Evidence map›Paper›PMID 30475980›Full record

ArticleBioinformatics (Oxford, England)2019

RT States: systematic annotation of the human genome using cell type-specific replication timing programs.

Axel Poulet, Ben Li, Tristan Dubos, Juan Carlos Rivera-Mulia, David M Gilbert, Zhaohui S Qin

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Axel PouletDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Ben LiDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Tristan DubosLaboratoire de Génétique, CHRU-Nancy, Nancy, France.
Juan Carlos Rivera-MuliaDepartment of Biological Science, Center for Genomics and Personalized Medicine, Florida State University, Tallahassee, FL, USA.
David M GilbertDepartment of Biological Science, Center for Genomics and Personalized Medicine, Florida State University, Tallahassee, FL, USA.
Zhaohui S QinDepartment of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA.

Funding

UNDERSTANDING MECHANISMS OF hESC SELF-RENEWAL AND CELL FATE COMMITMENTP01GM085354 · NIGMS · UNIVERSITY OF GEORGIA · PI DALTON, STEPHEN · 2008 to 2018
$18.3M
NIGMS NIH HHS P01 GM085354
6 · The paper itself

Abstract

motivationThe replication timing (RT) program has been linked to many key biological processes including cell fate commitment, 3D chromatin organization and transcription regulation. Significant technology progress now allows to characterize the RT program in the entire human genome in a high-throughput and high-resolution fashion. These experiments suggest that RT changes dynamically during development in coordination with gene activity. Since RT is such a fundamental biological process, we believe that an effective quantitative profile of the local RT program from a diverse set of cell types in various developmental stages and lineages can provide crucial biological insights for a genomic locus.

resultsIn this study, we explored recurrent and spatially coherent combinatorial profiles from 42 RT programs collected from multiple lineages at diverse differentiation states. We found that a Hidden Markov Model with 15 hidden states provide a good model to describe these genome-wide RT profiling data. Each of the hidden state represents a unique combination of RT profiles across different cell types which we refer to as 'RT states'. To understand the biological properties of these RT states, we inspected their relationship with chromatin states, gene expression, functional annotation and 3D chromosomal organization. We found that the newly defined RT states possess interesting genome-wide functional properties that add complementary information to the existing annotation of the human genome. AVAILABILITY AND IMPLEMENTATION: R scripts for inferring HMM models and Perl scripts for further analysis are available https://github.com/PouletAxel/script_HMM_Replication_timing. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

DNA Replication TimingGenome, HumanCell DifferentiationChromatinGenomicsHumansChromatin

Identifiers

PMID30475980
PMCPMC6681175

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.