From silence to song: Testosterone triggers extensive transcriptional changes in the female canary HVC
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eLife assessment
This paper is of interest to neuroscientists studying the effects of sex hormones on neural and behavioral plasticity, and more specifically to researchers studying the neural mechanisms underlying birdsong plasticity. The experimental design is excellent, and the work provides a comprehensive resource for understanding the intersection between testosterone's influence on gene expression and behavior. However, the work also makes claims concerning cellular effects and gene regulatory mechanisms that extend beyond the data and under the current analyses are not rigorously supported.
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Abstract
Seasonal song production in canaries, influenced by gonadal hormones, is a well-documented phenomenon. We explored testosterone-induced song development in adult female canaries—a behavior rarely exhibited naturally. Gene regulatory networks in the song-controlling brain area HVC were compared at multiple time points (1 hour to 14 days) post-treatment with those of placebo-treated controls, paralleling HVC and song development. Females began vocalizing within four days of testosterone treatment, with song complexity and HVC volume increasing progressively over two weeks. Rapid transcriptional changes involving 2,739 genes preceded song initiation. Over two weeks, 9,913 genes—approximately 64% of the canary’s protein-coding genome—were differentially expressed, with 98% being transiently regulated. These genes are linked to various biological functions, with early changes at the cellular level and later changes affecting the nervous system level after prolonged hormone exposure. Our findings suggest that testosterone-induced song development is accompanied by extensive and dynamic transcriptional changes in the HVC, implicating widespread neuronal involvement. The data reveal extensive transcriptomic changes, including alterations in steroid receptor expression and numerous transcription factors, coinciding with significant neural transformations. These changes underpin the gradual emergence of singing behavior, providing insights into the neural basis of seasonal behavioral patterns.
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Author Response
Reviewer #1 (Public Review):
First, we thank the reviewer for his instructive remarks. In the following we address the queries of Reviewer 1.
1.1) At several points, the authors make claims that I believe extend beyond the data presented here. For instance, in the Abstract (line 27), the authors state "the development of adult songs requires restructuring the entire HVC, including most HVC cell types, rather than altering only neuronal subpopulations or cellular components." The gene ontology analyses performed do suggest that there is a progression from cellular transcriptional changes to organ-level changes, however caution should be taken in claiming that "most HVC cell types" exhibit transcriptional changes. In fact, according to Fig. 3D most of the transcriptional changes appear restricted to neurons. As the …
Author Response
Reviewer #1 (Public Review):
First, we thank the reviewer for his instructive remarks. In the following we address the queries of Reviewer 1.
1.1) At several points, the authors make claims that I believe extend beyond the data presented here. For instance, in the Abstract (line 27), the authors state "the development of adult songs requires restructuring the entire HVC, including most HVC cell types, rather than altering only neuronal subpopulations or cellular components." The gene ontology analyses performed do suggest that there is a progression from cellular transcriptional changes to organ-level changes, however caution should be taken in claiming that "most HVC cell types" exhibit transcriptional changes. In fact, according to Fig. 3D most of the transcriptional changes appear restricted to neurons. As the authors themselves note elsewhere, claims at this resolution are difficult without support from single-cell approaches. I do not suggest that the authors need to perform single-cell RNA-seq for this work, but strong claims like this should be avoided.
We have revised our claim to more accurately reflect our findings. Our intended message is that testosterone treatment leads to extensive transcriptional changes in the HVC, likely affecting a majority of neuronal subpopulations rather than solely targeting specific cellular components. The revised text in lines 29-32 now reads: "Thus, the development of adult songs stimulated by testosterone results in widespread transcriptional changes in the HVC, potentially affecting a majority of neuronal subpopulations, rather than altering only specific cellular components."
