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ARS Home Midwest Area Columbia, Missouri Plant Genetics Research Research





- Gillman, Jason
- Krishnan, Hari
- Bilyeu, Kristin
- 2023
- 2022
- 2021
- 2020
- 2019
- 2018
- Publications
- Plant Genetic Resources, Genomics and Genetic Improvement (301)

Research Project: Gene Discovery and Designing Soybeans for Food, Feed, and Industrial Applications **Location:
                            Plant Genetics Research** 2019 Annual Report **Objectives**
                                

Objective 1:  Identify new soybean alleles, or effective combinations of existing genes, that positively impact commercially relevant oil or meal traits; work with breeders to incorporate them into modern backgrounds; confirm their expression or effectiveness under field conditions; and determine value in food or feed applications. 
	
Objective 2:  Identify and verify new genomic regions in soybean associated with improved stress tolerance, seed constituent (oil and protein), and quality traits, and use genomic strategies such as genetic mapping and genome analysis to make new genes rapidly available to breeders.  

Objective 3:  Develop novel strategies to increase concentrations of S-containing amino acids and to reduce levels of trypsin inhibitor and allergens; work with breeders to develop soybean germplasm that combine these genes in high protein backgrounds to meet the animal nutrient requirements. **Approach**
                                

Obj 1- New soybean germplasm will be developed with combinations of the high oleic-low linolenic oil trait and low raffinose oligosaccharide meal trait that is targeted to different maturity groups (MG). Seeds produced in an appropriate environment will be evaluated for trait interactions, environmental stability, protein and oil content, and yield. We will establish a novel panel of approximately 400 soybean accessions from the National Plant Germplasm System (NPGS) and conduct genome-wide association studies (GWAS) with protein and oil data. Mutant soybean lines will be screened to identify seed composition variants.
Obj 2- We will use a four pronged approach in order to dissect the genetic architecture underlying soybean seed value (principally seed oil and protein content) and abiotic stress adaptation: 2.1) a new GWAS using a diverse panel of 380 MG III genotypes to maximize genetic diversity within a very narrow maturity range; 2.2) Genomic Prediction to estimate seed composition breeding values for all 2,011 MG III accessions; 2.3) Fine mapping of a heat-tolerance trait from an exotic landrace; and 2.4) Development of a Multi-Parent Advanced Generation Inter-Cross (MAGIC) population. We will evaluate the potential of Genomic Prediction to predict seed composition and select parents with maximal genetic potential for developing a MAGIC population. We will Fine-map a previously identified major effect QTL associated with tolerance to heat-induced-seed-degradation.
Obj 3- We will develop and characterize soybean germplasm with increased sulfur (S)-containing amino acids and decreased anti-nutritional factors. To enhance the S amino acid content, we plan to overexpress an enzyme in the sulfur assimilation pathway. Additionally, high-protein soybean experimental lines lacking Kunitz trypsin inhibitor (KTI) and ß-conglycinin, will be developed using a traditional breeding approach. In order to verify if overexpression of tow enzymes simultaneously will further increase the overall S-amino acid content, we will characterize ATPS and OASS activity in greenhouse grown material from genetic crosses between overexpressing transgenic soybeans lines. To better understand the chilling stress responses in soybean, a comparative proteomic analysis will be performed. **Progress Report**
                                

Substantial progress towards Objective 1 has been made. A successful series of plant generations (one in the U.S. and two at the winter nursery) enabled the identification of key allele combinations as targeted in the project plan.  The experiments to break genetic linkages between maturity genes and seed composition genes is ahead of schedule.  Experiments to target maturity groups 0, I, and V with the seed composition combination are on schedule.  Soybean lines were identified that contain seed composition traits plus a yield-influencing plant architecture trait.  Seed protein and oil content were determined for the set of about 400 lines with seed produced in one environment. Seed protein and oil content were determined for yield tested lines with seed composition combinations.

For Objective 2, we completed a field study and data collection related to milestone 2.1 in FY2019 and are well on the way towards completion of 24 and 36 month milestones. Extant data allowed development of a genomic prediction model which identified the 100 most divergent seed composition lines from the germplasm collection, which are evaluated in a multi-location 2019 field experiment. Parental lines for a large multi-parent population have been identified and initial hybridizations will commence this summer, ahead of schedule.

