Cerebellum development
Cerebellum development
Time course ID: mouse_cerebellum
Sample provider:
Thomas Ha, Peter Zhang, Dan Goldowitz
Introduction
Brain development requires intricately controlled expression of specific gene regulatory networks across time. Despite recent development in genomics technology, temporally-dependent large-scale transcriptome analyses across neural development are lacking. The cerebellum is a less complex, anatomically discrete and well-studied part of the mammalian brain that lends itself to such an analysis. To identify active transcription factor networks in developing mouse cerebellum, we analyzed the sequenced CAGE libraries from 12 time points across cerebellar development (embryonic days 11-18 at 24 hour intervals and every 72hrs until postnatal day 9).
Background
Brain development requires intricately controlled expression of specific gene regulatory networks across time. Despite recent development in genomics technology, temporally-dependent large-scale transcriptome analyses across neural development are lacking. The cerebellum is a less complex, anatomically discrete and well-studied part of the mammalian brain that lends itself to such an analysis. In cerebellum, the rhombic lip (RL) gives rise to the excitatory neurons of the cerebellum: first glutamatergic cerebellar nuclear neurons and then granule cell precursors and unipolar brush cells whereas the ventricular neuroepithelium gives rise to Purkinje cells and other GABAergic interneurons and cerebellar nuclear neurons. The key transcription factors Math1 and Pax6 are expressed in RL and the external germinal layer (EGL), and Ptf1a is expressed in the ventricular neuroepithelium. Cerebellar granule cells go through several epochs of development from their origins in the rhombic lip around E12.5 to the trans-migratory cells that establish the EGL, to the highly proliferative and then migratory population that produces the largest cohort of neurons in the brain. In spite of numerous studies on granule cell development, the understanding of the genetic underpinnings of the establishment of the EGL is limited. By taking advantage of FANTOM5 Cerebellr Developmental Time Course analysis, we plan to identify the transcriptional network controlling the development of cerebellum with primary focus on cerebellar granule cells.
Samples
Mice were housed in a room with 12/12 hr light/dark controlled environment. Embryos were obtained from timed pregnant females at midnight of the day when a vaginal plug was detected; this was considered embryonic day 0 (E0). Pregnant females were cervically dislocated and embryos were harvested from the uterus. The cerebellum was isolated from each embryo, pooled with littermates of like genotype, and snap-frozen in liquid nitrogen. 3-4 replicate pools of 3-10 whole cerebella samples were collected from 12 time points across cerebellar development (embryonic days 11-18 at 24 hour intervals and every 72hrs until postnatal day 9)
Laser capture microdissection (LCM), a technique that can isolate specific cell types of interest from regions of tissue, was used to obtain pure populations of granule cells from early-stages of mouse cerebellar development. Fresh frozen brain tissue from mouse embryo (aged E13, 15 and 18) were collected and cyro-sectioned into 8 µm thick sections. The sections were then stained with cresyl violet for histological identification of the EGL. Veritas automated LCM system (Arcturus Veritus) was used to capture cells from external granular layer with infrared laser. Finally, the captured cells were lysed and RNA from pure granule cell population was extracted.
Quality control
Bioanalyzer analysis was performed to check RNA quality. All RNA samples used for the time series achieved high RNA Integrity (RIN) Score. 34 out of 36 samples had RIN score of 9.7 or higher (10 being the best).
Figure 2: CAGE expression of marker genes in TPM.
References
[1] Ha TJ, Swanson D, Kirova R, Yeung J, Choi K, Tong Y, Chesler E, Goldowitz D (2012) Genome-wide microarray comparison reveals downstream genes of Pax6 in the developing mouse cerebellum. Euro J Neurosci (In Press).
[2] Tong Y, Ha TJ, Liu L, Nishimoto A, Reiner A, Goldowitz D (2011) Spatial and temporal requirements for huntingtin (Htt) in neuronal migration and survival during brain development. J Neurosci 31:14794-14799.
[3] Swanson, D.J., Y. Tong, and D. Goldowitz, Disruption of cerebellar granule cell development in the Pax6 mutant, Sey mouse. Brain Res Dev Brain Res, 2005. 160(2): p. 176-93.
[4] Goldowitz, D. and K. Hamre, The cells and molecules that make a cerebellum. Trends Neurosci, 1998. 21(9): p. 375-82.
Beginning of non-public section
- Bioinformatics analysis
We propose a methodology applicable at genome and time-course scale to infer TFs with regulatory roles linked to gene expression changes in the time-course data. An abstract of the general methodology can be found at File:Mathelier Wasserman abstract.txt.
- Expression Analysis
Since CAGE data reveal the active promoters with a quantitative measure of intensity, one can determine the mRNAs differentially expressed between successive time-points. An analysis of differential expression for each time-point was performed by applying the edgeR R package to each pair of successive time-points.
- oPOSSUM motif enrichment
Sequence analysis of core promoter regions of these differentially expressed genes reveals over-represented transcription factor binding sites. The oPOSSUM analysis tool is used to measure motif enrichment analysis between a foreground set and a background set of DNA sequences. It is based on the JASPAR collection of TF binding profiles. For each time-point, the foreground set is composed of core-promoter regions of differentially expressed mRNAs and a matched background set is generated from the other mRNA core-promoters sharing similar sequence properties.
PRESENTATIONS
TEXT and FIGURES FOR MAIN/SATELLITE PAPER
The following is given as a starting point for the paper.
Figure 1
Cerebellum development w/ time-points.File:Cerebellum Time Course Fig1.pdf
Figure 2
Hierarchical clustering of the time-points/samples. File:Fantom5 mouse cerebellum-sample agg dendrogram rle.pdf, File:Fantom5 mouse cerebellum-sample dendrogram rle.pdf
Figure 3
Differentially expressed (DE) genes vs DE TFs along the time-course. File:Fantom5 mouse cerebellum-de mRNA and tfs mRNA.pdf
Figure 4
TSS switch engine (Emmanuel Dimont) - Figure depicting transition of TSS activity over development time course. Ideally with a gene encoding a TF.
Figure 5
Data Mogrify algorithm (Owen Rackham)
Figure 6
Self organizing map algorithm (Owen Rackham)
Figure 7
lncRNAs analysis (Leonard Lipovitch)
Figure 8
Transcriptional regulation network
Table 1
MARA + oPOSSUM merged results
Zenbu configurations and status
- Cerebellum development(COMPLETED ...)
Expression profiles
- Gene and CAGE cluster expression for the Cerebellum development series
MARA based network results
Related samples
- External Germinal Layer (EGL) short time series data (E13.5, E15.5 and E18.5)
- CbGRiTS (Cerebellar Gene Regulation in Time and Space) Microarray Data (www.cbgrits.org).
- Adult Cerebellum Data
Quality control
Marker gene expression
Short RNA expression
ISMARA analysis results
All samples: http://ismara.unibas.ch/ISMARA/scratch/CerebellumRERUN/ismara_report/index.html
Replicate averaged: http://ismara.unibas.ch/timecourses/CerebellumAvgd/averaged_report/index.html
For more information, see ISMARA.
