Location: Genomics and Bioinformatics ResearchTitle: Detecting cotton leaf curl virus resistance quantitative trait Loci in Gossypium hirsutum and iCottonQTL a new R/Shiny app to streamline genetic mapping in cotton
|SCHOONMAKER, ASHLEY - North Carolina State University|
|YOUNGBLOOD, RAMEY - Mississippi State University|
|RAHMAT, MS ZAINAB - National Institute Of Biotechnology And Genetic Engineering (NIBGE)|
|IQBAL, MUHAMMAD ATIF - University Of Sydney|
|MEHBOOB-UR-, RAHMAN - National Institute Of Biotechnology And Genetic Engineering (NIBGE)|
|KOCHAN, KELLI - Texas A&M University|
Submitted to: Plants
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/21/2023
Publication Date: 3/3/2023
Citation: Schoonmaker, A., Hulse-Kemp, A.M., Youngblood, R.C., Rahmat, M., Iqbal, M., Mehboob-Ur-, R., Kochan, K.J., Scheffler, B.E., Scheffler, J.A. 2023. Detecting cotton leaf curl virus resistance quantitative trait Loci in Gossypium hirsutum and iCottonQTL a new R/Shiny app to streamline genetic mapping in cotton. Plants. https://doi.org/10.3390/plants12051153.
Interpretive Summary: In the past two decades, the Middle East and parts of Asia have been affected by the devastation of the Cotton Leaf Curl Virus on cotton fields. If they survive, infected plants are severely stunted, never maturing enough to produce cotton fibers for harvest. The virus spreads from plant to plant through the saliva of a common pest, a whitefly. Given the whitefly is parasitic on plants other than cotton and the virus has already spread from its initial emergence into India and parts of eastern Asia, there is concern the disease will spread beyond the current affected regions. Currently, developing cotton plants inherently resistant to the disease involves sending each generation of seed to be grown in regions affected by the virus with limited ability to get seeds returned from those areas. In this project, we created populations from four crosses between resistant and susceptible plants. Assessing the genetic differences in a population of cotton plants that were derived from two parents that respond differently to the virus, one susceptible and one resistant, we used statistics and identified multiple regions of the genome associated with resistance to the virus. We developed a web application to streamline the analysis process and automatically generate specific software program input files for projects that will do similar genetic analyses in the future. Results showed there are different sources of resistance from each of the populations tested, meaning we may have multiple ways to provide resistance to new cotton plants. Overall this study provides many valuable details that will allow for more streamlined breeding of resistance into cotton in the future.
Technical Abstract: Cotton Leaf Curl Virus (CLCuV), the causative agent for the Cotton Leaf Curl Disease (CLCuD), causes devastating losses to fiber production beginning in Multan, Pakistan in the 1980s. Then spread into neighboring countries, i.e. India and China. There is concern the virus will move into unaffected countries before resistant varieties can be bred. Current development of resistant lines depends on screening each generation against disease pressure in a region where the disease is endemic with limited ability to return materials. Identification of markers associated with resistance would allow for development of varieties without field screening every generation. In this project, we utilized quantitative trait loci (QTL) mapping in six populations to identify single nucleotide polymorphism (SNP) markers associated with the CLCuD resistance trait. A new R/Shiny App was developed to streamline genetic mapping using SNP arrays and to deposit genetic data into the CottonGen database. Results from the QTL mapping identified several different QTL for each cross, indicating possible multiple modes of resistance in the different resistant lines. KASP markers were developed and validated for a subset of QTL which can later be used in further development of lines.