Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (2/2 displayed)

  • 2022Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations2citations
  • 2017A life cycle assessment of perovskite/silicon tandem solar cells91citations

Places of action

Chart of shared publication
Fordyce, Geoffry
1 / 1 shared
Mcgowan, Michael
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Corbet, Nicholas
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Warburton, Christie
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Engle, Bailey
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Corkish, Richard
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Lunardi, Marina Monteiro
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2022
2017

Co-Authors (by relevance)

  • Fordyce, Geoffry
  • Mcgowan, Michael
  • Corbet, Nicholas
  • Warburton, Christie
  • Engle, Bailey
  • Corkish, Richard
  • Alvarez-Gaitan, Juan Pablo
  • Lunardi, Marina Monteiro
  • Ho-Baillie, Anita
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document

Concurrently mapping quantitative trait loci associations from multiple subspecies within hybrid populations

  • Fordyce, Geoffry
  • Mcgowan, Michael
  • Corbet, Nicholas
  • Moore, Stephen
  • Warburton, Christie
  • Engle, Bailey
Abstract

<jats:title>Abstract</jats:title><jats:p>Many of the world’s agriculturally important plant and animal populations consist of hybrids of subspecies. Cattle in tropical and sub-tropical regions for example, originate from two genetically distinct subspecies, Bos indicus and Bos taurus. Methods to derive the underlying genetic architecture for these two subspecies are essential to develop accurate genomic predictions in these hybrid populations. We propose a novel method to achieve this.First, we use haplotypes to assign single nucleotide polymorphism (SNP) alleles to ancestral subspecies-of-origin in a multi-breed and multi-subspecies population.Then we use a BayesR framework to allow SNP alleles originating from the different subspecies to have different effects (unequal variances).Applying this method in a composite population of B. indicus and B. taurus hybrids, our results show that there are underlying genomic differences between the two subspecies, and these effects are not identified in multi-breed genomic evaluations that do not account for subspecies-of-origin effects. The method slightly improved the accuracy of genomic prediction.More significantly, by allocating SNP alleles to ancestral subspecies-of-origin, we were able to identify four SNP with high posterior probabilities of inclusion that have not been previously associated with cattle fertility and were very close to genes associated with fertility in other species. These results show that haplotypes can be used to trace subspecies-of-origin through the genome of this hybrid population and, in conjunction with our novel Bayesian analysis, subspecies SNP allele allocation can be used to increase the accuracy of quantitative trait loci (QTL) association mapping in genetically diverse populations.</jats:p>

Topics
  • inclusion
  • composite