Gene expression profiling of two distinct neuronal populations in the rodent spinal cord

Abstract

Background: In the field of neuroscience microarray gene expression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global gene expression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level.

Methodology/principal findings: We examine the microarray gene expression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The gene expression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential gene expression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population.

Conclusions/significance: We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressed genes between the motor neurons and the interneurons that reflect the functional differences between these two cell populations in generating and transmitting the motor output in the rodent spinal cord.

Figure 1. Labeling and laser microdissection.

A and B show the schematic labeling procedure of cell populations in the lumbar spinal cord of the neonatal rat. RDA is applied to cut axons and retrogradely transported to the cell bodies. A shows MN labeling and B shows dCIN labeling. C and D illustrate the LMD of MNs in 10 µm thick spinal cord transections. Orientation: midline (M) is towards the right, lateral (L) is towards the left and ventral is downwards. C shows a spinal cord transection before LMD and D after LMD. The green thick outline illustrates vaporized tissue due to the laser action from the dissection of one cell, so in essence less tissue is dissected than the wholes might suggest. Each labeled cell is cut out separately to minimize contamination from surrounding cells.

Figure 2. Affymetrix array normalization and quality control.

The color code for each distribution is the same throughout A–D. A. The distributions of log₂ transformed raw PM intensity values. The black dashed line illustrates the average distribution, I_ref, of all 22 arrays (7 MNs, 7 dCINs and 8 MIX) in both A and B. B. QLT distributions of array PM intensities. C. qq-plots of the QLT distributions versus the average distribution. Deviations from I_ref most pronounced at the distribution tails, i.e. at low and high intensities. D. qq-plot of Li-Wong summaries based on QLT+QPN PM values. E. Dendogram based on hierarchical clustering of correlation distance between individual microarray expression profiles (Li-Wong expression measures). The two major branches contain the two cell groups, MNs and dCINs respectively. MIX is dispersed in between the two groups. F. First two principal components of the gene expression profiles illustrating the Euclidian separation of individual microarrays. MNs and dCINs are nicely separated by the MIX, which are scattered in between these two groups. Symbols: 1 (black) = dCINs, 2 (red) = MIX, 3 (green) = MNs.

Figure 3. False Discover Rates.

A and B display the histogram of p-values based on the regularized test statistics from limma or Cyber-T respectively when comparing MNs with dCINs. Horizontal dashed line corresponds to the uniform distribution of p-values under the null hypothesis of no differential expression. A. Mixed model fit to Cyber-T p-values, one beta distribution (red): (λ₀, λ₁, r, s) = (0.904, 0.0960, 0.206, 1.570). Regressions that included two or three beta-functions gave λ₂ = λ₃ = 0. B. Mixed model fit to limma p-values, one beta distribution (red): (λ₀, λ₁, r, s) = (0.848, 0.152, 0.296, 1.636) and two beta distributions (green): (λ₀, λ₁, λ₂, r₁, s₁, r₂, s₂) = (0.760, 0.117, 0.122, 0.265, 2.245, 3.900, 10.042). C. Log transformed p-values versus the FDR for limma (black) and Cyber-T (red) for two different measures of FDR. Plot symbols: +represents mixture model FDR based on the fit to one beta distribution parameters from A or B and closed circles are BH FDR. D. Empirical FDR from SAM as a function of its t-statistic (d-score). Horizontal dashed line in C and D correspond to a 10% FDR cutoff.

Figure 4. Differentially expressed genes.

Positive ratios (M in A–B and y-axis in C–D) represent higher mRNA levels in dCINs than in MNs and negative ratios represent lower mRNA levels in dCINs than in MNs. The scale of ratios is displayed in normal values such that the value of the ratios can be read directly from the figures. Red triangles in A and B highlight the 50 most significantly DE genes from Table 1. The enlarged filled triangles in A and B are the genes chosen for real time RT-PCR validation, with the same color code throughout including bar-plots C–D. A. MA plot of MNs versus dCINs, i.e. for each gene the log₂ transformed average ratio, M (eq 5 and eq 6), is plotted as a function of the average log₂ transformed expression values, A (eq 7). B. Volcano plot of M (same as in A) versus the absolute log transformed p-values from Cyber-T. C. Bar-plot of log₂ transformed ratios (M values from A and B) of the genes chosen for real time RT-PCR. The genes are plotted in decreasing order of significance of DE within each group, dCINs and MNs. The error bars indicate the standard deviation of the log₂ transformed ratios. D. Barplot of log₂ transformed ratios (ΔΔC_T) from the real time RT-PCR validation of the same genes as in C. Color codes for the highlighted real time RT-PCR genes match on A–D: red = Ox2r, yellow = Viaat, dark green = Calcb, light green = Nefl, blue = VAChT, purple = Kcna1, pink = 5HT3r.