Source: CLEMSON UNIVERSITY submitted to
NATIONAL DATABASE RESOURCES FOR CROP GENOMICS, GENETICS AND BREEDING RESEARCH
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
COMPLETE
Funding Source
HATCH
Reporting Frequency
Annual
Accession No.
1022664
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
NRSP-10
Project Start Date
May 1, 2020
Project End Date
Sep 30, 2024
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Recipient Organization
CLEMSON UNIVERSITY
(N/A)
CLEMSON,SC 29634
Performing Department
Plant & Environmental Sciences
Non Technical Summary
The NRSP10 project will expand the Rosaceae, citrus, cotton, cool season food legumes and Vaccinium databases to integrate various types of Big Data (epigenomics, re-sequencing, expression and phenomics data) with whole genome sequence and other valuable genetic data. It will develop and deploy new open-source tools to integrate and visualize these new types of Big Data. In addition, it will enable databases to provide easy-to-access interfaces where users can run high-throughput analyses, view their results graphically and submit their data and results in appropriate formats when they want to release it publicly. Performing analyses through the community databases facilitates standardization of metadata, naming conventions, and ontology associations, as well as prompt data release. In addition, it will facilitate re-use of public data stored in community databases. Adding these functionalities to community databases will catalyze further applications in genomics-assisted breeding and advance the genomics, genetics, and physiology knowledge base. This effort will provide stable support to continue development and deployment of fundamental, research-enabling databases, used ubiquitously in the U.S. for target crops and be readily adaptable for other crops and organisms.
Animal Health Component
50%
Research Effort Categories
Basic
20%
Applied
50%
Developmental
30%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
2011114108150%
5021414108150%
Knowledge Area
201 - Plant Genome, Genetics, and Genetic Mechanisms; 502 - New and Improved Food Products;

Subject Of Investigation
1114 - Peach; 1414 - Lentil;

Field Of Science
1081 - Breeding;
Goals / Objectives
Expand the online community databases for Rosaceae, citrus, cotton, cool season food legumes and Vaccinium crops We will continue curation and integration of GGB data, adding the ability to handle new data types such as pan-genomic, epigenomic, and phenomic data, and providing tools for further analysis of new/updated whole genome sequencing data to connect to genes in other databases, find conserved syntenic regions and orthologous genes, and identify metabolic pathways. We will continue to develop utilities for QTL and marker identification, analysis of expression and methylation data as well as variation data from SNP array, resequencing and pan-genome analysis. In addition to publication/submitted data, we will add trait evaluation data from GRIN integrated with breeding data. Develop a Tripal module for visualization of epigenomics data Studies to understand epigenetic mechanisms underlying the basis of important traits are increasing for NRSP10 crops. To maximize utility of these data, we will develop a Tripal Epigenome module so users can search for genes/genomic fragments and view the level of epigenetic modification in various tissues and conditions. Integration with other genomic, transcriptomic, expression and genetic data will further increase the value and utility of this data. Enhance TripalMap to integrate genomic and genetic data We will expand TripalMap, our genetic map comparison and visualization viewer, to display genes and markers in chromosomes, as well as markers and QTL in linkage groups of genetic maps, similar to the NCBI map viewer. Chromosomes and linkage groups will be linked by shared markers, allowing users to explore the genomic features around QTL, even when only the genetic position is available. The genes in chromosome view in TripalMap will hyperlink to JBrowse and other graphical viewers, allowing exploration of expression, methylation and sequence variation data. Enhance TripalBIMS to (a) support phenomics data, (b) add GWAS analysis, and (c) global performance prediction capability Phenomics data is becoming increasingly available NRSP10 crops. BIMS will be enhanced to accommodate storage of high-throughput phenotyping, and integrate environmental and genotypic data. BIMS will be further enhanced by the addition of GAPIT for GWAS and genome prediction to allow users to identify genetic variations for important traits. A module will be developed that can combine national and international data for global performance predictions. Germplasm can perform differently in different environments and the module will enable breeders to predict the performance of their material under various conditions. In this tool, the phenotypic and genotypic data from various environmental conditions can be compiled in an anonymous database, allowing the effect of the environment on replicated genomic segments to be tracked. Users will be able to input the genotypic and phenotypic data of their materials then view the predicted performance under various conditions. Without revealing any proprietary information, breeders can contribute their data to the anonymous database to increase the accuracy of the prediction tool. We will also implement BrAPI web services (https://brapi.docs.apiary.io/#) so BIMS users can exchange their data with breeding tools in other systems using BrAPI.
Project Methods
Collectphenotypic field data for perennial fruit trees and cool legumes and upload to the TripalBIMS database.Assist project with validation and improvement of the existing and newly developed modules.Test the TripalBIMSand assist in adding features to the database for analyzing data and preparing reports.Utilize the TripalMap in local breeding programs and provide feedback on the utility and available statistical tools.Train breeders and allied scientists in collecting data using android application, uploading data to the TripalBIMS and using various modules and tools in analyzing uploaded data.Evaluate the global performance module in local breeding programs and provide the data to the project for testing,validating and improvement ofthe functionality of the module and predicted perfomance.

