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

Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
Multiple Allele Traits01:49

Multiple Allele Traits

The Concept of Multiple Allelism
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...
Dihybrid Crosses01:18

Dihybrid Crosses

Overview
Monohybrid Crosses01:20

Monohybrid Crosses

Overview
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...

You might also read

Related Articles

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

Sort by
Same author

Current approaches to measuring high-intensity locomotor actions in adult male professional soccer. A scoping review.

Biology of sport·2026
Same author

Variable contribution of inquilines to prey digestion in Nepenthes pitcher plants: the role of pitcher traits.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences·2026
Same author

Artificial intelligence in medical education: promise, caution, and the need for restraint.

Academic medicine : journal of the Association of American Medical Colleges·2026
Same author

Possession in motion: a five-season analysis of running in-possession and out-of-possession with match outcomes in the English Premier League.

Biology of sport·2026
Same author

Barley HvBODYGUARD1 controls cuticular specialisations regulated by SHINE transcription factors.

The New phytologist·2026
Same author

Intraday and Interday Reliability of Maximal and Explosive Handgrip Force-Time Metrics Using the Kinvent K-Grip Handheld Dynamometer.

Muscles (Basel, Switzerland)·2026

Related Experiment Video

Updated: Jun 14, 2026

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput
10:29

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

Published on: March 30, 2018

Exploiting induced variation to dissect quantitative traits in barley.

Arnis Druka1, Jerome Franckowiak, Udda Lundqvist

  • 1Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, Scotland, UK. Arnis.Druka@scri.ac.uk

Biochemical Society Transactions
|March 20, 2010
PubMed
Summary

Identifying genes for complex traits like grain yield is challenging. This study proposes using extreme mutant variants in barley (Hordeum vulgare) to efficiently clone quantitative trait loci (QTLs).

More Related Videos

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

Related Experiment Videos

Last Updated: Jun 14, 2026

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput
10:29

Measuring Gene Expression in Bombarded Barley Aleurone Layers with Increased Throughput

Published on: March 30, 2018

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
07:18

Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling

Published on: May 21, 2020

Area of Science:

  • Plant genetics
  • Agricultural science
  • Genomics

Background:

  • Identifying genes for complex traits like grain yield traditionally requires extensive mapping populations.
  • Extreme allelic variants from mutational studies offer a potentially more efficient approach for cloning quantitative trait loci (QTLs).

Purpose of the Study:

  • To explore the utility of induced or natural mutant alleles in barley (Hordeum vulgare) for efficient identification of genes controlling grain yield and its component traits.
  • To leverage high-throughput genome analysis and comparative genomics to pinpoint candidate genes for yield-related QTLs.

Main Methods:

  • Utilizing genotypic data from near-isogenic lines (NILs) carrying mutant alleles.
  • Comparing the location of mutant alleles with known QTLs for grain yield and its component traits (tillers per plant, kernels per spike, kernel size).
  • Employing comparative genomics by aligning barley gene maps with rice and sorghum physical maps to prioritize candidate genes.

Main Results:

  • Mutant alleles affecting yield component traits and located within QTL confidence intervals are strong candidates for underlying genes.
  • Comparative genomic models aid in prioritizing genes with known functions as candidates for both QTLs and induced mutations.

Conclusions:

  • Extreme allelic variants in barley provide a powerful tool for the efficient cloning of QTLs controlling complex traits like grain yield.
  • Integration of mutation analysis, QTL mapping, and comparative genomics accelerates the discovery of genes underlying important agricultural traits.