Genomic selection (GS) or genomic prediction is a promising approach for tree breeding to obtain higher genetic gains by shortening time of progeny testing in breeding programs. As proof-of-concept ...for Scots pine (Pinus sylvestris L.), a genomic prediction study was conducted with 694 individuals representing 183 full-sib families that were genotyped with genotyping-by-sequencing (GBS) and phenotyped for growth and wood quality traits. 8719 SNPs were used to compare different genomic with pedigree prediction models. Additionally, four prediction efficiency methods were used to evaluate the impact of genomic breeding value estimations by assigning diverse ratios of training and validation sets, as well as several subsets of SNP markers.
Genomic Best Linear Unbiased Prediction (GBLUP) and Bayesian Ridge Regression (BRR) combined with expectation maximization (EM) imputation algorithm showed slightly higher prediction efficiencies than Pedigree Best Linear Unbiased Prediction (PBLUP) and Bayesian LASSO, with some exceptions. A subset of approximately 6000 SNP markers, was enough to provide similar prediction efficiencies as the full set of 8719 markers. Additionally, prediction efficiencies of genomic models were enough to achieve a higher selection response, that varied between 50-143% higher than the traditional pedigree-based selection.
Although prediction efficiencies were similar for genomic and pedigree models, the relative selection response was doubled for genomic models by assuming that earlier selections can be done at the seedling stage, reducing the progeny testing time, thus shortening the breeding cycle length roughly by 50%.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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
Norway spruce (
(L.) Karst.) is a conifer species of substanital economic and ecological importance. In common with most conifers, the
genome is very large (∼20 Gbp) and contains a high fraction of ...repetitive DNA. The current
genome assembly (v1.0) covers approximately 60% of the total genome size but is highly fragmented, consisting of >10 million scaffolds. The genome annotation contains 66,632 gene models that are at least partially validated (www.congenie.org), however, the fragmented nature of the assembly means that there is currently little information available on how these genes are physically distributed over the 12
chromosomes. By creating an ultra-dense genetic linkage map, we anchored and ordered scaffolds into linkage groups, which complements the fine-scale information available in assembly contigs. Our ultra-dense haploid consensus genetic map consists of 21,056 markers derived from 14,336 scaffolds that contain 17,079 gene models (25.6% of the validated gene models) that we have anchored to the 12 linkage groups. We used data from three independent component maps, as well as comparisons with previously published
maps to evaluate the accuracy and marker ordering of the linkage groups. We demonstrate that approximately 3.8% of the anchored scaffolds and 1.6% of the gene models covered by the consensus map have likely assembly errors as they contain genetic markers that map to different regions within or between linkage groups. We further evaluate the utility of the genetic map for the conifer research community by using an independent data set of unrelated individuals to assess genome-wide variation in genetic diversity using the genomic regions anchored to linkage groups. The results show that our map is sufficiently dense to enable detailed evolutionary analyses across the
genome.
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.
Summary
Norway spruce is a boreal forest tree species of significant ecological and economic importance. Hence there is a strong imperative to dissect the genetics underlying important wood quality ...traits in the species. We performed a functional genome‐wide association study (GWAS) of 17 wood traits in Norway spruce using 178 101 single nucleotide polymorphisms (SNPs) generated from exome genotyping of 517 mother trees. The wood traits were defined using functional modelling of wood properties across annual growth rings. We applied a Least Absolute Shrinkage and Selection Operator (LASSO‐based) association mapping method using a functional multilocus mapping approach that utilizes latent traits, with a stability selection probability method as the hypothesis testing approach to determine a significant quantitative trait locus. The analysis provided 52 significant SNPs from 39 candidate genes, including genes previously implicated in wood formation and tree growth in spruce and other species. Our study represents a multilocus GWAS for complex wood traits in Norway spruce. The results advance our understanding of the genetics influencing wood traits and identifies candidate genes for future functional studies.
Significance Statement
Wood provides both structural support and a transport route for water and solutes in trees. Our work provides a framework to dissect the genetic nature of wood formation and adds to our understanding of tree growth and development. With the current research focus on wood cell wall biosynthesis in general, and lignocellulose feedstock for biorefineries, we believe that this contribution will be of wide interest for the plant science community.
Summary
Vast population movements induced by recurrent climatic cycles have shaped the genetic structure of plant species. During glacial periods species were confined to low‐latitude refugia from ...which they recolonized higher latitudes as the climate improved. This multipronged recolonization led to many lineages that later met and formed large contact zones.
We utilize genomic data from 5000 Picea abies trees to test for the presence of natural selection during recolonization and establishment of a contact zone in Scandinavia.
