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

Graham, Natalie; Suontama, Mari; Pleasants, Tony; Li, Yongjun; Bader, Martin K.‐F.; Klápště, Jaroslav; Dungey, Heidi S.; Williams, N.

doi:10.1007/s11295-018-1266-9

Cited by 13 publications

(11 citation statements)

References 48 publications

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“…Heritability of CNC was also in broad agreement with other studies performed in New Zealand (King and Burdon, 1991;Kumar et al, 2008;Suontama et al, 2019). The heritability of RNC resistance was similar to the heritability estimates obtained previously for P. radiata in New Zealand (Dungey et al, 2014;Graham et al, 2018). These estimates of heritability indicate that a portion of the variation of disease resistance among genotypes was attributable to genetic variation and that breeding values could be predicted with reasonable accuracy to enable selection for resistant genotypes.…”

Section: Discussionsupporting

confidence: 88%

Indication of Quantitative Multiple Disease Resistance to Foliar Pathogens in Pinus radiata D.Don in New Zealand

et al. 2020

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Increasing resistance against foliar diseases is an important goal in the Pinus radiata D.Don breeding program in New Zealand, and screening for resistance has been in place for some time, since the late 1960s. The current study presents results of four progeny trials within the breeding program to investigate whether multiple disease resistance could be detected against three different needle diseases in P. radiata: Dothistroma needle blight (DNB) caused by Dothistroma septosporum, Cyclaneusma needle cast (CNC) caused by Cyclaneusma minus, and red needle cast (RNC) caused by Phytophthora pluvialis. Four progeny trials in the North Island of New Zealand were available to estimate heritabilities and between-trait genetic correlations. Two of the trials were assessed for DNB, involving 63 full-sib families. A third trial was assessed for CNC, involving 172 half-sib families, and a fourth trial was assessed for RNC, involving 170 halfsib families. Disease resistances had moderate estimates of heritability (0.28-0.48) in all trials. We investigated the potential for multiple disease resistance to the three foliar diseases by estimating genetic correlations between disease resistances using a spatial linear mixed model. The correlation between DNB and CNC resistance was favorable and strong (0.81), indicating that genotypes that are highly resistant to DNB also have a high resistance to CNC. These results suggest that selection based on resistance to DNB could allow for simultaneous indirect selection for resistance to CNC, usually only expressed at a later age. This would allow selections to be made earlier due to the earlier expression of DNB than CNC and reduce the number of expensive disease assessments being undertaken. Conversely, genetic correlation estimates for RNC with DNB and CNC were close to zero, and very imprecise. As such, later-age assessments for this disease would still be required.

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Section: Discussionsupporting

confidence: 88%

Indication of Quantitative Multiple Disease Resistance to Foliar Pathogens in Pinus radiata D.Don in New Zealand

et al. 2020

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“…In addition, screening systems where environmental conditions are controlled could be advantageous in discovering the underlying genetic signal. The use of laboratory-based assays are under development as a possible option for discovering a stronger genetic signal, although even within more controlled conditions, variation remains a challenge [59]. Detached needle based experiments are especially useful in situations where two diseases often co-occur in the field and genetic signals can be confounded, for example, Phytophthora pluvialis and Phaeocryptopus gaeumannii causing Swiss needle cast in Douglas-fir [60].…”

Section: Potential Of Genomics To Predict Host Resistancementioning

confidence: 99%

Effect of trait’s expression level on single-step genomic evaluation of resistance to Dothistroma needle blight

