ssGSEA score-based Ras dependency indexes derived from gene expression data reveal potential Ras addiction mechanisms with possible clinical implications.

For nearly a decade, the difficulties associated with both the determination and reproducibility of Ras-dependency indexes (RDIs) have limited their application and further delineation of the biology underlying Ras dependency. In this report, we describe the application of a computational single sample gene set enrichment analysis (ssGSEA) method to derive RDIs with gene expression data. The computationally derived RDIs across the Cancer Cell Line Encyclopedia (CCLE) cell lines show excellent agreement with the experimentally derived values and high correlation with a previous in-house siRNA effector node (siREN) study and external studies. Using EMT signature-derived RDIs and data from cell lines representing the extremes in RAS dependency, we identified enriched pathways distinguishing these classes, including the Fas signaling pathway and a putative Ras-independent pathway first identified in NK cells. Importantly, extension of the method to patient samples from The Cancer Genome Atlas (TCGA) showed the same consensus differential expression patterns for these two pathways across multiple tissue types. Last, the computational RDIs displayed a significant association with TCGA cancer patients' survival outcomes. Together, these lines of evidence confirm that our computationally derived RDIs faithfully represent a measure of Ras dependency in both cancer cell lines and patient samples. The application of such computational RDIs can provide insights into Ras biology and potential clinical applications.

KRAS G13D sensitivity to neurofibromin-mediated GTP hydrolysis.

KRAS mutations occur in ∼35% of colorectal cancers and promote tumor growth by constitutively activating the mitogen-activated protein kinase (MAPK) pathway. KRAS mutations at codons 12, 13, or 61 are thought to prevent GAP protein-stimulated GTP hydrolysis and render KRAS-mutated colorectal cancers unresponsive to epidermal growth factor receptor (EGFR) inhibitors. We report here that KRAS G13-mutated cancer cells are frequently comutated with NF1 GAP but NF1 is rarely mutated in cancers with KRAS codon 12 or 61 mutations. Neurofibromin protein (encoded by the NF1 gene) hydrolyzes GTP directly in complex with KRAS G13D, and KRAS G13D-mutated cells can respond to EGFR inhibitors in a neurofibromin-dependent manner. Structures of the wild type and G13D mutant of KRAS in complex with neurofibromin (RasGAP domain) provide the structural basis for neurofibromin-mediated GTP hydrolysis. These results reveal that KRAS G13D is responsive to neurofibromin-stimulated hydrolysis and suggest that a subset of KRAS G13-mutated colorectal cancers that are neurofibromin-competent may respond to EGFR therapies.

GradientScanSurv-An exhaustive association test method for gene expression data with censored survival outcome.

Accurate assessment of the association between continuous variables such as gene expression and survival is a critical aspect of precision medicine. In this report, we provide a review of some of the available survival analysis and validation tools by referencing published studies that have utilized these tools. We have identified pitfalls associated with the assumptions inherent in those applications that have the potential to impact scientific research through their potential bias. In order to overcome these pitfalls, we have developed a novel method that enables the logrank test method to handle continuous variables that comprehensively evaluates survival association with derived aggregate statistics. This is accomplished by exhaustively considering all the cutpoints across the full expression gradient. Direct side-by-side comparisons, global ROC analysis, and evaluation of the ability to capture relevant biological themes based on current understanding of RAS biology all demonstrated that the new method shows better consistency between multiple datasets of the same disease, better reproducibility and robustness, and better detection power to uncover biological relevance within the selected datasets over the available survival analysis methods on univariate gene expression and penalized linear model-based methods.

IFNL4-ΔG Allele Is Associated with an Interferon Signature in Tumors and Survival of African-American Men with Prostate Cancer.

Purpose: Men of African ancestry experience an excessive prostate cancer mortality that could be related to an aggressive tumor biology. We previously described an immune-inflammation signature in prostate tumors of African-American (AA) patients. Here, we further deconstructed this signature and investigated its relationships with tumor biology, survival, and a common germline variant in the IFNλ4 (IFNL4) gene.Experimental Design: We analyzed gene expression in prostate tissue datasets and performed genotype and survival analyses. We also overexpressed IFNL4 in human prostate cancer cells.Results: We found that a distinct interferon (IFN) signature that is analogous to the previously described "IFN-related DNA damage resistance signature" (IRDS) occurs in prostate tumors. Evaluation of two independent patient cohorts revealed that IRDS is detected about twice as often in prostate tumors of AA than European-American men. Furthermore, analysis in TCGA showed an association of increased IRDS in prostate tumors with decreased disease-free survival. To explain these observations, we assessed whether IRDS is associated with an IFNL4 germline variant (rs368234815-ΔG) that controls production of IFNλ4, a type III IFN, and is most common in individuals of African ancestry. We show that the IFNL4 rs368234815-ΔG allele was significantly associated with IRDS in prostate tumors and overall survival of AA patients. Moreover, IFNL4 overexpression induced IRDS in three human prostate cancer cell lines.Conclusions: Our study links a germline variant that controls production of IFNλ4 to the occurrence of a clinically relevant IFN signature in prostate tumors that may predominantly affect men of African ancestry. Clin Cancer Res; 24(21); 5471-81. ©2018 AACR.

