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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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,...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...

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A Method to Study the C924T Polymorphism of the Thromboxane A2 Receptor Gene
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Single nucleotide polymorphisms and haplotypes in Native American populations.

Judith R Kidd1, Françoise Friedlaender, Andrew J Pakstis

  • 1Department of Genetics, Yale University Medical School, New Haven, CT 06520, USA. judith.kidd@yale.edu

American Journal of Physical Anthropology
|September 14, 2011
PubMed
Summary

Autosomal DNA polymorphisms offer insights into Native American population origins and relationships. Comprehensive datasets are crucial for accurately inferring both individual ancestry and historical population connections.

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Area of Science:

  • Population Genetics
  • Human Evolutionary Studies
  • Genomic Ancestry

Background:

  • Autosomal DNA polymorphisms are valuable for understanding Native American population history.
  • Marker selection for genetic studies can be subject to ascertainment bias.
  • Distinguishing between markers for ancestry inference and historical reconstruction is important.

Purpose of the Study:

  • To compare the effectiveness of large haplotype-based datasets versus smaller single nucleotide polymorphism (SNP) sets for Native American population genetics.
  • To determine optimal marker datasets for differentiating Native American populations and inferring individual ancestry.
  • To assess the utility of different genetic datasets for reconstructing historical/evolutionary relationships with Eurasian origins.

Main Methods:

  • Analysis of nine Native American populations using a large haplotype-based dataset.
  • Comparison with smaller, independent sets of single nucleotide polymorphisms (SNPs).
  • Evaluation of two distinct research questions: population differentiation/ancestry inference and historical/evolutionary relationship inference.

Main Results:

  • Comprehensive autosomal marker datasets are necessary to address both ancestry inference and historical relationship questions.
  • Smaller, limited marker sets can answer one question but not both.
  • A general trend of increasing genetic distance from Old World populations was observed from North to South America, with an exception for Maya and Quechua samples.

Conclusions:

  • Only large, comprehensive autosomal datasets can fully resolve questions of Native American population differentiation, ancestry, and historical relationships.
  • Different subsets of genetic markers are suited for specific research aims, but not for dual purposes.
  • The study highlights the complexity of Native American population genetics and the need for robust genomic data.