Progress 08/01/23 to 07/31/24

Outputs
Target Audience:This project's target audience encompasses a diverse range of individuals and groups that are critical for the conservation and understanding of Juglans cinerea (butternut), including undergraduate and graduate students, extension specialists, stakeholders, members of the Northern Nut Growers Association, scientists from the Department of Natural Resources (DNR) and USDA, landowners, university faculty, tree improvement scientist, botanical gardens across the eastern of United States, and Indigenous and Indian tribes. During the reporting period, I trained 5 undergraduate students, technicians, post-docs who contributed to laboratory and field research, employing a variety of classical and advanced phenotyping and genotyping techniques. This hands-on training taught students valuable skills and fostered their engagement in real-world conservation issues. A primary focus of our project was to develop methods to help identify the genetic background of Hartwood Tree Improvement plantation and assist Northern nut growers and stakeholders in accurately identifying the genetic backgrounds of their trees. Given the hybridization of Juglans cinerea with the Japanese walnut (an exotic species), many nut growers faced uncertainty regarding the purity of their trees. Misidentification can lead to the unnecessary removal of valuable butternut trees, which poses a significant threat to the conservation of this endangered species. By providing clear genetic insights, we empower stakeholders to make informed decisions that support conservation efforts. To disseminate our findings and enhance community understanding, we held monthly meetings that included representatives from the DNR, USDA, and other stakeholders. These meetings served as a platform for sharing our research progress and discussing strategies for conservation. Additionally, I presented our findings at significant scientific gatherings such as the annual meeting of the Hardwood Tree Improvement and Regeneration Center at Purdue University, Morton Arboretum Chicago, and conferences hosted by the National Breeding Associations and the Plant and Animal Genome conferences and hold a butternut workshop recently sharing to students, tree breeder. These presentations allowed us to connect with scientists and industry professionals, fostering collaboration and exchanging knowledge. Engaging with Indigenous communities was also a vital component of our outreach. We collaborated with these groups to collect butternut samples from their lands, fostering partnerships that enhance our genetic analysis and help Indigenous communities understand the genetic backgrounds of their trees. This collaboration is crucial for preserving butternut trees' cultural and ecological significancewithin Indigenous traditions. In summary, during this reporting period, our targeted outreach effortsfocused on equipping a diverse audience with the knowledge and tools necessary for conserving butternut trees. By engaging students, stakeholders, and Indigenous communities, we aim to create a collaborative network dedicated to preserving this threatened species for future generations. Changes/Problems: Nothing Reported What opportunities for training and professional development has the project provided?This project allowed me to train five undergraduates, two technicians, and two visiting scholars who contributed to achieving the project's goals. Additionally, I participated in the Purdue Postdoctoral Association (PPDA), which offers professional development, advocacy, and networking opportunities. Through the PPDA, I attended workshops, social events, and benefited from a supportive platform that helps postdocs connect, address concerns, and advance their careers. How have the results been disseminated to communities of interest?The results have been disseminated to communities of interest through a variety of activities, events, and services: · Activities: These included conducting high-throughput genotyping, advanced phenotyping, and training undergraduates and visiting scholars in field and lab techniques, image analysis, and Genome-Wide Association Analysis (GWAS). · Events and presentation: Findings were shared at several conferences and workshops, such as the HTIRC Annual Meeting (March 6, 2024), Northeastern Forest Pest Council Meeting (March 12-14, 2024, Keene, New Hemisphere), and the Plant and Animal Genome Conference (January 12-17, 2024). A butternut workshop at Purdue University on September 25, 2024, engaged scientists, stakeholders, and nut growers in understanding the use of DNA markers for identifying butternut from hybrids. · Services: Consulting and tutoring were provided to stakeholders and growers, guiding