Carya illinoinensis (pecan) belongs to the Juglandaceae family, and the native region extends from Illinois, USA to Oaxaca, Mexico. Pecan is a valuable economic crop due to its nutritious and tasty nuts, and the United States produced 275 million pounds of pecans in 2022. As temperatures are increasing it is important to understand the impact on pecan trees. By 2100, the average U.S. temperature is projected to increase by about 3°F to 12°F. Plants deal with heat stress in several different ways including the production of heat shock proteins (HSPs) and their transcription factors known as heat shock factors (HSFs). HSFs initiate the transcription of genes that encode heat shock proteins (HSPs), that deal with heat stress by initiating protein folding and aid in the repair or removal of damaged proteins. In this study, we aim to look at the genetic networks that are impacted when multiple genotypes are subjected to high-heat environments. For this study, seedstocks from multiple genotypes that span the geographic region of North America were introduced into micropropagation. These include seedstocks from ‘Elliott’, ‘Apache’, ‘Cape Fear’, ‘Mahan’, ‘Giles’, ‘Sioux’, ‘Wichita’, ‘Western’, and native seedstocks of unknown genetics from Ohio. A preliminary heat stress assay was performed on a micropropagated ‘Elliott’ line by subjecting three small trees to 43°C for two hours prior to flash freezing in liquid nitrogen and comparing these to the same clonal line (three trees) that remained at 23°C. Real time quantitative reverse transcription PCR (QRT-PCR) was performed on the heat stress and control trees. Normalized gene expression indicated that CiHSP1 expression was 2X higher in the heat-treated pecan trees than CiHSP1 expression of the control trees. The additional micropropagated seedstocks listed above are being subjected to heat stress at different temperature ranges and time intervals. The replicated assays will be analyzed using RNA-Seq and qRT-PCR to determine differential gene expression of control and heat-treated trees especially between the HSPs and HSFs. These assays will help determine the gene networks that pecan trees use as they experience heat stress and will help determine how different pecan genetics that originate in different geographic regions react to heat stress.
Late embryogenesis abundant (LEA) proteins, encoded by a family of LEA genes, are vital in conferring stress tolerance in plants through their unique intrinsically disordered structure that can stabilise cellular components under desiccated conditions. While the protective capabilities of LEA proteins are well-documented across various crops, their specific roles in pecan (Carya illinoinensis), a highly nutritious and economically significant nut crop, remain largely unexplored. This gap of knowledge needs to be addressed as pecan yields face threats from escalating drought and salinity issues, intensified by ongoing climate change. This study represents the first comprehensive analysis of LEA genes within the pecan genome. We have successfully identified 332 LEA genes distributed across 15 of the 16 chromosomes in four genomes of pecan, categorized into 8 distinct subgroups based on their conserved motif regions. Synteny analysis provided a deeper understanding of their evolutionary trajectories. Utilizing extensive transcriptomic datasets, we explored the tissue-specific expression patterns of LEA genes in pecan, discovering diverse expression profiles across various tissues. Ongoing studies include promoter analysis and assessments of gene expression under abiotic stress conditions. To specifically address the impact of drought, heat and salinity, clonal pecan plants are being subjected to these stressors under controlled conditions in tissue culture and greenhouse settings. This approach aims to directly observe the physiological and molecular responses of LEA genes under realistic stress simulations. The presence of LEA genes across a vast majority of pecan chromosomes and their diverse subgroup classifications suggests a genome-wide defense mechanism potentially key to enhancing the stress tolerance of pecan trees. By understanding and harnessing these genes, our research seeks to elucidate plant stress responses at the molecular level allowing the development of genetic strategies to ensure the sustainability of pecan by mitigating adverse environmental impacts on its production. This knowledge could also be applied in a diverse array of other economically significant crops.
Pecans (Carya illinoinensis (Wangenh.) K. Koch) are globally consumed nuts and an important agricultural commodity in the United States. Scab is a devastating pecan disease, which necessitates the application of numerous fungicide sprays in the growing season of pecans. Even with the control measures, in wet years, scab infection results in great yield loss (over 50% loss in susceptible varieties) and deterioration of nut quality. Although there have been various efforts to alleviate the scab, the development of scab-resistant pecan cultivars is the most effective method to control the disease. However, current methods to assess pecan scab resistance require multiple years of field screening and complicated laboratory (microscopic) techniques. Thus, a simple and reliable method that can rapidly evaluate pecan scab resistance at an early stage of infection is necessary. In this study, metabolomic analysis with machine learning algorithms was utilized to identify early biomarkers for the scab resistance of pecan seedlings. Two pecan seedlings with contrasting scab resistance ('Pawnee' and 'Desirable') were inoculated with water (control), Pa-OK-11 (isolated from 'Pawnee'), and De-Tif-11 (isolated from 'Desirable') for 7 days. 'Desirable' seedlings exhibited resistance to Pa-OK-11, while 'Pawnee' seedlings showed moderate resistance to De-Tif-11. Both cultivars were susceptible to their respective isolates. Leave samples from each seedling were collected at different time points (0, 1, 2, 3, 4, 5, 7 days). For the metabolomics work, liquid chromatography‒mass spectrometry (LC‒MS) was employed to analyze metabolites in samples, which can cover a wide range of primary and secondary metabolisms, including carbon fixation, glycolysis, citric acid cycle, amino acid metabolism, phenylpropanoid, monolignol, and flavonoid biosynthesis. Different machine learning algorithms were compared to find differentially regulated metabolites (biomarkers) between scab-resistant and -susceptible seedling groups. With a combination of machine learning models, we obtained reliable potential biomarkers, e.g., phenolic acids, flavonoids, plant hormones, and their intermediates and precursors, involved in the early stage of scab infection. The selected markers are expected to be used to classify scab resistance levels in pecan seedlings within a week after infection, which may replace the conventional method (phenotype-based mass selection) for pecan breeding selection. In short, this research breaks the bottleneck of resistance screening in pecans and will help facilitate the early selection of scab-resistant pecan cultivars to achieve breeding goals.
