Next generation Sitka spruce breeding informed by predictive and comparative genomics
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
The project aims to develop genomic prediction in Sitka spruce and thus create novel capacity to increase the rates of genetic gain in the UK's breeding of programme. Selective breeding is effective for increasing yields in Sitka spruce but it takes 30 years to select and propagate new varieties. Genomic prediction methods could shorten the breeding process and increase the rate of yield gains from 0.83% per year to 1.85% per year.
The proposed research will develop large-scale genotyping capacity, a genetic linkage map for Sitka spruce, a virtual genome map for the pine family and large training set for predictive genomics model development. We will use this platform to investigate three key issues relevant to prediction in forest trees: i) the accuracy of prediction as a function of training set properties; ii) model development for yield in conjunction with wood quality traits; and iii) development of genotype imputation to enable more cost efficient genotyping methods; iv) resistance traits and candidate genes as relevant to damaging weevils.
The project outputs will include a genetic diversity database and analysis platform. We will also develop statistical models that may be used by breeders to reduce the need for lengthy and costly field evaluations.
The proposed research will develop large-scale genotyping capacity, a genetic linkage map for Sitka spruce, a virtual genome map for the pine family and large training set for predictive genomics model development. We will use this platform to investigate three key issues relevant to prediction in forest trees: i) the accuracy of prediction as a function of training set properties; ii) model development for yield in conjunction with wood quality traits; and iii) development of genotype imputation to enable more cost efficient genotyping methods; iv) resistance traits and candidate genes as relevant to damaging weevils.
The project outputs will include a genetic diversity database and analysis platform. We will also develop statistical models that may be used by breeders to reduce the need for lengthy and costly field evaluations.
Planned Impact
WHO MIGHT BENEFIT? -
This project will impact tree breeding as the proposed predictive genomics methods will be direct applicable to Sitka spruce. With 6640 km2 under cultivation, the UK is the world's largest grower of Sitka spruce. Tee nurseries and growers, forestry operators and management firms, and large wood processors are the industries that profit from its production and are the expected commercial beneficiaries of the research. They are a major source of rural employment and many of them partner within the Sitka Spruce Breeding Cooperative also involving Government (Forest Research). Ireland, France, Scandinavia and North-America also grow 1000s of km2 of Sitka spruce industrially and represent an additional set of potential beneficiaries.
While the proposed research is primarily on Sitka spruce, the impacts will reach beyond this single species and the results will be of interest to diverse beneficiaries. This is because, we will produce an integrated genetic map for species within the Pine family which includes many ecologically significant and economically important trees in the UK and globally. It is also because the project will set up a platform of expertise that is lacking in the UK and this will help broaden the beneficiaries of forest genomics to other species and to uses including multi-purpose forest management, conservation, monitoring, and timber tracking, among others.
HOW MIGHT THEY BENEFIT? -
Genomic Prediction methods from the project have a high likelihood of direct and short term impact, and are expected to have a transformative effect on tree breeding as already realized in livestock. A large SNP database and a genotyping array covering 10,000 SNPs will also become available to industry for further developments. The UK's world leading Sitka spruce breeding program is a logical first target for GP development that is internationally competitive and has commercial impact. The acceleration of breeding that results from GP directly increases rates of genetic gain. The proposed work specifically aims to enable increased wood yields, shorter time to harvest and reduced risks of insect damage. The translation of results to industry is facilitated in the UK by a dynamic value chain from the breeders all the way to the wood processors - turning germplasm improvements into profits.
The expected economic impacts of the anticipated changes in breeding are tangible and could be very large. As the UK only produces 40% of the wood that it consumes and much of its land is under strong pressure for other agricultural and urbanisation uses, there is considerable scope for impact from increased biological efficiency of crops. One study simulating efficiency gains in spruce plantations showed that reducing the time to harvest by 20% would increase the net present value for growers by up to 73%. Applied to the hundreds of km2 that are restocked in Sitka spruce annually, the benefits would reach hundreds of £ millions over several years. Other benefits will result from more rapid development of new varieties and improvements in genetic diversity management as a key to enhancing adaptability to new pests and diseases as well as changing climates.
WHAT WILL BE DONE TO ENGAGE WITH POTENTIAL BENEFICIARIES? -
The commercial environment of the forestry sector involves Industries and Government (Forest Research and Forestry Commission) which we will bring together in our Project Advisory Board. This approach for engaging with end-users will support research co-development with users, improved uptake capacity of research outputs by end-users, and commercial developments. Other actions will include dissemination activities for industry and forestry professionals, a workshop on the transformative effects of genomics and formation of a Research Club in forest genomics. We will also engage with the broader public through public lectures on forest sustainability and press releases.
