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Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.

Genome Size and the Evolution of New Genes

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Evolutionary Relationships through Genome Comparisons

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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...

Complementary DNA

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Gene Duplication and Divergence

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The seminal work of Ohno in 1970 popularized the idea of gene duplication and divergence. DNA sequence comparison studies reveal that a large portion of the genes in bacteria, archaebacteria, and eukaryotes was generated by gene duplication and divergence, indicating its critical role in evolution.
The duplicated copies of the gene are called Paralogs. Paralogs with similar sequences and functions form a gene family. Across several species, a large number of gene families are...

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Updated: Mar 16, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

NRGC: a novel referential genome compression algorithm.

Subrata Saha¹, Sanguthevar Rajasekaran¹

¹Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269-4155, USA.

Bioinformatics (Oxford, England)

|August 4, 2016

Summary

This summary is machine-generated.

A new algorithm, Novel Referential Genome Compression (NRGC), offers effective and efficient compression for biological sequencing data. This method outperforms existing algorithms, addressing storage and transmission bottlenecks in genomics research.

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Metagenomic Analysis of Silage

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Published on: January 13, 2017

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Next-generation sequencing generates massive biological data, creating storage and transmission challenges.
Existing data compression algorithms are not optimized for the unique structure of genomic sequences.
Efficient compression is crucial for advancing genomic research and medical applications.

Purpose of the Study:

To develop a novel algorithm for effective and efficient compression of genomic sequences.
To address the data storage and transmission bottlenecks in genomics.

Main Methods:

Proposed a novel referential genome compression algorithm (NRGC).
Evaluated NRGC using real human genome datasets through rigorous experiments.

Main Results:

NRGC demonstrated effective genome compression capabilities.
The algorithm outperformed existing state-of-the-art compression algorithms in most cases.
Achieved impressive compression and decompression times.

Conclusions:

NRGC is a highly effective and efficient solution for genomic data compression.
The algorithm addresses critical challenges in managing large-scale biological sequence data.
The NRGC implementation is available for non-commercial use.