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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.

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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...

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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.

Genomics

Genomics

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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.
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RNA-seq

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Related Experiment Video

Updated: May 30, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Gee Fu: a sequence version and web-services database tool for genomic assembly, genome feature and NGS data.

Ricardo Ramirez-Gonzalez¹, Mario Caccamo, Daniel MacLean

¹The Genome Analysis Centre, Norwich Research Park, Colney Lane, Norwich, UK, NR4 7UH.

Bioinformatics (Oxford, England)

|August 2, 2011

Summary

Gee Fu is a new database tool that simplifies the storage and sharing of genomic assembly data. It enables easy access and updates for bioinformaticians and bench biologists, accelerating research.

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

Published on: March 22, 2018

Area of Science:

Genomics
Bioinformatics

Background:

High-throughput sequencing and short-read assembly enable rapid genome assembly.
The proliferation of genomic data necessitates efficient management tools.

Purpose of the Study:

To introduce Gee Fu, a database tool for managing genomic assembly and feature data.
To provide accessible platforms for data input, visualization, and retrieval.

Main Methods:

Developed Gee Fu as a Ruby-On-Rails web application.
Integrated a feature database with web and console interfaces.
Incorporated AnnoJ for feature data visualization and BAM file support.

Main Results:

Gee Fu offers web and console interfaces for data management.
Provides data access via web services and a Ruby API.
Facilitates storage and sharing of multiple assembly versions and associated features.

Conclusions:

Gee Fu enhances accessibility and usability of genomic data for diverse researchers.
The tool supports collaborative research by enabling easy data sharing and updates.
Streamlines the workflow for bioinformaticians and bench scientists working with genome assemblies.