Project Details:

Integrating Germplasm Evaluation, Genetic Engineering, Breeding and High-Throughput Phenotyping to Improve Sustainability of Soybean Production

Parent Project: This is the first year of this project.
Checkoff Organization:Kansas Soybean Commission
Categories:Breeding & genetics
NCSRP, USB, QSSB Project Code:1730
Project Year:2017
Lead Principal Investigator:William Schapaugh (Kansas State University)
Co-Principal Investigators:
William Schapaugh (Kansas State University)
Tim C. Todd (Kansas State University)
Harold Trick (Kansas State University)
Keywords:

Contributing Organizations

Funding Institutions

Information and Results

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Project Summary

1. Genomic selection. Advances in genomics have made whole-genome genotyping cost effective, but to utilize this information, robust models must be developed capable of predicting phenotype. Model development requires high-quality phenotypic data which we will collect.
2. Identify new sources of "good" germplasm. Limited genetic variation is present in the commercial gene pool. Without adequate levels of "good" genetic variation, progress from selection can slow, or even stop. Searching the germplasm collection for beneficial genetic variation will help maintain, or enhance improvements made through breeding.
3. Develop superior varieties using exotic germplasm. Potentially "good" germplasm will be used as parents to develop new progeny to help bridge the gap in performance between the exotic germplasm and elite varieties. This effort can result in the development of a new commercial product, or better enable the use of the exotic germplasm by private breeding programs. Additionally, there is a need for new and more effective sources of pest resistance, particularly for SCN. Private breeding programs primarily rely on a single source of resistance (PI 88788), which has become ineffective for many populations in Kansas and other North Central states.
4. Develop high yielding soybean varieties with desirable levels of protein and oil. Over the last 85 years protein levels in soybean have decreased about 2 percentage points. This trend will likely continue and negatively impact the value of soybean meal, unless better efforts are made to focus on composition while improving seed yield.
5. Develop high oleic varieties. High oleic soybean represents a value-added commodity.
6. Breed transgenic events into elite breeding lines. Incorporating transgenic events into elite breeding lines offers novel traits for SDS, SCN and RKN resistance.
7. Develop SDS resistant varieties. Soybean sudden death syndrome (SDS), caused by Fusarium virguliforme, consistently ranks within the top-five yield reducing soybean diseases. Even with the development of a recent seed treatment that reduces disease severity, higher levels of resistance are needed for effective management and maximum seed yields. This resistance is most effective when combined with SCN resistance.
8. Develop soybean varieties and germplasm with stacked traits. The traits that will be focused on for stacking represent some of the most important and chronic issues for Kansas soybean producers. Germplasm with stacked traits for pest resistance and yield stability will be useful to both public and private breeding programs. Varieties developed with such stacked traits will be useful to producers precisely because of their yield stability across the diverse environmental and pest conditions in Kansas.
9. Develop high throughput technology. This technology can improve the speed and accuracy of identifying superior breeding material, and permit the selection of traits that have never before been evaluated on a widespread basis.

Project Objectives

1. Provide high quality germplasm and phenotypic data for development of genome selection tools
2. Identify new sources of germplasm (exotic) and genes that improve yield and seed composition of elite U.S. soybean varieties
3. Develop superior varieties and germplasm using new sources of germplasm with improved yield under the extreme range of environmental conditions in KS
4. Develop high yielding varieties and germplasm lines with desirable levels of protein and oil
5. Develop non-GMO, high oleic soybean varieties and germplasm lines
6. Breed transgenic events into elite breeding lines
7. Develop superior SDS resistant varieties and germplasm lines using new sources of resistance
8. Develop soybean varieties and germplasm with stacked traits, including SCN and SDS resistance, optimal protein and oil concentrations, and stress tolerance
9. Develop enhanced high throughput technology to rapidly identify genotypes which have the desired disease resistance, yield potential, drought resistance or heat stress characteristics