1.2) Similarly the Abstract states that parallel regulation "directly" by androgen and estrogen receptors, as well as the transcription factor SP8, "lead" to the transcriptional and neural changes observed after testosterone treatment of females. However, experiments that demonstrate such a causal role have not been performed. The authors do perform a set of bioinformatic analyses that point in this direction - enrichment of androgen and estrogen receptor binding sites in the promoters of differentially expressed genes, high coexpression of SP8 with other genes, and the enrichment of predicted SP8 binding sites in coexpressed genes. However, further support for direct regulation, at the level that the authors claim, would require some form of transcription factor binding assay, e.g. ChIP-seq or CUT&RUN. I am fully aware that these assays are enormously challenging to perform in this system (and again I don’t suggest that these experiments need to be done for this work); however, statements of direct regulation should be tempered. This is especially true for the role of SP8. This does appear to be a compelling target, but without some manipulation of the activity of SP8 (e.g. through knockdowns) and subsequent analysis of gene expression, it is too much to claim that this transcription factor is a regulatory link in the testosterone-driven responses. SP8 does appear to be a highly connected hub gene in correlation network analysis, but this alone does not indicate that it acts as a hub transcription factor in a gene regulatory network.
We appreciate the reviewer's comment and have revised the statement concerning the role of SP8. Indeed, we document the coexpression of ESR2 and SP8, and our bioinformatics analysis suggests that SP8 might play an important role in transcriptomics. We have rephrased the statement in line 29-32 as follows: "Parallel gene regulation directly by androgen and estrogen receptors, potentially amplified by coexpressed transcription factors that are themselves steroid receptor regulated, leads to substantial transcriptomic and neural changes in specific behavior-controlling brain areas, resulting in the gradual seasonal occurrence of singing behavior." In addition, we have included discussions regarding limitations of promoter sequence analyses (lines 414 to 427).
1.3. Along these lines, the in-situ hybridizations of ESR2 and SP8 presented in Figure 5 need significant improvement. The signals in the red and green channels, SP8 and ESR2, look suspiciously similar, showing almost identical subcellular colocalization. This signal pattern usually suggests bleed-through during image acquisition, as it’s highly unlikely that the mRNA of both genes would show this degree of overlap. I would suggest that control ISHs be run with one probe left out, either SP8 or ESR2, and compare these ISHs with the dual label ISHs to determine if signal intensity and cellular distribution look similar. Furthermore, on lines 354-356 the authors write, "The fact that the two genes were expressed nearby in the same cell may indicate physical interactions between the gene pair and warrant further investigation into the nature of their relationship.". Yet, even if the overlap between ESR2 and SP8 shown in Figure 5 is confirmed, close localization of transcripts does not imply that the protein products physically interact. The STRING bioinformatic analysis is more convincing that there is a putative regulatory interaction between ESR2 and the SP8 locus, and this suggestion of protein-protein interaction is weak and should be omitted. In addition, the authors note that ESR2 has not been detected in the songbird HVC in a previous study. To further demonstrate the expression of ESR2 (and SP8) in HVC, it would be useful to plot their expression from the microarray data across the different testosterone conditions.
We repeated the coexpression study using confocal microscopy and fluorescent RNAScope in situ hybridization, which is now reflected in the revised Figure 5 and a new Figure 5 - Supplement Figure 1. We have also moderated our statement regarding the sparse co-expression of ESR2 and SP8 in HVC neurons. While the presence of co-expressing neurons may provide some anatomical basis for the bioinformatic findings, we have been cautious in our interpretation and have stated that "SP8 and ESR2 mRNAs exhibited low expression levels in HVC, co-localizing in a subset of cells, predominantly GABAergic cells" (lines 369-370). We have removed the speculation about potential protein interaction based on mRNA distribution. Additionally, we have highlighted that SP8 and ESR2 were differentially upregulated at T14d (lines 362-363).
1.4) My final concern lies in the interpretation of these results as generalizable to other sex hormone-modualated behaviors. On lines 452-455, the authors write, "This suggests that the testosterone (or estrogen)-triggered induction of adult behaviors, such as parental behavior and courtship, requires a much more extensive reorganization of the transcriptome and the associated biological functions of the brain areas involved than previously thought.". The experiments and argument likely apply to other neural systems to undergo large seasonal fluctuations in sex hormones and similar morphological changes. However, the authors argue that the large number of transcriptional changes seen here may generalize broadly to sex hormone modulated adult behaviors. I think there are a couple of problems with this argument. First, as described here and in past work, testosterone drives major morphological changes the song system of adult canaries; such dramatic changes are not seen for instance in sex hormone-receptive areas underlying mating behavior in adult mammals. Similarly, the study introduced testosterone into female birds which drives a greater morphological change in HVC relative to similar manipulations in males, which again may account for the large number of differentially expressed genes. I would temper the generality of these results and note how the experimental and biological differences between this system and other sex hormone-responsive systems and behaviors may contribute to the observed transcriptional differences.
