Purifying Selection in Deeply Conserved Human Enhancers Is More Consistent than in Coding Sequences

(c) 2014 De Silva et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Notch Signaling Regulates Bile Duct Morphogenesis in Mice

BACKGROUND: Alagille syndrome is a developmental disorder caused predominantly by mutations in the Jagged1 (JAG1) gene, which encodes a ligand for Notch family receptors. A characteristic feature of Alagille syndrome is intrahepatic bile duct paucity. We described previously that mice doubly heterozygous for Jag1 and Notch2 mutations are an excellent model for Alagille syndrome. However, our previous study did not establish whether bile duct paucity in Jag1/Notch2 double heterozygous mice resulted from impaired differentiation of bile duct precursor cells, or from defects in bile duct morphogenesis. METHODOLOGY/PRINCIPAL FINDINGS: Here we characterize embryonic biliary tract formation in our previously described Jag1/Notch2 double heterozygous Alagille syndrome model, and describe another mouse model of bile duct paucity resulting from liver-specific deletion of the Notch2 gene. CONCLUSIONS/SIGNIFICANCE: Our data support a model in which bile duct paucity in Notch pathway loss of function mutant mice results from defects in bile duct morphogenesis rather than cell fate specification

ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis

<p>Abstract</p> <p>Background</p> <p>Chromatin immunoprecipitation (ChIP) followed by microarray hybridization (ChIP-chip) or high-throughput sequencing (ChIP-seq) allows genome-wide discovery of protein-DNA interactions such as transcription factor bindings and histone modifications. Previous reports only compared a small number of profiles, and little has been done to compare histone modification profiles generated by the two technologies or to assess the impact of input DNA libraries in ChIP-seq analysis. Here, we performed a systematic analysis of a modENCODE dataset consisting of 31 pairs of ChIP-chip/ChIP-seq profiles of the coactivator CBP, RNA polymerase II (RNA PolII), and six histone modifications across four developmental stages of <it>Drosophila melanogaster</it>.</p> <p>Results</p> <p>Both technologies produce highly reproducible profiles within each platform, ChIP-seq generally produces profiles with a better signal-to-noise ratio, and allows detection of more peaks and narrower peaks. The set of peaks identified by the two technologies can be significantly different, but the extent to which they differ varies depending on the factor and the analysis algorithm. Importantly, we found that there is a significant variation among multiple sequencing profiles of input DNA libraries and that this variation most likely arises from both differences in experimental condition and sequencing depth. We further show that using an inappropriate input DNA profile can impact the average signal profiles around genomic features and peak calling results, highlighting the importance of having high quality input DNA data for normalization in ChIP-seq analysis.</p> <p>Conclusions</p> <p>Our findings highlight the biases present in each of the platforms, show the variability that can arise from both technology and analysis methods, and emphasize the importance of obtaining high quality and deeply sequenced input DNA libraries for ChIP-seq analysis.</p

Genome-wide Analysis of Simultaneous GATA1/2, RUNX1, FLI1, and SCL Binding in Megakaryocytes Identifies Hematopoietic Regulators

SummaryHematopoietic differentiation critically depends on combinations of transcriptional regulators controlling the development of individual lineages. Here, we report the genome-wide binding sites for the five key hematopoietic transcription factors—GATA1, GATA2, RUNX1, FLI1, and TAL1/SCL—in primary human megakaryocytes. Statistical analysis of the 17,263 regions bound by at least one factor demonstrated that simultaneous binding by all five factors was the most enriched pattern and often occurred near known hematopoietic regulators. Eight genes not previously appreciated to function in hematopoiesis that were bound by all five factors were shown to be essential for thrombocyte and/or erythroid development in zebrafish. Moreover, one of these genes encoding the PDZK1IP1 protein shared transcriptional enhancer elements with the blood stem cell regulator TAL1/SCL. Multifactor ChIP-Seq analysis in primary human cells coupled with a high-throughput in vivo perturbation screen therefore offers a powerful strategy to identify essential regulators of complex mammalian differentiation processes

A genome-wide screen in human embryonic stem cells reveals novel sites of allele-specific histone modification associated with known disease loci

<p>Abstract</p> <p>Background</p> <p>Chromatin structure at a given site can differ between chromosome copies in a cell, and such imbalances in chromatin structure have been shown to be important in understanding the molecular mechanisms controlling several disease loci. Human genetic variation, DNA methylation, and disease have been intensely studied, uncovering many sites of allele-specific DNA methylation (ASM). However, little is known about the genome-wide occurrence of sites of allele-specific histone modification (ASHM) and their relationship to human disease. The aim of this study was to investigate the extent and characteristics of sites of ASHM in human embryonic stem cells (hESCs).</p> <p>Results</p> <p>Using a statistically rigorous protocol, we investigated the genomic distribution of ASHM in hESCs, and their relationship to sites of allele-specific expression (ASE) and DNA methylation. We found that, although they were rare, sites of ASHM were substantially enriched at loci displaying ASE. Many were also found at known imprinted regions, hence sites of ASHM are likely to be better markers of imprinted regions than sites of ASM. We also found that sites of ASHM and ASE in hESCs colocalize at risk loci for developmental syndromes mediated by deletions, providing insights into the etiology of these disorders.</p> <p>Conclusion</p> <p>These results demonstrate the potential importance of ASHM patterns in the interpretation of disease loci, and the protocol described provides a basis for similar studies of ASHM in other cell types to further our understanding of human disease susceptibility.</p

Long-range DNA looping and gene expression analyses identify DEXI as an autoimmune disease candidate gene

