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Journal of Neuroscience Methods 157 (2006) 195–207

Expression profiling of intermingled long-range projection neuronsharvested by laser capture microdissection

Anthony J. Lombardino ∗, Moritz Hertel, Xiao-Ching Li 1, Bhagwattie Haripal,Laurel Martin-Harris, Eben Pariser, Fernando NottebohmLaboratory of Animal Behavior, The Rockefeller University, New York, NY 10021, United States

Received 14 February 2006; received in revised form 10 April 2006; accepted 10 April 2006

bstract

Gene expression data are most useful if they can be associated with specific cell types. This is particularly so in an organ such as the brain, whereany different cell types lie in close proximity to each other. We used zebra finches (Taeniopygia guttata), fluorescent tracers and laser captureicrodissection (LCM) to collect projection neurons and their RNAs from two interspersed populations from the same animal. RNA amplified

rom each cell class was reverse transcribed, fluorescently labeled, and hybridized to cDNA microarrays of genes expressed in the zebra finch brain.e applied strict fold-expression criteria, supplemented by statistical analysis, to single out genes that showed the most extreme and consistent

ifferential expression between the two cell classes. Confirmation of the true expression pattern of these genes was made by in situ hybridizationnd Taqman quantitative PCR (qPCR). High quality RNA was obtained, too, from backfilled neurons birth-dated with bromodeoxyuridine (BrdU).

e also quantified changes in the levels of three genes after singing behavior using qPCR. Thus, we have brought together a combination of

echniques allowing for the molecular profiling of intermingled populations of projection neurons of known connectivity, age and experience,hich should constitute a powerful tool for CNS research.2006 Elsevier B.V. All rights reserved.

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eywords: Laser capture microdissection; Projection neuron; Motor behavior;

. Introduction

Cell types differ in the genes they express and in the transcrip-ional levels of those genes. It is not known exactly how manyell types exist in the mature nervous system, but neurons maye the most diverse of all cell classes. This complicates mattershen studying what genes are expressed in different parts of

he brain. Different subtypes of neurons are distinguished onhe basis of connectivity, location, morphology, transmitters,nd electrophysiological properties, among other attributes.olecular signatures for specific subclasses of neurons are

eginning to be defined through analyses of the transcriptomesf particular classes of neurons (Bonaventure et al., 2002; Bi etl., 2002; Ginsberg and Che, 2004; D’Hellencourt and Harry,

Abbreviations: BrdU, bromodeoxyuridine; CTB, cholera toxin subunit B;VC, high vocal center; ISH, in situ hybridization; LCM, laser capture microdis-

ection; qPCR, quantitative PCR; RA, robust nucleus of arcopallium∗ Corresponding author. Tel.: +1 212 327 8381; fax: +1 212 327 8312.

E-mail address: lombara@mail.rockefeller.edu (A.J. Lombardino).1 Responsible for the construction of the zebra finch cDNA microarray.

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165-0270/$ – see front matter © 2006 Elsevier B.V. All rights reserved.oi:10.1016/j.jneumeth.2006.04.026

expression; Microarrays

005). These studies provide a snapshot in time of mRNAevels in these cells, and provide insights into the moleculareterogeneity of the brain. Even a widely accepted class ofeurons, such as hippocampal CA1 neurons, have been showno have a diversity of expression profiles when compared withne another (Kamme et al., 2003). To better understand theeuronal diversity, one needs studies of expressed RNAs fromell-defined neuron classes, preferably after specific functional

tates, so that gene expression differences can be related to bothell class and recent experience.

We wanted to study how neuronal age and experience affectene expression in two different, yet intermingled, populationsf projection neurons in the high vocal center (HVC) of theongbird forebrain. The HVC of zebra finches offers excep-ional material for relating the properties of two classes ofong-range projection neurons to a complex, learned behaviorNottebohm et al., 1976; Hahnloser et al., 2002). Moreover,

nly one HVC projection neuron class continues to be producednd replaced in adulthood (Alvarez-Buylla et al., 1988, 1990;irn and Nottebohm, 1993; Scharff et al., 2000). Understandingow HVC’s projection neurons function during song learning

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nd production promises to yield significant insights into basicspects of learning and the execution of a learned motor behaviorFee et al., 2004; Doupe et al., 2004).

We used the well-established technique of injecting neuronalracers (Lanciego and Wouterlood, 2000; Oztas, 2003) to backfillVC’s projection neurons, and then harvested several hundredf each type using laser capture microdissection (LCM) underonditions that preserve RNA (Bonner et al., 1997). Expres-ion profiling these cells revealed that while most genes werexpressed at similar levels, others showed differential expres-ion. This differential expression was confirmed and extendedy in situ hybridization (ISH) and Taqman quantitative PCRqPCR). We show that the expression of an immediate-early genencreases linearly with the number of songs produced during theour prior to killing. Finally, we show that these procedures areompatible with established immunohistochemical techniqueshat define neuronal age (Counts et al., 2005). Our combina-ion of techniques should be applicable to any nervous systemn which investigators wish to characterize in vivo gene expres-ion profiles from cellular components of specific neural circuits,ncluding changes in those profiles caused by experience.

