence errors in pandemic-scale phylogenetics.

Nature methods·2026

Same author

Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.

Nature methods·2026

Same author

Typhi Mykrobe: fast and accurate lineage identification and antimicrobial resistance genotyping directly from sequence reads for the typhoid fever agent Salmonella Typhi.

Genome medicine·2025

Same author

Sustainable data analysis with Snakemake.

F1000Research·2025

Same author

Pre- and postantibiotic epoch: The historical spread of antimicrobial resistance.

Science (New York, N.Y.)·2025

Search research articles

Related Experiment Video

Updated: Oct 21, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Gramtools enables multiscale variation analysis with genome graphs.

Brice Letcher¹, Martin Hunt^2,3, Zamin Iqbal⁴

¹EMBL-EBI, Hinxton, UK. bletcher@ebi.ac.uk.

|September 7, 2021

Summary

This summary is machine-generated.

Genome graphs represent genetic variation. Our gramtools software handles multiscale variation and genotyping on multiple references, outperforming existing methods for complex genomic regions.

Keywords:

Genome graph Mycobacterium tuberculosis Pangenome Plasmodium falciparum VCF Variant calling

More Related Videos

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Related Experiment Videos

Last Updated: Oct 21, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Published on: December 22, 2017

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Area of Science:

Genomics
Bioinformatics

Background:

Genome graphs offer flexible representations of genetic variation, accommodating single nucleotide polymorphisms (SNPs) and structural variants.
Current methods face challenges in transparently incorporating multiscale variation and multiple sequence backgrounds.

Purpose of the Study:

To implement a novel model for handling multiscale genetic variation.
To develop a JSON extension of VCF (jVCF) for variant calls on multiple references.
To introduce the gramtools software for efficient genomic analysis.

Main Methods:

Implementation of a multiscale variation model.
Development of a JSON extension of VCF (jVCF).
Utilizing the gramtools software for genotyping and variant calling.

Main Results:

gramtools demonstrates superior performance in genotyping SNPs overlapping large deletions in M. tuberculosis.
The software successfully genotypes variants on multiple alternate backgrounds in P. falciparum.
Previously undetected recombination events were revealed in P. falciparum.

Conclusions:

gramtools provides a robust solution for analyzing complex genetic variation.
The jVCF format enhances variant representation for multiple references.
This approach advances genomic analysis, particularly in challenging regions and for discovering recombination patterns.