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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: May 23, 2026

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

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A Scheduling Algorithm for Computational Grids that Minimizes Centralized Processing in Genome Assembly of

Jakelyne Lima¹, Louise Teixeira Cerdeira, Erick Bol

¹Institute of Exact and Natural Sciences, Federal University of Pará Pará, Brazil.

Frontiers in Genetics

|March 31, 2012

Summary

A new algorithm optimizes de novo genome assembly software (ABySS) for computational grids. This improves genome assembly speed in heterogeneous environments without sacrificing data quality.

Keywords:

NGS computational grids genome assembly task scheduling

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High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture (4C-seq)

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Area of Science:

Genomics
Bioinformatics
Computational Science

Background:

Genome sequencing generates massive datasets, increasing computational demands for genome assembly.
Existing grid computing solutions for resource aggregation may not offer optimal performance due to resource heterogeneity and decentralized management.

Purpose of the Study:

To develop and evaluate an algorithm that optimizes the de novo genome assembly software ABySS for operation in computational grids.
To improve the efficiency of genome assembly processes in distributed computing environments.

Main Methods:

Developed a novel algorithm to enhance ABySS functionality for grid environments.
Utilized the SimGrid simulator to run ABySS with and without the developed algorithm.
Evaluated performance in a simulated heterogeneous grid environment.

Main Results:

The developed algorithm demonstrated viability, flexibility, and scalability in heterogeneous grid environments.
Genome assembly time was significantly improved in computational grids using the optimized ABySS.
The quality of the genome assembly remained unchanged.

Conclusions:

The developed algorithm offers an effective solution for optimizing de novo genome assembly on computational grids.
The approach enhances the speed and scalability of genome assembly in distributed, heterogeneous computing infrastructures.
This work contributes to more efficient processing of large-scale genomic data.