Gunaratne et al. BMC Genomics 2011, 12:277
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RESEARCH ARTICLE
Open Access
Song exposure regulates known and novel
microRNAs in the zebra finch auditory forebrain
Preethi H Gunaratne1,2,3†, Ya-Chi Lin4†, Ashley L Benham1, Jenny Drnevich5, Cristian Coarfa11,
Jayantha B Tennakoon1, Chad J Creighton6, Jong H Kim1, Aleksandar Milosavljevic11, Michael Watson7,
Sam Griffiths-Jones8 and David F Clayton4,9,10*
Abstract
Background: In an important model for neuroscience, songbirds learn to discriminate songs they hear during
tape-recorded playbacks, as demonstrated by song-specific habituation of both behavioral and neurogenomic
responses in the auditory forebrain. We hypothesized that microRNAs (miRNAs or miRs) may participate in the
changing pattern of gene expression induced by song exposure. To test this, we used massively parallel Illumina
sequencing to analyse small RNAs from auditory forebrain of adult zebra finches exposed to tape-recorded
birdsong or silence.
Results: In the auditory forebrain, we identified 121 known miRNAs conserved in other vertebrates. We also
identified 34 novel miRNAs that do not align to human or chicken genomes. Five conserved miRNAs showed
significant and consistent changes in copy number after song exposure across three biological replications of the
song-silence comparison, with two increasing (tgu-miR-25, tgu-miR-192) and three decreasing (tgu-miR-92, tgumiR-124, tgu-miR-129-5p). We also detected a locus on the Z sex chromosome that produces three different novel
miRNAs, with supporting evidence from Northern blot and TaqMan qPCR assays for differential expression in males
and females and in response to song playbacks. One of these, tgu-miR-2954-3p, is predicted (by TargetScan) to
regulate eight song-responsive mRNAs that all have functions in cellular proliferation and neuronal differentiation.
Conclusions: The experience of hearing another bird singing alters the profile of miRNAs in the auditory forebrain
of zebra finches. The response involves both known conserved miRNAs and novel miRNAs described so far only in
the zebra finch, including a novel sex-linked, song-responsive miRNA. These results indicate that miRNAs are likely
to contribute to the unique behavioural biology of learned song communication in songbirds.
Background
Songbirds are important models for exploring the neural
and genomic mechanisms underlying vocal communication, social experience and learning (reviewed in [1]).
Songbirds communicate using both innate calls and
learned vocalizations (songs), and unique specializations
of the brain evolved to support this behavior (reviewed
in [2]). In the zebra finch, only the male produces
songs, although both sexes process and discriminate
specific songs [3-6]. The genome is actively engaged by
song communication, as first shown in an early
* Correspondence: dclayton@uiuc.edu
† Contributed equally
4
Department of Cell and Developmental Biology, University of Illinois,
Urbana-Champaign, IL 61801, USA
Full list of author information is available at the end of the article
demonstration of how gene responses in the brain discriminate among different song stimuli [7]. The genomic
response is not a simple correlate of neural activity and
it can vary significantly according to the salience and
behavioral context of the experience [8-13]. Recent studies using microarray technology have now shown that
song exposure affects the expression of thousands of
genes in the auditory forebrain [14,15]. Repeated exposure to one song leads to an altered gene expression
profile, correlated with habituation of both the behavioral and immediate genomic responses to that specific
song. These observations suggest the involvement of
large and dynamic transcriptional network in the recognition and memory of complex vocal signals [14].
MicroRNAs (miRNAs or miRs) are emerging as
potential control points in transcriptional networks, and
© 2011 Gunaratne et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly cited.
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may be particularly important for the evolution of brain
and behavior. Many miRNAs are expressed in the brain
[16], often in different patterns in different species
[17-19]. Brain miRNAs undergo dramatic changes in
expression during development [20-22] and aging [23]
and have been functionally implicated in neurological
disease [24]. They may also function in the normal physiological operation of the nervous system as suggested
by evidence for involvement of miR-132 and miR-219 in
circadian clock regulation [25] and miR-134 in control
of dendritic translation [26,27].
Here we apply massively parallel Illumina sequencing
to probe the involvement of miRNAs in the processing
of song experience in the zebra finch auditory forebrain.
We begin by identifying 155 different miRNA sequences
and the genomic loci of their precursor sequences in the
zebra finch genome, including 34 miRNA genes that
have not been detected in the genomes of other species.
We then ask whether the miRNA content changes after
song exposure and find robust evidence of miRNA
responses to song playbacks. We also assess correlations
between expression changes of a novel miRNA and its
predicted target mRNAs during song habituation. The
results indicate an active role for miRNAs in the neural
processing of a natural perceptual experience - hearing
the sound of another bird singing.
Results
The miRNAs of the zebra finch auditory forebrain
We carried out Illumina small RNA sequencing (RNAseq) on the small RNA (~18-30 nucleotides) fraction of
total RNA isolated from adult zebra finch auditory forebrain. Ultimately, we performed 6 Illumina runs on 6 different RNA samples, to assess the effects of song
exposure (next section). First we describe the overall
small RNA profile obtained by combining the results of
all the runs, representing 36 adult zebra finches (equal
numbers of males and females). A total of 20 million
reads were obtained (Table 1) and aligned to reference
miRNA sequences from other species (miRBase version
13.0). Overall we identified 107 non-redundant miRNAs
representing 52% of sequences that have been previously
identified in chicken, rodent and human. The remaining
sequences mapping to the piRNA database were denoted
as piRNA reads (~30%) (Additional File 1, Table S1).
