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  • 1
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    Laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS) maps changes in DNA methylation associated with gonadectomy-induced adrenocortical neoplasia in the mouse (2013)
    Oxford University Press
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    Publication Date: 2013-06-08
    Description: DNA methylation is a mechanism for long-term transcriptional regulation and is required for normal cellular differentiation. Failure to properly establish or maintain DNA methylation patterns leads to cell dysfunction and diseases such as cancer. Identifying DNA methylation signatures in complex tissues can be challenging owing to inaccurate cell enrichment methods and low DNA yields. We have developed a technique called laser capture microdissection-reduced representation bisulfite sequencing (LCM-RRBS) for the multiplexed interrogation of the DNA methylation status of cytosine–guanine dinucleotide islands and promoters. LCM-RRBS accurately and reproducibly profiles genome-wide methylation of DNA extracted from microdissected fresh frozen or formalin-fixed paraffin-embedded tissue samples. To demonstrate the utility of LCM-RRBS, we characterized changes in DNA methylation associated with gonadectomy-induced adrenocortical neoplasia in the mouse. Compared with adjacent normal tissue, the adrenocortical tumors showed reproducible gains and losses of DNA methylation at genes involved in cell differentiation and organ development. LCM-RRBS is a rapid, cost-effective, and sensitive technique for analyzing DNA methylation in heterogeneous tissues and will facilitate the investigation of DNA methylation in cancer and organ development.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 2
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    Patient-specific driver gene prediction and risk assessment through integrated network analysis of cancer omics profiles (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: Extensive and multi-dimensional data sets generated from recent cancer omics profiling projects have presented new challenges and opportunities for unraveling the complexity of cancer genome landscapes. In particular, distinguishing the unique complement of genes that drive tumorigenesis in each patient from a sea of passenger mutations is necessary for translating the full benefit of cancer genome sequencing into the clinic. We address this need by presenting a data integration framework (OncoIMPACT) to nominate patient-specific driver genes based on their phenotypic impact. Extensive in silico and in vitro validation helped establish OncoIMPACT's robustness, improved precision over competing approaches and verifiable patient and cell line specific predictions (2/2 and 6/7 true positives and negatives, respectively). In particular, we computationally predicted and experimentally validated the gene TRIM24 as a putative novel amplified driver in a melanoma patient. Applying OncoIMPACT to more than 1000 tumor samples, we generated patient-specific driver gene lists in five different cancer types to identify modes of synergistic action. We also provide the first demonstration that computationally derived driver mutation signatures can be overall superior to single gene and gene expression based signatures in enabling patient stratification and prognostication. Source code and executables for OncoIMPACT are freely available from http://sourceforge.net/projects/oncoimpact .
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 3
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    Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data (2015)
    Oxford University Press
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    Publication Date: 2015-12-02
    Description: Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, we present Allelome.PRO, an automated user-friendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively analyzed imprinted expression to give a complete picture of the ‘allelome’ by automatically categorising the allelic expression of all genes in a given cell type into imprinted, strain-biased, biallelic or non-informative. Allelome.PRO offers increased sensitivity to analyze lowly expressed transcripts, together with a robust false discovery rate empirically calculated from variation in the sequencing data. We used RNA-seq data from mouse embryonic fibroblasts from F1 reciprocal crosses to determine a biologically relevant allelic ratio cutoff, and define for the first time an entire allelome. Furthermore, we show that Allelome.PRO detects differential enrichment of H3K4me3 over promoters from ChIP-seq data validating the RNA-seq results. This approach can be easily extended to analyze histone marks of active enhancers, or transcription factor binding sites and therefore provides a powerful tool to identify candidate cis regulatory elements genome wide.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 4
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    iRNA-seq: computational method for genome-wide assessment of acute transcriptional regulation from total RNA-seq data (2015)
    Oxford University Press
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    Publication Date: 2015-04-02
    Description: RNA-seq is a sensitive and accurate technique to compare steady-state levels of RNA between different cellular states. However, as it does not provide an account of transcriptional activity per se , other technologies are needed to more precisely determine acute transcriptional responses. Here, we have developed an easy, sensitive and accurate novel computational method, iRNA-seq , for genome-wide assessment of transcriptional activity based on analysis of intron coverage from total RNA-seq data. Comparison of the results derived from iRNA-seq analyses with parallel results derived using current methods for genome-wide determination of transcriptional activity, i.e. global run-on (GRO)-seq and RNA polymerase II (RNAPII) ChIP-seq, demonstrate that iRNA-seq provides similar results in terms of number of regulated genes and their fold change. However, unlike the current methods that are all very labor-intensive and demanding in terms of sample material and technologies, iRNA-seq is cheap and easy and requires very little sample material. In conclusion, iRNA-seq offers an attractive novel alternative to current methods for determination of changes in transcriptional activity at a genome-wide level.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins (2015)
    Oxford University Press
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    Publication Date: 2015-02-18
