


Data from: Rund et al, 2011 PNAS 108(32):E421E430; and Rund et al, 2013 BMC Genomics 14(1): 218 You may search by: Tissue information: Head and body tissue samples are from adult females mated, but not bloodfed An. gambiae (Pimperena S form) mosquitoes maintained at 85% relative humidity and 27 ± 1^{o}C in either constant dark (DD) conditions or a 12:12 light:dark (LD) cycle (11 hrs full light (~250 lux), 11 hrs darkness, and 1 hr dawn and 1 hr dusk transitions). Access to a 5% solution of fructose was provided ad libitum. Experiments began with female 79 days post emergence with 2030 mosquitoes harvested every 4 hrs for 48 hrs. Chart information: yaxis  probe set fluorescence intensity after GCRMA normalization. xaxis  time in hours. The light:dark cycle (LD) experiments are described in Zeitgeber Time (ZT), with ZT12 defined as time of lights OFF under the LD cycle, and ZT0 defined as end of the dawn transition. Constant darkness (DD) experiments are described in Circadian Time (CT), with CT0 defined as the end of subjective dawn, inferred from ZT0 of the previous LD cycle. Gene symbol and description Gene names and description were annotated primarily from information stored at VectorBase, often using the closest homologue from Ae. aegypti (AAEG), Cx. quinquefasciatus (CQUI), Drosophila (DMEL) or C. elegans (CELG) (in that order), but also using published literature and the Database for Annotation, Visualization and Integrated Discovery (DAVID). Expression values: For gene profiles with values below an average fluorescence value of ~20, please be extra cautious when interpreting the data. For our paper, we chose to only include profiles with a mean fluorescent intensity across all 13 time points in both replicates of >20 (which would exclude >99% of Plasmodium genes on the microarray). Statistical detection of rhythmic components: You may filter by COSOPT pvalue. In Rund et al (2011) a pvalue < 0.1 was chosen as the maximum threshold for a rhythmic gene, in line with Panda et al (2002). COSOPT measures the goodnessoffit between our experimental data and a series of cosine curves with varying phases and (user defined) period lengths. Pvalues are determined by scrambling experimental data and refitting it to cosine curves to determine probability that the observed data matches a cosine curve by chance alone. In our analysis presented here, statistics are only reported for profiles with period lengths of 18.5  26.5 hrs for constant condition experiments (DD) or 2028 hrs for LD experiments. COSOPT generates period length and phase estimates. Where a pvalue is provided for only a single replicate time course, a "ONE" designate is provided in the far right column, and the COSOPT values provided (pvalue, period length and phase) are derived from this single time course. The charted data always show the combined replicate data. JTK_CYCLE is a nonparametric statistical algorithm designed to identify and characterize cycling variables in large data sets. It applies the JonckheereTerpstraKendall (JT) test and Kendall's tau (rank correlation) (K), finding the optimal combination of period and phase that minimizes the pvalue of Kendall tau correction between the experimental time series and each tested cyclical ordering, this being derived from cosine curves. Analysis was restricted to 16  28 hr period lengths. JTK_CYCLE generates period length, phase and amplitude estimates, as well as corrects for multiple comparisons post hoc. The pvalue for a given probe set was converted to a more stringent qvalue, which takes into consideration the possible false positive rate across all probe sets. Amplitude value reflects the 1cycle median signadjusted deviation from the median in relation to the optimal cosine pattern [for a perfect cosine wave, this is amplitude (median absolute derivation from the median)/sqrt(2)]. For example an amplitude of 0.45 represents approximately a 2.5fold peak to trough rhythm (e.g.cdsA), 0.88 represents a 10fold rhythm (e.g. CYP6M2), and 2.23 represents a 135fold rhythm (e.g. CRY2). Additional data formats and views: Gene Expression Omnibus (GEO): Accession no. GSE22585 VectorBase Gene Expression: (Click here) Relevant publications: Anopheles gambiae diel and circadian transcriptional profiling: Rund SSC, Hou TY, Ward SM, Collins FH and Duffield GE. 2011. Genomewide profiling of diel and circadian gene expression of the malaria vector Anopheles gambiae. Proceedings of the National Academy of Sciences USA 108 (32): E421E430 (Link) Rund SSC, Gentile JE and Duffield GE. 2013. Extensive circadian and light regulation of the transcriptome in the malaria mosquito Anopheles gambiae. BMC Genomics 14: 218 (Link) COSOPT algorithm: Straume M. 2004. DNA microarray time series analysis: Automated statistical assessment of circadian rhythms in gene expression patterning. Methods in Enzymology 383:14966 Panda S, Antoch MP, Miller BH, Su AI, Schook AB, Straume M, Schultz PG, Kay SA, Takahashi JS, Hogenesch JB. 2002. Coordinated transcription of key pathways in the mouse by the circadian clock. Cell 109:30720 JTK_CYCLE algorithm: Hughes ME, Hogenesch JB, Kornacker K. 2010. JTK_CYCLE: An efficient nonparametric algorithm for detecting rhythmic components in genomescale data sets. Journal of Biological Rhythms 25:37280 CIRCA System: Hughes ME, DeHaro L, DiTacchio L, Hayes K, Pullivarthy S, Panda S, and Hogenesch JB. 2007. High resolution time course analysis of gene expression from the liver and pituitary. Cold Spring Harbor Symposia on Quantitative Biology 72:381386 Hughes ME, DiTacchio L, Hayes K, Vollmers C, Pulivarthy S, Baggs J. 2009. Harmonics of circadian gene transcription in mammals. PLOS Genetics 5:e1000442 Pizarro A, Hayer K, Lahens NF, Hogenesch JB. 2013. CircaDB: a database of mammalian circadian gene expression profiles. Nucleic Acids Research 41(D1):D1009D1013 DAVID: Huang D, Sherman B, Lempicki R. 2008. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4:4457 
