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Genomic Resources for Songbird Research and Their Use in Characterizing Gene Expression during Brain Development

XiaoChing Li, Xiu-Jie Wang, Jonathan Tannenhauser, Sheila Podell, Piali Mukherjee, Moritz Hertel, Jeremy Biane, Shoko Masuda, Fernando Nottebohm and Terry Gaasterland
Proceedings of the National Academy of Sciences of the United States of America
Vol. 104, No. 16 (Apr. 17, 2007), pp. 6834-6839
Stable URL: http://www.jstor.org/stable/25427469
Page Count: 6
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Genomic Resources for Songbird Research and Their Use in Characterizing Gene Expression during Brain Development
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Abstract

Vocal learning and neuronal replacement have been studied extensively in songbirds, but until recently, few molecular and genomic tools for songbird research existed. Here we describe new molecular/genomic resources developed in our laboratory. We made cDNA libraries from zebra finch (Taeniopygia guttata) brains at different developmental stages. A total of 11,000 cDNA clones from these libraries, representing 5,866 unique gene transcripts, were randomly picked and sequenced from the 3' ends. A webbased database was established for clone tracking, sequence analysis, and functional annotations. Our cDNA libraries were not normalized. Sequencing ESTs without normalization produced many developmental stage-specific sequences, yielding insights into patterns of gene expression at different stages of brain development. In particular, the cDNA library made from brains at posthatching day 30-50, corresponding to the period of rapid song system development and song learning, has the most diverse and richest set of genes expressed. We also identified five microRNAs whose sequences are highly conserved between zebra finch and other species. We printed cDNA microarrays and profiled gene expression in the high vocal center of both adult male zebra finches and canaries (Serinus canaria). Genes differentially expressed in the high vocal center were identified from the microarray hybridization results. Selected genes were validated by in situ hybridization. Networks among the regulated genes were also identified. These resources provide songbird biologists with tools for genome annotation, comparative genomics, and microarray gene expression analysis.

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