Scandinavian P. abies is today made up of a southern genetic cluster originating from the Baltics, and a northern one originating from Northern Russia. The contact zone delineating them closely matches the limit between two major climatic regions. We show that natural selection contributed to its establishment and maintenance. First, an isolation‐with‐migration model with genome‐wide linked selection fits the data better than a purely neutral one. Second, many loci show signatures of selection or are associated with environmental variables. These loci, regrouped in clusters on chromosomes, are often related to phenology.
Altogether, our results illustrate how climatic cycles, recolonization and selection can establish strong local adaptation along contact zones and affect the genetic architecture of adaptive traits.
It is important to improve the understanding of the interactions between the trees and pathogens and integrate this knowledge about disease resistance into tree breeding programs. The conifer Norway ...spruce (Picea abies) is an important species for the forest industry in Europe. Its major pathogen is Heterobasidion parviporum, causing stem and root rot.
In this study, we identified 11 Norway spruce QTLs (Quantitative trait loci) that correlate with variation in resistance to H. parviporum in a population of 466 trees by association genetics. Individual QTLs explained between 2.1 and 5.2% of the phenotypic variance. The expression of candidate genes associated with the QTLs was analysed in silico and in response to H. parviporum hypothesizing that (a) candidate genes linked to control of fungal sapwood growth are more commonly expressed in sapwood, and; (b) candidate genes associated with induced defences are respond to H. parviporum inoculation. The Norway spruce laccase PaLAC5 associated with control of lesion length development is likely to be involved in the induced defences. Expression analyses showed that PaLAC5 responds specifically and strongly in close proximity to the H. parviporum inoculation. Thus, PaLAC5 may be associated with the lignosuberized boundary zone formation in bark adjacent to the inoculation site.
Heterobasidion parviporum is a major pathogen of Norway spruce in Europe. This study identified 11 Norway spruce QTLs for resistance to H. parviporum. One of the QTLs comprise the laccase PaLAC5 and expression analyses suggest that PaLAC5 may be associated with the lignosuberized boundary zone formation.
A genomic selection study of growth and wood quality traits is reported based on control-pollinated Norway spruce families established in 2 Northern Swedish trials at 2 locations using exome capture ...as a genotyping platform. Nonadditive effects including dominance and first-order epistatic interactions (including additive-by-additive, dominance-by-dominance, and additive-by-dominance) and marker-by-environment interaction (M×E) effects were dissected in genomic and phenotypic selection models. Genomic selection models partitioned additive and nonadditive genetic variances more precisely than pedigree-based models. In addition, predictive ability in GS was substantially increased by including dominance and slightly increased by including M×E effects when these effects are significant. For velocity, response to genomic selection per year increased up to 78.9/80.8%, 86.9/82.9%, and 91.3/88.2% compared with response to phenotypic selection per year when genomic selection was based on 1) main marker effects (M), 2) M + M×E effects (A), and 3) A + dominance effects (AD) for sites 1 and 2, respectively. This indicates that including M×E and dominance effects not only improves genetic parameter estimates but also when they are significant may improve the genetic gain. For tree height, Pilodyn, and modulus of elasticity (MOE), response to genomic selection per year improved up to 68.9%, 91.3%, and 92.6% compared with response to phenotypic selection per year, respectively.Subject Area: Quantitative genetics and Mendelian inheritance.
The taxonomically diverse phyllosphere fungi inhabit leaves of plants. Thus, apart from the fungi's dispersal capacities and environmental factors, the assembly of the phyllosphere community ...associated with a given host plant depends on factors encoded by the host's genome. The host genetic factors and their influence on the assembly of phyllosphere communities under natural conditions are poorly understood, especially in trees. Recent work indicates that Norway spruce (Picea abies) vegetative buds harbour active fungal communities, but these are hitherto largely uncharacterized. This study combines internal transcribed spacer sequencing of the fungal communities associated with dormant vegetative buds with a genome‐wide association study (GWAS) in 478 unrelated Norway spruce trees. The aim was to detect host loci associated with variation in the fungal communities across the population, and to identify loci correlating with the presence of specific, latent, pathogens. The fungal communities were dominated by known Norway spruce phyllosphere endophytes and pathogens. We identified six quantitative trait loci (QTLs) associated with the relative abundance of the dominating taxa (i.e., top 1% most abundant taxa). Three additional QTLs associated with colonization by the spruce needle cast pathogen Lirula macrospora or the cherry spruce rust (Thekopsora areolata) in asymptomatic tissues were detected. The identification of the nine QTLs shows that the genetic variation in Norway spruce influences the fungal community in dormant buds and that mechanisms underlying the assembly of the communities and the colonization of latent pathogens in trees may be uncovered by combining molecular identification of fungi with GWAS.