. Materials and methods

.1. Animals and behavior

Twenty-three adult male zebra finches aged 6 months to 4ears, raised at the Rockefeller University Field Research Cen-er in Millbrook, NY, were used in the microarray study. For therdU experiments, two juvenile male zebra finches aged 45–50ays were used. The care of the animals used in our experimentsollowed the standards set by the American Association of Lab-ratory Animal Care and the Rockefeller University Animal Usend Care Committee. Prior to surgery to inject retrograde trac-rs all birds were recorded while singing to a female finch withSennheiser MKE 2 Gold lavelier condenser microphone con-ected to a Tascam DAP1 portable digital audio tape (DAT)layer, with all sounds digitized at 44 kHz. Songs were trans-erred to a PC using a USB audio interface (Roland UA-30) andpectral derivates generated using Sound Analysis Pro softwarev. 1.04a) with default settings for zebra finches (Tchernichovskit al., 2000). For the purposes of routinely assessing changes toong caused by the surgery, these recordings were compared byisual inspection to those taken under the same conditions at var-ous time points after surgery. Song recordings were also madef birds in experiments comparing gene expression in singingnd non-singing birds. Four behavioral protocols were used forhis work, covering different time-courses of singing and dif-erent social contexts in which song was delivered. For all theserotocols, an adult male zebra finch was either presented at closeange with a female – which elicited the male’s directed singingMorris, 1954) – or was allowed to sing while alone, and thenhe male was killed as described in the next section. In the first

wo protocols, birds were allowed to sing to a female for 45 minN = 4) or 90 min (N = 5) and then killed. For the studies com-aring the effect that singing in a specific social context hadn immediate-early gene expression, male zebra finches previ-

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ience Methods 157 (2006) 195–207

usly injected with neuronal tracers (as described in the nextection) were allowed to sing for 25 min either in the presencef a female (N = 5, directed song) or by themselves (N = 6, undi-ected song), followed by 30 min during which the lights wereff, to prevent the bird from singing further. After the 30 min ofarkness, the birds were decapitated as described below. Songsere counted by first identifying the repeated unit (or ‘motif’,

ee Sossinka and Bohner, 1980) for each zebra finch’s song, andhen counting the number of times the motif was sung during theehavioral session just prior to sacrifice. The motif is the levelf analysis previously shown to most closely correlate with thehysiological activity of HVC-RA neurons (Hahnloser et al.,002).

.2. Surgical injection of tracers, brain dissection

Birds were anesthetized (ketamine 25 mg/kg and xylazine0 mg/kg) and injected bilaterally with cholera toxin B (CTB,% solution in sterile PBS) conjugated to AlexaFluor dyesMolecular Probes). These injections (40 nL per site, 4 siteser nucleus for a total of 16 injections per bird) were targetedtereotactically to nucleus RA and Area X using standard coor-inates, and after 3–12 days for retrograde transport the animalsere killed either prior to lights on in the morning (non-singing

ondition), or immediately following one of the singing proto-ols described above. Birds were killed by decapitation, 8 �L ofNAlater (Ambion, Austin, TX) was applied directly to HVCt the brain surface and the brains were frozen in a mold ofissue-Tek placed on a dry ice and ethanol slurry. The brainsere stored at −80 ◦C and were later sectioned on a cryostat

t 8 �m. The sections were stored at −80 ◦C until prepared forCM as described below.

.3. Laser capture microdissection (LCM) of identifiedopulations of projection neuron

Cell bodies from backfilled HVC-RA and HVC-X neuronsere identified by fluorescence in frozen tissue sections andicrodissected using a laser capture microscope (Pixcell IIe,rcturus Bioscience, Mountain View, CA). To maximize RNAield, we singled out for capture cells that were not overlappingith cells of the other backfilled type, that had large amounts ofuorescence and that, ideally showed much of the clear nucleusimmed by tracer fluorescence.

LCM employs a plastic cap that sits on top of a tissue section,nd an infrared laser beam is used to melt a small cone of plasticnto the tissue on top of the chosen cell. This can be done for

any cells in a section prior to lifting the cap and thus harvestinghe cells into which plastic has been melted by the laser. Confir-

ation that cellular material from the soma was removed fromhe sections came from seeing the retained fluorescent tracern the captured material, and this material was placed in con-act with 15 �L of RNA extraction buffer (PicoPure, Arcturus).

e microdissected 2000 HVC-RA neurons and 1500 HVC-Xeurons per bird from all regions of both HVCs, resulting in sim-lar amounts of RNA for each cell class. Seven birds were usedor the microarray analysis: three of them silent birds and four

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A.J. Lombardino et al. / Journal of N

inging. An additional 11 birds provided material as above thatas then used for qPCR confirmation of the expression patternredicted by the microarray data. The laser parameters for LCMere as follows: spot diameter 7.5 �m, laser power 65–74 mW,

aser duration 0.5–1.2 ms, 1–2 shots per cell. The tissue dehydra-ion regimen prior to LCM was as follows: thaw section 20–30 s,0 s 75% EtOH, 15 s H2O, 30 s 75% EtOH, 30 s 95% EtOH, 30 s00% EtOH, 1 min 100% EtOH, 3 min 100% EtOH, 2× 2 minylene, air dry 3 min.

.4. RNA purification, amplification, and confirmation ofhe linearity of amplification

RNA was column purified (PicoPure, Arcturus), treated withNase (Qiagen) on the column to remove genomic DNA, and

mplified through two rounds using the RiboAmp HS kit (Arc-urus), which is based on the linear T7 amplification techniqueeveloped by Eberwine and co-workers (Van Gelder et al., 1990;ee also Zhao et al., 2002). To determine the quality and yield ofhe aRNA that resulted from two rounds of linear amplification,e diluted 0.5 �L of eluted product 1:10 in RNase-free H2O,

nd measured 1 �L of this solution in duplicate on an Agilentioanalyer using the Nanochip. We used the remainder of the

olution to measure in triplicate the concentration of aRNA on aanoDrop ND-1000 spectrophotometer (NanoDrop Technolo-ies, Wilmington, DE). The yield of purified antisense amplifiedNA (aRNA) was approximately 90 �g for each neuron type perird, 400–1000 bp in length. A mean of the three NanoDrop mea-ures was taken to calculate the input aRNA for the microarraynd qPCR assays.

