Genomic selection (GS) can increase genetic gain by reducing the length of breeding cycle in forest trees. Here we genotyped 1370 control-pollinated progeny trees from 128 full-sib families in Norway ...spruce (Picea abies (L.) Karst.), using exome capture as genotyping platform. We used 116,765 high-quality SNPs to develop genomic prediction models for tree height and wood quality traits. We assessed the impact of different genomic prediction methods, genotype-by-environment interaction (G × E), genetic composition, size of the training and validation set, relatedness, and number of SNPs on accuracy and predictive ability (PA) of GS.
Using G matrix slightly altered heritability estimates relative to pedigree-based method. GS accuracies were about 11-14% lower than those based on pedigree-based selection. The efficiency of GS per year varied from 1.71 to 1.78, compared to that of the pedigree-based model if breeding cycle length was halved using GS. Height GS accuracy decreased to more than 30% while using one site as training for GS prediction and using this model to predict the second site, indicating that G × E for tree height should be accommodated in model fitting. Using a half-sib family structure instead of full-sib structure led to a significant reduction in GS accuracy and PA. The full-sib family structure needed only 750 markers to reach similar accuracy and PA, as compared to 100,000 markers required for the half-sib family, indicating that maintaining the high relatedness in the model improves accuracy and PA. Using 4000-8000 markers in full-sib family structure was sufficient to obtain GS model accuracy and PA for tree height and wood quality traits, almost equivalent to that obtained with all markers.
The study indicates that GS would be efficient in reducing generation time of breeding cycle in conifer tree breeding program that requires long-term progeny testing. The sufficient number of trees within-family (16 for growth and 12 for wood quality traits) and number of SNPs (8000) are required for GS with full-sib family relationship. GS methods had little impact on GS efficiency for growth and wood quality traits. GS model should incorporate G × E effect when a strong G × E is detected.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Fibromyalgia (FM) is an idiopathic chronic disease characterized by widespread musculoskeletal pain, hyperalgesia and allodynia, often accompanied by fatigue, cognitive dysfunction and other ...symptoms. Autoimmunity and neuroinflammatory mechanisms have been suggested to play important roles in the pathophysiology of FM supported by recently identified interferon signatures in affected individuals. However, the contribution of different components in the immune system, such as the B-lymphocytes, in the progression to FM are yet unknown. Furthermore, there is a great need for biomarkers that may improve diagnostics of FM. Herein, we investigated the gene expression profile in peripheral B-cells, as well as a panel of inflammatory serum proteins, in 30 FM patients and 23 healthy matched control individuals. RNA sequence analysis revealed 60 differentially expressed genes when comparing the two groups. The group of FM patients showed increased expression of twenty-five interferon-regulated genes, such as
and
, and an increased interferon score. Furthermore, FM was associated with elevated levels of 19 inflammatory serum proteins, such as IL8, AXIN1, SIRT2 and STAMBP, that correlated with the FM severity score. Together, the results shows that FM is associated with an interferon signature in B-cells and increased levels of a set of inflammatory serum proteins. Our findings bring further support for immune activation in the pathogenesis of FM and highlight candidate biomarkers for diagnosis and intervention in the management of FM.
Genome-wide association studies (GWAS) identify loci underlying the variation of complex traits. One of the main limitations of GWAS is the availability of reliable phenotypic data, particularly for ...long-lived tree species. Although an extensive amount of phenotypic data already exists in breeding programs, accounting for its high heterogeneity is a great challenge. We combine spatial and factor-analytics analyses to standardize the heterogeneous data from 120 field experiments of 483,424 progenies of Norway spruce to implement the largest reported GWAS for trees using 134 605 SNPs from exome sequencing of 5056 parental trees.
We identify 55 novel quantitative trait loci (QTLs) that are associated with phenotypic variation. The largest number of QTLs is associated with the budburst stage, followed by diameter at breast height, wood quality, and frost damage. Two QTLs with the largest effect have a pleiotropic effect for budburst stage, frost damage, and diameter and are associated with MAP3K genes. Genotype data called from exome capture, recently developed SNP array and gene expression data indirectly support this discovery.
