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

Trihybrid Crosses02:27

Trihybrid Crosses

26.7K
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...
26.7K
Chi-square Analysis02:46

Chi-square Analysis

44.7K
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...
44.7K
Monohybrid Crosses01:20

Monohybrid Crosses

241.2K
Overview
241.2K
Dihybrid Crosses01:18

Dihybrid Crosses

82.5K
Overview
82.5K
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

512
The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
512
Light Acquisition02:16

Light Acquisition

9.8K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
9.8K

You might also read

Related Articles

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

Sort by
Same author

The MYB transcription factor APL is a rational target for base editing to engineer flowering time.

The Plant cell·2026
Same author

Multiomics analysis of primary metabolism reveals the genetic basis of nitrogen partitioning modulated by ZmAVT1A-1 in maize.

Nature genetics·2026
Same author

Global genetic dissection of maize-teosinte divergence reveals EL3-2 as a pleiotropic domestication regulator.

Genome biology·2026
Same author

Genome-wide association study dissects the genetic architecture of kernel rate and its component traits in maize.

BMC plant biology·2026
Same author

PlantGFM: A Genomic Foundation Model for Discovery and Creation of Plant Genes.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Grading evaluation of haploid fertility restoration traits based on inception-ResNet in maize.

Plant phenomics (Washington, D.C.)·2026

Related Experiment Video

Updated: Mar 30, 2026

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development
10:08

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development

Published on: March 5, 2017

10.1K

KRN4 Controls Quantitative Variation in Maize Kernel Row Number.

Lei Liu1, Yanfang Du1, Xiaomeng Shen1

  • 1National Key Lab of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan Hubei, People's Republic of China.

Plos Genetics
|November 18, 2015
PubMed
Summary

Researchers identified a 1.2-Kb insertion in maize that increases kernel row number (KRN) and yield. This genetic variant, along with a specific SNP in the Unbranched3 gene, was strongly selected during maize domestication and improvement.

More Related Videos

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

1.8K
High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.
05:55

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Published on: June 16, 2018

7.6K

Related Experiment Videos

Last Updated: Mar 30, 2026

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development
10:08

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development

Published on: March 5, 2017

10.1K
Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes
06:41

Imaging and Analysis for Quantifying Maize (Zea mays) Abiotic Stress Phenotypes

Published on: March 28, 2025

1.8K
High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.
05:55

High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize Zea mays L.

Published on: June 16, 2018

7.6K

Area of Science:

  • Plant genetics
  • Maize breeding
  • Quantitative trait loci (QTL) analysis

Background:

  • Kernel row number (KRN) is a key trait for maize yield, influenced by quantitative trait loci (QTL).
  • Understanding the genetic basis of KRN is crucial for maize improvement.

Purpose of the Study:

  • To fine-map the major KRN QTL, KRN4, and identify the genetic elements responsible for quantitative variation in KRN.
  • To investigate the role of regulatory regions and gene variants in modulating UB3 expression and its effect on KRN.

Main Methods:

  • Fine-mapping of the KRN4 QTL region.
  • Association analysis of genetic variants, including a 1.2-Kb Presence-Absence Variant (PAV) and an SNP (S35) in the UB3 gene.
  • Analysis of selection signatures during maize domestication and improvement.

Main Results:

  • A ~3-Kb intergenic region regulating UB3 expression was identified as responsible for KRN variation.
  • A 1.2-Kb transposon-containing insertion within this region was strongly associated with increased KRN.
  • The 1.2-Kb PAV and the S35 SNP genetically interact to modulate KRN, with favorable alleles enriched during maize improvement.

Conclusions:

  • The KRN4 locus, particularly the 1.2-Kb PAV and S35 SNP, plays a significant role in quantitative variation of KRN.
  • Strong selection on favorable alleles of KRN4 during maize domestication and breeding has contributed to increased grain productivity.
  • Dissection of KRN4 provides insights into the genetic architecture of complex traits in maize.