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DNA as a Genetic Template

DNA as a Genetic Template

Two structural features of the DNA molecule provide a basis for the mechanisms of heredity: the four nucleotide bases and its double-stranded nature. The Watson-Crick model of double-helical DNA structure, proposed in 1952, drew heavily upon the X-ray crystallography work of researchers Rosalind Franklin and Maurice Wilkins. Watson, Crick, and Wilkins jointly received the Nobel Prize in Physiology or Medicine for their work in 1962. Franklin was, controversially, excluded from the prize for...

DNA as a Genetic Template

DNA as a Genetic Template

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

Genome Size and the Evolution of New Genes

Genomics

Genomics

Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...

Structure of a Gene

Structure of a Gene

A gene is the fundamental unit of heredity. Every individual has two copies of each gene, one inherited from each parent. Although most people contain the same genes, there is a small fraction that is slightly different amongst people. A gene with a small difference in its sequence of DNA bases forms different alleles, contributing to different phenotypes.
However, only 1% of the DNA is composed of genes that encode proteins; the rest, 99% is non-coding DNA. This non-coding DNA performs...

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Related Experiment Video

Updated: Mar 11, 2026

Novel Sequence Discovery by Subtractive Genomics

Novel Sequence Discovery by Subtractive Genomics

Published on: January 25, 2019

Finding Genes in Genome Sequence.

Alice Carolyn McHardy^1,2, Andreas Kloetgen^3,4

¹Department for Algorithmic Bioinformatics, Heinrich Heine University, Düsseldorf, Germany. mchardy@hhu.de.

Methods in Molecular Biology (Clifton, N.J.)

|November 30, 2016

Summary

Gene finding identifies DNA regions encoding proteins or functional RNAs, crucial for genomic analysis. This chapter details automated methods for protein-coding gene identification across diverse genomes.

Keywords:

Environmental sequence samples Gene finding Gene prediction Genomic sequence Next-generation sequencing Protein-coding sequences

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Last Updated: Mar 11, 2026

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Published on: October 6, 2014

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Gene finding is the critical first step in analyzing genomic sequences.
Accurate gene identification underpins all subsequent downstream analyses.
Understanding gene structure is essential for deciphering biological function.

Purpose of the Study:

To describe the biological basis of gene finding.
To present computational approaches for automated protein-coding gene identification.
To review the state-of-the-art in gene finding for various genomic contexts.

Main Methods:

Review of biological principles underlying gene structure.
Description of computational algorithms and software for gene prediction.
Analysis of gene finding performance across different genome types.

Main Results:

Comprehensive overview of automated gene finding techniques.
Discussion of methods applicable to bacterial, archaeal, and eukaryotic genomes.
Consideration of gene finding in complex environmental sequence data.

Conclusions:

Automated gene finding is a well-established yet evolving field.
The described methods provide a foundation for analyzing novel genomic data.
Accurate gene identification remains paramount for biological discovery.