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Genome Annotation and Assembly

Genome Annotation and Assembly

The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.

Next-generation Sequencing

Next-generation Sequencing

The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
Next-Generation Sequencing Methods
Although all next-generation methods use different technologies, they all share a set of standard features....

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Related Experiment Video

Updated: Mar 3, 2026

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Hybrid De Novo Genome Assembly for the Generation of Complete Genomes of Urinary Bacteria using Short- and Long-read Sequencing Technologies

Published on: August 20, 2021

Assembling draft genomes using contiBAIT.

Kieran O'Neill^1,2, Mark Hills³, Mike Gottlieb^1,4

¹Michael Smith Genome Sciences Centre, BC Cancer Agency.

Bioinformatics (Oxford, England)

|May 6, 2017

Summary

This summary is machine-generated.

Massively parallel sequencing relies on accurate reference assemblies. The new contiBAIT software uses Strand-seq data to improve genome assembly quality by correcting errors and gaps.

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Last Updated: Mar 3, 2026

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Published on: December 1, 2017

Area of Science:

Genomics
Bioinformatics

Background:

Massively parallel sequencing is a widely used technique in genomics.
Current reference assemblies often exist as scaffold or chromosome builds with gaps and errors.
Completing de novo assemblies is challenging due to repetitive regions and sequencing difficulties.

Purpose of the Study:

To present contiBAIT, an R/Bioconductor package.
To utilize Strand-seq data for repairing and improving existing genome assemblies.

Main Methods:

Strand-seq determines template strand inheritance in single cells.
This information aids in assessing relative genomic distance and orientation between scaffolds.
Strand-seq helps identify errors within assemblies.

Main Results:

contiBAIT leverages Strand-seq data to address assembly limitations.
The package aims to enhance the accuracy and completeness of genome assemblies.

Conclusions:

Accurate data interpretation in sequencing depends on high-quality reference assemblies.
Complementary methods like Strand-seq are crucial for finishing genome assemblies.
contiBAIT offers a novel solution for repairing and improving genome assemblies using Strand-seq data.