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Background Weight loss may decrease risk of colorectal cancer in obese individuals, yet its effect in the colorectum is not well understood. We used integrative network modeling, Passing Attributes between Networks for Data Assimilation, to estimate transcriptional regulatory network models from mRNA expression levels from rectal mucosa biopsies measured pre- and post-weight loss in 10 obese, pre-menopausal women. Results We identified significantly greater regulatory targeting of glucose transport pathways in the post-weight loss regulatory network, including “regulation of glucose transport” (FDR = 0.02), “hexose transport” (FDR = 0.06), “glucose transport” (FDR = 0.06) and “monosaccharide transport” (FDR = 0.08). These findings were not evident by gene expression analysis alone. Network analysis also suggested a regulatory switch from NFΚB1 to MAX control of MYC post-weight loss. Conclusions These network-based results expand upon standard gene expression analysis by providing evidence for a potential mechanistic alteration caused by weight loss.

In coronary artery bypass grafting (CABG), the combined use of left and right internal mammary arteries (LIMA and RIMA) — collectively known as bilateral IMAs (BIMAs) provides a survival advantage over the use of LIMA alone. However, gene expression in RIMA has never been compared to that in LIMA. Here we report a genome-wide transcriptional analysis of BIMA to investigate the expression profiles of these conduits in patients undergoing CABG. As expected, in comparing the BIMAs to the aorta, we found differences in pathways and processes associated with atherosclerosis, inflammation, and cell signaling — pathways which provide biological support for the observation that BIMA grafts deliver long-term benefits to the patients and protect against continued atherosclerosis. These data support the widespread use of BIMAs as the preferred conduits in CABG.

Although many methods have been developed for inference of biological networks, the validation of the resulting models has largely remained an unsolved problem. Here we present a framework for quantitative assessment of inferred gene interaction networks using knock-down data from cell line experiments. Using this framework we are able to show that network inference based on integration of prior knowledge derived from the biomedical literature with genomic data significantly improves the quality of inferred networks relative to other approaches. Our results also suggest that cell line experiments can be used to quantitatively assess the quality of networks inferred from tumor samples. © 2014., SCOPUS: ar.j, info:eu-repo/semantics/published

Next-generation sequencing is increasingly employed in biomedical investigations. Strong concordance between microarray and mRNA-seq levels has been reported in high quality specimens but information is lacking on formalin-fixed, paraffin-embedded (FFPE) tissues, and particularly for microRNA (miRNA) analysis. We conducted a preliminary examination of the concordance between miRNA-seq and cDNA-mediated annealing, selection, extension, and ligation (DASL) miRNA assays. Quantitative agreement between platforms is moderate (Spearman correlation 0.514–0.596) and there is discordance of detection calls on a subset of miRNAs. Quantitative PCR (q-RT-PCR) performed for several discordant miRNAs confirmed the presence of most sequences detected by miRNA-seq but not by DASL but also that miRNA-seq did not detect some sequences, which DASL confidently detected. Our results suggest that miRNA-seq is specific, with few false positive calls, but it may not detect certain abundant miRNAs in FFPE tissue. Further work is necessary to fully address these issues that are pertinent for translational research.

We employed ABI high-density oligonucleotide microarrays containing 31,700 sixty-mer probes (representing 27,868 annotated human genes) to determine differential gene expression in idiopathic dilated cardiomyopathy (DCM). We identified 626 up-regulated and 636 down-regulated genes in DCM compared to controls. Most significant changes occurred in the tricarboxylic acid cycle, angiogenesis, and apoptotic signaling pathways, among which 32 apoptosis- and 13 MAPK activity-related genes were altered. Inorganic cation transporter, catalytic activities, energy metabolism and electron transport-related processes were among the most critically influenced pathways. Among the up-regulated genes were HTRA1 (6.9-fold), PDCD8(AIFM1) (5.2) and PRDX2 (4.4) and the down-regulated genes were NR4A2 (4.8), MX1 (4.3), LGALS9 (4), IFNA13 (4), UNC5D (3.6) and HDAC2 (3) (p