In the model plant Arabidopsis, overexpression of adenosine triphosphate sulfurylase results in the production of elevated levels of cysteine and glutathione. Additionally, elevated levels of these compounds have been shown to protect the plants against environmental stress. Towards Objective 3, we are developing strategies to increase the concentration of S-containing amino acids in soybean. For this purpose, we are targeting overexpression of adenosine triphosphate sulfurylase, the entry point enzyme of sulfur assimilation to provide increased metabolic flux through the pathway. We have generated constructs for both seed-specific and constitutive expression of adenosine triphosphate sulfurylase in transgenic soybeans. To distinguish the introduced adenosine triphosphate sulfurylase in transgenic plants from the native enzyme, we have introduced a hexahistidine tag at the C-terminus of the enzyme. These constructs have been transferred into Agrobacterium tumefaciens and are currently being employed by the University of Missouri Plant Transformation Core Facility for the generation of transgenic soybeans. **Accomplishments** **Review Publications**
                            *Smallwood, C., Saxton, A., Gillman, J.D., Bhandari, H., Wadl, P.A., Fallen, B., Hyten, D., Song, Q., Pantalone, V. 2019. Context-specific genomic selection strategies outperform phenotypic selection for soybean quantitative traits in the progeny row stage. Crop Science. 59(1):54-67. https://doi.org/10.2135/cropsci2018.03.0197.*
                                *Alaswad, A.A., Oehrle, N.W., Krishnan, H.B. 2019. Classical soybean (Glycine max (L.) Merr) symbionts, Sinorhizobium fredii USDA191 and Bradyrhizobium diazoefficiens USDA110, reveal contrasting symbiotic phenotype on pigeon pea (Cajanus cajan (L.) Millsp). International Journal of Molecular Sciences. 20(5):1091. https://doi.org/10.3390/ijms20051091.*
                                *Kim, W., Krishnan, H.B. 2018. Impact of co-expression of maize 11 and 18 kDa delta-zeins and 27 kDa gamma-zein in transgenic soybeans on protein body structure and sulfur amino acid content. Plant Science. 280:340-347. https://doi.org/10.1016/j.plantsci.2018.12.016.*
                                *Krishnan, H.B., Kim, W., Givan, S.A. 2019. Draft genome sequence of bradyrhizobium sp. Strain LVM 105, a nitrogen-fixing symbiont of chamaecrista fasciculata (michx) greene. Microbiology Resource Announcements. 8(14):e00132-19. https://doi.org/10.1128/MRA.00132-19.*
                                *Krishnan, H.B., Oehrle, N.W., Alaswad, A.A., Stevens, W., John, M.K., Luthria, D.L., Natarajan, S.S. 2019. Biochemical and anatomical investigation of Sesbania herbacea (Mill.) McVaugh nodules grown under flooded and non-flooded conditions. International Journal of Molecular Sciences. 20(8):1824. https://doi.org/10.3390/ijms20081824.*
                                *Xu, Q., Liu, F., Qu, R., Gillman, J.D., Bi, C., Hu, X., Chen, P., Krishnan, H.B. 2018. Transcriptomic profiling of Lathyrus sativus L. metabolism of ß-ODAP, a neuroexcitatory amino acid associated with neurodegenerative lower limb paralysis. Plant Molecular Biology Reporter. 36(5-6):832-843. https://doi.org/10.1007/s11105-018-1123-x.*
                                *Miranda, C., Culp, C., Skrabisova, M., Joshi, T., Belzile, F., Grant, D.M., Bilyeu, K.D. 2019. Molecular tools for detecting Pdh1 can improve soybean breeding efficiency by reducing yield losses due to pod shatter. Molecular Breeding. 39:27. https://doi.org/10.1007/s11032-019-0935-1.*
                                *Krishnan, H.B., Jez, J.M. 2018. Review: The promise and limits for enhancing sulfur-containing amino acid content of soybean seed. Plant Science. 272:14-21. https://doi.org/10.1016/j.plantsci.2018.03.030.*
                                *Jones, L.D., Pangloli, P., Krishnan, H.B., Dia, V.P. 2018. BG-4, a novel bioactive peptide from momordica charantia, inhibits lipopolysaccharide-induced inflammation in THP-1 human macrophages. Phytomedicine. 42:226-232. https://doi.org/10.1016/j.phymed.2018.03.047.*
                                *Islam, N., Bates, P.D., John, M.K., Krishnan, H.B., Zhang, Z., Luthria, D.L., Natarajan, S.S. 2019. Quantitative proteomic analysis of low linolenic acid transgenic soybean reveals perturbations of fatty acid metabolic pathways. Proteomics. 19:1-11. https://doi.org/10.1002/pmic.201800379.*
                                *Combs, R., Bilyeu, K.D. 2019. Novel alleles of FAD2-1A induce high levels of oleic acid in soybean oil. Molecular Breeding. 39:79. https://doi.org/10.1007/s11032-019-0972-9.*
                                *Nieto-Veloza, A., Wang, Z., Zhong, Q., Krishnan, H.B., Dia, V.P. 2019. BG-4 from bitter gourd (Momordica charantia) differentially affects inflammation in vitro and in vivo. Antioxidants. 8(6):175. https://doi.org/10.3390/antiox8060175.*
                                *Jo, H., Lorenz, A., Rainey, K., Shannon, J., Chen, P., Bilyeu, K.D. 2019. Environmental stability study of soybeans with modified carbohydrate profiles in maturity groups 0 to V. Crop Science. 59(4):1531-1543. https://doi.org/10.2135/cropsci2018.09.0600.*


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