Corrections NEUROSCIENCE. For the article ‘‘A molecular neuroethological BIOPHYSICS. For the article ‘‘A molecular mechanism for os- approach for identifying and characterizing a cascade of behav- molyte-induced protein stability,’’ by Timothy O. Street, D. iorally regulated genes,’’ by Kazuhiro Wada, Jason T. Howard, Wayne Bolen, and George D. Rose, which appeared in issue 38, Patrick McConnell, Osceola Whitney, Thierry Lints, Miriam V. September 19, 2006, of Proc Natl Acad Sci USA (103:13997– Rivas, Haruhito Horita, Michael A. Patterson, Stephanie A. 14002; first published September 12, 2006; 10.1073͞pnas. White, Constance Scharff, Sebastian Haesler, Shengli Zhao, 0606236103), the authors note the following: ‘‘For Fig. 2 of our Hironobu Sakaguchi, Masatoshi Hagiwara, Toshiyuki Shiraki, article, we inadvertently published a plot of the contact surface Tomoko Hirozane-Kishikawa, Pate Skene, Yoshihide Hayash- area rather than the accessible surface area as intended. Also, izaki, Piero Carninci, and Erich D. Jarvis, which appeared in the correlation coefficient given should be 0.81, not 0.88 as in the issue 41, October 10, 2006, of Proc Natl Acad Sci USA original figure caption. All other aspects of the article remain (103:15212–15217; first published October 3, 2006; 10.1073͞ unaffected by this correction. We regret the errors.’’ The cor- pnas.0607098103), the authors note that Fig. 1 appeared incor- rected figure and legend appear below. rectly due to a printer’s error. The corrected figure and its legend appear below. Fig. 2. The polar fraction of osmolyte surface correlates with measured ⌬gtr osmolyte ⌬ values. Fractional polar SA, f polar surface, is plotted against gtr values from Table 1 for the 10 osmolytes in Fig. 1. The linear regression line (solid line) has a negative slope with a correlation coefficient of 0.81, indicating that back- bone͞osmolyte interactions become increasingly favorable as osmolytes be- come increasingly polar. www.pnas.org͞cgi͞doi͞10.1073͞pnas.0608836103 Fig. 1. Molecular functions and variant analysis. (A) Distribution of putative molecular functions for 1,924 clusters and 2,449 subclusters of zebra finch brain cDNAs that received gene ontology annotations (www.geneontology- .org), compared with 27,048 human genes. Genes can be represented in more than one category because of multiple molecular functions, and thus catego- ries add up to Ͼ100%. Human values were obtained from ref. 24. (B) mRNA variant analysis. Percentage represents the proportion of a specific variant type relative to the total number of variants from 100 randomly selected cDNA clusters containing 256 subclusters and 668 clones. *, P Ͻ 0.01 from chance distribution (horizontal line, t test across variant types in n ϭ 10 bins of 10 clusters each). Because not all clones have full sequence coverage, the abso- lute distribution may change when such sequences are present. Colors denote mRNA subdomains quantified. alt, Alternative. www.pnas.org͞cgi͞doi͞10.1073͞pnas.0608997103 17064–17065 ͉ PNAS ͉ November 7, 2006 ͉ vol. 103 ͉ no. 45 www.pnas.org Downloaded by guest on September 24, 2021 NEUROSCIENCE. For the article ‘‘Neurotoxic protein expression CELL BIOLOGY. For the article ‘‘A bio-chemo-mechanical model reveals connections between the circadian clock and mating for cell contractility,’’ by Vikram S. Deshpande, Robert M. behavior in Drosophila,’’ by Sebastian Kadener, Adriana Villella, McMeeking, and Anthony G. Evans, which appeared in issue 38, Elzbieta Kula, Kristyna Palm, Elzbieta Pyza, Juan Botas, Jeffrey September 19, 2006, of Proc Natl Acad Sci USA (103:14015– C. Hall, and Michael Rosbash, which appeared in issue 36, 14020; first published September 7, 2006; 10.1073͞pnas. September 5, 2006, of Proc Natl Acad Sci USA (103:13537–13542; 0605837103), the authors note that Eq. 3 is incorrect. The first published August 28, 2006; 10.1073͞pnas.0605962103), the corrected equation appears below. This error does not affect the authors note that there were errors in the Acknowledgments. conclusions of the article. The corrected version appears below. ˙␧ ␩ Ͻ Ϫ 0 ␧ ៮ We thank Nancy Bonini (Howard Hughes Medical Institute, University ˙o k␯ of Pennsylvania, Philadelphia, PA) for the UAS-MJDtr lines; R. Allada, ៮ ␴ k␯ ˙␧ ␩ ˙␧ P. Emery, K. Abruzzi, K. Dower, D. Stoleru, and S. Lacadie for critical ϭ 1 ϩ ͩ ͪ Ϫ Յ Յ 0. [3] ␴ ␩ ␧ ៮ ˙␧ readings of the manuscript; and Heather Felton for administrative o Ά ˙o k␯ o assistance. S.K. is a recipient of a Human Frontier Science Program ˙␧ Ͼ postdoctoral fellowship. This work was supported in part by National 1 ␧ 0 Institutes of Health Grants NS44232 (to M.R.), GM66778 (to J.C.H. and ˙o M.R.), and GM-21473 and NS33352 (to J.C.H.). www.pnas.org͞cgi͞doi͞10.1073͞pnas.0608707103 