Forest systems are increasingly threatened by emergent, exotic diseases, yet management strategies for forest trees may be hindered by long generation times and scant background knowledge. We tested whether nursery disease resistance and growth traits have predictive value for the conservation of Notholithocarpus densiflorus, the host most susceptible to sudden oak death. We established three experimental populations to assess nursery growth and resistance to Phytophthora ramorum, and correlations between nursery-derived breeding values with seedling survival in a field disease trial. Estimates of nursery traits' heritability were low to moderate, with lowest estimates for resistance traits. Within the field trial, survival likelihood was increased in larger seedlings and decreased with the development of disease symptoms. The seed-parent family wide likelihood of survival was likewise correlated with family predictors for size and resistance to disease in 2nd year laboratory assays, though not resistance in 1st year leaf assays. We identified traits and seedling families with increased survivorship in planted tanoaks, and a framework to further identify seed parents favored for restoration. The additive genetic variation and seedling disease dynamics we describe hold promise to refine current disease models and expand the understanding of evolutionary dynamics of emergent infectious diseases in highly susceptible hosts.

Abstract: Climate change is motivating a reassessment of how seeds are selected for reforestation, as rapid environmental change can lead to local maladaptation in trees. Genetic association studies and past seed source climate both have the potential to help identify appropriate planting stock, but these techniques have not been compared and tested as part of an operational planting program. In this study, we combined an analysis of single nucleotide polymorphisms (SNPs) associated with environmental gradients in sugar pine (Pinus lambertiana) with an analysis of post‐fire seedling survival and growth in a restoration experiment. Our genotype–environment association (GEA) tests of 92 individuals from varying climates within CA revealed 829 SNPs (out of 300,604) with significant association with climate gradients, especially April snowpack. Of these, 323 either had annotations that suggested potential functional importance or were identified by two different methods. We then built Bayesian models of survival and growth for all seedlings in a separate post‐fire planting experiment, to test the relative predictive ability of source elevation (a common proxy for source climate) versus the proportion of seedling alleles expected to be locally advantageous based on GEA. Across three sites within the King Fire scar in Eldorado National Forest in 2017, 2018, and 2019, 1774 seedlings were planted. Of these, 206 had enough green needles in 2020 to allow sample collection, and 161 were successfully genotyped. We found that source elevation was generally better at predicting seedling performance than genotype indices, perhaps because of the limited scope of the association analysis. Seed sources from 500 to 1800 ft (152.4–548.6 m) lower in elevation, and one seed zone further south generally performed as well or better than local seed sources. This result, and those of similar previous studies, suggest that “climate matching” using past climate information for existing seed sourcing units is a reasonable starting point for finding seedlings suited to already‐altered planting site climate conditions. However, further tests with more extensive genomic and performance data may improve the utility of genotype information for seed selection.

Climate change over the next century is predicted to cause widespread maladaptation in natural systems. This prediction, as well as many sustainable management and conservation practices, assumes that species are adapted to their current climate. However, this assumption is rarely tested. Using a large-scale common garden experiment combined with genome-wide sequencing, we found that valley oak (Quercus lobata), a foundational tree species in California ecosystems, showed a signature of adaptational lag to temperature, with fastest growth rates occurring at cooler temperatures than populations are currently experiencing. Future warming under realistic emissions scenarios was predicted to lead to further maladaptation to temperature and reduction in growth rates for valley oak. We then identified genotypes predicted to grow relatively fast under warmer temperatures and demonstrated that selecting seed sources based on their genotype has the potential to mitigate predicted negative consequences of future climate warming on growth rates in valley oak. These results illustrate that the belief of local adaptation underlying many management and conservation practices, such as using local seed sources for restoration, may not hold for some species. If contemporary adaptational lag is commonplace, we will need new approaches to help alleviate predicted negative consequences of climate warming on natural systems. We present one such approach, "genome-informed assisted gene flow," which optimally matches individuals to future climates based on genotype-phenotype-environment associations.

Phosphites have been used to control Sudden Oak Death; however, their precise mode of action is not fully understood. To study the mechanism of action of phosphites, we conducted an inoculation experiment on two open-pollinated tanoak families, previously found to be partially resistant. Stems of treatment group individuals were sprayed with phosphite, and seven days later, distal leaves were inoculated with the Sudden Oak Death pathogen Phytophthora ramorum. Leaves from treated and untreated control plants were harvested before and seven days after inoculation, and transcriptomes of both host and pathogen were analyzed. We found that tanoak families differed in the presence of innate resistance (resistance displayed by untreated tanoak) and in the response to phosphite treatment. A set of expressed genes associated with innate resistance was found to overlap with an expressed gene set for phosphite-induced resistance. This observation may indicate that phosphite treatment increases the resistance of susceptible host plants. In addition, genes of the pathogen involved in detoxification were upregulated in phosphite-treated plants compared to phosphite-untreated plants. In summary, our RNA-Seq analysis supports a two-fold mode of action of phosphites, including a direct toxic effect on P. ramorum and an indirect enhancement of resistance in the tanoak host.

