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Article ; Online: Expected benefit of genomic selection over forward selection in conifer breeding and deployment.

Yongjun Li / Heidi S Dungey

PLoS ONE, Vol 13, Iss 12, p e

2018 Volume 0208232

Abstract: Genomic selection is a proven technology in animal and plant breeding to accelerate genetic gain, but as yet is to be fully realised in forest tree breeding. This paper examines, through stochastic simulation, the potential benefits of genomic selection ( ...

Abstract	Genomic selection is a proven technology in animal and plant breeding to accelerate genetic gain, but as yet is to be fully realised in forest tree breeding. This paper examines, through stochastic simulation, the potential benefits of genomic selection (GS) over forward selection (FS) in a typical conifer breeding program. Methods of speeding the deployment of selected material were also considered, including top-grafting onto mature seed orchard ortets, using additional replicates of clones in archives for crossing, and embryogenesis and clonal propagation. Genetic gain per generation was found to increase considerably when the size of the training population was larger (800 c.f. 3000 clones), or when the heritability was higher (0.2 c.f. 0.5). The largest genetic gain, of 24% was achieved where large training populations (3000 clones) and high heritability traits (0.5) were combined. The accuracy of genomic breeding values (GEBVs) increased with the increase in the number of clones in the training population, the heritability of the trait and the density of the SNP markers. Calculated accuracies of simulated GEBVs and genetic gain per unit of time suggested that 2000 clones in the training population is the minimum size for effective genomic selection for conifers. Compared with forward selection, genomic selection with 2000 clones in the training population, and a 60K SNP panel, an increase of 1.58 mm per year in diameter-at-breast-height (DBH) and 2.44 kg/m3 per year for wood density can be expected. After one generation (9-years), this would be equivalent to 14.23 mm and 21.97 kg/m3 for DBH and wood density respectively. Deploying clones of the selected individuals always resulted in higher additional genetic gain than deploying progeny/seedlings. Deploying genetic material selected from genomic selection with top-grafting for early coning appeared to be the best option. Application of genomic selection to conifer breeding programs, combined with deployment tools such as top-grafting and embryogenesis are ...
Keywords	Medicine ; R ; Science ; Q
Subject code	590
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Chasing genetic correlation breakers to stimulate population resilience to climate change

Jaroslav Klápště / Emily J Telfer / Heidi S Dungey / Natalie J Graham

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 16

Abstract: Abstract Global climate change introduces new combinations of environmental conditions, which is expected to increase stress on plants. This could affect many traits in multiple ways that are as yet unknown but will likely require the modification of ... ...

Abstract	Abstract Global climate change introduces new combinations of environmental conditions, which is expected to increase stress on plants. This could affect many traits in multiple ways that are as yet unknown but will likely require the modification of existing genetic relationships among functional traits potentially involved in local adaptation. Theoretical evolutionary studies have determined that it is an advantage to have an excess of recombination events under heterogeneous environmental conditions. Our study, conducted on a population of radiata pine (Pinus radiata D. Don), was able to identify individuals that show high genetic recombination at genomic regions, which potentially include pleiotropic or collocating QTLs responsible for the studied traits, reaching a prediction accuracy of 0.80 in random cross-validation and 0.72 when whole family was removed from the training population and predicted. To identify these highly recombined individuals, a training population was constructed from correlation breakers, created through tandem selection of parents in the previous generation and their consequent mating. Although the correlation breakers showed lower observed heterogeneity possibly due to direct selection in both studied traits, the genomic regions with statistically significant differences in the linkage disequilibrium pattern showed higher level of heretozygosity, which has the effect of decomposing unfavourable genetic correlation. We propose undertaking selection of correlation breakers under current environmental conditions and using genomic predictions to increase the frequency of these ’recombined’ individuals in future plantations, ensuring the resilience of planted forests to changing climates. The increased frequency of such individuals will decrease the strength of the population-level genetic correlations among traits, increasing the opportunity for new trait combinations to be developed in the future.
Keywords	Medicine ; R ; Science ; Q
Subject code	333
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Genomics-Enabled Management of Genetic Resources in Radiata Pine

Jaroslav Klápště / Ahmed Ismael / Mark Paget / Natalie J. Graham / Grahame T. Stovold / Heidi S. Dungey / Gancho T. Slavov

Forests, Vol 13, Iss 282, p

2022 Volume 282

Abstract: Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) ... ...

