GplusE: Genomic selection and Environment modelling for next generation wheat breeding
Lead Research Organisation:
University of Edinburgh
Department Name: The Roslin Institute
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
This proposal will develop and evaluate strategies for next generation wheat breeding based on the use of Genomic and Phenomic data, which can now be recorded in large quantities cheaply. It will bring "Big Data" to wheat breeding. Genomic selection (GS) could revolutionize wheat breeding: cycle times could be shortened; accuracy and intensity of selection maintained or increased; and more widespread selection for hard to measure traits could be undertaken. The key advantage of GS in comparison to traditional breeding is the ability to use high-dimension genetic marker information to make accurate predictions of genetic value for selection candidates without having to wait for phenotypes to be collected.
Analogous to GS, Phenomics uses instruments to record high dimensional phenotypic (e.g. spectral images) and environmental (e.g. soil electro-magnetic imaging) data. These may be determinants or indicators of complex trait phenotypes such as yield. More accurate modelling of environment and phenotype could enable faster genetic improvement in wheat, or increased efficiency of assessment in any field trial. Phenomics is highly valuable for wheat breeding. This project will scale that value to field level, enabling it to drive genetic improvement.
This project will use a large field trial combined with simulation to study the key factors in the application of GS to wheat breeding: training population design and genotyping strategy. It will integrate GS with Phenomics so that they empower each other.
Analogous to GS, Phenomics uses instruments to record high dimensional phenotypic (e.g. spectral images) and environmental (e.g. soil electro-magnetic imaging) data. These may be determinants or indicators of complex trait phenotypes such as yield. More accurate modelling of environment and phenotype could enable faster genetic improvement in wheat, or increased efficiency of assessment in any field trial. Phenomics is highly valuable for wheat breeding. This project will scale that value to field level, enabling it to drive genetic improvement.
This project will use a large field trial combined with simulation to study the key factors in the application of GS to wheat breeding: training population design and genotyping strategy. It will integrate GS with Phenomics so that they empower each other.
Planned Impact
Genomic selection and Environment modelling for next generation wheat breeding (GplusE) links Phenomics and Genomics to deliver to the wheat breeding community a platform to greatly increase the rate of progress possible through breeding. Wheat is the UK's major crop and has the 3rd largest production of any cereal globally. This project has the potential to benefit individuals and organisations worldwide for whom improvement in wheat yields is important. This ranges from farmers in the developing world, through millers and bakers, to anyone buying bread in their local supermarket. The impact of the methods we develop will be seen first by the UK wheat breeders involved in this project, with delivery of improved varieties to market in the following few years.
More specifically:
The commercial breeding partners will benefit immediately by:
1. Initiation of propriety training populations of direct relevance to their breeding programs;
2. Protocols for cost reduction of genotyping by use of imputation and of phenotyping by remote capture of covariates;
3. Access to data generated in the project and to source code for programs required to implement GplusE.
Other breeders will benefit by publication of protocols for the application of GplusE within their own breeding programmes, including access to compiled versions of software developed within the project. This will be available following their publication.
Agronomists and field crop researchers will benefit from exemplars of the use of Phenomics and precision agriculture to improve the accuracy of treatment comparisons in field trials, for example in trials comparing agronomic inputs.
Suppliers of precision agriculture services and genotypes will benefit from new market opportunities in supplying services to field trials operators, including breeders.
The academic crop research community will benefit from improved techniques for field trials and demonstration of how novel physiological and other traits could be incorporated into breeding programmes within a quantitative genetics framework.
Longer term (>8 years) the linking of Phenomics and Genomics may result in development of varieties more adapted to specific environment conditions allowing, for example, automated switching of varieties during drilling to match micro-environmental conditions. This benefits the farmer in improving yield and the environment by reducing inputs currently required to compensate for variety weaknesses.
NIAB / RI will benefit from exposure to complementary expertise in each other's institutes. For NIAB this will result in improved application of big-data methods to their research interests in agricultural science and genetics. For RI, it will open opportunities for broader application of its quantitative genetics research and future funding and collaboration with both private and public sector crop and plant science communities.
The PDRAs funded by this project will benefit from contact with each other and with staff outside their host institutes. They will gain knowledge and expertise beyond the confines of their project areas.
This project will genotype, phenotype and analyse 3,000 lines. The size of the project and the disciplines involved, encompassing quantitative genetics, molecular genetics, plant physiology, Phenomics and agronomy will provide opportunities for training of scientific and technical staff in these fields. The research will also generate opportunities for field visits and workshops to stakeholders from outside RI and NIAB. NIAB Innovation Farm showcases innovation in agriculture, provides free support and assistance for small to medium businesses in the East of England and hosts national and international workshops. This infrastructure will be used to inform a wider public and scientific community.
More specifically:
The commercial breeding partners will benefit immediately by:
1. Initiation of propriety training populations of direct relevance to their breeding programs;
2. Protocols for cost reduction of genotyping by use of imputation and of phenotyping by remote capture of covariates;
3. Access to data generated in the project and to source code for programs required to implement GplusE.
Other breeders will benefit by publication of protocols for the application of GplusE within their own breeding programmes, including access to compiled versions of software developed within the project. This will be available following their publication.
Agronomists and field crop researchers will benefit from exemplars of the use of Phenomics and precision agriculture to improve the accuracy of treatment comparisons in field trials, for example in trials comparing agronomic inputs.
Suppliers of precision agriculture services and genotypes will benefit from new market opportunities in supplying services to field trials operators, including breeders.
