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Evolutionary Relationships through Genome Comparisons

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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Related Experiment Video

Updated: May 9, 2026

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
10:08

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis

Published on: August 12, 2019

Genomic evaluations using similarity between haplotypes.

J M Hickey1, B P Kinghorn, B Tier

  • 1School of Environmental and Rural Science, University of New England, Armidale, Australia.

Journal of Animal Breeding and Genetics = Zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie
|July 17, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for genomic prediction using haplotype similarity. While it better reflects true genetic relationships, it did not improve prediction accuracy over existing methods using unphased genotypes.

Keywords:
Genomic selectionhaplotypessimilarity

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Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Area of Science:

  • Animal Breeding and Genetics
  • Genomics
  • Statistical Genetics

Background:

  • Long-range phasing and haplotype imputation provide valuable genetic information for predicting breeding values and phenotypes.
  • Modeling long haplotypes directly in genomic prediction is computationally inefficient and sensitive to phasing errors.

Purpose of the Study:

  • To develop and evaluate a method that models haplotype similarity to capture genomic effects covariance.
  • To assess the impact of this haplotype similarity method on genomic prediction accuracy.

Main Methods:

  • Developed a simple method to construct a genomic relationship matrix based on haplotype similarity.
  • Tested the method's performance using simulation studies.
  • Compared haplotype-based genomic relationship matrices with those from unphased genotypes and unrelated haplotypes.

Main Results:

  • The genomic relationship matrix built using haplotype similarity showed higher correlations with true relationships than matrices from unphased genotypes or unrelated haplotypes.
  • Despite improved relationship estimation, haplotype-based prediction methods did not achieve higher prediction accuracy compared to methods using unphased genotypes.

Conclusions:

  • Haplotype similarity can more accurately represent true genetic relationships between individuals.
  • Current methods for incorporating haplotype information into genomic prediction do not yet surpass the accuracy of using unphased genotypes.