A recent study published by Sjoblom and colleagues [T. Sjoblom, S. Jones, L.D. Wood, D.W. Parsons, J. Lin, T.D. Barber, D. Mandelker, R.J. Leary, J. Ptak, N. Silliman, S. Szabo, P. Buckhaults, C. Farrell, P. Meeh, S.D. Markowitz, J. Willis, D. Dawson, J.K. Willson, A.F. Gazdar, J. Hartigan, L. Wu, C. Liu, G. Parmigiani, B.H. Park, K.E. Bachman, N. Papadopoulos, B. Vogelstein, K.W. Kinzler, V.E. Velculescu, The consensus coding sequences of human breast and colorectal cancers. Science 314 (2006) 268-274.] performed comprehensive sequencing of 13,023 human genes and identified mutations in genes specific to breast and colorectal tumors, providing insight into organ-specific tumor biology. Here we present a systematic analysis of the functional classifications of Sjoblom's “CAN” genes, a subset of these validated mutant genes, that identifies novel organ-specific biological themes and molecular pathways associated with disease-specific etiology. This analysis links four somatically mutated genes associated with diverse oncological types to colorectal and breast cancers through established TGF-β1-regulated interactions, revealing mechanistic differences in these cancers and providing potential diagnostic and therapeutic targets.

Well-established models of colorectal cancer progression are based on the idea that the disease evolves through a multistep process involving sequential genetic mutations, suggesting that progression through clinically defined stages should correlate with well-defined patterns of gene expression. The majority of studies to date, however, have assessed these processes one gene and one protein at a time. We report the first comprehensive assessment of both gene and protein expression performed in parallel across progressive stages of human colorectal neoplasia. Remarkably, despite the global nature of the gene expression assessment, very few genes could be linked with certainty to specific proteins through currently available annotations. Furthermore, the correlation of expression between identified genes and proteins was poor. Nevertheless, both produced expression signatures that differentiated normal mucosa and nonmalignant adenomas from each other and from the malignant carcinomas and both produced fairly consistent subclasses of the malignancies, suggesting that a molecular staging might be more appropriate provided that these profiles can be tied to clinical outcome. This is potentially important as clinical staging is widely used as a prognostic indicator and used in the decision to pursue adjuvant therapies.

To identify novel genes regulating the biologic response to lipopolysaccharide (LPS), we used a combination of quantitative trait locus (QTL) analysis and microarray-based gene expression studies of C57BL/6J x DBA/2J(BXD) F2 and recombinant inbred (RI) mice. A QTL affecting pulmonary TNF-alpha production was identified on chromosome 2, and a region affecting both polymorphonuclear leukocyte recruitment and TNF-alpha levels was identified on chromosome 11. Microarray analyses of unchallenged and LPS-challenged BXD RI strains identified approximately 500 genes whose expression was significantly changed by inhalation of LPS. Of these genes, 28 reside within the chromosomal regions identified by the QTL analyses, implicating these genes as high priority candidates for functional studies. Additional high priority candidate genes were identified based on their differential expression in mice having high and low responses to LPS. Functional studies of these genes are expected to reveal important molecular mechanisms regulating the magnitude of biologic responses to LPS.

A method for high-throughput, high-resolution physical mapping of complex genomes and human chromosomes called Genomic Sequence Sampling (GSS) has recently been proposed (Smith et al., 1994, Nature Genet. 7: 40-47). This mapping strategy employs high-density cosmid contig assembly over 200-kb to 1-Mb regions of the target genome coupled with DNA sequencing of the cosmid ends. The relative order and spacing of the sequence fragments is determined from the template contig, resulting in a physical map of 1- to 5-kb resolution that contains a substantial portion of the entire sequence at one-pass accuracy. The purpose of this paper is to determine the theoretical parameters for GSS mapping, to evaluate the effectiveness of the contig-building strategy, and to calculate the expected fraction of the target genome that can be recovered as mapped sequence. A novel aspect of the cosmid fingerprinting and contig-building strategy involves determining the orientation of the genomic inserts relative to the cloning vectors, so that the sampled sequence fragments can be mapped with high resolution. The algorithm is based upon complete restriction enzyme digestion, contig assembly by matching fragments, and end-orientation of individual cosmids by determining the best consistent fit of the labeled cosmid end fragments in the consensus restriction map.

Precise characterization of chromatin states is an important but difficult task for understanding the regulatory role of chromatin. A number of computational methods have been developed with varying levels of success. However, a remaining challenge is to model epigenomic patterns over multi-scales, as each histone mark is distributed with its own characteristic length scale. We developed a tiered hidden Markov model and applied it to analyze a ChIP-seq dataset in human embryonic stem cells. We identified a two-tier structure containing 15 distinct bin-level chromatin states grouped into three domain-level states. Whereas the bin-level states capture the local variation of histone marks, the domain-level states detect large-scale variations. Compared to bin-level states, the domain-level states are more robust and coherent. We also found active regions in intergenic regions that upon closer examination were expressed non-coding RNAs and pseudogenes. These results provide insights into an additional layer of complexity in chromatin organization.