The academic crop research community will benefit from improved techniques for field trials and demonstration of how novel physiological and other traits could be incorporated into breeding programmes within a quantitative genetics framework.
Longer term (>8 years) the linking of Phenomics and Genomics may result in development of varieties more adapted to specific environment conditions allowing, for example, automated switching of varieties during drilling to match micro-environmental conditions. This benefits the farmer in improving yield and the environment by reducing inputs currently required to compensate for variety weaknesses.
NIAB / RI will benefit from exposure to complementary expertise in each other's institutes. For NIAB this will result in improved application of big-data methods to their research interests in agricultural science and genetics. For RI, it will open opportunities for broader application of its quantitative genetics research and future funding and collaboration with both private and public sector crop and plant science communities.
The PDRAs funded by this project will benefit from contact with each other and with staff outside their host institutes. They will gain knowledge and expertise beyond the confines of their project areas.
This project will genotype, phenotype and analyse 3,000 lines. The size of the project and the disciplines involved, encompassing quantitative genetics, molecular genetics, plant physiology, Phenomics and agronomy will provide opportunities for training of scientific and technical staff in these fields. The research will also generate opportunities for field visits and workshops to stakeholders from outside RI and NIAB. NIAB Innovation Farm showcases innovation in agriculture, provides free support and assistance for small to medium businesses in the East of England and hosts national and international workshops. This infrastructure will be used to inform a wider public and scientific community.
People |
ORCID iD |
John Woolliams (Principal Investigator) | |
John Hickey (Co-Investigator) |
Publications
Antolín R
(2017)
A hybrid method for the imputation of genomic data in livestock populations.
in Genetics, selection, evolution : GSE
Aono AH
(2022)
A joint learning approach for genomic prediction in polyploid grasses.
in Scientific reports
Title | Genetic variation in recombination rate in the pig |
Description | Poster 2221A, Genetic variation in recombination rate in the pig, at TAGC 2020 Online (pdf format). |
Type Of Art | Film/Video/Animation |
Year Produced | 2020 |
URL | https://tagc2020.figshare.com/articles/Genetic_variation_in_recombination_rate_in_the_pig/12143580/1 |
Title | Genetic variation in recombination rate in the pig |
Description | Poster 2221A, Genetic variation in recombination rate in the pig, at TAGC 2020 Online (pdf format). |
Type Of Art | Film/Video/Animation |
Year Produced | 2020 |
URL | https://tagc2020.figshare.com/articles/Genetic_variation_in_recombination_rate_in_the_pig/12143580 |
Description | 1. We have developed novel strategies for the utilisation of genomic selection in pre-breeding programs in crops (Gorjanc et al., 2015) and within crop breeding programs themselves (Gaynor et al., accepted), for the efficient generation of genomic data in crops (Hickey et al., 2015; Gorjanc et al., 2017; Gorjanc et al (accepted)) and for the design of genomic selection training sets in crops (Hickey et al., 2014). 2. The principles that we had previously established on the effective design of genomic selection training sets apply to crops. 3. The simulations of our strategy for the utilisation of genomic selection in crop breeding programs show that if it was used crop breeding programs could increase the rate of genetic gain three fold. 4. We have been able to extend our simulation program AlphaSim (for simulating sequence, genotypic, phenotypic, and pedigree data) to a range of crop scenarios, adding several new features that apply to crops, allowing breeding programs to be simulated rapidly performing sensitivity analyses on key parameters of interest. We have used it to assess genotyping strategies in crop breeding programs (Gorjanc et al 2016). Given the potential of AlphaSim, and its increased use by the academic community, and we have recently developed a Graphical User Interface (AlphaSim GUI) that will make the use of AlphaSim much more accessible to a wide range of users. |
Exploitation Route | The first steps are already in place building on the industrial partnership award. We are aware that this technology also has interest, ultimately, for pharmaceutical companies and other industrial biotechnology companies. |
Sectors | Agriculture Food and Drink Manufacturing including Industrial Biotechology |
Description | They have contributed to changing the approach to plant breeding, accelearting change and introducing new genomic technology into the modus operandi of plant breeding companies. The results from this project have been tested and implemented in major plant breeding programmes. |
First Year Of Impact | 2020 |
Sector | Agriculture, Food and Drink,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology |
Impact Types | Societal Economic |
Description | Enabling and optimising utilisation of potato gene-bank resources |
Amount | £1,000 (GBP) |
Funding ID | WT iTPA PIII-012 (209710/Z/17/Z) |
Organisation | Wellcome Trust |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 01/2020 |
End | 01/2020 |
Description | GenoForage: Genomic breeding of forages |
Amount | £294,000 (GBP) |
Organisation | Lantmännen |
Sector | Academic/University |
Country | Sweden |
Start | 03/2022 |
End | 03/2024 |
Description | Lunbanga, Nelson - Train@ED Fellowship |
Amount | £72,690 (GBP) |
Funding ID | 801215 |
Organisation | European Commission H2020 |
Sector | Public |
Country | Belgium |
Start | 04/2020 |
End | 04/2023 |
Description | Newton Fund Workshop Brazil |
Amount | £52,000 (GBP) |
Funding ID | 228949780 |
Organisation | British Council |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2016 |
End | 09/2016 |
Description | Newton Fund Workshop Mexico |
Amount | £37,550 (GBP) |
Funding ID | 2016-RLWK7-10399 |
Organisation | British Council |
Sector | Charity/Non Profit |
Country | United Kingdom |
Start | 03/2017 |
End | 03/2018 |
Description | Next generation Sitka spruce breeding informed by predictive and comparative genomics |
