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Biology subjects

Whan, A.

Publications and source records attributed to Whan, A..

3 recordsLinked to original sources

The complex genetic architecture of recombination and structural variation in wheat uncovered using a large 8-founder MAGIC population

BackgroundIdentifying the genetic architecture of complex traits requires access to populations with sufficient genetic diversity and recombination. Multi-parent Advanced Generation InterCross (MAGIC) populations are a powerful resource due to their balanced population structure, allelic diversity and enhanced recombination. However, implementing a MAGIC population in complex polyploids such as wheat is not trivial, as wheat harbours many introgressions, inversions and other genetic factors that interfere with linkage mapping.\n\nResultsBy utilising a comprehensive crossing strategy, additional rounds of mixing and novel genotype calling approaches, we developed a bread wheat eight parent MAGIC population made up of more than 3000 fully genotyped recombinant inbred lines derived from 2151 distinct crosses, and achieved a dense genetic map covering the complete genome. Further rounds of inter-crossing led to increased recombination in inbred lines, as expected. The comprehensive and novel approaches taken in the development and analysis of this population provide a platform for genetic discovery in bread wheat. We identify previously unreported structural variation highlighted by segregation distortion, along with the identification of epistatic allelic interactions between specific founders. We demonstrate the ability to conduct high resolution QTL mapping using the number of recombination events as a trait, and identify several significant QTLs explaining greater than 50% of the variance.\n\nConclusionsWe report on a novel and effective resource for genomic and trait exploration in hexaploid wheat, that can be used to detect small genetic effects and epistatic interactions due to the high level of recombination and large number of lines. The interactions and genetic effects identified provide a basis for ongoing research to understand the basis of allelic frequencies across the genome, particularly where economically important loci are involved.

plant biology

Integrating past, present and future wheat research with Pretzel

MotivationMajor advances have been made in the assembly of complex genomes such as wheat. Remaining challenges include linking these new resources to legacy research, as well as lowering the bar to entry for members of the research community who may lack specific bioinformatics skills.\n\nResultsPretzel aims to solve these problems by providing an interactive, online environment for data visualisation and analysis which, when loaded with appropriately curated data, can enable researchers with no bioinformatics training to exploit the latest genomic resources. We demonstrate that Pretzel can be used to answer common questions asked by researchers as well as for advanced curation of pseudomolecule structure.\n\nAvailabilityPretzel is implemented in JavaScript and is freely available under a GPLv3 license online at: https://github.com/plantinformatics/pretzel.\n\nContactgabriel.keeble-gagnere@ecodev.vic.gov.au

bioinformatics

Heterozygote calling in significantly inbred populations

1. Introduction 1. Introduction 2. Model 3. Implementation 4. Example References Realising the potential of large genetic resources requires the ability to perform genotyping efficiently. In populations with tens or hundreds of thousands of SNP markers, it is infeasible to assign genotypes manually; this must be done automatically. This problem is generally solved by the application of mixture models [Xiao et al., 2007, Teo et al., 2007].\n\nWe describe a marker calling method able to correctly identify marker heterozygotes, in large populations generated according to some experimental design; e.g. the Collaborative Cross [Threadgill and Churchill, 2012] or MAGIC [Huang et al., 2015]. Identifying marker heterozygotes is of substantial value in these populations, which are substant ...

bioinformatics