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

Genome Annotation and Assembly03:36

Genome Annotation and Assembly

18.8K
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
18.8K
Proteomics01:33

Proteomics

7.3K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
7.3K
Genomics02:02

Genomics

36.2K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
36.2K
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

13.2K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
13.2K

You might also read

Related Articles

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

Sort by
Same author

Multi-scale analysis of brown seaweed fortified pasta on structural, functional, nutraceutical, sensorial and volatilomic attributes.

Food chemistry·2026
Same author

Analysis of the TaNAS gene family in bread wheat identifies additional members and candidates for intragenic biofortification.

Journal of experimental botany·2026
Same author

Bio-Accessibility of Phenolic Compounds from Green Banana-Fortified Bread During Simulated Digestion and Colonic Fermentation.

Molecules (Basel, Switzerland)·2025
Same author

Mobilizing Triticeae diversity from gene banks to farmer's field.

Molecular plant·2025
Same author

Near-complete assembly and comprehensive annotation of the wheat Chinese Spring genome.

Molecular plant·2025
Same author

The Physicochemical and Rheological Properties of Green Banana Flour-Wheat Flour Bread Substitutions.

Plants (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jun 14, 2025

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
08:36

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis

Published on: July 16, 2019

11.6K

Community Resource: Large-Scale Proteogenomics to Refine Wheat Genome Annotations.

Delphine Vincent1, Rudi Appels2

  • 1Independent Researcher, Melbourne, VIC 3000, Australia.

International Journal of Molecular Sciences
|August 29, 2024
PubMed
Summary

This study mapped wheat peptides to the reference genome, validating thousands of gene models and identifying new ones. The proteogenomics workflow enhances understanding of wheat gene expression under various conditions.

Keywords:
Triticum aestivumbottom-up proteogenomicsgene modelsgenome annotationmultiple sequence alignmentproteomics

More Related Videos

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

9.7K
Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
12:33

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Published on: July 28, 2017

12.9K

Related Experiment Videos

Last Updated: Jun 14, 2025

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis
08:36

Development of Targeting Induced Local Lesions IN Genomes TILLING Populations in Small Grain Crops by Ethyl Methanesulfonate Mutagenesis

Published on: July 16, 2019

11.6K
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

9.7K
Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing
12:33

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Published on: July 28, 2017

12.9K

Area of Science:

  • Plant genomics and bioinformatics
  • Wheat genetics and breeding
  • Proteomics and gene annotation

Background:

  • The International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.1 reference genome is crucial for wheat genetic research.
  • Protein-level evidence from proteomics is essential for accurate gene model annotation and proteogenomics.
  • Mapping identified peptides to the genome physically validates gene models and aids in discovering new ones.

Purpose of the Study:

  • To map publicly available wheat proteomics datasets to the IWGSC RefSeq v2.1 genome.
  • To validate existing wheat High Confidence (HC) and Low Confidence (LC) gene models using proteomic data.
  • To identify novel gene candidates and provide a comprehensive proteogenomic resource for the wheat community.

Main Methods:

  • Utilized the Basic Local Alignment Search Tool (tBLASTn) algorithm to align 861,759 unique wheat peptides against the IWGSC RefSeq v2.1 reference genome.
  • Analyzed alignment results to identify validated HC gene models, potential HC gene models from LC status, and orphan peptides for new gene discovery.
  • Developed and shared a Galaxy workflow and Python code for reproducible proteogenomic analysis.

Main Results:

  • Successfully mapped 92,719 peptide hits, with 83,015 unique peptides validating 31.4% of all wheat HC gene models.
  • Mapped 6685 unique peptides to 3702 LC gene models, suggesting their potential reclassification to HC status.
  • Identified 2934 orphan peptides, including examples on chromosome 4D, indicating potential for novel gene discovery.
  • Demonstrated limitations of tBLASTn in mapping peptides with mid-sequence frame shifts.

Conclusions:

  • The study provides significant proteomic evidence validating a substantial portion of wheat gene models and highlights potential candidates for reclassification.
  • The identified orphan peptides represent valuable resources for discovering novel wheat genes.
  • The shared workflow and data empower the wheat research community to expand proteogenomic resources and investigate gene expression under diverse environmental stresses.