This project will impact tree breeding as the proposed predictive genomics methods will be direct applicable to Sitka spruce. With 6640 km2 under cultivation, the UK is the world's largest grower of Sitka spruce. Tee nurseries and growers, forestry operators and management firms, and large wood processors are the industries that profit from its production and are the expected commercial beneficiaries of the research. They are a major source of rural employment and many of them partner within the Sitka Spruce Breeding Cooperative also involving Government (Forest Research). Ireland, France, Scandinavia and North-America also grow 1000s of km2 of Sitka spruce industrially and represent an additional set of potential beneficiaries.
While the proposed research is primarily on Sitka spruce, the impacts will reach beyond this single species and the results will be of interest to diverse beneficiaries. This is because, we will produce an integrated genetic map for species within the Pine family which includes many ecologically significant and economically important trees in the UK and globally. It is also because the project will set up a platform of expertise that is lacking in the UK and this will help broaden the beneficiaries of forest genomics to other species and to uses including multi-purpose forest management, conservation, monitoring, and timber tracking, among others.
HOW MIGHT THEY BENEFIT? -
Genomic Prediction methods from the project have a high likelihood of direct and short term impact, and are expected to have a transformative effect on tree breeding as already realized in livestock. A large SNP database and a genotyping array covering 10,000 SNPs will also become available to industry for further developments. The UK's world leading Sitka spruce breeding program is a logical first target for GP development that is internationally competitive and has commercial impact. The acceleration of breeding that results from GP directly increases rates of genetic gain. The proposed work specifically aims to enable increased wood yields, shorter time to harvest and reduced risks of insect damage. The translation of results to industry is facilitated in the UK by a dynamic value chain from the breeders all the way to the wood processors - turning germplasm improvements into profits.
The expected economic impacts of the anticipated changes in breeding are tangible and could be very large. As the UK only produces 40% of the wood that it consumes and much of its land is under strong pressure for other agricultural and urbanisation uses, there is considerable scope for impact from increased biological efficiency of crops. One study simulating efficiency gains in spruce plantations showed that reducing the time to harvest by 20% would increase the net present value for growers by up to 73%. Applied to the hundreds of km2 that are restocked in Sitka spruce annually, the benefits would reach hundreds of £ millions over several years. Other benefits will result from more rapid development of new varieties and improvements in genetic diversity management as a key to enhancing adaptability to new pests and diseases as well as changing climates.
WHAT WILL BE DONE TO ENGAGE WITH POTENTIAL BENEFICIARIES? -
The commercial environment of the forestry sector involves Industries and Government (Forest Research and Forestry Commission) which we will bring together in our Project Advisory Board. This approach for engaging with end-users will support research co-development with users, improved uptake capacity of research outputs by end-users, and commercial developments. Other actions will include dissemination activities for industry and forestry professionals, a workshop on the transformative effects of genomics and formation of a Research Club in forest genomics. We will also engage with the broader public through public lectures on forest sustainability and press releases.
Organisations
- University of Edinburgh (Lead Research Organisation)
- UNIVERSITY OF OXFORD (Collaboration)
- UNIVERSITY OF EDINBURGH (Collaboration)
- INRA Bordeaux-Aquitaine (Collaboration)
- Forestart Ltd (Collaboration)
- BSW Timber Ltd (Collaboration)
- Norwegian University of Science and Technology (NTNU) (Collaboration)
- University of Laval (Collaboration)
- Maelor Forest Nurseries (Collaboration)
- Conifer Breeding Co-operative (Collaboration)
Publications
Bancic J
(2023)
Plant breeding simulations with AlphaSimR
Hem IG
(2021)
Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge.
in Genetics
Ilska JJ
(2023)
Additive and non-additive genetic variance in juvenile Sitka spruce (Picea sitchensis Bong. Carr).
in Tree genetics & genomes
Lubanga N
(2023)
Genomic selection strategies to increase genetic gain in tea breeding programs.
in The plant genome
Werner C
(2020)
Genomic selection strategies for clonally propagated crops
Whalen A
(2020)
AlphaFamImpute: high-accuracy imputation in full-sib families from genotype-by-sequencing data.
