During this residential training, you will acquire skills in high throughput sequence analysis, the use of reproducible genomic workflows and download data using APIs. Through this mini-project, you will get to solidify and consolidate the skills you will have acquired.
Background
Maize lethal necrosis is caused by a synergistic co-infection of Maize chlorotic mottle virus (MCMV) and a specific member of the Potyviridae, such as Sugarcane mosaic virus (SCMV), Wheat streak mosaic virus (WSMV) or Johnson grass mosaic virus (JGMV). Typical maize lethal necrosis symptoms include severe yellowing and leaf drying from the edges. In Kenya, we detected plants showing typical and atypical symptoms. Both groups of plants often tested negative for SCMV by ELISA.
Methods
We used next-generation sequencing to identify viruses associated with maize lethal necrosis in Kenya through a metagenomics analysis. Symptomatic and asymptomatic leaf samples were collected from maize and sorghum representing sixteen counties.
Results
Complete and partial genomes were assembled for MCMV, SCMV, Maize streak virus (MSV) and Maize yellow dwarf virus-RMV (MYDV-RMV). These four viruses (MCMV, SCMV, MSV and MYDV-RMV) were found together in 30 of 68 samples. A geographic analysis showed that these viruses are widely distributed in Kenya. Phylogenetic analyses of nucleotide sequences showed that MCMV, MYDV-RMV and MSV are similar to isolates from East Africa and other parts of the world. Single nucleotide polymorphism, nucleotide and polyprotein sequence alignments identified three genetically distinct groups of SCMV in Kenya. Variation mapped to sequences at the border of NIb and the coat protein. Partial genome sequences were obtained for the other four potyviruses and one polerovirus.
Conclusion
Our results uncover the complexity of the maize lethal necrosis epidemic in Kenya. MCMV, SCMV, MSV and MYDV-RMV are widely distributed and infect both maize and sorghum. SCMV population in Kenya is diverse and consists of numerous strains that are genetically different from isolates from other parts of the world. Several potyviruses, and possibly poleroviruses, are also involved.
The study uses several genomic and Bioinformatics approaches. In this project, you are required to reproduce the genomic analysis carried out in the study. The data is available from NCBI. You are expected to:
- Download the sequence data programmatically using an API
- Carry out RNA sequence processing and de novo assembly
- Perform single nucleotide polymorphism (SNP) analysis
In your report, you should address the following question:
- Are you able to arrive at similar conclusions as those in the paper? Why or why not?
- What else can you glean from your re-analysis?
- Are the descriptions in the methodology section detailed for reproducibility? If not, what could you have done to improve reproducibility?