Biology subjects

Grahn, T.

Publications and source records attributed to Grahn, T..

4 recordsLinked to original sources

bioRxiv2021

Identification of genetic markers and wood properties that predict wood biorefinery potential in aspen bioenergy feedstock (Populus tremula).

BackgroundWood represents the majority of the biomass on land and constitutes a renewable source of biofuels and other bioproducts. However, wood is recalcitrant to bioconversion, raising a need for feedstock improvement in production of, for instance, biofuels. We investigated the properties of wood that affect bioconversion, as well as the underlying genetics, to help identify superior tree feedstocks for biorefining. ResultsWe recorded 65 wood-related and growth traits in a population of 113 natural aspen genotypes from Sweden. These traits included three growth and field performance traits, 20 traits for wood chemical composition, 17 traits for wood anatomy and structure, and 25 wood saccharification traits as indicators of bioconversion potential. Glucose release after saccharification with acidic pretreatment correlated positively with tree stem height and diameter and the carbohydrate content of the wood, and negatively with the content of lignin and the hemicellulose sugar units. Most of these traits displayed extensive natural variation within the aspen population and high broad-sense heritability, supporting their potential in genetic improvement of feedstocks towards improved bioconversion. Finally, a genome wide association study (GWAS) revealed 13 genetic loci for saccharification yield (on a whole tree biomass basis), with six of them intersecting with associations for either height or stem diameter of the trees. ConclusionsThe simple growth traits of stem height and diameter were identified as good predictors of wood saccharification yield in aspen trees. GWAS elucidated the underlying genetics, revealing putative genetic markers for bioconversion of bioenergy tree feedstocks.

plant biology↗

bioRxiv2020

Effect of number of annual rings and tree ages on genomic predictive ability for solid wood properties of Norway spruce

Genomic selection (GS) or genomic prediction is considered as a promising approach to accelerate tree breeding and increase genetic gain by shortening breeding cycle, but the efforts to develop routines for operational breeding are so far limited. We investigated the predictive ability (PA) of GS based on 484 progeny trees from 62 half-sib families in Norway spruce (Picea abies (L.) Karst.) for wood density, modulus of elasticity (MOE) and microfibril angle (MFA) measured with SilviScan, as well as for measurements on standing trees by Pilodyn and Hitman instruments. GS predictive abilities were comparable with those based on pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Use of different statistical methods had no significant impact on the estimated PAs. We also compared the abilities to predict density, MFA and MOE of 19 year old trees with models trained on data from coring at different ages and to different depths into the stem. 78-95% of the maximal PAs obtained from coring to the pith at high age were reached by using data possible to obtain by drilling 3-5 rings towards the pith at tree age 10-12, thereby shortening the cycle and reducing the impact on the tree.

plant biology↗

bioRxiv2019

Genetic control of tracheid properties in Norway spruce wood

[tpltrtarr] Through the use of genome-wide association (GWAS) mapping it is possible to establish the genetic basis of phenotypic trait variation. Our GWAS study presents the first such an effort in Norway spruce (Picea abies (L). Karst.) for the traits related to wood tracheid characteristics.\n[tpltrtarr]The study employed an exome capture genotyping approach that generated 178 101 high quality Single Nucleotide Polymorphisms (SNPs) from 40 018 probes within a population of 517 Norway spruce mother trees. We applied a LASSO based association mapping method using a functional multi-locus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine significant Quantitative Trait Loci (QTLs). Expression of the identified candidate genes was examined using publicly available spruce databases.\n[tpltrtarr]The analysis have provided 31 loci and 26 mostly novel candidate genes, majority of which showing specific expression in wood-forming tissues or high ubiquitous expression, potentially controlling tracheids dimensions, their cell wall thickness and microfibril angle. Among most promising candidates, the analysis identified Picea abies BIG GRAIN 2 (PabBG2) with predicted function in auxin transport and sensitivity, and MA_373300g0010 - similar to wall-associated receptor kinases (WAKs), both associated to cell wall thickness.\n[tpltrtarr]The results demonstrate feasibility of GWAS to identify novel candidate genes controlling industrially-relevant tracheid traits in Norway spruce. The presence of many traits with several significant QTLs supports the notion that the majority of these traits are polygenic in nature.

genetics↗

bioRxiv2018

Genetic analysis using parent-progeny relationship for wood quality traits in Norway spruce (Picea abies (L.) Karst.)

Two-generations pedigree involving 524 plus trees and their open-pollinated (OP) progenies were jointly studied to estimate parent-progeny correlation and heritability. Three wood traits (wood density, MFA, and MOE) were determined by SilviS-can in one ramet per plus tree and 12 OP progenies. Three ramets per plus tree and 12 OP were also measured with two indirect methods, Pilodyn and Hitman. The overall correlation between OP-based breeding values and plus tree-based phenotypes was low to moderate for all traits. The correlations between the phenotypic values of the mother trees and the breeding values estimated on their half-sib pro-genies are low to moderate. Reasons for this may be experimental errors in progeny trials and lack of experimental design in archives, contributing to the parent and progeny correlation. The management practices in the archive may contribute more to such low correlation. Offspring progeny heritability estimates based on SilviScan measurements were higher than parent-offspring regression using one single ramet from the archive. Moreover, when three ramets were measured the parent-offspring regression heritability estimates were higher than those based solely on progeny data for the Pilodyn and Hitman on the standing trees. The standard error of the heritability estimates decreased with increasing progeny size.

plant biology↗