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Advanced Genetic Technologies, KY
Department of Plant Pathology
DNA sequencing technologies and associated methods for analyzing DNA sequences have become so advanced and affordable that rapid sequencing of the entire genetic constitution (whole genome sequencing) of microbial species is now routine. Application of whole genome sequencing to parasites and symbionts of plants and animals allows deep insight into their interactions with hosts, and can be used to address productivity and diseases of crops and livestock. Such insights require facile analysis of the very large datasets generated by whole genome sequencing.
This project will use, as a test case, a group of fungi that range from parasitic to beneficial in their interactions with common forage grasses and wild grass relatives. Whole genomes will be sequenced from 14 of these fungi, sets of closely homologous genes will be identified and their sequences will be compared in order to discern the evolutionary relationships of those genes. The results will provide insight into the underlying genetics of plant pathogenesis as well as beneficial symbiosis.
These studies will require streamlining and standardizing computer analysis of the large volume of data obtained by whole genome sequencing. Therefore, a central activity will be to refine computer methods and algorithms for acquisition, collation, management and analysis of these data, thereby greatly enhancing the bioinformatic capabilities at the University of Kentucky.
2011 Project Description
Genome sequences were determined for twelve genomes from fungi in genera Aciculosporium, Claviceps, Colletotrichum (i.e., Glomerella), Epichloe, Neotyphodium and Periglandula. These fungi were chosen for the potential to relate their gene contents to their diverse interactions with grass species, ranging from biotrophic (colonizing only living plant tissue) to hemibiotrophic (colonizing living tissue, then killing and further colonizing host cells), and from mutualistic symbionts to pathogens.
Considerable progress was made in establishing computational pipelines for gene annotation, comparative genomics and phylogenetics. Gene models were constructed based on combinations of ab initio gene predictions and biological data in the form of messenger RNA (mRNA) sequences. Gene functions are assigned based on results of homology searches with Blast2GO, and hidden markov model (HMM) searches of the sequences for signatures that identify protein and enzyme families.
The comparative genomics pipeline employed two computer algorithms run in series to identify sets of orthologous genes between genomes, and to align the sequences of orthologs to facilitate phylogenetic analysis on a genome-wide scale.
This project served as a key training ground for staff and students in high-throughput genome (DNA) and transcriptome (RNA) sequencing and annotation. A bioinformatician attended the blast2GO workshop and undertook bioinformatic analysis of data generated in the DNA sequencing core facility.
Genome sequences, together with ortholog groups and alignments of protein sequences inferred from the annotated genomes, have been published to a web site, www.endophyte.uky.edu, and also have been uploaded to the Genbank database at the National Center for Biotechnology Information (NCBI).
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