Finding loci associated to partial resistance to white pine blister rust in sugar pine (Pinus lambertiana Dougl.).

Abstract

White pine blister rust (WPBR) is an exotic disease threatening five-needle pines in North America. In spite of its relatively recent introduction, some five-needle pines such as sugar pine (Pinus lambertiana) have developed both complete (major) gene resistance and partial (quantitative) resistance to WPBR. While significant effort has been dedicated to clone and locate the position of the major gene of WPBR resistance in sugar pine, the genetic basis of quantitative resistance remains largely unknown in all Strobus pines. In this work, we took a preliminary approach to identify potential genotype × phenotype associations using the results of long-term survival and symptoms of infection in both experimental and applied breeding populations. Our study found significant associations between several genes and WPBR disease symptoms such as normal active cankers and blights, important symptoms in the development of partial resistance. No significant associations were found with percentage of survival, probably due to the complex inheritance of the disease and long time to infection. With this study, we hope to lay the ground for further genome-wide association studies using large phenotypic data sets in sugar pine and other Strobus pines.

Introduction

White pine blister rust (WPBR), caused by the fungal pathogen Cronartium ribicola J.C. Fisch, has caused severe economic and ecological loss in five-needle pines around the world (Kim et al. 2010; Zhang et al. 2010; Liu et al. 2015). Since its arrival to North America in early 1900s, WPBR has infected and threatened natural populations of at least nine five-needle pine species (McDonald and Hoff 2001). Species such as western white pine (Pinus monticola Dougl.), limber pine (P. flexilis James), and whitebark pine (P. albicaulis Engelm.) have suffered severe mortality, and some populations have been reduced up to 90% of their original distribution due to WPBR infection (Kinloch 2003; Liu et al. 2015). Despite the relatively recent WPBR introduction to North America, species such as sugar pine (P. lambertiana), western white pine (P. monticola), eastern white pine (P. strobus), whitebark pine (P. albicaulis), and limber pine (P. flexilis) have some natural resistance to the pathogen (Sneizko et al. 2014).

Two types of resistance to WPBR have been recognized in pines: the complete resistance or major gene resistance (monogenic) and the incomplete or partial resistance (polygenic) (Zambino and McDonald 2004). In a complete resistance, a hypersensitive response is developed. After inoculation and infection of the host, the fungus is subsequently sequestered in necrotic lesions and later killed inside the tree. Mendelian segregation of the major gene resistance suggests a single dominant allele for resistance in sugar pine (Cr1), western white pine (Cr2), southwestern white pine (Cr3), and limber pine (Cr4) (Kinloch and Dupper 2002; Sniezko et al. 2014; Liu et al. 2017). For the partial or incomplete resistance, the pine species shows a set of resistance mechanisms called slow-rusting resistance (SRR) that is quantitatively inherited. Slow-rusting resistance occurs at moderate to low frequencies within host families. Even though branches and stems become infected, and symptoms of infection may last for years, growth of the fungus is halted within woody tissue, and the fungus is eventually killed. Although partial resistance mechanisms have been documented on some five-needle pines, their genetic basis remains unknown (Sniezko et al. 2014).

C. ribicola causes different phenotypes on trees that in one classification system have been given five general infection symptoms (Kinloch and Littlefield 1977; Sniezko et al. 2000). The normal reaction (N) is characterized by an active canker, usually accompanied by swelling that could produce fungal spores. Infected trees may develop bark reactions, where cankers with a diamond shape are observed on limbs or the bole. Bark reaction cankers could be both abortive without a clear signal of living rust (BR), or with some active mycelial growth (normal bark reaction; NBR). In some cases, infection on limbs induces self-pruning of the branch, stopping canker growth, and leaving a signal of blight (BL). Blight reactions can be partial or incomplete (NBL) with persisting mycelial activity and where spore production can be observed (Kinloch and Littlefield 1977; Maloy 2003).