Pecan (Carya illinoinensis) is a nut crop native to the United States and Mexico which is becoming an increasingly important crop globally. Juglandaceous nuts are uniquely high in antioxidants among nuts and a conversion equivalent derived from studies in mice indicates that consumption of 22-38 pecans per day may reverse metabolic disorder in an individual weighing 132 pounds, implying a role in a healthy diet. Despite this importance, relatively little is known about the molecular basis of pecan nut ontogeny compared to other nut crops, leading to difficulties in understanding the physiological issues which plague growers. Susceptibility to various biotic and abiotic disorders including pecan scab, vivipary, water split, and shuck decline are dependent upon the stage of development the pecan nut is in. To better understand the molecular basis and timing of pecan nut development, developmental time-course RNA-Seq was carried out on nuts collected from cultivars ‘Mahan’ (a large nut bearing pecan from Mississippi) and ‘Tiny Tim’ (a small nut bearing native pecan from Missouri) approximately biweekly through the growing season of 2022. Using this data, genes were grouped together into distinct developmental phases, connecting transcriptional changes to the already well-characterized ontogenic stages of pecan nut development.
There is significant variation in tree size, which determines productivity, in commercial pistachio orchards planted with UCB-1 seedling rootstocks. It has been unclear to extent to which this is due to genetic differences or environmental variation. Nurseries have tried to tackle this problem by rogueing young seedlings before they are planted in orchards. However, our data previously demonstrated that performance in the first year is a poor predictor of later tree size. Genotyping by sequencing data from experimental and commercial orchards and genome wide association studies (GWAS), combined with our chromosome-scale, high quality, genome assemblies for the parental Pistacia atlantica and P. integerrima trees resulted in two highly informative molecular markers for vigor. Based on the genomic sequence information, we developed an inexpensive, quick, and easy qPCR protocol for single nucleotide polymorphism (SNP) marker analysis. We were able to predict the improved size distribution that extant orchards would have had if this marker had been used to rogue seedlings prior to planting in the orchards. We want this marker to make it available for nurseries to rogue out trees which would exhibit low vigor and productivity later in an orchard.
The California almond industry has funded multiple, multi-site almond variety evaluation trials over the last several decades. These field trials have previously evaluated many of the varieties that are now the most widely planted in California. Although, field evaluation trials are helpful for revealing which varieties are promising, they are, perhaps, most valuable to the industry for revealing which varieties/selection have serious flaws and should not be planted by growers. Thirty named cultivars and numbered breeder selections were planted in three replicated commercial orchards across California’s Central Valley in 2014. Of these 30, as of April 2024, one numbered selection Y116-161-99 from the USDA has been commercially released as ‘Yorizane’. However, nine of the 30 varieties/selections were dropped from further evaluation in the trial in 2022 for a variety of reasons: low yield (five), lack of interest by the breeder (two), extremely early bloom timing (one), and poor harvestability (one). Of the 21 still being evaluated in 2024, many have one of these major flaws, or additional flaws, that will likely prevent commercial adoption, including a high percentage of double kernels, susceptibility to bacterial blast (Pseudomonas syringae pv. syringae), Botryosphaeria canker disease susceptibility, hull rot susceptibility, and a high percentage of kernel creases or twins, just to name some of the additional flaws. Even if a variety/selection has high yield, good kernel quality, and none of these major flaws documented after ten years of evaluation (e.g. Y117-91-03 from USDA), further observation in the UC trial sites or in the orchards of early adopters may reveal important flaws that prevent sustained and widespread variety adoption. This long-term challenge is why some believe it takes decades to prove a new scion variety. The wide diversity of potentially fatal flaws underscores the need for cultivar evaluation to take place by a third-party like UC Cooperative Extension in long-term replicated trials to reduce substantial financial risk to the grower to the greatest extent possible. Keywords: Prunus dulcis, almond, variety evaluation, breeding, nut crop
