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From DNA to Protein03:06

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The flow of genetic information in cells from DNA to mRNA to protein is described by the central dogma, which states that genes specify the sequence of mRNAs, which in turn specify the sequence of amino acids making up all proteins. The decoding of one molecule to another is performed by specific proteins and RNAs. Because the information stored in DNA is so central to cellular function, it makes intuitive sense that the cell would make mRNA copies of this information for protein synthesis...
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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...
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Related Experiment Video

Updated: Mar 31, 2026

Residue-specific Incorporation of Noncanonical Amino Acids into Model Proteins Using an Escherichia coli Cell-free Transcription-translation System
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A Mutation Model from First Principles of the Genetic Code.

Steinar Thorvaldsen

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |October 21, 2015
    PubMed
    Summary

    A new Codons Probability Mutations (CPM) model quantifies genetic decay using Markov processes. Organisms in warmer environments show higher genetic decay than those in colder ones.

    Area of Science:

    • Molecular Evolution
    • Bioinformatics
    • Computational Biology

    Background:

    • Standard models like PAM and BLOSUM analyze protein evolution.
    • Genetic decay, or the loss of genetic information, is a key aspect of molecular evolution.
    • Understanding genetic decay is crucial for evolutionary studies.

    Purpose of the Study:

    • To introduce a novel, neutral Codons Probability Mutations (CPM) model for molecular evolution and genetic decay.
    • To provide an alternative to existing substitution matrix models (PAM, BLOSUM).
    • To quantify genetic decay using a codon-based Markov process.

    Main Methods:

    • Developed a Markov process model with a 20-dimensional state space for amino acid probability distributions.
    • Incorporated mutation rates and genetic code-compatible single point mutations into the transition matrix.

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  • Quantified genetic decay by comparing species' amino acid distributions to the model's equilibrium distribution.

    • Main Results:

    • The CPM model, alongside the PAM model, predicts genetic decay towards an equilibrium value of 1 across eukaryotes, bacteria, and archaea.
    • Analysis of a bacterial family revealed that organisms in warmer environments exhibit greater genetic decay than those in colder environments.
    • The study demonstrates a codon-based approach to measuring genetic decay.

    Conclusions:

    • The CPM model offers a new codon-based framework for studying genetic entropy increase over time in neutral evolution.
    • The findings suggest a correlation between environmental temperature and the rate of genetic decay.
    • This work represents a foundational step towards utilizing codon-based Markov models in evolutionary biology.