We have presented here a comprehensive survey of differentially expressed transcripts in the main nuclei of the song control system of quiet, unstimulated zebra finches, based on a combination of microarray and in situ hybridization data. While the data largely support previous findings, they also reveal large sets of previously undescribed constitutive molecular specializations of nuclei in both the direct motor pathway (DMP) and the anterior forebrain pathway (AFP). These include complements of G-protein couple receptors, neuroactive receptors, axon guidance related molecules, and voltage-gated K+ channels that were shared among, but also unique to each nucleus, as well as varying pathways related to calcium signaling, CAM-kinase activation, and neurotransmitter binding. Among the newly discovered markers are numerous members of gene families with links to the establishment and maintenance of neuronal projections, regulation of neuronal excitability, the modulation of neurotransmission and synaptic function. Together, these findings allow us to generate novel hypotheses regarding possible molecular determinants of the unique properties of the song control system.
The publically available datasets analyzed here were previously examined separately to identify singing regulated genes [28, 33, 35] and convergent specializations of analogous vocal nuclei in birds and humans [23], but not to systematically identify constitutive molecular specializations of all major song system nuclei. We note that Whitney et al. [28] analyzed baseline gene expression within individual song nuclei compared to other song nuclei, but did not analyze the expression of these same genes “outside” of the song system in areas adjacent to each song nucleus. Thus, from that analysis it is not possible to know whether or not the observed contrasting expression patterns for a given nucleus represent specialized properties of that particular nucleus, or whether they reflect global properties of the general brain region where each song nucleus is located. We also note that these previous studies provided only partial reports of the microarray data. For HVC, the robust statistical approach used here identified 717 differential genes (compared to 279 in Lovell et al. [24]). For RA, only ~ 3% of markers identified here were previously reported [23], since that study focused on the small subset of shared markers of vocal areas in birds and humans. For Area X, previous efforts focused on singing-induced genes [32, 33], with constitutive genes treated as controls and not separately analyzed. The specific data from a microarray screening for nXIIts vs. SSP [35] have not been previously reported.
Our analysis differed further from previous efforts as we used the large in situ hybridization database in ZEBrA as an independent method to establish rigorous and objective cut-off criteria for microarray data from each nucleus examined. We therefore did not have to rely on arbitrary cut-offs and post hoc validation by qPCR or in situs. The curatorial effort was also critical to our analysis. Since the cDNA and oligo microarrays were constructed prior to the zebra finch genome, the specificity and adequacy of individual probes had not been previously determined. By aligning each oligo/EST sequence to the zebra finch genome we were able to identify and remove ~ 5500 oligos and ~ 1500 cDNA because they had: (a) multiple high-scoring alignments, indicating a lack of specificity, (b) non-informative alignments (i.e. low-scoring or no alignment, or alignments exclusive to chromosome Unknown) that precluded gene identification, or (c) were artifacts of mis-priming or cloning. We also removed additional oligos (3000–10,000) from each differential screening because they had no detectable signal or behaved inconsistently (high variance) across arrays. Finally, our efforts revealed that ~ 29% of the oligos we examined on these arrays, originally annotated using automated approaches, present various annotation issues that greatly limit the accuracy of the data interpretation. By addressing these issues, our curatorial effort vastly improved the overall sensitivity, reliability, and accuracy of the microarray approach to identify differential gene sets. This in turn facilitated discovering molecular features unique to individual song nuclei or shared across multiple nuclei. Overall, the data represent the most rigorously vetted and annotated set of constitutive molecular specializations of the zebra finch song system performed to date.
Importantly, we found that the microarray and in situ data were largely concordant, but note some inconsistencies, some of which possibly reflecting differential regulation of splice variants. We also note that while the microarray data provided broad and unbiased assessments of the differential song nuclei transcriptomes, examination of gene families helped to identify targets of regulation in the context of specific pathways and categories. These general and specific insights are discussed in further detail below.