The linearity of the amplification process was confirmed bybtaining samples from 20, 50, 100, and 200 LCM laser shots1 shot per cell), purifying the RNA from these samples, andndependently amplifying it. The aRNA quality and yield weressessed by the Bioanalyzer and NanoDrop as described above,nd individual gene levels determined by Taqman as describedelow.

.5. cDNA microarray construction and arrayybridizations

Total brain mRNA from zebra finches of different develop-ental stages (embryonic, juvenile, and adult) was used to make

DNA libraries. The cDNA libraries were oligo-dT primed andloned into the EcoRI and NotI sites of pBluescript plasmid vec-or. Randomly picked clones were sequenced from the 3′-end,ielding 700–800 nucleotides of readable sequence. Sequencenalysis was performed with the MAGPIE system, a high-hroughput clone analysis and annotation program. Our microar-ay consisted of a random selection of 5000 unique, sequence-erified clones printed on a glass slide with a Genomics Solu-ions MicroGrid II arrayer. The entire array was printed inuplicate on each slide. Test slides showed a very high consis-

ency of hybridization, including one or two small areas (10–15lones-worth) of blurring, indicating the printing process wasighly reproducible. X-C.L. was responsible for the microarrayonstruction.

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ience Methods 157 (2006) 195–207 197

Based on the concentration measures from the Nanodroppectrophotometer, 2.5 �g of the two-round aRNA from eachrojection neuron type was reverse transcribed in the presencef Cy3- or Cy5-coupled UTP (Amersham Biosciences), respec-ively, in a direct labeling reaction. Additional replicate samplesn which the Cy-dye/projection neuron type association waswitched (a ‘fluor-flip’) were generated for each sample. OurDNA microarrays were hybridized with this labeled cDNA,sing a two-color experimental design, with the ProntoTM Plusystem (Corning Inc., Acton, MA). The cDNA from each bird’sVC-RA neurons was compared to that of its HVC-X neurons

i.e. within-animal comparisons). Including the fluor-flips, twoicroarray slides were run for each bird. Since each slide was

rinted with two complete microarrays, a total of four repli-ate arrays were run for each bird. The data analysis pooledhe microarray data from all 7 birds, giving each microarraypot 28 representations. After array hybridization, intensity read-ngs at each wavelength were imported to the software packageeneTraffic Duo (Stratagene, LaJolla, CA) for normalization

LOWESS subgrid method) and fold-change analysis of differ-ntial expression.

.6. Quantitative PCR, normalization, and generation oftandard curves

Microarray data are exploratory by nature, and require otherene expression techniques for confirmation (Chuaqui et al.,002). We chose to use Taqman qPCR to confirm the expressionattern predicted by our microarray data (Bustin, 2000). Ampli-ed RNA from 18 birds, including the 7 used for microarraynalysis, was used for qPCR analysis. Seven of the 18 birdsere non-singers and 11 were singers; those in the latter groupere killed either 45 min (N = 6) or 90 min (N = 5) after onset of

inging. Equal amounts of aRNA from HVC-RA and HVC-Xeurons from each of these birds were reverse transcribed usingandom decamers (Retroscript kit, Ambion). The cDNA wassed in Taqman qPCR assays with primers and probes (Appliediosystems, Foster City, CA) designed against zebra finch

equences using Primer Express software (Applied Biosystems)nd Taqman Universal Master Mix (Applied Biosystems). Theoncentration of primer was 900 nM and the concentration ofrobe 250 nM for all genes. Reactions were run in triplicate intotal volume of 25 �L, with the following cycling parameters:0 ◦C for 2 min, 95 ◦C for 10 min, 95 ◦C for 15 s, and 60 ◦C formin. ‘No template’ control wells were sprinkled throughoutll plates, and only plates showing a cycle threshold of at least8 cycles in the ‘no template’ wells were included in subsequentnalyses. Standard curves were constructed from five 10-folderial dilutions of PAGE-purified DNA (Sigma-Genosys)orresponding to the predicted amplicon; these were used toalculate absolute copy numbers in the amplified material,s described (Bustin, 2000). In all cases the r2 value forhis standard curve was greater than 0.990. Normalization of

aqman data was to total amplified RNA as measured on theanoDrop spectrophotometer. Student’s t-tests were used to

ssess the significance of differences between group means asndicated in the figure legends. QPCR analysis was performed

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n five zebra finch genes: synelfin, HTPAP, GAPDH, �-actinnd ZENK. All of these genes met our microarray criteria forifferential expression and could be homologized to knownammalian genes. Sequences of primers and sequences/labels

or the probes used to amplify these genes were as follows:ynelfin: Forward primer: ACAGGAGTGACGGCGGTG;everse primer: ACCAAACCAGTGGCTGCAG; Probe:FAM-AAGACCGTGGAAGGAGCAGGGAACATC-MGB-FQ; HTPAP: Forward primer: ATGTCCAGAGGAAGGC-GGA; Reverse primer: CCAAGAGCATGGTGAGCTGA;robe: 6FAM-ACAGTTTTCCACCAATCCCATCCCACAT-GBNFQ; GAPDH: Forward primer: ATGGCTTTCCGT-TGCCA; Reverse primer: TGGTTTTTCCAGACGGCAG;robe: 6FAM-CCCCTAACGTGTCTGTTGTGGACCTGA-GBNFQ; Actin: Forward primer: AATCGTGCGTGACAT-AAGG; Reverse primer: CAGCTGTGGCCATCTCCTG;robe: 6FAM-CTGTGCTATGTCGCCCTGGATTTCGA-GBNFQ; ZENK: Forward primer: ACCACATTCCCAT-CCCTTC; Reverse primer: GCCACTTGGGTTTGAAA-GTG; Probe: 6FAM-CAACCACTTACCCCTCTGGCACCG-GBNFQ.

