Genomic regulatory networks underline the Mesendoderm specification and
cancer formation
Te-Hsuan Jang1, Yu-i Lin1, Hua-Ling Chen1, Wen-Fang Tseng1, Tzu-Min Chan1,
Eric H. Davidson2, Chiou-Hwa Yuh1,
1Division
of Molecular and Genomic Medicine, National Health Research Institute, 35,
Keyan Road, Zhunan Town, Miaoli County 350, Taiwan, ROC.
2
Division of Biology, California Institute of Technology, Pasadena, CA91125, USA
The genomic program for development and disease operates mainly by the regulated
expression of genes encoding transcription factors and the signaling pathways. In the
post-genomic era, the most urgent topic in studying complex biological systems is
functional genomics. It has become apparent that the only level of analysis from which
explanations of major developmental phenomena directly emerge, is the system level
represented by the sea urchin GRN. The gene regulatory networks employed
experimental analysis to pursue an integrated, vertical mode of genes interaction. In that
our experiments are directed at all levels of biological organization, extending from the
transcription factor-DNA interactions that control spatial and temporal expression of
specific genes to the system level analysis of large regulatory networks. The architecture
of the networks is based on perturbation and expression data, on data from cis-regulatory
analyses for several genes, and on other experiments. Figure 1 is the mesendoderm GRN
of the sea urchin embryo from Dr. Davidson’s group at Caltech.
Figure 1. The
complete view from the
genome of the
endomesoderm Gene
Rugulatory Networks of
the sea urchin embryos.
The interactions
between genes were
obtained by perturbation
and Q-PCR analysis on
embryos. After
microinject the
perturbants into
fertilized embryos, the
RNA were collected
from different stages
embryos, and the QPCR was performed to
detect the changes of
gene expression of other
genes. The nodes were
confirmed by the
promoter and mutation
analysis on the
individual transcription
factors binding sites.
The overall goal of this project is to establish the Gene regulatory Networks
underlying the mesendoderm development in zebrafish. The main reasons we use
zebrafish as model system are: A, Zebrafish is vertebrate; the research of the GRN can
apply to higher vertebrate organism, like human. B. Zebrafish embryos develop very fast;
it can form a complete individual with well-defined organs within 48 hours after
fertilization. C. We can easily knock down the genes’ function by injecting morpholino
antisense oligonucleotide into the embryos. We also can make the transgenic animals
very easily by microinjecting the cDNA clones of specific genes into the embryos. D.
There are enormous efforts from all over the world using zebrafish for studying the gene
regulation, cancer formation and developmental biology, but there are very few integrated
studies regarding the gene regulation networks in zebrafish.
According to literatures, the de-regulation of many transcription factors and signal
transduction pathways are related to colorectal cancer formation. Those are the mutations
of the components in PI3 kinase pathway, activation of Wnt pathway, changes at TGFpathway, and loss-of-function mutations in the JNK pathway. The lost function of
FoxH1, smad2, smad4, CDX-2 and activation of SOX-9 and over expression of SNAIL
gene product are also related to colorectal cancer formation. Interestingly, those
transcription factors and signaling pathways are all in the mesendoderm networks we
discovered from zebrafish model. We will combine the information we gathered from
mesendoderm GRN and test their functions in the colorectal cancer formation.
To understand the complex gene regulatory networks underlying the development
and cancer formation, we need the help from computational modeling. In recent years,
mathematical theories and computer simulations have started to become a useful tool in
the Systems Biology study. We are going to collaborate with Professor Feng-Sheng Wang,
hoping to establish the gene networks using reverse-engineering computational modeling
method.
References:
1. Yuh, C. H., Dorman E. R., Howard M. L. and Davidson, E. H.
An otx cis-regulatory module: a key node in the sea urchin endomesoderm gene
regulatory network. Dev Biol. 2004 May 15;269(2):536-51.
2. Davidson EH, Rast JP, Oliveri P, Ransick A, Calestani C, Yuh C. H., Minokawa T,
Amore G, Hinman V, Arenas-Mena C, Otim O, Brown CT, Livi CB, Lee PY, Revilla
R, Rust AG, Pan Z, Schilstra MJ, Clarke PJ, Arnone MI, Rowen L, Cameron RA,
McClay DR, Hood L, Bolouri H.
A genomic regulatory network for development, Science, 295, 1669-1678, 2002.
3. Yuh, C. H., Bolouri, H. and Davidson, E. H.
Genomic Cis-regulatory Logic: Experimental and Computational Analysis of a Sea
Urchin Gene. Science, 279, 1896-1902, 1998.
Useful link and software:
http://labs.systemsbiology.net/bolouri/software/BioTapestry/#launch
http://family.caltech.edu/tutorial/
http://sugp.caltech.edu/endomes/