2019
Integrating Germplasm Evaluation, Genetic Engineering, Breeding and High-Throughput Phenotyping to Improve Sustainability of Soybean Production
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Contributor/Checkoff:
Kansas Soybean Commission
Category:
Sustainable Production
Keywords:
GeneticsGenomics
Parent Project:
Integrating Germplasm Evaluation, Genetic Engineering, Breeding and High-Throughput Phenotyping to Improve Sustainability of Soybean Production
Lead Principal Investigator:
William Schapaugh, Kansas State University
Co-Principal Investigators:
Tim C. Todd, Kansas State University
Harold Trick, Kansas State University
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Project Code:
1930
Contributing Organization (Checkoff):
Kansas Soybean Commission
$250,000
Leveraged Funding (Non-Checkoff):
Funding from the Kansas Soybean Commission (KSC) has enabled/leveraged funds from the United Soybean Board (USB) and the North Central Soybean Research Program (NCSRP). A former USB grant enabled us to evaluate the use of microRNAs to enhance silencing of the targeted genes, while a former NCSRP grant supported us to produce stable transgenic lines targeting nematode genes. We have identified transgenic lines that have enhanced soybean cyst nematode (SCN) resistance and now are incorporating those traits into Kansas adapted lines. A USB grant is supporting our development of germplasm with improved protein concentration and seed yield, and another USB grant is supporting our efforts to evaluate and develop of germplasm with improved abiotic (drought) stress resistance. A NCSRP grant is providing support to develop genomic and high-throughput selection tools to improve genetic gain.
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Institution Funded:
Kansas State University
$250,000
Brief Project Summary:

Objectives of this project include providing high quality germplasm and phenotypic data to develop genome selection tools; identifying new sources of germplasm and genes that improve yield and seed composition; developing superior varieties using new sources of germplasm with improved yield under the extreme environmental conditions; developing high yielding varieties and germplasm lines with desirable levels of protein and oil; developing non-GMO, high oleic soybean varieties and germplasm lines; breeding transgenic events into elite breeding lines; developing sudden death syndrome resistant varieties and germplasm with stacked traits; developing enhanced high-throughput technology to rapidly identify genotypes that have disease and drought resistance, and yield potential.

Key Benefactors:
farmers, breeders, plant pathologists

Information And Results
Final Project Results

Update:

View uploaded report PDF file

Outcomes of research on variety development, SCN resistance, genetic gain, drought, and high-throughput phenotyping, FY20:

Variety Development:
This project enabled the development of 300 new breeding populations, and advancement of over 400 populations in the F1, F2, F3, F4 and F4:5 generations. Parents used to create these populations were selected for their yield potential, drought tolerance, herbicide resistance (Roundup Ready 1 and STS), seed protein content, oil composition, disease resistance (primarily SCN and Soybean Sudden Death Syndrome), and genetic diversity.

Nearly 7000 genotypes were evaluated in over 19,000 plots in Kansas in 2019. Over 1600 K-lines were evaluated in our preliminary trials. Over 1400 K-lines were evaluated in our preliminary trials. Over 190 K-lines were evaluated in our KS advanced yield trials. Over 400 (including 31 K-lines) breeding lines from programs across the country were evaluated in our KS Uniform Tests and Uniform Preliminary yield trials. Over 1000 genotypes, (experimental breeding lines and plant introductions) were evaluated in our drought, remote sensing, and diversity yield trials.

Funding from this project enabled the development and release of the following soybean varieties: KS4120NSGT (early maturity group (MG) IV, glyphosate tolerant, cyst nematode resistant, STS tolerant), KS4520NS (mid MG IV, cyst nematode resistant, STS tolerant) and KS5120NS (early MT IV, cyst nematode resistant and STS tolerant). These varieties can be used for commercial production and as parents by plant breeders for the development of new varieties.

SCN Resistance:
Our evaluations for SCN resistance have characterized the level of SCN resistance in soybean experimental lines, commercial varieties and new transgenic genotypes.

Breeding lines:
Soybean resistance to HG Type 7 was evaluated in replicated screening trials for >1,500 breeding lines. Approximately 60% of breeding lines in both the Preliminary and Advanced Tests displayed moderate or better levels of resistance. Kansas Soybean Performance Test: Soybean resistance to SCN was evaluated in replicated screening trials for 94 entries in the Kansas Soybean Variety Performance Test (KSVPT). Evaluations involved SCN populations that varied in their virulence to the common resistance source PI 88788. Eighty-five percent of KSVPT entries were resistant to moderately resistant to the HG Type 7 population, while only six entries were resistant to moderately resistant to the HG Type 2 populations. Female indices averaged ~50% for HG Type 2 populations compared to 23% for the HG Type 7 population, confirming that most KSVPT entries shared a common source of resistance (PI 88788).
Results of these evaluations are posted online at: https://www.agronomy.k-state.edu/services/crop-performance-tests/documents/soybean/2019%20SVPT%20SCN%20ratings.pdf.