Reads that did not align to known RNAs were
assessed for miRNA potential through a novel miRNA
discovery pipeline described by Creighton et al.[28]
which tests for properties that are characteristic of
known miRNAs. These properties include the following:
1) The mature sequence must map to the stem region
of the hairpin sequence of the putative precursor
extracted from the zebra finch genome. 2) The mature
miRNA sequence must map to the precursor such that
it can be processed following the Drosha processing
rules [29]. All novel miRNA candidates that map to the
loop region and/or lack appropriate Drosha processing
sites are failed. 3) Known miRNAs have stable 5’-ends
that vary at the most by +/- 1 nucleotide. 4) By contrast
the 3’-ends of miRNAs are highly heterogeneous in
length due to imprecise Dicer processing [29,30] and
exhibit non-templated nucleotide sequence changes due
to RNA editing [29-31]. 5) Consequently, the putative
precursor must give a strong signal of sequence alignments in a tight area of 18-25 nucleotides. Small RNA
sequences that are distributed fairly evenly along the
entire length of the precursor are rejected since they
likely represent degraded products of a large RNA. The
candidates that also demonstrate the presence of the
miRNA star sequence (miR*) mapping on the opposite
side of the mature miRNA and occurring at a lower
abundance in the deep sequencing data are considered
to be confirmed novel miRNAs in zebra finch. Using
this pipeline (Figure 1) we discovered 48 putative novel
miRNAs that map on the zebra finch genome to a stem
loop structure that folds with a minimum free energy of
< -20 kcal/mol [32]. The complete analysis and mapping
information for all the novel miRNA candidates is given
in Additional File 1, Tables S2 and S3.
All novel miRNA candidates were mapped to genomic
loci in the zebra finch genome assembly [33], and also
to human and chicken genomes using the BLAT function of the UCSC Genome Browser (Additional File 1,
Table S3). In the zebra finch genome, the loci include
both annotated exons and introns as well as unannotated intergenic regions. Thirty-four (34) novel microRNAs uncovered from zebra finch are not presently
detected in the human or chicken genome assemblies.
Eleven (11) map to genome positions in chicken, and six
to positions in the human (with three of these found in
Table 1 Summary statistics for the read alignments
Male silence
Male song
Female silence
Female song
Mix silence
Mix song
Total Reads
2,704,778
2,056,391
3,173,108
3,546,038
3,962,050
4,738,528
Total Usable Reads
1,179,330
1,155,168
2,244,376
2,498,648
2,249,188
2,950,398
401,934
209,944
1,638,528
1,755,748
1,348,109
2,113,006
34%
18%
73%
70%
60%
72%
Reads aligning with
Total
known miRNA
Fraction
Six different pools of auditory forebrain were analyzed independently by Illumina small RNA sequencing, as described in the text.
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Figure 1 Pipeline with yields for analysis of putative novel miRNAs. 52 small RNA sequences did not align to miRBase reference sequences
and were assessed for miRNA potential. 48 sequences passed the minimum criteria and were categorized into three groups according to
strength of evidence (sequences are color-coded in Additional File 1, Table S3, as indicated). Seven (7) are confirmed novel miRNAs since they
had all the characteristics of known miRNAs and in addition also had a less abundant miR* sequence that maps on the opposite side of the
stem from the putative novel miRNA. These are labelled green in Additional File 1, Table S3. Twenty-one (21) putative novel miRNAs are highly
confident (labelled blue) since they also shared characteristics of known miRNAs but no sequence was found aligning to the miR* region. Given
that the miR and miR* sequences for most known miRNAs have vastly different copy numbers such that the miR* sequence is sometimes not
found, the highly confident candidates are also highly likely to be genuine novel miRNAs, Twenty (20) candidates (labelled grey) had a subset of
the characteristics of known miRNAs but not all and therefore were deemed potential candidates that require more evidence.
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males and females. In total, therefore, we performed
three independent “song-silence” pairwise comparisons
by small RNA-seq, with an overall sex balance but different sex ratios in each individual comparison. These second and third experiments were done six months after
the first and Illumina technology had improved by this
time so that we obtained twice as many read counts
(Table 1) - but again we normalized to the total mapped
read number in each individual sample for our statistic
analyses. As in the first experiment, we again observed
differential read counts for roughly a third of the miRNAs, but the identities of the miRNAs affected were
somewhat different in each comparison. This is summarized graphically as a Venn diagram (Additional File 2,
Figure S1), and comprehensive read count data are presented in Additional File 1, Table S4. Across all three
experiments, five conserved miRNAs showed changes
that were both significant and in same direction in all
comparisons (Table 2). For a number of other miRNAs,
including let-7f, an apparent effect of song exposure was
measured in all three experiments but the direction of
change was not consistent (Additional File 1, Table S4).
We performed TaqMan assays on RNA from additional
birds, probing for eleven of the “significantly affected”
miRNAs, and obtained fluorescent signals in PCR for
ten. In nine out of ten cases, we observed the same
direction of song response by TaqMan as in the small
RNA-seq experiment, although the P-value by TaqMan
was below 0.05 in only five cases (tgu-miR-124, tgumiR-29a, tgu-miR-92, tgu-129-5p, and tgu-miR-2954-3p,
Additional File 1, Table S4). The lack of statistical significance in the TaqMan assay for the others could
reflect differences in the sensitivity and resolution of
Illumina vs. TaqMan assays, or the operation of other
uncontrolled factors in our experiments that lead to
variability in the expression of some miRNAs.