Philosophiae Doctor - PhD
Apple scab, powdery mildew and woolly apple aphid are a major concern for apple breeders and producers. Control of these diseases is a significant economic and marketing ...priority for the South African apple industry. Application of chemicals and orchard management practices are the main methods for controlling these diseases. These diseases require an average of 15 chemical sprays per season, which leads to increased production costs for the farmer. The increased cost of;
chemical based control programs and demand from consumers for ‘organic apples’ grown with very little to no chemical sprays makes it important to breed for commercial apple cultivars with endogenous disease resistance genes (R-genes). The use of genetic tools (apple genetic linkage maps and the apple genome sequence) to track and introgress endogenous R-genes in breeding and to confer durable disease resistance in commercial apple cultivars will lead to a more cost;
effective means of disease control for apple producers. Historically, most breeding programmes rely on recurrent conventional breeding systems. This involves the crossing of apple selections showing resistance to a given disease with a susceptible;
elite variety. This is followed by phenotyping the progeny to identify trees exhibiting segregating field resistance. Several crosses and backcrossing are required to produce resistant varieties and to fix the resistance trait using this breeding strategy. This breeding technique is time consuming, especially in perennial tree species such as apples, which have a long juvenile period. Molecular;
markers have enabled the building of genetic maps, which has allowed for tracking of the inheritance of genes contributing towards the observed resistances. This has given breeders the opportunity to start the implementation of marker-assisted-breeding (MAB) and marker-assistedselection (MAS). MAB and MAS greatly reduce the time required to select for favourable genotypes, given that MAB facilitates efficient selection for inherited traits at the seedling stage. With the publication of the apple genome sequence, the identification of the genes involved in disease resistances has been made possible and this will allow researchers to venture into;
cisgenics for apples, which will further reduce the time required for the introgression of desirable genes into commercial cultivars. The main thrust of this research was to generate dense genetic linkage maps for three mapping;
populations segregating for apple scab, woolly apple aphid and powdery mildew resistance. The three mapping populations are ‘Mildew Resistant’ x ‘Golden Delicious’, ‘Russian Seedling’ x ‘Golden Delicious’ and Malus platycarpa x ‘Mildew Resistant’ and are Malus full-sib outbreed mapping populations. The generation of the genetic maps was for use in the subsequent identification candidate disease resistance QTLs/genes that can be implemented in apple cisgenics. Integrated genetic maps using SSRs, DArTs and SNP marker data were generated for all the three crosses. The integrated map of ‘Mildew Resistance’ x ‘Golden Delicious’ consists of 1, 563 markers with a total map length of 1, 298.8 cM. The ‘Russian Seedling’ x ‘Golden Delicious’ genetic map is composed of 979 markers with a total map length of 1, 729.9 cM. The Malus platycarpa x ‘Mildew Resistant’ integrated map has 616 markers and a total map length of 1,324.3 cM. Due to the fragmentation of some of the linkage groups in the ‘Russian Seedling’ x;
‘Golden Delicious’ and in the Malus platycarpa x ‘Mildew Resistant’ genetic maps, a;
phylogenetic analysis was performed to evaluate the genetic distances between the parents of the crosses in order to understand the cause of the fragmentation of these two integrated genetic maps. QTLs were detected through the statistical correlation of the phenotypic and map data using restricted Multiple QTL Mapping (rMQM) from MapQTL® 6.0. The genome-wide LOD score minimum QTL detection thresholds were determined using 10 000 permutations for each population. The minimum QTL detection threshold for accepting a putative QTL was then;
determined to be 4.5 for ‘Mildew Resistant’ x ‘Golden Delicious’ and 4.6 for both the ‘Malus platycarpa’ x ‘Mildew Resistant’ and ‘Russian Seedling’ x ‘Golden Delicious’ mapping populations. A total of 17 putative QTLs were detected for the ‘Mildew Resistant’ x ‘Golden Delicious’ population, 10 putative QTLs for the Malus platycarpa x ‘Mildew Resistant’ population and nine putative QTLs for the ‘Russian Seedling’ x ‘Golden Delicious’ population were detected for the three diseases under study. The two putative QTLs for apple scab resistance detected on LG 02 of the ‘Russian Seedling’ x ‘Golden Delicious’ map coincided with the loci previously identified as encoding two apple scab resistance genes Vh2 and Vh4 on ‘Russian apple’. The QTL for apple scab resistance identified on the proximal QTL of LG 02 co-localized with SNP marker R_8936738_Lg2 on the loci where Vh4 was previously identified. The distal QTL on LG 02 shown to encode the Vh2 R-gene was linked with the SNP marker R_32981524_Lg2. With ‘Russian apple’ being known to carry a;