We modified this statement in lines 473-478: “The testosterone-driven changes in female HVC morphology and function represent some of the most notable modifications known in the vertebrate brain. However, how this extensive, testosterone-induced gene regulation in the HVC applies to other seasonally testosterone-sensitive brain areas remains to be seen. Endpoint analysis of testosterone-induced singing in male canaries during the non-reproductive season also indicates considerable regulation of HVC transcriptomes (Frankl-Vilches et al., 2015; Ko et al., 2021)”.
Reviewer #2 (Public Review):
First, we would like to express our gratitude to Reviewer #2 for the constructive feedback. We have addressed the concerns in detail below:
2.1). The bulk of the manuscript details WGCNA, GO terms, and promoter ARE/ERE motif abundance, using the initial pairwise comparisons for each timepoint as input lists. However, there are no p/adjp values provided for these pair-wise comparisons that form the basis of all subsequent analyses. Nor are there supplementary tables to indicate how consistent the replicates are within each group or how abundantly the genes-of-interest are expressed. With the statistical tests used here, and the lack of relevant information in the supplementary tables, I cannot determine if the data support the authors’ conclusions. These omissions mar what is otherwise a conceptually intriguing line of investigation.
We appreciate the reviewer’s concerns. Please refer to our response addressing this point and the subsequent one (2.2) together in the section below.
Reviewer #3 (Public Review):
We appreciate the positive feedback from the reviewer and below addressed the issues pointed out by the reviewer.
3.1) My biggest concern is the sample size. Most of the time points only have 5 or 6 individuals represented, and I question whether these numbers provide sufficient statistical power to uncover the effects the authors are trying to explore. This is a particular problem when it comes to evaluating the supposed "transient" of testosterone on gene expression. There is currently little basis for distinguishing such effects from noise that accrues because of low power. This can be a major problem with studies of gene expression in non-model species, like canaries, where among-individual variability in transcript abundance is quite high. Thus, it is possible that one or two outliers at a given time point cause the effect testosterone at this time point to become indistinguishable from the controls; if so, then a gene may get put into the transient category, when in fact its regulation was not likely transient.
We acknowledge that our sample sizes may appear moderate. To address the concern regarding temporal regulation analysis, we followed Reviewer 3's suggestion and conducted a probe-level power analysis (point 2 of recommendations for the authors; labelled as point 3.9 below). We then excluded differentially expressed genes with a power less than 0.8 prior to conducting temporal classification. Consequently, 93% of our differentially expressed genes demonstrated a power ≥ 0.8 (9025/9710). Following further classification by temporal regulation pattern, we identified 29 constantly upregulated, 41 constantly downregulated, 39 dynamically regulated, and 8916 transiently regulated genes. If we apply a stricter constraint by requiring each differentially expressed gene to have at least two probe-sets with a power ≥ 0.8, 83% of differentially expressed genes (8033/9710) still have sufficient power.
We recognize that our sample size may not be sufficient to detect weakly differentially expressed genes. However, we have intentionally excluded these genes from the beginning (those with |log2(fold change)| ≤ 0.5 were excluded).
The scenario outlined by the reviewer, where outliers might cause the effect of testosterone to blend with controls, leading to misclassification, is indeed plausible. This could occur either because the genes are weakly regulated, or because the power to detect differential expression is insufficient, thus preventing these genes from surpassing the threshold to be deemed significantly differentially expressed. However, this also illustrates that the effect of testosterone does not regulate every gene in the same way.
We have appended a column indicating high power genes (≥ 0.8) in the DiffExpression.tsv file, available in the Dryad repository. The power analysis has been incorporated to the method section at lines 801-808 and result section at lines 188-192.
