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ARS Home » Southeast Area » Stoneville, Mississippi » Genomics and Bioinformatics Research » Research » Research Project #434717
Research Project: Applied Agricultural Genomics and Bioinformatics Research

Location: Genomics and Bioinformatics Research

2022 Annual Report


Objectives
1. Advance and accelerate translational research for ARS and its collaborators that addresses the agricultural needs of primarily the Southeast region, through data generation, data analysis, and data management, with an emphasis on genomic approaches and on crop, animal, insect, and microbiome analyses; support germplasm analysis for breeding and for trait genetic and molecular analyses; and support gene expression analysis and gene discovery. 1.A. A cross section of GBRU operations in genomics and bioinformatics. 1.B. Specific ongoing collaborative projects. 1.C. Data Management. 2. Accelerate ARS bioinformatics community development and capacity building, primarily for the Southeast region, through training workshops, webinars, and direct project participation; develop and evaluate new tools, workflows, and systems that enable ARS and its collaborators to more efficiently manage, analyze, and share diverse streams of biological data and knowledge, including high throughput genotyping and phenotyping, thereby enhancing crop and animal genetic improvement, health, and nutrition. 2.A. Bioinformatics community development and capacity building. 2.B. Development of new tools and procedures.


Approach
The Genomics and Bioinformatics Research Unit’s (GBRU) primary function is conducting research in the areas of bioinformatics and genomics on a wide array of species and topics. Genomic technologies are powerful tools for germplasm improvement using marker assisted selection (MAS), biotechnology, or synthetic biology, and for analyzing associated biological processes (genetics, physiology, cell and molecular biology, biochemistry, and evolutionary biology). Thus, many ARS scientists, e.g., crop and animal breeders, have a direct need for genomic tools in their research. Others, e.g., soil scientists, can enhance their research dramatically using genomic tools to analyze the microbiome, if the technologies and appropriate expertise are available. However, not all ARS locations have sufficient resources to support core genomic technologies. Thus, the mission of the ARS Genomics and Bioinformatics Research Unit (GBRU), is to: (1) coordinate, facilitate, collaborate and conduct genomics and bioinformatics research emphasizing the Southeast region; (2) serve as a research and training resource for genomic technologies and bioinformatic analyses in support of ARS scientists and their collaborations; and (3) serve as a technical resource for ARS research programs that have not typically utilized these technologies, and aid in their development of genomic resources. Within the GBRU, this research project will conduct and collaborate on genome sequencing, sequence assembly and analysis, diversity analysis, marker development, haplotyping, physical and genetic map production, and transcription profiling research. Thus, essential product development includes new and improved reference genomes for plants, animals, insects, fish, and microbes that enable genomics-assisted breeding; new physical and genetic maps; improved cultivars, germplasm, or breeding lines; and new information on key agricultural problems such as disease resistance and drought tolerance.


Progress Report
In relation to genomes, the unit has contributed to several genomes including spinach, peanut, blueberry, and numerous insect pests. The unit has continued to lead multiple aspects of Ag100Pest project, and has become the lead on spin-off synergistic project, the Beenome. The team has continued to serve on aspects of training and advancing capacity and capabilities of SciNet including multiple Data Carpentry courses were taught and assisted by the unit, focusing on Unix, Git, R Software and Python. Breeding Insight OnRamp project has expanded this year to include support for four commodities: citrus, sugarcane, soybean and cotton. Significant portions of the citrus and sugarcane breeding programs have been transferred to the respective databases and are currently being utilized by the breeding programs. Support continues to expand to prepare for utilizing database applications for field analyses, archiving historical data, developing trait ontologies and initiating development of advanced genotyping capabilities. Machine Learning driven GeneSieve tool for gene discovery: Genomic regions associated with a trait can contain many genes, any one of which could be responsible for phenotypic differences between carriers. To help plant geneticists prioritize these genes for experimental confirmation, we have aggregated extensive biomics data from four keystone model species and created a query-able database that can be used for any crop. In collaboration with computer scientist at the University of Texas, Arlington, we are developing a front-end interface for the visualization of user results. We are also collaborating with that group to optimize the GeneSieve scoring algorithm using a range of machine learning techniques. Pan-genomic graph of agriculturally relevant peanut cultivars: In collaboration with Hudson-Alpha and University of Georgia, Athens, we are embarking on the first MAGIC (multi-parent advanced generation inter-cross) genetic experiment built from the ground-up with pangenomic techniques in mind. We have initiated the graph-based pipeline starting with 5 high-quality assemblies of founder lines. These will be merged with additional founder genomes and extensive genotypic and phenotypic data from the resultant experimental population. Beenome: Genomic resources for the U.S.’s most important pollinators: Both “cultivated” European honeybees and native bee species pollinate the majority of fruits and vegetables in the U.S. We are helping to improve gene discovery, population characterization, and bee breeding by developing a pangenomic resource for critical U.S. honeybee and native bee material, in collaboration with ARS lab in Baton Rouge, Louisiana. Five of the six target genomes for the honeybee component have been assembled by to chromosome scale. A collaboration, leveraging the scientific expertise across the unit along with ARS researchers in Charleston, South Carolina, has led to a new process for utilizing genomics data. Multiple genomes were used simultaneously for more accurate genetic analysis. The usefulness was exemplified by its ability to identify the causative genes for three different fungal resistance traits in melon within the same study. Something that would not have been possible using traditional approaches. A finalized method for determining the sex of chicken eggs based on their odor using machine learning has been developed. This technology could potentially solve a major issue for the egg-laying industry which currently has to cull day-old male chicks. The unit has discovered that dengue virus in Florida is passing directly from mosquitoes to their offspring, which can allow the spread of the virus without a host. This surprising finding has led mosquito control districts to start monitoring for Dengue directly before human cases are found, stopping outbreaks before they begin.