Amount | £175,351 (GBP) |
Funding ID | BB/P018653/1 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 09/2017 |
End | 09/2022 |
Description | Oliveira, Thiago - Train@ED Fellowship |
Amount | £72,690 (GBP) |
Funding ID | 80215 |
Organisation | Marie Sklodowska-Curie Actions |
Sector | Charity/Non Profit |
Country | Global |
Start | 05/2020 |
End | 05/2023 |
Description | Oliveira, Thiago - Train@ED Fellowship |
Amount | £72,690 (GBP) |
Funding ID | 801215 |
Organisation | European Commission H2020 |
Sector | Public |
Country | Belgium |
Start | 04/2020 |
End | 04/2023 |
Description | On-line course on in-silico modelling of breeding programmes (DataLab) |
Amount | £105,000 (GBP) |
Organisation | The Datalab |
Sector | Charity/Non Profit |
Start | 01/2020 |
End | 03/2021 |
Description | Optimising selection and maintenance of diversity in plant breeding |
Amount | £18,045 (GBP) |
Funding ID | BBSRC IAA PIII-036 (main award R45393) |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 06/2019 |
End | 11/2019 |
Description | Quantifying the drivers of genetic change in plant breeding (with Limagrain via TRAIN@Ed: Horizon 2020 Marie Sklodowska-Curie Action COFUND) |
Amount | £205,000 (GBP) |
Organisation | University of Edinburgh |
Sector | Academic/University |
Country | United Kingdom |
Start | 08/2020 |
End | 09/2023 |
Description | Temporal and genomic analysis of non-additive genetic variance |
Amount | £20,676 (GBP) |
Funding ID | BBSRC IAA PIII086 |
Organisation | Biotechnology and Biological Sciences Research Council (BBSRC) |
Sector | Public |
Country | United Kingdom |
Start | 07/2021 |
End | 11/2021 |
Title | Additional file 2 of Genetic variation in recombination rate in the pig |
Description | Additional file 2: Table S1. Male map of the landscape of pig recombination rate in 1-Mb windows |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Genetic_variation_in_recom... |
Title | Additional file 2 of Genetic variation in recombination rate in the pig |
Description | Additional file 2: Table S1. Male map of the landscape of pig recombination rate in 1-Mb windows |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Genetic_variation_in_recom... |
Title | Additional file 3 of Genetic variation in recombination rate in the pig |
Description | Additional file 3: Table S2. Female map of the landscape of pig recombination rate in 1-Mb windows. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Genetic_variation_in_recom... |
Title | Additional file 3 of Genetic variation in recombination rate in the pig |
Description | Additional file 3: Table S2. Female map of the landscape of pig recombination rate in 1-Mb windows. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Genetic_variation_in_recom... |
Title | Additional file 4 of Genetic variation in recombination rate in the pig |
Description | Additional file 4: Table S3. Sex-averaged map of the landscape of pig recombination rate in 1-Mb windows. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_Genetic_variation_in_recom... |
Title | Additional file 4 of Genetic variation in recombination rate in the pig |
Description | Additional file 4: Table S3. Sex-averaged map of the landscape of pig recombination rate in 1-Mb windows. |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_4_of_Genetic_variation_in_recom... |
Title | MOESM1 of The potential of shifting recombination hotspots to increase genetic gain in livestock breeding |
Description | Additional file 1: Table S1. Mean and variance of 10 replicates across all scenarios.This file presents the data used for plotting the mean and variance across each replicate for each scenario for the 80 generations of selection. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/MOESM1_of_The_potential_of_shifting_recombinati... |
Title | MOESM1 of The potential of shifting recombination hotspots to increase genetic gain in livestock breeding |
Description | Additional file 1: Table S1. Mean and variance of 10 replicates across all scenarios.This file presents the data used for plotting the mean and variance across each replicate for each scenario for the 80 generations of selection. |
Type Of Material | Database/Collection of data |
Year Produced | 2017 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/MOESM1_of_The_potential_of_shifting_recombinati... |
Description | Flexible optimal contribution selection with KWS |
Organisation | KWS Group |
Country | Germany |
Sector | Private |
PI Contribution | Developing flexible extensions to the optimal contribution selection method and software implementation |
Collaborator Contribution | Supplying data and species knowledge |
Impact | Still active |
Start Year | 2019 |
Description | GplusE consortium |
Organisation | Elsoms Seeds |
Country | United Kingdom |
Sector | Private |
PI Contribution | Execution of field trials Collecting phenotype data Creating and processing of genotype data Data analysis |
Collaborator Contribution | Created test crosses Supplied seeds |
Impact | Journal publications (partially still in preparation) Genotype data sets Phenomics data sets |
Start Year | 2015 |
Description | GplusE consortium |
Organisation | KWS UK |
Country | United Kingdom |
Sector | Private |
PI Contribution | Execution of field trials Collecting phenotype data Creating and processing of genotype data Data analysis |
Collaborator Contribution | Created test crosses Supplied seeds |
Impact | Journal publications (partially still in preparation) Genotype data sets Phenomics data sets |
Start Year | 2015 |
Description | GplusE consortium |
Organisation | Limagrain |
Country | France |
Sector | Private |
PI Contribution | Execution of field trials Collecting phenotype data Creating and processing of genotype data Data analysis |
Collaborator Contribution | Created test crosses Supplied seeds |
Impact | Journal publications (partially still in preparation) Genotype data sets Phenomics data sets |
Start Year | 2015 |
Description | GplusE consortium |
Organisation | RAGT Seeds |
Country | United Kingdom |
Sector | Private |
PI Contribution | Execution of field trials Collecting phenotype data Creating and processing of genotype data Data analysis |
Collaborator Contribution | Created test crosses Supplied seeds |
Impact | Journal publications (partially still in preparation) Genotype data sets Phenomics data sets |
Start Year | 2015 |
Title | AlphaPlantImpute |