them in identifying genetic backgrounds of their trees and assisting with DNA lab referrals for genotyping and data analysis. · Collaborations: Partnerships have been established with entities such as the Department of Natural Resources, the Morton Arboretum, USDA, Vermont University, the Abenaki tribe, and Canadian scientists, all focusing on further genotyping and conservation efforts for butternut. The efforts included organizing workshops and building a collaborative network to ensure effective communication of the project's results to interested parties. For more details, a recording of the butternut workshop can be foundhttps://rngr.net/resources/webinars/2024-butternut-workshop/ What do you plan to do during the next reporting period to accomplish the goals?Monitoring of Phenology, Butternut Canker Disease, and Growth: Detailed observations will be conducted in the spring of 2025 to track the phenological stages of butternut trees, assess the incidence and severity of butternut canker disease, and measure tree growth. This will build on previous data to identify trends and variations over time. Genotyping by Sequencing (GBS): We will process GBS for 1000 individual trees. This will expand the genetic dataset that can be used for structure analysis and GWAS. Spectral Data Analysis: Advanced analysis of collected spectral data, including both multispectral and hyperspectral imagery as well as RGB, will be carried out. This will help that helps to quantify butternut canker disease. Drone Imagery Analysis: Detailed analysis of drone-collected imagery will be performed, focusing on both multispectral and hyperspectral data. This work aims to improve understanding of how remote sensing data can be used to monitor butternut health and differentiate between pure and hybrid butternuts. Genotype-Phenotype Association, Genome Selection, and Selective Sweep Analysis: These analyses will be conducted to link genetic data with observable traits, identify beneficial genetic variations, and detect regions of the genome related to butternut canker disease

Impacts
What was accomplished under these goals? To accomplish the first goal of the project--Paternal identification of trees in HTIRC's butternut tree improvement collection using phenotypic and genotypic (GBS) data--we employed multiple approaches: Classical and Advanced Phenotyping We monitored disease incidence, diameter, height of trees and bud break in butternut plantations at Martell Forest, Indiana, using manual observations and advanced imagery techniques, including RGB, multispectral, hyperspectral, and LiDAR data from drones. Monitoring took place from mid-April to mid-May, with bi-weekly drone deployments for RGB imagery of bud break. Data collection extended into early August using multispectral and hyperspectral imaging to track foliage development. Monthly RGB captures provided summer insights, while in September and October 2023 and 2024, we focused on leaf senescence to understand seasonal changes. Using drones with RGB sensors provided high-resolution data, enriching our understanding of bud break and seasonal responses. The multispectral and hyperspectral data added depth, offering insights into tree health, environmental interactions, and disease quantification. Tree mortality and butternut canker disease were rated on a 5-point scale, showing that phenology can be tracked with RGB imagery. Additionally, multispectral images were effective in assessing canker damage. Ongoing analyses aim to understand butternut phenotypic diversity further. This part of the project focuses on tracking bud breaks in butternut trees using manual and drone-based observations throughout the growing season. It leverages high-resolution, multispectral, and hyperspectral imagery better to understand the seasonal behaviors and health of the trees. The key finding of this part of the project involves monitoring bud breaks in butternut trees using a combination of manual observations and advanced drone imagery from spring to fall. This approach provided comprehensive insights into the trees' seasonal responses and overall health through collecting high-resolution, multispectral, and hyperspectral data. Additionally, the data is being used to assess the potential of drone imagery for distinguishing between pure and hybrid butternuts. The incidence, severity, and mortality related to butternut canker disease have also been documented for each tree during the 2023-2024. Genotyping Leaf samples from 2000 butternut trees at the Hardwood Tree Improvement and Regeneration Center (HTIRC) were collected last year. The leaves were freeze-dried, and DNA was extracted using CTAB methods in 96 deep-well plates. These samples were processed to create a custom