Repository logo
  • Log In
    New user? Click here to register.Have you forgotten your password?
University College Dublin
    Colleges & Schools
    Statistics
    All of DSpace
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. UCD Electronic Theses
  3. College of Science
  4. Biology and Environmental Science Theses
  5. Exploring Genomic and Phenotypic Variability in Hemp (Cannabis sativa)
 
  • Details
Options

Exploring Genomic and Phenotypic Variability in Hemp (Cannabis sativa)

Author(s)
Trubanová, Nina  
Uri
http://hdl.handle.net/10197/31666
Date Issued
2025
Date Available
2026-03-10T14:45:12Z
Abstract
Cannabis sativa L. is a highly diverse species of substantial economic importance, exhibiting high variability in agronomically important traits. While high diversity provides a valuable resource for breeding programs and enhances adaptability to various environments, greater uniformity is often preferred for commercial applications. However, the genetic basis of phenotypic variability remains understudied. This thesis explores the genetic and phenotypic variability in C. sativa utilising diverse approaches and methodologies, aiming to advance breeding efforts and support the development of sustainable production systems. Phenotypic and genomic characterisation of ten hemp cultivars and landraces revealed high intervarietal as well as intravarietal variability in traits such as flowering time, plant height, and biomass yield. Genomic analysis identified pervasive genetic differences among cultivars, while clustering analysis demonstrated genetic similarities within cultivars, aligning with their known breeding histories. The intravarietal variability of C. sativa was further explored utilising a population originating from a self-pollinated plant. Correlation analysis highlighted relationships among key traits, including plant height, flowering time, and biomass yield. A novel genome-specific association study identified markers and haplotypes significantly associated with each of the agronomically important traits such as flowering time and biomass yield. Finally, the MADS-box genes, a family of transcription factors known to play a crucial role in plant development and stress responses, was analysed in different C. sativa genomes. Phylogenetic analysis confirmed the presence of all MADS-box gene subfamilies present in other plant species as well as lineage-specific gene duplications and a unique SEPALLATA-like gene subfamily compared to other plant species, providing insights into the genetic mechanisms underlying phenotypic variability. This research underscores the high genetic and phenotypic variability within C. sativa and provides innovative methodologies for studying complex traits.The findings enhance our understanding of the diversity of C. sativa and highlight the potential for genetic improvement through breeding and genetic engineering, as well as the need for conservation of this diversity. These insights contribute to fundamental plant biology and have practical implications for breeding programs, with potential applications to other highly heterozygous species.
Type of Material
Doctoral Thesis
Qualification Name
Doctor of Philosophy (Ph.D.)
Publisher
University College Dublin. School of Biology and Environmental Science
Copyright (Published Version)
2025 the Author
Subjects

Cannabis sativa

Variability

Traits

Transcription factors...

Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
Loading...
Thumbnail Image
Name

Trubanová2025.pdf

Size

17.55 MB

Format

Adobe PDF

Checksum (MD5)

daa82204a70d5b8ef576db2e5ce8b0d0

Owning collection
Biology and Environmental Science Theses

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

For all queries please contact research.repository@ucd.ie.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement