ABI Bioinformatics Guide 2024
  • INTRODUCTION
    • How to use the guide
  • MOLECULAR BIOLOGY
    • The Cell
      • Cells and Their Organelles
      • Cell Specialisation
      • Quiz 1
    • Biological Molecules
      • Carbohydrates
      • Lipids
      • Nucleic Acids (DNA and RNA)
      • Quiz 2
      • Proteins
      • Catalysis of Biological Reactions
      • Quiz 3
    • Information Flow in the Cell
      • DNA Replication
      • Gene Expression: Transcription
      • Gene Expression: RNA Processing
      • Quiz 4
      • Chromatin and Chromosomes
      • Regulation of Gene Expression
      • Quiz 5
      • The Genetic Code
      • Gene Expression: Translation
    • Cell Cycle and Cell Division
      • Quiz 6
    • Mutations and Variations
      • Point mutations
      • Genotype-Phenotype Interactions
      • Quiz 7
  • PROGRAMMING
    • Python for Genomics
    • R programming (optional)
  • STATISTICS: THEORY
    • Introduction to Probability
      • Conditional Probability
      • Independent Events
    • Random Variables
      • Independent, Dependent and Controlled Variables
    • Data distribution PMF, PDF, CDF
    • Mean, Variance of a Random Variable
    • Some Common Distributions
    • Exploratory Statistics: Mean, Median, Quantiles, Variance/SD
    • Data Visualization
    • Confidence Intervals
    • Comparison tests, p-value, z-score
    • Multiple test correction: Bonferroni, FDR
    • Regression & Correlation
    • Dimentionality Reduction
      • PCA (Principal Component Analysis)
      • t-SNE (t-Distributed Stochastic Neighbor Embedding)
      • UMAP (Uniform Manifold Approximation and Projection)
    • QUIZ
  • STATISTICS & PROGRAMMING
  • BIOINFORMATICS ALGORITHMS
    • Introduction
    • DNA strings and sequencing file formats
    • Read alignment: exact matching
    • Indexing before alignment
    • Read alignment: approximate matching
    • Global and local alignment
  • NGS DATA ANALYSIS & FUNCTIONAL GENOMICS
    • Experimental Techniques
      • Polymerase Chain Reaction
      • Sanger (first generation) Sequencing Technologies
      • Next (second) Generation Sequencing technologies
      • The third generation of sequencing technologies
    • The Linux Command-line
      • Connecting to the Server
      • The Linux Command-Line For Beginners
      • The Bash Terminal
    • File formats, alignment, and genomic features
      • FASTA & FASTQ file formats
      • Basic Unix Commands for Genomics
      • Sequences and Genomic Features Part 1
      • Sequences and Genomic Features Part 2: SAMtools
      • Sequences and Genomic Features Part 3: BEDtools
    • Genetic variations & variant calling
      • Genomic Variations
      • Alignment and variant detection: Practical
      • Integrative Genomics Viewer
      • Variant Calling with GATK
    • RNA Sequencing & Gene expression
      • Gene expression and how we measure it
      • Gene expression quantification and normalization
      • Explorative analysis of gene expression
      • Differential expression analysis with DESeq2
      • Functional enrichment analysis
    • Single-cell Sequencing and Data Analysis
      • scRNA-seq Data Analysis Workflow
      • scRNA-seq Data Visualization Methods
  • FINAL REMARKS
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  • Nucleotide substitutions
  • Deletions and insertions

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  1. MOLECULAR BIOLOGY
  2. Mutations and Variations

Point mutations

PreviousMutations and VariationsNextGenotype-Phenotype Interactions

Last updated 1 year ago

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Mutations are changes in the genetic information of a cell, arising from various sources, including errors during DNA replication and repair. While some mutations lead to large-scale changes in the genome, such as chromosomal translocations, others, known as point mutations, involve alterations of a single base pair in the DNA. Point mutations are the most common type of mutation and are the focus of this chapter.

Mutations can occur in either germline cells, which give rise to gametes and can be passed on to offspring, or somatic cells, which make up the body but are not involved in reproduction. Germline mutations can be inherited by future generations, while somatic mutations are only passed on to descendant cells during cell division. Accumulation of somatic mutations over time can lead to the development of cancer.

Most mutations in the human genome occur in non-coding DNA regions and thus have no or little impact on the phenotype. Mutations causing significant consequences usually occur in the genes or their regulatory regions.

Nucleotide substitutions

Substitution is a type of mutation in which one nucleotide in the DNA sequence is replaced by another (e.g. adenine is substituted by guanine).

These substitutions can have varying effects on the resulting protein. Silent mutations occur when the substitution does not alter the amino acid sequence of the protein due to the redundancy of the genetic code. In other words, the codon affected by a silent mutation still codes for the same amino acid, so the protein's function remains unchanged.

Missense mutations result in the substitution of one amino acid for another in the protein sequence. Depending on the location and type of the alteration, missense mutations vary in their effect. Some missense mutations may only cause subtle changes in protein function, while others can significantly alter the protein's structure or activity e.g. when a mutation changes the shape of an enzyme's active site.

Nonsense mutations are substitutions that change a codon coding for an amino acid into a stop codon. This premature termination of translation leads to the production of a truncated protein, which is often non-functional.

Deletions and insertions

The effects of adding (insertion) or removing (deletion) a nucleotide from the DNA sequence in a coding region are often detrimental. Because the genetic code is read in sets of three nucleotides (codons), the addition or deletion of a single nucleotide causes a frameshift. Deletions and insertions change the reading frame and thus the whole sequence of codons downstream from the mutation. This results in totally different amino acids and, since a stop codon usually appears close to a frameshift mutation, in a truncated polypeptide.

Germline and somatic mutations Image source: Prostate cancer genotyping for risk stratification and precision treatment - Scientific Figure on ResearchGate, https://www.researchgate.net/figure/Fundamental-difference-between-germline-and-somatic-mutations-wwwlearncolontownorg_fig3_380066207, CC BY 4.0
Consequences of nucleotide substitutions Image source: CNX OpenStax - http://cnx.org/contents/GFy_h8cu@10.53:rZudN6XP@2/Introduction, CC BY 4.0, https://commons.wikimedia.org/w/index.php?curid=49926491
Frameshift mutations result in a wrong amino acid sequence and truncated polypeptide Image source: National Human Genome Research Institute – https://www.genome.gov/genetics-glossary/Frameshift-Mutation, CC BY 4.0