Final Activity Report Summary - ASGEN (Identification of genes linked to gum quality in the gum producing gum arabic tree - Acacia senegal (L.) Willd. using the association genetics approach)
The gum arabic tree, scientifically known as acacia senegal, is native to the sub-Saharan region of Africa and also occurs in the Arabian peninsula and Indian sub-continents. Gum arabic is a valuable tree product which is internationally traded. It is a natural emulsifier and stabiliser, making it a versatile additive in processed food and drinks, pharmaceutical, cosmetic and lithographic products.
Given this economic potential and the prospect of acacia senegal to provide a new, valuable, income source to people in arid and semi-arid sub-Saharan Africa, there is considerable interest in developing improved planting material to produce more yield and better quality gum. Therefore, the scientific objective of this project was to investigate the potential of association genetics to identify markers or genes that were linked to gum quality and productivity and to create a framework for applying these tools, including creation of a sample archive and generation of new non-coding and gene-based datasets.
During the project, more than 1 500 deoxyribonucleic acid (DNA) samples were successfully extracted from individual trees in planted trials, natural populations and herbarium collections originating from Kenya, Mali, Mauritania, Senegal, Somalia, Ethiopia, Cameroon, Niger, Burkina Faso, Sudan, Tanzania, Chad, South Africa, Zimbabwe, Oman, Pakistan and India. The DNA samples were securely stored at -20 °C and were anticipated to be an important resource for future species development. Phenotyping was done by analysing gum samples from the same trees using near infra-red spectroscopy (NIRS). Calibrations of the NIRS results showed high precision of specific rotation, which was a key parameter for gum quality. There also was a high phenotypic variation in gum quality, measured as specific rotation, both within and among populations. The high precision on specific rotation implied that gum quality could now be directly determined in a large number of samples by NIRS, a high throughput system.
Moreover, genotyping of individual trees was undertaken on the entire DNA sample databank using a number of nuclear and chloroplast markers, such as cpSSR, trnH-psbA, ITS, SSR and SNPs. In both chloroplast and nuclear datasets high levels of genetic diversity were found within and among populations, while genetic differentiation among populations was low, indicating a history of extensive gene flow across the natural distribution range. These results provided the baseline dataset for the development of a framework for association genetics for gum yield and quality traits that would be deployed in improvement programmes for acacia senegal.
In addition, a structured programme of formal and informal training activities and objectives that were identified for the candidate was implemented. They included both in-house, i.e. hands-on, and residential training and encompassed technical and further personal and professional development in key skills.
Given this economic potential and the prospect of acacia senegal to provide a new, valuable, income source to people in arid and semi-arid sub-Saharan Africa, there is considerable interest in developing improved planting material to produce more yield and better quality gum. Therefore, the scientific objective of this project was to investigate the potential of association genetics to identify markers or genes that were linked to gum quality and productivity and to create a framework for applying these tools, including creation of a sample archive and generation of new non-coding and gene-based datasets.
During the project, more than 1 500 deoxyribonucleic acid (DNA) samples were successfully extracted from individual trees in planted trials, natural populations and herbarium collections originating from Kenya, Mali, Mauritania, Senegal, Somalia, Ethiopia, Cameroon, Niger, Burkina Faso, Sudan, Tanzania, Chad, South Africa, Zimbabwe, Oman, Pakistan and India. The DNA samples were securely stored at -20 °C and were anticipated to be an important resource for future species development. Phenotyping was done by analysing gum samples from the same trees using near infra-red spectroscopy (NIRS). Calibrations of the NIRS results showed high precision of specific rotation, which was a key parameter for gum quality. There also was a high phenotypic variation in gum quality, measured as specific rotation, both within and among populations. The high precision on specific rotation implied that gum quality could now be directly determined in a large number of samples by NIRS, a high throughput system.
Moreover, genotyping of individual trees was undertaken on the entire DNA sample databank using a number of nuclear and chloroplast markers, such as cpSSR, trnH-psbA, ITS, SSR and SNPs. In both chloroplast and nuclear datasets high levels of genetic diversity were found within and among populations, while genetic differentiation among populations was low, indicating a history of extensive gene flow across the natural distribution range. These results provided the baseline dataset for the development of a framework for association genetics for gum yield and quality traits that would be deployed in improvement programmes for acacia senegal.
In addition, a structured programme of formal and informal training activities and objectives that were identified for the candidate was implemented. They included both in-house, i.e. hands-on, and residential training and encompassed technical and further personal and professional development in key skills.