Network analysis of microRNA and mRNA seasonal dynamics in a highly plastic sensorimotor neural circuit

Abstract

Background: Adult neurogenesis and the incorporation of adult-born neurons into functional circuits requires precise spatiotemporal coordination across molecular networks regulating a wide array of processes, including cell proliferation, apoptosis, neurotrophin signaling, and electrical activity. MicroRNAs (miRs) - short, non-coding RNA sequences that alter gene expression by post-transcriptional inhibition or degradation of mRNA sequences - may be involved in the global coordination of such diverse biological processes. To test the hypothesis that miRs related to adult neurogenesis and related cellular processes are functionally regulated in the nuclei of the avian song control circuit, we used microarray analyses to quantify changes in expression of miRs and predicted target mRNAs in the telencephalic nuclei HVC, the robust nucleus of arcopallium (RA), and the basal ganglia homologue Area X in breeding and nonbreeding Gambel's white-crowned sparrows (Zonotrichia leucophrys gambelli).

Results: We identified 46 different miRs that were differentially expressed across seasons in the song nuclei. miR-132 and miR-210 showed the highest differential expression in HVC and Area X, respectively. Analyzing predicted mRNA targets of miR-132 identified 33 candidate target genes that regulate processes including cell cycle control, calcium signaling, and neuregulin signaling in HVC. Likewise, miR-210 was predicted to target 14 mRNAs differentially expressed across seasons that regulate serotonin, GABA, and dopamine receptor signaling and inflammation.

Conclusions: Our results identify potential miR-mRNA regulatory networks related to adult neurogenesis and provide opportunities to discover novel genetic control of the diverse biological processes and factors related to the functional incorporation of new neurons to the adult brain.

Fig. 1

Experimental design. a A schematic of the song nuclei sampled for microarray analysis. The dotted line indicates where tissue samples were obtained. b Experimental time-line for all experimental groups. A red line indicates termination of the experiment for the given group. c Representative images of Nissl-stained brain sections confirming tissue punch locations in HVC, RA and Area X. The arrowheads indicate the borders of the respective nuclei as determined by cell morphology and density

Fig. 2

Patterns of changing expression of mRNA and miR transcripts between breeding and nonbreeding conditions. Expression data were converted to z-scores for each mRNA or miR. Thus colors represent up (red) or down (blue) regulation of a miR or mRNA in a particular sample, as compared to the mean expression for that gene. a The relative expression of mRNAs that were differentially regulated in at least one experimental group (i.e. LD + T 3D, 7D, 21, or LDW) compared to SD. A p-value of <0.0001 and a fold change >2.0 were used as the threshold for inclusion. b Relative expression of miRs that were differentially regulated in at least one experimental group with a fold change >2.0 and p < 0.0005 compared to SD. miRs of interest based on predicted function or miRs specific to birds are denoted

Fig. 3

qRT-PCR validation miR microarray identification of miR-132 as differentially regulated between seasons. Fold change in expression of miR-132 from the microarray (M; shown in light colors) compared to qRT-PCR (P; dark colors). All fold-changes are relative to SD. miR-132 trended towards differential expression with qRT-PCR at LD + T 7D in HVC (adjusted-p = 0.0802) and achieved significant differential expression at LD + T 21D in RA (adjusted-p = 0.0427)

Fig. 4

The seasonal miR-132–mRNA regulatory network in HVC. a The relative expression changes of mRNA targets of miR-132 that were differentially regulated in at least one experimental group (i.e. LD + T 3D, 21, or LDW) compared to SD, as well as having an inverse correlation to miR-132 in the same comparison. A p-value of <0.005 and a fold change >1.5 at any time point were used as selection criteria for mRNAs presented in the heat map. b An interaction network of mRNAs that were differentially anti-expressed with a fold change > -1.5 and p < 0.005 from conditions in which miR-132 was also differentially expressed (i.e. fold change > 2.0). IPA network analyses revealed several key pathways were down-regulated during periods of HVC new neuronal addition and functional incorporation

Fig. 5

The seasonal miR-210 –mRNA regulatory network in HVC. a The expression fold changes of miR-210 mRNA that were differentially regulated and inversely correlated in at least one experimental group in which miR-210 was also differentially expressed (i.e. LD + T 7D, 21, or LDW) compared to SD. A p-value of <0.005 and fold change >1.5 at any time point were used as selection criteria for mRNAs presented in the heat map. b An interaction network of mRNAs that were differentially anti-expressed with a fold change > 1.5 and p < 0.005 (bright) or p < 0.05 (faded) from conditions in which miR-210 was also differentially expressed (i.e. fold change > –2.0). IPA network analyses revealed several key pathways were up-regulated in Area X during periods of volume expansion