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29 Background: Hematological malignancies are forms of cancer that originates in blood-forming tissue, such as bone marrow, or in the cells of the immune system. Detection of genetic alteration in hematological malignancies are increasingly important because of diverse variants associated with classification and diagnosis of subtypes, and prognostic and therapeutic-response prediction. Next-generation sequencing (NGS) is a powerful technology to simultaneously analyze multiple genes to identify clinically well-described variants, as well as rare variants related to hematological malignancies for clinical diagnostics. Methods: We developed the targeted NGS panel (HEMEaccuTest) and automatic analysis software (NGeneAnalySys) for estimating pathogenicity of genetic variants related to hematological malignancies. HEMEaccuTest covers entire coding region of 108 genes that have putatively known for associations with the diseases according to the WHO, NCCN and ELN guidelines. The diagnostic utility of HEMEaccuTest and NGeneAnalySys were validated using reference materials and clinical specimens. Results: The results showed that pathogenic variants were effectively detected with an average coverage depth of 600X and a minimum coverage depth of 100X. It demonstrated an excellent limit of detection, with 100% sensitivity for SNVs at 2% VAF and for indel at 4% VAF. In addition, the analytical sensitivity, specificity and precision of the panel were higher compared to conventional methods such as Sanger sequencing, FISH, and real-time PCR. Noticeably, the approximately 300-bp-size insertions of FLT3-ITD was efficiently detected by a simulating algorithm. Conclusions: This analytical validation study demonstrated that HEMEaccuTest and NGeneAnalySys can be an excellent and useful tool for disease definition and therapeutic strategy in hematological malignancies. NGeneAnalySys provides the evidence-based categorization and clinical interpretation supported by Tier classification (Therapeutic, Prognostic, Diagnostic) of professional guidelines (ACMG/AMP, AMP/ASCO/CAP. etc).

e14606 Background: Hematological malignancies are forms of cancer that originate in blood-forming tissue, such as bone marrow, or in the cells of the immune system. Hematological malignancies can be classified as leukemias, lymphomas, multiple myeloma (MM), myelodysplastic syndromes (MDS) and myeloproliferative neoplasms (MPN) based on the cell type where they originate. Detection of genetic alteration in hematological malignancies is increasingly important because of diverse variants associated with classification and diagnosis of subtypes, and prognostic and therapeutic-response prediction. Next-generation sequencing (NGS) is an advanced technology to simultaneously analyze multiple genes to identify clinically well-described variants, as well as rare variants related for clinical diagnostics. Methods: We developed the targeted NGS panel, HEMEaccuTest and automatic analysis software, NGeneAnalySys for estimating the relative pathogenicity of hematological malignancies. HEMEaccuTest covers about the 310 kilobases with exon regions of 108 genes that have putatively known for associations with the diseases according to the WHO, NCCN and ELN guidelines. the diagnostic utility of the panel and software were validated using genotype-known reference materials and clinical specimens. Results: The results showed that pathogenic variants were effectively detected with an average coverage depth of 600x and a minimum coverage depth of 100x. It demonstrated an excellent limit of detection, with 100% sensitivity for SNVs at 2% VAF and for indel at 4% VAF. In addition, the analytical sensitivity and specificity of the panel were high in a comparison to conventional methods such as Sanger sequencing, FISH, and real-time PCR. Noticeably, the approximately 300-bp-size insertions of FLT3-ITD was efficiently detected by an excellent simulating algorithm of NGeneAnalySys. Conclusions: This analytical validation demonstrated that HEMEaccuTest and NGeneAnalySys can be an excellent tool for disease definition and therapeutic strategy in hematological malignancies.

Since the completion of the Saccharomyces cerevisiae genome sequencing project in 1996, the genomes of over 80 fungal species have been sequenced or are currently being sequenced. Resulting data provide opportunities for studying and comparing fungal biology and evolution at the genome level. To support such studies, the Comparative Fungal Genomics Platform (CFGP; http://cfgp.snu.ac.kr), a web-based multifunctional informatics workbench, was developed. The CFGP comprises three layers, including the basal layer, middleware and the user interface. The data warehouse in the basal layer contains standardized genome sequences of 65 fungal species. The middleware processes queries via six analysis tools, including BLAST, ClustalW, InterProScan, SignalP 3.0, PSORT II and a newly developed tool named BLASTMatrix. The BLASTMatrix permits the identification and visualization of genes homologous to a query across multiple species. The Data-driven User Interface (DUI) of the CFGP was built on a new concept of pre-collecting data and post-executing analysis instead of the ‘fill-in-the-form-and-press-SUBMIT’ user interfaces utilized by most bioinformatics sites. A tool termed Favorite, which supports the management of encapsulated sequence data and provides a personalized data repository to users, is another novel feature in the DUI.