Sugar pine (Pinus lambertiana Dougl.) is an important component of the California flora, growing in a variety of habitats throughout the Cascade Range in Oregon to as far south as Northern Baja California, Mexico, with the majority of its range occurring within the mixed conifer forest of the Sierra Nevada (Eckert et al. 2015; Vangestel et al. 2016). Its abundance, large stature, and clear wood properties give it commercial importance in the lumber industry. However, this species has been declining due to change in forest structure and dynamics relating to fire suppression, climate change, and the moderate to low levels of genetic resistance against the invasive white pine blister rust (Van Mantgem et al. 2004; Tomback and Achuff 2010; Maloney et al. 2011).

While significant effort has been dedicated to clone and locate the position of the major gene of WPBR resistance in sugar pine (Devey et al. 1995; Harkins et al. 1998; Jermstad et al. 2006; Jermstad et al. 2011; Stevens et al. 2016), the genetic basis of quantitative resistance remains largely unknown. In this work, we took a preliminary approach to identify potential genotype × phenotype associations in WPBR partial resistance by using the results of long-term survival and symptoms of infection in experimental and breeding populations. By doing this, we also aim to test the potential for different disease phenotypes (survival and symptoms) to accurately dissect genotype × phenotype associations, and the transferability of the results in this small-scale study to an ongoing large-scale genome-wide analysis (GWAS) in sugar pine.

Material and methods

Experimental design

Two different experimental designs were evaluated in this study. For the sake of simplicity, we will call them “Association” and “Mapping” designs. In the Association design, seedlings from unrelated individuals from populations across California were collected, planted, and naturally infected with a vCr1 strain of blister rust in a common garden at the experimental field in Happy Camp, California in year 1986. Every 2–3 years, survival and signals of infection were evaluated. Frequency distribution of survival showed a bimodal distribution with biased survival for trees younger than 15 years. For this reason, we focused in the percentage of survival in families tested over 15 years or more. In addition, we selected families with progenies larger than eight siblings, resulting in a selection of 230 families from a total of 1000. Two survival traits were evaluated, SUR1 is defined as the number of individuals that survive WPBR infection, and the second one, SUR2 is defined as the number of individuals that survive WPBR infection and associated symptoms (see below).

In the Mapping design, 93 individuals were selected from a controlled-cross two-generation full-sib population of 972 individuals naturally infected with a vCr1 strain of blister rust in Happy Camp, California. Unaffected and affected cases were selected, considering affected trees on the basis of the incidence of one or more different infection symptoms (Supplementary Material, Table S1). The Mapping experimental design was previously created for the genetic mapping of quantitative trait locus (QTL) conferring partial resistance in sugar pine (Jermstad et al. 2011). No replicates were included in the design. Phenotypes of young trees (15 years) under infection were quantified considering five different symptoms: normal active cankers (N), normal active blights (NBL), normal bark reaction (NBR), blights (BL), and bark reactions (BR).

Sample collection and DNA extraction

For individuals from the Association design, seeds from the same mother tree stored in a bank seed at the Institute of Forest Genetics, Placerville, CA, were collected. Eight megagametophytes (haploid maternal tissue) from every mother were used to reconstruct the genotype, following previous work from Krutovsky et al. (2009). Prior to DNA extraction, seeds were soaked in 3% hydrogen peroxide at 4 °C for 2 days, and then megagametophytes were dissected from each seed. DNA was extracted from megagametophytes through a 2-day protocol, involving 1 day of lysis and incubation at 65 °C followed by a second day of column extraction with the Qiagen DNeasy mini-prep Plant kit. DNA concentration was quantified using picogreen on a Qubit. For individuals from the Mapping design, needles were collected, dried, and DNA was extracted with the same protocol used for megagametophytes.