Molecular Specializations of the Song System
Ion channel physiology, which is critical for many aspects of neuronal function, emerged from both the bioinformatics and Venn diagram analyses as a major target of regulation in the song system (Fig. 3; Table 3). This outcome is consistent with our previous findings of widespread regulation of potassium channel genes in the song system [25], and likely reflects a need for the song system to tightly regulate features of cellular excitability and spiking fidelity. The present study also reveals that members of the sodium-, calcium-, chloride-channel gene families are important targets of regulation in the song system. A comprehensive analysis of these gene families and their brain expression is being prepared as part of a separate study (Friedrich et al., in preparation). Of note, the specific complements of differential ion channel genes differ across nuclei, suggesting that each nucleus uses a distinct set of mechanisms to regulate features related to excitability and spike timing. Overall, the lists of differential ion channel genes in this study represent fundamental reference sets for future pharmacological and genetic manipulations.
By far the most prominent shared enrichments were for GPCR-related pathways (Table 2B). Despite the shared pathway annotation, however, closer inspection of the complements of genes underlying these GPCR-related specializations revealed they were quite different. For example, while striatal Area X had several dopaminergic receptors, pallial HVC was enriched for cholinergic receptors. These findings are consistent with the known dopaminergic and cholinergic inputs and modulations of these respective nuclei [51,52,53]. Thus, the specific genes identified represent well-supported candidate targets for gene and pharmacological manipulation to better understand the contribution of these neuromodulatory pathways to vocal learning.
Other more general trends included shared enrichments in pathways related to neuromodulation, neurotransmission, and peptidergic modulation, and within the nuclei of the DMP, a shared enrichment of genes in reelin-related pathways. The fact that both RELN and its VLDLR and LRP8 receptors are differential markers of DMP nuclei suggests the possible involvement of the reelin pathway in the formation of DMP connections (discussed in more detail below). The low pathway diversity in nucleus RA is also intriguing, given the large number of differential markers of this nucleus. Possible explanations include a lower diversity of cell types compared to other nuclei or a higher representation of genes per pathway, either of which would suggest that RA is highly specialized compared to other song nuclei.
Axonal guidance and synaptic plasticity genes
The observed patterns of axonal guidance cues genes are potentially of relevance for understanding the regulation of connections across nuclei, but also raise questions about ligand-receptor pairing rules in this system. Among semaphorins and plexins, there is precedence for SEMA3E expression in presynaptic terminals having repulsive interactions with post-synaptic terminals expressing the PLXND1 receptor, but co-expression of PLXND1 with NRP1 can flip this interaction to be attractive, thus making a co-expressing nucleus an attractive target for SEMA3E-expressing terminals [54, 55]. Indeed, interactions between SEMA3E and PLXND1 play an important role in establishing specificity of cortico-thalamo-striatal connections [56]. Intriguingly, SEMA3E shows remarkably high expression in HVC and LMAN, and thus could be involved in influencing the projections of these nuclei to their common targets RA and/or striatal Area X. Consistent with this possibility, NRP1 expression is high in Area X. However, PLXND1 expression in Area X and in the striatum, as a whole was quite weak, and expression of the PLXND1/NRP1 co-receptors was not particularly marked in RA either. On the other hand, PLXND1/NRP1 are both highly expressed in HVC, which might make HVC attractive to inputs that express SEMA3E. Unfortunately, SEMA3E expression in nuclei that project to HVC (NIf, Uva, MMAN) has yet to be determined. Alternatively, there is precedence in developing sensory-motor circuits in the mammalian spinal cord for post-synaptic SEMA3E interacting with pre-synaptic PLXND1 and/or NRP [55, 56]. Under this scenario, the high expression of SEMA3E in HVC and LMAN might help to regulate inputs to these nuclei. However, this scenario seems unlikely because prominent expression of PLXND1/NRP1 appears largely lacking in nuclei that provide inputs to LMAN or HVC. In short, more work is needed to determine whether and how this particular axon guidance system operates in birds.