Agrobacterium tumefaciens-mediated transformation (ATMT) has become a prevalent tool for functional genomics of fungi, but our understanding of T-DNA integration into the fungal genome remains limited relative to that in plants. Using a model plant-pathogenic fungus, Magnaporthe oryzae, here we report the most comprehensive analysis of T-DNA integration events in fungi and the development of an informatics infrastructure, termed a T-DNA analysis platform (TAP). We identified a total of 1110 T-DNA-tagged locations (TTLs) and processed the resulting data via TAP. Analysis of the TTLs showed that T-DNA integration was biased among chromosomes and preferred the promoter region of genes. In addition, irregular patterns of T-DNA integration, such as chromosomal rearrangement and readthrough of plasmid vectors, were also observed, showing that T-DNA integration patterns into the fungal genome are as diverse as those of their plant counterparts. However, overall the observed junction structures between T-DNA borders and flanking genomic DNA sequences revealed that T-DNA integration into the fungal genome was more canonical than those observed in plants. Our results support the potential of ATMT as a tool for functional genomics of fungi and show that the TAP is an effective informatics platform for handling data from large-scale insertional mutagenesis.

Rapid translation of genome sequences into meaningful biological information hinges on the integration of multiple experimental and informatics methods into a cohesive platform. Despite the explosion in the number of genome sequences available, such a platform does not exist for filamentous fungi. Here we present the development and application of a functional genomics and informatics platform for a model plant pathogenic fungus, Magnaporthe oryzae. In total, we produced 21,070 mutants through large-scale insertional mutagenesis using Agrobacterium tumefaciens-mediated transformation. We used a high-throughput phenotype screening pipeline to detect disruption of seven phenotypes encompassing the fungal life cycle and identified the mutated gene and the nature of mutation for each mutant. Comparative analysis of phenotypes and genotypes of the mutants uncovered 202 new pathogenicity loci. Our findings demonstrate the effectiveness of our platform and provide new insights on the molecular basis of fungal pathogenesis. Our approach promises comprehensive functional genomics in filamentous fungi and beyond.

Hot pepper (Capsicum annuum), one of the oldest domesticated crops in the Americas, is the most widely grown spice crop in the world. We report whole-genome sequencing and assembly of the hot pepper (Mexican landrace of Capsicum annuum cv. CM334) at 186.6× coverage. We also report resequencing of two cultivated peppers and de novo sequencing of the wild species Capsicum chinense. The genome size of the hot pepper was approximately fourfold larger than that of its close relative tomato, and the genome showed an accumulation of Gypsy and Caulimoviridae family elements. Integrative genomic and transcriptomic analyses suggested that change in gene expression and neofunctionalization of capsaicin synthase have shaped capsaicinoid biosynthesis. We found differential molecular patterns of ripening regulators and ethylene synthesis in hot pepper and tomato. The reference genome will serve as a platform for improving the nutritional and medicinal values of Capsicum species.

The fungal genus Fusarium includes many plant and/or animal pathogenic species and produces diverse toxins. Although accurate species identification is critical for managing such threats, it is difficult to identify Fusarium morphologically. Fortunately, extensive molecular phylogenetic studies, founded on well-preserved culture collections, have established a robust foundation for Fusarium classification. Genomes of four Fusarium species have been published with more being currently sequenced. The Cyber infrastructure for Fusarium (CiF; http://www.fusariumdb.org/) was built to support archiving and utilization of rapidly increasing data and knowledge and consists of Fusarium-ID, Fusarium Comparative Genomics Platform (FCGP) and Fusarium Community Platform (FCP). The Fusarium-ID archives phylogenetic marker sequences from most known species along with information associated with characterized isolates and supports strain identification and phylogenetic analyses. The FCGP currently archives five genomes from four species. Besides supporting genome browsing and analysis, the FCGP presents computed characteristics of multiple gene families and functional groups. The Cart/Favorite function allows users to collect sequences from Fusarium-ID and the FCGP and analyze them later using multiple tools without requiring repeated copying-and-pasting of sequences. The FCP is designed to serve as an online community forum for sharing and preserving accumulated experience and knowledge to support future research and education.

Because less than one-third of clinically relevant fusaria can be accurately identified to species level using phenotypic data (i.e., morphological species recognition), we constructed a three-locus DNA sequence database to facilitate molecular identification of the 69 Fusarium species associated with human or animal mycoses encountered in clinical microbiology laboratories. The database comprises partial sequences from three nuclear genes: translation elongation factor 1α ( EF-1α ), the largest subunit of RNA polymerase ( RPB1 ), and the second largest subunit of RNA polymerase ( RPB2 ). These three gene fragments can be amplified by PCR and sequenced using primers that are conserved across the phylogenetic breadth of Fusarium . Phylogenetic analyses of the combined data set reveal that, with the exception of two monotypic lineages, all clinically relevant fusaria are nested in one of eight variously sized and strongly supported species complexes. The monophyletic lineages have been named informally to facilitate communication of an isolate's clade membership and genetic diversity. To identify isolates to the species included within the database, partial DNA sequence data from one or more of the three genes can be used as a BLAST query against the database which is Web accessible at FUSARIUM-ID ( http://isolate.fusariumdb.org ) and the Centraalbureau voor Schimmelcultures (CBS-KNAW) Fungal Biodiversity Center ( http://www.cbs.knaw.nl/fusarium ). Alternatively, isolates can be identified via phylogenetic analysis by adding sequences of unknowns to the DNA sequence alignment, which can be downloaded from the two aforementioned websites. The utility of this database should increase significantly as members of the clinical microbiology community deposit in internationally accessible culture collections (e.g., CBS-KNAW or the Fusarium Research Center) cultures of novel mycosis-associated fusaria, along with associated, corrected sequence chromatograms and data, so that the sequence results can be verified and isolates are made available for future study.

Background Since the full genome sequences of Saccharomyces cerevisiae were released in 1996, genome sequences of over 90 fungal species have become publicly available. The heterogeneous formats of genome sequences archived in different sequencing centers hampered the integration of the data for efficient and comprehensive comparative analyses. The Comparative Fungal Genomics Platform (CFGP) was developed to archive these data via a single standardized format that can support multifaceted and integrated analyses of the data. To facilitate efficient data visualization and utilization within and across species based on the architecture of CFGP and associated databases, a new genome browser was needed. Results The Seoul National University Genome Browser (SNUGB) integrates various types of genomic information derived from 98 fungal/oomycete (137 datasets) and 34 plant and animal (38 datasets) species, graphically presents germane features and properties of each genome, and supports comparison between genomes. The SNUGB provides three different forms of the data presentation interface, including diagram, table, and text, and six different display options to support visualization and utilization of the stored information. Information for individual species can be quickly accessed via a new tool named the taxonomy browser. In addition, SNUGB offers four useful data annotation/analysis functions, including 'BLAST annotation.' The modular design of SNUGB makes its adoption to support other comparative genomic platforms easy and facilitates continuous expansion. Conclusion The SNUGB serves as a powerful platform supporting comparative and functional genomics within the fungal kingdom and also across other kingdoms. All data and functions are available at the web site http://genomebrowser.snu.ac.kr/.

Summary: Genomes of more than 60 fungal species have been sequenced to date, yet there has been no systematic approach to analyze fungal transcription factors (TFs) kingdom widely. We developed a standardized pipeline for annotating TFs in fungal genomes. Resulting data have been archived in a new database termed the Fungal Transcription Factor Database (FTFD). In FTFD, 31 832 putative fungal TFs, identified from 62 fungal and 3 Oomycete species, were classified into 61 families and phylogenetically analyzed. The FTFD will serve as a community resource supporting comparative analyses of the distribution and domain structure of TFs within and across species. Availability: All data described in this study can be browsed through the FTFD web site at http://ftfd.snu.ac.kr/. Contact: yonglee@snu.ac.kr

Background Sequences and organization of the mitochondrial genome have been used as markers to investigate evolutionary history and relationships in many taxonomic groups. The rapidly increasing mitochondrial genome sequences from diverse insects provide ample opportunities to explore various global evolutionary questions in the superclass Hexapoda. To adequately support such questions, it is imperative to establish an informatics platform that facilitates the retrieval and utilization of available mitochondrial genome sequence data. Results The Insect Mitochondrial Genome Database (IMGD) is a new integrated platform that archives the mitochondrial genome sequences from 25,747 hexapod species, including 112 completely sequenced and 20 nearly completed genomes and 113,985 partially sequenced mitochondrial genomes. The Species-driven User Interface (SUI) of IMGD supports data retrieval and diverse analyses at multi-taxon levels. The Phyloviewer implemented in IMGD provides three methods for drawing phylogenetic trees and displays the resulting trees on the web. The SNP database incorporated to IMGD presents the distribution of SNPs and INDELs in the mitochondrial genomes of multiple isolates within eight species. A newly developed comparative SNU Genome Browser supports the graphical presentation and interactive interface for the identified SNPs/INDELs. Conclusion The IMGD provides a solid foundation for the comparative mitochondrial genomics and phylogenetics of insects. All data and functions described here are available at the web site http://www.imgd.org/.

Background Fungi secrete various proteins that have diverse functions. Prediction of secretory proteins using only one program is unsatisfactory. To enhance prediction accuracy, we constructed Fungal Secretome Database (FSD). Description A three-layer hierarchical identification rule based on nine prediction programs was used to identify putative secretory proteins in 158 fungal/oomycete genomes (208,883 proteins, 15.21% of the total proteome). The presence of putative effectors containing known host targeting signals such as RXLX [EDQ] and RXLR was investigated, presenting the degree of bias along with the species. The FSD's user-friendly interface provides summaries of prediction results and diverse web-based analysis functions through Favorite, a personalized repository. Conclusions The FSD can serve as an integrated platform supporting researches on secretory proteins in the fungal kingdom. All data and functions described in this study can be accessed on the FSD web site at http://fsd.snu.ac.kr/.