3.2) More on the transient categorization. Would a gene whose expression is not immediately upregulated (within 1 hour), but is upregulated later on (say in the 14d group) be considered transient? If so, this seems problematic. Aren’t the authors setting the null expectation of "non-transient" as a gene that does not increase immediately after 1 hour of treatment? The authors even recognize that it is quite surprising that gene expression changes after an hour. It may be that some genes whose regulation is classified as transient are simply slower to upregulate; but, really, would we say their expression in transient per se? Maybe I’m misunderstanding the categorizations?
We appreciate the reviewer's insightful discussion regarding the transient categorization. We understand that it is indeed more challenging for a gene to be classified as constantly regulated than transiently regulated, due to smaller effects by testosterone or being undetectable owing to low power. To address this concern, we further dissected the transiently regulated category by reporting the number of time points at which a gene is differentially expressed in Figure 2 - Figure supplement 1. Approximately half of the transiently regulated genes were only regulated at one time point, further illustrating that the effect of testosterone on gene expression was not constant during the time window we examined (see lines 184 - 187).
3.3) The authors don’t fully explain the logic for using females in this study to measure a "male-typical" behavior (singing). My understanding is that females have underlying circuitry to sign, and T administration triggers it; thus, this situation that creates a natural experiment in which we can explore T’s on brain and behavior, unlike in males which have fluctuating T. First, it might be good to clarify this logic for readers, unless perhaps I’m misunderstanding something. Second, I found myself questioning this logic a little. Our understanding of basic sex differences and the role that steroid hormones play in generating them has changed over the last few decades. There are, for example, a variety of genetic factors that underlie the development of sex differences in the brain (I’m especially thinking about the incredible work from Art Arnold and many others that harness the experimental power of the four core genotype mice). Might some of these factors influence female development, such that T’s effects on the female brain and subsequent ability to increase HVC size and sing is not the same as males.
Indeed, sex-chromosome dosage compensation is absent in birds leading to higher Z-chromosomal gene expression in males. We demonstrated substantial sex differences in gene expression in our earlier work [Ko, M.-C., Frankl-Vilches, C., Bakker, A., Gahr, M., 2021. The Gene Expression Profile of the Song Control Nucleus HVC Shows Sex Specificity, Hormone Responsiveness, and Species Specificity Among Songbirds. Frontiers in Neuroscience 15].
We have revised the introduction (lines 96-98) to clarify our rationale for using female canaries as a model for adult behavioral development, not as a model for male canaries. After testosterone treatment, these females start to sing, with song structure developing over time, similar to male seasonal progression. This approach eliminates the confounding effect of fluctuating testosterone levels seen in males, supported by distinct HVC transcriptomes in testosterone-implanted singing female canaries compared to males (Ko et al., 2021).
The revised paragraph reads as below: Female canaries (Serinus canaria) are typically non-singers, with their spontaneous songs displaying less complexity than their male counterparts (Hartley et al., 1997; Herrick and Harris, 1957; Ko et al., 2020; Pesch and Güttinger, 1985). Despite their infrequent singing, these females possess the necessary underlying circuitry that can be activated by testosterone. Following testosterone treatment, these females start to produce simple songs, which gradually evolve in structure over weeks—paralleling the seasonal progression of male singing (Hartog et al., 2009; Ko et al., 2020; Shoemaker, 1939; Vallet et al., 1996; Vellema et al., 2019). Moreover, testosterone induces the differentiation of song control-related brain nuclei in adult female canaries, a critical step for song development (Fusani et al., 2003; Madison et al., 2015; Nottebohm, 1980). In this study, we focus on these testosterone-treated female canaries as a model for adult behavioral development rather than a model for male canaries. This unique model allows us to examine transcriptional cascades in parallel with the differentiation of the song control system and the progression of song development, without the confounding impact of fluctuating testosterone levels seen in males, which often results in considerable individual differences in the non-reproductive season baseline singing behavior. This approach is backed by the observation that the HVC transcriptomes of testosterone-implanted singing female canaries are distinct from those of singing males (Ko et al., 2021).
