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SUMMARY We perform an immunogenomics analysis utilizing whole-transcriptome sequencing of 657 pediatric extra-cranial solid cancer samples representing 14 diagnoses, and additionally utilize transcriptomes of 131 pediatric cancer cell lines and 147 normal tissue samples for comparison. We describe patterns of infiltrating immune cells, T cell receptor (TCR) clonal expansion, and translationally relevant immune checkpoints. We find that tumor-infiltrating lymphocytes and TCR counts vary widely across cancer types and within each diagnosis, and notably are significantly predictive of survival in osteosarcoma patients. We identify potential cancer-specific immunotherapeutic targets for adoptive cell therapies including cell-surface proteins, tumor germline antigens, and lineage-specific transcription factors. Using an orthogonal immunopeptidomics approach, we find several potential immunotherapeutic targets in osteosarcoma and Ewing sarcoma and validated PRAME as a bona fide multi-pediatric cancer target. Importantly, this work provides a critical framework for immune targeting of extracranial solid tumors using parallel immuno-transcriptomic and -peptidomic approaches., Graphical Abstract, In brief Brohl et al. perform immunogenomics analysis of a cohort of 788 pediatric extracranial solid tumors and cell lines, representing 14 diagnoses, utilizing RNA sequencing. They broadly describe prognostically relevant immunophenotypes and provide proof of concept of a transcriptomics-informed adoptive cellular therapy approach, validating PRAME as a multi-pediatric cancer immunotherapy target.

Summary The Annotation, Visualization and Impact Analysis (AVIA) is a web application combining multiple features to annotate and visualize genomic variant data. Users can investigate functional significance of their genetic alterations across samples, genes and pathways. Version 3.0 of AVIA offers filtering options through interactive charts and by linking disease relevant data sources. Newly incorporated services include gene, variant and sample level reporting, literature and functional correlations among impacted genes, comparative analysis across samples and against data sources such as TCGA and ClinVar, and cohort building. Sample and data management is now feasible through the application, which allows greater flexibility with sharing, reannotating and organizing data. Most importantly, AVIA’s utility stems from its convenience for allowing users to upload and explore results without any a priori knowledge or the need to install, update and maintain software or databases. Together, these enhancements strengthen AVIA as a comprehensive, user-driven variant analysis portal. Availabilityand implementation AVIA is accessible online at https://avia-abcc.ncifcrf.gov.

MicroRNAs (miRNAs) function as master regulators of gene expression in many physiological and pathological conditions including cancer. Sequence variants or isoforms (isomiRs) can account for between 40 to 60% of total miRNA counts, yet despite this overwhelming abundance, their function continues to be debated. Recent studies demonstrate that certain isomiRs can regulate unique sets of target mRNAs by altering their seed sequence or stabilizing 3’ pairing, while others are decay intermediates indicating an active miRNA turnover. Given their short sequence length and high heterogeneity, mapping isomiRs can be challenging; without adequate depth and data aggregation, low frequency events are often disregarded. To address these challenges, we present the Tumor IsomiR Encyclopedia (TIE): a dynamic database of isomiRs from over 10,000 adult and pediatric tumor samples in The Cancer Genome Atlas (TCGA) and The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) projects. A key novelty of TIE is its ability to annotate heterogeneous isomiR sequences and aggregate the variants obtained across all samples and datasets. The database provides annotation of templated and non-templated nucleotides as well as other advanced analysis. All data can be browsed online or downloaded as simple spreadsheets. Here we show analysis of isomiRs of miR-21 and miR-30a to demonstrate the utility of TIE. TIE search engine and data are hosted at https://isomir.ccr.cancer.gov/.