The high expression of PLXNA4s and NRPs in HVC and RA suggests these nuclei might be attractive targets for terminals expressing their corresponding SEMA3-type (A/C/D/F) ligands. Notably, the patterns in zebra finch are consistent with those in another vocal-learner, the Bengalese finch [57], suggesting a conserved program of axon guidance cues in the songbird lineage. While data to test this idea are not yet available, one would predict high expression of these ligands in nuclei (e.g., L/MMAN, Uva, NIf) that provide inputs to PLXNA4-expressing nuclei. SEMA7A was found to be a positive marker of all song nuclei examined, consistent with its prominent role in the maturation of mammalian cortical circuits [58]. Intriguingly, the down-regulation of the PLXNC1 receptor would make projection targets receptive to SEMA7A-positive terminals if this ligand-receptor interaction were repulsive, as in other systems [59]. Under this scenario, SEMA7A-expressing axonal terminals from a given input (this could apply to several song nuclei) would interact with PLXNC1-expressing cells outside the target nucleus and be inhibited from making contact, and/or compelled to continue towards the target by other attractants. For example, SEMA7A interacts prominently with integrin receptors, which would make the high ITGA1 expression in RA and nXIIts relevant for the HVC-to-RA and RA-to-nXIIts projections. Similarly, the high expression of PLXNC1 in DLM shell compared to its core (Fig. 14d) could play a role in the specificity of the X-to-DLM projection. The patterns observed for SEMA5A and 6D and their PLXNA4 receptors suggest similar roles in the projections of the DMP as for SEMA7A. Interestingly, the pattern of SEMA6A in zebra finch is consistent with the prominent role of this SEMA in guiding descending fibers from PLXNA4-expressing corticospinal neurons in the brainstem in mammals [60]. In this context, the high expression of PLXNA4 in RA and the prominent expression of its ligand SEMA6A in several brainstem nuclei, but down-regulation in nXIIts could help to regulate the specificity of the RA-to-nXIIts projection. In contrast to all above, the SEMA4s/PLXNBs patterns suggest a lack of prominent roles in song system projections.
Cadherins and protocadherins are a large family of genes that are involved in cell-cell adhesion and play important roles in neuronal connection formation. Our data suggests some specific song system projections where CDHs might play a role through homophilic interactions. This includes CDH6 (HVC-to-X projection), CDH13 (RA-to-nXIIts projection), and CDH9 (all projections of the DMP). The overall trend, however, was down-regulation, suggesting several CDH-related pathways are shut down in the adult zebra finch song system. Previous studies have shown differential expression of some cadherins in song nuclei of Bengalese finches [61], or explored a potential role of cadherins in vocal control [62]. While we report on a much larger set of genes in this family, consistent observations across studies include: a) the up-regulation of CDH6 (a.k.a. Cad6b) in HVC, Area X, and DM, b) up-regulation of CDH9 in HVC, c) down-regulation of CDH4 (a.k.a. Rcad) in all major forebrain song nuclei and in nXIIts, and d) down-regulation of CDH7 in RA. However, we did not observe marked up-regulation of CDH6 in RA and LMAN, nor the up-regulation of CDH10 in RA, as reported in Bengalese finches. While these could be real species differences, they could also derive from different behavioral conditions, or uncharacterized transcript variants. CDH1 was previously reported as a positive marker of HVC (Lovell et al. [24]), however a close examination of alignments to the now available zebra finch genome reveals that the reported clone is GAS8 and that CDH1 was not evaluated.
The high expression of RELN in DM and of the RELN receptors VLDLR and LRP8 in nXIIts suggests a possible role in the DM-to-nXIIts projection- an important pathway for vocal-motor patterning. Because both RELN and VLDLR are known targets of FOXP2, this brainstem vocal projection could represent a still unexplored pathway (outside of the basal ganglia) for FOXP2 modulation of vocal behaviors. Alternatively, the differential expression of RELN in DM versus nXIIts could play a role in the specificity of the projections from RA to these two brainstem targets. Our data are largely consistent with previous observations in canaries [63], although we did not detect up-regulation in Area X. Overall, the in situ data support the bioinformatics indication of the reelin pathway (Table 3C) as an important target of regulation, and the marked RELN down-regulation suggests suppression may be important for the maintenance of the song system circuitry. As for SLIT/ROBO genes, our data support previous observations of convergent specializations between RA and the human primary laryngeal motor cortex [23], and of differential regulation of SLITs and ROBOs in nuclei of the vocal-motor circuitry [64]. ROBOs are generally thought to be axonally-expressed receptors that have repulsive interactions with target-secreted SLIT ligands. Thus, the down-regulation of SLIT1 in RA and nXIIts could facilitate the targeting of ROBO-expressing terminals from HVC-to-RA and from RA-to-nXIIts, respectively. ROBO1 is largely down-regulated in RA but is highly expressed in a sparse cell population, which could correspond to a subset of projection neurons. Alternatively, the SLIT down-regulation in HVC and RA, coupled with the up-regulation of ROBOs in RA and nXIIts, might play a role in the targeting specificity of the HVC-to-RA and the RA-to-nXIIts projections. This notion has been previously suggested as helping to establish the specificity of the RA-to-nXIIts projection [64], a connection critical for learned vocalizations, but it would require the pre- and post-synaptic localizations of SLITs and ROBOs, respectively. The lack of prominent expression of SLITs or ROBOs in DM further supports a differential role of these genes in the RA-to-nXIIts projection. Lastly, the prominent differential regulation within these gene families in AFP nuclei (Area X, DLM, LMAN) suggests further roles in other parts of the song system.