3.4) I was surprised by the authors assertion that testosterone would only influence several tens or hundreds of genes. My read of the literature says that this is low, and I would have expected 100s, if not 1,000s, of genes to be influenced. I think that the total number of genes influenced by T is therefore quite consistent with the literature.
We apologize for any confusion caused by our statement. We did not mean to imply that testosterone only influences several tens or hundreds of genes, but rather that we did not expect such an extensive transcriptional regulation in the HVC by testosterone. We have clarified this in our revised manuscript, specifically in lines 450-451. Thank you for helping us to clarify this point.
3.5) I found the GO analyses presented herein uncompelling. As the authors likely know, not all GO terms are created equally. Some GO terms are enriched by hundreds of genes and thus reflect broad functional categories, whereas other GO terms are much more specific and thus are enriched by only a few genes. The authors report broad GO terms that don’t tell us much about what is happening in the HVC functionally. This is particularly the case when a good 50% of the genome is being differentially regulated.
We appreciate the reviewer's comment. We have added KEGG pathway enrichment analysis in Figure 3 - Figure supplement 1 as an alternative. However, we believe that the GO term enrichment results still provide valuable insights, and therefore we have retained them in Fig. 3.
3.6) The Genomatix analyses are similarly uncompelling. This approach to finding putative response elements can uncover many false positives, and these should always be validated thoroughly. Don’t get me wrong-I appreciate that these validations are not trivial, and I value the authors response element analysis.
We appreciate the reviewer's comment on the presence of AR or ER motifs in promoters and acknowledge that in mammals, AR and ER predominantly bind at distal enhancers rather than promoters. Our analysis focused on promoter regions due to the limitations of available tools and resources for our study species. We understand that this approach may not capture the full complexity of AR and ER regulation. We have revised our manuscript to note the limitations of our approach and clarify that the presence of AREs and EREs alone is not indicative of active receptor binding or direct regulation (lines 416-427).
3.7) I’m sceptical about the section of the paper that speculates about modification of steroid sensitivity in the HVC. These conclusions are based on analyses of mRNA expression of AKR1D1, SRD5A2, and the like. However, this does not reflect a different in the capacity to metabolize steroids, or at least there is little evidence to suggest this. Note that many of these transcripts have different isoforms, which could also influence steroidal metabolism.
We agree that mRNA expression levels of AKR1D1, SRD5A2, and other transcripts involved in steroid metabolism do not necessarily reflect changes in steroid metabolizing capacity. However, we believe that these changes in mRNA expression are indicative of potential changes in steroid sensitivity in the HVC, which could affect the neural response to steroids. We acknowledge that isoform differences of these transcripts may influence steroid metabolism and further studies are necessary to confirm our findings and elucidate the mechanisms underlying the observed changes in gene expression. In response to this comment, we have amended the text in lines 245-249 to reflect this consideration.
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eLife assessment
This paper is of interest to neuroscientists studying the effects of sex hormones on neural and behavioral plasticity, and more specifically to researchers studying the neural mechanisms underlying birdsong plasticity. The experimental design is excellent, and the work provides a comprehensive resource for understanding the intersection between testosterone's influence on gene expression and behavior. However, the work also makes claims concerning cellular effects and gene regulatory mechanisms that extend beyond the data and under the current analyses are not rigorously supported.
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Reviewer #1 (Public Review):
Testosterone modulates a range of adult behaviors, and its signaling contributes to behavioral plasticity. One of the more remarkable examples of this influence can be found in female canaries, who do not normally sing or have elevated levels of testosterone. However, introducing testosterone experimentally causes female canaries to begin singing within days and results in an enlargement of the neural circuitry responsible for song production. This work seeks to characterize the transcriptional responses in a key song brain region, HVC, to testosterone treatment in female canaries. They assay gene expression at a number of time points following testosterone administration and perform analyses characterizing patterns of differential expression using a broad range of approaches. This analysis in particular has …
Reviewer #1 (Public Review):
Testosterone modulates a range of adult behaviors, and its signaling contributes to behavioral plasticity. One of the more remarkable examples of this influence can be found in female canaries, who do not normally sing or have elevated levels of testosterone. However, introducing testosterone experimentally causes female canaries to begin singing within days and results in an enlargement of the neural circuitry responsible for song production. This work seeks to characterize the transcriptional responses in a key song brain region, HVC, to testosterone treatment in female canaries. They assay gene expression at a number of time points following testosterone administration and perform analyses characterizing patterns of differential expression using a broad range of approaches. This analysis in particular has a focus on understanding the putative gene regulatory networks that drive the observed testosterone-driven transcriptional responses, with the ultimate aim of understanding how these networks influence neural and behavioral properties.