in Bioinformatics (Oxford, England)
Description | It has been shown that prediction can be made accurately within the large full-sib families of trees for economically important traits and across sites, without phenotypes. Previously it was impossible to predict individual merit among full sibs without obtaining phenotypes. In addition, we have shown how phasing and imputation can be used in such populations to boost and consolidate different sources of genomic data. |
Exploitation Route | These results will be taken forward by the broad Forest breeding and genetics community, including industry, to improve Sitka Spruce populations in the UK. We are in discussions with the community on the best ways to take these results forward. |
Sectors | Agriculture Food and Drink Environment |
URL | https://sitkaspruced.web.ox.ac.uk/home |
Description | The Roslin Institute direct involvement in this project was in the final 2 years. The Academic partnership with University of Oxford had a series of very successful meetings with the Sitka Spruce Co-operative which are the industry funders in this IPA, in which we explored the use of genomics in other breeding schemes and developed plans for making the Co-operative more influential in developing science for their objectives. This was delivering the Pathways to Impact as planned in the proposal. We have continued build on the industrial partnership and to help the Sitka Spruce Co-operative develop a research portfolio that is targeted towards a more effective forestry. We have also co-oragnised an Industry Day at Roslin Institute in September 2019, in collaboration with our partners. This was held very successfully with excellent feedback. Three of the Sitka Spruced research team met with industry representatives on site at a modern sawmill (James Jones & Sons) to discuss the objectives, limitations and opportunities offered by modern processing. At a field day in a local forest plantation held by Royal Scottish Forestry Society a very brief summary of the project was given to encourage a follow up visit to NRS at Roslin to hear about the work in progress by Sitka Spruced. These activities have prompted a serious consideration of the industry to co-fund the further work to develop a genomics-led breeding program. We are now at the end of the project and actively discuss with the stakeholders on how to build a project that will follow upon the success of the results and interactions from the SitkaSpruced project. |
First Year Of Impact | 2019 |
Sector | Agriculture, Food and Drink,Environment |
Impact Types | Economic Policy & public services |
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 |
Title | Tree breeding simulation |
Description | Tree breeding simulation using AlphaSimR - see details at Unlocking genome-based prediction and selection in conifers: the key role of within-family prediction accuracy https://www.biorxiv.org/content/10.1101/2024.01.25.577259v1 |
Type Of Material | Computer model/algorithm |
Year Produced | 2023 |
Provided To Others? | Yes |
Impact | Enables tree breeders to evaluate their breeding programmes |
URL | https://github.com/HighlanderLab/vpapin_pine_gs |
Description | BSW Timber Group |
Organisation | BSW Timber Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Co PI in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Funding through IPA. |
Impact | Early days. |
Start Year | 2017 |
Description | Collaboration with INRAE on tree breeding and genetics |
Organisation | INRA Bordeaux-Aquitaine |
Country | France |
Sector | Charity/Non Profit |
PI Contribution | Visiting student Victor Papin studying the power of genomic prediction in tree breeding populations |
Collaborator Contribution | Simulation study on the power of genomic prediction in tree breeding populations |
Impact | Simulation study on the power of genomic prediction in tree breeding populations - pre-print Unlocking genome-based prediction and selection in conifers: the key role of within-family prediction accuracy Context Genomic selection is a promising approach for forest tree breeding. However, its advantage in terms of prediction accuracy over conventional pedigree-based methods is unclear and within-family accuracy is rarely assessed. Aims We used an pedigree-based model (ABLUP) with corrected pedigree data as a baseline reference for assessing the prediction accuracy of genome-based model (GBLUP) at the global and within-family levels in maritime pine (Pinus pinaster Ait). Methods We sampled 39 full-sib families, each comprising 10 to 40 individuals, to constitute an experimental population of 833 individuals. A stochastic simulation model was also developed to explore other scenarios of heritability, training set size and tagging density. Results Prediction accuracies with GBLUP and ABLUP were similar and accuracy with GBLUP within-family was on average zero with large variation between families. Simulations revealed that the number of individuals in the training set was the principal factor limiting GBLUP accuracy in our study and likely in many forest tree breeding programmes. Accurate within-family prediction is possible if 40-65 individuals per full-sib family are included in the genomic training set, from a total of 1600-2000 individuals in the training set. Conclusion Such conditions lead to a significant advantage of GBLUP over ABLUP in terms of prediction accuracy and more clearly justify the switch to genome-based prediction and selection in forest trees. |
Start Year | 2022 |