Description | AlphaPlantImpute is a software package designed for phasing and imputing genotype data in plant breeding populations. AlphaPlantImpute can be implemented within and across bi-parental populations to phase and impute focal individuals genotyped at low-density to high-density. |
Type Of Technology | Software |
Year Produced | 2018 |
Impact | This package was found to be extremely useful by our project partner global breeder KWS Saat SE. |
URL | https://alphagenes.roslin.ed.ac.uk/wp/software/alphaplantimpute/ |
Title | AlphaSim |
Description | One of the fundamental questions in populations dynamic is assessing how changes in the current structure and environment affect the structure composition in both the short and long-term. Plant and animal breeding programs benefits from having a tool to evaluate the potential of different selection strategies or new emerging technologies to improve population performance. Empirical datasets to assess the effect of different factors on one population are difficult to collect, since they require substantial financial and time investments and are subject to noise and error. Simulation is a key tool for both researchers and breeders to assess the impact of different factors given a known historical and current population structure prior to implementation within a real-life setting. AlphaSim is a fast and flexible software tool that enables researchers and breeders to do this. Unlike other simulation tools, AlphaSim has the functionality to manipulate fine details of the population structure in order to simulate realistic scenarios and provides detailed outputs for use in downstream analyses. |
Type Of Technology | Software |
Year Produced | 2016 |
Impact | AlphaSim is a freely available software package that simulates genetic population and can assess breeding programs. The AlphaSim package includes a manual, tutorial, and access to technical support with the aim of benefiting the academic research community in animal breeding. This software package has already attracted users from a number of different academic institutions and has supported a number of peer-reviewed academic publications. These publications include: Potential of gene drives with genome editing to increase genetic gain in livestock breeding programs. 2017. Gonen, S, J. Jenko, G. Gorjanc, A.J. Mileham, C.B.A. Whitelaw, J.M. Hickey. Genetics Selection Evolution, 49:3. AlphaSim: Software for Breeding Program Simulation. 2016. Faux A. M., G. Gorjanc, R. C. Gaynor , M. Battagin, S. M. Edwards, D. L. Wilson, Sarah J. Hearne, S. Gonen, and J. M. Hickey. The Plant Genome vol. 9, no.3. AlphaSim is not only used in academic research, but has also attracted industrial collaborations. One such example is our recently awarded Innovate UK grant in collaboration with Driscoll's. |
URL | http://www.alphagenes.roslin.ed.ac.uk/alphasuite-softwares/alphasim/ |
Title | AlphaSimR: An R-package for Breeding Program Simulations |
Description | AlphaSimR is an R package for stochastic simulations of plant and animal breeding programs. AlphaSimR is a highly flexible software package able to simulate a wide range of plant and animal breeding programs for diploid and autopolyploid species. AlphaSimR is ideal for testing the overall strategy and detailed design of breeding programs. AlphaSimR utilizes a scripting approach to building simulations that is particularly well suited for modeling highly complex breeding programs, such as commercial breeding programs. The primary benefit of this scripting approach is that it frees users from preset breeding program designs and allows them to model nearly any breeding program design. |
Type Of Technology | Software |
Year Produced | 2017 |
Open Source License? | Yes |
Impact | AlphaSimR has been used widely by researchers and practitioners in breeding and genetics, most notably it drives and supports development of genomic and quantitative genetic methods and tools at Roslin, optimisation of world-leading breeding programmes, such as Genus, PIC, Bayer CropScience, KWS, Limagrain, BASF, Beta Bugs, and CGIAR Excellence in Breeding platform. |
URL | https://github.com/AlphaGenes/AlphaSimR |
Title | AlphaSuite of software for data science, genetics, and breeding |
Description | AlphaSuite of software for data science, genetics, and breeding available from https://github.com/AlphaGenes The major tools include: * AlphaSimR for simulation of breeding programmes https://github.com/AlphaGenes/AlphaSimR * AlphaBayes for estimation of SNP effects on phenotype https://github.com/AlphaGenes/AlphaBayes * AlphaAssign for finding progeny-parent (pedigree) relationships https://github.com/AlphaGenes/AlphaAssign * AlphaPhase for phasing and imputation of SNP array genotype data https://github.com/AlphaGenes/AlphaPhase * AlphaImpute for phasing and imputation of SNP array genotype data https://github.com/AlphaGenes/AlphaImpute * AlphaImpute2 for phasing and imputation of SNP array genotype data (version 2) https://github.com/AlphaGenes/AlphaImpute2 * AlphaPeel for genotype calling, phasing, and imputation in pedigreed populations https://github.com/AlphaGenes/AlphaPeel * AlphaFamImpute for genotype calling, phasing, and imputation in families https://github.com/AlphaGenes/AlphaFamImpute * AlphaPlantImpute for phasing and imputation in plant populations (version 2) https://github.com/AlphaGenes/AlphaPlantImpute * AlphaPlantImpute2 for phasing and imputation in plant populations (version 2) https://github.com/AlphaGenes/AlphaPlantImpute2 * AlphaMate for balancing selection and management of genetic diversity in breeding programmes https://github.com/AlphaGenes/AlphaMate * AlphaPart for analysing trend in genetic means and variances https://github.com/AlphaGenes/AlphaPart |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | AlphaSuite is used by leading public and private animal and plant breeding programmes that supply genetics worldwide in the Global North and Global South. |
URL | https://github.com/AlphaGenes |
Description | "A multipart breeding strategy for introgression of exotic germplasm in elite breeding programs using genomic selection" at 6th Conference on Cereal Biotechnology and Breeding: EUCARPIA |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation on "A multipart breeding strategy for introgression of exotic germplasm in elite breeding programs using genomic selection" at 6th Conference on Cereal Biotechnology and Breeding: EUCARPIA 3-5 Nov 2021 On-line |