The transcriptional response in the auditory forebrain
of zenk and other mRNAs is specific to song relative to
human but not chicken assemblies). Tgu-mir-2976 maps
to three loci in the finch and 14 in the chicken, indicating a probable expansion of this miRNA in the chicken
lineage. This putative novel miRNA is not currently
detected in the human assembly HG18. Tgu-mir-2985 is
intriguing as it is located within two stem loops within
the introns of two functionally related genes: the glutamate receptor subunits GRIA2 and GRIA4 in all three
genomes.
miRNA responses to song exposure
When zebra finches are exposed to playback of a song
they have not heard recently, changes occur in the
expression of many different mRNAs as detected 30
min after stimulus onset [14]. To determine whether
specific miRNAs also change in expression, we counted
the Illumina reads in samples of RNA pooled from the
auditory forebrain of birds either 30 min after onset of
song playback (Song group) or from matched controls
(Silence group). In our first such experiment, the birds
in both groups were all males (n = 6 each). The read
count for each miRNA in each sample was normalized
to the total number of usable reads mapped in that sample. We then calculated the ratio of the normalized
count in the Song-stimulated condition compared to the
Silence condition and performed a Fisher’s exact test
(with correction for multiple testing) to evaluate
whether the ratio differed significantly from the range of
expected values at a 95% confidence interval. In the
initial experiment with males, 49 of the known conserved miRNAs showed a significant difference, with 28
decreasing and 21 increasing in the group exposed to
song (Additional File 1, Table S4).
To address the biological reproducibility of the miRNA
responses to song more broadly, we then repeated the
small RNA-seq comparison two additional times using
new groups of birds. In the second experiment, we used
only females, and in the third we used an equal mix of
Table 2 Conserved miRNAs with consistent responses to song exposure
Male
Silence Song Fold Change
Female
FDR-P
Silence
Song
Fold Change
Mix
FDR-P
Silence
Song
Fold Change
FDR-P
Increasing
tgu-miR-25
227
423
3.57
1.6E-27
55
212
3.60
1.4E-10
35
160
2.92
2.1E-05
tgu-miR-192
26
69
5.08
1.2E-06
36
90
2.33
5.5E-03
11
97
5.63
4.3E-06
6.3E-108
Decreasing
tgu-miR-92
359
100
0.53
1.1E-04
5479
5398
0.92
5.5E-03
7461
6887
0.59
tgu-miR-124
24624
7056
0.55
2.1E-251
56802
46434
0.76
1.1E-206
50955
77220
0.97
1.6E-04
tgu-miR-129-5p
2020
602
0.57
4.0E-19
9778
7272
0.69
2.8E-62
12128
9284
0.49
2.6E-293
Shown are the Illumina read data for the five miRNAs that show a consistent response to song (same direction of change, significant in all three comparisons).
“Song” and “Silence” list raw counts from the Illumina read analysis (Additional File 1, Table S4). “Fold Change” is the ratio of Song versus Silence read counts,
after the raw counts were normalized within each run to the sum of mapped reads for that sample. Thus a value of > 1 indicates a relative increase in the group
exposed to song, and < 1 indicates a decrease. “FDR-P” indicates the result of the Fisher’s exact test (FDR adjusted) for this comparison. See Additional File 1,
Table S4 for full list of values for all miRNAs, and associated TaqMan values for a subset of these miRNAs (measured in a different set of males and females).
Gunaratne et al. BMC Genomics 2011, 12:277
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non-song auditory stimuli [6,7,34,35]. To test for songspecificity of the miRNA response, we conducted a
further TaqMan experiment assessing the levels of six
miRNAs (tgu-miR-124, tgu-miR-92, tgu-miR-129-5p,
and three miRNAs derived from the tgu-miR-2954
locus, next section), in birds who had heard either a
normal song or a carefully matched non-song acoustic
stimulus, “song enveloped noise” (SEN). SEN has the
same amplitude envelope as the song from which it is
derived but spectral content has been randomized so it
does not sound like a song [34]. By TaqMan PCR, we
confirmed that normal song induced a larger increase in
zenk mRNA in these birds than did SEN (Additional
File 2, Figure S3 panel D). In these same animals, normal song, but not SEN, triggered a significant decrease
in the levels of tgu-miR-124, tgu-mir-129-5p, tgu-miR92 and tgu-miR-2954-3p (Additional File 2, Figure S3
panels A-C, H). Thus we conclude that there is indeed a
unique miRNA response in the auditory forebrain that
is selective for song over non-song acoustic stimuli.
A complex sex-linked miRNA locus in zebra finch and
other birds
The novel miRNA, tgu-mir-2954, that was detected
most frequently in our Illumina assays maps to the
sense strand of an intron in the XPA gene, on the Z
chromosome (Figure 2A). The precursor hairpin contains reads from both arms, thus meeting our bioinformatic criteria for a confirmed miRNA (Figure 2B). By
contrast to most known miRNAs, the numbers of reads
from both 5’ and 3’ arms were found at similar copy
numbers, suggesting that both arms may make functional mature miRNAs. BLAST analysis of the mir-2954
hairpin precursor sequence against the NCBI nr database identified a putative mature miRNA in chicken (gi|
145279910|emb|AM691163.1|), and BLAT analysis of a
collection of transcripts from crocodile and 11 other
bird species [36] detected mir-2954 transcripts in 2 nonpasserine species (two hummingbirds) and 3 passerine
species (the American crow, the pied flycatcher, and the
golden collared manakin) (Additional File 2, Figure S2).