SNP selection and genotyping

Individuals were genotyped using an Illumina GoldenGate SNP Genotyping Assay at the DNA technologies Core in the UC Davis Genome Center. For this assay, we selected a total of 384 SNPs. A subset of 359 SNPs was previously discovered and tested in an oligo pool assay (Jermstad et al. 2011), choosing those SNPs located in genes associated with biotic stress and general stress response (Supplementary Material Table S2). An additional set of 25 SNPs for specific disease-resistance genes was included in the assay. These SNPs were discovered from a preliminary needle transcriptome assembly for P. lambertiana and were later visually inspected using the Integrative Genomics Viewer 2.3 (IGV) (Supplementary Material Table S2). Probes designed on flanking regions were tested bioinformatically against P. taeda genome (http://treegenesdb.org), to filter probes that were non-specific or likely to appear in paralogous or intronic regions. Genotype calls were obtained as described in Vangestel et al. 2016. Mendelian segregation ratios were tested for all SNPs, and those showing deviations were excluded for further analyses (Supplementary Material Table S3). Genotype calls were conducted as described in Vangestel et al. (2016). After quality filtering and exclusion of monomorphic loci, 186 SNPs were selected for the association analyses of the population from the Association design, and 104 for the Mapping population analyses (Supplementary Material Table S2).

Statistical tests

For the Mapping design, associations among the five symptoms under infection were tested separately using case-control approaches on PLINK (Purcell et al., 2007). Associations between the minor frequency of the allele (MAF), frequency of alternate alleles or genotypes, with cases on the full-sib family were examined with a chi-square test and a Fisher exact test and corrected P values were obtained with gene-dropping permutation option on PLINK.

For the Association design, we examined the relationship between genotypes and survival using general linear models (GLM) implemented in TASSEL (Bradbury et al. 2007). GLMs were controlled by population structure by using a Q-matrix. Population structure was assessed using STRUCTURE version 2.3.2 (Pritchard et al. 2000). The admixture model with a putative number of clusters (K) from one to ten was run with a burn-in of 100,000 and 200,000 Markov chain Monte Carlo repetitions. Each run was replicated ten times to estimate delta K using the method developed by Evanno et al. (2005) with the program STRUCTURE HARVESTER version v0.6.94 (Earl and VonHoldt 2012). In addition, a principal component analysis (PCA) was run with the R package adegenet (Jombart and Ahmed 2011). Bonferroni-Holm correction for multiple testing was applied to the P values resulting from the Association tests in TASSEL. In addition, a Kruskal-Wallis test was applied to identify significant differences in the medians of survival among genotypes. The position of all SNPs in the genome was assessed via Gmap (Wu and Watanabe 2005).

Results

Mapping design

Phenotypes of young trees under infection were quantified considering five different symptoms: normal active cankers (N), normal active blights (NBL), normal bark reaction (NBR), blights (BL), and bark reactions (BR). More than 50% of trees showed no signal of infection, and the most frequent symptom (in approximately 30% of trees) was the presence of normal active cankers overlapping with other symptoms. There were no significant correlations between symptom occurrences, even though bark reactions were more frequently not overlapped with other symptoms (data not shown). Bark reactions may indicate greater resistance than other symptoms such as normal cankers, although trees affected by BR may develop other symptoms as they grow older (R. Sniezko, personal communication). In any case, we did not find a correlation between the different infection symptoms and the stage of infection. Whether each symptom has a different genetic basis is yet to be demonstrated. Long-term assessment could yield to clearer patterns of relationships among symptoms.