Progress 05/01/20 to 09/30/20

Outputs
Target Audience:The target audiences are: Southeast and U.S. peach industry, fruit breeders, germplasm repositoriesresearch staff and associated researchers,the American pulse and vegetable stakeholder community, including local, national, and international pulse growers (Northern Pulse Growers Association, American Pulse Association, the USA Dry Pea and Lentil Council, SC Specialty Crop Growers, and ICARDA partners in Morocco and India), and local organic vegetable producers from South Carolina. The others are pulse breeders, researches, food quality, and processors. SC emerging scholars (high school seniors and juniors), SC commissioner school (highschool), Clemson University undergraduate, and graduate students have also targeted audiences for this project results. All the above groups were approachedthis reporting period. Changes/Problems:COVID-19 has affected field data collection and evaluations. Lentil will not be included in this project. What opportunities for training and professional development has the project provided?Fellow plant breeders were trained on utility of FieldBook app, data upload to the BIMS, and usage in peach breeding program. How have the results been disseminated to communities of interest?Via webinar and individual virtual consultation. What do you plan to do during the next reporting period to accomplish the goals?Continue with using the FieldBook app to collect the epphenotypic data for peach, kale and field pea. Upload the data to BIMS and use it to test and improvefunctionalities in BIMS. Educate undergraduate and graduate students on field data collection using FieldBoook app and functionalities in the Rosaceae and cool season food legumes. Provide colleced data to the coresponding databases and participate in improvement and testing of functionalities in both databases and BIMS. Provide support for training fellow breeders and reseachers in using FieldBook app and BIMS in their operations.

Impacts
What was accomplished under these goals? Under Goal 4: Peach FiledBook app is routinely used in the peach breeding program to collect phenotypic data in field and lab. More than 600 advanced selections are evaluated in the field by at least two researchers using FieldBook app and data acquired are uploaded to the BIMS database on a weekly basis and actively used in breeding decisions. About 150 advanced selections have been removed from the selection block using statistical analyses of data from 5 or more years provided in BIMS. We provided support to FieldBook developer for fixing some issues with photo trait. Assistedthe BIMS developing team in improving functionalities and fixing some upload issues from FieldBook exported file to BIMS. Provided support to fellow breeders in using FieldBook and BIMS. Presented examples from the peach breeding program to lentil breeders on FieldBook usage. Field Pea The Pheno App, Field Book, was integrated throughout the organic field pea breeding trials to facilitate in-field data collection for evaluating trial entries. Field Book was simple and easy to use, allowing efficient data collection and limiting data errors. Trial entries were uploaded to the app, containing identification information (plot number, variety, and accession) for 156 plots, including 29 advanced cultivars and 23 elite breeding lines with three replicates. Field Book's tools allowed to tailor genotype evaluations for each agronomic trait and dictate the criteria or scale to accommodate the assessment's particular needs. The majority of agronomic data recorded using the app was quantitative or visual assessment data. We created various traits to evaluate entries and select a format based on the data type to be recorded. Quantitative data, such as vine length, pod height, canopy height, were recorded using the numerical trait format. Visual assessment traits were often in the categorical or multicat format, which allowed the assignment of one or more ratings based on predetermined categories we created. Categorical trait formats were implemented to document disease and insect pressure, lodging, germination, vigor, and overall performance. Field Book was used to record photos and text. This feature was relevant, as it logged photographs and notes for observations of a particular plot. All data collected during the trial was stored within the app, avoiding the need for re-entering written data into spreadsheets. After completing field evaluations, data was exported into a CSV/Excel file, which allowed quick and reliable data for analysis. Ten field pea parents were selected to incorporate into the breeding pipeline to develop cultivars suitable organic production after analyzing cultivar performance data. Kale The Field Book app was used to assess 36 kale genotypes' organic adaptability in a field study. The Field Book app allowed the collection of quantitative and qualitative data, which supported various measurements, including plant height, width, color, insect damage, weed presence, and additional notes. The ability to take categorical data was convenient, specifically when noting weed presence, severity, and color. Multiple categories for color were created to classify plant accessions. The option to take text-based notes allowed the freedom to indicate any irregularities and was particularly useful in noting premature flowering. Field Book exceedingly facilitated taking data because it allowed for effortless switching between plots and agronomic traits.

