BLAST Sequences queried against the nr or grass databases. GO ANALYSIS

1. Next Generation Sequencing On Species Important to the Turfgrass Industry Keenan Amundsen1,2, Geunhwa Jung3, Dilip Lakshman2, Scott Warnke2 1George Mason University, 2United States Department of Agriculture, 3University of Massachusetts SAMPLE PREPARATION Preparation of samples for sequencing (approximately 3 days). EXPRESSION ANALYSIS Relative expression of 232 conserved S.homoeocarpa ESTs expressed as number of 36-mer reads/kb. S. homoeocarpa 1 S. homoeocarpa 2 Each vertical line represents one conserved EST. Sequences expressed equally in each library should have equal length ( ) and ( ) bars. ABSTRACT The bentgrasses (Agrostis spp.) are important species to the turfgrass industry because of their unique growth and aesthetic characteristics that make them ideally suited for use on golf course tees, fairways, and putting greens.  Molecular marker development is difficult in Agrostis due to the limited amount of available DNA sequence data.  For example there are 16,992 Agrostis EST sequences (as of April 23, 2009) published in the National Center for Biotechnology Information databases, dwarfed by the millions of EST sequences available for cereal grasses.  Illumina sequencing technology is among the most popular of the next generation sequencing technologies and provides an affordable way of producing large amounts of sequence data.  The objective of this study was to evaluate the Illumina Genome Analyzer for the generation of EST sequence data from one velvet bentgrass (A. canina L.), three creeping bentgrasses (A. stolonifera L.), two dollar spot causing fungal isolates (Sclerotinia homeocarpa FT Bennett), and one brown patch causing fungal isolate (Rhizoctonia solani Kühn).   In addition, the feasibility of assembling the short Illumina sequencing reads into usable data was tested.  A total of 1,026,283 (Agrostis), 1,834,661 (Sclerotinia), and 326,174 (Rhizoctonia) 36-mer sequences were generated.  The software programs Edena and Velvet were used to assemble the sequences into contigs.  A total of 387 contigs were assembled for the turfgrass libraries, 2,947 for the Sclerotinia libraries, and 258 for the Rhizoctonia library.  While this sequencing run generated approximately 10 percent of the expected amount of data, more than 3,000 EST sequences were recovered.  This preliminary experiment demonstrates the utility of high throughput sequencing on species important to the turfgrass industry and the need for additional sequencing. Total RNA Isolate mRNA cDNA Synthesis LigateAdaptoers Cluster Station DNA Sequencing Illumina sequencing run and data analysis (approximately 5 days). Illumina GAII Normalize Intensities DNA Basecalls SNP Design Identified single nucleotide polymorphisms to be used as genetic markers. Identified 56 SNPs by comparing the A. canina 36-mer sequence data to published A. capillaris and A. stolonifera EST sequences. Used the published full length Agrostis EST sequences to design molecular beacons for SNP detection. SEQUENCE ASSEMBLY 36-mer sequences were assembled into contigs using the software programs Edena and Velvet. • PROBLEM • There is limited publicly available DNA sequence data for several species important to the turfgrass industry. • What is the practicality of implementing next generation sequencing technologies to expand the collection ofsequence data for these species? • Can we use next generation sequencing for sequence assembly and comparative genomics without a reference sequence? • Can we develop novel genetic markers based on next generation sequence data? • Can we use next generation sequencing for expression profiling? A.canina CGCCGCCATGCCTTACACGGGGATTACATGAGAAGA A.stolonifera CGCCGCCATGCCTTACACGGGGATTACATGAGAAGA A.capillaris CGCCGCCATGCCTTACACGGGGATTACATGGGAAGA ****************************** ***** A.capillaris ATCGCCGCCATGCCTTACACGGGGATTACATGGGAAGACTTAGAGCGAGAGGCCGCCGGACTCCTCGTCCTCG ||||||||||||||||||||||||||||||||.|||||||||||||||||||||||||||||||||||||||| A.stolonifera ATCGCCGCCATGCCTTACACGGGGATTACATGAGAAGACTTAGAGCGAGAGGCCGCCGGACTCCTCGTCCTCG • FUTURE DIRECTION • Expand DNA sequence knowledgebase of important turf and fungal species. • Profile differentially expressed genes in response to disease and abiotic stress. • Develop genetic markers for marker assisted selection and linkage map development. • Monitor expression of siRNAs and their influence on gene network regulation. • Explore species relationships through comparative genomics and phylogenetic studies. • Address concerns for data management. GENOTYPES Total RNA was extracted from 4 Agrostis, 2 Sclerotinia, and 1 Rhizoctonia samples. 3 Agrostis stolonifera 2 Sclerotinia homoeocarpa 1 Rhizoctonia solani 1 Agrostis canina Causes Dollar Spot Causes Brown Patch INSTRUMENTATION Sequencing reactions were performed on the Illumina platform. Cluster station Illumina GAII BLAST Sequences queried against the nr or grass databases. GO ANALYSIS Contigs classified based on homology to known plant or fungal genes. CONCLUSIONS Next generation sequencing is a viable sequencing technology for studying species important to the turfgrass industry. In this study, we were able to assemble 36-mers into contigs without a reference sequence, characterize the sequences, develop SNP markers in Agrostis, and compare the relative expression of conserved ESTs between two S. homoeocarpa isolates. It is estimated that a successful sequencing run would provide 10-fold more 36-mers and yield significantly more assembled contigs. ACKNOWLEDGEMENTS Thanks are given to the United States Golf Association and to the United States Department of Agriculture for supporting this research. 1 2 3 4 5