Abstract	Traditional tree improvement is cumbersome and costly. Our main objective was to assess the extent to which genomic data can currently accelerate and improve decision making in this field. We used diameter at breast height (DBH) and wood density (WD) data for 4430 tree genotypes and single-nucleotide polymorphism (SNP) data for 2446 tree genotypes. Pedigree reconstruction was performed using a combination of maximum likelihood parentage assignment and matching based on identity-by-state (IBS) similarity. In addition, we used best linear unbiased prediction (BLUP) methods to predict phenotypes using SNP markers (GBLUP), recorded pedigree information (ABLUP), and single-step “blended” BLUP (HBLUP) combining SNP and pedigree information. We substantially improved the accuracy of pedigree records, resolving the inconsistent parental information of 506 tree genotypes. This led to substantially increased predictive ability (i.e., by up to 87%) in HBLUP analyses compared to a baseline from ABLUP. Genomic prediction was possible across populations and within previously untested families with moderately large training populations ( N = 800–1200 tree genotypes) and using as few as 2000–5000 SNP markers. HBLUP was generally more effective than traditional ABLUP approaches, particularly after dealing appropriately with pedigree uncertainties. Our study provides evidence that genome-wide marker data can significantly enhance tree improvement. The operational implementation of genomic selection has started in radiata pine breeding in New Zealand, but further reductions in DNA extraction and genotyping costs may be required to realise the full potential of this approach.
Keywords	tree breeding ; pedigree reconstruction ; genomic selection ; genomic prediction ; single-step BLUP ; Pinus radiata ; Plant ecology ; QK900-989
Subject code	006
Language	English
Publishing date	2022-02-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Genotype by environment interaction for growth and Dothistroma resistance and clonal connectivity between environments in radiata pine in New Zealand and Australia.

Yongjun Li / Heidi S Dungey / Mike Carson / Sue Carson

PLoS ONE, Vol 13, Iss 10, p e

2018 Volume 0205402

Abstract: Twenty-eight clonal trials of radiata pine planted across Australia and New Zealand were used to investigate genetic variation and genotype by environment (G×E) interaction for diameter-at-breast-height (DBH), height and Dothistroma resistance (DO_R). ... ...

Abstract	Twenty-eight clonal trials of radiata pine planted across Australia and New Zealand were used to investigate genetic variation and genotype by environment (G×E) interaction for diameter-at-breast-height (DBH), height and Dothistroma resistance (DO_R). The average narrow-sense heritabilities were 0.11, 0.21 and 0.30 while the average broad-sense heritabilities were 0.27, 0.34 and 0.40 for DBH, height and Dothistroma resistance, respectively. Dothistroma resistance was assessed as the percentage of needles that were not affected by Dothistroma needle blight. G×E interactions were analysed using an approximate reduced factor analytic model. Apparent G×E interactions were estimated for DBH, height and Dothistroma resistance. Estimates of G×E interactions and their standard errors were strongly influenced by the level of connectivity between trials, in terms of common clones and common parents. When there was sufficient connectivity between trials (more than 30% common clones between trials), a high level of G×E interaction was found for DBH and height but not for Dothistroma resistance. In two simulated clonal trials planted in two environments, low connectivity between environments resulted in a lower estimated genetic correlation between environments with an increased standard error. These results suggest that the number of clones in common between clonal trials is a key factor for inclusion in future experimental designs for estimating G×E interaction. When designing clonal trials for use in multiple environments for accurately estimating the level of G×E, if the resource for creating connectivity between environments is limited, at least 30% of the clones need to be in common between environments.
Keywords	Medicine ; R ; Science ; Q
Subject code	630
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Use of “Genotyping-by-Sequencing” to Recover Shared Genealogy in Genetically Diverse Eucalyptus Populations

Jaroslav Klápště / Rachael L. Ashby / Emily J. Telfer / Natalie J. Graham / Heidi S. Dungey / Rudiger Brauning / Shannon M. Clarke / Ken G. Dodds

Forests, Vol 12, Iss 904, p

2021 Volume 904

Abstract: The recovery of genealogy in both natural and captive populations is critical for any decision in the management of genetic resources. It allows for the estimation of genetic parameters such as heritability and genetic correlations, as well as defining ... ...