As climate changes, locally adapted tree populations may become maladapted to the sites in which they presently occur. When natural adaptive processes are insufficient for populations to keep pace with changing climate, human-assisted relocation of genotypes (assisted gene flow) may be a useful tool for maintaining forest resilience. While existing empirical evidence provides insight into the potential outcomes and consequences of assisted gene flow, its applicability to large-scale plantings needs to be evaluated. We conducted a test of assisted gene flow in the context of operational postfire restoration plantings in three U.S. Department of Agriculture National Forests in California. Our experimental restoration plantings included seedling provenances representing both the local planting site and lower-elevation provenances that may be adapted to hotter and drier conditions. For the duration of the experiment, the planting sites experienced anomalously hot, dry conditions, offering a window into the potential outcomes of assisted gene flow in a future climate characterized by warmer temperatures and more frequent drought. In most cases, there was no significant difference in seedling growth or survival among provenances. However, in a few cases, lower-elevation provenances performed better than local provenances, suggesting a potential benefit of assisted gene flow as a management response to climate change. Our analyses accounted for spatial variation in shrub cover and detected a consistent and substantial negative association between shrub cover and seedling growth. In addition, our study revealed that the use of operational seed collections that are not geographically precise (and therefore also not climatically precise) can complicate selection of appropriate provenances and lead to unpredictable outcomes. Numerous other risks and uncertainties—including the fact that tree populations are often adapted to local site factors other than climate and that long-term outcomes may differ from short-term observations—complicate evaluations of the potential utility of assisted gene flow.

Background

Metastatic relapse of prostate cancer after radiotherapy is a significant cause of prostate cancer-related morbidity and mortality. PLOD2 is a mediator of invasion and metastasis that we identified as being upregulated in our highly aggressive radiorecurrent prostate cancer cell line.

Methods

Patient dataset analysis was conducted using a variety of prostate cancer cohorts. Prostate cancer cell lines were treated with siRNA, or the drug PX-478 prior to in vitro invasion, migration, or in vivo chick embryo (CAM) extravasation assay. Protein levels were detected by western blot. For RNA analysis, RNA sequencing was conducted on PLOD2 knockdown cells and validated by qRT-PCR.

Results

PLOD2 is a negative prognostic factor associated with biochemical relapse, driving invasion, migration, and extravasation in radiorecurrent prostate cancer. Mechanistically, HIF1α upregulation drives PLOD2 expression in our radiorecurrent prostate cancer cells, which is effectively inhibited by HIF1α inhibitor PX-478 to reduce invasion, migration, and extravasation. Finally, the long non-coding RNA LNCSRLR acts as a promoter of invasion downstream of PLOD2.

Conclusions

Together, our results demonstrate for the first time the role of PLOD2 in radiorecurrent prostate cancer invasiveness, and point towards its potential as a therapeutic target to reduce metastasis and improve survival outcomes in prostate cancer patients.

Whitebark pine (WBP, Pinus albicaulis) is a white pine of subalpine regions in the Western contiguous United States and Canada. WBP has become critically threatened throughout a significant part of its natural range due to mortality from the introduced fungal pathogen white pine blister rust (WPBR, Cronartium ribicola) and additional threats from mountain pine beetle (Dendroctonus ponderosae), wildfire, and maladaptation due to changing climate. Vast acreages of WBP have suffered nearly complete mortality. Genomic technologies can contribute to a faster, more cost-effective approach to the traditional practices of identifying disease-resistant, climate-adapted seed sources for restoration. With deep-coverage Illumina short reads of haploid megagametophyte tissue and Oxford Nanopore long reads of diploid needle tissue, followed by a hybrid, multistep assembly approach, we produced a final assembly containing 27.6 Gb of sequence in 92,740 contigs (N50 537,007 bp) and 34,716 scaffolds (N50 2.0 Gb). Approximately 87.2% (24.0 Gb) of total sequence was placed on the 12 WBP chromosomes. Annotation yielded 25,362 protein-coding genes, and over 77% of the genome was characterized as repeats. WBP has demonstrated the greatest variation in resistance to WPBR among the North American white pines. Candidate genes for quantitative resistance include disease resistance genes known as nucleotide-binding leucine-rich repeat receptors (NLRs). A combination of protein domain alignments and direct genome scanning was employed to fully describe the 3 subclasses of NLRs. Our high-quality reference sequence and annotation provide a marked improvement in NLR identification compared to previous assessments that leveraged de novo-assembled transcriptomes.

Conifers are the dominant plant species throughout the high latitude boreal forests as well as some lower latitude temperate forests of North America, Europe, and Asia. As such, they play an integral economic and ecological role across much of the world. This study focused on the characterization of needle transcriptomes from four ecologically important and understudied North American white pines within the Pinus subgenus Strobus The populations of many Strobus species are challenged by native and introduced pathogens, native insects, and abiotic factors. RNA from the needles of western white pine (Pinus monticola), limber pine (Pinus flexilis), whitebark pine (Pinus albicaulis), and sugar pine (Pinus lambertiana) was sampled, Illumina short read sequenced, and de novo assembled. The assembled transcripts and their subsequent structural and functional annotations were processed through custom pipelines to contend with the challenges of non-model organism transcriptome validation. Orthologous gene family analysis of over 58,000 translated transcripts, implemented through Tribe-MCL, estimated the shared and unique gene space among the four species. This revealed 2025 conserved gene families, of which 408 were aligned to estimate levels of divergence and reveal patterns of selection. Specific candidate genes previously associated with drought tolerance and white pine blister rust resistance in conifers were investigated.

To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new cases recruited online by SPARK. We identified 60 genes with exome-wide significance (P < 2.5 × 10^-6), including five new risk genes (NAV3, ITSN1, MARK2, SCAF1 and HNRNPUL2). The association of NAV3 with autism risk is primarily driven by rare inherited loss-of-function (LoF) variants, with an estimated relative risk of 4, consistent with moderate effect. Autistic individuals with LoF variants in the four moderate-risk genes (NAV3, ITSN1, SCAF1 and HNRNPUL2; n = 95) have less cognitive impairment than 129 autistic individuals with LoF variants in highly penetrant genes (CHD8, SCN2A, ADNP, FOXP1 and SHANK3) (59% vs 88%, P = 1.9 × 10^-6). Power calculations suggest that much larger numbers of autism cases are needed to identify additional moderate-risk genes.