Field evaluation of stable transgenic lines:
Transgenic soybean lines developed with Kansas Soybean Commission funding were evaluated in naturally-infested soil to confirm their utility as sources of novel SCN resistance. With one exception, transgenic lines averged 75% lower SCN egg densities compared to the non-transgenic background JackX. The best of these lines and being used as parents in crosses to transfer the resistance genes into adapted cultivars.

A new SCN Coalition free soil-testing program for Kansas soybean producers was initiated in 2019. To date, 47% of samples received for testing were positive for the presence of SCN, with an average egg density of 311 eggs per 100 cm3 soil.

A new HG Type survey of SCN populations in Kansas was initiated in 2019 in collaboration with DuPont Pioneer. Preliminary results suggest that the average female index of Kansas SCN populations now exceeds 20% on PI 88788, with all populations tested to date identified as HG Type 2.

This information will assist soybean growers in making informed variety selection decisions that impact SCN management and aid our breeding and genetic program in the selection and develop of new SCN resistant germplasm.

Genetic gain:
In 2019 we initiated a project to use genomic selection to attempt to increase genetic gain. We are using a rapid cycling method where three cycles (three generations) of selection can be completed in 12 months by evaluating F1 plants. Two cycles of selection were completed in 2019 and a third cycle is being grown in the greenhouse. Selection criteria based on genotypic data includes seed yield, plant maturity, protein and oil concentrations in the seed, and genetic distance among the progeny. Following each cycle of selection inbreeding of the selected and unselected F1s is being implemented to produce lines for evaluation in replicated field trials to characterize the effectiveness of the genomic selection and rapid cycling methodology.

High-throughput phenotyping to increase genetic gain and improve evaluations under drought stress:
We continue to develop models utilizing canopy reflectance and canopy thermal properties to estimate relative soybean maturity, seed yield, drought stress, and disease resistance. The focus in 2019 was obtaining remote sensing data on our progeny rows and on germplasm and varieties evaluated for drought stress and evaluate selections based on remote sensing in yield trials. Selections based on data collected using the UAVs were made in 2017 and 2018 progeny rows have been evaluated in replicated yield trials in 2018 and 2019 to characterize the benefits of using this technology. In both evaluation years, selections based on remote sensing reflectance data resulted in selections with higher average seed yields that random selections from progeny rows. This method is now being routinely used in our progeny rows.

While drought conditions were limited in Kansas in 2019, we were able to take some visual ratings for wilting, and also use an small unmanned aircraft to collect spectral reflectance data on the plots under evaluation. Drought research in previous projects funded by the United Soybean Board and the Kansas Soybean Commission has established a relationship between wilting ratings and canopy temperatures. With this knowledge we continue to move forward to develop a platform to use remote sensing to characterize drought stress.

Opportunities for Training and Professional Development:
One graduate student worked on objectives related to this project in Agronomy, and one additional student in Bio and Ag Engineering worked cooperatively using the field plots developed and evaluated through this project.

Dissemination of Results:
Peer-reviewed publications, extension publications, news releases, and experiment station reports, field days, extension meetings and tours are used to share the results of this project. Web pages have been developed to disseminate information on new releases and germplasm and pests. Distribution of results of genotype characterization for resistance are published online. Distribution of SCN survey results to cliental will provide much-needed information for making informed decisions by producers regarding variety selections for SCN management and by soybean breeders for the development of varieties with improved levels of resistance.

Publications in peer-reviewed publications in 2019 included:

Ye H, Song L, Schapaugh WT, Ali MDL, Sinclair TR, Riar MK, Raymond RN, Li Y, Vuong T, Valliyodan B, Neto PA, Klepadlo M, Song Q, Shannon JG, Chen P, Nguyen HT. 2019. The importance of slow canopy wilting in drought tolerance in soybean, Journal of Experimental Botany 71, 642–652.Maduraimuthu Djanaguiraman, William Schapaugh, Felix Fritschi, Henry Nguyen and P.V. Vara Prasad. 2018. Reproductive success of soybean cultivars and exotic lines under high daytime temperature. Plant, Cell and Environment. https://doi.org/10.1111/pce.13421.

Clinton J. Steketee, William T. Schapaugh, Thomas E. Carter and Zenglu Li. 2020. Genome-Wide Association Analyses Reveal Genomic Regions Controlling Canopy Wilting in Soybean. G3: Genes, Genomes, Genetics, 2020 vol. 10 no. 4 1413-1425; https://doi.org/10.1534/g3.119.401016.

Heng Ye, Li Song, William T Schapaugh, Md Liakat Ali, Thomas R Sinclair, Mandeep K Riar, Raymond N Mutava, Yang Li, Tri Vuong, Babu Valliyodan, Antonio Pizolato Neto, Mariola Klepadlo, Qijian Song, J Grover Shannon, Pengyin Chen, Henry T Nguyen, The importance of slow canopy wilting in drought tolerance in soybean, Journal of Experimental Botany, Volume 71, Issue 2, 7 January 2020, Pages 642–652, https://doi.org/10.1093/jxb/erz150.

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.