Supplemental Digital Content is available in the text, Introduction: Provisioning care for traumatically injured patients makes conducting research very proximal to injury difficult. These studies also inherently have regulatory barriers to overcome. Here we outline a protocol for acute-phase enrollment of traumatically injured patients into a prospective observational clinical trial with precise and comprehensive sample acquisition in support of a systems biology approach to a research study. Methods: Experts in trauma, burn, blood coagulation, computational biology, and integrative systems biology developed a prospective study that would capture the natural history of coagulation pathology after traumatic injury. Blood was sampled at admission and serial time points throughout hospitalization. Concurrently, demographic and outcomes data were recorded and on-site point-of-care testing was implemented. Protocols were harmonized across sites and sampling protocols validated through demonstration of feasibility and sample quality assurance testing. A novel data integration platform was developed to store, visualize, and enable large-scale analysis of empirical and clinical data. Regulatory considerations were also addressed in protocol development. Results: A comprehensive Manual of Operations (MOO) was developed and implemented at 3 clinical sites. After regulatory approval, the MOO was followed to collect 5,348 longitudinal samples from 1,547 patients. All samples were collected, processed, and stored per the MOO. Assay results and clinical data were entered into the novel data management platform for analyses. Conclusion: We used an iterative, interdisciplinary process to develop a systematic and robust protocol for comprehensive assessment of coagulation in traumatically injured patients. This MOO can be a template for future studies in the acute setting.

DNA damage in somatic cells originates from both environmental and endogenous sources, giving rise to mutations through multiple mechanisms. When these mutations affect the function of critical genes, cancer may ensue. Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology. Recent studies have presented genome-wide sets of somatic mutations as a 96-element vector, a procedure that only captures the immediate neighbors of the mutated nucleotide. Herein, we present a 32 × 12 mutation matrix that captures the nucleotide pattern two nucleotides upstream and downstream of the mutation. A somatic autosomal mutation matrix (SAMM) was constructed from tumor-specific mutations derived from each of 909 individual cancer genomes harboring a total of 10,681,843 single-base substitutions. In addition, mechanistic template mutation matrices (MTMMs) representing oxidative DNA damage, ultraviolet-induced DNA damage, 5mCpG deamination, and APOBEC-mediated cytosine mutation, are presented. MTMMs were mapped to the individual tumor SAMMs to determine the maximum contribution of each mutational mechanism to the overall mutation pattern. A Manhattan distance across all SAMM elements between any two tumor genomes was used to determine their relative distance. Employing this metric, 89.5 % of all tumor genomes were found to have a nearest neighbor from the same tissue of origin. When a distance-dependent 6-nearest neighbor classifier was used, 86.9 % of all SAMMs were assigned to the correct tissue of origin. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues. Electronic supplementary material The online version of this article (doi:10.1007/s00439-015-1566-1) contains supplementary material, which is available to authorized users.

The Frederick National Laboratory for Cancer Research hosts a Data Coordinating Center and Toolset (the Metadata Designer plus Validator) hereafter referred to as the DCC that embodies a scalable, next-generation biological and cancer research data repository that is flexible, intuitive, and adaptive. The DCC provides integrated management of datasets across all deposited projects making its data more accessible and easily reusable by the cancer research community. The DCC stores and manages access to data, enabling researchers or data depositors to grant controlled access only to specific collaborators while maintaining a user-specified embargo on deposited datasets. The DCC enables a data access and sharing capability aimed to facilitate the development of new biological insights. The DCC implements the ISA (Investigation-Study-Assay) paradigm. The ISA framework provides a rich description of experimental metadata that is agnostic and irrespective of sample characteristic, technology or measurement type. It provides clear and simple sample-to-data relationships that enables resulting data and discoveries to be reproducible and reusable. These data are in the standard Investigation-Study-Assay tab-delimited format (ISA-TAB) format, which describes a scientific investigation, its study or studies, and each study's assay(s). The DCC portal is a public repository of experiment-related information describing cancer and biomedical research investigations. The portal can be used to browse, search, and access data from uploaded datasets. Through its stand-alone Toolset (Metadata Designer plus Validator), the DCC offers data depositors and researchers a simple interface to create and validate ISA-Tab compatible metadata associated with data generated in their research. Deriving new insights from aggregates of datasets and the need for reproducible research has never been more apparent. However, a fundamental requirement for these is a comprehensive metadata annotation and documentation of the research processes - an art that is elusive to researchers. Beyond the resultant publication is the data and metadata. These two basic ingredients are building blocks for a successful reproducible research project. In addition, appropriately curated data and metadata are invaluable resources for meta-analyses of seemingly disparate research studies. Further emphasizing the importance of these basic elements, are the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) - to guide data producers and publishers around obstacles and help maximize added-value gained from published studies. The DCC provides a much-needed resource to the research community for simplifying the sharing of data sets that meet these principles. The DCC portal is located at https://cssi-dcc.nci.nih.gov/cssiportal/ Citation Format: Paul Aiyetan, Paul Donovan, David Mott, Matthew Starr, Rajani Kuchipudi, Mahesh Yelisetti, Debra Hope, Corinne Zeitler, Uma Mudunuri, Andrew Quong. Enabling data access, sharing, collaborative and reproducible research: The Frederick National Laboratory for Cancer Research (FNLCR) data coordinating center [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2489.