The marked differential regulation of UNC5s in all song nuclei, including RA and its targets DM and nXIIts (Fig. 6c), suggests a prominent role for this pathway in song circuit connectivity. Interestingly, axonal terminals that express UNC5 receptors are repulsed by their main known ligands (netrins; [65, 66]). Our limited data suggest a lack of prominent regulation of netrins in the forebrain, but expression analysis of other netrins and examination of brainstem nuclei would be important next steps to establish the role of UNC5s. We also note that FLRTs, which provide alternative non-netrin repulsive cues to UNC5 receptors [67], and NEO1 (a.k.a. DCC), which has been implicated in chemo-attraction of netrins [68], are respectively up- and down-regulated in HVC and its targets, further suggesting UNC5-related effects at multiple sites in the song circuitry. Other classes of guidance cues (NTNGs-, NLGNs- and RTN4-related) showed down-regulation trends, with no apparent coordinated expression of known ligand-receptor pairs between connected song nuclei. We did not observe an enrichment of NTNGs in thalamo-cortical projection neurons (e.g. DLM) as reported in mammals [50, 69]. Lastly, the general down-regulation of No-Go-related cues and receptors (LINGOS, RTN4s) suggests that suppression of this axonal guidance pathway is a prominent feature of the mature song circuitry.
The marked differential expression of axonal guidance and connectivity cue genes in adult song nuclei suggests that the maintenance and/or plasticity of song system projections is under active regulation in adults. In several cases we did not see coordinated regulation of known ligand-receptor pairs in connected nuclei, suggesting that not all ligand-receptor interactions in songbirds conform to known rules of axon guidance. We note that most such rules derive from work in non-avian organisms that do not possess brain pathways for learned vocalizations. Thus, the patterns observed in finches might reflect axon guidance rules that are unique to birds, or related to the emergence of the song system in songbirds. A deeper understanding of how axonal guidance cues modulate song system connections requires developmental studies, a definition of the cellular distribution of proteins in pre-synaptic vs. post-synaptic structures, and gene manipulations to test specific hypotheses.
Excitatory and inhibitory neurotransmitter receptors
Significant insights were also gained from the analysis of inhibitory and excitatory neurotransmitter receptors. Consistent with their general roles, GABAergic and glutamatergic receptor families were broadly expressed in all song nuclei, but several genes showed evidence of regulated expression. For GABAergic receptors, the non-differential expression of the more abundant and fundamental alpha subunits of type-A receptors contrasted markedly with the differential regulation of multiple beta, delta, and epsilon subunits, suggesting these less prevalent subunits are more prominent targets of differential regulation in the song system. In particular, the up-regulation of delta subunits in all major telencephalic song nuclei, consistent with a previous report [70], suggests a distinctive feature of inhibitory neurotransmission, but its functional significance is unknown. The data on glycine receptor subunits is also intriguing, as the patterns of alpha and beta subunits seem largely complementary rather than overlapping. These receptors play important roles during development, and in adults tend to be more constrained to brainstem regions, including auditory nuclei [71,72,73,74]. Since functional receptors depend on the presence of both alpha and beta subunits, the patterns in adult finches suggest that they may play other roles, rather than reflecting functional glycine receptors.