The brain responds to injury and infection by activating innate defense and tissue repair mechanisms. Working upon the hypothesis that the brain defense response involves common genes and pathways across diverse pathologies, we analysed global gene expression in brain from mouse models representing three major central nervous system disorders, cerebral stroke, multiple sclerosis and Alzheimer's disease compared to normal brain using DNA microarray expression profiling. A comparison of dysregulated genes across disease models revealed common genes and pathways including key components of estrogen and TGF-β signaling pathways that have been associated with neuroprotection as well as a neurodegeneration mediator, TRPM7. Further, for each disease model, we discovered collections of differentially expressed genes that provide novel insight into the individual pathology and its associated mechanisms. Our data provide a resource for exploring the complex molecular mechanisms that underlie brain neurodegeneration and a new approach for identifying generic and disease-specific targets for therapy.

Physical mapping of human chromosomes at a resolution of 100 kb to 1 Mb will provide important reagents for gene identification and framework templates for ultimately determining the complete DNA sequence. Sequence-tagged site (STS) content mapping, coupled with large fragment cloning in yeast artificial chromosomes, provides an efficient mechanism for producing first-generation, low-resolution maps of human chromosomes. Previously, we produced a set of standardized STSs for human chromosome 11 regionally localized by fluorescence in situ hybridization or somatic cell hybrid analysis. In this paper, we used these as well as other STSs to map over 900 YAC clones to chromosome 11, organize yeast artificial chromosome (YAC) clones into contigs by STS content, and identify 109 islands spanning an estimated 218 Mb on the 126-Mb chromosome. Since about 62% of the islands contain markers ordered on chromosome 11 by genetic or radiation hybrid analysis, this data set represents a first-order approximation of a physical map of human chromosome 11. This set of clones, contigs, and associated STSs will provide the material for the production of a continuous overlapping set of YACs as well for high-resolution physical mapping based upon sampled and complete DNA sequencing.

Human chromosome 11 harbors many genes of medical significance and cancer-related rearrangements. The availability of cloned DNA in cosmids and in yeast artificial chromosomes (YACs), combined with fluorescence in situ hybridization analysis, has led to the cloning of genes at sites of chromosomal breakpoints in acute leukemias in 11q23 and in Ewing tumors in 11q24. YAC cloning has facilitated the construction of contigs covering large portions of chromosomes for the detailed analysis of disease gene regions. Here we have cloned in YACs approximately 3.2 Mb of DNA within band 11q24, spanning the Ewing sarcoma breakpoint. Landmark cosmids 23.2 (D11S374) and 5.8 (D11S372), shown by FISH to flank the breakpoint within a 1.5- to 1.8-Mb segment, were used to seed two YAC "walks" both centromeric and telomeric to the breakpoint by YAC-end cloning and screening of two total genomic YAC libraries. The centromeric YAC contig, which consists of 23 overlapping YACs and orders 19 sequence-tagged sites (STSs), covers a minimum of 2.2 Mb and spans the Ewing sarcoma breakpoint. c-ets 1 and Fli-1, two members of the ets family, have been linked within 400 kb of intervening DNA within this contig, which also comprises a polymorphic microsatellite, D11S912 (CA)n, which we have localized within the Fli-1 gene. The telomeric YAC contig, which consists of 11 overlapping YACs, comprises 5 STSs and covers a minimum of 1 Mb distal to the breakpoint. Taken together, the two contigs, which consist of a total of 34 YACs and comprise 24 STSs, are separated by a maximum gap of 200-400 kb and cover as a whole 3.2 Mb of DNA. This represents about 70% of human chromosomal band 11q24, which extends over approximately 4.4 Mb of DNA.

Hedgehog interacting protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis.

Clopidogrel is an oral antiplatelet pro-drug prescribed to 40million patients worldwide who are at risk for thrombotic events or receiving percutaneous coronary intervention (PCI). However about a fifth of patients treated with clopidogrel do not respond adequately to the drug. From a cohort of 105 patients on whom we had functional data on clopidogrel response, we used ultra-high throughput sequencing to assay mutations in CYP2C19 and ABCB1, the two genes genetically linked to respond. Testing for mutations in CYP2C19, as recommended by the FDA, only correctly predicted if a patient would respond to clopidogrel 52.4% of the time. Similarly, testing of the ABCB1 gene only correctly foretold response in 51 (48.6%) patients. These results are clinically relevant and suggest that until additional genetic factors are discovered that predict response more completely, functional assays are more appropriate for clinical use.