DNA damage in somatic cells originates from both environmental and endogenous sources, giving rise to mutations through multiple mechanisms. When these mutations affect the function of critical genes, cancer may ensue. Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology. Recent studies have presented genome-wide sets of somatic mutations as a 96-element vector, a procedure that only captures the immediate neighbors of the mutated nucleotide. Herein, we present a 32 × 12 mutation matrix that captures the nucleotide pattern two nucleotides upstream and downstream of the mutation. A somatic autosomal mutation matrix (SAMM) was constructed from tumor-specific mutations derived from each of 909 individual cancer genomes harboring a total of 10,681,843 single-base substitutions. In addition, mechanistic template mutation matrices (MTMMs) representing oxidative DNA damage, ultraviolet-induced DNA damage, (5m)CpG deamination, and APOBEC-mediated cytosine mutation, are presented. MTMMs were mapped to the individual tumor SAMMs to determine the maximum contribution of each mutational mechanism to the overall mutation pattern. A Manhattan distance across all SAMM elements between any two tumor genomes was used to determine their relative distance. Employing this metric, 89.5% of all tumor genomes were found to have a nearest neighbor from the same tissue of origin. When a distance-dependent 6-nearest neighbor classifier was used, 10.4% of the SAMMs had an Undetermined tissue of origin, and 92.2% of the remaining SAMMs were assigned to the correct tissue of origin. [corrected]. Thus, although tumors from different tissues may have similar mutation patterns, their SAMMs often display signatures that are characteristic of specific tissues.

The accumulation of mutations is a contributing factor in the initiation of premalignant mammary lesions and their progression to malignancy and metastasis. We have used a mouse model in which the carcinogen is the mouse mammary tumor virus (MMTV) which induces clonal premalignant mammary lesions and malignant mammary tumors by insertional mutagenesis. Identification of the genes and signaling pathways affected in MMTV-induced mouse mammary lesions provides a rationale for determining whether genetic alteration of the human orthologues of these genes/pathways may contribute to human breast carcinogenesis. A high-throughput platform for inverse PCR to identify MMTV-host junction fragments and their nucleotide sequences in a large panel of MMTV-induced lesions was developed. Validation of the genes affected by MMTV-insertion was carried out by microarray analysis. Common integration site (CIS) means that the gene was altered by an MMTV proviral insertion in at least two independent lesions arising in different hosts. Three of the new genes identified as CIS for MMTV were assayed for their capability to confer on HC11 mouse mammary epithelial cells the ability for invasion, anchorage independent growth and tumor development in nude mice. Analysis of MMTV induced mammary premalignant hyperplastic outgrowth (HOG) lines and mammary tumors led to the identification of CIS restricted to 35 loci. Within these loci members of the Wnt, Fgf and Rspo gene families plus two linked genes (Npm3 and Ddn) were frequently activated in tumors induced by MMTV. A second group of 15 CIS occur at a low frequency (2-5 observations) in mammary HOGs or tumors. In this latter group the expression of either Phf19 or Sdc2 was shown to increase HC11 cells invasion capability. Foxl1 expression conferred on HC11 cells the capability for anchorage-independent colony formation in soft agar and tumor development in nude mice. The published transcriptome and nucleotide sequence analysis of gene expression in primary human breast tumors was interrogated. Twenty of the human orthologues of MMTV CIS associated genes are deregulated and/or mutated in human breast tumors.