natural pyramid of R-genes for apple scab on LG 02, therefore, the ‘Russian Seedling’ used in this study was screened by a set of 14 SSR markers to determine if it was related to ‘Russian apple. The 14 SSRs produced identical alleles to those amplified by ‘Russian apple’, which means “Russian Seedling’ and ‘Russian apple’ are closely related or identical. The LG 02 pseudo-chromosome sequence was extracted from the NCBI database housing the apple genome sequence and was then used to mine for the putative R-genes within the two QTL regions. The region corresponding to the Vh2 loci, which was roughly a 600 kb region, had two;
clusters of ABC (PDR) disease resistance related genes. These were predicted using a full Pfam domain search and were only detected on the negative strand. The 60 kb region corresponding to the Vh4 loci comprised a cluster of LRR domains that were also detected on the negative strand using a full Pfam domain search. This 60 kb region was further analysed using Phytozome and Genome Database for Rosaceae (GDR) leading to two candidate disease resistance genes being identified. Ten consensus gene sequences were present within the 60 kb region, with only two transcripts MDP0000657246 and MDP0000128458 identified as being disease resistance related genes. The MDP0000657246 was identified on the contig MDC000294 of the Malus x domestica reference genome as being a Leucine Rich Repeat protein kinase family, which is one of the most abundant disease resistance family mainly involved in the gene-for-gene resistance mechanism. The MDP0000128458 locus was identified on contig MDC015161 as being a Ser/Thr phosphatase 7. The Ser/Thr phosphatase genes have been associated with the regulation of MAP kinase cascades that have been shown to induce the hypersensitive response (HR) in tobacco. Therefore these two genes are likely to be the loci associated with the hypersensitive response associated with the infection of apples with race 4 of apple scab, carrying the Vh4 apple scab resistance gene. Recurrent putative QTLs were detected that still need to be validated in order to be used for MAB. The ‘Russian Seedling’ x ‘Golden Delicious’ cross produced a single powdery mildew resistance QTL located on LG08 and conferring a 1:1 resistance to susceptible phenotypic segregation ratio. These results indicate that the source of the resistance thus was a single dominant resistance gene. The ‘Mildew Resistant’ x ‘Golden Delicious’ mapping population also showed two stable QTLs one for powdery mildew on LG 03, which co-segregated with SNP GD_LG03snp00866 and in addition SNP R_13071892_Lg10 was also identified to be co-segregating with the QTL for apple scab resistance on LG10. However, none of these recurrent QTLs co-localized with known genes or QTLs. For the phylogenetic analysis, re-sequenced data using the Illumina® sequencing technologies and the apple SNP chip data for ‘Russian Seedling’, ‘Mildew Resistant’, Malus platycarpa, a Chinese accession of Malus sieversii and ‘Anna’ where used to infer relatedness of the five genotypes. The Chinese accession of Malus sieversii was included in the analysis since ‘Russian Seedling’ was thought to be relatively close genetically. Whilst ‘Anna’ is known to be a low chilling cultivar of Malus x domestica (Borkh) and therefore would add in the phylogenetic placement of ‘Mildew Resistant’ and Malus platycarpa. These were sequenced to coverage of approximately 60X for ‘Russian Seedling’ and 6X for the other four genotypes. The sequence data was aligned to the reference Malus x domestica cv Golden Delicious mitochondrial genome sequence. Phylogenetic;
analysis was then performed using both the data from the apple SNP-chip and the aligned mitochondrial genomes. The results from both sets of data supported the putative evolutionary distances between the five genotypes. ‘Russian Seedling’ and M. sieversii were closely related, while both were genetically divergent from the closely related ‘Anna’ and ‘Golden Delicious’ commercial cultivars. This analysis however indicated that ‘Mildew Resistant’ was relatively closely related to ‘Golden Delicious’ and hence the low number of markers showing segregation distortions for the ‘Mildew Resistant’ x ‘Golden Delicious’ population in the 17 LGs of the;
integrated map. However, the other two mapping population exhibited a high number of markers with segregation distortions. Markers which are closely associated with disease resistance to apple scab powdery mildew and woolly apple aphid resistance will play a major role in the identification of the genes responsible;
for the resistances being observed. The identification of the two candidate genes for the Vh4 gene associated with apple scab resistance will be the platform from which a cisgenic p
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