.7. In situ hybridization

As a further confirmation of the pattern of expression pre-icted by our microarray data, and to visualize the pattern of genexpression in regions outside of HVC, we used in situ hybridiza-ion for a subset of the genes identified on our arrays. Theseenes were malonyl CoA decarboxylase, a Slit-like 1 familyember, decorin, the serotonin receptor 1B, a gene highly simi-

ar to phosphatidic acid phosphatase type 2B (HTPAP), synelfinthe zebra finch homolog of synuclein, George et al., 1995), andbiquitin carboxy-terminal hydrolase (UCHL1). Birds receivednjections of cholera toxin B conjugated to a fluorescent marker,s explained above, and were killed 3–11 days later. Fresh frozenections 6–12 �m thick were fixed in 4% cold fresh formalde-yde and hybridized with one million cpm of 33P UTP-labeledntisense probe as per standard in situ procedures, including pre-ybridization acetylation of the sections and a post-hybridizationNase digest. After dipping in X-ray film emulsion (Kodak), the

ections were exposed for 2–4 weeks and developed. The den-ity of silver grains over each of the two backfilled cell typesas examined under bright-field conditions, and compared to

he presence of CTB viewed under fluorescent conditions toetermine which projection neuron type showed a greater con-entration of silver grains overlying the cell nucleus. Theseesults were used to confirm the microarray and qPCR data.n this case our goal was to see if the autoradiography resultsgreed qualitatively with the other two analyses.

.8. BrdU immunohistochemistry in preparation for LCM

Slides containing frozen sections from birds injected with

rdU and CTB were thawed and fixed in 4% paraformaldehyde

n PBS for 10 min. After three PBS washes, the slides werelaced in 2N HCl (heated to 37 ◦C) for 30 min, followed by a0 min incubation in 0.1 M sodium borate buffer. After a 5 min

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ience Methods 157 (2006) 195–207

BS wash, the sections were blocked in 10% serum in 0.2%riton-X PBS for 30 min. Primary antibody (1:1000) againstrdU (DAKO) was applied overnight. After 3 PBX washes

he following day, secondary antibody (1:500) was appliedor 30 min, followed by 3 PBS washes of 5 min each. RNasenhibitor was included in all solutions. After the final PBS wash,he slides were dehydrated as described above in preparation forCM on cells labeled for both BrdU (a nuclear stain in green)nd CTB (a peri-nuclear stain in red).

. Results

.1. Song behavior is not affected by multiple injections ofuorescent CTB

No changes to the acoustic structure of each bird’s directedong were seen after multiple injections of CTB to nucleusA and Area X (Fig. 1B), whether birds were recorded daysr weeks after surgery (Fig. 1A). The long call, an additionalearned vocalization mediated by the HVC-RA pathway, waslso unchanged after CTB injection in these birds (data nothown). These data suggest that the neurons we were samplingere functioning normally despite the uptake and transport ofuorescent tracer and despite the multiple injections to theirfferent targets.

.2. Laser capture microdissection of two types ofrojection neurons from HVC

The song control system in oscine birds in shown schemat-cally in Fig. 1C, which depicts some of the key brain nucleinvolved in the acquisition and production of learned song. TheVC at the top of these circuits is set off from the surrounding

issue by its darker neuropil and its larger and more spaced neu-ons (Fig. 1D). HVC contains two types of projection neuron,hose axons project rostrally and caudally, respectively, to Area(a homologue of the mammalian striatum), and to the robust

ucleus of the arcopallium, RA (Fig. 1C), a structure homolo-ous to layer V of the mammalian motor cortex (Nottebohm etl., 1976, 1982; Nixdorf et al., 1989; Fortune and Margoliash,995; Dutar et al., 1998; Foster and Bottjer, 1998; Wild et al.,005). We call these neurons HVC-X and HVC-RA neurons,espectively (Fig. 1C). Whereas HVC-RA neurons are involvedith the acquisition and production of learned song, the HVC-Xeurons are part of an anterior forebrain pathway that is neces-ary for song acquisition, but not – once the song is learned –or its production (Bottjer et al., 1984).

Frozen frontal sections at the level of HVC were thawed andehydrated, and in these unstained sections HVC was identifiedy location and distinctive shape (Fig. 1D). Under UV light,he fluorescence of the tracers further confirmed the identity ofVC (Fig. 1E). At higher power, the smaller, more numerousVC-RA neurons (red in Fig. 1F) were easily distinguished

rom the larger, sparser HVC-X neurons (green in Fig. 1F). Weelected neurons for capturing (white arrows in Fig. 1F, see alsoig. 1G) based on their physical separation from the other neuronubtype, to reduce contamination. We expected that the pools of

A.J. Lombardino et al. / Journal of Neuroscience Methods 157 (2006) 195–207 199

Fig. 1. Laser capture microdissection of HVC projection neurons from the songbird brain. (A) Zebra finch showing the typical posture taken during singing directedto a female (off screen, to right of microphone). (B) Spectral representations of songs produced before (top) and after (bottom) injection of tracers show little orno change to the song structure (y-axis is frequency, x-axis is time, with the entire song occurring in about 0.5 s). (C) Schematic of the song system and of theconnectivity between some of its major nuclei, with injection sites to RA (red pipette) and Area X (green pipette) depicted. The inset depicts the red HVC-RA andgreen HVC-X neurons after they have been backfilled by tracer. (D) Dehydrated tissue section prior to laser capture, in which the outline of HVC can be seen as as ew ofn ghtedc the t

