Location: Plant Germplasm Introduction and Testing Research
2023 Annual Report
Objectives
Objective 1: Identify DNA markers associated with resistance to soil borne diseases in alfalfa to clearly define the genetic basis of resistance to disease and accelerate breeding programs. (NP215 2A)
Objective 2: Identify alfalfa DNA markers and germplasm associated with drought and salt tolerance to clearly define the genetic basis of resistance to these stressors and accelerate breeding programs. (NP215 2A).
Approach
Approach 1: Marker-assisted selection for disease resistance will increase selection accuracy and reduce selection cycles in alfalfa breeding programs. First, genome-wide association mapping will be used to identify loci associated with VW resistance. Then, genetic regions responsible for VW resistance will be sequenced and compared among different genotypes using haplotyping and comparative genomics approaches. Significant SNP markers linked to VW resistance loci will be validated in various breeding populations provided by collaborators. High throughput platforms such as Kompetitive Allele Specific PCR (KASP) (www.lgcgenomics.com) or Taqman (www.thermofisher.com) assays will be used to test the cosegregation of marker loci and disease resistance scores. Flanking sequences for the significant SNP markers will be used for designing specific primers for array-based genotyping platforms (KASP or Taqman). Multiplex primer combinations will be used for evaluating the resistance locus or candidate gene, and all markers will be scored in a given genotype. Single markers with two character states will be tested for significant phenotypic differences between genotype groups by the t test for each trait, and Mann–Whitney U test for chip quality. Marker combinations will be analyzed using analysis of variance (ANOVA) for each trait, and Kruskal–Wallis test for chip quality. Statistical analyses will use SAS software (SAS Institute Inc. 2011, SAS OnlineDoc 9.3, Cary, NC, USA).
Approach 2: Breeding for abiotic stress tolerance is challenged by genotype x environment interactions (G x E). Genomic selection provides greater gain and increased selection accuracy than conventional breeding. To develop a genome-wide marker platform and statistical models for genomic selection of drought tolerant alfalfa. BC1 populations have been developed and will be screened for drought tolerance. Selected plants will be randomly intermated in the greenhouse in order to generate an elite base population. The population will used for associated mapping and genomic selection for alleles that affect drought tolerance, salt tolerance, forage quality and other economical traits. We will test statistic models by using the majority of the training population to create a prediction model, which is then used to predict a Genomic Estimated Breeding Value (GEBV) for each of the remaining individuals in the training population based only on their genotype data. Once validated, the model can then be applied to a breeding population to calculate GEBVs of each individual based only on a plant’s genotype information. Such GEBVs represent the overall predicted value of an individual as a potential parent for crossing.
Progress Report
This report documents the progress achieved in fiscal year (FY) 2023 for project 2090-21000-036-000D, titled, “Enhancing Resistance to Biotic and Abiotic Stresses in Alfalfa”.
In support of Objective 1, research continued on the validation of the markers associated with resistance to Verticillium wilt (VW) of alfalfa, which is a devastating disease that reduces forage yields by up to 50% in the Northern United States and Canada. To understand the genetic basis of resistance in alfalfa to Verticillium wilt an ARS scientist in Prosser, Washington, used DNA markers to identify genes associated with disease resistance. Multiple loci were associated with VW resistance in alfalfa. Three markers tightly linked with the resistance loci were developed for use with high throughput breeding strategies. The markers can be used to identify resistance alleles in parents and progeny in alfalfa. These markers have been transferred to seeds companies for marker-assisted selection in their breeding program. Additionally, two linked R genes associated with VW resistance have been cloned and their functions were characterized. One of the R genes identified functions positively in defense against VW while another responds negatively. The results have been reported in the 2022 Plant and Animal Genome Conference and published in peer-reviewed Journals.
In support of Sub-objective 2A, ARS researchers made progress on developing molecular markers associated with drought resistance. In the western United States, the great majority of alfalfa is produced with supplemental irrigation water, which represents a large part of the total costs for a producer. An ARS scientist in Prosser, Washington, in collaboration with ARS researchers in Logan, Utah, and several universities, developed multiparent populations using 32 drought resistant parents crossed with the elite cultivar Guardsman II. The F1 progeny was then backcrossed with parents to create F1B1 populations. These have been testing in the field for drought resistance. Biomass yield, plant height and growth vigor under drought were measured and analyzed with a marker-based strategy for genomic selection (GS). Alfalfa lines with resistance to drought were selected using the GS models to create new resistant alfalfa varieties.