Year(s) Of Engagement Activity | 2021 |
URL | https://akcongress.com/cbb/ |
Description | AlphaGenes Twitter channel |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The AlphaGenes updates the scientific community and a broader audience about news around our research group, scientific output and engagement activities |
Year(s) Of Engagement Activity | 2012,2013,2014,2015,2016,2017,2018,2019,2020 |
URL | https://twitter.com/Alpha_Genes |
Description | AlphaGenes website |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The AlphaGenes website informs the scientific community about the groups research activities, outputs, courses and available software tools. |
Year(s) Of Engagement Activity | 2017,2018,2019,2020 |
URL | https://alphagenes.roslin.ed.ac.uk |
Description | Big Data in Agriculture, Part of the DuPont Pioneer Plant Sciences Symposia Series, at Roslin Institute, 14-15 May 2018 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Symposium held at the Roslin institute, organised by members of my group, sponsored by third parties from the breeding industry |
Year(s) Of Engagement Activity | 2018 |
Description | Co-organized workshop "Simulation of Genetic and Genomic Systems" at Plant and Animal Genome xxviii conference |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | This workshop was held for the first time in the worlds most important Ag-Genomics meeting. It made academic and industry scientists aware of the power of simulation as a important emerging research discipline in this area. |
Year(s) Of Engagement Activity | 2020 |
URL | https://www.intlpag.org/2020/ |
Description | Course on The Next Generation Breeding (Iowa State University) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | We organised a course on The Next Generation Breeding at The Iowa State University in Ames in May 2018 to present and teach about our research, principles of the developed methods and application of our software with real data. The course was very well received with plenty of discussions involving both academia, research and industry participants. It also initiated a series of offline research and application discussions. |
Year(s) Of Engagement Activity | 2018 |
Description | Course on The Next Generation Breeding (KWS group) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | We organised an internal course on The Next Generation Breeding at The KWS group in Germany in Einbeck in March 2019 to present and teach about our research, principles of the developed methods and application of our software with real data. The course was very well received with plenty of discussions involving both academia, research and industry participants. It also initiated a series of offline research and application discussions. |
Year(s) Of Engagement Activity | 2019 |
Description | Course on The Next Generation Breeding (University of Zagreb) |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | We organised a course on The Next Generation Breeding at The University Of Zagreb (Croatia) in July 2018 to present and teach about our research, principles of the developed methods and application of our software with real data. The course was very well received with plenty of discussions involving both academia, research and industry participants. It also initiated a series of offline research and application discussions. |
Year(s) Of Engagement Activity | 2018 |
Description | Data-Driven Breeding and Genetics course (2 weeks) on-line |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The principles of animal and plant breeding are increasingly coalescing due to advances in technology and increasing demands and opportunities for agriculture. This two-week graduate level course of integrated lectures and practicals is designed to equip students, academics, and practitioners with theoretical and applied knowledge, skills and tools to design, optimise, and deploy Data Driven Breeding and Genetics techniques for Animals and Plants. It was jointly delivered by scientists and teachers from the University of Edinburgh and colleagues from the Swedish University of Agricultural Sciences and the CGIAR's Excellence in Breeding Platform, with guest lectures from various academic and industry collaborators. Due to the pandemic the course took place in virtual format from the 20th Sep and 1st Oct 2021. The course lectures were pre-recorded to enable asynchronous worldwide delivery. Course participants engaged with the lectures and practicals at their own pace. They engaged with course instructors and other participants via Slack and daily Zoom sessions (one in the UK morning and one in the UK afternoon time). Day 1 - Introduction to breeding Welcome and Introduction (Gregor Gorjanc) Introduction to breeding programme modelling (Gregor Gorjanc) AlphaSimR MOOC - Introduction (Gregor Gorjanc) AlphaSimR MOOC - Relationship between DNA & traits (Gregor Gorjanc) R crash course on using ggplot and tidyverse (Thiago Paula Oliveira) The role of livestock in global food security (Geoff Simm) Day 2 - Breeding programme design AlphaSimR MOOC - DNA lottery (Gregor Gorjanc) AlphaSimR MOOC - Response to selection (Gregor Gorjanc) AlphaSimR MOOC - Modelling complex breeding programmes (Gregor Gorjanc) How does a major multinational animal breeding programme operate in the 21st century (Andreas Kranis) How does a major multinational plant breeding programme operate in the 21st century (Brian Gardunia) Day 3 - Genomic data in breeding Genomic data, SNP array genotyping and sequencing, and Strategies to generate genomic data in breeding programmes (Gregor Gorjanc) Phasing genomic data with heuristic and probabilistic methods (Gregor Gorjanc) Imputation of genomic data (Gregor Gorjanc) AlphaPeel practical - probabilistic genotype calling, phasing, and imputation of genomic data in pedigreed populations (Jana Obsteter) AlphaImpute2 practical - fast phasing and imputation (Jana Obsteter) AlphaFamImpute practical - genotype calling, phasing, and imputation algorithm for large full-sib families (Jana Obsteter) AlphaAssign practical - parentage assignment (Jana Obsteter) Breeding in aquaculture (Ross Houston) Tea breeding and a genomic selection outlook (Nelson Lubanga) Day 4 - Modelling phenotype data to estimate environmental effects Introduction to experimental