Location: National Germplasm Resources LaboratoryTitle: High throughput sequencing, a routine tool for sugarcane virus detection
|MALAPI-WIGHT, MARTHA - Animal And Plant Health Inspection Service (APHIS)|
Submitted to: American Society of Sugar Cane Technologists
Publication Type: Abstract Only
Publication Acceptance Date: 4/21/2020
Publication Date: 6/1/2020
Citation: Mollov, D.S., Grinstead, S.C., Fuentes-Bueno, I., Malapi-Wight, M. 2020. High throughput sequencing, a routine tool for sugarcane virus detection. American Society of Sugar Cane Technologists. Vol 83:1, page 20.
Technical Abstract: Sugarcane viruses at the USDA-APHIS Plant Germplasm Quarantine Program (PGQP) are currently detected with validated standard molecular techniques and high throughput sequencing (HTS). The complete quarantine process for imported sugarcane clones is approximately two years. One goal of PGQP is to validate the use of HTS as a routine diagnostic tool for the detection of pathogens in each imported sugarcane accession. Before adopting HTS, efficient pipelines must be developed using bioinformatic and statistical approaches. In this study, six infected sugarcane accessions used as positive controls for testing at the USDA-APHIS PGQP were transferred to the USDA-ARS National Germplasm Resources Laboratory in early summer of 2019 to perform the HTS validation experiments. These plants are infected with sugarcane streak mosaic virus, sugarcane yellow leaf virus, sugarcane white streak virus, sugarcane striate mosaic associated virus, and sugarcane bacilliform virus. PGQP sugarcane samples are normally tested for viruses in the fall to spring period. In September and December 2019 leaves, stems, and roots were collected from each of the six sugarcane clones and total RNA from each sample was isolated. A total of 18 RNA samples were subjected to cDNA library preparation and HTS analysis. A minimum of 15 million reads were obtained from each sample and the data from the first two collections was analyzed. A third collection occurred in April 2020 and samples are being processed. Optimization and normalization across each data set will be determined for each virus to provide consistently reliable detection. Factors such as the total number of reads, reads mapped, target sequence coverage depth, number of contigs, contig length, read length, virus taxa, and host will be evaluated in the development process. The minimum number of reads, contig length, and virus genome coverage depth will be determined for when a sample can be considered positive. The outcome of this research will be used to develop more efficient quarantine testing, which ultimately will benefit the U.S. sugarcane industry.