There was no BLAT hit in the crocodile, the remaining
3 non-passerine birds (Emu, budgerigar, and ringneck
dove), and 3 passerine species (collared flycatcher, blue
tit and Eastern phoebe). The lack of a hit does not
necessarily mean absence of the gene as these datasets
represent incomplete transcriptomes derived by 454
sequencing [36]. These results clarify that the sequence
is not unique to the zebra finch or passerines, but may
nevertheless have a restricted distribution within birds.
To validate the existence of these two miRNAs in
zebra finch, we performed TaqMan analyses for both,
using their reverse complements as controls. Interestingly, we got significant expression values not only for
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the predicted miRNAs but also for one of the reversecomplement miRNAs (tgu-miR-2954R-5p) although no
significant song regulation for miR-2954R-5p was found
(Additional File 2, Figure S3 panels I-J). With respect to
the XPA gene within which this locus is embedded (Figure 2A), these data suggest that precursor-miRNA-stem
loops are produced from both the sense (same orientation as XPA) and antisense strands. The stem loop precursor processed by Drosha from the sense RNA (tgumir-2954) generates two active miRNAs from its both
arms (tgu-miR-2954-3p and tgu-miR-2954-5p). The
stem loop precursor processed by Drosha from the antisense RNA (tgu-mir-2954R) generates at least one active
miRNA (tgu-miR-2954R-5p) from its 5’ end sequence.
We carried out Northern analysis on tgu-miR-29543p, which is the miRNA that has the highest number of
read counts detected in our Illumina assays among the
three miRNAs from the tgu-mir-2954 locus. A robust
signal at ~22 nucleotides is evident in mixed-sex pools
of RNA from birds hearing either song or silence, and a
weaker signal is also detectable in two female-only pools
of RNA (Figure 2C). Greater expression in males is consistent with the ZZ genotype of males and the lack of
efficient sex chromosome dosage compensation in the
zebra finch [37,38].
By TaqMan as well as by Illumina, we observed an
apparent sex difference in the direction of the response
of tgu-miR-2954-3p to song - up in males and down in
females (Figure 3 and Additional File 1, Table S4). This
suggests this locus may be under complex regulation,
integrating information about sex, auditory or social
experience and perhaps also other factors related to
XPA gene expression.
To gain insight into the potential functional role of
tgu-miR-2954-3p in the response to song, we used a
conservative strategy to predict gene targets that are
both conserved in birds and responsive to song exposure in the zebra finch. Potential targets of miRNAs are
described as mRNAs that have sequences that can
undergo Watson-Crick base pairing with the 5’-seed
(nucleotide 2-7) of the miRNA [39]. For target prediction we applied the TargetScan (5.1) algorithm using the
chicken genome as an initial reference, and then confirmed presence of the target sequence in the zebra
finch. For evidence of song responsiveness, we used the
data set of Dong et al. [14]. Eight genes met all these
criteria (Table 3) and are thus both song-responsive and
also subject to regulation by tgu-miR-2954-3p. These
genes all have functions in control of cell proliferation
or neurite outgrowth (see below).
Discussion
Here we show that a natural perceptual experience,
hearing the sound of another bird singing, alters the
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Figure 2 The genome locus for tgu-mir-2954 produces three different miRNAs. A. Alignments via the UCSC Genome Browser of the three
detected miRNAs to the intron of the zebra finch XPA gene. B. Hairpin precursors for the three miRNAs. C. Northern blot analysis using an RNA
probe complementary to novel miRNA tgu-miR-2954-3p.
profile of miRNAs in parts of the songbird brain responsible for auditory perception, integration and memory.
The song-regulated population includes both known
(conserved) and novel miRNAs. We highlight one sexlinked song-responsive miRNA and identify mRNAs
that are potential targets of its action during song exposure. Thus miRNAs may have roles in the information
processing functions of the brain, in addition to their
roles in brain development and evolution.
To demonstrate this, we first catalogued the miRNAs
expressed in the adult zebra finch auditory forebrain.
We used massively parallel Illumina sequencing of small
RNAs to perform this cataloguing efficiently. In addition
to known conserved miRNAs, our analysis identified 48
small RNA sequences that meet the structural criteria
for miRNAs but had not been described in miRBase in
any organism at the time of our analysis. Fourteen of
these are detected in the chicken or human genome
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A. TaqMan
B. Illumina
Figure 3 Analysis of miRNAs produced at the tgu-mir-2954 locus. TaqMan and Illumina RNA-seq data generated from independent sets of
birds (n = 6 in each data set) for expression from the tgu-mir-2954 locus. A) TaqMan results, where the relative gene expression of each
individual bird (open circle) was obtained by using the 2^-ddCt method [98]; the relative gene expression of either Silence (white bar) or Song
(gray bar) group was the mean of six individuals; the P value was calculated by paired t test since each song stimulated animal was explicitly
paired with a silence control animal collected simultaneously. B) Read counts from the Illumina RNA-seq for miR-2954-3p and miR-2954-5p (also
shown in the Additional File 1, Table S4).
