Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs

BACKGROUND: In bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes. RESULTS: In this work, we report that genomic distribution of transcription factors binding sites is biased towards IRs, and that this bias is conserved amongst bacterial species. We further take advantage of this observation to develop an algorithm that can efficiently identify promoter boxes by a distribution-dependent approach rather than a direct sequence comparison approach. This strategy, which can easily be combined with other methodologies, allowed the identification of promoter sequences in ten species and can be used with any annotated bacterial genome, with results that rival with current methodologies. Experimental validations of predicted promoters also support our approach. CONCLUSION: Considering that complete genomic sequences of over 1000 bacteria will soon be available and that little transcriptional information is available for most of them, our algorithm constitutes a promising tool for the prediction of promoter sequences. Importantly, our methodology could also be adapted to identify DNA sequences recognized by other regulatory proteins

Systems consequences of amplicon formation in human breast cancer

Chromosomal structural variations play an important role in determining the transcriptional landscape of human breast cancers. To assess the nature of these structural variations, we analyzed eight breast tumor samples with a focus on regions of gene amplification using mate-pair sequencing of long-insert genomic DNA with matched transcriptome profiling. We found that tandem duplications appear to be early events in tumor evolution, especially in the genesis of amplicons. In a detailed reconstruction of events on chromosome 17, we found large unpaired inversions and deletions connect a tandemly duplicated ERBB2 with neighboring 17q21.3 amplicons while simultaneously deleting the intervening BRCA1 tumor suppressor locus. This series of events appeared to be unusually common when examined in larger genomic data sets of breast cancers albeit using approaches with lesser resolution. Using siRNAs in breast cancer cell lines, we showed that the 17q21.3 amplicon harbored a significant number of weak oncogenes that appeared consistently coamplified in primary tumors. Down-regulation of BRCA1 expression augmented the cell proliferation in ERBB2-transfected human normal mammary epithelial cells. Coamplification of other functionally tested oncogenic elements in other breast tumors examined, such as RIPK2 and MYC on chromosome 8, also parallel these findings. Our analyses suggest that structural variations efficiently orchestrate the gain and loss of cancer gene cassettes that engage many oncogenic pathways simultaneously and that such oncogenic cassettes are favored during the evolution of a cancer.Singapore. Agency for Science, Technology and ResearchNational Science Foundation (U.S.) (East Asia and Pacific Summer Institutes (OISE-1108282)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data

<div><p>Genome-scale metabolic models (GEMs) are mathematically structured knowledge bases of metabolism that provide phenotypic predictions from genomic information. GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass objective function (BOF) that is designed to include key cellular biomass components such as the major macromolecules (DNA, RNA, proteins), lipids, coenzymes, inorganic ions and species-specific components. Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. BOFdat has a modular implementation that divides the BOF definition process into three independent modules defined here as steps: 1) the coefficients for major macromolecules are calculated, 2) coenzymes and inorganic ions are identified and their stoichiometric coefficients estimated, 3) the remaining species-specific metabolic biomass precursors are algorithmically extracted in an unbiased way from experimental data. We used BOFdat to reconstruct the BOF of the <i>Escherichia coli</i> model <i>i</i>ML1515, a gold standard in the field. The BOF generated by BOFdat resulted in the most concordant biomass composition, growth rate, and gene essentiality prediction accuracy when compared to other methods. Installation instructions for BOFdat are available in the documentation and the source code is available on GitHub (<a href="https://github.com/jclachance/BOFdat" target="_blank">https://github.com/jclachance/BOFdat</a>).</p></div

Recurrent Fusion Genes in Gastric Cancer: CLDN18-ARHGAP26 Induces Loss of Epithelial Integrity.

Genome rearrangements, a hallmark of cancer, can result in gene fusions with oncogenic properties. Using DNA paired-end-tag (DNA-PET) whole-genome sequencing, we analyzed 15 gastric cancers (GCs) from Southeast Asians. Rearrangements were enriched in open chromatin and shaped by chromatin structure. We identified seven rearrangement hot spots and 136 gene fusions. In three out of 100 GC cases, we found recurrent fusions between CLDN18, a tight junction gene, and ARHGAP26, a gene encoding a RHOA inhibitor. Epithelial cell lines expressing CLDN18-ARHGAP26 displayed a dramatic loss of epithelial phenotype and long protrusions indicative of epithelial-mesenchymal transition (EMT). Fusion-positive cell lines showed impaired barrier properties, reduced cell-cell and cell-extracellular matrix adhesion, retarded wound healing, and inhibition of RHOA. Gain of invasion was seen in cancer cell lines expressing the fusion. Thus, CLDN18-ARHGAP26 mediates epithelial disintegration, possibly leading to stomach H(+) leakage, and the fusion might contribute to invasiveness once a cell is transformed. Cell Rep 2015 Jul 14; 12(2):272-285

The Euchromatic and Heterochromatic Landscapes Are Shaped by Antagonizing Effects of Transcription on H2A.Z Deposition

A role for variant histone H2A.Z in gene expression is now well established but little is known about the mechanisms by which it operates. Using a combination of ChIP–chip, knockdown and expression profiling experiments, we show that upon gene induction, human H2A.Z associates with gene promoters and helps in recruiting the transcriptional machinery. Surprisingly, we also found that H2A.Z is randomly incorporated in the genome at low levels and that active transcription antagonizes this incorporation in transcribed regions. After cessation of transcription, random H2A.Z quickly reappears on genes, demonstrating that this incorporation utilizes an active mechanism. Within facultative heterochromatin, we observe a hyper accumulation of the variant histone, which might be due to the lack of transcription in these regions. These results show how chromatin structure and transcription can antagonize each other, therefore shaping chromatin and controlling gene expression

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth