Dynamic expression of groucho-related genes Grg1 and Grg3 in foregut endoderm and antagonism of differentiation

El pdf del artículo es el manuscrito de autor.While much is known about Groucho corepressors in Drosophila development, less is known about Grg homologs in mammalian embryogenesis. The transcription factors FoxA1 and FoxA2 are redundantly necessary for liver-inductive competence of the endoderm, and recently we found that FoxA factors bind Grg3, recruit the corepressor to FoxA target genes, and cause transcriptional repression, when Grg3 is ectopically expressed in adult liver cell lines that express little or no endogenous Grg. Unexpectedly, we now find that Grg1 and Grg3 mRNAs are co-expressed with FoxA factors in the foregut endoderm, prior to liver differentiation, though only Grg3 protein is expressed there. Grg3 mRNA and protein are extinguished at the onset of liver differentiation. Lentiviral delivery of Grg3 to explants of foregut endoderm suppresses liver gene induction. We suggest that Grg expression in the endoderm helps suppress the liver program and find that endodermal competence involves a balance between activators and corepressors.The research was supported by a grant from the Dirección General de Investigación SAF-2007-60614 (MICINN) and Salvador de Madariaga Program (MEC) to P.S., a FPI predoctoral fellowship (MICINN) to P.R., an NIH CA-009035-34 postdoctoral fellowship to D.E.M., and NIH grant R37GM36477 toK.S.Z.Peer Reviewe

Predator Mimicry: Metalmark Moths Mimic Their Jumping Spider Predators

Cases of mimicry provide many of the nature's most convincing examples of natural selection. Here we report evidence for a case of predator mimicry in which metalmark moths in the genus Brenthia mimic jumping spiders, one of their predators. In controlled trials, Brenthia had higher survival rates than other similarly sized moths in the presence of jumping spiders and jumping spiders responded to Brenthia with territorial displays, indicating that Brenthia were sometimes mistaken for jumping spiders, and not recognized as prey. Our experimental results and a review of wing patterns of other insects indicate that jumping spider mimicry is more widespread than heretofore appreciated, and that jumping spiders are probably an important selective pressure shaping the evolution of diurnal insects that perch on vegetation

An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding

Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.National Science Foundation (U.S.) (Graduate Research Fellowship under Grant 0645960)National Institutes of Health (U.S.) (grant P01 NS055923)Pennsylvania State University. Center for Eukaryotic Gene Regulatio

Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape

We describe protein interaction quantitation (PIQ), a computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning techniques, PIQ identified binding sites for >700 TFs from one DNase I hypersensitivity analysis followed by sequencing (DNase-seq) experiment with accuracy comparable to that of chromatin immunoprecipitation followed by sequencing (ChIP-seq). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into prepancreatic and intestinal endoderm. We identified 120 and experimentally validated eight 'pioneer' TF families that dynamically open chromatin. Four pioneer TF families only opened chromatin in one direction from their motifs. Furthermore, we identified 'settler' TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and nondirectional pioneer activity shapes the chromatin landscape for population by settler TFs.National Institutes of Health (U.S.) (Common Fund 5UL1DE019581)National Institutes of Health (U.S.) (Common Fund RL1DE019021)National Institutes of Health (U.S.) (Common Fund 5TL1EB008540)National Institutes of Health (U.S.) (Grant 1U01HG007037)National Institutes of Health (U.S.) (Grant 5P01NS055923

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease