Getting Down to Specifics

McClure, Colin D.; Southall, Tony D.

doi:10.1016/bs.adgen.2015.06.003

Cited by 12 publications

(4 citation statements)

References 240 publications

(353 reference statements)

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“…Imaging studies have been used to demonstrate gross changes to chromatin structure, for example changes to the distribution of heterochromatin have been observed in post-mitotic cells ( Francastel et al, 2000 ; Le Gros et al, 2016 ). Molecular studies investigating chromatin states in vivo during development have tended to utilise heterogeneous tissues due to the fact that profiling the epigenome of individual cell types frequently requires physical isolation of cells or nuclei, which can be laborious and prone to human error ( McClure and Southall, 2015 ). Therefore, there is a lack of information regarding cell-type-specific changes to chromatin states in in vivo models.…”

Section: Introductionmentioning

confidence: 99%

CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiation in vivo

Aughey

Estacio-Gómez

Thomson

et al. 2018

eLife

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During development eukaryotic gene expression is coordinated by dynamic changes in chromatin structure. Measurements of accessible chromatin are used extensively to identify genomic regulatory elements. Whilst chromatin landscapes of pluripotent stem cells are well characterised, chromatin accessibility changes in the development of somatic lineages are not well defined. Here we show that cell-specific chromatin accessibility data can be produced via ectopic expression of E. coli Dam methylase in vivo, without the requirement for cell-sorting (CATaDa). We have profiled chromatin accessibility in individual cell-types of Drosophila neural and midgut lineages. Functional cell-type-specific enhancers were identified, as well as novel motifs enriched at different stages of development. Finally, we show global changes in the accessibility of chromatin between stem-cells and their differentiated progeny. Our results demonstrate the dynamic nature of chromatin accessibility in somatic tissues during stem cell differentiation and provide a novel approach to understanding gene regulatory mechanisms underlying development.

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Section: Introductionmentioning

confidence: 99%

CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiation in vivo

Aughey

Estacio-Gómez

Thomson

et al. 2018

eLife

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“…Because the fully developed heart contributes less than 1% of the nuclei to the embryo, so far these approaches have been performed with earlier stages when the cardiogenic mesoderm makes up a larger fraction of the embryo and better signal-to-noise ratios can be obtained ( Table 1 ). In future experiments, enrichment of heart cells or nuclei prior to immunoprecipitation may circumvent this limitation (e.g., BiTS-ChIP) [ 62 , 63 ]. In addition, methods employing inducible GFP fusion proteins have recently been developed that allow tissue specific ChIP-seq even for factors that are expressed in several different tissues (CAST-ChIP [ 64 ]).…”

Section: Genome-wide Searches For Binding Sites and Target Genes Omentioning

confidence: 99%

Genome-Wide Approaches to Drosophila Heart Development

Frasch

2016

JCDD

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The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi) reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.

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“…The antibody specificity may be insufficient, or it could block successive interactions between TFs, making it difficult to observe indirect interactions. DamID is largely limited by its resolution as the GATC motifs are required, although it does not require the use of antibodies and therefore has advantages over ChIP protocols [17]. Thus, the currently known TF-gene associations are incomplete due to the limitations of experimental techniques.…”

Section: Introductionmentioning

confidence: 99%

Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm

Lim

Xie

2018

Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics

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Identifying the target genes of transcription factors (TFs) is one of the key factors to understand transcriptional regulation. However, our understanding of genome-wide TF targeting profile is limited due to the cost of large scale experiments and intrinsic complexity. Thus, computational prediction methods are useful to predict the unobserved associations. Here, we developed a new one-class collaborative filtering algorithm tREMAP that is based on regularized, weighted nonnegative matrix tri-factorization. The algorithm predicts unobserved target genes for TFs using known gene-TF associations and protein-protein interaction network. Our benchmark study shows that tREMAP significantly outperforms its counterpart REMAP, a bi-factorization-based algorithm, for transcription factor target gene prediction in all four performance metrics AUC, MAP, MPR, and HLU. When evaluated by independent data sets, the prediction accuracy is 37.8% on the top 495 predicted associations, an enrichment factor of 4.19 compared with the random guess. Furthermore, many of the predicted novel associations by tREMAP are supported by evidence from literature. Although we only use canonical TF-target gene interaction data in this study, tREMAP can be directly applied to tissue-specific data sets. tREMAP provides a framework to integrate multiple omics data for the further improvement of TF target gene prediction. Thus, tREMAP is a potentially useful tool in studying gene regulatory networks. The benchmark data set and the source code of tREMAP are freely available at https://github.com/hansaimlim/REMAP/tree/master/TriFacREMAP.

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Getting Down to Specifics

Cited by 12 publications

References 240 publications

CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiation in vivo

CATaDa reveals global remodelling of chromatin accessibility during stem cell differentiation in vivo

Genome-Wide Approaches to Drosophila Heart Development

Target Gene Prediction of Transcription Factor Using a New Neighborhood-regularized Tri-factorization One-class Collaborative Filtering Algorithm

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