et al. 2020

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Background: Many conifer breeding programs are paying increasing attention to breeding for resistance to needle disease due to the increasing importance of climate change. Phenotyping of traits related to resistance has many biological and temporal constraints that can often confound the ability to achieve reliable phenotypes and consequently, reliable genetic progress. The development of next generation sequencing platforms has also enabled implementation of genomic approaches in species lacking robust reference genomes. Genomic selection is, therefore, a promising strategy to overcome the constraints of needle disease phenotyping. Results: We found high accuracy in the prediction of genomic breeding values in the disease-related traits that were well characterized, reaching 0.975 for genotyped individuals and 0.587 for non-genotyped individuals. This compared well with pedigree-based accuracies of up to 0.746. Surprisingly, poorly phenotyped disease traits also showed very high accuracy in terms of correlation of predicted genomic breeding values with pedigree-based counterparts. However, this was likely caused by the fact that both were clustered around the population mean, while deviations from the population mean caused by genetic effects did not appear to be well described. Caution should therefore be taken with the interpretation of results in poorly phenotyped traits. Conclusions: Implementation of genomic selection in this test population of Pinus radiata resulted in a relatively high prediction accuracy of needle loss due to Dothistroma septosporum compared with a pedigree-based approach. Using genomics to avoid biological/temporal constraints where phenotyping is reliable appears promising. Unsurprisingly, reliable phenotyping, resulting in good heritability estimates, is a fundamental requirement for the development of a reliable prediction model. Furthermore, our results are also specific to the single pathogen mating-type that is present in New Zealand, and may change with future incursion of other pathogen varieties. There is no doubt, however, that once a robust genomic prediction model is built, it will be invaluable to not only select for host tolerance, but for other economically important traits simultaneously. This tool will thus future-proof our forests by mitigating the risk of disease outbreaks induced by future changes in climate.

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“…the infection initiated from incoming inoculum [21], we designed a detached-needle assay, where only individual detached pine needles were inoculated and monitored for 11 days. This period has been previously demonstrated to cover the period of primary infection up to peak infection and to needle senescence [22]. To study the secondary infection by the pathogen, i.e.…”

Section: Methodsmentioning

confidence: 99%

“…Pinus radiata genotypes were preselected from the Radiata Pine Breeding Company’s Elite Clones series as published previously [22]. Four genotypes were selected for higher susceptibility and four genotypes for higher resistance to RNC, respectively.…”

Section: Methodsmentioning

confidence: 99%

Modelling the key drivers of an aerial Phytophthora foliar disease epidemic, from the needles to the whole plant

Gómez-Gallego¹,

Gommers²,

Bader³

et al. 2019

PLoS ONE

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Understanding the epidemiology of infectious diseases in a host population is a major challenge in forestry. Radiata pine plantations in New Zealand are impacted by a foliar disease, red needle cast (RNC), caused by Phytophthora pluvialis . This pathogen is dispersed by water splash with polycyclic infection affecting the lower part of the tree canopy. In this study, we extended an SI (Susceptible-Infectious) model presented for RNC to analyse the key epidemiological drivers. We conducted two experiments to empirically fit the extended model: a detached-needle assay and an in vivo inoculation. We used the detached-needle assay data to compare resistant and susceptible genotypes, and the in vivo inoculation data was used to inform sustained infection of the whole plant. We also compared isolations and real-time quantitative PCR (qPCR) to assess P . pluvialis infection. The primary infection rate and the incubation time were similar for susceptible and resistant genotypes. The pathogen death rate was 2.5 times higher for resistant than susceptible genotypes. Further, external proliferation of mycelium and sporangia were only observed on 28% of the resistant ramets compared to 90% of the susceptible ones. Detection methods were the single most important factor influencing parameter estimates of the model, giving qualitatively different epidemic outputs. In the early stages of infection, qPCR proved to be more efficient than isolations but the reverse was true at later points in time. Isolations were not influenced by the presence of lesions in the needles, while 19% of lesioned needle maximized qPCR detection. A primary infection peak identified via qPCR occurred at 4 days after inoculation (dai) with a secondary peak observed 22 dai. Our results have important implications to the management of RNC, by highlighting the main differences in the response of susceptible and resistant genotypes, and comparing the most common assessment methods to detect RNC epidemics.

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

Cited by 13 publications

References 48 publications

Indication of Quantitative Multiple Disease Resistance to Foliar Pathogens in Pinus radiata D.Don in New Zealand

Indication of Quantitative Multiple Disease Resistance to Foliar Pathogens in Pinus radiata D.Don in New Zealand

Effect of trait’s expression level on single-step genomic evaluation of resistance to Dothistroma needle blight

Modelling the key drivers of an aerial Phytophthora foliar disease epidemic, from the needles to the whole plant

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