The botulinum neurotoxins (BoNT, serotypes A-G) are some of the most toxic proteins known and are the causative agents of botulism. Following exposure, the neurotoxin binds and enters peripheral cholinergic nerve endings and specifically and selectively cleaves one or more SNARE proteins to produce flaccid paralysis. This review centers on the kinetics of the Zn-dependent proteolytic activities of these neurotoxins, and briefly describes inhibitors, activators and factors underlying persistence of toxin action. Some of the structural, enzymatic and inhibitor data that are discussed here are available at the botulinum neurotoxin resource, BotDB (http://botdb.abcc.ncifcrf.gov).

As the discipline of biomedical science continues to apply new technologies capable of producing unprecedented volumes of noisy and complex biological data, it has become evident that available methods for deriving meaningful information from such data are simply not keeping pace. In order to achieve useful results, researchers require methods that consolidate, store and query combinations of structured and unstructured data sets efficiently and effectively. As we move towards personalized medicine, the need to combine unstructured data, such as medical literature, with large amounts of highly structured and high-throughput data such as human variation or expression data from very large cohorts, is especially urgent. For our study, we investigated a likely biomedical query using the Hadoop framework. We ran queries using native MapReduce tools we developed as well as other open source and proprietary tools. Our results suggest that the available technologies within the Big Data domain can reduce the time and effort needed to utilize and apply distributed queries over large datasets in practical clinical applications in the life sciences domain. The methodologies and technologies discussed in this paper set the stage for a more detailed evaluation that investigates how various data structures and data models are best mapped to the proper computational framework.

This unit describes basic protocols on using the non-B DNA Motif Search Tool (nBMST) to search for sequence motifs predicted to form alternative DNA conformations that differ from the canonical right-handed Watson-Crick double-helix, collectively known as non-B DNA and on using the associated PolyBrowse, a GBrowse (Stein et al., 2002) based genomic browser. The nBMST is a web-based resource that allows users to submit one or more DNA sequences to search for inverted repeats (cruciform DNA), mirror repeats (triplex DNA), direct/tandem repeats (slipped/hairpin structures), G4 motifs (tetraplex, G-quadruplex DNA), alternating purine-pyrimidine tracts (left-handed Z-DNA), and Aphased repeats (static bending). Basic protocol 1 illustrates different ways of submitting sequences, the required file input format, results comprising downloadable Generic Feature Format (GFF) files, static Portable Network Graphics (PNG) images, dynamic PolyBrowse link, and accessing documentation through the Help and Frequently Asked Questions (FAQs) pages. Basic Protocol 2 illustrates a brief overview of some of the PolyBrowse functionalities, particularly with reference to possible associations between predicted non-B DNA forming motifs and disease causing effects. The nBMST is versatile, simple to use, does not require bioinformatics skills, and can be applied to any type of DNA sequences, including viral and bacterial genomes, up to 20 megabytes (MB).

Botulinum neurotoxin is a pharmaceutical treatment used for an increasing number of neurological and non-neurological indications, symptoms and diseases. Despite the wealth of clinical reports that involve the timing of the therapeutic effects of this toxin, few studies have attempted to integrate these data into unified models. Secondary reactions have also been examined including the development of adverse events, resistance to repeated applications, and nerve terminal sprouting. Our primary intent for conducting this review was to gather relevant pharmacodynamic data from suitable biomedical literature regarding botulinum neurotoxins via the use of automated data-mining techniques. We envision that mathematical models will ultimately be of value to those who are healthcare decision makers and providers, as well as clinical and basic researchers. Furthermore, we hypothesize that the combination of this computer-intensive approach with mathematical modeling will predict the percentage of patients who will favorably or adversely respond to this treatment and thus will eventually assist in developing the increasingly important area of personalized medicine.

