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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease
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An expanded sequence context model broadly explains variability in polymorphism levels across the human genome.

Varun Aggarwala1, Benjamin F Voight2,3

  • 1Genomics and Computational Biology Program, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

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Summary

Human genome polymorphism rates vary, influencing evolution and disease. A new heptanucleotide context model explains over 81% of substitution variability, identifying novel mutation hotspots and aiding genetic disease prediction.

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Area of Science:

  • Genomics
  • Human Genetics
  • Evolutionary Biology

Background:

  • Single-nucleotide polymorphism (SNP) rates vary across the human genome, impacting evolution and genetic disease.
  • Previous studies focused on trinucleotide contexts, leaving larger sequence context impacts unclear.

Purpose of the Study:

  • To investigate the impact of larger sequence contexts on human genome polymorphism rates.
  • To develop a novel statistical framework for analyzing substitution probabilities and identifying mutation-promoting motifs.
  • To create new intolerance scores for genes and amino acids and demonstrate clinical utility.

Main Methods:

  • Utilized a new statistical framework and data from the 1000 Genomes Project.
  • Analyzed heptanucleotide sequence contexts to explain variability in substitution probabilities.
  • Developed gene and amino acid substitution intolerance scores.

Main Results:

  • A heptanucleotide context explained over 81% of variability in substitution probabilities.
  • Identified novel mutation-promoting motifs, including ApT dinucleotides, CAAT, and TACG sequences.
  • Discovered undocumented variability in C-to-T substitutions at CpG sites and demonstrated clinical application in neuropsychiatric diseases.

Conclusions:

  • Sequence context, particularly heptanucleotide, is a major driver of human genome polymorphism.
  • The developed model provides a more comprehensive understanding of mutation rates and their impact on genetic disease.
  • New intolerance scores offer valuable tools for genetic research and clinical applications.