Abstract	The recovery of genealogy in both natural and captive populations is critical for any decision in the management of genetic resources. It allows for the estimation of genetic parameters such as heritability and genetic correlations, as well as defining an optimal mating design that maintains a large effective population size. We utilised “genotyping-by-sequencing” (GBS) in combination with bioinformatics tools developed specifically for GBS data to recover genetic relatedness, with a focus on parent-offspring relationships in a Eucalyptus nitens breeding population as well as recognition of individuals representing other Eucalyptus species and putative hybrids. We found a clear advantage on using tools specifically designed for data of highly variable sequencing quality when recovering genetic relatedness. The parent-offspring relatedness showed a significant response to data filtering from 0.05 to 0.3 when the standard approach ( G1 ) was used, while it oscillated around 0.4 when the specifically designed method ( G5 ) was implemented. Additionally, comparisons with commonly used tools demonstrated vulnerability of the relatedness estimates to incorrect imputation of missing data when shallow sequencing information and genetically distant individuals are present in the population. In turn, these biased imputed genotypes negatively affected the estimation of genetic relatedness between parents and offspring. Careful filtering for both genetic outliers and shallowly sequenced markers led to improvements in estimations of genetic relatedness. Alternatively, a method that avoided missing data imputation and took sequence depth into consideration improved the accuracy of parent-offspring relationship coefficients where sequencing data quality was highly variable.
Keywords	genotyping-by-sequencing ; Eucalyptus ; genetic relatedness ; genotyping errors ; Plant ecology ; QK900-989
Subject code	310
Language	English
Publishing date	2021-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Genotype by environment interactions in forest tree breeding: review of methodology and perspectives on research and application

Li, Yongjun / Mari Suontama / Rowland D. Burdon / Heidi S. Dungey

Tree genetics & genomes. 2017 June, v. 13, no. 3

2017

Abstract: Genotype by environment interaction (GÃE) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. ...

Abstract	Genotype by environment interaction (GÃE) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. GÃE can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of GÃE, the role of environments in generating GÃE and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying GÃE: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of GÃE for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of GÃE tend to be reported for growth traits, with low levels of GÃE for form traits and wood properties. Finally, we discuss possible ways of exploiting GÃE to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rank-change interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of GÃE on tree breeding, some environmental factors that cause GÃE and the strategies for dealing with GÃE in tree breeding, and the future role of genomics.
Keywords	Eucalyptus ; Pinus ; Pseudotsuga menziesii ; analytical methods ; breeding programs ; environmental factors ; forest trees ; forests ; genetic improvement ; genetic variation ; genomics ; genotype ; genotype-environment interaction ; growth traits ; heritability ; models ; tree breeding ; wood properties
Language	English
Dates of publication	2017-06
Size	p. 60.
Publishing place	Springer Berlin Heidelberg
Document type	Article
Note	Review
ZDB-ID	2180926-4
ISSN	1614-2950 ; 1614-2942
ISSN (online)	1614-2950
ISSN	1614-2942
DOI	10.1007/s11295-017-1144-x
Database	NAL-Catalogue (AGRICOLA)

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Article: Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

Dash, Jonathan P / Grant D. Pearse / Heidi S. Dungey / Marie Heaphy / Michael S. Watt

ISPRS journal of photogrammetry and remote sensing. 2017 Sept., v. 131

2017

Abstract: Research into remote sensing tools for monitoring physiological stress caused by biotic and abiotic factors is critical for maintaining healthy and highly-productive plantation forests. Significant research has focussed on assessing forest health using ... ...