Tumor RAS Gene Expression Levels Are Influenced by the Mutational Status of RAS Genes and Both Upstream and Downstream RAS Pathway Genes.

The 3 human RAS genes play pivotal roles regulating proliferation, differentiation, and survival in normal cells and become mutated in 15% to 20% of all human tumors and amplified in many others. In this report, we examined data from The Cancer Genome Atlas to investigate the relationship between RAS gene mutational status and messenger RNA expression. We show that all 3 RAS genes exhibit increased expression when they are mutated in a context-dependent manner. In the case of KRAS, this increase is manifested by a larger proportional increase in KRAS4A than KRAS4B, although both increase significantly. In addition, the mutational status of RAS genes can be associated with expression changes in other RAS genes, with most of these cases showing decreased expression. The mutational status associations with expression are recapitulated in cancer cell lines. Increases in expression are mediated by both copy number variation and contextual differences, including mutational status of epidermal growth factor receptor (EGFR) and BRAF. These findings potentially reveal an adaptive response during tumor evolution that is dependent on the mutational status of proximal genes in the RAS pathway and cellular context. Cell contextual differences in these adaptations may influence therapeutic responsiveness and alternative resistance mechanisms.

Comparative proteomics of a model MCF10A-KRasG12V cell line reveals a distinct molecular signature of the KRasG12V cell surface.

Oncogenic Ras mutants play a major role in the etiology of most aggressive and deadly carcinomas in humans. In spite of continuous efforts, effective pharmacological treatments targeting oncogenic Ras isoforms have not been developed. Cell-surface proteins represent top therapeutic targets primarily due to their accessibility and susceptibility to different modes of cancer therapy. To expand the treatment options of cancers driven by oncogenic Ras, new targets need to be identified and characterized at the surface of cancer cells expressing oncogenic Ras mutants. Here, we describe a mass spectrometry-based method for molecular profiling of the cell surface using KRasG12V transfected MCF10A (MCF10A-KRasG12V) as a model cell line of constitutively activated KRas and native MCF10A cells transduced with an empty vector (EV) as control. An extensive molecular map of the KRas surface was achieved by applying, in parallel, targeted hydrazide-based cell-surface capturing technology and global shotgun membrane proteomics to identify the proteins on the KRasG12V surface. This method allowed for integrated proteomic analysis that identified more than 500 cell-surface proteins found unique or upregulated on the surface of MCF10A-KRasG12V cells. Multistep bioinformatic processing was employed to elucidate and prioritize targets for cross-validation. Scanning electron microscopy and phenotypic cancer cell assays revealed changes at the cell surface consistent with malignant epithelial-to-mesenchymal transformation secondary to KRasG12V activation. Taken together, this dataset significantly expands the map of the KRasG12V surface and uncovers potential targets involved primarily in cell motility, cellular protrusion formation, and metastasis.

An Immune-Inflammation Gene Expression Signature in Prostate Tumors of Smokers.

Smokers develop metastatic prostate cancer more frequently than nonsmokers, suggesting that a tobacco-derived factor is driving metastatic progression. To identify smoking-induced alterations in human prostate cancer, we analyzed gene and protein expression patterns in tumors collected from current, past, and never smokers. By this route, we elucidated a distinct pattern of molecular alterations characterized by an immune and inflammation signature in tumors from current smokers that were either attenuated or absent in past and never smokers. Specifically, this signature included elevated immunoglobulin expression by tumor-infiltrating B cells, NF-κB activation, and increased chemokine expression. In an alternate approach to characterize smoking-induced oncogenic alterations, we also explored the effects of nicotine in human prostate cancer cells and prostate cancer-prone TRAMP mice. These investigations showed that nicotine increased glutamine consumption and invasiveness of cancer cells in vitro and accelerated metastatic progression in tumor-bearing TRAMP mice. Overall, our findings suggest that nicotine is sufficient to induce a phenotype resembling the epidemiology of smoking-associated prostate cancer progression, illuminating a novel candidate driver underlying metastatic prostate cancer in current smokers.

