Detecting Cotton Leaf Curl Virus Resistance Quantitative Trait Loci in <i>Gossypium hirsutum</i> and iCottonQTL a New R/Shiny App to Streamline Genetic Mapping
Ashley N. Schoonmaker,
Amanda M. Hulse-Kemp,
Ramey C. Youngblood,
Zainab Rahmat,
Muhammad Atif Iqbal,
Mehboob-ur Rahman,
Kelli J. Kochan,
Brian E. Scheffler,
Jodi A. Scheffler
Affiliations
Ashley N. Schoonmaker
Bioinformatics Graduate Program, North Carolina State University, Raleigh, NC 27695, USA
Amanda M. Hulse-Kemp
Bioinformatics Graduate Program, North Carolina State University, Raleigh, NC 27695, USA
Ramey C. Youngblood
Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Starkville, MS 39762, USA
Zainab Rahmat
Plant Genomics and Molecular Breeding Laboratory, National Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences, (NIBGE-C, PIEAS), Faisalabad 38000, Punjab, Pakistan
Muhammad Atif Iqbal
School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Mehboob-ur Rahman
School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
Kelli J. Kochan
Institute for Genome Sciences and Society, Texas A&M University, College Station, TX 77843, USA
Brian E. Scheffler
USDA Agricultural Research Service, Genomics and Bioinformatics Research Unit, Stoneville, MS 38776, USA
Jodi A. Scheffler
USDA Agricultural Research Service, Crop Genetics Research Unit, Stoneville, MS 38776, USA
Cotton leaf curl virus (CLCuV) causes devastating losses to fiber production in Central Asia. Viral spread across Asia in the last decade is causing concern that the virus will spread further before resistant varieties can be bred. Current development depends on screening each generation under disease pressure in a country where the disease is endemic. We utilized quantitative trait loci (QTL) mapping in four crosses with different sources of resistance to identify single nucleotide polymorphism (SNP) markers associated with the resistance trait to allow development of varieties without the need for field screening every generation. To assist in the analysis of multiple populations, a new publicly available R/Shiny App was developed to streamline genetic mapping using SNP arrays and to also provide an easy method to convert and deposit genetic data into the CottonGen database. Results identified several QTL from each cross, indicating possible multiple modes of resistance. Multiple sources of resistance would provide several genetic routes to combat the virus as it evolves over time. Kompetitive allele specific PCR (KASP) markers were developed and validated for a subset of QTL, which can be used in further development of CLCuV-resistant cotton lines.
