scholarly journals ExtRamp Online: Enabling ramp sequence calculations via an intuitive web interface.

Author(s):  
Justin B. Miller ◽  
Matthew W. Hodgman ◽  
Kyle N. Miller ◽  
Taylor E. Meurs ◽  
Mark T. W. Ebbert ◽  
...  

Abstract Motivation: Ramp sequences are an understudied evolutionarily-conserved mechanism for regulating protein translational efficiency. Slowly-translated codons concentrated at the 5' end of genes form ramp sequences that counterintuitively increase overall translational efficiency by evenly spacing ribosomes at initiation, which limits downstream ribosomal collisions. We previously developed ExtRamp, which is the only algorithm to identify translational ramp sequences in single genes. ExtRamp currently lacks a web interface to facilitate wider adoption and application for non-programmers. Additionally, ExtRamp currently identifies ramp sequences using only species-wide codon efficiencies that may lack the specificity of tissue and cell type-specific codon usage biases.Results: We present an online interface for ExtRamp to facilitate wider adoption and application for non-programmers, along with a significant improvement to the underlying algorithm to calculate tissue and cell type-specific ramp sequences (https://ramps.byu.edu/ExtRampOnline). ExtRamp Online contains all options available in the original ExtRamp algorithm with additional pre-set default values to enable researchers to calculate human tissue-specific or genome-wide ramp sequences on any web browser. Human tissue and cell type-specific codon usage biases have been precomputed and can be applied with a simple drop-down menu. Hover-over hints provide users with detailed information on all available options, which will help facilitate future creative analyses using ramp sequences. Availability: ExtRamp Online is publicly available at https://ramps.byu.edu/ExtRampOnline. All associated scripts are publicly available at https://github.com/ridgelab/ExtRampOnline.

2016 ◽  
Author(s):  
Boris Simovski ◽  
Daniel Vodak ◽  
Sveinung Gundersen ◽  
Diana Domanska ◽  
Abdulrahman Azab ◽  
...  

AbstractGenome-wide, cell-type-specific profiles are being systematically generated for numerous genomic and epigenomic features. There is, however, no universally applicable analytical methodology for such data. We present GSuite HyperBrowser, the first comprehensive solution for integrative analysis of dataset collections across the genome and epigenome. The GSuite HyperBrowser is an open-source system for streamlined acquisition and customizable statistical analysis of large collections of genome-wide datasets. The system is based on new computational and statistical methodologies that permit comparative and confirmatory analyses across multiple disparate data sources. Expert guidance and reproducibility are facilitated via a Galaxy-based web-interface. The software is available athttps://hyperbrowser.uio.no/gsuite


2015 ◽  
Author(s):  
Hilary Kiyo Finucane ◽  
Brendan Bulik-Sullivan ◽  
Alexander Gusev ◽  
Gosia Trynka ◽  
Yakir Reshef ◽  
...  

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.


2019 ◽  
Author(s):  
Hyeon-Jin Kim ◽  
Galip Gürkan Yardımcı ◽  
Giancarlo Bonora ◽  
Vijay Ramani ◽  
Jie Liu ◽  
...  

AbstractSingle-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate twelve different single-cell combinatorial indexed Hi-C (sciHi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 25,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sciHi-C data in the form of “chromatin topics.” We further show enrichment of particular compartment structures associated with locus pairs in these topics.


2019 ◽  
Author(s):  
Igor Mačinković ◽  
Ina Theofel ◽  
Tim Hundertmark ◽  
Kristina Kovač ◽  
Stephan Awe ◽  
...  

Abstract CoREST has been identified as a subunit of several protein complexes that generate transcriptionally repressive chromatin structures during development. However, a comprehensive analysis of the CoREST interactome has not been carried out. We use proteomic approaches to define the interactomes of two dCoREST isoforms, dCoREST-L and dCoREST-M, in Drosophila. We identify three distinct histone deacetylase complexes built around a common dCoREST/dRPD3 core: A dLSD1/dCoREST complex, the LINT complex and a dG9a/dCoREST complex. The latter two complexes can incorporate both dCoREST isoforms. By contrast, the dLSD1/dCoREST complex exclusively assembles with the dCoREST-L isoform. Genome-wide studies show that the three dCoREST complexes associate with chromatin predominantly at promoters. Transcriptome analyses in S2 cells and testes reveal that different cell lineages utilize distinct dCoREST complexes to maintain cell-type-specific gene expression programmes: In macrophage-like S2 cells, LINT represses germ line-related genes whereas other dCoREST complexes are largely dispensable. By contrast, in testes, the dLSD1/dCoREST complex prevents transcription of germ line-inappropriate genes and is essential for spermatogenesis and fertility, whereas depletion of other dCoREST complexes has no effect. Our study uncovers three distinct dCoREST complexes that function in a lineage-restricted fashion to repress specific sets of genes thereby maintaining cell-type-specific gene expression programmes.