Project Deliverables

1. qgnomjc_selegtiQL2 In support of an NCSRP project, produce new genotypes and evaluate those genotypes in field evaluations to collect agronomic data used in the development of genomic selection tools. Evaluations will consist of exotic germplasm, elite breeding lines, and advanced lines in the Uniform Soybean Performance Tests.
2. Identify new sources of "good" germplasm. Screen hundreds of different germplasm (exotic germplasm) not contributing to the genetic diversity of US soybean varieties for seed yield, maturity, lodging, shattering, seed composition, and stress response. Genotypic data is also being collected on these accessions in support of Objective 1.
3. Develop superior varieties using exotic germplasm. Each year, develop approximately 40 populations involving exotic parents or lines derived from exotic germplasm with high yielding, elite varieties. Evaluate progeny in both dryland and irrigation field conditions in KS and the US and characterize resistance to soybean cyst nematode (SCN) and Soybean Sudden Death Syndrome (SDS). Increase the diversity in SCN populations used in screening trials to represent the natural diversity in SCN populations across Kansas.
4. Develop high yielding soybean varieties with desirable levels of protein and oil. Through a USB project, utilize exotic sources to breed for increased protein and yield. We will also target oil concentrations in our work in KS. Each year, develop approximately 15 populations involving exotic parents or lines derived from exotic germplasm with high yielding, elite varieties. Evaluate progeny in both dryland and irrigation field conditions in KS and the US and characterize resistance to SCN and SDS.
5. Develop high oleic varieties. Conventional germplasm owned jointly by the USDA and the Missouri Soybean Merchandizing Council is available with high oleic acid. Once an MTA is signed, the high-oleic trait will be incorporated into KS adapted material through backcrossing and forward crosses.
6. Breed transgenic events into elite breeding lines. In previous funding from KSC, NCSRP, and USB we have produced stable transgenic lines showing enhanced resistance to SCN. Current KSC research is evaluating alternative methods for SDS, SCN and RKN. Together with stable lines already produced we will move these traits to elite breeding lines that have traditional resistances.
7. Develop SDS resistant varieties. Use resistant lines identified from a previous NCSRP SDS breeding project to combine SDS and SCN resistance. Each year, develop approximately 15 populations involving exotic parents or lines derived from exotic germplasm with high yielding, elite varieties. Evaluate progeny in both dryland and irrigation field conditions in KS and the US and characterize resistance to SCN and SDS.
8. Develop soybean varieties and germplasm with stacked traits. Each year, soybean lines exhibiting a wide range of desirable traits, including pest resistance, yield stability, and seed quality will be used to develop new populations to produce progeny with combinations of the most desirable traits for Kansas soybean producers, with the ultimate goal of developing varieties with broad pest resistance and yield stability.
9. Develop high throughput technology. Record in-season soybean canopy thermal and spectral profiles with a small unmanned aircraft system (sUAS) at irrigated and dryland research plots. Genotypes possessing extremes in phenotypes (such as disease resistance, wilting and canopy temperature) will be included in the evaluations. Effectiveness of the system will be assessed by correlating thermal and spectral canopy profiles with relative seed yield, relative maturity, and wilting scores. This phenotypic data will be used to support gene mapping.

Progress of Work

Update:
We completed the release and licensing of the new soybean variety KS4117Ns this quarter.

During the summer of 2017, experimental lines in maturity groups III-V will be tested at eight breeding nurseries located throughout Kansas.

We will be evaluating the 29 Conventional K-lines in the National Regional trials this year in maturity groups III through V.

We will be increasing two conventional group 4 varieties, three conventional group 5 varieties and one glyphosate resistant group IV variety for possible release in 2018.

We are in the processes of SCN screening in the greenhouse, and STS screening in the lab.

The Spring greenhouse of backcross populations was harvested and seeds incorporated into the summer crossing block.

The F1 generation in the Puerto Rico winter nursery was harvested and the F2 generation planted.

Plans for our field trials currently involve the evaluation of more than 6800 experimental K-lines and another 800+ experimental lines/plant introductions from cooperative trials in over 14,000 plots. To date, six of our eight sites have been planted, including:

On 5/15 planted tests at Onaga consisting of 110 Kansas Advanced (KA) entries in 240 plots, 50 Uniform Test (UT) entries in 120 plots and 45 Soybean Variety Performance Test (SVPT) entries in 180 plots.

