Defining the fine structure of promoter activity on a genome-wide scale with CISSECTOR.

Classic promoter mutagenesis strategies can be used to study how proximal promoter regions regulate the expression of particular genes of interest. This is a laborious process, in which the smallest sub-region of the promoter still capable of recapitulating expression in an ectopic setting is first identified, followed by targeted mutation of putative transcription factor binding sites. Massively parallel reporter assays such as survey of regulatory elements (SuRE) provide an alternative way to study millions of promoter fragments in parallel. Here we show how a generalized linear model (GLM) can be used to transform genome-scale SuRE data into a high-resolution genomic track that quantifies the contribution of local sequence to promoter activity. This coefficient track helps identify regulatory elements and can be used to predict promoter activity of any sub-region in the genome. It thus allows in silico dissection of any promoter in the human genome to be performed. We developed a web application, available at cissector.nki.nl, that lets researchers easily perform this analysis as a starting point for their research into any promoter of interest.

High-throughput identification of human SNPs affecting regulatory element activity.

Most of the millions of SNPs in the human genome are non-coding, and many overlap with putative regulatory elements. Genome-wide association studies (GWAS) have linked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resolution to identify the causal SNPs. Functional screens based on reporter assays have previously been of insufficient throughput to test the vast space of SNPs for possible effects on regulatory element activity. Here we leveraged the throughput and resolution of the survey of regulatory elements (SuRE) reporter technology to survey the effect of 5.9 million SNPs, including 57% of the known common SNPs, on enhancer and promoter activity. We identified more than 30,000 SNPs that alter the activity of putative regulatory elements, partially in a cell-type-specific manner. Integration of this dataset with GWAS results may help to pinpoint SNPs that underlie human traits.

SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site.

The DNA-binding interfaces of the androgen (AR) and glucocorticoid (GR) receptors are virtually identical, yet these transcription factors share only about a third of their genomic binding sites and regulate similarly distinct sets of target genes. To address this paradox, we determined the intrinsic specificities of the AR and GR DNA-binding domains using a refined version of SELEX-seq. We developed an algorithm, SelexGLM, that quantifies binding specificity over a large (31-bp) binding site by iteratively fitting a feature-based generalized linear model to SELEX probe counts. This analysis revealed that the DNA-binding preferences of AR and GR homodimers differ significantly, both within and outside the 15-bp core binding site. The relative preference between the two factors can be tuned over a wide range by changing the DNA sequence, with AR more sensitive to sequence changes than GR. The specificity of AR extends to the regions flanking the core 15-bp site, where isothermal calorimetry measurements reveal that affinity is augmented by enthalpy-driven readout of poly(A) sequences associated with narrowed minor groove width. We conclude that the increased specificity of AR is correlated with more enthalpy-driven binding than GR. The binding models help explain differences in AR and GR genomic binding and provide a biophysical rationale for how promiscuous binding by GR allows functional substitution for AR in some castration-resistant prostate cancers.

Genome-wide mapping of autonomous promoter activity in human cells.

Previous methods to systematically characterize sequence-intrinsic activity of promoters have been limited by relatively low throughput and the length of the sequences that could be tested. Here we present 'survey of regulatory elements' (SuRE), a method that assays more than 108 DNA fragments, each 0.2-2 kb in size, for their ability to drive transcription autonomously. In SuRE, a plasmid library of random genomic fragments upstream of a 20-bp barcode is constructed, and decoded by paired-end sequencing. This library is used to transfect cells, and barcodes in transcribed RNA are quantified by high-throughput sequencing. When applied to the human genome, we achieve 55-fold genome coverage, allowing us to map autonomous promoter activity genome-wide in K562 cells. By computational modeling we delineate subregions within promoters that are relevant for their activity. We show that antisense promoter transcription is generally dependent on the sense core promoter sequences, and that most enhancers and several families of repetitive elements act as autonomous transcription initiation sites.

Inhibition of WISE preserves renal allograft function.

Wnt-modulator in surface ectoderm (WISE) is a secreted modulator of Wnt signaling expressed in the adult kidney. Activation of Wnt signaling has been observed in renal transplants developing interstitial fibrosis and tubular atrophy; however, whether WISE contributes to chronic changes is not well understood. Here, we found moderate to high expression of WISE mRNA in a rat model of renal transplantation and in kidneys from normal rats. Treatment with a neutralizing antibody against WISE improved proteinuria and graft function, which correlated with higher levels of ß-catenin protein in kidney allografts. In addition, treatment with the anti-WISE antibody reduced infiltration of CD68(+) macrophages and CD8(+) T cells, attenuated glomerular and interstitial injury, and decreased biomarkers of renal injury. This treatment reduced expression of genes involved in immune responses and in fibrogenic pathways. In summary, WISE contributes to renal dysfunction by promoting tubular atrophy and interstitial fibrosis.

Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers.

A vast majority of pharmacological compounds and their metabolites are excreted via the urine, and within the complex structure of the kidney,the proximal tubules are a main target site of nephrotoxic compounds. We used the model nephrotoxicants mercuric chloride, 2-bromoethylamine hydrobromide, hexachlorobutadiene, mitomycin, amphotericin, and puromycin to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. Male Sprague-Dawley rats were dosed via intraperitoneal injection once daily for mercuric chloride and amphotericin (up to 7 doses), while a single dose was given for all other compounds. Animals were exposed to 2 different doses of these compounds and kidney tissues were collected on day 1, 3, and 7 postdosing. Gene expression profiles were generated from kidney RNA using 17K rat cDNA dual dye microarray and analyzed in conjunction with histopathology. Analysis of gene expression profiles showed that the profiles clustered based on similarities in the severity and type of pathology of individual animals. Further, the expression changes were indicative of tubular toxicity showing hallmarks of tubular degeneration/regeneration and necrosis. Use of gene expression data in predicting the type of nephrotoxicity was then tested with a support vector machine (SVM)-based approach. A SVM prediction module was trained using 120 profiles of total profiles divided into four classes based on the severity of pathology and clustering. Although mitomycin C and amphotericin B treatments did not cause toxicity, their expression profiles were included in the SVM prediction module to increase the sample size. Using this classifier, the SVM predicted the type of pathology of 28 test profiles with 100% selectivity and 82% sensitivity. These data indicate that valid predictions could be made based on gene expression changes from a small set of expression profiles. A set of potential biomarkers showing a time- and dose-response with respect to the progression of proximal tubular toxicity were identified. These include several transporters (Slc21a2, Slc15, Slc34a2), Kim 1, IGFbp-1, osteopontin, alpha-fibrinogen, and Gstalpha.