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ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Molecular Plant Pathology Laboratory Research





- Nemchinov, Lev
- 2023
- 2022
- 2021
- 2020
- 2019
- Publications
- Grass, Forage, and Rangeland Agroecosystems (215)
- Plant Genetic Resources, Genomics and Genetic Improvement (301)
- Plant Diseases (303)

Research Project: **Location:
                            Molecular Plant Pathology Laboratory** Project Number: 8042-21000-300-000-D
                        
                        Project Type: In-House Appropriated Start Date: Mar 25, 2019
                        
                        End Date: Mar 24, 2024 **Objective:**
                        
                        1.	 Identify and develop molecular characterizations of new and emerging disease-causing pathogens in alfalfa to prevent potential threats to alfalfa production.

Many known bacterial, fungal, oomycete, nematode, mollicute or viral diseases represent causes of concern for alfalfa industry. In addition, new, emerging and invasive pathogens of uncertain impact pose a serious challenge to the alfalfa improvement. Rapid identification of the causal agents, their characterization at the molecular level and development of sensitive diagnostic assays will reduce yield losses and prompt new insights into practices of alfalfa disease management.

2.	Identify genes involved in stress responses in alfalfa to define the genetic basis of resistance and accelerate breeding programs.
Emerging disease challenges demand novel approaches to maintain and improve alfalfa production. Understanding molecular mechanisms of stress tolerance is an essential requirement for improvement of alfalfa adaptability and acceleration of breeding programs in increasingly less favorable environmental conditions. **Approach:**
                        
                        To fulfill the main goal of Objective 1, the Project will pursue rapid identification of the causal agents, their characterization at the molecular level, and development of sensitive diagnostic assays, aiming to reduce yield losses and to prompt new insights into practices of alfalfa disease management. The approach and research methodology for the detection and/or discovery of new biological and environmental stressors influencing alfalfa quality and productivity will include the following steps critical for the success of the Project:

•	Specimens collection: alfalfa samples delivery will be negotiated with colleagues, collaborators, alfalfa extension specialists, commercial growers, industry professionals and with diagnostic laboratories-participants of the National Plant Diagnostic Network. Samples will also be collected during on-site visits to alfalfa fields for detection of plant pathogens.
•	Diagnostics and identification: alfalfa samples will be evaluated by visual assessment, microscopic tools, molecular detection methods (PCR/RT-PCR, LAMP and others), serological assays, and next generation sequencing.
•	Molecular characterization: identified plant pathogens will be further characterized at the molecular level using comprehensive bioinformatics, molecular and phylogenetic tools.
•	Development of specific diagnostics tools for pathogen detection, such as pathogen-specific PCRs (conventional, RT-PCR, quantitative PCR, nested and multiplex PCR), molecular hybridization techniques, and serological assays.
•	Field pathogenomics: integration of genomic data into traditional pathogen surveillance activities.

To fulfill the main goal of Objective 2, the Project will use modern experimental and genomic tools combined with computational analysis and systems biology research. Consecutively applied toward each of the plant-pathogen interaction studies, these state-of-the-art methodologies will enable identification and characterization of the genes, involved in stress responses in alfalfa.
•	Experimental approaches will primarily include the latest high-throughput sequencing methodologies to capture and quantify transcripts present in an RNA extract.
•	Computational approach will include transcript quantification (estimation of gene and transcript expression); differential gene expression analysis (comparison of expression values among different samples); and functional profiling of RNA-seq data (characterization of the molecular functions or pathways in which differentially expressed genes (DEGs) are involved)
•	Systems biology research will integrate quantitative metagenomics data into descriptions of genes, pathways, cellular processes and networks to uncover biological insights of alfalfa adaptive responses.
•	To supplement high-throughput transcriptomics data, the project will attempt to employ global proteomic profiling to identify and characterize proteins involved in alfalfa responses to stress.


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