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Table 3 Song-regulated targets of tgu-miR-2954-3p
Ensembl ID
Gene Symbol
EST
Gene Name
ENSTGUG00000001349 ELAVL2
CK313262 ELAV-like protein 2 (Hu-antigen B)(HuB)(ELAV-like neuronal protein 1)(Nervous system-specific
RNA-binding protein Hel-N1)
ENSTGUG00000001404 LINGO2
DV957508 Leucine-rich repeat and immunoglobulin-like domain-containing nogo receptor-interacting
protein 2 Precursor (Leucine-rich repeat neuronal protein 6C)(Leucine-rich repeat neuronal
protein 3)
ENSTGUG00000003073 TLK2
CK305975 Serine/threonine-protein kinase tousled-like 2 (EC 2.7.11.1)(Tousled-like kinase 2)(PKU-alpha)
ENSTGUG00000008207 BTG1
CK303273 Protein BTG1 (B-cell translocation gene 1 protein)
ENSTGUG00000008540 CHD2
DV958991 Chromodomain-helicase-DNA-binding protein 2 (CHD-2)(EC 3.6.1.)(ATP-dependent helicase
CHD2)
ENSTGUG00000010181 XP_002196848.1 CK304764 crk-like protein (v-crk avian sarcoma virus CT10 oncogene homolog-like) (CRKL)
ENSTGUG00000010364 NEGR1
DV954047 Neuronal growth regulator 1 Precursor
ENSTGUG00000011700 HMGB1
CK314519 High mobility group protein B1 (High mobility group protein 1)(HMG-1)
We used TargetScan to find binding sites of tgu-miR-2954-3p on eight chicken genes and here are listed the information of their homologous genes in the zebra
finch genome including Ensembl IDs, Gene Symbols, EST (Accession numbers of song-regulated EST identified in the previous microarray study) and Gene Names
(or aliases in parenthesis).
assemblies and may give rise to miRNAs that have not
yet been described elsewhere due to low copy number,
restricted tissue distribution or other factors. The
remaining novel miRNAs, 34 in number, may be unique
to the zebra finch or the songbird lineage. Few studies
have attempted de novo identification of miRNAs from
the brain [18] and ours is the first to report direct
sequencing of songbird brain miRNAs. A previous study
did identify precursor sequences for five conserved miRNAs in the developing zebra finch brain [40]. Also, in
parallel with our own Illumina analysis, Li and her colleagues used 454 sequencing to identify miRNAs in the
brain and liver of adult zebra finches. These different
sets of annotations are compared and collated in a supplement to the analysis of the zebra finch genome
assembly [33].
By comparing birds hearing novel song playbacks or
silence, we found evidence for experience-dependent
fluctuations in large numbers of miRNAs in the auditory
forebrain. We performed three separate pairwise comparisons by Illumina, where all aspects of the experimental conditions were carefully counterbalanced
between the two groups in each comparison. The three
comparisons were not direct replications of each other,
as each had a different sex ratio. Our reasons for varying
the sex ratio were partly pragmatic (limited numbers of
birds of the same sex that could be removed from our
aviary) and partly analytical (males and females have different behavioral responses to songs). Some of the differences between the three sets of results may reflect
real biological differences in the responses of males and
females. Indeed, our Northern analysis of the tgu-miR2954-3p confirms a sex difference in expression of this
Z-linked miRNA gene. This is especially intriguing
because we also obtained TaqMan evidence for both
sense and antisense transcripts of this miRNA. One can
imagine scenarios where different ratios of sense and
antisense transcription occur in males (two copies of the
gene) and females (one copy of the gene) with different
consequences on the transcriptional networks affected
by song exposure in the two sexes.
Ignoring the potential effects of sex, we identified five
miRNAs that showed significant and consistent changes
in response to song across all three Illumina comparisons. Three miRNAs consistently decreased after song
(tgu-miR-92, tgu-miR-124, tgu-miR-129-5p) and two
increased (tgu-miR-25, tgu-miR-192). The down-regulated miRNAs are at much higher abundance (> 1000
reads in each run) and perhaps for this reason we were
more successful at detecting them and replicating their
song regulation by TaqMan assay in subsequent experiments with additional groups of birds. The most abundant miRNA in our regulated set, tgu-miR-124,
consistently met the statistical test for significant downregulation by song, in each of six separate experiments
(three Illumina comparisons, two TaqMan analyses in
Additional File 1, Table S4, and the TaqMan comparison of song vs. SEN in Additional File 2, Figure 3).
In studies in other species, miR-124 has been linked to
brain plasticity and development in several contexts.
Chronic cocaine administration results in down-regulation of miR-124 in the rodent mesolimbic dopaminergic
system [41]. In the developing chick neural tube, miR124a is a component of a regulatory network that controls the transition between neural progenitors and
post-mitotic neurons [42]. miR-124 also regulates adult
neurogenesis, and its overexpression promotes neuronal
differentiation [42,43] and neurite outgrowth [44]. Intriguingly, in songbirds neurogenesis continues in the forebrain throughout adulthood, from a population of
precursor cells that line the walls of the lateral ventricles
and have the characteristics of neural stem cells [45-47].
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The net rate of neuronal addition and loss in the adult
songbird has been shown to depend on social and environmental influences [48-51]. Perhaps tgu-miR-124 is a
regulatory link between experience and neurogenesis further study of this fascinating possibility is clearly
warranted.