Author(s):  
Xiangyu Luo ◽  
Joel Schwartz ◽  
Andrea Baccarelli ◽  
Zhonghua Liu

Abstract Epigenome-wide mediation analysis aims to identify DNA methylation CpG sites that mediate the causal effects of genetic/environmental exposures on health outcomes. However, DNA methylations in the peripheral blood tissues are usually measured at the bulk level based on a heterogeneous population of white blood cells. Using the bulk level DNA methylation data in mediation analysis might cause confounding bias and reduce study power. Therefore, it is crucial to get fine-grained results by detecting mediation CpG sites in a cell-type-specific way. However, there is a lack of methods and software to achieve this goal. We propose a novel method (Mediation In a Cell-type-Specific fashion, MICS) to identify cell-type-specific mediation effects in genome-wide epigenetic studies using only the bulk-level DNA methylation data. MICS follows the standard mediation analysis paradigm and consists of three key steps. In step1, we assess the exposure-mediator association for each cell type; in step 2, we assess the mediator-outcome association for each cell type; in step 3, we combine the cell-type-specific exposure-mediator and mediator-outcome associations using a multiple testing procedure named MultiMed [Sampson JN, Boca SM, Moore SC, et al. FWER and FDR control when testing multiple mediators. Bioinformatics 2018;34:2418–24] to identify significant CpGs with cell-type-specific mediation effects. We conduct simulation studies to demonstrate that our method has correct FDR control. We also apply the MICS procedure to the Normative Aging Study and identify nine DNA methylation CpG sites in the lymphocytes that might mediate the effect of cigarette smoking on the lung function.


PLoS Genetics ◽  
2013 ◽  
Vol 9 (10) ◽  
pp. e1003756 ◽  
Author(s):  
Laure Saujet ◽  
Fátima C. Pereira ◽  
Monica Serrano ◽  
Olga Soutourina ◽  
Marc Monot ◽  
...  

2013 ◽  
Vol 13 (2) ◽  
pp. 397-406 ◽  
Author(s):  
Linn Fagerberg ◽  
Björn M. Hallström ◽  
Per Oksvold ◽  
Caroline Kampf ◽  
Dijana Djureinovic ◽  
...  

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 211-211
Author(s):  
Amber Hogart ◽  
Jens Lichtenberg ◽  
Subramanian Ajay ◽  
Elliott Margulies ◽  
David M. Bodine

Abstract Abstract 211 The hematopoietic system is ideal for the study of epigenetic changes in primary cells because hematopoietic cells representing distinct stages of hematopoiesis can be enriched and isolated by differences in surface marker expression. DNA methylation is an essential epigenetic mark that is required for normal development. Conditional knockout of the DNA methyltransferase enzymes in the mouse hematopoietic compartment have revealed that methylation is critical for long-term renewal and lineage differentiation of hematopoietic stem cells (Broske et al 2009, Trowbridge el al 2009). To better understand the role of DNA methylation in self-renewal and differentiation of hematopoietic cells, we characterized genome-wide DNA methylation in primary cells representing three distinct stages of hematopoiesis. We isolated mouse hematopoietic stem cells (HSC; Lin- Sca-1+ c-kit+), common myeloid progenitor cells (CMP; Lin- Sca-1- c-kit+), and erythroblasts (ERY; CD71+ Ter119+). Methyl Binding Domain Protein 2 (MBD2) is an endogenous reader of DNA methylation that recognizes DNA with a high concentration of methylated CpG residues. Recombinant MBD2 enrichment of DNA followed by massively-parallel sequencing was used to map and compare genome-wide DNA methylation patterns in HSC, CMP and ERY. Two biological replicates were sequenced for each cell type with total read counts ranging from 32,309,435–46,763,977. Model-based analysis of ChIP Seq (MACS) with a significance cutoff of p<10−5 was used to determine statistically significant peaks of methylation in each replicate. Globally, the number of methylation peaks was highest in HSC (85,797peaks), lower in CMP (50,638 peaks), and lowest in ERY (27,839 peaks). Comparison of the peaks in HSC, CMP and ERY revealed that only 2% of the peaks in CMP or ERY are absent in HSC indicating that the vast majority of methylation in HSC is lost during differentiation. Comparison of methylation with genomic features revealed that CpG islands associated with promoters are hypomethylated, while many non-promoter CpG islands are methylated. Furthermore, methylation of non-promoter associated CpG islands occurs infrequently in cell-type specific peaks but is more abundant in common methylation peaks. When the DNA methylation patterns were compared to mRNA expression, we found that as expected, proximal promoter sequences of expressed genes were hypomethylated in all three cell types, while methylation in the gene body positively correlated with gene expression in HSC and CMP. Utilizing de novo motif discovery we found a subset of transcription factor consensus binding motifs that were overrepresented in methylated sequences. Motifs for several ETS transcription factors, including GABPalpha and ELF1 were found to be overrepresented in cell-type specific as well as common methylated regions. Other transcription factor consensus sites, such as the NFAT factors involved in T-cell activation, were specifically overrepresented in the methylated promoter regions of CMP and ERY. Comparison of our methylation data with the occupancy of hematopoietic transcription factors in the HPC7 cell line, which is similar to CMP (Wilson et al 2010), revealed a significant anti-correlation between DNA methylation and the binding of Fli1, Lmo2, Lyl1, Runx1, and Scl. Our genome-wide survey provides new insights into the role of DNA methylation in hematopoiesis. Firstly, the methylation of CpG islands is associated with the most primitive hematopoietic cells and is unlikely to drive hematopoietic differentiation. We feel that the elevated genome-wide DNA methylation in HSC compared to CMP and ERY, combined with the positive association between gene body methylation and gene expression demonstrates that DNA methylation is a mark of cellular plasticity in HSC. Finally, the finding that transcription factor binding sites are over represented in the methylated sequences of the genome leads us to conclude that DNA methylation modulates key hematopoietic transcription factor programs that regulate hematopoiesis. Disclosures: No relevant conflicts of interest to declare.


2011 ◽  
Vol 22 (1) ◽  
pp. 9-24 ◽  
Author(s):  
B.-K. Lee ◽  
A. A. Bhinge ◽  
A. Battenhouse ◽  
R. M. McDaniell ◽  
Z. Liu ◽  
...  

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