Telomeres are extraordinarily dynamic chromosomal structures. They are essential for genome stability and faithful chromosome replication and mediate a host of key biological activities, including cell cycle regulation, cellular aging, movements and localization of chromosomes within the nucleus, and transcriptional regulation of subtelomeric genes (Blasco et al. 1999; Feuerbach et al. 2002). Specialized functions involving telomeric and subtelomeric DNA have evolved in a wide range of eukaryotes; for example, frequent subtelomeric gene conversion provides diversity for surface antigens in Trypanosomes (McCulloch et al. 1997), and rapidly evolving subtelomeric gene families confer selective advantages for closely related yeast strains (Carlson et al. 1985). A conserved, (TTAGGG)n tract forms the DNA component of each chromosome terminus in humans (Moyzis et al. 1988). A specialized enzyme called telomerase can lengthen the telomere repeat motif by adding on motif-specific nucleotides in a DNA template-independent manner (Morin 1989). However, both telomerase-associated and telomerase-independent pathways for maintaining (TTAGGG)n repeats exist; the major telomerase-independent pathways are recombination based, sometimes involve coamplification of subtelomeric sequences along with the simple repeat tracts found at chromosome termini (Murnane et al. 1994; Bryan et al. 1995; Lundblad and Wright 1996; Henson et al. 2002) and can generate very long and heterogeneous stretches of (TTAGGG)n-containing repeats (Rizki and Lundblad 2001; Henson et al. 2002). Transcription of subtelomeric genes can be regulated by (TTAGGG)n tract length (Baur et al. 2001) and by subtelomeric repeat content and abundance, possibly by contributing specific sequence elements necessary for local silencing (Fourel et al. 1999; Pryde and Louis 1999) or by providing extended homology regions required for somatic pairing and heterochromatin formation (Donaldson and Karpen 1997). Subtelomeric DNA, along with pericentromeric chromosome regions, are preferential sites of segmentally duplicated DNA. Estimated to comprise ∼5% of the human genome, this class of low-copy repeat DNA is characterized by very high sequence similarity (90% to >99.5%) between homology tracts, and variable, but often very large tract lengths (1 kb to >200 kb). These large homology segments have complicated mapping and sequencing efforts, and caused a disproportionate number of assembly errors in the initial working draft sequence of the human genome. Segmental duplications can predispose associated chromosome segments to genetic instability and have been connected with several genetic diseases (Bailey et al. 2001). Evolutionarily recent duplicative transposition of these large DNA tracts has led to the generation of new gene families and to the formation of fusion transcripts with potentially new functions (Bailey et al. 2002). In this study, we define segmental duplications occurring in more than one subtelomeric region “subtelomeric repeats,” and refer to all others simply as segmental duplications. Large variant alleles of many human subtelomeric regions exist, and are believed to consist entirely of subtelomeric repeats (Wilkie et al. 1991; Macina et al. 1994, 1995; Trask et al. 1998; Mefford and Trask 2002). For example, Wilkie et al (1991) found that three alleles varying in length up to 260 kb exist at the 16p telomere. Trask et al. (1998) examined the structure and genomic distribution of a cosmid-sized block of segmentally duplicated subtelomeric DNA. They found that this block was consistently present at the 3q, 15q, and 19p telomeres in humans, was variably distributed at an additional subset of human telomeres, but was present in a single copy in nonhuman primate genomes. Similar studies have demonstrated more recently that the evolution of most primate subtelomeric regions has involved multiple, lineage-dependent duplications in recent evolutionary time (Martin et al. 2002; van Geel et al. 2002). The duplications have colonized many individual human subtelomeric regions in a variable fashion since the divergence of human and primate lineages. A complete reference sequence for each human subtelomere region is an essential starting point for analysis of their function and evolution. Here, we report the mapping and initial analysis of a complete set of subtelomeric sequence assemblies. Comprised of both draft and finished public sequence accessions available as of August 1, 2003, the draft fragments are properly ordered and the assemblies are positioned relative to the respective telomere. These properties permit a comparison of subtelomeric sequence organization at each of the separate human telomeres, and the proper placement of transcripts relative to subtelomeric sequence elements and terminal (TTAGGG)n tracts.