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lightly darker oval bordered by the lateral ventricle at top. The fluorescence vieurons at higher magnification. Four HVC-X neurons (white arrows) are highliells by the laser. (H) The four HVC-X neurons after they have been lifted from

NA we wished to profile were located around the nucleus in theell soma, the site where tracer fluorescence also accumulates.herefore, neurons were identified as suitable for capturing by

he following additional criteria: clear round nuclei or parts of

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this same field is shown in (E). (F) Red HVC-RA neurons and green HVC-Xfor capture. (G) The plastic from the LCM cap has been melted over these fourissue section. The same fluorescence filter set was used for (E–H).

uclei rimmed with fluorescence, with greater amounts of fluo-escence preferable to lesser amounts of fluorescence, and withome separation from cells of the other backfilled type. Theseriteria assured that we captured cells that had been clearly back-

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lled, and that we captured a majority of their cell soma, makingt less likely that we captured the soma of a neighboring cell, andhat we obtained much of the RNA of interest from the desiredeuron subtype. When viewed outside the tissue section, theuccess of the dissection could be assessed by the presence ofissue still carrying fluorescence inside the melted plastic circleFig. 1H).

.3. High quality amplified RNA can be obtained from theaptured neurons

RNA purified from the captured cells was amplified throughwo rounds. Bioanalyzer readings of the eluted aRNA productndicated that consistently high quality aRNA averaging about00 bp in length was obtained from samples of both neuron sub-ypes (Fig. 2). We set a minimal requirement that our aRNAe of this quality for application to cDNA microarrays, so thatariability in the array results associated with applying differentized pieces of cDNA was minimized.

.4. Microarray analysis of genes expressed in these twoeuronal subtypes

A total of 10,902 out of 161,252 hybridized spots (6.8%)ere flagged by GeneTraffic as aberrant, and were discarded

rom further analysis, leaving 150,350 successfully hybridizedpots for the entire experiment. As illustrated by the plot in Fig. 3,

hich shows the distribution of fluorescence intensity at red andreen wavelengths for all spots from a single slide, most spotsad yellow coloration (yellow crosses along the line of slope 1),ndicating that the levels of expression of these genes in the two

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ig. 2. Typical bioanalyzer profiles of the amplified RNA obtained from 2000 HVCarker. The virtual gel at right shows the size distribution of the aRNA for six sampl

ience Methods 157 (2006) 195–207

euron types compared were similar. This result is not surpris-ng given the similarity of the cell types being compared: bothre projection neurons from a single brain region devoted to aommon behavior in the same animal. Profiles similar to thathown in Fig. 3 were seen from all microarray slides, indicatinghigh consistency and uniformity to our microarray data, somef which could be expected given that all our comparisons wereithin-animal, within brain region, and between neuron sub-

lass. Despite the overall similarities in gene expression, genesould be identified that were dramatically and consistently dif-erent in their expression pattern between the two cell types (e.g.utlying red or green crosses in Fig. 3). A total of 1318 spots0.88% of all valid spots) met a two-fold cutoff for differentialxpression; 7210 spots (4.8%) met a 1.5-fold cutoff of differ-ntial expression. So as to initially narrow down the number ofenes of interest, we examined just those spots that showed ateast two-fold differential expression in the majority of all thepots hybridized for that gene, across all animals in the experi-ent. The 14 spots that met this criterion were singled out for

urther validation. The differential expression and consistencyriteria we used were later supplemented with a significancenalysis of microarray (SAM) analysis (Tusher et al., 2001),hich validated all of the previously identified spots, in addi-

ion to new ones that will not be discussed here. Details of theAM analysis that we applied to our data will be described in auture publication. Of the 14 spots, two represented UCHL1,hich we had already identified on a smaller microarray as

ramatically overexpressed in HVC-X neurons (Lombardino etl., 2005), validating this result across array platforms. Six ofhe remaining 12 spots were from sequences that could not beomologized to known genes and will not be discussed further

-RA and 1500 HVC-X neurons. The sharp peak at about 25 s is a fluorescentes (1–6), with an average length of about 400 bp (see ladder lane, L).

A.J. Lombardino et al. / Journal of Neurosc

Fig. 3. Typical image of zebra finch cDNA microarray hybridized with HVCneuron-specific material (top, showing portion of one slide), and plot of fluo-rescence intensities at the red and green wavelengths (bottom, for a single slidecontaining 11,521 spots). Most spots (crosses) lie on top of each other alongthe yellow line, indicating relatively even expression between the two neurontypes compared. A small number of outliers in red and green are evident at allio

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ere. The remaining spots uniquely identified homologs to sixenes, each of which we chose to examine further: (1) mal-nyl coA decarboxylase (MCD), (2) a Slit-like family member,

3) decorin, (4) a serotonin receptor, 5-HT1B, (5) synelfin, and6) phosphatidic acid phosphatase type 2 domain containing 1BHTPAP). All of these genes except HTPAP were expressed atigher levels in HVC-X neurons compared to HVC-RA neurons

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ience Methods 157 (2006) 195–207 201

ccording to the microarray data. HTPAP was overexpressed inVC-RA neurons. All of these genes showed an average differ-

ntial expression across all spots hybridized of two-fold or morerange 2.19–2.66), regardless of singing condition.

.5. Differential expression confirmed by in situybridization

We chose ISH to validate the predicted direction of overex-ression in each of the six unstudied, homologous genes. Toisualize in situ patterns at the cellular level, we used film emul-ion developed over 2–4 weeks and compared the pattern of grainccumulation with the pattern of backfilled cells in the sameection under brightfield and fluorescence conditions. With thexception of decorin, for which the in situ pattern did not confirmhe microarray data, each of the genes showed a tight concen-ration of grains overlying projection neurons of the predictedype (Fig. 4).