On 5/9 planted tests at Rossville for yield and SDS evaluations consisting of 131 SVPT entries in 393 plots and 160 NAM entries in 640 plots.

On 5/25 planted tests at Manhattan irrigated field consisting of: 170 KA entries in 380 plots; 6111 progeny rows containing K-lines; 567 Kansas preliminary yield plots; 123 UT entries in 289 plots; 286 Diversity entries in 572 plots; 26 lines to serve as parents for the 2017 summer crosses.

On 5/16 planted tests at Ottawa consisting of; 190 KA entries in 380 plots; 50 UT entries in 120 plots; 74 diversity entries in 222 plots.

On 5/18 planted tests at Salina consisting of: 34 SVPT entries in 136 plots; 544 Germplasm lines in 1446 plots; 190 KA entries in 380 plots.

On 5/30 planted tests at Pittsburg consisting of: 70 KA entries in 140 plots; 155 UT entries in 370 plots; 56 SVPT entries in 224 plots.

Work continued to setup tests and packet seed to evaluate entries in the following trials:

For Manhattan dryland: 110 KA entries in 240 plots; 50 UT entries in 120 plots; 450 KP entries in 450 plots; F3 and F4 populations.

For McCune: 70 KA entries in 140 plots; 155 UT entries in 370 plots; 68 SVPT entries in 272 plots.

We plan to continue our remote sensing projects this summer to produce models that accurately predict relative seed yield, relative maturity and SDS resistance. This year, we are expanding our drone-based sensors.

Update:
On 6/5 planted tests for the Manhattan irrigated progeny row consisting of over 6000 genotypes.

On 6/6 planted over 150 seed increases consisting of lines in advanced stages of testing.

On 6/7 planted material for the Manhattan dryland location, consisting of: 120 KA entries in 240 plots; 450 KP plots and our F3 and F4 populations.

On 6/12 planted double-crop tests at Pittsburg, consisting of: 56 SVPT entries in 224 plots.

On 6/13 planted tests at McCune, consisting of: 70 KA entries in 140 plots; 155 UT entries in 370 plots; 68 SVPT entries in 272 plots.

On 6/21 replanted planted tests at Ottawa that were destroyed by hail in May.

We completed our 2017 crossing season with over 70 different populations created. A detailed list of the populations will be included in the final report after the successful crosses are harvested.

We have completed the Race 3 SCN screening tests for our breeding material and commercial varieties and now are evaluating resistance to a Race 4 population. Initial SDS ratings have been taken on breeding material and commercial varieties at the Rossville disease nurseries. Final rating will be completed in September.

Since July we have captured spectral and thermal remotely sensed data every 7 to 14 days at our Salina, Manhattan and Rossville nurseries using drones. We will use this data to produce models that accurately predict relative seed yield, maturity and SDS resistance.

Multiple populations continue to be advanced at our winter nursery facility in Puerto Rico.

Update:
Over 50 new populations created this season were harvested, and the F1 generation has been advanced to the winter nursery in Puerto Rico. This generation has been planted and good stands were established. Over 60 F3 populations were advanced to the F4 generation during the summer of 2016. High priority populations have been continuously advanced in our winter nursery in Puerto Rico to produce experimental varieties for field testing one year earlier than our standard breeding cycle. We continued the conversion of six high yielding elite conventional lines into RR1 varieties in the field crosses and have established a fall greenhouse in Manhattan to: 1) continue to advance the generations during the winter of RR1 and high oleic germplasm and 2) create new populations focusing on seed yield, seed composition and disease resistance.

We completed harvest this quarter involving the evaluation of over 6000 experimental K-lines and another 350 elite experimental lines from other states field trials. Productivity and precision of the 2017 season was good. Seed yield was collected on over 14000 plots in 2017. Data are being compiled for all K-lines and experimental lines from other experiment stations. Decisions on what lines to advance, increase or discard will be finalized next quarter.

