Unfortunately, no perfect model exists, and all models have inherent limitations

s determined using a qPCR method on a AB 7500 Real-Time PCR System according to the manufacturer’s protocol . The primers matched sequences within adapters flanking an Illumina sequencing library. Before starting qPCR, a control template was selected to measure the libraries for quantification. The control template was a library with a known quantification, template size and library type. The quality of libraries was determined on an Agilent 2100 Bioanalyzer per the manufacturer’s instructions. The size and purity of the samples were checked. The final product was a band at approximately 260 bp. Transcriptome Sequence Assembly and Annotation For sequencing and data analysis, cDNA libraries resulting from male Drosophila were combined in equal concentrations into a single pool and cDNA libraries resulting from female Drosophila were combined in equal concentrations into another pool. Each pool was sequenced in two lanes of the HiSeqTM 2000 sequencing platform during the same sequencing run for a side-by-side comparison. Image data output from the sequencing device were transformed into raw reads and stored in the FASTQ format. These data were filtered to remove raw reads that included the adapter DNA Fragment Enrichment To selectively enrich DNA fragments with adapter molecules on both ends and to amplify the amount of DNA in the library, the PCR process was used according to the manufacturer’s protocol. All of the libraries were processed manually. Gene Expression after Radiation and Pollutants PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/19653943 sequence or which were of low quality. The transcriptome was assembled using Novoalign software and we used Berkeley Drosophila Genome Project assembly, release 5 as a reference. The number of reads per transcript was counted by the coverageBed application. Each of the libraries yielded approximately 50 million or more high-quality filtered sequences. The data discussed in this publication have been MEK162 deposited in NCBI’s Gene Expression Omnibus and are accessible through GEO Series accession number GSE50377. Bioinformatics Analysis of Transcriptome Sequence Data Most of the data analysis procedures were performed in the statistical programming environment R. We used the R package DESeq to conduct comparisons of the genes for all experimental groups, using principal component analysis. PCA is the method of clustering of variance stabilized data to get sampleto-sample distances. It helps to overview over similarities and dissimilarities between samples. PCA was performed to group samples on the basis of their inter-varietal and inter-sex differences in the transcriptomes for 500 top most expressed genes in each sample. The values of the variables were standardized by subtracting their means and dividing by their standard deviation. Plot of the first two principal components is useful for visualizing the overall effect of experimental covariates. We identified differentially expressed genes by comparing all treated groups with an intact control in the R package DSS at Gene Expression after Radiation and Pollutants finally a list of pathways was obtained. Each pathway was assigned an enrichment-score, which was calculated as the ratio of the number of genes from the list included in the pathway to the number of genes in every pathway. We consider a score reliable if it was not less than 0.5. qPCR Verification of RNA-Seq Results qPCR was performed with the primers and probes listed in influence where E efficiency of reaction, Ct threshold cycle, ref ref