The chromosome 16p13 region has been associated with several autoimmune diseases, including type 1 diabetes (T1D) and multiple sclerosis (MS). CLEC16A has been reported as the most likely candidate gene in the region, since it contains the most disease-associated single-nucleotide polymorphisms (SNPs), as well as an imunoreceptor tyrosine-based activation motif. However, here we report that intron 19 of CLEC16A, containing the most autoimmune disease-associated SNPs, appears to behave as a regulatory sequence, affecting the expression of a neighbouring gene, DEXI. The CLEC16A alleles that are protective from T1D and MS are associated with increased expression of DEXI, and no other genes in the region, in two independent monocyte gene expression data sets. Critically, using chromosome conformation capture (3C), we identified physical proximity between the DEXI promoter region and intron 19 of CLEC16A, separated by a loop of >150 kb. In reciprocal experiments, a 20 kb fragment of intron 19 of CLEC16A, containing SNPs associated with T1D and MS, as well as with DEXI expression, interacted with the promotor region of DEXI but not with candidate DNA fragments containing other potential causal genes in the region, including CLEC16A. Intron 19 of CLEC16A is highly enriched for transcription-factor-binding events and markers associated with enhancer activity. Taken together, these data indicate that although the causal variants in the 16p13 region lie within CLEC16A, DEXI is an unappreciated autoimmune disease candidate gene, and illustrate the power of the 3C approach in progressing from genome-wide association studies results to candidate causal genes

Macrophage-derived Wnt opposes Notch signaling to specify hepatic progenitor cell fate in chronic liver disease

During chronic injury a population of bipotent hepatic progenitor cells (HPCs) become activated to regenerate both cholangiocytes and hepatocytes. Here we show in human diseased liver and mouse models of the ductular reaction that Notch and Wnt signaling direct specification of HPCs via their interactions with activated myofibroblasts or macrophages. In particular, we found that during biliary regeneration, expression of Jagged 1 (a Notch ligand) by myofibroblasts promoted Notch signaling in HPCs and thus their biliary specification to cholangiocytes. Alternatively, during hepatocyte regeneration, macrophage engulfment of hepatocyte debris induced Wnt3a expression. This resulted in canonical Wnt signaling in nearby HPCs, thus maintaining expression of Numb (a cell fate determinant) within these cells and the promotion of their specification to hepatocytes. By these two pathways adult parenchymal regeneration during chronic liver injury is promoted

Expanding the clinical spectrum of hereditary fibrosing poikiloderma with tendon contractures, myopathy and pulmonary fibrosis due to <i>FAM111B </i>mutations

BACKGROUND: Hereditary Fibrosing Poikiloderma (HFP) with tendon contractures, myopathy and pulmonary fibrosis (POIKTMP [MIM 615704]) is a very recently described entity of syndromic inherited poikiloderma. Previously by using whole exome sequencing in five families, we identified the causative gene, FAM111B (NM_198947.3), the function of which is still unknown. Our objective in this study was to better define the specific features of POIKTMP through a larger series of patients. METHODS: Clinical and molecular data of two families and eight independent sporadic cases, including six new cases, were collected. RESULTS: Key features consist of: (i) early-onset poikiloderma, hypotrichosis and hypohidrosis; (ii) multiple contractures, in particular triceps surae muscle contractures; (iii) diffuse progressive muscular weakness; (iv) pulmonary fibrosis in adulthood and (v) other features including exocrine pancreatic insufficiency, liver impairment and growth retardation. Muscle magnetic resonance imaging was informative and showed muscle atrophy and fatty infiltration. Histological examination of skeletal muscle revealed extensive fibroadipose tissue infiltration. Microscopy of the skin showed a scleroderma-like aspect with fibrosis and alterations of the elastic network. FAM111B gene analysis identified five different missense variants (two recurrent mutations were found respectively in three and four independent families). All the mutations were predicted to localize in the trypsin-like cysteine/serine peptidase domain of the protein. We suggest gain-of-function or dominant-negative mutations resulting in FAM111B enzymatic activity changes. CONCLUSIONS: HFP with tendon contractures, myopathy and pulmonary fibrosis, is a multisystemic disorder due to autosomal dominant FAM111B mutations. Future functional studies will help in understanding the specific pathological process of this fibrosing disorder

Identification of critical paralog groups with indispensable roles in the regulation of signaling flow

Extensive cross-talk between signaling pathways is required to integrate the myriad of extracellular signal combinations at the cellular level. Gene duplication events may lead to the emergence of novel functions, leaving groups of similar genes - termed paralogs - in the genome. To distinguish critical paralog groups (CPGs) from other paralogs in human signaling networks, we developed a signaling network-based method using cross-talk annotation and tissue-specific signaling flow analysis. 75 CPGs were found with higher degree, betweenness centrality, closeness, and ‘bowtieness’ when compared to other paralogs or other proteins in the signaling network. CPGs had higher diversity in all these measures, with more varied biological functions and more specific post-transcriptional regulation than non-critical paralog groups (non-CPG). Using TGF-beta, Notch and MAPK pathways as examples, SMAD2/3, NOTCH1/2/3 and MEK3/6-p38 CPGs were found to regulate the signaling flow of their respective pathways. Additionally, CPGs showed a higher mutation rate in both inherited diseases and cancer, and were enriched in drug targets. In conclusion, the results revealed two distinct types of paralog groups in the signaling network: CPGs and non-CPGs. Thus highlighting the importance of CPGs as compared to non-CPGs in drug discovery and disease pathogenesis