Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genome-wide Association Studies-GWAS

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...

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

Position-effect Variegation

Position-effect Variegation

In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.

Single Nucleotide Polymorphisms-SNPs

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,...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Clinical Characteristics of Cerebral Venous Sinus Thrombosis in Patients with Systemic Lupus Erythematosus: A Single-Centre Experience in China.

Journal of immunology research·2015

Same author

[Clinical characteristics of 15 cases of microscopic polyangiitis associated with alveolar hemorrhage].

Zhonghua nei ke za zhi·2015

Same author

Identification of low Ca(2+) stress-induced embryo apoptosis response genes in Arachis hypogaea by SSH-associated library lift (SSHaLL).

Plant biotechnology journal·2015

Same author

A simple score for predicting renal artery stenosis in patients with ischemic heart disease.

International journal of clinical and experimental medicine·2015

Same author

HLA-DPB1 variant rs3117242 is associated with anti-neutrophil cytoplasmic antibody-associated vasculitides in a Han Chinese population.

International journal of rheumatic diseases·2015

Same author

Identification of jasmonic acid-associated microRNAs and characterization of the regulatory roles of the miR319/TCP4 module under root-knot nematode stress in tomato.

Journal of experimental botany·2015

Search research articles

Related Experiment Video

Updated: Apr 20, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

A hidden Markov model for investigating recent positive selection through haplotype structure.

Hua Chen¹, Jody Hey², Montgomery Slatkin³

¹Center for Computational Genomics, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; Center for Computational Genetics and Genomics, Temple University, Philadelphia PA 19122, United States.

Theoretical Population Biology

|December 3, 2014

Summary

We developed a hidden Markov model (HMM) to detect recent positive selection by identifying long ancestral haplotypes. This method accurately estimates selection intensity and allele age, outperforming existing approaches.

Keywords:

Allele age Haplotype structure Hidden Markov model Recent positive selection Selection intensity

More Related Videos

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Related Experiment Videos

Last Updated: Apr 20, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Methods to Increase the Sensitivity of High Resolution Melting Single Nucleotide Polymorphism Genotyping in Malaria

Published on: November 10, 2015

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Following the Dynamics of Structural Variants in Experimentally Evolved Populations

Published on: February 3, 2023

Area of Science:

Population genetics
Genomics
Evolutionary biology

Background:

Recent positive selection leaves detectable signatures on ancestral haplotypes.
Identifying these signatures is crucial for understanding evolutionary adaptation.

Purpose of the Study:

To develop a novel method for detecting recent positive selection.
To infer selection intensity and allele age using haplotype structures.

Main Methods:

A hidden Markov model (HMM) was employed to identify extended ancestral haplotype structures.
A population genetic model was used for parameter inference of selection and allele age.

Main Results:

The HMM-based method demonstrates high power in detecting selection across various conditions.
It provides accurate estimates of selection coefficients and allele ages, particularly for strong selection.
The method efficiently analyzes large genomic datasets.

Conclusions:

The developed HMM approach is a powerful tool for identifying recent positive selection.
It successfully identified candidate regions under selection in HapMap III data and provided estimates for known selected genes.