Strengths
This work is well-focused on a specific question and has a number of excellent qualities. The experimental design of this study is strong, and the fine temporal resolution analysis of testosterone effects on gene expression in female songbirds is a novel and compelling approach to understanding the molecular basis of sex hormone-regulated neural plasticity. The authors have carefully assessed the influence of testosterone on a range of female song features, providing an excellent behavioral reference point for their transcriptional analysis. The gene expression analysis, from differential expression to correlation-based network analysis, appears generally sound and provides a good overview of the effects of testosterone on gene expression in HVC. Combined, the expression, neural, and behavioral data provide a rich resource to better understand the molecular mechanisms underlying testosterone-modulate neural and behavioral plasticity.
Weaknesses
However, I do have several concerns about this work, and these concerns fall into three main areas:
At several points, the authors make claims that I believe extend beyond the data presented here. For instance, in the Abstract (line 27), the authors state "the development of adult songs requires restructuring the entire HVC, including most HVC cell types, rather than altering only neuronal subpopulations or cellular components." The gene ontology analyses performed do suggest that there is a progression from cellular transcriptional changes to organ-level changes, however caution should be taken in claiming that "most HVC cell types" exhibit transcriptional changes. In fact, according to Fig. 3D most of the transcriptional changes appear restricted to neurons. As the authors themselves note elsewhere, claims at this resolution are difficult without support from single-cell approaches. I do not suggest that the authors need to perform single-cell RNA-seq for this work, but strong claims like this should be avoided.
Similarly the Abstract states that parallel regulation "directly" by androgen and estrogen receptors, as well as the transcription factor SP8, "lead" to the transcriptional and neural changes observed after testosterone treatment of females. However, experiments that demonstrate such a causal role have not been performed. The authors do perform a set of bioinformatic analyses that point in this direction - enrichment of androgen and estrogen receptor binding sites in the promoters of differentially expressed genes, high coexpression of SP8 with other genes, and the enrichment of predicted SP8 binding sites in coexpressed genes. However, further support for direct regulation, at the level that the authors claim, would require some form of transcription factor binding assay, e.g. ChIP-seq or CUT&RUN. I am fully aware that these assays are enormously challenging to perform in this system (and again I don't suggest that these experiments need to be done for this work); however, statements of direct regulation should be tempered. This is especially true for the role of SP8. This does appear to be a compelling target, but without some manipulation of the activity of SP8 (e.g. through knockdowns) and subsequent analysis of gene expression, it is too much to claim that this transcription factor is a regulatory link in the testosterone-driven responses. SP8 does appear to be a highly connected hub gene in correlation network analysis, but this alone does not indicate that it acts as a hub transcription factor in a gene regulatory network.
Along these lines, the in situ hybridizations of ESR2 and SP8 presented in Figure 5 need significant improvement. The signals in the red and green channels, SP8 and ESR2, look suspiciously similar, showing almost identical subcellular colocalization. This signal pattern usually suggests bleed-through during image acquisition, as it's highly unlikely that the mRNA of both genes would show this degree of overlap. I would suggest that control ISHs be run with one probe left out, either SP8 or ESR2, and compare these ISHs with the dual label ISHs to determine if signal intensity and cellular distribution look similar. Furthermore, on lines 354-356 the authors write, "The fact that the two genes were expressed nearby in the same cell may indicate physical interactions between the gene pair and warrant further investigation into the nature of their relationship.". Yet, even if the overlap between ESR2 and SP8 shown in Figure 5 is confirmed, close localization of transcripts does not imply that the protein products physically interact. The STRING bioinformatic analysis is more convincing that there is a putative regulatory interaction between ESR2 and the SP8 locus, and this suggestion of protein-protein interaction is weak and should be omitted. In addition, the authors note that ESR2 has not been detected in the songbird HVC in a previous study. To further demonstrate the expression of ESR2 (and SP8) in HVC, it would be useful to plot their expression from the microarray data across the different testosterone conditions.