Although miRNAs can have diverse functions, they
often act by altering the concentrations of specific
mRNAs they target via complementary base pairing. We
used the TargetScan algorithm [52] to predict binding
sites of tgu-miR-2954-3p in chicken genes, and then we
confirmed the presence of the same conserved target
sequence in the zebra finch genome assembly. We
found eight targets that met these criteria and were also
regulated by song in the Dong et al. microarray data
[14]. These eight genes have a provocative coherence in
their function, as they are all implicated in control of
cell proliferation and neuronal differentiation. Six operate by affecting gene expression and chromatin remodeling as we briefly review here. ELAVL2 is a member of a
protein family that binds AU-rich regions in the 3’UTR
of genes such as c-fos and promotes the shift from cell
proliferation into cellular differentiation [53-57]. TLK2
is a kinase tightly associated with DNA replication during cell division [58]. At least one of its targets, the histone chaperone Asf1, controls chromatin assembly, thus
TLK2 activity can regulate transcription and elongation
[59-61]. BTG1 is also regulated during the cell cycle
[62]. It acts as a cofactor for Hoxb9, a transcription factor that controls cell proliferation and differentiation,
and BTG1 reduces rates of cell proliferation [62-64].
CHD2 can potentially affect transcription of many genes
by remodeling chromatin [65,66]; disruption of CHD2
has profound consequences for development and is
implicated in many human diseases [67-69]. HMGB1 is
another DNA binding protein that facilitates transcription by altering chromatin structure to ease promoter
binding [70-73]. Some of the genes regulated by
HMGB1 may play a role in cell proliferation and migration [74,75]. Neuronal migration and neurite outgrowth
are affected by CRKL, a transcriptional activator that is
a component of the reelin pathway [76-79]. Unlike the
other six genes, NEGR1 and LINGO2 do not seem to
alter transcription but they do have established roles in
neuronal differentiation. NEGR1 affects cell-cell adhesion to modulate neurite outgrowth and synapse formation [80-82]. LINGO2 is one member of a family of
transmembrane proteins that are involved in neural and
axonal regeneration [83,84]. The function of LINGO2 is
untested, but expression of a related protein, LINGO1,
is attenuated in cortical areas deprived of sensory input
and is a partner in a signaling pathway that correlates
with neuronal activity during a learning paradigm
[85,86].
Page 9 of 14
Conclusions
In conclusion, these data reveal a network of miRNAs in
the zebra finch’s auditory forebrain, responsive to the
experience of hearing another bird sing. The network
includes well-characterized conserved miRNA known to
have roles in neuronal differentiation (miR-124), and
novel miRNAs that can target genes that control neuronal differentiation (tgu-miR-2954-3p). Our data suggest
this miRNA network may influence the fundamental shift
we have observed in the transcriptional and metabolic
state of the auditory forebrain during the process of
song-specific habituation [14,87]. Further study of song
responses in the zebra finch may reveal general insights
into the neurogenomic mechanisms that underlie learning, memory and the ongoing adaptation to experience.
Methods
Song stimulation and brain dissections
Zebra finches were obtained from aviaries maintained at
the University of Illinois. All procedures involving animals were conducted with the approval of the University
of Illinois Institutional Animal Care and Use Committee. The birds were raised in a standard breeding aviary
and were tutored under normal social conditions (i.e.,
by their parents or other adult birds in the breeding colony). All birds used in this study were adults (older than
90 days after hatching). The song playback procedures
and brain dissections were performed exactly as in previous microarray analyses, using the same equipment
[14,88]. Briefly, each bird was put individually into a
sound isolation chamber for 18 hours on the first day,
and on the second day those in the song group heard
30 minutes of a song not heard previously ("novel
song”). Matched controls collected in parallel heard no
song playback ("silence”). Birds were sacrificed in songsilence pairs, so that 5 minutes before the end of the
song playback to one bird, a bird in the silence group
was sacrificed and its auditory forebrain was dissected
and frozen in dry ice. Then the auditory forebrain of the
song-stimulated bird was dissected and frozen in dry
ice. The auditory forebrain dissection (also referred to
as auditory lobule) is described in [89] and collects
NCM (caudomedial nidopallium), CMM (caudomedial
mesopallium) and the enclosed Field L subregions. At
the end of the song stimulation procedure, all auditory
forebrains were transferred and stored at -80C until
RNA isolation. For the comparison of responses after
overnight isolation to song versus SEN (Additional File
2, Figure S3), we used two matched stimuli derived
from bird “C7” as previously described [34].
RNA Samples
For Illumina analyses: Total RNA was extracted using
the mirVana miRNA Isolation Kit (Ambion) from three
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pairs of pooled auditory forebrain samples. 1) Males
(samples S7 and S8): 6 birds per pool, collected in
November 2008. 2) Females (samples S1 and S2): 6
birds per pool, collected in May 2009. 3) Mixed (samples S3 and S4), 3 males and 3 females each pool, collected in May 2009. Samples with odd numbers were
from birds hearing song, and even number hearing
silence.
For Northern analysis: Auditory forebrains of 22 birds
(12 females and 10 males) were collected in April 2009,
and total RNA was extracted by Tri-Reagent (Ambion).
Male and female samples were pooled after extraction.
For TaqMan analysis: Analyses were performed on
total RNA extracted either by mirVana or Tri-Reagent
(Ambion), from the auditory forebrains of individual
males or females, collected in April-August 2009, March
2010 or December 2010.