    Description: The emergence of new sequencing technologies has facilitated the use of bacterial whole genome alignments for evolutionary studies and outbreak analyses. These datasets, of increasing size, often include examples of multiple different mechanisms of horizontal sequence transfer resulting in substantial alterations to prokaryotic chromosomes. The impact of these processes demands rapid and flexible approaches able to account for recombination when reconstructing isolates’ recent diversification. Gubbins is an iterative algorithm that uses spatial scanning statistics to identify loci containing elevated densities of base substitutions suggestive of horizontal sequence transfer while concurrently constructing a maximum likelihood phylogeny based on the putative point mutations outside these regions of high sequence diversity. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistically parameterized models of bacterial evolution, and achieves convergence in only a few hours on alignments of hundreds of bacterial genome sequences. Gubbins is appropriate for reconstructing the recent evolutionary history of a variety of haploid genotype alignments, as it makes no assumptions about the underlying mechanism of recombination. The software is freely available for download at github.com/sanger-pathogens/Gubbins , implemented in Python and C and supported on Linux and Mac OS X.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    Interaction-based discovery of functionally important genes in cancers (2014)
    Oxford University Press
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    Publication Date: 2014-02-11
    Description: A major challenge in cancer genomics is uncovering genes with an active role in tumorigenesis from a potentially large pool of mutated genes across patient samples. Here we focus on the interactions that proteins make with nucleic acids, small molecules, ions and peptides, and show that residues within proteins that are involved in these interactions are more frequently affected by mutations observed in large-scale cancer genomic data than are other residues. We leverage this observation to predict genes that play a functionally important role in cancers by introducing a computational pipeline ( http://canbind.princeton.edu ) for mapping large-scale cancer exome data across patients onto protein structures, and automatically extracting proteins with an enriched number of mutations affecting their nucleic acid, small molecule, ion or peptide binding sites. Using this computational approach, we show that many previously known genes implicated in cancers are enriched in mutations within the binding sites of their encoded proteins. By focusing on functionally relevant portions of proteins—specifically those known to be involved in molecular interactions—our approach is particularly well suited to detect infrequent mutations that may nonetheless be important in cancer, and should aid in expanding our functional understanding of the genomic landscape of cancer.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 7
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    A robust PCR primer design platform applied to the detection of Acidobacteria Group 1 in soil (2012)
    Oxford University Press
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    Publication Date: 2012-06-28
    Description: Environmental biosurveillance and microbial ecology studies use PCR-based assays to detect and quantify microbial taxa and gene sequences within a complex background of microorganisms. However, the fragmentary nature and growing quantity of DNA-sequence data make group-specific assay design challenging. We solved this problem by developing a software platform that enables PCR-assay design at an unprecedented scale. As a demonstration, we developed quantitative PCR assays for a globally widespread, ecologically important bacterial group in soil, Acidobacteria Group 1. A total of 33 684 Acidobacteria 16S rRNA gene sequences were used for assay design. Following 1 week of computation on a 376-core cluster, 83 assays were obtained. We validated the specificity of the top three assays, collectively predicted to detect 42% of the Acidobacteria Group 1 sequences, by PCR amplification and sequencing of DNA from soil. Based on previous analyses of 16S rRNA gene sequencing, Acidobacteria Group 1 species were expected to decrease in response to elevated atmospheric CO 2 . Quantitative PCR results, using the Acidobacteria Group 1-specific PCR assays, confirmed the expected decrease and provided higher statistical confidence than the 16S rRNA gene-sequencing data. These results demonstrate a powerful capacity to address previously intractable assay design challenges.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 8
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    Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways (2013)
    Oxford University Press
    Details
    Publication Date: 2013-05-04
    Description: Various ‘omics’ technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 9
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    RAG1 targeting in the genome is dominated by chromatin interactions mediated by the non-core regions of RAG1 and RAG2 (2016)
    Oxford University Press
    Details
    Publication Date: 2016-12-01
    Description: The RAG1/RAG2 endonuclease initiates V(D)J recombination at antigen receptor loci but also binds to thousands of places outside of these loci. RAG2 localizes directly to lysine 4 trimethylated histone 3 (H3K4me3) through a plant homeodomain (PHD) finger. The relative contribution of RAG2-dependent and RAG1-intrinsic mechanisms in determining RAG1 binding patterns is not known. Through analysis of deep RAG1 ChIP-seq data, we provide a quantitative description of the forces underlying genome-wide targeting of RAG1. Surprisingly, sequence-specific DNA binding contributes minimally to RAG1 targeting outside of antigen receptor loci. Instead, RAG1 binding is driven by two distinct modes of interaction with chromatin: the first is driven by H3K4me3, promoter-focused and dependent on the RAG2 PHD, and the second is defined by H3K27Ac, enhancer-focused and dependent on ‘non-core’ portions of RAG1. Based on this and additional chromatin and genomic features, we formulated a predictive model of RAG1 targeting to the genome. RAG1 binding sites predicted by our model correlate well with observed patterns of RAG1-mediated breaks in human pro-B acute lymphoblastic leukemia. Overall, this study provides an integrative model for RAG1 genome-wide binding and off-target activity and reveals a novel role for the RAG1 non-core region in RAG1 targeting.
    Keywords: Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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