Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Population Genetics?01:25

What is Population Genetics?

57.9K
A population is composed of members of the same species that simultaneously live and interact in the same area. When individuals in a population breed, they pass down their genes to their offspring. Many of these genes are polymorphic, meaning that they occur in multiple variants. Such variations of a gene are referred to as alleles. The collective set of all the alleles within a population is known as the gene pool.
57.9K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.1K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.1K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.7K
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...
5.7K

You might also read

Related Articles

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

Sort by
Same author

Comparative Effects of Live and Heat-Killed <i>Lacticaseibacillus paracasei</i> HP7 on Intestinal Motility, Barrier-Related Markers, and Gut Microbiota in Delayed Transit Mice.

Journal of microbiology and biotechnology·2026
Same author

Nanoparticle-mediated inhibition of Yes-associated protein prevents corneal scarring after traumatic injury.

Materials today. Bio·2026
Same author

Spin-orbit effects on the molecular properties of Group 14 tetracoordinate compounds TX4 (T = Ge, Sn, and Pb; X = H, F, Cl, Br, and I): Natural electron configuration-based rationalization of structural variations.

The Journal of chemical physics·2026
Same author

Glycine-modulating Slc6a20a-ASO restores NMDA receptor function in SHANK2 and SHANK3-mutant mice and cortical organoids.

Nature communications·2026
Same author

Human norovirus GII genotypic diversity in Gwangju, South Korea, based on ORF1-ORF2 junction (RdRp-VP1) analysis from 2020 to 2024.

Scientific reports·2026
Same author

<i>Lactiplantibacillus plantarum</i> HY7718 Modulates Gut-Kidney Axis-Associated Inflammation, Gastrointestinal Dysfunction, and Gut Microbiota in Adenine-Induced Chronic Kidney Disease Mice.

International journal of molecular sciences·2026

Related Experiment Video

Updated: Jul 1, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.2K

PAPipe: A Pipeline for Comprehensive Population Genetic Analysis.

Nayoung Park1, Hyeonji Kim1, Jeongmin Oh1

  • 1Department of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.

Molecular Biology and Evolution
|March 1, 2024
PubMed
Summary

PAPipe is a new automated pipeline for population genetic analysis using next-generation sequencing data. It simplifies complex analyses, making population genetics more accessible to researchers.

Keywords:
next-generation sequencingpipelinepopulation genetic analysissingle nucleotide polymorphism

More Related Videos

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K
Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

27.5K

Related Experiment Videos

Last Updated: Jul 1, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
08:03

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

2.2K
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
14:06

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

15.2K
Pyrosequencing: A Simple Method for Accurate Genotyping
13:06

Pyrosequencing: A Simple Method for Accurate Genotyping

Published on: January 8, 2008

27.5K

Area of Science:

  • Population genetics
  • Bioinformatics
  • Genomics

Background:

  • Next-generation sequencing (NGS) generates vast population genetic variant data.
  • Existing analysis tools require diverse environments and formats, hindering accessibility for general researchers.
  • A need exists for integrated and user-friendly population genetic analysis tools.

Purpose of the Study:

  • To develop an automated and comprehensive pipeline (PAPipe) for population genetic analyses.
  • To simplify the analysis of population genetic variant data from NGS.
  • To provide an accessible tool for understanding population structure and evolution.

Main Methods:

  • Developed PAPipe, an automated pipeline integrating read trimming, mapping, variant calling, filtering, and format conversion.
  • Integrated nine key population genetic analyses: PCA, phylogenetic, population tree, population structure, LD decay, selective sweep, admixture, SMC++, and Fst.
  • Implemented an intuitive web interface for parameter setting and results browsing.

Main Results:

  • PAPipe automates and integrates multiple complex population genetic analyses.
  • The pipeline handles various data formats and analysis parameters seamlessly.
  • An accessible web interface enhances user convenience and data usability.

Conclusions:

  • PAPipe addresses the accessibility barrier in population genetic analysis of NGS data.
  • The pipeline provides comprehensive insights into population structure and evolution.
  • PAPipe enhances data usability and researcher convenience in population genetics.