A genome-wide screen for genetic variants that modify the recruitment of REST to its target genes.

Increasing numbers of human diseases are being linked to genetic variants, but our understanding of the mechanistic links leading from DNA sequence to disease phenotype is limited. The majority of disease-causing nucleotide variants fall within the non-protein-coding portion of the genome, making it likely that they act by altering gene regulatory sequences. We hypothesised that SNPs within the binding sites of the transcriptional repressor REST alter the degree of repression of target genes. Given that changes in the effective concentration of REST contribute to several pathologies-various cancers, Huntington's disease, cardiac hypertrophy, vascular smooth muscle proliferation-these SNPs should alter disease-susceptibility in carriers. We devised a strategy to identify SNPs that affect the recruitment of REST to target genes through the alteration of its DNA recognition element, the RE1. A multi-step screen combining genetic, genomic, and experimental filters yielded 56 polymorphic RE1 sequences with robust and statistically significant differences of affinity between alleles. These SNPs have a considerable effect on the the functional recruitment of REST to DNA in a range of in vitro, reporter gene, and in vivo analyses. Furthermore, we observe allele-specific biases in deeply sequenced chromatin immunoprecipitation data, consistent with predicted differenes in RE1 affinity. Amongst the targets of polymorphic RE1 elements are important disease genes including NPPA, PTPRT, and CDH4. Thus, considerable genetic variation exists in the DNA motifs that connect gene regulatory networks. Recently available ChIP-seq data allow the annotation of human genetic polymorphisms with regulatory information to generate prior hypotheses about their disease-causing mechanism.

Differentiation driven changes in the dynamic organization of Basal transcription initiation.

Studies based on cell-free systems and on in vitro-cultured living cells support the concept that many cellular processes, such as transcription initiation, are highly dynamic: individual proteins stochastically bind to their substrates and disassemble after reaction completion. This dynamic nature allows quick adaptation of transcription to changing conditions. However, it is unknown to what extent this dynamic transcription organization holds for postmitotic cells embedded in mammalian tissue. To allow analysis of transcription initiation dynamics directly into living mammalian tissues, we created a knock-in mouse model expressing fluorescently tagged TFIIH. Surprisingly and in contrast to what has been observed in cultured and proliferating cells, postmitotic murine cells embedded in their tissue exhibit a strong and long-lasting transcription-dependent immobilization of TFIIH. This immobilization is both differentiation driven and development dependent. Furthermore, although very statically bound, TFIIH can be remobilized to respond to new transcriptional needs. This divergent spatiotemporal transcriptional organization in different cells of the soma revisits the generally accepted highly dynamic concept of the kinetic framework of transcription and shows how basic processes, such as transcription, can be organized in a fundamentally different fashion in intact organisms as previously deduced from in vitro studies.

GATA-1 is essential in EGF-mediated induction of nucleotide excision repair activity and ERCC1 expression through ERK2 in human hepatoma cells.

The nucleotide excision repair (NER) pathway and its leading gene excision-repair cross-complementary 1 (ERCC1) have been shown to be up-regulated in hepatocellular carcinomas even in the absence of treatment with chemotherapeutics. The aim of this study was to determine the mechanism involved in NER regulation during the liver cell growth observed in hepatocellular carcinoma. Both NER activity and ERCC1 expression were increased after exposure to the epidermal growth factor (EGF) in cultured normal and tumoral human hepatocytes. These increases correlated with the activation of the kinase signaling pathway mitogen-activated protein/extracellular signal-regulated kinase (ERK) kinase (MEK)/ERK that is known to be a key regulator in the G(1) phase of the hepatocyte cell cycle. Moreover, EGF-mediated activation of ERCC1 was specifically inhibited by either the addition of U0126, a MEK/ERK inhibitor or small interfering RNA-mediated knockdown of ERK2. Basal expression of ERCC1 was decreased in the presence of the phosphoinositide-3-kinase (PI3K) inhibitor and small hairpin RNA (shRNA) against the PI3K pathway kinase FKBP12-rapamycin-associated protein or mammalian target of rapamycin. Transient transfection of human hepatocytes with constructs containing different sizes of the 5'-flanking region of the ERCC1 gene upstream of the luciferase reporter gene showed an increase in luciferase activity in EGF-treated cells, which correlated with the presence of the nuclear transcription factor GATA-1 recognition sequence. The recruitment of GATA-1 was confirmed by chromatin immunoprecipitation assay. In conclusion, these results represent the first demonstration of an up-regulation of NER and ERCC1 in EGF-stimulated proliferating hepatocytes. The transcription factor GATA-1 plays an essential role in the induction of ERCC1 through the mitogen-activated protein kinase (MAPK) pathway, whereas the PI3K signaling pathway contributes to ERCC1 basal expression.

Comprehensive characterization of complex structural variations in cancer by directly comparing genome sequence reads.

The development of high-throughput sequencing technologies has advanced our understanding of cancer. However, characterizing somatic structural variants in tumor genomes is still challenging because current strategies depend on the initial alignment of reads to a reference genome. Here, we describe SMUFIN (somatic mutation finder), a single program that directly compares sequence reads from normal and tumor genomes to accurately identify and characterize a range of somatic sequence variation, from single-nucleotide variants (SNV) to large structural variants at base pair resolution. Performance tests on modeled tumor genomes showed average sensitivity of 92% and 74% for SNVs and structural variants, with specificities of 95% and 91%, respectively. Analyses of aggressive forms of solid and hematological tumors revealed that SMUFIN identifies breakpoints associated with chromothripsis and chromoplexy with high specificity. SMUFIN provides an integrated solution for the accurate, fast and comprehensive characterization of somatic sequence variation in cancer.