design of field trials (Daniel Tolhurst) Introduction to linear mixed models for plant breeding (Daniel Tolhurst) Analysis of phenotype data, including data collected from i) single field trials (with spatial) and ii) field trials across multiple (Daniel Tolhurst) ASReml practicals (Daniel Tolhurst & Thiago Paula Oliveira) Overview of forest tree breeding (Jaroslav Klapste) Genomic selection provides new opportunities for intercrop breeding (Jon Bancic) Day 5 - Population and Quantitative genetics for breeding Introduction to population and quantitative genetics for breeding (Martin Johnsson) Change in frequencies with drift (Martin Johnsson) Change in frequencies with mutation, migration and selection (Martin Johnsson) Additive effects (Martin Johnsson) Non-additive effects (Martin Johnsson) Inbreeding depression and heterosis (Martin Johnsson) Practicals (Martin Johnsson) Genetic evaluation in a multinational plant breeding programs AND/OR CGIAR Excellence in Breeding platform (Eduardo Covarrubias-Pazaran) Roadmap for black soldier fly breeding (Leticia de Castro Lara) Day 6 - Quantitative genetics for breeding II Variance, covariance, correlation and heritability (Eduardo Covarrubias-Pazaran) Correlated response to selection (Eduardo Covarrubias-Pazaran) Recurrent selection strategies (Eduardo Covarrubias-Pazaran) Practicals (Eduardo Covarrubias-Pazaran) National breeding programme for the Norwegian Red dairy cattle (Janez Jenko) Breeding a man's best friend (Joanna Ilska) Day 7 - Modelling phenotype data to estimate genetic effects Genetic evaluations with focus on pedigree-based BLUP (Ivan Pocrnic) Introduction to genome-wide association studies (Ivan Pocrnic) Genomic evaluations (Ivan Pocrnic) Practicals (Ivan Pocrnic) A multipart breeding strategy for introgression of exotic germplasm in elite breeding programs using genomic selection (Irene Breider) Population genetics tools with perspective in dog research (Mateja Janes) Day 8 - Sustainable breeding Breeders' dillema Optimal contribution selection Optimal cross selection AlphaMate practical - optimising selection, management of diversity, and mate allocation in breeding programs A walk-through of three examples AlphaPart - quantifying the drivers of genetic change (Jana Obsteter & Thiago Paula Oliveira) Recursive models in animal breeding (Maria Martinez Castillero) Economic objectives in animal and plant breeding (Cheryl Quinton) Day 9 - Exploiting modern technologies in breeding programmes The role of reproductive technologies to boost animal breeding (Gabriela Mafra Fortuna & Gerson Oliveira) Breeding for disease resistance in animals (Andrea Doeschel-Wilson) Editing livestock genomes (Simon Lillico) Evaluating the use of gene drives to limit the spread of invasive populations (Nicky Faber) The potential of genome editing and gene drives for improving complex traits (Gregor Gorjanc) Day 10 - Open-ended work on topics of participants' interest |
Year(s) Of Engagement Activity | 2021 |
Description | Excellence in Breeding: Breeding Scheme Optimization Tools Training |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Breeders and Quantitative Geneticists play an important role in the seed sector as designers of manufacturing pipelines. In this workshop, the students learned to work with our breeding simulation platform AlphaSimR. The students reported back they had become aware of the power of the simulation of breeding programs, as well as the possibilities to make breeding programs more effective by using less conventional breeding schemes. |
Year(s) Of Engagement Activity | 2020 |
URL | https://excellenceinbreeding.org/module2 |
Description | HighlanderLab Twitter channel |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The HighlanderLab updates the scientific community and a broader audience about news around our research group, scientific output and engagement activities - on management and improvement of populations using data science, genetics, and breeding. |
Year(s) Of Engagement Activity | 2019,2020,2021,2022 |
URL | https://twitter.com/HighlanderLab |
Description | HighlanderLab website |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | The HighlanderLab updates the scientific community and a broader audience about news around our research group, scientific output and engagement activities - on management and improvement of populations using data science, genetics, and breeding. |
Year(s) Of Engagement Activity | 2021,2022 |
URL | http://www.ed.ac.uk/roslin/HighlanderLab |
Description | Invited talk at Plant Quantitative Genetics meeting "Genomic and temporal analysis of genetic variance" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Genomic and temporal analysis of genetic variance, UK Plant Quantitative Genetics meeting, 2019-11-07, Birmingham, UK. |
Year(s) Of Engagement Activity | 2019 |
Description | Invited talk at the Symposium in Statistics on "Modelling Genomic and Spatial Effects in Breeding" |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Modelling Genomic and Spatial Effects in Breeding, NTNU Trondheim Symposium in Statistics 2019, 2019-09-28, Trondheim, Norway. |
Year(s) Of Engagement Activity | 2019 |
Description | John Hickey Guest in Farming Today (BBC Radio 4) |
Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | On Monday 26th September, The BBC Radio 4 Farming Today had Professor John Hickey as specialist scientist on the subject of breeding programs and scientific impact. |
Year(s) Of Engagement Activity | 2016 |
URL | http://www.bbc.co.uk/programmes/b07w5xxq |
Description | Massive Online On-demand Course on Modelling breeding programmes using AlphaSimR |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Breeding programmes are key to the genetic improvement of plant varieties and animal breeds used in agriculture. This unique course shows how to model an existing or new breeding programme and the evaluation of alternative breeding scenarios.The course is free and lasts for 5 weeks. https://www.edx.org/course/breeding-programme-modelling-with-alphasimr |
Year(s) Of Engagement Activity | 2022,2023 |
URL | https://www.edx.org/course/breeding-programme-modelling-with-alphasimr |
Description | Modern plant and animal applied genomics driven by genotype and sequence data, Universitat Politècnica de Valencia, |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Visiting teaching activity with advanced course in plant and animal breeding. |