Publications

  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Abdelghafar A.*, Okie W., Reighard G. and K. Gasic (2020) Mapping QTLs for phytochemical compounds and fruit quality in peach. Mol Breeding 40 (3) 1-18 https://doi.org/10.1007/s11032-020-01114-y
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Rawandoozi Z., Hartmann T., Carpenedo S., Gasic K., da Silva Linge C., Van de Weg E. and Byrne D. (2020) Identification and characterization of QTLs for blush, soluble solids concentration (SSC), and titratable acidity (TA) in peach through a multi-family approach. BMC Genomics https://doi.org/10.21203/rs.3.rs-20345/v1.
  • Type: Journal Articles Status: Published Year Published: 2020 Citation: Tony Reda , Pushaparajah Thavarajah, Robert Polomski, William Bridges, Emerson Shipe, Dil Thavarajah, 2020. Reaching the Highest Shelf: An Organic Approach to Increasing the Nutritional Quality and Shelf Life of Kale (Brassica oleracea var. acephala). Plants, People, Planet, PPP-R-2020-00226.
  • Type: Book Chapters Status: Published Year Published: 2020 Citation: Dil Thavarajah!, Sarah Powers, Casey R. Johnson, George Vandermark, Pushparajah Thavarajah 2020. Pulse crop biofortification towards human health - target traits prebiotic carbohydrates, protein, and micronutrients. In: Biofortification of staple crops. Ed: Shiv Kumar, H.K.Dikshit, G.P.Mishra, and Akanksha Singh. Springer Nature.
  • Type: Book Chapters Status: Published Year Published: 2020 Citation: Dil Thavarajah!, Casey R. Johnson, Tristan J. Lawrence, Michael Lake, Pushparajah Thavarajah, 2020. Kale (Brassica oleracea L. var. acephala) - a Nutritional Powerhouse Leafy Vegetable In: Agricultural Research Updates, Volume 31: Chapter 3, Prathamesh Gorawala and Srushti Mandhatri (Editors). Nova Science Publishers, Inc., NY, USA. https://novapublishers.com/shop/agricultural-research-updates-volume-31/.
  • Type: Conference Papers and Presentations Status: Published Year Published: 2020 Citation: Gasic K. (2020) Advances in cultivar and rootstock breeding: A case study in peach. Acta Horticulture 1281 doi: 10.17660/ActaHortic.2020.1281.1
  • Type: Journal Articles Status: Accepted Year Published: 2020 Citation: Dil Thavarajah!, Tristan Lawrence, Sarah Powers, Boone John, Nathan Johnson, Joshua Kay, Anurudha Bandaranayake, Emerson Shipe, Pushparajah Thavarajah, 2020. Genetic variation in the prebiotic carbohydrate and mineral composition of kale (Brassica oleracea L. var. acephala) adapted to an organic cropping system. Journal of Food Composition and Analysis, JFCA-D-20-00211