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Related Concept Videos

Dihybrid Crosses01:18

Dihybrid Crosses

Overview
Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Law of Segregation01:49

Law of Segregation

When crossing pea plants, Mendel noticed that one of the parental traits would sometimes disappear in the first generation of offspring, called the F1 generation, and could reappear in the next generation (F2). He concluded that one of the traits must be dominant over the other, thereby causing masking of one trait in the F1 generation. When he crossed the F1 plants, he found that 75% of the offspring in the F2 generation had the dominant phenotype, while 25% had the recessive phenotype.
Trihybrid Crosses02:27

Trihybrid Crosses

Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal chance to...
Chi-square Analysis02:46

Chi-square Analysis

The chi-square test is a statistical hypothesis test. It is used to check whether there is a significant difference between an expected value and an observed value. In the context of genetics, it enables us to either accept or reject a hypothesis, based on how much the observed values deviate from the expected values.
The chi-square test was developed by Pearson in 1990.
The first step of performing a Chi-square analysis is to establish a null hypothesis, which assumes that there is no real...

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Related Experiment Video

Updated: May 24, 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

Linkage analysis merging replicate phenotypes: an application to three quantitative phenotypes in two African

Anthony L Hinrichs1, Robert C Culverhouse, Brian K Suarez

  • 1Department of Psychiatry, Washington University School of Medicine, 660 South Euclid Ave,, Campus Box 8134, St, Louis, MO 63110, USA. tony@fire.wustl.edu.

BMC Proceedings
|March 1, 2012
PubMed
Summary
This summary is machine-generated.

We developed two linkage analysis methods for replicate phenotypes. One novel method, applied to quantitative traits in African families, identified significant linkage signals for Q1, but not for Q2 or Q4.

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Last Updated: May 24, 2026

Genetic Mapping of Thermotolerance Differences Between Species of Saccharomyces Yeast via Genome-Wide Reciprocal Hemizygosity Analysis
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Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Linkage analysis is crucial for identifying genes associated with diseases.
  • Analyzing complex family pedigree data with replicate phenotypes presents unique challenges.
  • The Genetic Analysis Workshop 17 (GAW17) provided a valuable dataset for methodological development.

Purpose of the Study:

  • To develop and evaluate novel approaches for linkage analysis in the presence of replicate phenotypes.
  • To compare a new method tailored for replicate data against a standard linkage analysis approach.
  • To investigate the genetic basis of quantitative traits (Q1, Q2, Q4) in African families using these methods.

Main Methods:

  • Two distinct linkage analysis strategies were employed: a novel method for replicate structures and a standard approach.
  • Analyses were performed on three quantitative phenotypes (Q1, Q2, Q4) from African family datasets.
  • All analyses were conducted blind to the known genetic model of the data.

Main Results:

  • Numerous significant linkage signals were detected for quantitative trait Q1 using both methods.
  • However, population colocalization was largely absent for the identified Q1 linkage signals.
  • Linkage analysis for quantitative traits Q2 and Q4 did not yield any strong significant signals.

Conclusions:

  • The novel linkage analysis approach shows promise for identifying genetic loci associated with quantitative traits, particularly in datasets with replicate phenotypes.
  • The findings suggest complex genetic architectures for Q2 and Q4, or that the analyzed regions do not harbor major quantitative trait loci.
  • Further investigation is warranted to understand the genetic underpinnings of these quantitative traits in the studied population.