Several important QTLs associated with growth and frost damage have been verified in several southern and northern progeny plantations, indicating that these loci can be used in QTL-assisted genomic selection. Our study also demonstrates that existing heterogeneous phenotypic data from breeding programs, collected over several decades, is an important source for GWAS and that such integration into GWAS should be a major area of inquiry in the future.
Primeval forests are today exceedingly rare in Europe, and transfer of forest reproductive material for afforestation and improvement has been very common, especially over the last two centuries. ...This can be a serious impediment when inferring past population movements in response to past climate changes such as the last glacial maximum (LGM), some 18,000 years ago. In the present study, we genotyped 1,672 individuals from three Picea species (P. abies, P. obovata, and P. omorika) at 400K SNPs using exome capture to infer the past demographic history of Norway spruce (P. abies) and estimate the amount of recent introduction used to establish the Norway spruce breeding program in southern Sweden. Most of these trees belong to P. abies and originate from the base populations of the Swedish breeding program. Others originate from populations across the natural ranges of the three species. Of the 1,499 individuals stemming from the breeding program, a large proportion corresponds to recent introductions from mainland Europe. The split of P. omorika occurred 23 million years ago (mya), while the divergence between P. obovata and P. abies began 17.6 mya. Demographic inferences retrieved the same main clusters within P. abies than previous studies, that is, a vast northern domain ranging from Norway to central Russia, where the species is progressively replaced by Siberian spruce (P. obovata) and two smaller domains, an Alpine domain and a Carpathian one, but also revealed further subdivision and gene flow among clusters. The three main domains divergence was ancient (15 mya), and all three went through a bottleneck corresponding to the LGM. Approximately 17% of P. abies Nordic domain migrated from P. obovata ~103K years ago, when both species had much larger effective population sizes. Our analysis of genomewide polymorphism data thus revealed the complex demographic history of Picea genus in Western Europe and highlighted the importance of material transfer in Swedish breeding program.
Norway spruce (Picea abies) is a dominant conifer species of major economic importance in northern Europe. Extensive breeding programs were established to improve phenotypic traits of economic ...interest. In southern Sweden, seeds used to create progeny tests were collected on about 3,000 trees of outstanding phenotype (‘plus’ trees) across the region. In a companion paper, we showed that some were of local origin but many were recent introductions from the rest of the natural range. The mixed origin of the trees together with partial sequencing of the exome of >1,500 of these trees and phenotypic data retrieved from the Swedish breeding program offered a unique opportunity to dissect the genetic basis of local adaptation of three quantitative traits (height, diameter and bud‐burst) and assess the potential of assisted gene flow. Through a combination of multivariate analyses and genome‐wide association studies, we showed that there was a very strong effect of geographical origin on growth (height and diameter) and phenology (bud‐burst) with trees from southern origins outperforming local provenances. Association studies revealed that growth traits were highly polygenic and bud‐burst somewhat less. Hence, our results suggest that assisted gene flow and genomic selection approaches could help to alleviate the effect of climate change on P. abies breeding programs in Sweden.
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. Marker-based PAs were generally 25-30% higher for traits density, MFA and MOE measured with SilviScan than for their respective standing tree-based method which measured with Pilodyn and Hitman. Prediction accuracy (PC) of the standing tree-based methods were similar or even higher than increment core-based method. 78-95% of the maximal PAs of density, MFA and MOE 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.