The glutamate receptor patterns were largely consistent with previous data [26], both studies pointing to the differential regulation of multiple subunits at multiple sites as a distinctive feature of the song system. The possible implications of the observed patterns for regulating firing, deactivation, and plasticity within song nuclei (discussed more extensively in Wada et al. [26]), are not clear in the absence of pharmacological or genetic manipulations. While the present study presents the first expression data on delta-subunits in the song system, other differences between studies include the differential expression of GRIA3 in HVC and GRM4 in LMAN in the present study only, and of GRIK2/GRM8 in LMAN, GRM1/GRM5 in Area X, and GRM8 in HVC, seen by Wada et al. only. We also note that gene down- or up-regulation in distinct cell populations is more readily apparent with the non-radioactive approach used here (e.g. Fig. 12h, GRID1 in Area X; Figs. 10k-m, GRM1, GRID1, and GRID3 in HVC). Moreover, there is evidence of alternative splicing among zebra finch glutamate receptors subunits (e.g. Wada et al. [26], Fig. 5), which could further contribute to observed differences between the studies.
The expression of neuromodulatory receptors was consistent with and extends previous studies, and may help explain the differential ligand binding in autoradiographic assays. For example, the high expression of ADRA2A in HVC, LMAN, and to a lesser extent Area X, provides a likely basis for the high binding of alpha-2 adrenergic ligands to these nuclei [75]. However, the high alpha-2 ligand binding to RA and the modulation of RA via alpha-2 agonists/antagonists [76] remain unexplained, as ADRA2A was non-differential and ADRA2C was down-regulated in RA. The data on dopaminergic receptors are consistent with the more extensive study by [77], but the down-regulation of DRD2 in RA and up-regulation of DRD5 in HVC were not previously seen. With regards to DRD7, a gene markedly differential in several song nuclei, we adopted a term that better reflects its presence throughout the vertebrate phylogeny (DRD7 in Danio rerio, previously D1DR in finch [77] and DD1CR in chicken) and absence in mammals. As for serotonergic receptors, the marked up-regulation of multiple subunits in forebrain nuclei (except for HTR1B down-regulation HVC) points to serotonergic modulation as a major feature of the song system, consistent with pharmacological and electrophysiological studies (e.g. [78]). For cholinergic receptors, the data confirm the high expression of CHRM4 in Area X previously seen by Lovell et al. [24], and provide a basis for the higher binding of a muscarinic cholinergic antagonist to Area X compared to the surrounding striatum [79]. In contrast, the low expression of CHRM5 in RA might contribute to the low ligand binding described for this nucleus. We have also confirmed the high expression of CHRNA5 and CHRNA7 in HVC (previously seen by Lovell et al. [24]). This is consistent with the high alpha bungarotoxin binding for these nicotinic receptors in HVC [80]. In situ hybridization shows that CHRN4 is highly expressed in a sparse cell population within Area X. Of note, genomic alignments show that the cDNA clone annotated as CHRNA2 in Lovell et al. [24] actually corresponds to CHRNA4, thus the CHRNA2 expression pattern remains unknown in zebra finch. Overall, the data point to HVC and Area X as major targets of modulation by cholinergic inputs, particularly via CHRNA7 receptors, consistent with previous pharmacological and physiological data [81].
Our data are also consistent with and expand upon previous reports of peptide-related regulation in the song system based on gene expression and immunostaining data [24, 82,83,84]. In fact, peptide-related patterns provide some striking examples of differential regulation, suggesting important contributions to the physiology of the song system. They also often occur in sparse cell populations, suggesting roles in neuronal cell type diversification. We note that differential SST expression was not detected in HVC or RA, which contrasts with the described immunostained somata in these nuclei in comparison with the adjacent tissues [83]. Further, VIP was down in RA and Area X, consistent with [85], but PENK (MET) was not up in RA as expected based on the peptide distribution, suggesting that differential translation plays a role in this differential regulation. TAC1 is a remarkable marker of Area X (also reported in [86]), but is also highly expressed in nucleus accumbens (www.zebrafinchatlas.org). This finding likely explains why TAC1 was not detected as differential in Area X on the array. We also note that expression of opioid receptors in song nuclei was not detectable with our in situ protocol. This differs from reports suggesting that mu-opioid mRNA expression is not only detected, but marginally higher in HVC and RA than in surrounds [87]. We note, however that this previous report contradicts previous ligand binding autoradiographic studies in another songbird (Dark-eyed Junco) that reported no apparent differences in binding of mu-opioid ligands in the song system [88].