The somatic autosomal mutation matrix in cancer genomes.

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.

Performance comparison of SNP detection tools with illumina exome sequencing data--an assessment using both family pedigree information and sample-matched SNP array data.

To apply exome-seq-derived variants in the clinical setting, there is an urgent need to identify the best variant caller(s) from a large collection of available options. We have used an Illumina exome-seq dataset as a benchmark, with two validation scenarios--family pedigree information and SNP array data for the same samples, permitting global high-throughput cross-validation, to evaluate the quality of SNP calls derived from several popular variant discovery tools from both the open-source and commercial communities using a set of designated quality metrics. To the best of our knowledge, this is the first large-scale performance comparison of exome-seq variant discovery tools using high-throughput validation with both Mendelian inheritance checking and SNP array data, which allows us to gain insights into the accuracy of SNP calling through such high-throughput validation in an unprecedented way, whereas the previously reported comparison studies have only assessed concordance of these tools without directly assessing the quality of the derived SNPs. More importantly, the main purpose of our study was to establish a reusable procedure that applies high-throughput validation to compare the quality of SNP discovery tools with a focus on exome-seq, which can be used to compare any forthcoming tool(s) of interest.

Pathway-specific engineered mouse allograft models functionally recapitulate human serous epithelial ovarian cancer.

The high mortality rate from ovarian cancers can be attributed to late-stage diagnosis and lack of effective treatment. Despite enormous effort to develop better targeted therapies, platinum-based chemotherapy still remains the standard of care for ovarian cancer patients, and resistance occurs at a high rate. One of the rate limiting factors for translation of new drug discoveries into clinical treatments has been the lack of suitable preclinical cancer models with high predictive value. We previously generated genetically engineered mouse (GEM) models based on perturbation of Tp53 and Rb with or without Brca1 or Brca2 that develop serous epithelial ovarian cancer (SEOC) closely resembling the human disease on histologic and molecular levels. Here, we describe an adaptation of these GEM models to orthotopic allografts that uniformly develop tumors with short latency and are ideally suited for routine preclinical studies. Ovarian tumors deficient in Brca1 respond to treatment with cisplatin and olaparib, a PARP inhibitor, whereas Brca1-wild type tumors are non-responsive to treatment, recapitulating the relative sensitivities observed in patients. These mouse models provide the opportunity for evaluation of effective therapeutics, including prediction of differential responses in Brca1-wild type and Brca1-deficient tumors and development of relevant biomarkers.

miR-126 contributes to Parkinson's disease by dysregulating the insulin-like growth factor/phosphoinositide 3-kinase signaling.

Dopamine (DA) neurons in sporadic Parkinson's disease (PD) display dysregulated gene expression networks and signaling pathways that are implicated in PD pathogenesis. Micro (mi)RNAs are regulators of gene expression, which could be involved in neurodegenerative diseases. We determined the miRNA profiles in laser microdissected DA neurons from postmortem sporadic PD patients' brains and age-matched controls. DA neurons had a distinctive miRNA signature and a set of miRNAs was dysregulated in PD. Bioinformatics analysis provided evidence for correlations of miRNAs with signaling pathways relevant to PD, including an association of miR-126 with insulin/IGF-1/PI3K signaling. In DA neuronal cell systems, enhanced expression of miR-126 impaired IGF-1 signaling and increased vulnerability to the neurotoxin 6-OHDA by downregulating factors in IGF-1/PI3K signaling, including its targets p85ß, IRS-1, and SPRED1. Blocking of miR-126 function increased IGF-1 trophism and neuroprotection to 6-OHDA. Our data imply that elevated levels of miR-126 may play a functional role in DA neurons and in PD pathogenesis by downregulating IGF-1/PI3K/AKT signaling and that its inhibition could be a mechanism of neuroprotection.

AVIA: an interactive web-server for annotation, visualization and impact analysis of genomic variations.

MOTIVATION: The plethora of information that emerges from large-scale genome characterization studies has triggered the development of computational frameworks and tools for efficient analysis, interpretation and visualization of genomic data. Functional annotation of genomic variations and the ability to visualize the data in the context of whole genome and/or multiple genomes has remained a challenging task. We have developed an interactive web-based tool, AVIA (Annotation, Visualization and Impact Analysis), to explore and interpret large sets of genomic variations (single nucleotide variations and insertion/deletions) and to help guide and summarize genomic experiments. The annotation, summary plots and tables are packaged and can be downloaded by the user from the email link provided. AVAILABILITY AND IMPLEMENTATION: http://avia.abcc.ncifcrf.gov.

