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A spatial analysis of Norwegian spruce cone developmental stages

The Norway spruce Picea abies is an economically important export to the Swedish economy. There are a number of environmental and endogenous factors that impact the generation time of this species meaning that it can take 20-25 years for a tree to mature. The long generation time creates a challenge for plant breeding programs in terms of how genetic mechanisms are able to be studied as well as how quickly trees can be produced for lumber. The characterization of gene expression patterns in the context of special tissue domains is essential to understanding the underlying functions behind complex biological systems and in the case of P. abies may prove more crucial to determining the activation of genes at specific reproductive growth points. There are several techniques available for the analysis of spatial expression profiles, however, the unique high throughput nature coupled to the morphological information provided by Spatial Transcriptomics creates new opportunities for exploratory analysis. Spatial Transcriptomics offers a distinct approach to answering fundamental questions about the genetic mechanisms that regulate reproductive phase change and cone-setting in conifers. This study focuses on spatial gene expression analysis and the integration of de novo transcriptome assembly contigs to confirm the spatial context of putatively discovered genes such as DAL1, DAL2, DAL3, and DAL10 from previous studies and to potentially localize transcripts that could not previously be identified due to the inability to obtain complete transcripts. The aim is to create a workflow to identify genes that contribute to the growth patterns in the naturally occurring acrocona mutant that could prove useful to improving tree breeding programs.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:uu-425746
Date January 2020
CreatorsOrozco, Alina
PublisherUppsala universitet, Institutionen för biologisk grundutbildning
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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