Mango: a bias-correcting ChIA-PET analysis pipeline

Phanstiel, Douglas H.; Boyle, Alan P.; Heidari, Nastaran; Snyder, M

doi:10.1093/bioinformatics/btv336

Cited by 131 publications

(144 citation statements)

References 24 publications

Supporting

Mentioning

142

Contrasting

Unclassified

Order By: Relevance

“…Moreover, these data suggest an interaction between ZNF143 and specific CTCF sites, consistent with previous observations of functional interactions between these two DNA binding proteins, which affect the threedimensional structure of such chromatin loops by linking CTCF with distal regulatory elements, facilitating specific gene regulation. [19][20][21] Here, ZNF143 binds to the PMM2 promoter, as confirmed by our EMSA data (Figure 4). By simultaneously binding CTCF and the PMM2 promoter, ZNF143 could establish a functional chromatin loop enabling interaction between the promoter and a number of regulatory binding sites.…”

Section: Promoter Mutation and Chromatin Loopssupporting

confidence: 81%

Polycystic Kidney Disease with Hyperinsulinemic Hypoglycemia Caused by a Promoter Mutation in Phosphomannomutase 2

Cabezas

Flanagan

Stanescu

et al. 2017

JASN

105

View full text Add to dashboard Cite

General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. We propose that the promoter mutation alters tissue-specific chromatin loop formation with consequent organ-specific deficiency of PMM2 leading to the restricted phenotype of HIPKD. Our findings extend the spectrum of genetic 5 causes for both HI and PKD and provide insights into gene regulation and PMM2 pleiotropy.6

show abstract

Section: Promoter Mutation and Chromatin Loopssupporting

confidence: 81%

Polycystic Kidney Disease with Hyperinsulinemic Hypoglycemia Caused by a Promoter Mutation in Phosphomannomutase 2

Cabezas

Flanagan

Stanescu

et al. 2017

JASN

105

View full text Add to dashboard Cite

show abstract

“…Пакет Mango (https://github.com/dphansti/mango) оценивает статистическую достоверность оценок хромосомных контактов [28], для анализа экспериментов ChIA-PET.…”

Section: компьютерные инструменты анализа трёхмерной организации геноunclassified

Computer methods of analysis of chromosome contacts in the cell nucleus based on sequencing technology data

et al. 2017

View full text Add to dashboard Cite

The study spatial chromosome structure and chromosome folding in the interphase cell nucleus is an important challenge of world science. Detection of eukaryotic genome regions that physically interact with each other could be done by modern sequencing technologies. A basic method of chromosome folding by total sequencing of contacting DNA fragments is HI-C. Long-range chromosomal interactions play an important role in gene transcription and regulation. The study of chromosome interactions, 3D (three-dimensional) genome structure and its effect on gene transcription allows revealing fundamental biological processes from a viewpoint of structural regulation and are important for cancer research. The technique of chromatin immunoprecipitation and subsequent sequencing (ChIP-seq) make possible to determine binding sites of transcription factors that regulate expression of eukaryotic genes; genome transcription factors binding maps have been. The ChIA-PET technology allows exploring not only target protein binding sites, but also pairs of such sites on proximally located and interacting with each other chromosomes co-located in three-dimensional space of the cell nucleus. Here we discuss the principles of the construction of genomic maps and matrices of chromosome contacts according to ChIA-PET and Hi-C data that capture the chromosome conformation and overview existing software for 3D genome analysis including in house programs of gene location analysis in topological domains.

show abstract

“…PET interactions were identified and classified following the approach in Li et al (2010), with modifications described by Tang et al (2015), using a PET cutoff of 4-PET clusters with counts <4 are considered not significant, and these weak interactions are grouped with PET singletons. Although we prefer this analysis method, several methods are available for calling PET interactions (Paulsen et al 2014;He et al 2015;Phanstiel et al 2015), and the output of any of these methods is suitable as input to 3D-GNOME.…”

Section: Chia-pet Datamentioning

confidence: 99%

An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization

et al. 2016

View full text Add to dashboard Cite

ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures.

show abstract

Mango: a bias-correcting ChIA-PET analysis pipeline

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 131 publications

References 24 publications

Polycystic Kidney Disease with Hyperinsulinemic Hypoglycemia Caused by a Promoter Mutation in Phosphomannomutase 2

Polycystic Kidney Disease with Hyperinsulinemic Hypoglycemia Caused by a Promoter Mutation in Phosphomannomutase 2

Computer methods of analysis of chromosome contacts in the cell nucleus based on sequencing technology data

An integrated 3-Dimensional Genome Modeling Engine for data-driven simulation of spatial genome organization

Contact Info

Product

Resources

About