RNA sequencing reveals two major classes of gene expression levels in metazoan cells

被引:231
作者
Hebenstreit, Daniel [1 ]
Fang, Miaoqing [2 ]
Gu, Muxin [1 ]
Charoensawan, Varodom [1 ]
van Oudenaarden, Alexander [3 ,4 ]
Teichmann, Sarah A. [1 ]
机构
[1] MRC, Mol Biol Lab, Struct Studies Div, Cambridge CB2 0QH, England
[2] MIT, Dept Biol Engn, Cambridge, MA 02139 USA
[3] MIT, Dept Phys, Cambridge, MA 02139 USA
[4] MIT, Dept Biol, Cambridge, MA 02139 USA
基金
英国医学研究理事会;
关键词
bimodal; ChIP-seq; expression levels; RNA-FISH; RNA-seq; MESSENGER-RNA; STEM-CELLS; SEQ; DIFFERENTIATION; TRANSCRIPTOME; PROTEINS; PROTEOME; SYSTEMS; GENOME; MODEL;
D O I
10.1038/msb.2011.28
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The expression level of a gene is often used as a proxy for determining whether the protein or RNA product is functional in a cell or tissue. Therefore, it is of fundamental importance to understand the global distribution of gene expression levels, and to be able to interpret it mechanistically and functionally. Here we use RNA sequencing (RNA-seq) of mouse Th2 cells, coupled with a range of other techniques, to show that all genes can be separated, based on their expression abundance, into two distinct groups: one group comprised of lowly expressed and putatively non-functional mRNAs, and the other of highly expressed mRNAs with active chromatin marks at their promoters. These observations are confirmed in many other microarray and RNA-seq data sets of metazoan cell types. Molecular Systems Biology 7: 497; published online 7 June 2011; doi:10.1038/msb.2011.28
引用
收藏
页数:9
相关论文
共 35 条
[1]   NEW LOOK AT STATISTICAL-MODEL IDENTIFICATION [J].
AKAIKE, H .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1974, AC19 (06) :716-723
[2]  
[Anonymous], 1986, DENSITY ESTIMATION
[3]  
[Anonymous], 2001, STAT INFERENCE
[4]   GO::TermFinder - open source software for accessing Gene Ontology information and finding significantly enriched Gene Ontology terms associated with a list of genes [J].
Boyle, EI ;
Weng, SA ;
Gollub, J ;
Jin, H ;
Botstein, D ;
Cherry, JM ;
Sherlock, G .
BIOINFORMATICS, 2004, 20 (18) :3710-3715
[5]   Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments [J].
Bullard, James H. ;
Purdom, Elizabeth ;
Hansen, Kasper D. ;
Dudoit, Sandrine .
BMC BIOINFORMATICS, 2010, 11
[6]   Using FlyAtlas to identify better Drosophila melanogaster models of human disease [J].
Chintapalli, Venkateswara R. ;
Wang, Jing ;
Dow, Julian A. T. .
NATURE GENETICS, 2007, 39 (06) :715-720
[7]   Stem cell transcriptome profiling via massive-scale mRNA sequencing [J].
Cloonan, Nicole ;
Forrest, Alistair R. R. ;
Kolle, Gabriel ;
Gardiner, Brooke B. A. ;
Faulkner, Geoffrey J. ;
Brown, Mellissa K. ;
Taylor, Darrin F. ;
Steptoe, Anita L. ;
Wani, Shivangi ;
Bethel, Graeme ;
Robertson, Alan J. ;
Perkins, Andrew C. ;
Bruce, Stephen J. ;
Lee, Clarence C. ;
Ranade, Swati S. ;
Peckham, Heather E. ;
Manning, Jonathan M. ;
McKernan, Kevin J. ;
Grimmond, Sean M. .
NATURE METHODS, 2008, 5 (07) :613-619
[8]   Chromatin Signatures in Multipotent Human Hematopoietic Stem Cells Indicate the Fate of Bivalent Genes during Differentiation [J].
Cui, Kairong ;
Zang, Chongzhi ;
Roh, Tae-Young ;
Schones, Dustin E. ;
Childs, Richard W. ;
Peng, Weiqun ;
Zhao, Keji .
CELL STEM CELL, 2009, 4 (01) :80-93
[9]   Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins [J].
Graumann, Johannes ;
Hubner, Nina C. ;
Kim, Jeong Beom ;
Ko, Kinarm ;
Moser, Markus ;
Kumar, Chanchal ;
Cox, Juergen ;
Schoeler, Hans ;
Mann, Matthias .
MOLECULAR & CELLULAR PROTEOMICS, 2008, 7 (04) :672-683
[10]   EXPRESSION OF 3 ABUNDANCE CLASSES OF MESSENGER-RNA IN MOUSE TISSUES [J].
HASTIE, ND ;
BISHOP, JO .
CELL, 1976, 9 (04) :761-774