MYC-driven accumulation of 2-hydroxyglutarate is associated with breast cancer prognosis.

Metabolic profiling of cancer cells has recently been established as a promising tool for the development of therapies and identification of cancer biomarkers. Here we characterized the metabolomic profile of human breast tumors and uncovered intrinsic metabolite signatures in these tumors using an untargeted discovery approach and validation of key metabolites. The oncometabolite 2-hydroxyglutarate (2HG) accumulated at high levels in a subset of tumors and human breast cancer cell lines. We discovered an association between increased 2HG levels and MYC pathway activation in breast cancer, and further corroborated this relationship using MYC overexpression and knockdown in human mammary epithelial and breast cancer cells. Further analyses revealed globally increased DNA methylation in 2HG-high tumors and identified a tumor subtype with high tissue 2HG and a distinct DNA methylation pattern that was associated with poor prognosis and occurred with higher frequency in African-American patients. Tumors of this subtype had a stem cell-like transcriptional signature and tended to overexpress glutaminase, suggestive of a functional relationship between glutamine and 2HG metabolism in breast cancer. Accordingly, 13C-labeled glutamine was incorporated into 2HG in cells with aberrant 2HG accumulation, whereas pharmacologic and siRNA-mediated glutaminase inhibition reduced 2HG levels. Our findings implicate 2HG as a candidate breast cancer oncometabolite associated with MYC activation and poor prognosis.

Knowledge and theme discovery across very large biological data sets using distributed queries: a prototype combining unstructured and structured data.

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.

Guanine holes are prominent targets for mutation in cancer and inherited disease.

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.

Analysis of 454 sequencing error rate, error sources, and artifact recombination for detection of Low-frequency drug resistance mutations in HIV-1 DNA.

BACKGROUND: 454 sequencing technology is a promising approach for characterizing HIV-1 populations and for identifying low frequency mutations. The utility of 454 technology for determining allele frequencies and linkage associations in HIV infected individuals has not been extensively investigated. We evaluated the performance of 454 sequencing for characterizing HIV populations with defined allele frequencies. RESULTS: We constructed two HIV-1 RT clones. Clone A was a wild type sequence. Clone B was identical to clone A except it contained 13 introduced drug resistant mutations. The clones were mixed at ratios ranging from 1% to 50% and were amplified by standard PCR conditions and by PCR conditions aimed at reducing PCR-based recombination. The products were sequenced using 454 pyrosequencing. Sequence analysis from standard PCR amplification revealed that 14% of all sequencing reads from a sample with a 50:50 mixture of wild type and mutant DNA were recombinants. The majority of the recombinants were the result of a single crossover event which can happen during PCR when the DNA polymerase terminates synthesis prematurely. The incompletely extended template then competes for primer sites in subsequent rounds of PCR. Although less often, a spectrum of other distinct crossover patterns was also detected. In addition, we observed point mutation errors ranging from 0.01% to 1.0% per base as well as indel (insertion and deletion) errors ranging from 0.02% to nearly 50%. The point errors (single nucleotide substitution errors) were mainly introduced during PCR while indels were the result of pyrosequencing. We then used new PCR conditions designed to reduce PCR-based recombination. Using these new conditions, the frequency of recombination was reduced 27-fold. The new conditions had no effect on point mutation errors. We found that 454 pyrosequencing was capable of identifying minority HIV-1 mutations at frequencies down to 0.1% at some nucleotide positions. CONCLUSION: Standard PCR amplification results in a high frequency of PCR-introduced recombination precluding its use for linkage analysis of HIV populations using 454 pyrosequencing. We designed a new PCR protocol that resulted in a much lower recombination frequency and provided a powerful technique for linkage analysis and haplotype determination in HIV-1 populations. Our analyses of 454 sequencing results also demonstrated that at some specific HIV-1 drug resistant sites, mutations can reliably be detected at frequencies down to 0.1%.

Transcription signatures encoded by ultraconserved genomic regions in human prostate cancer.

