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Related Concept Videos

Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

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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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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.
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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
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Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
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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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Frequency and Distribution of Crossovers in Caenorhabditis elegans Meiosis by SNP Genotyping using Real-time PCR
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Efficient Estimation of Realized Kinship from Single Nucleotide Polymorphism Genotypes.

Bowen Wang1, Serge Sverdlov1, Elizabeth Thompson2

  • 1Department of Statistics, University of Washington, Seattle, Washington 98195-4322.

Genetics
|January 20, 2017
PubMed
Summary

We developed new methods for estimating kinship using genetic data. Our optimal estimators improve accuracy by considering marker linkage disequilibrium and physical location.

Keywords:
genomic relationship matrix (GRM)linkage disequilibriumlocal identity by descent (IBD)locus weightingrealized kinship

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Area of Science:

  • Population Genetics
  • Statistical Genetics

Background:

  • Realized kinship is crucial for analyzing genetic data, including individual relatedness and population structure.
  • Existing kinship estimators often use dense single nucleotide polymorphism (SNP) genotypes.

Purpose of the Study:

  • Introduce a novel class of kinship estimators.
  • Derive properties and identify an optimal estimator within this class.
  • Develop and apply marker weighting accounting for linkage disequilibrium (LD).

Main Methods:

  • Developed a new class of kinship estimators.
  • Derived theoretical properties of these estimators.
  • Introduced LD-aware marker weighting.
  • Evaluated estimators using simulation studies.

Main Results:

  • Identified an optimal kinship estimator within the new class.
  • Demonstrated improved estimator performance through LD-aware weighting.
  • Showed benefits of considering marker linkage disequilibrium and physical genome contiguity.

Conclusions:

  • The novel class of estimators offers improved accuracy for kinship estimation.
  • Marker weighting strategies, particularly those incorporating LD, enhance genetic analyses.
  • Optimal weighting and consideration of genomic context are key for precise kinship estimation.