Author
GAUTAM, DILIP - Mississippi State University | |
JOHNSTON, IAN - Mississippi State University | |
BHOWMIK, TANMAY - Mississippi State University | |
ANKALA, ARNKANTH - Mississippi State University | |
Sonstegard, Tad | |
Schroeder, Steven - Steve | |
WILKINSON, JEFF - Mississippi State University | |
PERKINS, ANDY - Mississippi State University |
Submitted to: International Conference on Bioinformatics and Computational Biology
Publication Type: Abstract Only Publication Acceptance Date: 2/4/2010 Publication Date: 2/19/2010 Citation: Gautam, D., Johnston, I., Bhowmik, T., Ankala, A., Sonstegard, T.S., Schroeder, S.G., Wilkinson, J., Perkins, A.D. 2010. High Throughput Sequence Analysis for Disease Resistance in Maize. International Conference on Bioinformatics and Computational Biology. Interpretive Summary: Preliminary results of a computational analysis of high throughput sequencing data from Zea mays and the fungus Aspergillus are reported. The Illumina Genome Analyzer was used to sequence RNA samples from two strains of Z. mays (Va35 and Mp313) collected over a time course as well as several species and strains of Aspergillus, with the ultimate goal of identifying genes possibly involved in resistance of maize to Aspergillus infection. Raw sequence reads were 26bp and 36bp for maize and Aspergillus, respectively. Most reads contained portions of the Solexa gene expression adapter sequences, which were removed before performing alignment, resulting in an average read length of about 18bp for both maize and Aspergillus data. After filtering, Phred quality was analyzed and determined to be on average 31 for maize and 28 for Aspergillus sequences. The alignment tool Bowtie was used to perform an initial alignment to the B73 4a.53 draft of the maize genome and the A. flavus NRRL3357 genome, respectively. Initial mappings on maize produced an average of 98% of sequences mapping to a genomic location with up to two mismatches allowed, with about 57% mapping uniquely within the best stratum. Aspergillus sequences fared better with 91% of sequences mapping and almost 73% mapping to a unique genomic location. The remaining unmapped sequences were analyzed for potential matches to exon junctions and intronic regions. An overview of possible further computational approaches to handling these situations, as well as the remaining ambiguous mappings, is presented. Technical Abstract: Preliminary results of a computational analysis of high throughput sequencing data from Zea mays and the fungus Aspergillus are reported. The Illumina Genome Analyzer was used to sequence RNA samples from two strains of Z. mays (Va35 and Mp313) collected over a time course as well as several species and strains of Aspergillus, with the ultimate goal of identifying genes possibly involved in resistance of maize to Aspergillus infection. Raw sequence reads were 26bp and 36bp for maize and Aspergillus, respectively. Most reads contained portions of the Solexa gene expression adapter sequences, which were removed before performing alignment, resulting in an average read length of about 18bp for both maize and Aspergillus data. After filtering, Phred quality was analyzed and determined to be on average 31 for maize and 28 for Aspergillus sequences. The alignment tool Bowtie was used to perform an initial alignment to the B73 4a.53 draft of the maize genome and the A. flavus NRRL3357 genome, respectively. Initial mappings on maize produced an average of 98% of sequences mapping to a genomic location with up to two mismatches allowed, with about 57% mapping uniquely within the best stratum. Aspergillus sequences fared better with 91% of sequences mapping and almost 73% mapping to a unique genomic location. The remaining unmapped sequences were analyzed for potential matches to exon junctions and intronic regions. An overview of possible further computational approaches to handling these situations, as well as the remaining ambiguous mappings, is presented. |