- My final concern lies in the interpretation of these results as generalizable to other sex hormone-modualated behaviors. On lines 452-455, the authors write, "This suggests that the testosterone (or estrogen)-triggered induction of adult behaviors, such as parental behavior and courtship, requires a much more extensive reorganization of the transcriptome and the associated biological functions of the brain areas involved than previously thought.". The experiments and argument likely apply to other neural systems to undergo large seasonal fluctuations in sex hormones and similar morphological changes. However, the authors argue that the large number of transcriptional changes seen here may generalize broadly to sex hormone modulated adult behaviors. I think there are a couple of problems with this argument. First, as described here and in past work, testosterone drives major morphological changes the song system of adult canaries; such dramatic changes are not seen for instance in sex hormone-receptive areas underlying mating behavior in adult mammals. Similarly, the study introduced testosterone into female birds which drives a greater morphological change in HVC relative to similar manipulations in males, which again may account for the large number of differentially expressed genes. I would temper the generality of these results and note how the experimental and biological differences between this system and other sex hormone-responsive systems and behaviors may contribute to the observed transcriptional differences.
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Reviewer #2 (Public Review):
During the breeding season, testosterone (T) levels rise in males, leading to seasonal song production. This behavioral plasticity is accompanied by changes in the size of brain nuclei that control song production, particularly the HVC, which expresses both androgen and estrogen receptors. To determine how testosterone controls song production, Ko et al performed a six point timecourse in female birds implanted with T capsules. The authors carefully document the onset of song production around day 4, and the subsequent progression from sub-songs to plastic songs with more complex syllables. They demonstrate a corresponding increase in HVC volume by 14 days. To identify the genes that direct these events, the authors compared gene expression in the HVC at each timepoint, ranging from 1 hr to 14 days. They …
Reviewer #2 (Public Review):
During the breeding season, testosterone (T) levels rise in males, leading to seasonal song production. This behavioral plasticity is accompanied by changes in the size of brain nuclei that control song production, particularly the HVC, which expresses both androgen and estrogen receptors. To determine how testosterone controls song production, Ko et al performed a six point timecourse in female birds implanted with T capsules. The authors carefully document the onset of song production around day 4, and the subsequent progression from sub-songs to plastic songs with more complex syllables. They demonstrate a corresponding increase in HVC volume by 14 days. To identify the genes that direct these events, the authors compared gene expression in the HVC at each timepoint, ranging from 1 hr to 14 days. They report strong induction of gene expression at only 1 hr after T treatment. At subsequent time points, the number of induced genes varies markedly, with the greatest number of differential genes detected at day 14, when the HVC has increased in volume. Overall, a relatively small number of genes show consistent changes in expression across the duration of treatment, while the majority fall into a "transient" category of showing up- or -downregulation at one or a subset of timepoints. The authors put forward a model whereby T can rapidly induce the expression of transcription factors within the first 1-3 hours, followed by additional gene expression cascades directed by the induced TFs. These downstream pathways would then permit changes in HVC structure and connectivity to facilitate singing.
The bulk of the manuscript details WGCNA, GO terms, and promoter ARE/ERE motif abundance, using the initial pairwise comparisons for each timepoint as input lists. However, there are no p/adjp values provided for these pair-wise comparisons that form the basis of all subsequent analyses. Nor are there supplementary tables to indicate how consistent the replicates are within each group or how abundantly the genes-of-interest are expressed. With the statistical tests used here, and the lack of relevant information in the supplementary tables, I cannot determine if the data support the authors' conclusions. These omissions mar what is otherwise a conceptually intriguing line of investigation.