Accomplishments
1. Tool for applying CRISPR tecnology to agriculture crops. ARS researchers in Stoneville, Mississippi, developed software that makes it easy to design genome-wide screens of gene function in non-model organisms using new CRISPR technology. As the majority of USDA-ARS research systems are non-model, this software will better enable research in agricultural research systems. The software is available as a command-line software, a stand-alone web application, and a tool in the CyVerse Discovery Environment.

2. Sex determination in spinach. Multiple spinach genomes have been developed, which ultimately allowed for identification of a sex determination region, responsible for differentiating male from female spinach plants. A number of sex determination systems have evolved in different plant systems, in spinach the sex chromosomes have involved an insertion followed by an inversion and subsequent burst of repetitive elements. A male specific gene was identified within the insertion which is a strong candidate for the sex determination factor. Resequencing of a large number of lines across studies enables ARS researchers in Stoneville, Mississippi, to research leaf morphology and understanding variation among germplasm lines.


Review Publications
Aslam, M.Q., Naqvi, R.Z., Asif, M., Akhter, K.P., Scheffler, B.E., Scheffler, J.A., Liu, S., Amin, I., Mansoor, S. 2022. Analysis of a tetraploid cotton line Mac7 transcriptome reveals mechanisms underlying resistance against the whitefly Bemisia tabaci. Gene. 820:146200. https://doi.org/10.1016/j.gene.2022.146200.
 Coatsworth, H., Bozic, J., Carillo, J., Buckner, E., Rivers, A.R., Dinglasan, R., Mathias, D. 2022. Intrinsic variation in the vertically transmitted core virome of the mosquito Aedes aegypti. Molecular Ecology. 31(9):2545-2561. https://doi.org/10.1111/mec.16412.
 Foxx, A., Franco Melendez, K.P., Hariharan, J., Kozik, A., Wattenburger, C., Godoy-Vitorino, F., Rivers, A.R. 2021. Advancing equity and inclusion in microbiome research and training. mSystems. 6(5):e01151-21. https://doi.org/10.1128/mSystems.01151-21.
 Gao, M., Gold, S.E., Gu, X., Satterlee, T.R., Duke, M.V., Scheffler, B.E., Glenn, A.E. 2022. Transcriptomic Responses of Fusarium verticillioides to Lactam and Lactone Xenobiotics. Frontiers in Fungal Biology. https://doi.org/10.3389/ffunb.2022.923112.
 Restrepo-Montoya, D., Hulse-Kemp, A.M., Scheffler, J.A., Haigler, C., Hinze, L.L., Love, J., Percy, R.G., Jones, D.C., Frelichowski, J.E. 2022. Leveraging national germplasm collections to determine significantly associated categorical traits in crops: Upland and Pima Cotton as a case study. Frontiers in Plant Science. 13:837038. https://doi.org/10.3389/fpls.2022.837038.
 Redpath, L., Aryal, R., Lynch, N., Spencer, J.A., Hulse-Kemp, A.M., Ballington, J.R., Green, J., Bassil, N.V., Hummer, K.E., Ranney, T., Ashrafi, H. 2022. Nuclear DNA contents and ploidy levels of North American Vaccinium species and interspecific hybrids. Scientia Horticulturae. 297. Article 110955. https://doi.org/10.1016/j.scienta.2022.110955.
 Ma, X., Yu, L., Fatima, M., Wadlington, W.H., Hulse-Kemp, A.M., Zhang, X., Zhang, S., Xu, X., Van Deynze, A., Ming, R. 2022. Sex chromosome evolution, domestication and introgression history revealed by a YY genome in spinach. Genome Biology. https://doi.org/10.1186/s13059-022-02633-x.
 Edger, P.P., Iorizzo, M., Bassil, N.V., Benevenuto, J., Ferrao, L.F., Giongo, L., Hummer, K.E., Lawas, L.F., Leisner, C.P., Li, C., Munoz, P., Ashrafi, H., Atucha, A., Babiker, E.M., Canales, E., Chagne, D., DeVetter, L., Ehlenfeldt, M.K., Espley, R.V., Gallardo, K., Gunther, C.S., Hardigan, M.A., Hulse-Kemp, A.M., Jacobs, M.L., Lila, M., Luby, C.H., Main, D., Mengist, M.F., Owens, G.L., Perkins-Veazie, P., Polashock, J.J., Pottorff, M., Rowland, L.J., Sims, C.A., Song, G., Spencer, J., Vorsa, N., Yocca, A.E., Zalapa, J.E. 2022. There and back again; historical perspective and future directions for Vaccinium breeding and research studies. Horticulture Research. 9. Article uhac083. https://doi.org/10.1093/hr/uhac083.
 Guard, J.Y., Rivers, A.R., Vaughn, J.N., Rothrock Jr, M.J., Oladeinde, A.A., Shah, D. 2021. AT homopolymer strings in salmonella enterica subspecies I contribute to speciation and serovar diversity. Microorganisms. 9(10):2075. https://doi.org/10.3390/microorganisms9102075.
 Poudel, R., Trujillo-Rodriguez, L., Reisch, C., Rivers, A.R. 2022. GuideMaker: software to design CRISPR-Cas guide RNA pools in non-model genomes. Gigascience. 11. Article giac007. https://doi.org/10.1093/gigascience/giac007.