Description | Finn Lindgren (University of Edinburgh, School of Mathematics): Statistical and computational methods for quantitative genetics |
Organisation | University of Edinburgh |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We are developing new statistical and computational methods for quantitative genetics |
Collaborator Contribution | Discussion on the state of of the art statistical and computational methods |
Impact | Collaboration just begun |
Start Year | 2018 |
Description | Forestart |
Organisation | Forestart Ltd |
Country | United Kingdom |
Sector | Private |
PI Contribution | Co PI in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Funding for IPA. |
Impact | Early days. |
Start Year | 2017 |
Description | Ingelin Steinsland (Norwegian University of Science and Technology, Department of Mathematical Sciences): Statistical methods for quantitative genetics |
Organisation | Norwegian University of Science and Technology (NTNU) |
Department | Department of Mathematical Sciences |
Country | Norway |
Sector | Academic/University |
PI Contribution | We are developing new statistical methods for quantitative genetics |
Collaborator Contribution | Discussion on the state of of the art statistical methods |
Impact | Collaboration just begun |
Start Year | 2018 |
Description | Julian Hall (University of Edinburgh, School of Mathematics): Operations research methods for breeding |
Organisation | University of Edinburgh |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We are developing new operations research methods for breeding |
Collaborator Contribution | Discussion on the state of of the art operations research methods |
Impact | Collaboration just begun |
Start Year | 2018 |
Description | Laval University |
Organisation | University of Laval |
Country | Canada |
Sector | Academic/University |
PI Contribution | Co PI with Oxford University in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Making available background IP on conifer genomes, genotyping and sequencing services, bioinformatic analysis of sequence data. |
Impact | Early days. |
Start Year | 2017 |
Description | Maelor |
Organisation | Maelor Forest Nurseries |
Country | United Kingdom |
Sector | Private |
PI Contribution | Co PI in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Funding for IPA. |
Impact | Early days. |
Start Year | 2017 |
Description | Sitka Spruce Breeding Co-operative |
Organisation | Conifer Breeding Co-operative |
Country | United Kingdom |
Sector | Private |
PI Contribution | Co PI in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Funding for IPA. |
Impact | Early days. |
Start Year | 2017 |
Description | University of Oxford |
Organisation | University of Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co PI in project "Next generation Sitka spruce breeding informed by predictive and comparative genomics" (BB/P018653/1). Designing experiment and carrying out quantitative genetic analyses using pedigree and genomic data, establishing imputation protocols. |
Collaborator Contribution | Molecular genetic analysis of conifer genome analysis, comparative genomics, insect resistance expertise, turpene assays, expression arrays. |
Impact | Early days. |
Start Year | 2016 |
Title | AlphaPeel |
Description | AlphaPeel is a software package for calling, phasing, and imputing genotype and sequence data in pedigree populations. This program implements single locus peeling, multi locus peeling, and hybrid peeling |
Type Of Technology | Software |
Year Produced | 2018 |
Open Source License? | Yes |
Impact | AlphaPeel enabled genotype calling, phasing, and imputation of the largest whole-genome sequencing data in a pedigreed population to date. |
URL | https://github.com/AlphaGenes/AlphaPeel |
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 | 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 (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 | 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 | 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 | Meeting of Forestry Interest Group |
Form Of Engagement Activity | Participation in an open day or visit at my research institution |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | At a site visit to local forest plantation by Royal Scottish Forestry Society, a brief indicative summary was given of work being undertaken on Sitka Spruced to seek further engagement. |
Year(s) Of Engagement Activity | 2019 |
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 | 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 | University of Edinburgh Stats-Roslin day |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | Regional |
Primary Audience | Professional Practitioners |
Results and Impact | In January 2018 The Centre for Statistics of the University of Edinburgh organised a joint research day with The Roslin institute to share research problems and ideas and start collaborations. I have contributed with a talk titled "Statistics supported breeding", which showcased the mathematicians and statisticians that there is a considerable common ground between the two fields and spurred collaboration in this area. |
Year(s) Of Engagement Activity | 2018 |
Description | Visiting Sawmill |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Visit to modern working sawmill to discuss the Sitka Spruced objectives, understand industry perspectives on further progress and how industry infrastructure would influence feasibility of future objectives. |
Year(s) Of Engagement Activity | 2019 |
URL | https://sitkaspruced.web.ox.ac.uk/home |