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BatchMap: A parallel implementation of the OneMap R package for fast computation of F-1 linkage maps in outcrossing species
Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
Umeå University, Faculty of Science and Technology, Department of Ecology and Environmental Sciences.
Umeå University, Faculty of Science and Technology, Umeå Plant Science Centre (UPSC).
2017 (English)In: PLOS ONE, E-ISSN 1932-6203, Vol. 12, no 12, article id e0189256Article in journal (Refereed) Published
Abstract [en]

With the rapid advancement of high throughput sequencing, large numbers of genetic markers can be readily and cheaply acquired, but most current software packages for genetic map construction cannot handle such dense input. Modern computer architectures and server farms represent untapped resources that can be used to enable higher marker densities to be processed in tractable time. Here we present a pipeline using a modified version of OneMap that parallelizes over bottleneck functions and achieves substantial speedups for producing a high density linkage map (N = 20,000). Using simulated data we show that the outcome is as accurate as the traditional pipeline. We further demonstrate that there is a direct relationship between the number of markers used and the level of deviation between true and estimated order, which in turn impacts the final size of a genetic map.

Place, publisher, year, edition, pages
2017. Vol. 12, no 12, article id e0189256
National Category
Genetics
Identifiers
URN: urn:nbn:se:umu:diva-144110DOI: 10.1371/journal.pone.0189256ISI: 000418564200037PubMedID: 29261725Scopus ID: 2-s2.0-85038843145OAI: oai:DiVA.org:umu-144110DiVA, id: diva2:1176680
Available from: 2018-01-23 Created: 2018-01-23 Last updated: 2023-03-24Bibliographically approved
In thesis
1. Embracing the data flood: integrating diverse data to improve phenotype association discovery in forest trees
Open this publication in new window or tab >>Embracing the data flood: integrating diverse data to improve phenotype association discovery in forest trees
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Complex traits represent valuable research targets as many highly desirable properties of plants and animals (such as growth rate and height) fall into this group. However, associating biological markers with these traits is incredibly challenging, in part due to their small effect sizes. For the two species at the core of our research, European aspen (Populus tremula) and Norway spruce (Picea abies), association studies are even more challenging, primarily due to the fragmented state of their genome assemblies. These assemblies represent the gene space well, but poorly represented inter-genic regions hinder variant discovery and large scale association studies.

In this thesis, I present my work to improve association discovery of complex traits in forest trees. Firstly, to overcome the issues with assembly fragmentation, I have created an updated version of the P. tremula genome, which is highly contiguous and anchored in full chromosomes. To calculate the dense linkage map required to order and orient the aspen assembly, I developed "BatchMap", a parallel implementation of linkage mapping software. BatchMap has been successfully applied to several dense linkage maps, including aspen and Norway spruce, and was essential to the progress in improving the aspen genome assembly. Further, I developed seidr, which represents a starting point in multi-layer, network-based systems biology, an analysis technique with promising prospects for complex trait association analysis. As a case study, I applied some of the methods developed to the analysis of leaf shape in natural populations of European aspen, a complex, omnigenic trait.

The multi-layer model of systems biology and related analysis techniques offer promise in the analysis of complex traits, and this thesis represents a starting point toward an intricate, holistic model of systems biology that may help to unravel the overwhelmingly complicated nature of complex traits.

Place, publisher, year, edition, pages
Umeå: Umeå University, 2020. p. 83
Keywords
Systems Biology, Association Discovery, Genomics, Transcriptomics, Genome Assembly, Gene Networks, Forest Tree, Aspen, Spruce
National Category
Biological Sciences
Research subject
biology
Identifiers
urn:nbn:se:umu:diva-170643 (URN)978-91-7855-273-3 (ISBN)978-91-7855-274-0 (ISBN)
Public defence
2020-06-12, KBE303 - Stora hörsalen, Umeå, 10:00 (English)
Opponent
Supervisors
Note

2020-06-10: Errata spikblad - Ny tid för disputation. 

Available from: 2020-05-20 Created: 2020-05-13 Last updated: 2020-06-10Bibliographically approved

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Schiffthaler, BastianBernhardsson, CarolinaStreet, Nathaniel R.
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