Results from our evaluation of about 130 commercial soybean varieties for Soybean Cyst Nematode Races 3 and 4 in the greenhouse and Soybean Sudden Death in the field have been completed and analyzed. Results will be posted on the Agronomy Department’s Crop Performance Tests website.

Working with Shrada (Ag Eng) and Asebedo (Agron) we captured over 10,000 spectral images on breeding plots located at Rossville, Manhattan and Assaria. We are analyzing these images now to help characterize drought response, seed yield, plant maturity and resistance to Soybean Sudden Death Syndrome.

A total of over 500 plant introductions in MG’s 3 through 5, along with 200 elite lines were grown in Manhattan, KS and/or Ottawa, KS in replicated plots. Maturity, lodging, plant height, shattering and seed yield were collected on most of the genotypes. Seed samples are being collected for seed composition determination, and seed quality and seed weight measurements. Data will be summarized along with information from other states to identity unique germplasm which could benefit breeding efforts across the country.

We initiated crossing of transgenic lines expressing transgenic resistance to SCN to KS germplasm (K11-2363 and K12-2333). Also, we crossed resistant transgenic lines together (hpRNAi-Y25 and hpRNAi-Prp17) to attempt to combine the two resistance mechanisms into a single variety. Field trials of some of this material is planned for 2018.

From work partially supported by the Kansas Soybean Commission the following publications have been accepted or submitted.

Published in TAG: Genome-wide association mapping of canopy wilting in diverse soybean genotypes. Avjinder S. Kaler, Jeffery D. Ray, William T. Schapaugh, C. Andy King, Larry C. Purcell.

Published in TAG: Meta-analysis to refine map position and reduce confidence intervals for delayed-canopy-wilting QTLs in soybean. Sadal Hwang, C. Andy King, Pengyin Chen, Jeffery D. Ray, Perry B. Cregan,T.E. Carter Jr., Zenglu Li, Hussein Abdel-Haleem , Kevin W. Matson, William Schapaugh Jr., Larry C. Purcell.

Accepted for publication in G3: Genome-wide analysis of grain yield stability and environmental interactions in a multi-parental soybean population.

Published in BMC Genomics: Genome-wide identification of soybean microRNA responsive to soybean cyst nematodes infection by deep sequencing. B. Tian, S. Wang, T.C. Todd, C.D. Johnson, G. Tang, H.N. Trick.

Submitted: Association mapping identifies loci for canopy temperature under drought in diverse soybean genotypes, UAR and KSU.

Updated June 21, 2018:

View uploaded report PDF file

Final Project Results

Benefit to Soybean Farmers

• Searching the germplasm collection for beneficial genetic variation will help maintain, or enhance improvements made through breeding. For example, protein levels in soybean have decreased about 2 percentage points over the past 85 years. This trend will likely continue and negatively impact the value of soybean meal, unless better efforts are made to focus on composition while improving seed yield. Additional traits targeted for improvement include high oleic content, which represents a value-added commodity.
• Incorporating transgenic events into elite breeding lines offers novel traits for SDS, SCN and RKN resistance. There is an urgent need for new and more effective sources of pest resistance, particularly for SCN. Private breeding programs primarily rely on a single source of resistance (PI 88788), which has become ineffective for many populations in Kansas and other North Central states.
• Soybean sudden death syndrome (SDS), caused by Fusarium virguliforme, consistently ranks within the top-five yield reducing soybean diseases. Even with the development of a recent seed treatment that reduces disease severity, higher levels of resistance are needed for effective management and maximum seed yields. This resistance is most effective when combined with SCN resistance.
• The traits that will be focused on for stacking represent some of the most important and chronic issues for Kansas soybean producers. Germplasm with stacked traits for pest resistance and yield stability will be useful to both public and private breeding programs. Varieties developed with such stacked traits will be useful to producers precisely because of their yield stability across the diverse environmental and pest conditions in Kansas.
• High throughput technology can improve the speed and accuracy of identifying superior breeding material, and permit the selection of traits that have never before been evaluated on a widespread basis.

Performance Metrics

Project Years