.6. Differential gene expression between neuron types wasonfirmed by Taqman quantitative PCR

We reverse transcribed 2–4 �g of the aRNA derived fromaptured HVC neurons for quantitative analysis of one HVC-Xverexpressing gene (zebra finch synelfin) and one HVC-RAverexpressing gene (zebra finch HTPAP). As expected fromhe microarray data, both genes were differentially expressedn the predicted direction at greater than two-fold in all birdsxamined (Fig. 5). The average expression difference fromhe qPCR data was 2.62-fold for synelfin and 3.28-fold forTPAP.

.7. Induction of the immediate-early gene ZENK inVC-RA neurons is linearly related to the number of songsroduced prior to sacrifice

The immediate-early gene ZENK is known to be rapidlynduced by singing behavior in the HVC of male zebra finchesJarvis and Nottebohm, 1997) but that earlier study did not iden-ify the cell types in which this occurred. We examined thexpression levels of this gene in HVC-RA and HVC-X neu-ons from birds that sang directed song for 25 min (N = 5), sangndirected song for 25 min (N = 6), or that had not sung for the2 h prior to sacrifice (N = 4). In the singing birds a silent periodf 30 min was imposed to allow gene induction to proceed afteringing (see Section 2). There was in both cell types a higherxpression of ZENK in the singing than in the non-singing birds,nd the levels of ZENK increased linearly with the amount ofong produced prior to sacrifice in the HVC-RA neurons, withhe pattern not so clear in the HVC-X projecting ones (Fig. 6).ENK expression levels were normalized to total aRNA. We

ormalized to total aRNA (Bustin and Nolan, 2004) after weealized that genes normally presented as “housekeeping” genesnd used for normalization, were also regulated by singing, asescribed below.

202 A.J. Lombardino et al. / Journal of Neuroscience Methods 157 (2006) 195–207

Fig. 4. In situ hybridization confirmed the differential expression predicted from the microarray data. The left panels show data for synelfin, predicted to beo se celb ntrate

3r

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3

Fn

verexpressed in HVC-X neurons, with clusters of grains concentrated over thee overexpressed in HVC-RA neurons. Clusters of grains in this case are conce

.8. Two common ‘housekeeping’ genes are highlyegulated by behavior

Normalization to ‘housekeeping’ genes is known to be prob-ematic in a wide variety of circumstances (Huggett et al., 2005).

e examined the levels of two of the most widely used of these

enes, beta-actin and GAPDH, using qPCR on our laser cap-ured material. Birds were killed 45 or 90 min after the start ofhe singing session. The results reveal a marked regulation ofoth of these genes at the later time point (Fig. 7, open bars),

p

e

ig. 5. Taqman qPCR data confirm the differential expression predicted by the microaeurons), the right panel shows the results for HTPAP (overexpressed in HVC-RA ne

ls (backfilled in green). The right panels show the data for HTPAP, predicted tod over these cells (backfilled in red, lower right panel).

ith GAPDH showing a dramatic decline (Fig. 7, left panels)nd �-actin (Fig. 7, right panels) showing a marked increaseompared to levels in non-singing birds or in birds killed at thearlier time point.

.9. In situ data show that not every neuron of a given

rojection type has similar expression levels

We did not know if when a neuron class shows differentialxpression of a particular gene, this would hold for all neu-

rray data. The left panel shows the results for synelfin (overexpressed in HVC-Xurons).

A.J. Lombardino et al. / Journal of Neurosc

Fig. 6. Expression of ZENK mRNA in HVC-RA neurons increases linearly withthe number of songs sung prior to sacrifice. The top panel shows the data forbirds singing directed song, the bottom panel for birds singing undirected song,f

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vmaebsspouecfof the comparisons we made: two defined neuron subtypes from

or 25 min prior to sacrifice. The best-fit line and equation of that line are shown.

ons of that class, because the microarray data were generatedrom pooled samples of each neuron subtype, and reflectednly the mean levels of the transcript across one cell type,djusted for the total amount of RNA in the samples. In effectur measures were the percentage of the total amplified RNAessages represented by a given sequence. Within our five

enes there were two obvious cases where the ISH results showigh expression in only a subset of neurons of a given projec-ion type, with other backfilled neurons showing little or noxpression. Fig. 8 shows the overexpression of the gene forerotonin receptor subtype 1B in some HVC-X neurons (green),ut not others (white arrows), indicating that not all of theseeurons are identical in their expression profile, and there mayxist further subtypes within the class defined by projectionlone. A second example is the gene predicted to be overex-ressed in HVC-RA neurons, HTPAP (Fig. 4, right panels).n this case, too, there were marked differences in expressionmong neurons of this projection class. Since the timing ofhe birth of HVC-RA neurons is known to vary (reviewed in

ottebohm, 2002), perhaps one should expect heterogeneityased on cellular age alone, a point we address further in the nextection.

aaf

ience Methods 157 (2006) 195–207 203

.10. Laser capture microdissection of projection neuronsan be combined with immunohistochemical techniques tourther define the cell types compared

HVC-RA projection neurons are produced and replaced indult life (Kirn and Nottebohm, 1993). For this reason, somef these neurons may be relatively recent arrivals while othersre considerably older; some may be in the process of form-ng connections (Paton and Nottebohm, 1984), others may bereparing to die. An age distinction within the class of HVC-A neurons may not matter for some research questions, but forthers, including any process where cellular age plays a role, its important to know the age of the neurons captured, and byxtension, their possible participation in earlier or more recentvents in the cell’s or the animal’s life.