Abstract	Research into remote sensing tools for monitoring physiological stress caused by biotic and abiotic factors is critical for maintaining healthy and highly-productive plantation forests. Significant research has focussed on assessing forest health using remotely sensed data from satellites and manned aircraft. Unmanned aerial vehicles (UAVs) may provide new tools for improved forest health monitoring by providing data with very high temporal and spatial resolutions. These platforms also pose unique challenges and methods for health assessments must be validated before use. In this research, we simulated a disease outbreak in mature Pinus radiata D. Don trees using targeted application of herbicide. The objective was to acquire a time-series simulated disease expression dataset to develop methods for monitoring physiological stress from a UAV platform. Time-series multi-spectral imagery was acquired using a UAV flown over a trial at regular intervals. Traditional field-based health assessments of crown health (density) and needle health (discolouration) were carried out simultaneously by experienced forest health experts. Our results showed that multi-spectral imagery collected from a UAV is useful for identifying physiological stress in mature plantation trees even during the early stages of tree stress. We found that physiological stress could be detected earliest in data from the red edge and near infra-red bands. In contrast to previous findings, red edge data did not offer earlier detection of physiological stress than the near infra-red data. A non-parametric approach was used to model physiological stress based on spectral indices and was found to provide good classification accuracy (weighted kappa=0.694). This model can be used to map physiological stress based on high-resolution multi-spectral data.
Keywords	data collection ; discoloration ; disease outbreaks ; environmental factors ; forest health ; forest plantations ; herbicides ; models ; monitoring ; multispectral imagery ; Pinus radiata ; remote sensing ; satellites ; time series analysis ; trees ; unmanned aerial vehicles
Language	English
Dates of publication	2017-09
Size	p. 1-14.
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1007774-1
ISSN	0924-2716
ISSN	0924-2716
DOI	10.1016/j.isprsjprs.2017.07.007
Database	NAL-Catalogue (AGRICOLA)

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Article: Assessing Very High Resolution UAV Imagery for Monitoring Forest Health During a Simulated Disease Outbreak

Dash, Jonathan P / Michael S. Watt / Grant D. Pearse / Marie Heaphy / Heidi S. Dungey

ISPRS Journal of Photogrammetry and Remote Sensing. 2017,

2017

Abstract	Research into remote sensing tools for monitoring physiological stress caused by biotic and abiotic factors is critical for maintaining healthy and highly-productive plantation forests. Significant research has focussed on assessing forest health using remotely sensed data from satellites and manned aircraft. Unmanned aerial vehicles (UAVs) may provide new tools for improved forest health monitoring by providing data with very high temporal and spatial resolutions. These platforms also pose unique challenges and methods for health assessments must be validated before use. In this research, we simulated a disease outbreak in mature Pinus radiata (D.Don) trees using targeted application of herbicide. The objective was to acquire a time-series simulated disease expression dataset to develop methods for monitoring physiological stress from a UAV platform. Time-series multi-spectral imagery was acquired using a UAV flown over a trial at regular intervals. Traditional field-based health assessments of crown health (density) and needle health (discolouration) were carried out simultaneously by experienced forest health experts. Our results showed that multi-spectral imagery collected from a UAV is useful for identifying physiological stress in mature plantation trees even during the early stages of tree stress. We found that physiological stress could be detected earliest in data from the red edge and near infra-red bands. In contrast to previous findings, red edge data did not offer earlier detection of physiological stress than the near infra-red data. A non-parametric approach was used to model physiological stress based on spectral indices and was found to provide good classification accuracy (weighted kappa = 0.694). This model can be used to map physiological stress based on high-resolution multi-spectral data.
Keywords	Pinus radiata ; data collection ; discoloration ; disease outbreaks ; environmental factors ; experts ; forest health ; forest plantations ; herbicides ; models ; monitoring ; multispectral imagery ; remote sensing ; satellites ; time series analysis ; trees ; unmanned aerial vehicles
Language	English
Size	p. .
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ZDB-ID	1007774-1
ISSN	0924-2716
ISSN	0924-2716
DOI	10.1016/j.isprsjprs.2017.07.007
Database	NAL-Catalogue (AGRICOLA)

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Article: Quantification of realised genetic gain in radiata pine and its incorporation into growth and yield modelling systems

Kimberley, Mark O / John R. Moore / Heidi S. Dungey

Canadian journal of forest research =. 2015 Sept. 2, v. 45, no. 12

2015

Abstract: Realised genetic gain for radiata pine (Pinus radiata D. Don) was estimated using data from 46 installations of three series of block-plot trials spanning a wide range of site types throughout New Zealand. These trials contained 63 unique seedlots with ... ...

