Identification of Virus Genome sequences from RNA-seq data of a field-grown tomato plant

Viral diseases in crops have a detrimental agricultural and economical impact globally, especially in developing countries. However, efforts to mitigate the impact of crop viruses are hampered by the lack of low-cost and efficient tools that can geographically detect and characterize crop viruses. With the recent advent of next generation sequencing technologies, novel methods could be developed to efficiently identify plant virus genomes by employing these technologies. In this project, we propose a novel method of deep sequencing plant transcriptomes (RNA-seq) to detect virus genomes. By de novo assembly of an RNA-seq dataset generated from fruits of an Ithaca field-grown tomato plant (cultivar M82), we were able to identify three virus genomes, although the plant did not show any visible disease symptoms: potato virus Y, southern tomato virus and tomato mosaic virus. The identified potato virus Y and southern tomato virus are same as previous reported genomes (GenBank Acc#: X12456 and EF442780, respectively), while the tomato mosaic virus is a new isolate, which shares 86% nucleotide sequence identity to the previous reported genome (GenBank Acc#: AF332868). With this approach, it will be highly efficient to geographically identify and characterize virus genome for major food crops; a key step towards the overall goal of reducing crop loss due to viral diseases.

My Experience

The opportunity to work as a bioinformatics intern in the Fei lab at the Boyce Thompson Institute gave me the opportunity to finally combine my knowledge from biology and computer science in real world research, an opportunity not available at my liberal arts college. I enriched my skills in programming while learning new biological concepts and solidifying old ones through work with next generation sequencing tools. The most exciting part of this summer experience, was the chance to work on the tomato virus genome project, a precursor to a bigger project towards identification of virus genome in Pan-African sweet potato that the Fei lab will be working on. This opportunity did not only strengthened my desire to study bioinformatics or computational biology at the graduate level but as a student from Ghana, also the possibility to focus on plant and agricultural research in developing regions such as sub-Saharan Africa.