爱丁堡大学PhD Position in SparseHybrids: Sparse designs, statistical machinery and breeding tools for leveraging heterosis in plants and animals申请条件要求-申请方
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爱丁堡大学
PhD直招介绍
About the Project
Summary: Unique PhD project in quantitative genetics, biometrics and selective breeding with leading academic and industry experts from UK, Europe and Australia. Focus on translational activities and multi-disciplinary engagement with plant and animal communities.
Background: Breeders exploit heterosis by crossing parents from two complementary populations (heterotic groups) to produce superior yield, quality and climate resilient hybrids. Hybrid maize, for example, contributes over 30% of total worldwide cereal production. Hybridisation is becoming more prevalent in wheat and oilseed rape, and most pig and poultry production is based on crossbreeding.
Plant breeders evaluate new parents by crossing to “tester” varieties representing the opposing group’s genetics. However, the testers are too few and often outdated, creating severly underpowered data not relevant to the current heterotic groups and growing conditions. Consequently, superior parents are falsely discarded, delaying the genetic progress by multiple years. Cross breeding plans are predominately less advanced in animal breeding.
Objectives: The objective of SparseHybrids is to revolutionise early-stage evaluation by removing testers and reducing current resources. Sparse crossing designs and statistical machinary will be developed which fully leverage heterosis, earlier in the breeding pipeline, thereby accelerating superior hybrids to market and increasing global food production.
Work packages
1. Optimising sparse (testerless) designs for accurately evaluating new parents and hybrids by crossing combinations of parents which maximise the power of phenotypic data.
2. Novel extensions of state-of-the-art statistical machinery for modelling multi-trait hybrid data, augmented with high-dimensional genomic/marker data and environmental/climate data.
3. Merging multi-trait index selection and optimal contribution selection, simultaneously improving short- and long-term heterosis by maximising genetic diversity within and between heterotic groups.
Work packages will be developed in our simulation software ecosystem (AlphaSimR and FieldSimR), validated with real breeding data, and coded into open-source R package for dissemination to the wider plant, animal and aquaculture breeding communities.
References
González-Diéguez et al. (2021) Genomic prediction of hybrid crops allows disentangling dominance and epistasis. Genet. 218 https://doi.org/10.1093/genetics/iyab026
Werner CR, Gemenet DC, Tolhurst DJ (2024) FieldSimR: An R package for simulating plot data in multi-environment field trials. Front. Plant Sci. 15. https://doi.org/10.3389/fpls.2024.1330574
Gorjanc G, Hickey JM (2018) AlphaMate: a program for optimising selection, maintenance of diversity, and mate allocation in breeding programs. Bioinform. https://doi.org/10.1093/bioinformatics/bty375
爱丁堡大学 PhD Position in SparseHybrids: Sparse designs, statistical machinery and breeding tools for leveraging heterosis in plants and animals项目有没有奖学金，是不是全奖Phd招生，下面我们一起看一下【大学名称】Phd的奖学金资助情况
项目资助情况
This 3.5 year studentship opportunity is open to UK and international students and provides funding to cover stipend, tuition fees and consumable/travel costs.
联系人
邮箱：RDSVS.Studentship.Applications@ed.ac.uk
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