Illumina small RNA sequencing and novel miRNA
discovery
Fifteen micrograms of total RNA from auditory forebrain of song bird samples described above were gelfractionated to isolate 18-30 nt small RNAs. 3’ and 5’
adapters were ligated to the small RNAs and constructs
amplified following RT-PCR following the conditions
specified in the small RNA kit (FC-102-1009, Illumina)
protocol. The small RNA library was sequenced using a
Solexa/Illumina GA-1 Genome analyzer. Small RNA
sequences were analyzed through a high-throughput
computational pipeline described by [28,29,90,91]. To
identify zebra finch miRNAs that are also conserved in
chicken, human and mouse, we performed a local
Smith-Waterman alignment of each unique sequence
read against each of the mature miRNAs in miRBase
version 13.0 for each of these species. We allowed for a
3 base overhang on the 5’ end and a 6 base overhang on
the 3’ end. In the case of redundantly aligning reads,
mature miRNA sequences were equally apportioned
among each of the hairpins. For each sample, all
sequence reads were aligned to a reference set of precursor miRNAs from miRBase version 13.0. The reads
that did not align to any known miRNA were passed to
our novel miRNA discovery platform as previously
described [28]. Briefly, each sequence is first mapped to
the reference genome sequence (WUGSC 3.2.4) and 200
bases of flanking sequence are extracted to further
define the putative hairpin. This extracted sequence is
then folded using the Vienna RNA folding package [92]
and those sequences that form a plausible hairpin are
selected as potential novel miRNA hairpins. These candidates are filtered through a set of three Ambros criteria: 1) the mature putative miRNA sequence must rest
on one side of a single hairpin; 2) the putative miRNA
sequence must bind relatively tightly within the hairpin
Page 10 of 14
stem containing no large or energetically unfavorable
loops; and 3) the putative hairpin must have a miRNAappropriate energy (free energy below -20 kcal/mol). All
sequences that passed were then carefully curated to
determine if Drosha and Dicer processing could yield
the resulting mature sequence from the predicted hairpin. These candidates are then divided into four different categories: “not likely”, “potential”, “high
confidence”, and “confirmed” (as in red, gray, blue and
green colors in Additional File 1, Tables S2 and S3).
Candidates that are flagged red as “not likely” either
failed to map in a pile of sequences in a very tight space
of 15-25 nt of the predicted hairpin (e.g. were scattered
evenly across the full length of the hairpin), mapped
within the loop of the hairpin, or mapped to known
tRNAs or rRNAs. Candidates that passed all of the
above criteria, and also mapped within a hairpin with
predicted Drosha and Dicer cut sites were categorized
as “high confidence” (blue annotation in Additional File
1, Tables S2 and S3). All high confidence candidates for
which we detected both the mature sequence and the
putative star sequence from the same hairpin we categorized as “confirmed” (green annotation in Additional
File 1, Table S3). In addition to miRNA precursors, the
reads were also mapped to the reference zebra finch
genome using the Pash software package [93,94], and
uploaded to the Genboree platform (http://www.genboree.com) to identify potential mappings to piRNAs,
snoRNAs and other annotations in addition to miRNAs
(data shown in Additional File 1, Table S1). PiRNAs (i.
e., Piwi-interacting RNAs) have a central role in the
maintenance of the integrity of genomes through the
silencing of transposable elements [95]. SnoRNAs (small
nucleolar RNAs) function in site-specific ribosomal
RNA modification, rRNA processing and more recently
have been found to guide alternate splicing and RNA
editing of mRNA transcripts [96].
TaqMan qPCR
To measure the mature miRNA, the TaqMan MicroRNA Assay Kit (Applied Biosystems) was used according to the manufacturer’s instructions. Probe sequences
used for each target miRNA are given in Table 4.
Northern Blot Analysis
Northern blotting to confirm novel miRNA tgu-miR2954-3p was performed by modifying the protocol of
[97]. 2 μg of total RNA was heated at 65°C for 5 min
with 2X loading dye (Ambion), quenched on ice, and
loaded on a 15% TBE Urea gel (Invitrogen). Total RNA
was separated by electrophoresis at 200V for 50 min.
The gel was stained with with EtBr in 1x TBE (4 μL of
10 mg/ml EtBr per 100 ml of 1x TBE) for 3 minutes with
gentle shaking and transferred to nylon membrane for 90
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Page 11 of 14
Table 4 Probes used for Taqman analysis of specific miRNA sequences
miRBase name
Company name
Sequence detected
tgu-let-7a
let-7a
5’-UGAGGUAGUAGGUUGUAUAGUU-3’
tgu-let-7f
let-7f
5’-UGAGGUAGUAGAUUGUAUAGUU-3’
tgu-miR-124
miR-124
5’-UAAGGCACGCGGUGAAUGCC-3’
tgu-miR-9
miR-9
5’-UCUUUGGUUAUCUAGCUGUAUGA-3’
tgu-miR-129-5p
miR-129-5p
5’-CUUUUUGCGGUCUGGGCUUGC-3’
tgu-miR-129-3p
miR-129-3p
5’-AAGCCCUUACCCCAAAAAGCAU-3’
tgu-miR-29a
miR-29c
5’-UAGCACCAUUUGAAAUCGGU-3’
tgu-miR-92
tgu-miR-25
miR-92a
miR-25
5’-UAUUGCACUUGUCCCGGCCUGU-3’
5’-CAUUGCACUUGUCUCGGUCUGA-3’
RNU6B
RNU6B
5’-CGCAAGGAUGACACGCAAAUUCGUGAAGCGUUCCAUAUUUUU-3’
tgu-miR-2954-5p
novel51F-5p
5’-GCUGAGAGGGCUUGGGGAGAGGA-3’
tgu-miR-2954-3p
novel51F-3p
5’-CAUCCCCAUUCCACUCCUAGCA-3’ (Northern validated)
tgu-miR-2954R-5p
novel51R-5p
5’-UGCUAGGAGUGGAAUGGGGAUG-3’
tgu-miR-2954R-3p
novel51R-3p
5’-UCCUCUCCCCAAGCCCUCUCAGC-3’
min at 200V using 1X TBE buffer at room temperature.
