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

Curation of microarray oligonucleotides and corresponding ESTs/cDNAs used for gene expression analysis in zebra finches

OBJECTIVES

Zebra finches are a major model organism for investigating mechanisms of vocal learning, a trait that enables spoken language in humans. The development of cDNA collections with expressed sequence tags (ESTs) and microarrays has allowed for extensive molecular characterizations of circuitry underlying vocal learning and production. However, poor database curation can lead to errors in transcriptome and bioinformatics analyses, limiting the impact of these resources. Here we used genomic alignments and synteny analysis for orthology verification to curate and reannotate ~ 35% of the oligonucleotides and corresponding ESTs/cDNAs that make-up Agilent microarrays for gene expression analysis in finches.

DATA DESCRIPTION

We found that: (1) 5475 out of 43,084 oligos (a) failed to align to the zebra finch genome, (b) aligned to multiple loci, or (c) aligned to Chr_un only, and thus need to be flagged until a better genome assembly is available, or (d) reflect cloning artifacts; (2) Out of 9635 valid oligos examined further, 3120 were incorrectly named, including 1533 with no known orthologs; and (3) 2635 oligos required name update. The resulting curated dataset provides a reference for correcting gene identification errors in previous finch microarrays studies, and avoiding such errors in future studies.

The zebra finch, Taeniopygia guttata: an avian model for investigating the neurobiological basis of vocal learning

Songbirds are capable of learning their vocalizations by copying a singing adult. This vocal learning ability requires juveniles to hear and memorize the sound of the adult song, and later to imitate it through a process involving sensorimotor integration. Vocal learning is a trait that songbirds share with humans, where it forms the basis of spoken language acquisition, with other avian groups (parrots and hummingbirds), and with a few other mammals (cetaceans, bats). It is however absent in traditional model organisms such as rodents and nonhuman primates. Zebra finches, a songbird species from Australia, are popular pets and are easy to breed. They also sing a relatively simple and stereotyped song that is amenable to quantitative analysis. Zebra finches have thus emerged as a choice model organism for investigating the neurobiological basis of vocal learning. A number of tools and methodologies have been developed to characterize the bioacoustics properties of their song, analyze the degree of accurate copying during vocal learning, map the brain circuits that control singing and song learning, and investigate the physiology of these circuits. Such studies have led to a large base of knowledge on song production and learning, and their underlying neural substrate. Several molecular resources have recently become available, including brain cDNA/EST databases, microarrays, BAC libraries, a molecular brain atlas, a complete genome assembly, and the ability to perform transgenesis. The recent availability of many other avian genomes provides unique opportunities for comparative analysis in the search for features unique to vocal learning organisms.

Evaluation of reference genes for quantitative real-time PCR in the brain, pituitary, and gonads of songbirds

Quantitative real-time PCR (qPCR) is becoming a popular tool for the quantification of gene expression in the brain and endocrine tissues of songbirds. Accurate analysis of qPCR data relies on the selection of appropriate reference genes for normalization, yet few papers on songbirds contain evidence of reference gene validation. Here, we evaluated the expression of ten potential reference genes (18S, ACTB, GAPDH, HMBS, HPRT, PPIA, RPL4, RPL32, TFRC, and UBC) in brain, pituitary, ovary, and testis in two species of songbirds: zebra finch and white-throated sparrow. We used two algorithms, geNorm and NormFinder, to assess the stability of these reference genes in our samples. We found that the suitability of some of the most popular reference genes for target gene normalization in mammals, such as 18S, depended highly on tissue type. Thus, they are not the best choices for brain and gonad in these songbirds. In contrast, we identified alternative genes, such as HPRT, RPL4 and PPIA, that were highly stable in brain, pituitary, and gonad in these species. Our results suggest that the validation of reference genes in mammals does not necessarily extrapolate to other taxonomic groups. For researchers wishing to identify and evaluate suitable reference genes for qPCR in songbirds, our results should serve as a starting point and should help increase the power and utility of songbird models in behavioral neuroendocrinology.

