Behavior-specific changes in transcriptional modules lead to distinct and predictable neurogenomic states

被引:141
作者
Chandrasekaran, Sriram [1 ]
Ament, Seth A. [2 ]
Eddy, James A. [3 ]
Rodriguez-Zas, Sandra L. [4 ,5 ]
Schatz, Bruce R. [2 ,5 ,6 ]
Price, Nathan D. [1 ,2 ,3 ,5 ,7 ]
Robinson, Gene E. [2 ,5 ,8 ]
机构
[1] Univ Illinois, Ctr Biophys & Computat Biol, Urbana, IL 61801 USA
[2] Univ Illinois, Neurosci Program, Urbana, IL 61801 USA
[3] Univ Illinois, Dept Bioengn, Urbana, IL 61801 USA
[4] Univ Illinois, Dept Anim Sci, Urbana, IL 61801 USA
[5] Univ Illinois, Inst Genom Biol, Urbana, IL 61801 USA
[6] Univ Illinois, Dept Med Informat Sci, Urbana, IL 61801 USA
[7] Univ Illinois, Dept Chem & Biomol Engn, Urbana, IL 61801 USA
[8] Univ Illinois, Dept Entomol, Urbana, IL 61801 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
Apis mellifera; gene regulation; social behavior; systems biology; REGULATORY NETWORKS; HONEY-BEE; DROSOPHILA; EXPRESSION; ALGORITHM; COLONIES;
D O I
10.1073/pnas.1114093108
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
070301 [无机化学]; 070403 [天体物理学]; 070507 [自然资源与国土空间规划学]; 090105 [作物生产系统与生态工程];
摘要
Using brain transcriptomic profiles from 853 individual honey bees exhibiting 48 distinct behavioral phenotypes in naturalistic contexts, we report that behavior-specific neurogenomic states can be inferred from the coordinated action of transcription factors (TFs) and their predicted target genes. Unsupervised hierarchical clustering of these transcriptomic profiles showed three clusters that correspond to three ecologically important behavioral categories: aggression, maturation, and foraging. To explore the genetic influences potentially regulating these behavior-specific neurogenomic states, we reconstructed a brain transcriptional regulatory network (TRN) model. This brain TRN quantitatively predicts with high accuracy gene expression changes of more than 2,000 genes involved in behavior, even for behavioral phenotypes on which it was not trained, suggesting that there is a core set of TFs that regulates behavior-specific gene expression in the bee brain, and other TFs more specific to particular categories. TFs playing key roles in the TRN include well-known regulators of neural and behavioral plasticity, e.g., Creb, as well as TFs better known in other biological contexts, e.g ., NF-kappa B (immunity). Our results reveal three insights concerning the relationship between genes and behavior. First, distinct behaviors are subserved by distinct neurogenomic states in the brain. Second, the neurogenomic states underlying different behaviors rely upon both shared and distinct transcriptional modules. Third, despite the complexity of the brain, simple linear relationships between TFs and their putative target genes are a surprisingly prominent feature of the networks underlying behavior.
引用
收藏
页码:18020 / 18025
页数:6
相关论文
共 29 条
[1]
FlyTF:: a systematic review of site-specific transcription factors in the fruit fly Drosophila melanogaster [J].
Adryan, Boris ;
Teichmann, Sarah A. .
BIOINFORMATICS, 2006, 22 (12) :1532-1533
[2]
Honey bee aggression supports a link between gene regulation and behavioral evolution [J].
Alaux, Cedric ;
Sinha, Saurabh ;
Hasadsri, Linda ;
Hunt, Greg J. ;
Guzman-Novoa, Ernesto ;
DeGrandi-Hoffman, Gloria ;
Luis Uribe-Rubio, Jose ;
Southey, Bruce R. ;
Rodriguez-Zas, Sandra ;
Robinson, Gene E. .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2009, 106 (36) :15400-15405
[3]
Reverse engineering of regulatory networks in human B cells [J].
Basso, K ;
Margolin, AA ;
Stolovitzky, G ;
Klein, U ;
Dalla-Favera, R ;
Califano, A .
NATURE GENETICS, 2005, 37 (04) :382-390
[4]
Schlank, a member of the ceramide synthase family controls growth and body fat in Drosophila [J].
Bauer, Reinhard ;
Voelzmann, Andre ;
Breiden, Bernadette ;
Schepers, Ute ;
Farwanah, Hany ;
Hahn, Ines ;
Eckardt, Franka ;
Sandhoff, Konrad ;
Hoch, Michael .
EMBO JOURNAL, 2009, 28 (23) :3706-3716
[5]
A predictive model for transcriptional control of physiology in a free living cell [J].
Bonneau, Richard ;
Facciotti, Marc T. ;
Reiss, David J. ;
Schmid, Amy K. ;
Pan, Min ;
Kaur, Amardeep ;
Thorsson, Vesteinn ;
Shannon, Paul ;
Johnson, Michael H. ;
Bare, J. Christopher ;
Longabaugh, William ;
Vuthoori, Madhavi ;
Whitehead, Kenia ;
Madar, Aviv ;
Suzuki, Lena ;
Mori, Tetsuya ;
Chang, Dong-Eun ;
DiRuggiero, Jocelyne ;
Johnson, Carl H. ;
Hood, Leroy ;
Baliga, Nitin S. .
CELL, 2007, 131 (07) :1354-1365
[6]
The Inferelator:: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo [J].
Bonneau, Richard ;
Reiss, David J. ;
Shannon, Paul ;
Facciotti, Marc ;
Hood, Leroy ;
Baliga, Nitin S. ;
Thorsson, Vesteinn .
GENOME BIOLOGY, 2006, 7 (05)
[7]
The transcriptional network for mesenchymal transformation of brain tumours [J].
Carro, Maria Stella ;
Lim, Wei Keat ;
Alvarez, Mariano Javier ;
Bollo, Robert J. ;
Zhao, Xudong ;
Snyder, Evan Y. ;
Sulman, Erik P. ;
Anne, Sandrine L. ;
Doetsch, Fiona ;
Colman, Howard ;
Lasorella, Anna ;
Aldape, Ken ;
Califano, Andrea ;
Iavarone, Antonio .
NATURE, 2010, 463 (7279) :318-U68
[8]
Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC) [J].
Eddy, James A. ;
Hood, Leroy ;
Price, Nathan D. ;
Geman, Donald .
PLOS COMPUTATIONAL BIOLOGY, 2010, 6 (05) :1-17
[9]
Least angle regression - Rejoinder [J].
Efron, B ;
Hastie, T ;
Johnstone, I ;
Tibshirani, R .
ANNALS OF STATISTICS, 2004, 32 (02) :494-499
[10]
HIERARCHICAL-CLASSIFICATION OF COMMUNITY DATA [J].
GAUCH, HG ;
WHITTAKER, RH .
JOURNAL OF ECOLOGY, 1981, 69 (02) :537-557