The membrane was cross-linked at 1200 kJ for 45 seconds. RNA probes were synthesized for tgu-miR-2954-3p
probe 5’ - UGCUAGGAGUGGAAUGGGGAU G - 3’ by
Integrated DNA Technologies. Radio labeling was carried
out in a reaction of 12.0ul dH2O + 2.0ul PNK buffer +
1.0ul (100ng/ul) probe + 1.0ul PNK polymerase (Promega) + 4.0ul P32-gamma-ATP (10mCi/ml) (PerkinElmer). The reaction was incubated at 37°C for 1 hour and
inactivated at 65°C for 10 min. The probe was purified
using Nick columns from GE following manufacturer’s
instructions. The membranes were pre-hybridized for 30
min with 20 ml of pre-hybridization buffer (5X SSC + 20
mM NaPO4 + 7X SDS + 2X Denhardt (pre warmed) at
60° C) in a rotating hybridization oven. Hybridization
was carried out at 50°C in a rotating incubator for 24h.
The membranes were washed for 10 min at 50°C with
20-30mL of wash buffer (2X SSC + 0.5% SDS). When
background was ~0.5 cpm, the membranes were
wrapped in saran wrap and exposed at -80°C for ~72h.
Additional material
Additional file 1: Supplemental tables.xls. This one file contains all
four Supplemental Tables, each as a separate worksheet. Table S1 ("1
overview”) is a summary of Illumina sequence read alignments for six
pools of RNA from zebra finch auditory forebrain responding to song
versus silence, and shows the distribution of sequence reads in relation
to multiple genomes and multiple annotations in the current genomic
databases. Table S2 ("2 novel hairpins”) gives detailed alignments of
putative pre-miRNAs and read sequences. Table S3 ("3 novel genes”)
shows annotations of all novel miRNA loci mapped in genome
assemblies of zebra finch, chicken or human. Table S4 ("4 all read
counts”) gives read counts and current annotation in miRBase of all
conserved and novel miRNAs, with statistics.
Additional file 2: Supplemental figures.doc. This one file contains all
three supplemental figures. Figure S1 is a Venn diagram of numbers of
miRNAs with significant differential expression in response to novel song
in three Illumina experiments. Figure S2 shows a comparative mapping
in other avian transcriptomes of tgu-mir-2954. Figure S3 demonstrates
the song-specificity of the miRNA response, using TaqMan to compare
the levels of specific miRNAs in animals from groups that heard song,
matching song-enveloped noise, or silence.
Acknowledgements
We thank Sarah London for useful discussions and contributions to the text.
Supported by NIH RO1 NS045264 and RO1 NS051820 (to D.F.C).
Note Added in Proof:
The novel miRNA referred to here as “miR-2954-3p” is now identified in
miRBase as “miR-2954”. The novel miRNA referred to here as “miR-2954-5p”
is now identified in miRBase as “miR-2954*”.
Author details
1
Department of Biology and Biochemistry, University of Houston, Houston,
Texas 77204, USA. 2Departments of Pathology, Baylor College of Medicine,
Houston, Texas 77030, USA. 3Human Genome Sequencing Center, Baylor
College of Medicine, Houston, Texas 77030, USA. 4Department of Cell and
Developmental Biology, University of Illinois, Urbana-Champaign, IL 61801,
USA. 5W.M. Keck Center for Comparative and Functional Genomics, Roy J.
Carver Biotechnology Center, University of Illinois, Urbana-Champaign, IL
61801, USA. 6Dan Duncan Cancer Center, Baylor College of Medicine,
Houston, TX 77030, USA. 7ARK-Genomics, The Roslin Institute and R(D)SVS,
University of Edinburgh, Easter Bush, EH25 9RG, UK. 8Faculty of Life Sciences,
University of Manchester, Manchester, M13 9PT, UK. 9Institute for Genomic
Biology, University of Illinois, Urbana-Champaign, IL 61801, USA. 10Beckman
Institute, University of Illinois, Urbana-Champaign, IL 61801, USA.
11
Bioinformatics Research Laboratory (BRL), Department of Molecular &
Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
Authors’ contributions
PHG coordinated the work of Illumina RNA-seq and prepared the
manuscript. YL conducted the song exposure experiments and subsequent
dissections and RNA extractions, performed TaqMan qPCR, analyzed
differentially expressed miRNAs and participated in drafting the manuscript.
ALB performed Illumina RNA-seq and Northern blot. JD helped analyze
expression data of Illumina RNA-seq and TaqMan qPCR. CC, JBT, CJC, JHK,
and AM participated in mapping and analyzing Illumina RNA-seq data. MW
and SGJ helped with miRNA sequence annotation. DFC designed and
coordinated the study and drafted the manuscript. All authors read and
approved the manuscript.
Received: 28 July 2010 Accepted: 31 May 2011 Published: 31 May 2011
Gunaratne et al. BMC Genomics 2011, 12:277
http://www.biomedcentral.com/1471-2164/12/277
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doi:10.1186/1471-2164-12-277
Cite this article as: Gunaratne et al.: Song exposure regulates known
and novel microRNAs in the zebra finch auditory forebrain. BMC
Genomics 2011 12:277.
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