Analysis of transcription factor mRNAs in identified oxytocin and vasopressin magnocellular neurons isolated by laser capture microdissection

The oxytocin (Oxt) and vasopressin (Avp) magnocellular neurons (MCNs) in the hypothalamus are the only neuronal phenotypes that are present in the supraoptic nucleus (SON), and are characterized by their robust and selective expression of either the Oxt or Avp genes. In this paper, we take advantage of the differential expression of these neuropeptide genes to identify and isolate these two individual phenotypes from the rat SON by laser capture microdissection (LCM), and to analyze the differential expression of several of their transcription factor mRNAs by qRT-PCR. We identify these neuronal phenotypes by stereotaxically injecting recombinant Adeno-Associated Viral (rAAV) vectors which contain cell-type specific Oxt or Avp promoters that drive expression of EGFP selectively in either the Oxt or Avp MCNs into the SON. The fluorescent MCNs are then dissected by LCM using a novel Cap Road Map protocol described in this paper, and the purified MCNs are extracted for their RNAs. qRT-PCR of these RNAs show that some transcription factors (RORA and c-jun) are differentially expressed in the Oxt and Avp MCNs.

Seasonal changes in patterns of gene expression in avian song control brain regions

Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log₂ 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity.

Evo-devo, deep homology and FoxP2: implications for the evolution of speech and language

The evolution of novel morphological features, such as feathers, involves the modification of developmental processes regulated by gene networks. The fact that genetic novelty operates within developmental constraints is the central tenet of the 'evo-devo' conceptual framework. It is supported by findings that certain molecular regulatory pathways act in a similar manner in the development of morphological adaptations, which are not directly related by common ancestry but evolved convergently. The Pax6 gene, important for vision in molluscs, insects and vertebrates, and Hox genes, important for tetrapod limbs and fish fins, exemplify this 'deep homology'. Recently, 'evo-devo' has expanded to the molecular analysis of behavioural traits, including social behaviour, learning and memory. Here, we apply this approach to the evolution of human language. Human speech is a form of auditory-guided, learned vocal motor behaviour that also evolved in certain species of birds, bats and ocean mammals. Genes relevant for language, including the transcription factor FOXP2, have been identified. We review evidence that FoxP2 and its regulatory gene network shapes neural plasticity in cortico-basal ganglia circuits underlying the sensory-guided motor learning in animal models. The emerging picture can help us understand how complex cognitive traits can 'descend with modification'.

Genes and vocal learning

Could a mutation in a single gene be the evolutionary lynchpin supporting the development of human language? A rare mutation in the molecule known as FOXP2 discovered in a human family seemed to suggest so, and its sequence phylogeny reinforced a Chomskian view that language emerged wholesale in humans. Spurred by this discovery, research in primates, rodents and birds suggests that FoxP2 and other language-related genes are interactors in the neuromolecular networks that underlie subsystems of language, such symbolic understanding, vocal learning and theory of mind. The whole picture will only come together through comparative and integrative study into how the human language singularity evolved.

High quality RNA from multiple brain regions simultaneously acquired by laser capture microdissection

Background

Laser capture microdissection enables the isolation of single cells or small cell groups from histological sections under direct microscopic observation. Combined with quantitative PCR or microarray, it is a very powerful approach for studying gene expression profiles in discrete cell populations. The major challenge for such studies is to obtain good quality RNA from small amounts of starting material.

Results

We have developed a simple, flexible, and low-cost method for simultaneously producing RNA from discrete cell groups in embryonic day 15 mouse brain. In particular, we have optimized the following key steps in the procedure: staining, cryosectioning, storage of sections and harvesting of microdissected cells. We obtained the best results when staining 20 μm-thick sections with 1% cresyl violet in 70% ethanol and harvesting the microdissected tissue in RNA stabilization solution. In addition, we introduced three stop-points in the protocol which makes the tedious process of laser capture microdissection more flexible, without compromising RNA quality.

Conclusion

Using this optimized method, we have consistently obtained RNA of high quality from all four simultaneously microdissected cell groups. RNA integrity numbers were all above 8, and long cDNA fragments (> 1.2 kb) were successfully amplified by reverse transcription PCR from all four samples. We conclude that RNAs isolated by this method are well suited for downstream quantitative PCR or microarray studies.