Abstract	Realised genetic gain for radiata pine (Pinus radiata D. Don) was estimated using data from 46 installations of three series of block-plot trials spanning a wide range of site types throughout New Zealand. These trials contained 63 unique seedlots with different levels of genetic improvement. Realised genetic gain was quantified using two measures of productivity: site index and 300 Index (a measure of volume productivity). The level of genetic improvement of each seedlot was determined by its GF Plus rating, a genetic rating system based on breeding values used for New Zealand radiata pine. There was a positive relationship between GF Plus rating and both productivity measures. Differences of 25% in total standing volume at age 30 years and of 5.6% in site index were found between unimproved (GF Plus 9.9) and highly improved (GF Plus 25) seedlots. Each unit increase in GF Plus rating was associated with a 1.51% increase in volume growth rate. In absolute terms, the magnitude of the increase was greater on more productive sites compared with less productive sites, although in percentage terms, it varied little between sites or regions. Quantification of genetic gain in this manner enables it to be easily incorporated into existing growth and yield simulators.
Keywords	Pinus radiata ; breeding value ; genetic improvement ; models ; site index ; realised genetic gain ; growth modelling ; tree improvement ; block plots ; genotypeâenvironment interaction ; New Zealand
Language	English
Dates of publication	2015-0902
Size	p. 1676-1687.
Publishing place	NRC Research Press
Document type	Article
ZDB-ID	1473096-0
ISSN	1208-6037 ; 0045-5067
ISSN (online)	1208-6037
ISSN	0045-5067
DOI	10.1139/cjfr-2015-0191
Database	NAL-Catalogue (AGRICOLA)

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Article: Assessing the genetic variation of tolerance to red needle cast in a Pinus radiata breeding population

Graham, Natalie J / Heidi S. Dungey / Jaroslav Klápště / Mari Suontama / Martin K.-F. Bader / Nari M. Williams / Tony Pleasants / Yongjun Li

Tree genetics & genomes. 2018 Aug., v. 14, no. 4

2018

Abstract: Breeding for disease resistance or tolerance is a viable option for disease management programmes and is important for the continued success and resilience of planted forests. Red needle cast (RNC) is a disease that affects radiata pine (Pinus radiata) ... ...

Abstract	Breeding for disease resistance or tolerance is a viable option for disease management programmes and is important for the continued success and resilience of planted forests. Red needle cast (RNC) is a disease that affects radiata pine (Pinus radiata) and is caused by Phytophthora pluvialis. Knowledge is still very limited regarding the potential for genetic tolerance to this pathogen. The application of controlled screening techniques is clearly required. Using a detached needle assay, we screened 392 clonally replicated individuals (clones) from an elite P. radiata population for quantitative tolerance to RNC. Data was highly skewed and required logarithmic data transformation and Poisson distributions for the estimation of best linear unbiased predictions. These estimates revealed a broad range in susceptibility/tolerance to RNC, and enabled the identification of clones that were clearly susceptible and clones that were clearly tolerant. There was a high correlation between the number and length of lesions that developed in response to inoculation with P. pluvialis. Broad-sense heritability estimates were low to moderate, indicating that there is potential for improving tolerance through breeding. These results provide evidence that breeding for tolerance to P. pluvialis is possible, although continued work into understanding and minimising causes for variance are required.
Keywords	breeding ; clones ; disease control ; disease resistance ; forests ; genetic variation ; heritability ; pathogens ; Phytophthora ; Pinus radiata ; Poisson distribution ; prediction ; screening ; variance
Language	English
Dates of publication	2018-08
Size	p. 55.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	2180926-4
ISSN	1614-2950 ; 1614-2942
ISSN (online)	1614-2950
ISSN	1614-2942
DOI	10.1007/s11295-018-1266-9
Database	NAL-Catalogue (AGRICOLA)

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