Associations between genetic variation with affected individuals for each symptom were detected through distribution of the minor allele frequency (MAF) in affected cases and using full model association tests, to recognize association of genotypes with symptoms. Case/control associations of minor allele frequency with affected vs. unaffected cases, using a chi-square and a Fisher exact test revealed 20 significant allele frequency associations from 12 genes (Supplementary Material Table S4), even though only four SNPs (from three genes) were significantly associated with N and BL (Table 1) after correction of P values for multiple testing. None of the alternate alleles and genotype association tests retrieved significant P-adjusted values (data not shown). Significantly associated SNPs showed presence of the dominant resistant allele, and their minor allele frequencies ranged from 0.21 to 0.26 (Table 1). Alignment to the reference genome of sugar pine v1.0 (https://dendrome.ucdavis.edu/treegenes) suggests these genes are widely distributed, although a linkage map is necessary to define locations in the currently fragmented genome assembly. Our results indicate that SNP CL635Contig1_01-newSnpIndex_70 was significantly associated to N and NBL symptoms (Table 1). After P value correction for multiple testing, this SNP remained associated to normal active cankers. SNPs 2_6596_01-newSnpIndex_325, 0_4054_02-oldSnpPosition_225, and 0_4054_02-oldSnpPosition_65 were significantly associated to BL (Table 1, Fig. 1). It is worth to mention that a second SNP for the gene 2_6596_01 showed association between unaffected cases and the heterozygous genotypes (P = 0.020), even though this SNP did not pass the P-adjusted test.

Table 1 Significant association of SNPs with affected individuals with normal active cankers and blights. Results came from the Mapping Design
Fig. 1
figure1

Number of allelic counts by phenotype for significant associated SNPs. A and B denote the different alleles present in each gene. Results came from the Mapping Design

Association design

General linear models were controlled by population structure by using a population structure matrix Q. Results of the Evanno test suggested a K = 2 (Supplementary Material Fig. S1); and the PCA analysis suggested no significant population structure was present in the data set (Supplementary Material Fig. S2). Kruskal-Wallis analyses revealed a significant difference in survival among genotypes in 16 genes (Supplementary Material Table S5). Most of these genes were also found associated with either SUR1 or SUR2, as result of the GLM analyses in TASSEL (Supplementary Material Table S6). However, when P values were adjusted for multiple comparisons, these genes were no longer significant.

Discussion

Conifers are dominant species in most boreal and temperate forests on the planet and several species of this group also play important roles in other ecosystems (Gernandt and Vázquez-Lobo 2014). Alas, anthropogenic disturbance such as climate change and movement of alien species for international trade could be the cause of an increase of new diseases in forest ecosystems (Stenlid et al. 2011), as is the case of the introduction of WPBR to North America. An important step to learn to control the rise of new diseases is to know which are the natural defenses of hosts. Despite its ecological and economic importance, the development of knowledge in genetics and genomics for conifers has been slow in contrast to flowering plants. In sugar pine, the reference genome and transcriptome were published very recently (Stevens et al. 2016; Gonzalez-Ibeas et al. 2016). Due to the long generation times and huge dimensions of conifer trees, experimental populations for studies that allow statistical association between genotype and phenotype while controlling environmental variation, are uncommon. For this reason, long-term trials such the U.S. Forest Service field testing site in the Siskiyou Mountains near Happy Camp, California, are an excellent opportunity to study complex phenotypes in replicated genetic tests.

Different approaches have been used to identify the genetic mechanisms underlying complete resistance to WPBR in different pine species. Through genetic mapping, it has been possible to identify the position of the Cr genes for different pine species (Jermstad et al. 2011; Liu et al. 2016; Liu et al. 2017), which has shown the lack of synteny between these loci, highlighting that the defense mechanisms in pines against C. ribicola have evolved independently, probably before the introduction of C. ribicola into North America (Liu et al. 2016). Complete resistance can be overcome by a change in the pathogen whereas partial resistance is long lasting, involving numerous plant responses controlled by multiple genes with inconsistent effects (Poland et al. 2009). Given that this resistance could involve different mechanisms in plants, it has a low heritability and particularly in P. lambertiana has an inconsistent transmission (Kinloch et al. 2008).