Validation of immuno-laser capture microdissection coupled with quantitative RT-PCR to probe blood-brain barrier gene expression in situ

Laser capture microdissection (LCM) holds great potential for analyzing gene expression profiles in situ. Most recently, this laboratory employed a novel immunostain-based LCM protocol (immuno-LCM) to selectively retrieve brain microvascular endothelial cells (BMEC) from intimately associated perivascular cells. However, before this protocol can be confidently coupled to downstream analytical platforms, it must be demonstrated that any variability associated with it is minimal, so as not to obscure data interpretation. As various factors could contribute to variability, this study focused on determining whether technical inconsistency and/or biological diversity of sample populations, played such a role. Specifically, two separate immuno-LCM-derived BMEC samples derived from adjacent tissue sections of a single mouse (to detect only technical variability), and from analogous tissue sections of three different mice (to detect technical and biological variability) were compared for their relative expression of 16 genes, using quantitative-RT-PCR (qRT-PCR). Both significant linear and rank-order correlations were observed between different sections from the same animal, underscoring lack of technical variability in this LCM application. Furthermore, a three-dimensional scatter plot of gene expression profiles from the three animals was linear, and ANOVA showed absence of statistically significant differences between any of the animals, confirming lack of biological variability. These findings argue that immuno-LCM coupled to qRT-PCR affords a reproducible means to assay gene expression in situ.

Twenty-five years of quantitative PCR for gene expression analysis

Following its invention 25 years ago, PCR has been adapted for numerous molecular biology applications. Gene expression analysis by reverse-transcription quantitative PCR (RT-qPCR) has been a key enabling technology of the post-genome era. Since the founding of BioTechniques, this journal has been a resource for the improvements in qPCR technology, experimental design, and data analysis. qPCR and, more specifically, real-time qPCR has become a routine and robust approach for measuring the expression of genes of interest, validating microarray experiments, and monitoring biomarkers. The use of real-time qPCR has nearly supplanted other approaches (e.g., Northern blotting, RNase protection assays). This review examines the current state of qPCR for gene expression analysis now that the method has reached a mature stage of development and implementation. Specifically, the different fluorescent reporter technologies of real-time qPCR are discussed as well as the selection of endogenous controls. The conceptual framework for data analysis methods is also presented to demystify these analysis techniques. The future of qPCR remains bright as the technology becomes more rapid, cost-effective, easier to use, and capable of higher throughput.

Transcriptome changes associated with instructed learning in the barn owl auditory localization pathway

Owls reared wearing prismatic spectacles learn to make adaptive orienting movements. This instructed learning depends on re-calibration of the midbrain auditory space map, which in turn involves the formation of new synapses. Here we investigated whether these processes are associated with differential gene expression, using longSAGE. Newly fledged owls were reared for 8-36 days with prism or control lenses at which time the extent of learning was quantified by electrophysiological mapping. Transciptome profiles were obtained from the inferior colliculus (IC), the major site of synaptic plasticity, and the optic tectum (OT), which provides an instructive signal that controls the direction and extent of plasticity. Twenty-two differentially expressed sequence tags were identified in IC and 36 in OT, out of more than 35,000 unique tags. Of these, only four were regulated in both structures. These results indicate that regulation of two largely independent gene clusters is associated with synaptic remodeling (in IC) and generation of the instructive signal (in OT). Real-time PCR data confirmed the changes for two transcripts, ubiquitin/polyubiquitin and tyrosine 3-monooxgenase/tryotophan 5-monooxygenase activation protein, theta subunit (YWHAQ; also referred to as 14-3-3 protein). Ubiquitin was downregulated in IC, consistent with a model in which protein degradation pathways act as an inhibitory constraint on synaptogenesis. YWHAQ was up-regulated in OT, indicating a role in the synthesis or delivery of instructive information. In total, our results provide a path towards unraveling molecular cascades that link naturalistic experience with synaptic remodeling and, ultimately, with the expression of learned behavior.