Year(s) Of Engagement Activity | 2018 |
Description | Modern plant and animal applied genomics driven by genotype and sequence data, University of Zagreb, Croatia, 17-19 July 2018 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Workshop organised and given by me and two other members of my group. |
Year(s) Of Engagement Activity | 2018 |
Description | Newton Fund workshop UK-Mexico on Genetic Improvement of Populations |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Newton Fund workshop UK-Mexico on Genetic Improvement of Populations took place in February 2018 at the Centro Nacional de Recursos Genéticos (Jalisco, Mexico). Participants (undergraduate and postgraduate students, group leaders and professionals) from UK and Mexico exchanged research results and showed applications of genetic improvement in different agricultural populations, including livestock, fish, crops, grasses and trees. I have contributed with a lecture on "Statistical methods for genetic evaluation of populations" and two talks titled "Economics of genotyping for genomic selection" and "Optimising selection, maintenance of genetic diversity and logistic constraints". The local organisers have increased interest in the presented topics. |
Year(s) Of Engagement Activity | 2018 |
Description | Organization of a Workshop on wood quality in conifer breeding, annual member's day of the Conifer Breeding Cooperative |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | 35 forestry practitioners from forest tree nurseries, forest management, wood product manufacturers, government and academia attended a full day workshop involving 1) a demonstration at Nappier University of wood testing methods, 2) 5 presentations by experts in the area of wood properties and 3) round table discussions. I. PRESENTATIONS A) Introduction. Why breed conifer trees for improved wood properties? Prof John MacKay, University of Oxford The theme of wood properties in tree breeding follows the links between wood properties, timber grading and product recovery in softwoods. Log dimensions, along with external form and defects, and internal properties such as stiffness and specific gravity determine the product type and timber strength. The breeder has a role to play in ensuring that wood properties are favourable for grading and performance of timber. Understanding the opportunities and challenges is the key to setting objectives for the long term. B)Timber properties and grading for today's market Prof Daniel Ridley-Ellis, Napier University This presentation reviewed grading principles and methods applied to softwoods. It showed that there is wide variation in grades within species grown in the UK and small to moderate shifts between species, with larch being an outlier and much higher grades. An overview of different grading approaches included mechanical and acoustic testing, and visual grading. The negative relationship between growth rate and strength was explained. Several considerations were presented pertaining to strength grading; among them, density is not an appropriate predictor of strength, and that strength grading isn't about properties of individual pieces - it's about collective properties of all pieces assigned to a grade. C)Faster growing trees and timber markets. Considerations for tree breeding. Dr Paul Mclean, Forest Research This presentation looked at faster growing trees, primarily genetically improved Sitka. Variation in wood properties depend roughly at equal levels on site effects, inter-tree differences and within tree differences. This is why understanding and optimizing wood properties is complex. British spruce grade is limited by low stiffness, which generally just matches C16 performance, whereas strength and density generally match C20 performance. Stiffness is particularly limiting in the juvenile core, which affects the major cuts of timber as the span the centre of the log (especially in smaller diameter trees). Owing to the relationship between growth rate, site limitations, and juvenile core properties, breeding should aim to improve the juvenile core as a key to obtaining fast growth whilst maintaining a desirable proportion of C16+ timber. The conclusions form this presentation were: 1) Don't ignore stiffness in the core of the tree; 2) Don't ignore the growth dynamics of productive forests; 3) Keep an eye on research; 4) Invest in research. D)Engineered wood products: an efficient use of resource Prof Robert Hairstans This presentation outlined the wide range of engineered wood products, their attractive performance attributes and their advantages including social, economic and environmental benefits. Some of the advantages of engineered wood products is that they are suitable to facilitate a more circular economy and decrease waste. They performance and design advantages mean that they are able to displace metal and concrete, while at the same time having a lower carbon footprint. At present, most of the European production capacity is located in the central Europe. Engineered wood products an attractive utilisation for British grown softwoods and have the potential change future wood uses and markets. The wood quality requirements for engineered products should be taken into account in future proofing tree breeding strategies. E)Breeding conifers for wood properties: goals, opportunities, and challenges Prof John MacKay, University of Oxford The presentation outlined the significant potential to genetically improve wood quality traits in softwood trees. This opportunity for improvement is underpinned by relatively high levels of variability within species and high levels of heritability of most wood traits. This is well established and has been shown in diverse species including spruces, pines, among others. The potential for improvement creates an opportunity for alignment of tree breeding objectives with industrial needs. The long-term vision for conifer breeding will need to integrate this opportunity and other needs, while conifer growth rates and tree form have been the main focus to date. New objectives may include increased productivity whilst maintaining wood quality, timber yield and product performance, adaptation to changing climate, resilience to pests. To facilitate the integration of several objectives, an "index selection" approach may be used to