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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...

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.

RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Related Experiment Video

Updated: Jun 11, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

FindCSV: a long-read based method for detecting complex structural variations.

Yan Zheng¹, Xuequn Shang²

¹School of Computer Science, Northwestern Polytechnical University, West Youyi Road 127, Xi'an, 710072, China. yan.zheng@mail.nwpu.edu.cn.

BMC Bioinformatics

|September 28, 2024

Summary

This summary is machine-generated.

A new deep learning method, FindCSV, improves the detection of complex structural variations (SVs) using long-read sequencing. This advancement offers higher accuracy for identifying genetic variations impacting health and evolution.

Keywords:

Complex structural variations Consensus sequences Deep learning Long-read sequencing data

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Last Updated: Jun 11, 2025

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Ultra-long Read Sequencing for Whole Genomic DNA Analysis

Published on: March 15, 2019

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

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Published on: December 9, 2016

Area of Science:

Genomics
Bioinformatics

Background:

Structural variations (SVs) are crucial in genetic diseases and evolution.
Simple SV detection methods are established, but complex SVs' impact is increasingly recognized.
Precise detection methods for complex SVs are currently lacking, necessitating new approaches.

Purpose of the Study:

To develop a novel, highly efficient, and accurate method for detecting complex structural variations.
To address the limitations of existing methods in identifying complex genomic alterations.

Main Methods:

Proposed FindCSV, a novel method utilizing deep learning techniques.
Employed consensus sequences for enhanced structural variation detection.
Utilized long-read sequencing data for analysis.

Main Results:

FindCSV demonstrated superior performance in detecting both complex and simple structural variations compared to existing methods.
The method achieved reasonable accuracy on both real and simulated genomic data.

Conclusions:

FindCSV is a new, accurate tool for detecting complex and simple structural variations.
The developed method shows promise for advancing genomic research and clinical applications.
Source code is publicly available for community use and further development.