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

18.7K
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.
18.7K
Light Acquisition02:16

Light Acquisition

8.4K
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.
8.4K
Trihybrid Crosses02:27

Trihybrid Crosses

22.9K
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...
22.9K
Inheritance01:25

Inheritance

322
Gregor Mendel's pioneering work on the principles of inheritance fundamentally transformed our understanding of how traits are transmitted from generation to generation. His experiments with pea plants laid the groundwork for the discovery of genes, discrete units within organisms that control heredity.
Each gene exists in pairs, and the combination of these genes from both parents forms an individual's genotype. This genotype is a blueprint of potential traits. Examples of genotype...
322
Polygenic Traits01:18

Polygenic Traits

64.6K
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
64.6K
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

Genetic mechanisms underlying temperature-mediated changes in flower development.

Journal of experimental botany·2026
Same author

High-throughput Raman-activated cell sorting of microalgal genome-wide edited library revealed a regulatory pathway for carotenoid synthesis.

Nature communications·2026
Same author

Kinetic parameter prediction using neural networks identifies limitations to C<sub>4</sub> photosynthesis.

The New phytologist·2026
Same author

Temperature-mediated plasticity of floral and fitness traits in <i>Arabidopsis thaliana</i>.

Quantitative plant biology·2026
Same author

Diversity of Root System Architecture in Mediterranean Maize Inbred Lines Provides New Breeding Opportunities to Improve Stress Resilience and Resource Efficiency.

Plants (Basel, Switzerland)·2026
Same author

GraFT: A robust network-based spatiotemporal analysis of filamentous structures.

Science advances·2026
Same journal

N-myristoylation-mediated shuttling of TaMP from plasma membrane to chloroplasts increases wheat susceptibility to rust fungi.

Nature plants·2026
Same journal

New tools crack repetitive cane.

Nature plants·2026
Same journal

Somatic embryogenesis resets the epigenetic cold memory.

Nature plants·2026
Same journal

Resetting of epigenetic cold memory through somatic embryogenesis in plant regeneration.

Nature plants·2026
Same journal

Protecting plants, protecting lives.

Nature plants·2026
Same journal

Author Correction: Rice roots recruit Bacillus via the secretion of heptadecanoic acid.

Nature plants·2026
See all related articles
  1. Home
  3. Predicting Plant Trait Dynamics From Genetic Markers.
  1. Home
  3. Predicting Plant Trait Dynamics From Genetic Markers.

Related Experiment Video

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&#8211;Environment Interactions
15:30

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

11.4K

Predicting plant trait dynamics from genetic markers.

David Hobby1,2, Hao Tong1,2, Marc Heuermann3

  • 1Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany.

Nature Plants
|April 17, 2025

View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces dynamicGP, a new computational method for predicting plant traits over time. dynamicGP improves the prediction of crop development dynamics using genetic markers and high-throughput phenotyping data.

More Related Videos

Author Spotlight: Non-Invasive High-Resolution Measurement of Chlorophyll Synthesis During De-Etiolation
07:58

Author Spotlight: Non-Invasive High-Resolution Measurement of Chlorophyll Synthesis During De-Etiolation

Published on: January 12, 2024

700
Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

19.6K

Related Experiment Videos

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant&#8211;Environment Interactions
15:30

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions

Published on: August 5, 2020

11.4K
Author Spotlight: Non-Invasive High-Resolution Measurement of Chlorophyll Synthesis During De-Etiolation
07:58

Author Spotlight: Non-Invasive High-Resolution Measurement of Chlorophyll Synthesis During De-Etiolation

Published on: January 12, 2024

700
Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

19.6K

Area of Science:

  • Plant science
  • Genetics
  • Computational biology

Background:

  • Crop development involves complex molecular and physiological changes.
  • Predicting plant phenomes from genetic markers is challenging due to these dynamic changes.

Purpose of the Study:

  • To develop an efficient computational approach for predicting genotype-specific dynamics of plant traits.
  • To characterize temporal changes in the plant phenome.

Main Methods:

  • Genomic prediction combined with dynamic mode decomposition (dynamicGP).
  • Utilized high-throughput phenotyping data from maize and Arabidopsis thaliana.
  • Assessed prediction accuracy for morphometric, geometric, and colorimetric traits.

Main Results:

  • dynamicGP significantly outperformed a baseline genomic prediction approach.
  • Traits with stable heritability over time showed higher prediction accuracy.
  • Demonstrated the ability to characterize and predict genotype-specific trait dynamics.

Conclusions:

  • dynamicGP offers an efficient method for analyzing and predicting plant development dynamics.
  • The approach can integrate genotype and environment interactions over time.
  • Improves prediction accuracy for agronomically important traits.