pools of embryos were treated form 2-3 dpf in 75 uM Lycorine in 1% DMSO, or 1% DMSO alone
Growth protocol
embryos were raised in E3 media at 28.5C
Extracted molecule
total RNA
Extraction protocol
embryos were dissociated using Roche liberase, cell populations were sorted directly in Trizol LS using an Aria cell sorter, Trizol extraction was performed as per the manufacturer's instructions, with the addition of Sigma GenElute LPA
Label
biotin
Label protocol
total RNA was amplified and labeled using the NuGEN Ovation Pico WTA System V2 and Encore Biotin Module kits, respectively
Hybridization protocol
Hybridization Control Kit, and Hybridization, Wash, and Staining Kit from Ambion
Scan protocol
Genechip Scanner 3000 7G
Description
RNA amplified using NuGEN Ovation Pico WTA System V2
Data processing
All ZebGene 1.0 ST arrays were processed using the BioConductor [1] package oligo [2]. Arrays were assessed for quality with arrayQualityMetrics [3] and normalized using the Robust Multichip Average (RMA [4]) method at the probe level, collapsing probes into core transcripts based on the pd.zebgene.1.0.db annotation package [5]. Batch correction was performed with the sva [6] package and the ComBat method [7]. Control probes and those with either mean log transformed intensity values of less than 2.5 or standard deviations of less than 0.1 among all samples were removed. Probes were assigned to genes using Netaffx [8] annotations (ZebGene-1_0-st-v1.na33.3.zv9.transcript.csv); probes were not combined at the gene level, but were treated as independent assays. Differential expression statistics for pairwise and three-way (interaction terms) comparisons were generated by linear model for microarray data analysis (limma) [9] using empirical Bayes shinkage methods. Differentially expressed genes were assessed as those with least a log fold expression change of 1 and an FDR [10] based adjusted pvalue of less than 0.1. [1] R. C. Gentleman, V. J. Carey, D. M. Bates, B. Bolstad, M. Dettling, S. Dudoit, B. Ellis, L. Gautier, Y. Ge, J. Gentry, K. Hornik, T. Hothorn, W. Huber, S. Iacus, R. Irizarry, F. Leisch, C. Li, M. Maechler, A. J. Rossini, G. Sawitzki, C. Smith, G. Smyth, L. Tierney, J. Y. H. Yang, and J. Zhang, “Bioconductor: open software development for computational biology and bioinformatics.,” Genome Biol., vol. 5, no. 10, p. R80, 2004. [2] B. S. Carvalho and R. A. Irizarry, “A framework for oligonucleotide microarray preprocessing.,” Bioinformatics, vol. 26, no. 19, pp. 2363–2367, Oct. 2010. [3] A. Kauffmann, R. Gentleman, and W. Huber, “arrayQualityMetrics--a bioconductor package for quality assessment of microarray data.,” Bioinformatics, vol. 25, no. 3, pp. 415–416, Feb. 2009. [4] B. M. Bolstad, R. A. Irizarry, M. Astrand, and T. P. Speed, “A comparison of normalization methods for high density oligonucleotide array data based on variance and bias.,” Bioinformatics, vol. 19, no. 2, pp. 185–193, Jan. 2003. [5] Benilton Carvalho. pd.zebgene.1.0.st: Platform Design Info for Affymetrix ZebGene-1_0-st. R package version 3.8.0. [6] J. T. Leek, W. E. Johnson, H. S. Parker, A. E. Jaffe, and J. D. Storey, “The sva package for removing batch effects and other unwanted variation in high-throughput experiments.,” Bioinformatics, vol. 28, no. 6, pp. 882–883, Mar. 2012. [7] W. E. Johnson, C. Li, and A. Rabinovic, “Adjusting batch effects in microarray expression data using empirical Bayes methods.,” Biostatistics, vol. 8, no. 1, pp. 118–127, Jan. 2007. [8] G. Liu, A. E. Loraine, R. Shigeta, M. Cline, J. Cheng, V. Valmeekam, S. Sun, D. Kulp, and M. A. Siani-Rose, “NetAffx: Affymetrix probesets and annotations.,” Nucleic Acids Res., vol. 31, no. 1, pp. 82–86, Jan. 2003. [9] G. K. Smyth, “Linear models and empirical bayes methods for assessing differential expression in microarray experiments.,” Stat Appl Genet Mol Biol, vol. 3, p. Article3, 2004. [10] Y. Benjamini and Y. Hochberg, “Controlling the false discovery rate: a practical and powerful approach to multiple testing,” Journal of the Royal Statistical Society Series B …, 1995.
