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

Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

20.1K
Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
20.1K
In-vitro Mutagenesis01:16

In-vitro Mutagenesis

15.4K
To learn more about the function of a gene, researchers can observe what happens when the gene is inactivated or “knocked out,” by creating genetically engineered knockout animals. Knockout mice have been particularly useful as models for human diseases such as cancer, Parkinson’s disease, and diabetes.
15.4K
Genetic Screens02:46

Genetic Screens

5.2K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
5.2K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

60.1K
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).
60.1K
Hybrid Zones02:29

Hybrid Zones

20.6K
Hybrid zones are narrow regions where two closely related species interact, mate, and produce hybrids. Relative to either parent species, hybrids may possess distinct phenotypic or genetic differences that impact their survival and reproductive success. The genetic variances introduced by hybridization influence species diversity and speciation processes within the hybrid zone.
20.6K
Monohybrid Crosses01:20

Monohybrid Crosses

233.1K
Overview
233.1K

You might also read

Related Articles

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

Sort by
Same author

Decoding RNA N6-Methyladenosine Methylome of Wheat Using Machine Learning and Nanopore Direct RNA Sequencing.

Genomics, proteomics & bioinformatics·2026
Same author

PanGraphRNA: An efficient and flexible bioinformatics platform for graph pangenome-based RNA-seq data analysis.

Journal of integrative plant biology·2026
Same author

deepTFBS: Improving within- and Cross-Species Prediction of Transcription Factor Binding Using Deep Multi-Task and Transfer Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2025
Same author

The N6-methyladenosine reader ECT1 regulates seed germination via gibberellic acid- and phytochrome B-mediated signaling.

Plant physiology·2025
Same author

PEA-m6A: an ensemble learning framework for accurately predicting N6-methyladenosine modifications in plants.

Plant physiology·2024
Same author

iFLAS: positive-unlabeled learning facilitates full-length transcriptome-based identification and functional exploration of alternatively spliced isoforms in maize.

The New phytologist·2024

Related Experiment Video

Updated: Oct 16, 2025

Scalable Transfection of Maize Mesophyll Protoplasts
08:38

Scalable Transfection of Maize Mesophyll Protoplasts

Published on: June 23, 2023

3.1K

Genome optimization via virtual simulation to accelerate maize hybrid breeding.

Qian Cheng1, Shuqing Jiang2, Feng Xu2

  • 1State Key Laboratory of Crop Stress Biology for Arid Areas, Center of Bioinformatics, College of Life Sciences, Northwest A&F University, Shaanxi, China.

Briefings in Bioinformatics
|October 22, 2021
PubMed
Summary

Genome optimization via virtual simulation (GOVS) aids maize breeding by selecting superior lines using genotypes, complementing genomic selection (GS) and accelerating doubled-haploid (DH) line development.

Keywords:
Zea mayscomputational simulationdoubled haploidgenomic selectiongenotype-to-phenotype predictionplant breeding

More Related Videos

Agrobacterium-Mediated Immature Embryo Transformation of Recalcitrant Maize Inbred Lines Using Morphogenic Genes
10:28

Agrobacterium-Mediated Immature Embryo Transformation of Recalcitrant Maize Inbred Lines Using Morphogenic Genes

Published on: February 14, 2020

23.9K
An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants
09:32

An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

Published on: November 8, 2017

8.0K

Related Experiment Videos

Last Updated: Oct 16, 2025

Scalable Transfection of Maize Mesophyll Protoplasts
08:38

Scalable Transfection of Maize Mesophyll Protoplasts

Published on: June 23, 2023

3.1K
Agrobacterium-Mediated Immature Embryo Transformation of Recalcitrant Maize Inbred Lines Using Morphogenic Genes
10:28

Agrobacterium-Mediated Immature Embryo Transformation of Recalcitrant Maize Inbred Lines Using Morphogenic Genes

Published on: February 14, 2020

23.9K
An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants
09:32

An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

Published on: November 8, 2017

8.0K

Area of Science:

  • Plant breeding
  • Genomics
  • Computational biology

Background:

  • Doubled-haploid (DH) technology accelerates maize inbred line development.
  • Genomic selection (GS) is crucial for selecting superior lines due to high phenotyping costs.
  • Efficient genotype-based screening of numerous inbred lines remains a challenge.

Purpose of the Study:

  • To implement and evaluate a novel 'genome optimization via virtual simulation' (GOVS) toolbox.
  • To assist in the selection of superior maize lines based on genomic contributions to a virtual genome.
  • To optimize the strategy for doubled-haploid (DH) line production by identifying complementary elite lines.

Main Methods:

  • Utilized genotype and phenotype data from 1404 maize lines and their F1 progeny.
  • Developed GOVS to simulate a virtual genome with abundant optimal genotypes.
  • Assessed line superiority based on contributions of genomic fragments to the simulated genome.

Main Results:

  • GOVS facilitates selection of superior lines by identifying those contributing more optimal genotype fragments.
  • GOVS-assisted selection avoids arbitrary thresholds common in traditional GS.
  • Selected lines demonstrated complementary advantageous alleles, aiding DH production strategy.

Conclusions:

  • GOVS provides a novel approach to complement traditional genomic selection in maize.
  • The GOVS toolbox can guide breeding decisions and optimize DH line development.
  • Integrating DH production, GS, and genome optimization enhances genomically designed breeding in maize.