Projects per year
Abstract
Pangenomes aim to represent the complete repertoire of the genome diversity present within a species or cohort of species, capturing the genomic structural variance between individuals. This genomic information coupled with phenotypic data can be applied to identify genes and alleles involved with abiotic stress tolerance, disease resistance, and other desirable traits. The characteri-sation of novel structural variants from pangenomes can support genome editing approaches such as Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR associated protein Cas (CRISPR-Cas), providing functional information on gene sequences and new target sites in variant-specific genes with increased efficiency. This review discusses the application of pangenomes in genome editing and crop improvement, focusing on the potential of pangenomes to accurately identify target genes for CRISPR-Cas editing of plant genomes while avoiding adverse off-target effects. We consider the limitations of applying CRISPR-Cas editing with pangenome references and potential solutions to overcome these limitations.
Original language | English |
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Article number | 2276 |
Journal | International Journal of Molecular Sciences |
Volume | 23 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1 Feb 2022 |
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Dive into the research topics of 'Expanding Gene-Editing Potential in Crop Improvement with Pangenomes'. Together they form a unique fingerprint.Projects
- 3 Finished
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Understanding disease resistance gene evolution across the Brassicaceae
Batley, J. (Investigator 01) & Edwards, D. (Investigator 02)
ARC Australian Research Council
1/06/21 → 30/06/24
Project: Research
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The Life and Death Of Plant Genes
Bayer, P. (Chief Investigator)
ARC Australian Research Council
1/01/21 → 31/12/23
Project: Research
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Who’s who in the plant gene world?
Edwards, D. (Investigator 01) & Batley, J. (Investigator 02)
ARC Australian Research Council
1/01/20 → 31/12/24
Project: Research
Research output
- 18 Citations
- 3 Doctoral Thesis
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Application of deep learning to leverage high-throughput phenotyping for crop breeding
Furaste Danilevicz, M., 2023, (Unpublished)Research output: Thesis › Doctoral Thesis
File75 Downloads (Pure) -
Using representative gene sets to validate gene models in legume annotations (Fabaceae)
Tay Fernandez, C., 2023, (Unpublished)Research output: Thesis › Doctoral Thesis
File354 Downloads (Pure) -
Local haplotyping software development and integrated bioinformatics analysis uncovering impacts of domestication on legume genomes
Marsh, J., 2022, (Unpublished)Research output: Thesis › Doctoral Thesis
File412 Downloads (Pure)