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Related Concept Videos

Evolutionary Relationships through Genome Comparisons02:54

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: Jul 8, 2026

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
09:32

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis

Published on: October 15, 2021

Haplotype inference from diploid sequence data: evaluating performance using non-neutral MHC sequences.

David H Bos1, Sara M Turner, J Andrew Dewoody

  • 1Bindley Bioscience Center and Department of Forestry & Natural Resources, Purdue University, West Lafayette, Indiana, USA. dbos@purdue.edu

Hereditas
|January 25, 2008
PubMed
Summary

Directly sequencing DNA from diploid organisms is challenging. Analytical methods, like the PHASE program, effectively infer haplotypes from complex sequences, even under strong selection.

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Stability and Structure of Bat Major Histocompatibility Complex Class I with Heterologous β2-Microglobulin
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Last Updated: Jul 8, 2026

Immunopeptidomics: Isolation of Mouse and Human MHC Class I- and II-Associated Peptides for Mass Spectrometry Analysis
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Published on: October 15, 2021

Stability and Structure of Bat Major Histocompatibility Complex Class I with Heterologous β2-Microglobulin
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Stability and Structure of Bat Major Histocompatibility Complex Class I with Heterologous β2-Microglobulin

Published on: March 10, 2021

Area of Science:

  • Population Genetics
  • Bioinformatics
  • Molecular Evolution

Background:

  • Direct sequencing of PCR products from diploid organisms presents challenges in phase inference due to heterozygosity.
  • Existing molecular methods (cloning, SSCP, DGGE) reduce diploid sequences to haploid components but are time-consuming and costly.
  • Analytical approaches offer a more efficient alternative to molecular methods for haplotype inference.

Purpose of the Study:

  • To evaluate the performance of the Bayesian algorithm implemented in the PHASE program for haplotype inference.
  • To assess the effectiveness of analytical methods using non-neutral Major Histocompatibility Complex (MHC) sequences with numerous heterozygous sites.

Main Methods:

  • Utilized non-neutral MHC sequences, known for high heterozygosity and strong balancing selection, to test analytical algorithms.
  • Evaluated the performance of the PHASE program, a popular Bayesian algorithm for haplotype inference.
  • Compared the accuracy of analytical inference against empirical data, although not explicitly detailed as a comparative method in the abstract.

Main Results:

  • The PHASE program demonstrated admirable performance in inferring haplotypes from non-neutral sequences.
  • The algorithm successfully handled sequences with a large number of heterozygous sites, characteristic of MHC class II genes.
  • Results indicate the robustness of PHASE even when standard assumptions of neutral evolution are violated.

Conclusions:

  • Analytical approaches, exemplified by the PHASE program, show significant potential for large-scale population genetic analyses.
  • These methods can reliably infer haplotypes from complex diploid sequences, reducing the need for extensive molecular work.
  • Recommends empirical validation of analytical results, especially at the beginning of population-level studies, to ensure accuracy.