BACKGROUND: Ultraconserved regions (UCR) are genomic segments of more than 200 base pairs that are evolutionarily conserved among mammalian species. They are thought to have functions as transcriptional enhancers and regulators of alternative splicing. Recently, it was shown that numerous RNAs are transcribed from these regions. These UCR-encoded transcripts (ucRNAs) were found to be expressed in a tissue- and disease-specific manner and may interfere with the function of other RNAs through RNA: RNA interactions. We hypothesized that ucRNAs have unidentified roles in the pathogenesis of human prostate cancer. In a pilot study, we examined ucRNA expression profiles in human prostate tumors. METHODS: Using a custom microarray with 962 probesets representing sense and antisense sequences for the 481 human UCRs, we examined ucRNA expression in resected, fresh-frozen human prostate tissues (57 tumors, 7 non-cancerous prostate tissues) and in cultured prostate cancer cells treated with either epigenetic drugs (the hypomethylating agent, 5-Aza 2'deoxycytidine, and the histone deacetylase inhibitor, trichostatin A) or a synthetic androgen, R1881. Expression of selected ucRNAs was also assessed by qRT-PCR and NanoString®-based assays. Because ucRNAs may function as RNAs that target protein-coding genes through direct and inhibitory RNA: RNA interactions, computational analyses were applied to identify candidate ucRNA:mRNA binding pairs. RESULTS: We observed altered ucRNA expression in prostate cancer (e.g., uc.106+, uc.477+, uc.363 + A, uc.454 + A) and found that these ucRNAs were associated with cancer development, Gleason score, and extraprostatic extension after controlling for false discovery (false discovery rate < 5% for many of the transcripts). We also identified several ucRNAs that were responsive to treatment with either epigenetic drugs or androgen (R1881). For example, experiments with LNCaP human prostate cancer cells showed that uc.287+ is induced by R1881 (P < 0.05) whereas uc.283 + A was up-regulated following treatment with combined 5-Aza 2'deoxycytidine and trichostatin A (P < 0.05). Additional computational analyses predicted RNA loop-loop interactions of 302 different sense and antisense ucRNAs with 1058 different mRNAs, inferring possible functions of ucRNAs via direct interactions with mRNAs. CONCLUSIONS: This first study of ucRNA expression in human prostate cancer indicates an altered transcript expression in the disease.

An integrated understanding of the physiological response to elevated extracellular phosphate.

Recent studies have suggested that changes in serum phosphate levels influence pathological states associated with aging such as cancer, bone metabolism, and cardiovascular function, even in individuals with normal renal function. The causes are only beginning to be elucidated but are likely a combination of endocrine, paracrine, autocrine, and cell autonomous effects. We have used an integrated quantitative biology approach, combining transcriptomics and proteomics to define a multi-phase, extracellular phosphate-induced, signaling network in pre-osteoblasts as well as primary human and mouse mesenchymal stromal cells. We identified a rapid mitogenic response stimulated by elevated phosphate that results in the induction of immediate early genes including c-fos. The mechanism of activation requires FGF receptor signaling followed by stimulation of N-Ras and activation of AP-1 and serum response elements. A distinct long-term response also requires FGF receptor signaling and results in N-Ras activation and expression of genes and secretion of proteins involved in matrix regulation, calcification, and angiogenesis. The late response is synergistically enhanced by addition of FGF23 peptide. The intermediate phase results in increased oxidative phosphorylation and ATP production and is necessary for the late response providing a functional link between the phases. Collectively, the results define elevated phosphate, as a mitogen and define specific mechanisms by which phosphate stimulates proliferation and matrix regulation. Our approach provides a comprehensive understanding of the cellular response to elevated extracellular phosphate, functionally connecting temporally coordinated signaling, transcriptional, and metabolic events with changes in long-term cell behavior.

SRAdb: query and use public next-generation sequencing data from within R.

BACKGROUND: The Sequence Read Archive (SRA) is the largest public repository of sequencing data from the next generation of sequencing platforms including Illumina (Genome Analyzer, HiSeq, MiSeq, .etc), Roche 454 GS System, Applied Biosystems SOLiD System, Helicos Heliscope, PacBio RS, and others. RESULTS: SRAdb is an attempt to make queries of the metadata associated with SRA submission, study, sample, experiment and run more robust and precise, and make access to sequencing data in the SRA easier. We have parsed all the SRA metadata into a SQLite database that is routinely updated and can be easily distributed. The SRAdb R/Bioconductor package then utilizes this SQLite database for querying and accessing metadata. Full text search functionality makes querying metadata very flexible and powerful. Fastq files associated with query results can be downloaded easily for local analysis. The package also includes an interface from R to a popular genome browser, the Integrated Genomics Viewer. CONCLUSIONS: SRAdb Bioconductor package provides a convenient and integrated framework to query and access SRA metadata quickly and powerfully from within R.