Literature DB >> 29082337

Inference of cell type specific regulatory networks on mammalian lineages.

Deborah Chasman1, Sushmita Roy1,2.   

Abstract

Transcriptional regulatory networks are at the core of establishing cell type specific gene expression programs. In mammalian systems, such regulatory networks are determined by multiple levels of regulation, including by transcription factors, chromatin environment, and three-dimensional organization of the genome. Recent efforts to measure diverse regulatory genomic datasets across multiple cell types and tissues offer unprecedented opportunities to examine the context-specificity and dynamics of regulatory networks at a greater resolution and scale than before. In parallel, numerous computational approaches to analyze these data have emerged that serve as important tools for understanding mammalian cell type specific regulation. In this article, we review recent computational approaches to predict the expression and sequence-based regulators of a gene's expression level and examine long-range gene regulation. We highlight promising approaches, insights gained, and open challenges that need to be overcome to build a comprehensive picture of cell type specific transcriptional regulatory networks.

Entities:  

Keywords:  cell lineage; chromatin state; gene regulation; regulatory networks; three-dimensional genome organization; transcription factor binding

Year:  2017        PMID: 29082337      PMCID: PMC5656272          DOI: 10.1016/j.coisb.2017.04.001

Source DB:  PubMed          Journal:  Curr Opin Syst Biol        ISSN: 2452-3100


  112 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2003-12-12       Impact factor: 11.205

2.  High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells.

Authors:  Alan P Boyle; Lingyun Song; Bum-Kyu Lee; Darin London; Damian Keefe; Ewan Birney; Vishwanath R Iyer; Gregory E Crawford; Terrence S Furey
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Review 3.  Topology of mammalian developmental enhancers and their regulatory landscapes.

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Journal:  Nature       Date:  2013-10-24       Impact factor: 49.962

4.  Histone modification levels are predictive for gene expression.

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Journal:  Proc Natl Acad Sci U S A       Date:  2010-02-01       Impact factor: 11.205

Review 5.  Computational and analytical challenges in single-cell transcriptomics.

Authors:  Oliver Stegle; Sarah A Teichmann; John C Marioni
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Authors:  Suhas S P Rao; Miriam H Huntley; Neva C Durand; Elena K Stamenova; Ivan D Bochkov; James T Robinson; Adrian L Sanborn; Ido Machol; Arina D Omer; Eric S Lander; Erez Lieberman Aiden
Journal:  Cell       Date:  2014-12-11       Impact factor: 41.582

7.  The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements.

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Journal:  Genome Res       Date:  2015-03-09       Impact factor: 9.043

8.  An experimentally validated network of nine haematopoietic transcription factors reveals mechanisms of cell state stability.

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Journal:  Elife       Date:  2016-02-22       Impact factor: 8.140

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Journal:  Nature       Date:  2015-02-19       Impact factor: 69.504

10.  Integrative epigenomic analysis reveals unique epigenetic signatures involved in unipotency of mouse female germline stem cells.

Authors:  Xiao-Li Zhang; Jun Wu; Jian Wang; Tingting Shen; Hua Li; Jun Lu; Yunzhao Gu; Yani Kang; Chee-Hong Wong; Chew Yee Ngan; Zhifeng Shao; Ji Wu; Xiaodong Zhao
Journal:  Genome Biol       Date:  2016-07-27       Impact factor: 13.583

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  5 in total

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2.  swCAM: estimation of subtype-specific expressions in individual samples with unsupervised sample-wise deconvolution.

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3.  Subtype-specific regulatory network rewiring in acute myeloid leukemia.

Authors:  Salam A Assi; Maria Rosaria Imperato; Daniel J L Coleman; Anna Pickin; Sandeep Potluri; Anetta Ptasinska; Paulynn Suyin Chin; Helen Blair; Pierre Cauchy; Sally R James; Joaquin Zacarias-Cabeza; L Niall Gilding; Andrew Beggs; Sam Clokie; Justin C Loke; Phil Jenkin; Ash Uddin; Ruud Delwel; Stephen J Richards; Manoj Raghavan; Michael J Griffiths; Olaf Heidenreich; Peter N Cockerill; Constanze Bonifer
Journal:  Nat Genet       Date:  2018-11-12       Impact factor: 38.330

Review 4.  Bioengineering the human spinal cord.

Authors:  Nisha R Iyer; Randolph S Ashton
Journal:  Front Cell Dev Biol       Date:  2022-08-26

5.  Topological structure analysis of chromatin interaction networks.

Authors:  Juris Viksna; Gatis Melkus; Edgars Celms; Kārlis Čerāns; Karlis Freivalds; Paulis Kikusts; Lelde Lace; Mārtiņš Opmanis; Darta Rituma; Peteris Rucevskis
Journal:  BMC Bioinformatics       Date:  2019-12-27       Impact factor: 3.169

  5 in total

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