library and submitted to the genomic center for genotyping-by-sequencing (GBS) analysis. This approach used two enzymes to target specific genomic regions across the entire genome. Results from the GBS analysis of 1,000 samples are complete, while an additional 1,000 samples are currently being processed. This comprehensive method provides insights into the genetic background of butternut trees, focusing on hybridity and paternal identification within the HTIRC collection. Among the 1,000 processed individuals, 771 were identified as pure butternut, 120 as backcrosses, 28 as F1 hybrids, and ten as Japanese walnuts. The key findings are the development of a high-throughput genotyping-by-sequencing technique involves DNA extraction, library preparation, and sequencing of 1,000 individuals already sequenced, along with processing an additional 1000 trees for genotyping in this project. Chemotyping and photosynthesis measurement: Spectral data was collected from butternut trees at two Indiana sites: Martell Forest, West Lafayette ("Martell"), and the Southeast Purdue Agriculture Center, Butlerville ("SEPAC"). Martell has a higher incidence of disease than SEPAC, offering a unique opportunity to explore how environmental conditions affect disease progression in open-pollinated pure and hybrid butternut families. The study involves around 20 families at each site, with roughly 10 families per species (pure butternut and hybrids). Approximately five trees per family were sampled in June, July, and August to monitor changes in foliar spectral profiles over time, focusing on pure and hybrid butternut trees with varying degrees of butternut canker disease severity. Three leaves were collected from a standardized canopy location on each tree for consistency. Spectral data from the adaxial side of these leaves was captured using near-infrared (NIR) spectroscopy with two complementary instruments: a VIS/NIR device and a NeoSpectra Scanner, which operates in the short-wave infrared region. Additionally, measurements of chlorophyll content, leaf dry weight, and photosynthesis rates using LiCor were taken alongside the spectral data. This methodology thoroughly analyzes the trees' responses to environmental conditions and disease. The results suggest that spectral devices are valuable for accurately quantifying disease incidence and understanding the genetic makeup of butternut trees. Notably, pure butternut trees exhibited lower photosynthesis rates than their hybrid counterparts, highlighting potential differences in stress response and physiological adaptation. To achieve the second goal of the project--identifying genes linked to butternut canker disease--we used genotype and phenotype data to conduct a Genome-Wide Association Analysis (GWAS). Sequence reads were aligned to the butternut genome using the TASSEL GBS pipeline (Glaubitz et al., 2014) and BWA (Li and Durbin, 2009), retaining tags appearing at least 10 times with a BWA MAPQ score of 20 or higher. Filtering criteria included a depth threshold (less than 5 set to missing), and removal of taxa with over 90% missing data, indels, multi-allelic SNPs, and SNPs with over 50% missing data, resulting in a final dataset of 1,000 samples and 58,000 SNPs. Beagle 5.0 (Browning et al., 2018) was used for imputation, achieving a median concordance of 95.9% between replicates. The imputed data was converted into a VCF format using TASSEL 5 (Bradbury et al., 2007) and linked with phenotypic data for GWAS analysis. This process identified SNPs associated with bud break, height, and butternut canker disease.

Publications

• Type: Conference Papers and Presentations Status: Published Year Published: 2024 Citation: 1) 'From Phenome to Genome: Current Status of Butternut Research' by Ebrahimi et al., 2024 Butternut Workshop, West Lafayette IN, USA. September 25, 2024. https://rngr.net/resources/webinars/2024-butternut-workshop/ 2) Butternut Genetics Across North America' by Ebrahimi et al., Northeastern Forest Pest Council 86th Annual Meeting (March 12-14, 2024), Best Western Plus  Keene, New Hemisphere. 3) Integrating phenotype and genomics approach to support HTIRC butternut conservation and resistance breeding efforts,' by Ebrahimi et al., HTIRC annual meeting, West Lafayette IN, USA. March 6, 2024 4) 'Aerial Mapping of Butternut Plantations Affected by Butternut Canker Disease Using UAVs, Hyperspectral Imaging, and Artificial Intelligence,' by Ebrahimi et al., Digital Forestry, mini-conference, West Lafayette IN, USA. February 24, 2024 5) Integrating Landscape Genetics for Effective Conservation of Threatened Butternut (J. cinerea) in North American Forests,' by Ebrahimi et al., Plant and Animal Genome Conference/PAG 31 (January 12-17, 2024), San Diego, USA.