This study indicates standing tree-based measurements is a cost-effective alternative method for GS. PA of GS methods were comparable with those pedigree-based prediction. The highest PAs were reached with at least 80-90% of the dataset used as training set. Selection for trait density could be conducted at an earlier age than for MFA and MOE. Operational breeding can also be optimized by training the model at an earlier age or using 3 to 5 outermost rings at tree age 10 to 12 years, thereby shortening the cycle and reducing the impact on the tree.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Genotype-by-environment (G × E) interaction for tree height measured at ages 7 to 13 was investigated in 20 large open-pollinated progeny trials for Norway spruce (
Picea abies
(L.) H. Karst.) in ...southern and central Sweden. Factor analytic method using spatially adjusted data and a reduced animal model was used to explore the pattern of G × E interaction. Extended factor analyses captured 93.0% of additive G × E interaction variances using three factors. The mean daily temperature less than 3.2 °C in May and June explained 27.8% G × E interaction, and it was moderately correlated with the first factor, indicating that spring or autumn frost weather condition could be a main driver for G × E interaction in Norway spruce. Cluster analysis has divided 20 trials into either 6 clusters or 3 clusters. Both sets of clusters reflected the geography of the trials (climates) and the genetic connectedness among testing series, indicating that more trials with better connectedness are required to examine whether current delineation of breeding or seed zones is optimal. Parental stability using latent regression could be used to locate best parents that have the highest breeding values and are highly stable across trials.
Key message
Spatial analysis could improve the accuracy of genetic analyses, as well as increasing the accuracy of predicting breeding values and genetic gain for Norway spruce trials.
Context
...Spatial analysis has been increasingly used in genetic evaluation of field trials in tree species. However, the efficiency of spatial analysis relative to the analysis using the conventional experimental designs or pre- and post-blocking method in Swedish genetic trials has not been systematically evaluated.
Aims
This study aims to examine the effectiveness of spatial analysis in improving the accuracy of predicting breeding values and genetic gain.
Methods
Spatial analysis, using separable first-order autoregressive processes of residuals in rows and columns, was used in nine types of trait classes from 145 field trials of Norway spruce (
Picea abies
(L.) Karst.) in Sweden.
Results
Ninety-six percent of variables (traits) were converged for the spatial model. Large trials with a large block variance tend to have a larger improvement from the model of experimental design to spatial model in accuracy. Growth and Pilodyn measurement traits showed greater improvements in log likelihood, accuracy, and genetic gain. Block variance was reduced by more than 80% for trait height and diameter using spatial analysis, indicating that it is more effective using both pre-blocking and post-blocking analyses in Swedish Norway spruce trials. The prediction accuracy for diameter and height for progeny breeding values showed an increase of 3.6 and 3.4%, respectively. The improvement of efficiency for growth traits is also related to the geographical location of test sites, tree age, number of survival trees, and the spacing of the trial.
Conclusion
The spatial analysis approach is more efficient in Swedish Norway spruce trials than the conventional methods using models based on the experimental design.
A consensus linkage map of Picea abies, an economically important conifer, was constructed based on the segregation of 686 SNP markers in a F1 progeny population consisting of 247 individuals. The ...total length of 1889.2 cM covered 96.5% of the estimated genome length and comprised 12 large linkage groups, corresponding to the number of haploid P. abies chromosomes. The sizes of the groups (from 5.9 to 9.9% of the total map length) correlated well with previous estimates of chromosome sizes (from 5.8 to 10.8% of total genome size). Any locus in the genome has a 97% probability to be within 10 cM from a mapped marker, which makes the map suited for QTL mapping. Infecting the progeny trees with the root rot pathogen Heterobasidion parviporum allowed for mapping of four different resistance traits: lesion length at the inoculation site, fungal spread within the sapwood, exclusion of the pathogen from the host after initial infection, and ability to prevent the infection from establishing at all. These four traits were associated with two, four, four and three QTL regions respectively of which none overlapped between the traits. Each QTL explained between 4.6 and 10.1% of the respective traits phenotypic variation. Although the QTL regions contain many more genes than the ones represented by the SNP markers, at least four markers within the confidence intervals originated from genes with known function in conifer defence; a leucoanthocyanidine reductase, which has previously been shown to upregulate during H. parviporum infection, and three intermediates of the lignification process; a hydroxycinnamoyl CoA shikimate/quinate hydroxycinnamoyltransferase, a 4-coumarate CoA ligase, and a R2R3-MYB transcription factor.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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