Data from: Leming et al, 2014 BMC Genomics 15(1):1128 You may search by: Tissue information: Mosquitoes were maintained at 85% relative humidity and 27 ± 1^{o}C in either constant dark (DD) conditions or a 12:12 light:dark (LD) cycle (11 hrs full light (~250 lux), 11 hrs darkness, with 1 hr dawn and 1 hr dusk transitions). Access to a 5% solution of fructose was provided ad libitum. Head tissue samples were collected from adult female presumed mostly mated but not bloodfed Ae. aegypti mosquitoes of the Wh (Higgs White Eye) strain. Experiments began with females 26 days post emergence with 2030 mosquitoes harvested every 4 hrs for 44 hrs. Chart information yaxis  average probe set fluorescence intensity. These values were determined after normalization with the Robust Multiarray Average (RMA) as described by Irizarry et al (2003). xaxis  time in hours. The light:dark cycle (LD) experiments are described in Zeitgeber Time (ZT), with ZT13 defined as the time of lights off under the LD cycle, and ZT1 defined as end of the dawn transition. Constant darkness (DD) experiments are described in Circadian Time (CT), with CT1 defined as the end of subjective dawn, inferred from ZT1 of the previous LD cycle. Gene symbol and description: Gene names and description were annotated from the information stored on VectorBase.org. Expression values: The RMA algorithm was used to determine expression values for all genes. Background levels of fluorescence was determined to be 52.8 in LD and 51.7 in DD. Therefore, for gene profiles with expression values below these please be extra cautious when interpreting the data. To determine background levels the expression data was log2 transformed, mean centered, and normalized across the time course for each gene. We then identified a group of genes that showed minimal expression across the experimental samples by using the Cluster 3.0 program. The Pearson correlation was used as a distance measure to cluster the expression variation for identification of different gene groups as previously described. From this we determined that the level of background for fluorescence was as mentioned above. Statistical detection of rhythmic components: In Leming et al (2014) a pvalue of 0.05 was chosen as the maximum threshold for a rhythmic gene. JTK_CYCLE is a nonparametric statistical algorithm designed to identify and characterize cycling variables in large data sets. This algorithm generates period length, phase and amplitude estimates, and also corrects for multiple comparisons post hoc. To achieve this, JTK_CYCLE applies the JonckheereTerpstraKendall (JT) test and Kendall's tau (rank correlation) (K). These tests find the optimal combination of period and phase that minimizes the pvalue of the Kendall tau correction between the experimental time series and all tested cyclical orders, this being derived from cosine curves. Amplitude values reflect the 1cycle median signadjusted deviation from the median in relation to the optimal cosine pattern [for a perfect cosine wave, this is amplitude (median absolute derivation from the median)/sqrt(2)]. Analysis was restricted to 2028 hr period lengths in LD and 1828 hr period lengths in DD. Additional data formats and views: Gene Expression Omnibus (GEO): Accession no. GSE60496 VectorBase Gene Expression: (Coming Soon) Relevant publications: Ae. aegypti diel and circadian transcriptional profiling: Leming MT, Rund SSC, Behura SK, Duffield GE, O'Tousa JE. 2014. A database of circadian and diel rhythmic gene expression in the yellow fever mosquito Aedes aegypti. BMC Genomics 15(1):1128 (Link) JTK_CYCLE algorithm: Hughes ME, Hogenesch JB, Kornacker K. 2010. JTK_CYCLE: An efficient nonparametric algorithm for detecting rhythmic components in genomescale data sets. Journal of Biological Rhythms 25:37280 Statistical analysis: Irizarry RA, Bolstad BM, Collin F, Cope LM, Hobbs B, and Speed TP. 2003. Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Research 31: e15 de Hoon MJ, Imoto S, Nolan J and Miyano S. 2004. Open source clustering software. Bioinformatics 20: 14534 Chauhan C, Behura SK, Debruyn B, Lovin DD, Harker BW, GomezMachorro C, Mori A, RomeroSeverson J and Severson DW. 2012. Comparative expression profiles of midgut genes in dengue virus refractory and susceptible Aedes aegypti across critical period for virus infection. PLoS One 7: e47350 Eisen MB, Spellman PT, Brown PO and Botstein D. 1998. Cluster analysis and display of genomewide expression patterns. Proceedings of the National Academy of Sciences USA 95: 148638 