In support of Sub-objective 2B, progress was made on developing molecular markers associated with salt resistance. Many agricultural lands in the Western United States have soil with high concentrations of salt, which are detrimental to alfalfa survival and production, especially under limited water conditions. Developing salt tolerant varieties is imperative for sustainable alfalfa production in areas with increasing soil salinity. An ARS scientist in Prosser, Washington, in collaboration with another ARS scientist from Logan, Utah, used alfalfa breeding populations in a genome-wide association analysis and identified 49 loci associated with salt tolerance. Twenty-one candidate genes underlying the intervals of the resistance loci have been reported to play roles in response to salt stress. The closely linked markers can be used for marker-assisted selection in developing alfalfa with enhanced resistance to high salinity soil. These markers have been published the peer-reviewed journals and reported in the World Alfalfa Congress.
Accomplishments
1. Development of DNA markers for Verticillium wilt resistance in alfalfa. Verticillium wilt is an alfalfa disease that reduces forage yields by up to 50 percent. Current breeding strategies primarily rely on field or greenhouse screening to identify disease resistant plants, which is a time-consuming process requiring specific conditions to produce reliable results. An ARS scientist in Prosser, Washington, identified VW resistance genes and developed high-throughput DNA markers and related strategy to identify VW resistance alleles in alfalfa breeding populations. Three DNA markers have been transferred by MTA to a major alfalfa commercial producer to accelerate breeding programs to develop new varieties with enhanced resistance to Verticillium wilt.
2. Selection of alfalfa lines with drought tolerance for alfalfa breeding programs. In the western United States, the great majority of alfalfa is produced with supplemental irrigation water, which represents a large part of the total costs for a producer. An ARS scientist in Prosser, Washington, tested 200 accessions of alfalfa in the field for drought tolerance, and selected 8 drought resistance lines. These lines were transferred to two seeds companies for their breeding programs with MTAs. Seeds of drought resistance germplasm were submitted to the ARS Western Regional Plant Introduction Station for distribution.
3. Selection of alfalfa lines with salt tolerance for pre-breeding. In the western United States, the impacts of soil salinization on alfalfa production will become more pervasive and severe in the future. An ARS scientist in Prosser, Washington, in collaboration with another ARS scientist tested 200 alfalfa accessions in the field for salt resistance. Agronomic traits were measured and analyzed with statistic models for phenotypic variation in the populations. Alfalfa lines with salt resistance have been selected and seeds were produced. They can be used as pre-breeding materials for developing new varieties with improved resistance to high salinity soil.
Review Publications
He, X., Zhang, F., He, F., Shen, Y., Yu, L., Zhang, T., Kang, J. 2022. Accuracy of genomic selection for alfalfa biomass yield in two full-sib populations. Frontiers in Plant Science. 13. Article 1037272. https://doi.org/10.3389/fpls.2022.1037272.
Jiang, X., Yu, A., Zhang, F., Yang, T., Wang, C., Gao, T., Yang, Q., Yu, L., Wang, Z., Kang, J. 2022. Identification of QTL and candidate genes associated with biomass yield and feed quality in response to water deficit in alfalfa (Medicago sativa L.) using linkage mapping and RNA-Seq. Frontiers in Plant Science. 13. Article 996672. https://doi.org/10.3389/fpls.2022.996672.
Lin, S., Medina, C., Wang, G., Combs, D., Shewmaker, G., Fransen, S., Llewellyn, D., Norberg, S., Yu, L. 2023. Identification of genetic loci associated with five agronomic traits in alfalfa using multi-environment trials. Journal of Theoretical and Applied Genetics. 136. Article 121. https://doi.org/10.1007/s00122-023-04364-4.
Jiao, Y., He, X., Song, R., Wang, X., Zhang, H., Aili, R., Chao, Y., Shen, Y., Yu, L., Zhang, T., Jia, S. 2022. Recent structural variations in the Medicago chloroplast genomes and their horizontal transfer into nuclear chromosomes. Journal of Systematics and Evolution. 61(4):627-642. https://doi.org/10.1111/jse.12900.
Long, R., Zhang, F., Zhang, Z., Li, M., Chen, L., Wang, X., Liu, W., Zhang, T., Yu, L., He, F., Jiang, X., Yang, X., Yang, C., Wang, Z., Kang, J., Yang, Q. 2022. Genome assembly of alfalfa cultivar Zhongmu-4 and identification of SNPs associated with agronomic traits. Genomics, Proteomics and Bioinformatics. 20(1):14-28. https://doi.org/10.1016/j.gpb.2022.01.002.
