Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species

Perennial crops, such as oil palm (Elaeis guineensis Jacq.) have a long breeding cycle (typically 20 years per cycle) and inherently heterogeneous populations. Oil palm is the most productive and traded vegetable oil globally compared to other oil crops such as soybean, rapeseed etc, but it has only...

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Main Author: Ong, Ai Ling
Format: Thesis (University of Nottingham only)
Language:English
Published: 2022
Subjects:
Online Access:https://eprints.nottingham.ac.uk/66659/
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author Ong, Ai Ling
author_facet Ong, Ai Ling
author_sort Ong, Ai Ling
building Nottingham Research Data Repository
collection Online Access
description Perennial crops, such as oil palm (Elaeis guineensis Jacq.) have a long breeding cycle (typically 20 years per cycle) and inherently heterogeneous populations. Oil palm is the most productive and traded vegetable oil globally compared to other oil crops such as soybean, rapeseed etc, but it has only undergone four generations of selection since breeding started 80 years ago. No doubt genome-enabled biology in oil palm breeding is crucial yet genetics and crop improvement have been actively pursued in research but with limited deployment in the industry. Further, the oil yield has stagnated for many years, hence the realistic approach of genome-based breeding is needed. High resolution genetic map maximizes discoveries of recombination events and thus empowers comparative genomic and quantitative trait locus (QTL) studies. The present study aims to develop multiple ultra-dense linkage maps using high density marker panel and integrate these with physical genome map of oil palm. To improve the current genome assembly, more of the previously unplaced genomic scaffolds can now anchored to chromosomes using mapped markers from the genetic maps. Linkage maps generated using three populations contained 11,421 transferable markers - consolidate each and the total maps span, on average, 1,355.64 cM with the lowest average marker intervals of 0.04 cM. These are by far the densest linkage maps reported in oil palm. The creation of a consensus linkage maps from combinations of different mapping populations provides essential information about the consistency of marker order and genetic distance among oil palm populations, while increasing map precision and resolution. The published oil palm physical genome size is 657.98 Mb while the assembled scaffolds add up to 1.53 Gb. The coverage of the assembled physical genome still leaves more than 60% to be fully covered. The estimation of genome-wide recombination rates revealed varying degrees of genetic exchange across different populations and between chromosomes. The integration of the high-density linkage maps with the published oil palm genome could potentially improve the current genome for utilisation in oil palm improvement programmes. The outcome of this study has significantly improved the assembly of oil palm genome by anchoring more genome sequence scaffolds to chromosomes, resulting in 1.2 Gb equivalent to extension of 79% of the publicly available genome version. The creation of the most complete genome map within palm species here, allows comprehensive comparative genomic studies. Applications of genome information in oil palm breeding through genome-wide association study (GWAS) and genomic selection (GS) and their combinations will pave the way for crop improvement not only in oil palm but also the exploration of economically important traits within palm species generally.
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spelling nottingham-666592025-02-28T15:13:29Z https://eprints.nottingham.ac.uk/66659/ Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species Ong, Ai Ling Perennial crops, such as oil palm (Elaeis guineensis Jacq.) have a long breeding cycle (typically 20 years per cycle) and inherently heterogeneous populations. Oil palm is the most productive and traded vegetable oil globally compared to other oil crops such as soybean, rapeseed etc, but it has only undergone four generations of selection since breeding started 80 years ago. No doubt genome-enabled biology in oil palm breeding is crucial yet genetics and crop improvement have been actively pursued in research but with limited deployment in the industry. Further, the oil yield has stagnated for many years, hence the realistic approach of genome-based breeding is needed. High resolution genetic map maximizes discoveries of recombination events and thus empowers comparative genomic and quantitative trait locus (QTL) studies. The present study aims to develop multiple ultra-dense linkage maps using high density marker panel and integrate these with physical genome map of oil palm. To improve the current genome assembly, more of the previously unplaced genomic scaffolds can now anchored to chromosomes using mapped markers from the genetic maps. Linkage maps generated using three populations contained 11,421 transferable markers - consolidate each and the total maps span, on average, 1,355.64 cM with the lowest average marker intervals of 0.04 cM. These are by far the densest linkage maps reported in oil palm. The creation of a consensus linkage maps from combinations of different mapping populations provides essential information about the consistency of marker order and genetic distance among oil palm populations, while increasing map precision and resolution. The published oil palm physical genome size is 657.98 Mb while the assembled scaffolds add up to 1.53 Gb. The coverage of the assembled physical genome still leaves more than 60% to be fully covered. The estimation of genome-wide recombination rates revealed varying degrees of genetic exchange across different populations and between chromosomes. The integration of the high-density linkage maps with the published oil palm genome could potentially improve the current genome for utilisation in oil palm improvement programmes. The outcome of this study has significantly improved the assembly of oil palm genome by anchoring more genome sequence scaffolds to chromosomes, resulting in 1.2 Gb equivalent to extension of 79% of the publicly available genome version. The creation of the most complete genome map within palm species here, allows comprehensive comparative genomic studies. Applications of genome information in oil palm breeding through genome-wide association study (GWAS) and genomic selection (GS) and their combinations will pave the way for crop improvement not only in oil palm but also the exploration of economically important traits within palm species generally. 2022-02-27 Thesis (University of Nottingham only) NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/66659/1/PhD_thesis%28corrected%29_024942.pdf Ong, Ai Ling (2022) Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species. PhD thesis, University of Nottingham. oil palm linkage map physical map genome-enabled breeding
spellingShingle oil palm
linkage map
physical map
genome-enabled breeding
Ong, Ai Ling
Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title_full Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title_fullStr Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title_full_unstemmed Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title_short Integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
title_sort integration of linkage and physical genome map of oil palm for the exploration of important traits within palm species
topic oil palm
linkage map
physical map
genome-enabled breeding
url https://eprints.nottingham.ac.uk/66659/