Both QTL and Association Mapping aim to identify loci underlying quantitative characters through tests of marker-trait associations. The difference relies in that in the QTL analysis there are few opportunities for recombination in pedigrees with no ancestry; whereas in Association Mapping there has been numerous opportunities for historical recombination and genetic variation to accumulate, resulting in high-resolution mapping (Zhu et al. 2008). In this research, we take advantage of the Association Mapping using two different designs, one at the family level looking for genetic association with symptoms (mapping design), and another at the population level evaluating survivorship of unrelated trees (association design). The reasoning behind the use of different phenotypic approaches was based on the availability of the datasets. Through case-control analyses, we found one gene associated to normal active cankers and other two genes associated to blight case phenotypes (Table 1). These genes’ annotations suggest they could be involved in plant responses to biotic stress. Sequence CL635Contig1 contains an ATPase AAA domain, which belongs to a superfamily of proteins that has been associated to cell death and hypersensitive responses in plants (Sugimoto et al. 2004; Zhang et al. 2014). Erythronate-4-phosphate dehydrogenase-like protein is associated with vitamin B6 biosynthesis (Titiz et al. 2006), which in turn has been related with plant defense response in Nicotiana tabacum (Solanaceae), through modulation of active oxygen species (Denslow et al. 2005). Two SNPs were located in a gene containing a DUF789 domain, which has been detected differentially expressed between a wild-type Oryza sativa (Poaceae) and a mutant line resistant to bacterial blight, caused by Xanthomonas oryza pv. oryzae (Yi et al. 2013).

The lack of significant associations with the survivorship of families under C. ribicola infection for the association design could be attributed to different causes. First of all, due to the complexity of the WPBR quantitative resistance, the percentage of survival may not be a good phenotypic trait to measure genotype × phenotype associations. The so-called “slow-rust” takes years to develop and several years to kill a tree, therefore the percentage of survival will depend on the year the trait was evaluated, as a tree considered “healthy” in 1 year may die a few years later because of infection. In this sense, the use of different infection symptoms has proven to be a much more useful method to detect genotype × phenotype associations in this study. Results from this study suggest a more detailed phenotyping in combination with a large number of unrelated families may increase the power of the GWAS analysis in the Association design. In addition, even though the environmental effect is controlled in common gardens, so that the phenotypes will reflect the genotypes; there is some uncertainty when trying to estimate the genotype of the mother when evaluating the phenotype of the progeny, as occurred in the association design. Although imperfect, this method is extremely valuable as infection of natural populations is unthinkable for obvious ecological reasons. Unfortunately, we cannot test the power of either the Mapping or Association designs or the different phenotyping methods, as we do not have direct comparisons.

Association mapping analyses take advantage of the ancestral recombination events of natural populations to detect with accuracy loci relying phenotypes (Flint-García et al. 2005), for this purpose numerous allelic markers should be considered to find associations. In widely distributed and highly outcrossing conifer species, a large number of markers are required to study polygenic traits due to the rapid decay of linkage disequilibrium. In spite of the relatively small number of genes in a genome-wide context, our study was able to find three genes significantly associated with WPBR quantitative resistance, laying the ground for further large-scale GWAS studies on disease resistance. Ongoing GWAS studies based on whole genome re-sequencing data should allow a finer dissection of the genomic basis of WPBR quantitative resistance in sugar pine.

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Acknowledgements

We would like to thank the U.S. Forest Service sugar pine breeding program in California for establishing the Mapping population used in this study. AVL was supported by a UC MEXUS-CONACyT Postdoctoral fellowship.

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Correspondence to Amanda R. De La Torre.

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SNP sequences will be submitted to Tree Genes database (http://treegenesdb.org) and accession numbers will be supplied once available, prior to final acceptance of the manuscript.

Communicated by S. C. González-Martínez

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Vázquez-Lobo, A., De La Torre, A.R., Martínez-García, P.J. et al. Finding loci associated to partial resistance to white pine blister rust in sugar pine (Pinus lambertiana Dougl.).. Tree Genetics & Genomes 13, 108 (2017). https://doi.org/10.1007/s11295-017-1190-4

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Keywords

  • White pine blister rust
  • Sugar pine
  • Disease resistance
  • Genotype × phenotype associations