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Reviewer #3 (Public Review):
I found this paper fascinating. It is a study that needed to be done in the field of behavioral endocrinology, as it addresses our understanding of exactly how steroid hormone action might regulate behavioral output like few other published studies. For decades, researchers have been implanting animals with steroids and observing corresponding changes in behavior, noting that some behavioral traits are immediately expressed, while others take time to be expressed. Why would this be? The answer lies in the temporal dynamics of steroid action, but few have ever addressed this. Having said this, I do have several issues with the manuscript that I think need to be addressed.
My biggest concern is the sample size. Most of the time points only have 5 or 6 individuals represented, and I question whether these …
Reviewer #3 (Public Review):
I found this paper fascinating. It is a study that needed to be done in the field of behavioral endocrinology, as it addresses our understanding of exactly how steroid hormone action might regulate behavioral output like few other published studies. For decades, researchers have been implanting animals with steroids and observing corresponding changes in behavior, noting that some behavioral traits are immediately expressed, while others take time to be expressed. Why would this be? The answer lies in the temporal dynamics of steroid action, but few have ever addressed this. Having said this, I do have several issues with the manuscript that I think need to be addressed.
My biggest concern is the sample size. Most of the time points only have 5 or 6 individuals represented, and I question whether these numbers provide sufficient statistical power to uncover the effects the authors are trying to explore. This is a particular problem when it comes to evaluating the supposed "transient" of testosterone on gene expression. There is currently little basis for distinguishing such effects from noise that accrues because of low power. This can be a major problem with studies of gene expression in non-model species, like canaries, where among-individual variability in transcript abundance is quite high. Thus, it is possible that one or two outliers at a given time point cause the effect testosterone at this time point to become indistinguishable from the controls; if so, then a gene may get put into the transient category, when in fact its regulation was not likely transient.
More on the transient categorization. Would a gene whose expression is not immediately upregulated (within 1 hour), but is upregulated later on (say in the 14d group) be considered transient? If so, this seems problematic. Aren't the authors setting the null expectation of "non-transient" as a gene that does not increase immediately after 1 hour of treatment? The authors even recognize that it is quite surprising that gene expression changes after an hour. It may be that some genes whose regulation is classified as transient are simply slower to upregulate; but, really, would we say their expression in transient per se? Maybe I'm misunderstanding the categorizations?
The authors don't fully explain the logic for using females in this study to measure a "male-typical" behavior (singing). My understanding is that females have underlying circuitry to sign, and T administration triggers it; thus, this situation that creates a natural experiment in which we can explore T's on brain and behavior, unlike in males which have fluctuating T. First, it might be good to clarify this logic for readers, unless perhaps I'm misunderstanding something. Second, I found myself questioning this logic a little. Our understanding of basic sex differences and the role that steroid hormones play in generating them has changed over the last few decades. There are, for example, a variety of genetic factors that underlie the development of sex differences in the brain (I'm especially thinking about the incredible work from Art Arnold and many others that harness the experimental power of the four core genotype mice). Might some of these factors influence female development, such that T's effects on the female brain and subsequent ability to increase HVC size and sing is not the same as males.
I was surprised by the authors assertion that testosterone would only influence several tens or hundreds of genes. My read of the literature says that this is low, and I would have expected 100s, if not 1,000s, of genes to be influenced. I think that the total number of genes influenced by T is therefore quite consistent with the literature.
I found the GO analyses presented herein uncompelling. As the authors likely know, not all GO terms are created equally. Some GO terms are enriched by hundreds of genes and thus reflect broad functional categories, whereas other GO terms are much more specific and thus are enriched by only a few genes. The authors report broad GO terms that don't tell us much about what is happening in the HVC functionally. This is particularly the case when a good 50% of the genome is being differentially regulated.
The Genomatix analyses are similarly uncompelling. This approach to finding putative response elements can uncover many false positives, and these should always be validated thoroughly. Don't get me wrong-I appreciate that these validations are not trivial, and I value the authors response element analysis.
I'm sceptical about the section of the paper that speculates about modification of steroid sensitivity in the HVC. These conclusions are based on analyses of mRNA expression of AKR1D1, SRD5A2, and the like. However, this does not reflect a different in the capacity to metabolize steroids, or at least there is little evidence to suggest this. Note that many of these transcripts have different isoforms, which could also influence steroidal metabolism.
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