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0608504103 CORRECTIONS PNAS ͉ November 7, 2006 ͉ vol. 103 ͉ no. 45 ͉ 17065 Downloaded by guest on September 24, 2021 A molecular neuroethological approach for identifying and characterizing a cascade of behaviorally regulated genes Kazuhiro Wada*†, Jason T. Howard*, Patrick McConnell‡, Osceola Whitney*, Thierry Lints§, Miriam V. Rivas*, Haruhito Horita*, Michael A. Patterson*, Stephanie A. White¶, Constance Scharffʈ, Sebastian Haeslerʈ, Shengli Zhao*, Hironobu Sakaguchi**, Masatoshi Hagiwara††, Toshiyuki Shiraki‡‡§§, Tomoko Hirozane-Kishikawa‡‡§§, Pate Skene*, Yoshihide Hayashizaki‡‡§§, Piero Carninci‡‡§§, and Erich D. Jarvis*† *Department of Neurobiology and ‡Duke Bioinformatics Shared Resource, Duke University Medical Center, Durham, NC 27710; §Department of Biology, City College of New York, New York, NY 10031; ¶Department of Physiological Science, University of California, Los Angeles, CA 90095; ʈNeurobiology Group, Max Planck Institute for Molecular Genetics, 14195 Berlin, Germany; **Department of Physiology and Biological Information, Dokkyo Medical University, Tochigi 321-0293, Japan; ††Department of Functional Genomics, Tokyo Medical and Dental University, Tokyo 113-8519, Japan; ‡‡Genome Science Laboratory, RIKEN, Wako Main Campus, Saitama 351-0198, Japan; and §§Laboratory for Genome Exploration Research Group, RIKEN Yokohama Institute, Yokohama 230-0045, Japan Communicated by Fernando Nottebohm, The Rockefeller University, Millbrook, NY, August 18, 2006 (received for review November 4, 2005) Songbirds have one of the most accessible neural systems for the lecular resource that was focused, from start to finish, on cloning study of brain mechanisms of behavior. However, neuroethologi- full-length cDNAs expressed in the brain from a variety of devel- cal studies in songbirds have been limited by the lack of high- opmental and behavioral conditions. The resource includes an throughput molecular resources and gene-manipulation tools. To annotated database, cDNA microarrays, and a gene-manipulation overcome these limitations, we constructed 21 regular, normal- approach. We used this resource to identify a dynamic cascade of ized, and subtracted full-length cDNA libraries from brains of zebra genes up- and down-regulated in brain vocal nuclei by singing finches in 57 developmental and behavioral conditions in an behavior. The genes include some activity-dependent transcription attempt to clone as much of the brain transcriptome as possible. factors and many late-response housekeeping molecules. Their From these libraries, Ϸ14,000 transcripts were isolated, represent- functions and differential patterns suggest that large gene regula- ing an estimated 4,738 genes. With the cDNAs, we created a tory networks for basic brain processes are recruited as a result of hierarchically organized transcriptome database and a large-scale behavioral performance. Figs. 10–21, Tables 1–6, and Appendix, songbird brain cDNA microarray. We used the arrays to reveal a set which are published as supporting information on the PNAS web of 33 genes that are regulated in forebrain vocal nuclei by singing site, all cited below, show additional information. behavior. These genes clustered into four anatomical and six temporal expression patterns. Their functions spanned a large Results range of cellular and molecular categories, from signal transduc- Brain Transcriptome Libraries. We used brains of 60 zebra finches in tion, trafficking, and structural, to synaptically released molecules. 57 different developmental, pathological, and behavioral states With the full-length cDNAs and a lentiviral vector system, we were (Table 1) to create 21 cDNA libraries: 6 normalized, 4 abundant, 5 able to overexpress, in vocal nuclei, proteins of representative subtracted, and 6 regular (Table 2; definitions are in Glossary in singing-regulated genes in the absence of singing. This publicly Appendix). The 6 normalized libraries were made from a silent ͞͞ accessible resource http: songbirdtranscriptome.net can now be male, undirected singing males, directed singing males, embryonic used to study molecular neuroethological mechanisms of behavior. males and females, 50 juvenile and adult animals in different behavioral states, and animals undergoing rapid vocal learning (Fig. scine songbirds learn their songs by imitating those of adults. 10 and Table 2). Subtracted libraries were focused on enriching for OTheir song behavior is readily quantified and is controlled by genes related to vocal learning and singing. For each library, the a system of discreet brain vocal nuclei (Fig. 8, which is published as first-strand reactions were made with primers that contain unique supporting information on the PNAS web site) (1, 2). For these 3Ј sequence