assign different weights to traits under selection. As tree breeding addresses this challenge, it will also be faced with knowledge gaps to fill, new technologies to develop and implement, and an even greater need to engage with the forestry sector. II - ROUND TABLE AND PLENARY DISCUSSIONS Four topics were explored; the discussions are summarized below 1. Conifer breeding objectives - What is the long term vision? There was a consensus that conifer breeding objectives have to align with product manufacture aiming for high value products such as timber of construction grade, that attention to product grading and performance attributes is crucial and should be emphasized. In addition, resilience to both changing climates and pests represents an increasing concern and comes with new challenges. Diversification to broaden the species portfolio and decrease the reliance on Sitka spruce is also seen as desirable but was perceived as constrained by site conditions and threats from pets. 2. What is the role of wood properties in delivery the vision? There is a relatively well-understood but complex relationship between timber grading (C16-C24), site constraints and silviculture, tree growth, and wood properties. Increasing yield is a high priority but more rapid tree growth generally increases the juvenile core and the decreases the overall grade of timber. It was agreed that breeding should seek a balance between productivity and wood properties, i.e. increase yields whilst maintaining quality. This means that selection and breeding for wood stiffness should be introduced in species like Sitka spruce. A less strongly held view was to prioritize performance over growth, i.e. aim for C24 and maintain yield, and this may be more easily achieved in other conifers that spruce. Another topic of debate was whether different varieties should be developed for different products, different sites or silviculture regimes. For example, silviculture with or without thinning will produce trees of different sizes and grade potentials. 3. What are the major knowledge gaps? The discussions identified many knowledge gaps. How much improvement may be expected in wood properties such as stiffness (Sitka) in the juvenile core? What causes frost cracks and is it under genetic control? What are the limits of tree breeding - e.g. can trees be developed that stop height growth when they reach a critical height on windy sites so as to reduce the risk of wind through? To what extent will climate warming decrease sites that are suitable for Sitka and what can be done to mitigate the impacts of dryer conditions? What is the best approach to remain competitive with C24 timber from Scandinavia and continental Europe? 4. What are the sector engagement needs? A major need for engagement is with timber processing and marketing about the quality and value of British grown timber and the benefits of tree breeding. Engagement with community and environmental groups is also crucial about the social and environmental benefits of commercial forestry. |
Year(s) Of Engagement Activity | 2019 |
Description | Public engagement at the Royal Highland Show |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Public/other audiences |
Results and Impact | All members of the research group engaged the visitors of the RHS, to show the importance of their research towards the enhancement of the agricultural sector in direct or indirect ways. |
Year(s) Of Engagement Activity | 2019 |
URL | https://www.royalhighlandshow.org |
Description | Researcher Links workshop at CNRG, INIFAP, Tepatitlán and Guadalajara, Mexico, 3-7 February 2018 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Workshop organised and given by me and the members of my group |
Year(s) Of Engagement Activity | 2018 |
Description | Roslin symposium in honour of Professor Robin Thompson |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | In June 2018 The University of Edinburgh has conferred the degree of Doctor Honoris Causa to Robin Thompson for contributions to statistics, quantitative genetics, and animal and plant breeding. To celebrate this occasion we organised a symposium at The Roslin Institute in his honour. More than 100 delegates came from Argentina, Australia, Finland, Netherlands, New Zealand, Mexico, Spain, Sweden, UK, and USA. Speakers' talks covered animal breeding, statistics in breeding, plant breeding and human genetics, which showed the breadth of impact of the work of Professor Robin Thompson. |
Year(s) Of Engagement Activity | 2018 |
Description | Teaching course: Next Generation Plant and Animal Breeding Programs, Animal Science Department, University of Nebraska, Lincoln. |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Series of the lectures and workshops on Plant and Animal Breeding Programs exploring current practices and future areas of research. The course was designed and imparted by John Hickey and key members of his team. |
Year(s) Of Engagement Activity | 2016 |
URL | http://animalscience.unl.edu/next-generation-plant-and-animal-breeding-programs |
Description | The Expert Working Group on Wheat Breeding Methods and Strategies |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Expert Working Group on Wheat Breeding Methods and Strategies seeks to exchange breeding methods research information and germ plasm to expert build capacity and support in wheat breeding programs, with more efficient breeding methods consistent with the latest scientific advances. The EWG is working on activities such us workshops, training courses, communications, and sharing of germplasm and information to reach larger pool of wheat breeders and trained in state-of-the-art breeding methods. |
Year(s) Of Engagement Activity | 2015,2016,2017 |
URL | http://www.wheatinitiative.org/activities/expert-working-groups/wheat-breeding-methods-and-strategie... |
Description | Training: Next generation plant breeding programs |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Workshop to teach professionals in the crop breeding sector to use modern bioinformatics tools to process molecular data and simulate breeding programs in order to make these more efficient. The audience was very pleased with their acquired insights and skills, and considered the training extremely useful. |
Year(s) Of Engagement Activity | 2019 |
URL | https://alphagenes.roslin.ed.ac.uk/wp/teaching-2/kwsgermany/ |