Presumably some of the variability in gene expressionetween HVC-RA neurons could be reduced by focusing onlyn cells of similar birth date.

As a first approach to this question, we injected BrdU touvenile zebra finches (45–50 days of age) at a time when

any HVC-RA neurons are being added to HVC (Nordeen andordeen, 1988), and allowed these birds to survive for 6 weeks.

mmediately prior to preparing the tissue sections for LCM, wepplied a shortened version of a previously published proto-ol for visualizing BrdU that does not severely degrade RNACounts et al., 2005). Neurons were selected for capturing ifhey were positive for both the BrdU and CTB, indicating anVC-RA projection neuron born during the period of BrdU

dministration. Fig. 9A shows a typical profile for such double-abeled neurons: the green nucleus labeled with an antibody tordU is surrounded by a red cell body filled with CTB. LCM of0–80 of these cells yielded 6 �g of RNA after 2-round linearmplification, and the quality of this aRNA was only slightlyess than that obtained from neurons not subjected to BrdUmmunohistochemistry (Fig. 9B, note small peak of degradedNA preceding smooth hill).

. Discussion

Cellular resolution is a key objective in studies of the ner-ous system, especially where the characterization of specificolecules is involved (Crick, 1999). We chose membership inneural circuit as the criterion for selecting neurons for gene

xpression analysis. In our material, long distance connectionsetween neurons afford the opportunity to cleanly label cellomata in vivo for subsequent dissection by LCM. Our resultshow that this approach permits the molecular phenotyping ofrojection neurons of two different types even when membersf these two types are closely interspersed with each other. Bysing stringent fold-change criteria for selecting genes of inter-st, we were able to identify differentially expressed genes andonfirm this differential expression by ISH and qPCR. The uni-ormity of our microarray data was likely due to the closeness

same animal obtained from a single brain region devoted tocommon behavior. Such close comparisons are well suited

or statistical analyses of microarray data, which assume that

204 A.J. Lombardino et al. / Journal of Neuroscience Methods 157 (2006) 195–207

Fig. 7. Taqman qPCR shows singing regulation of two housekeeping genes, GAPDH (left panels) and �-Actin (right panels), in HVC-RA neurons (top panels) andH at wer4 crifica

muB

ap2tIawareetMoidtfiiwtn

Fnc

ifccearrfpt5csca(Hc

VC-X neurons (bottom panels). Each bar represents the mean of 5–7 birds th5 min prior to sacrifice (gray bars), or that were singing for 90 min prior to sand the bars are standard errors of the mean.

ost genes are expressed at similar levels and that outliers arenlikely to occur by chance (Geschwind, 2000; Lockhart andarlow, 2001).

We believe that the approach we describe offers distinctdvantages over a previously reported purification of long-rangerojection neurons using fluorescent cell sorting (Arlotta et al.,005). In the latter procedure, considerable time elapses betweenhe intact state of the neurons and the stabilization of their RNAs.n the protocol we followed the time involved is much shorter,nd there is no need to disrupt neuronal connections in vivo,hile gene expression profiles can still change. Both of these

dvantages should be reflected in expression profiles that betterepresent those of the intact animal. Our data on singing-inducedxpression of ZENK mRNA, which demonstrated an increasedxpression of this gene with increased singing, further supporthe view that our methods preserve in vivo transcription profiles.

oreover, the use of CTB as a tracer offers several advantagesver Fluorogold (Yao et al., 2005; Perez-Manso et al., in press):t retains bright fluorescence through the stringent tissue dehy-ration required for LCM, it comes in more than one color, sohat projection neurons of two different kinds can be harvestedrom a same section. In addition, the quenching time of CTBs much longer than Fluorogold, an important factor when try-

ng to determine if a given target cell is labeled with tracer asell as a second marker, such as BrdU. Despite multiple injec-

ions of this substance, the function of the backfilled neurons isot compromised, at least as assessed by behavioral integrity.

tsoa

e not singing for at least 12 h prior sacrifice (black bars), that were singing fore (open bars). The indicated p-values are from t-tests comparing these means,

luorogold at high concentrations (e.g. 4% solution) can lesioneurons (our unpublished data) and may be toxic at lower con-entrations (Franklin and Druhan, 2000).

When studying a highly integrated organ such as the brain,t is not known a priori what is the optimal sampling of cellsor subsequent analysis. For example, is it best to study singleells (Kamme et al., 2003; Ginsberg and Che, 2004), cohorts ofells sharing common features (Torres-Munoz et al., 2004), orntire brain regions that are functionally homogeneous (Segal etl., 2005)? In our studies we pooled hundreds of projection neu-ons of a given type based on their connectivity. This approachisks blurring subtler distinctions among individual neurons inavor of detecting large differences between classes of neuronsrojecting to different brain regions. The ISH data for two ofhe genes we found to be differentially expressed, HTPAP and-HT1B, show that in fact not all projection neurons of a givenlass express these genes at similar levels. The 5-HT1B expres-ion in HVC-X neurons differed markedly between individualells suggesting a previously unsuspected functional diversitymong neurons of this class (Fig. 8). In the case of HTPAPFig. 4, right panels), for which overall levels were higher inVC-RA neurons, its variable expression between HVC-RA

ells might have something to do with the fact that at any one

ime some of these cells are dying and being replaced, with a con-equent diversity in the cell ages represented. Our modificationf an existing protocol for visualizing the cell birth marker BrdUllows us to combine this procedure with retrograde tracing and

A.J. Lombardino et al. / Journal of Neurosc

Fot

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fatrrriastgtanPt

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ig. 8. In situ hybridization for the serotonin receptor 1B, showing concentrationf grains (bottom panel) over some HVC-X neurons (green backfilled cells inop panel), but not others (white arrows in top panel).

aser capture microdissection, to obtain populations of HVC-RAeurons that are more homogeneous with respect to cellular age.he profile of amplified RNA obtained from dozens of such neu-

ons (Fig. 9B) is very encouraging, and suggests that microarraynd qPCR analyses will be possible using this material.

