Literature DB >> 33372598

Comprehensive network modeling from single cell RNA sequencing of human and mouse reveals well conserved transcription regulation of hematopoiesis.

Shouguo Gao1, Zhijie Wu2, Xingmin Feng2, Sachiko Kajigaya2, Xujing Wang3, Neal S Young2.   

Abstract

BACKGROUND: Presently, there is no comprehensive analysis of the transcription regulation network in hematopoiesis. Comparison of networks arising from gene co-expression across species can facilitate an understanding of the conservation of functional gene modules in hematopoiesis.
RESULTS: We used single-cell RNA sequencing to profile bone marrow from human and mouse, and inferred transcription regulatory networks in each species in order to characterize transcriptional programs governing hematopoietic stem cell differentiation. We designed an algorithm for network reconstruction to conduct comparative transcriptomic analysis of hematopoietic gene co-expression and transcription regulation in human and mouse bone marrow cells. Co-expression network connectivity of hematopoiesis-related genes was found to be well conserved between mouse and human. The co-expression network showed "small-world" and "scale-free" architecture. The gene regulatory network formed a hierarchical structure, and hematopoiesis transcription factors localized to the hierarchy's middle level.
CONCLUSIONS: Transcriptional regulatory networks are well conserved between human and mouse. The hierarchical organization of transcription factors may provide insights into hematopoietic cell lineage commitment, and to signal processing, cell survival and disease initiation.

Entities:  

Keywords:  Co-expression network; Cross-species network analysis; Gene regulatory network; Hematopoiesis; Single-cell RNA sequencing

Mesh:

Year:  2020        PMID: 33372598      PMCID: PMC7771096          DOI: 10.1186/s12864-020-07241-2

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  47 in total

1.  Collective dynamics of 'small-world' networks.

Authors:  D J Watts; S H Strogatz
Journal:  Nature       Date:  1998-06-04       Impact factor: 49.962

2.  Analysis of diverse regulatory networks in a hierarchical context shows consistent tendencies for collaboration in the middle levels.

Authors:  Nitin Bhardwaj; Koon-Kiu Yan; Mark B Gerstein
Journal:  Proc Natl Acad Sci U S A       Date:  2010-03-29       Impact factor: 11.205

3.  High-Resolution CRISPR Screens Reveal Fitness Genes and Genotype-Specific Cancer Liabilities.

Authors:  Traver Hart; Megha Chandrashekhar; Michael Aregger; Zachary Steinhart; Kevin R Brown; Graham MacLeod; Monika Mis; Michal Zimmermann; Amelie Fradet-Turcotte; Song Sun; Patricia Mero; Peter Dirks; Sachdev Sidhu; Frederick P Roth; Olivia S Rissland; Daniel Durocher; Stephane Angers; Jason Moffat
Journal:  Cell       Date:  2015-11-25       Impact factor: 41.582

Review 4.  Network medicine: a network-based approach to human disease.

Authors:  Albert-László Barabási; Natali Gulbahce; Joseph Loscalzo
Journal:  Nat Rev Genet       Date:  2011-01       Impact factor: 53.242

5.  Densely interconnected transcriptional circuits control cell states in human hematopoiesis.

Authors:  Noa Novershtern; Aravind Subramanian; Lee N Lawton; Raymond H Mak; W Nicholas Haining; Marie E McConkey; Naomi Habib; Nir Yosef; Cindy Y Chang; Tal Shay; Garrett M Frampton; Adam C B Drake; Ilya Leskov; Bjorn Nilsson; Fred Preffer; David Dombkowski; John W Evans; Ted Liefeld; John S Smutko; Jianzhu Chen; Nir Friedman; Richard A Young; Todd R Golub; Aviv Regev; Benjamin L Ebert
Journal:  Cell       Date:  2011-01-21       Impact factor: 41.582

6.  Functions of bifans in context of multiple regulatory motifs in signaling networks.

Authors:  Azi Lipshtat; Sudarshan P Purushothaman; Ravi Iyengar; Avi Ma'ayan
Journal:  Biophys J       Date:  2008-01-04       Impact factor: 4.033

Review 7.  A census of human cancer genes.

Authors:  P Andrew Futreal; Lachlan Coin; Mhairi Marshall; Thomas Down; Timothy Hubbard; Richard Wooster; Nazneen Rahman; Michael R Stratton
Journal:  Nat Rev Cancer       Date:  2004-03       Impact factor: 60.716

8.  A single-cell resolution map of mouse hematopoietic stem and progenitor cell differentiation.

Authors:  Sonia Nestorowa; Fiona K Hamey; Blanca Pijuan Sala; Evangelia Diamanti; Mairi Shepherd; Elisa Laurenti; Nicola K Wilson; David G Kent; Berthold Göttgens
Journal:  Blood       Date:  2016-06-30       Impact factor: 22.113

9.  STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets.

Authors:  Damian Szklarczyk; Annika L Gable; David Lyon; Alexander Junge; Stefan Wyder; Jaime Huerta-Cepas; Milan Simonovic; Nadezhda T Doncheva; John H Morris; Peer Bork; Lars J Jensen; Christian von Mering
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

10.  The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment.

Authors:  Elisa Laurenti; Sergei Doulatov; Sasan Zandi; Ian Plumb; Jing Chen; Craig April; Jian-Bing Fan; John E Dick
Journal:  Nat Immunol       Date:  2013-05-26       Impact factor: 25.606

View more
  5 in total

Review 1.  Tubby-like proteins (TLPs) transcription factor in different regulatory mechanism in plants: a review.

Authors:  Nasreen Bano; Shahre Aalam; Sumit Kumar Bag
Journal:  Plant Mol Biol       Date:  2022-10-18       Impact factor: 4.335

2.  Comparative Transcriptomic Analysis of the Hematopoietic System between Human and Mouse by Single Cell RNA Sequencing.

Authors:  Shouguo Gao; Zhijie Wu; Jeerthi Kannan; Liza Mathews; Xingmin Feng; Sachiko Kajigaya; Neal S Young
Journal:  Cells       Date:  2021-04-21       Impact factor: 6.600

3.  Integrated Analysis Reveals a lncRNA-miRNA-mRNA Network Associated with Pigeon Skeletal Muscle Development.

Authors:  Tao Zhang; Can Chen; Shushu Han; Lan Chen; Hao Ding; Yueyue Lin; Genxi Zhang; Kaizhou Xie; Jinyu Wang; Guojun Dai
Journal:  Genes (Basel)       Date:  2021-11-11       Impact factor: 4.096

4.  A global [Formula: see text] gene co-expression network constructed from hundreds of experimental conditions with missing values.

Authors:  Junyao Kuang; Nicolas Buchon; Kristin Michel; Caterina Scoglio
Journal:  BMC Bioinformatics       Date:  2022-05-09       Impact factor: 3.307

5.  In search of a Drosophila core cellular network with single-cell transcriptome data.

Authors:  Ming Yang; Benjamin R Harrison; Daniel E L Promislow
Journal:  G3 (Bethesda)       Date:  2022-09-30       Impact factor: 3.542

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.