The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.

Single base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease., Author Summary A large number of DNA mutations identified in cells from patients with cancer or human inherited disease were analyzed to address a fundamental issue in human pathology, viz, the mutational mechanisms that cause irreversible changes to DNA. By using bioinformatics and computational methods, we found that mutations do not occur randomly, but instead affect specific bases, most often guanines flanked by other guanines or adenines. We attribute this effect to electron transfer, a chemical reaction known to underlie basic biological processes such as cellular respiration and photosynthesis. Certain types of carcinogens, oxidants or radiation can interact with DNA and abstract an electron. Our results imply that the ensuing sites of electron loss can migrate from their original position in the DNA to neighboring guanines where they become trapped, leading to further chemical modifications that may eventually result in mutations. Many of the mutations known to be important for tumor growth (driver mutations), as well as passenger mutations and mutations associated with inherited disease, appear to be caused by electron transfer. Beyond pathological mutations, electron transfer may represent a universal mechanism by which genetic changes occur in all life forms to drive population fitness over evolutionary time.

The literature search section (botXminer) in the botulinum resource database (BotDB; http://botdb.abcc.ncifcrf.gov) contains a new query tool - 'Batch Search'. In basic mode, a user can submit a list of words or phrases that are used to conduct a sequential search of the titles, abstracts and MEDLINE contents of clostridial neurotoxin citations. A table of results is returned that contains the numbers of citations found for each query term that are, in turn, linked to information from PubMed and MEDLINE for each citation. In matrix mode, a user can join two lists of user-defined terms in which all of the results from the combinatorial pairs are returned in a matrix. Each matrix element is linked to a citation list. In both modes, searches can be refined by selecting a range of publication years. Examples of 'Batch Search' matrices are statistically analysed for their quality by calculating their recall and precision values.

DNA sequence motifs with the ability to form non-B (non-canonical) structures have been linked to a variety of regulatory and pathological processes. Although the exact mechanism is unknown, recent work has provided significant evidence that non-B DNA structures may play a role in DNA instability and mutagenesis, leading to both DNA rearrangements and increased mutational rates, which are hallmarks of cancer. We have developed algorithms to identify a wide variety of non-B-DNA-forming motifs, including G-quadruplex-forming repeats, direct repeats and slipped motifs, inverted repeats and cruciform motifs, mirror repeats and triplex motifs, and A-phased repeats. After identifying these motifs in the mammalian reference genomes of human, mouse, chimpanzee, macaque, cow, dog, rat and platypus, the data were made publicly available in non-B DB [1]. However, it soon became apparent that it was not feasible to annotate the ever-growing list of genomic data and that it would be more effective to provide researchers with a systematic tool to predict these motifs in their own genomic data. Thus, the non-B DNA Motif Search Tool (nBMST) was created, and it is freely available online [2]. nBMST is a web interface that enables researchers to interactively submit any DNA sequence for searching for non-B DNA motifs. Once a user submits one or more DNA sequences in FASTA format, nBMST returns a comprehensive results page that contains the following: downloadable files in both a tab-delimited format and a generic feature format (GFF); a visualization, including PNG images; and a dynamic genome browser created using the Generic Genome Browser (GBrowse) [3] (version 2.0). Currently, nBMST allows file sizes of up to 20 MB of DNA sequence to be uploaded and stores the results for registered users for up to six months. In summary, the purpose of nBMST is to help provide insight into the involvement of alternative DNA conformations in cancer and other diseases, as well as into other potential biological functions.