The protocol we followed for harvesting and amplifying RNArom two sets of projection neurons from the brain of a samenimal is time consuming and labor intensive. We maximizedhe utility of the resulting aRNA by using it for both microar-ay and qPCR analysis. We performed our qPCR analyses oneverse-transcribed aRNA, rather than on recaptured samples ofeverse-transcribed RNA, for several technical reasons. First, its difficult to accurately measure the total RNA yield from as fews hundreds of laser-captured neurons, and typically the entireample is required for any such measurement of RNA quan-ity and quality. Thus one cannot readily normalize the levels ofenes detected by Taqman in terms of the total RNA put intohe reaction. This leaves normalization to housekeeping genes,

nd as we have shown, this is problematic in this system, whereeurons sit relatively quiescent until called upon during singing.erforming Taqman on amplified RNA makes normalization to

otal aRNA easy, since the amounts of aRNA produced can be

innt

ience Methods 157 (2006) 195–207 205

easured very precisely. Second, the pool of aRNA producedrom our captures provides enough material for both microarraynalysis and – because of the sensitivity of Taqman – for exten-ive qPCR assays for many different genes. Even in those caseshere we did not run our aRNA on microarrays, this option exists

or future studies. We have checked the quality of our aRNA aftertoring it at −80 ◦C for 18 months, and no obvious degradationad occurred, presumably due to the purity of this material dur-ng the amplification process. Our approach thus maximizes thetility of the limited laser-captured material laboriously obtainedrom each animal. When qPCR analyses of amplified materialre undertaken using material from the same animals on whichhe microarrays were run, they validate the latter data in a moreimited way, providing an alternate methodology for assayinghe same material. When qPCR is performed on aRNA fromdditional animals, a further assessment of the generality ofhe results is obtained (McReynolds et al., 2005). Finally, byapturing defined numbers of cells, amplifying these samplesndependently, and then checking levels of specific genes in this

aterial with Taqman, we could assure ourselves of the linearityf the amplification process with respect to these genes.

The song control system has been an especially fruitfulodel in which to explore questions of how behavior regulates

ene expression, particularly with regard to the induction ofhe immediate-early gene ZENK (Jarvis and Nottebohm, 1997;in and Clayton, 1997; Ribeiro et al., 1998; Avey et al., 2005).ene expression studies to date have focused on entire song con-

rol regions, and quantification of gene levels has been limitedo semi-quantitative measures derived from ISH averaged overhe entire region. These techniques depend on certain assump-ions about cell density and the unchanging nature of a controlrain region for normalization, and they do not provide infor-ation about the cell type in which the gene induction occurs.he combination of techniques described here was able to track

he previously described relationship between number of songsung and the amount of ZENK mRNA produced in HVC, and ourata extend this result to the level of a specific projection neuronubtype. The ability to rigorously quantify the levels of specificenes using qPCR, and to identify the cell types in which theseenes are expressed as a function of singing, promises to pro-ide important insights on how behavior regulates transcription.or example, whether a male zebra finch is singing directly to aemale or while alone is known to dramatically regulate the levelf ZENK in the anterior forebrain circuit nuclei lMAN and Area(Jarvis et al., 1998). It will be interesting to further explore the

evels of ZENK in HVC-X neurons as a function of social con-ext, given that ZENK expression in the brain region innervatedy the HVC-X neurons differs so dramatically depending on theontext in which singing occurs. Initial studies suggest that theENK response in these neurons is complex, and does not fit the

inear increase with number of songs seen with HVC-RA neu-ons. As further refinements are made to the behavioral modelsn which ZENK induction is studied, there will be an increas-

ng need for the cellular and molecular techniques to keep pace,ot only to detect subtler changes in expression, but also to askew questions about the meaning of higher levels of a particularranscript (and presumably the protein it encodes, see Whitney

206 A.J. Lombardino et al. / Journal of Neuroscience Methods 157 (2006) 195–207

Fig. 9. Micrograph of neurons backfilled with CTB (red cell body) and positive for BrdU (green nucleus). Double-labeled cells (white arrow in A) are HVC-RAneurons born several weeks earlier when the BrdU was administered. (Panel B) The bioanalyzer profile of aRNA obtained from 80 cells double-labeled as in (A).T mentc ld of ac

aiooa

A

eSmabo

R

A

A

A

A

B

B

B

B

B

B

C

C

he small peak just to the left of the smooth hill represents degraded RNA fragaptured without treatment to visualize BrdU (Panel C). Note also the lower yieompared to the marker peak at about 22 s.

nd Johnson, 2005) in a type of neuron after a given behav-oral state. The results we report here provide an integrated setf techniques that allow for the dissection of molecular eventsccurring in intermingled classes of cells associated with thecquisition and performance of a complex, learned behavior.

cknowledgements

We thank the staff of the Genomics Resource Center at Rock-feller University for assistance with the microarray studies,haron Sepe, Helen Ecklund, Daun Jackson, for excellent ani-al care, and Dr. Kan Yang of the Strang Cancer Center for

ccess to the Pixcell IIe microscope. This work was supportedy a post-doctoral grant from Pfizer Global Research and Devel-pment (A.L.), and by PHS grants MH18343 and 63132 (F.N.).

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