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Genetic control of tracheid properties in Norway spruce wood
SLU Swedish University of Agricultural Science, Sweden.
SLU Swedish University of Agricultural Science, Sweden.
SLU Swedish University of Agricultural Science, Sweden.
SLU Swedish University of Agricultural Science, Sweden.
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2020 (English)In: Scientific Reports, E-ISSN 2045-2322, Vol. 10, no 1, article id 18089Article in journal (Refereed) Published
Abstract [en]

Through the use of genome-wide association studies (GWAS) mapping it is possible to establish the genetic basis of phenotypic trait variation. Our GWAS study presents the first such effort in Norway spruce (Picea abies (L). Karst.) for the traits related to wood tracheid characteristics. The study employed an exome capture genotyping approach that generated 178 101 Single Nucleotide Polymorphisms (SNPs) from 40 018 probes within a population of 517 Norway spruce mother trees. We applied a least absolute shrinkage and selection operator (LASSO) based association mapping method using a functional multi-locus mapping approach, with a stability selection probability method as the hypothesis testing approach to determine significant Quantitative Trait Loci (QTLs). The analysis has provided 30 significant associations, the majority of which show specific expression in wood-forming tissues or high ubiquitous expression, potentially controlling tracheids dimensions, their cell wall thickness and microfibril angle. Among the most promising candidates based on our results and prior information for other species are: Picea abies BIG GRAIN 2 (PabBG2) with a predicted function in auxin transport and sensitivity, and MA_373300g0010 encoding a protein similar to wall-associated receptor kinases, which were both associated with cell wall thickness. The results demonstrate feasibility of GWAS to identify novel candidate genes controlling industrially-relevant tracheid traits in Norway spruce. © 2020, The Author(s).

Place, publisher, year, edition, pages
Nature Research , 2020. Vol. 10, no 1, article id 18089
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Natural Sciences
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URN: urn:nbn:se:ri:diva-50422DOI: 10.1038/s41598-020-72586-3Scopus ID: 2-s2.0-85093836555OAI: oai:DiVA.org:ri-50422DiVA, id: diva2:1505897
Note

Funding details: Science for Life Laboratory, SciLifeLab; Funding details: Vetenskapsrådet, VR; Funding details: Knut och Alice Wallenbergs Stiftelse; Funding text 1: We acknowledge the Bio4Energy consortium for giving us accesss to the Silviscan wood properties data collection. We also acknowledge the support from Science for Life Laboratory, the Knut and Alice Wallenberg Foundation, the National Genomics Infrastructure funded by the Swedish Research Council, and Uppsala Multidisciplinary Center for Advanced Computational Science for assistance with massively parallel sequencing and access to the UPPMAX computational infrastructure. John Baison was supported though a postdoc position funded by the Kempe foundation, and Swedish Strategic Foundation project.

Available from: 2020-12-02 Created: 2020-12-02 Last updated: 2024-01-29Bibliographically approved

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Grahn, Thomas

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