Drosophila melanogaster is one of the most well studied genetic model organisms, nonetheless its genome still contains unannotated coding and non-coding genes, transcripts, exons, and RNA editing sites. Full discovery and annotation are prerequisites for understanding how the regulation of transcription, splicing, and RNA editing directs development of this complex organism. We used RNA-Seq, tiling microarrays, and cDNA sequencing to explore the transcriptome in 30 distinct developmental stages. We identified 111,195 new elements, including thousands of genes, coding and non-coding transcripts, exons, splicing and editing events and inferred protein isoforms that previously eluded discovery using established experimental, prediction and conservation-based approaches. Together, these data substantially expand the number of known transcribed elements in the Drosophila genome and provide a high-resolution view of transcriptome dynamics throughout development.

Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species.

To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.

Animal transcriptomes are dynamic, each cell type, tissue and organ system expressing an ensemble of transcript isoforms that give rise to substantial diversity. We identified new genes, transcripts, and proteins using poly(A)+ RNA sequence from Drosophila melanogaster cultured cell lines, dissected organ systems, and environmental perturbations. We found a small set of mostly neural-specific genes has the potential to encode thousands of transcripts each through extensive alternative promoter usage and RNA splicing. The magnitudes of splicing changes are larger between tissues than between developmental stages, and most sex-specific splicing is gonad-specific. Gonads express hundreds of previously unknown coding and long noncoding RNAs (lncRNAs) some of which are antisense to protein-coding genes and produce short regulatory RNAs. Furthermore, previously identified pervasive intergenic transcription occurs primarily within newly identified introns. The fly transcriptome is substantially more complex than previously recognized arising from combinatorial usage of promoters, splice sites, and polyadenylation sites.

Sex chromosomes are primary determinants of sexual dimorphism in many organisms. These chromosomes are thought to arise via the divergence of an ancestral autosome pair and are almost certainly influenced by differing selection in males and females. Exploring how sex chromosomes differ from autosomes is highly amenable to genomic analysis. We examined global gene expression in Drosophila melanogaster and report a dramatic underrepresentation of X-chromosome genes showing high relative expression in males. Using comparative genomics, we find that these same Xchromosome genes are exceptionally poorly conserved in the mosquito Anopheles gambiae. These data indicate that the X chromosome is a disfavored location for genes selectively expressed in males.

High-throughput sequencing of cDNA (RNA-seq) is a widely deployed transcriptome profiling and annotation technique, but questions about the performance of different protocols and platforms remain. We used a newly developed pool of 96 synthetic RNAs with various lengths, and GC content covering a 2 20 concentration range as spike-in controls to measure sensitivity, accuracy, and biases in RNA-seq experiments as well as to derive standard curves for quantifying the abundance of transcripts. We observed linearity between read density and RNA input over the entire detection range and excellent agreement between replicates, but we observed significantly larger imprecision than expected under pure Poisson sampling errors. We use the control RNAs to directly measure reproducible protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias. These effects lead to biased quantification for short transcripts and individual exons, which is a serious problem for measurements of isoform abundances, but that can partially be corrected using appropriate models of bias. By using the control RNAs, we derive limits for the discovery and detection of rare transcripts in RNA-seq experiments. By using data collected as part of the model organism and human Encyclopedia of DNA Elements projects (ENCODE and modENCODE), we demonstrate that external RNA controls are a useful resource for evaluating sensitivity and accuracy of RNA-seq experiments for transcriptome discovery and quantification. These quality metrics facilitate comparable analysis across different samples, protocols, and platforms.[Supplemental material is available for this article.]High-throughput sequencing applications are revolutionizing genome-wide analysis (Mardis 2008;Mortazavi et al. 2008;Celniker et al. 2009;Morozova et al. 2009;Gerstein et al. 2010;Metzker 2010;Roy et al. 2010). RNA-seq offers single-nucleotide resolution, strand specificity, and short-range connectivity through pairedend sequencing. Because of these strengths, there has been great interest in using RNA-seq to distinguish isoforms, calculate expression levels for transcripts, and uncover low abundance RNAs (He et al. 2008;Mortazavi et al. 2008;Nagalakshmi et al. 2008;Sultan et al. 2008;Wang et al. 2008Wang et al. , 2010Passalacqua et al. 2009;Gerstein et al. 2010;Roy et al. 2010;Trapnell et al. 2010;Berezikov et al. 2011;Graveley et al. 2011).While there are clear advantages to RNA-seq, it is less clear how well the procedure performs, as several studies have reported conflicting RNA-seq accuracy results. RNA-seq-determined concentrations of six in vitro synthetic transcripts show good linearity (Mortazavi et al. 2008), and in a study using quantitative PCR as the benchmark, RNA-seq showed better performance for genes with high expression, while two-channel microarrays were more sensitive in identifying differential expression between genes with low ex...

No abstract

For more than 100 years, the fruit fly Drosophila melanogaster has been one of the most studied model organisms. Here, we present a single-cell atlas of the adult fly, Tabula Drosophilae , that includes 580,000 nuclei from 15 individually dissected sexed tissues as well as the entire head and body, annotated to >250 distinct cell types. We provide an in-depth analysis of cell type–related gene signatures and transcription factor markers, as well as sexual dimorphism, across the whole animal. Analysis of common cell types between tissues, such as blood and muscle cells, reveals rare cell types and tissue-specific subtypes. This atlas provides a valuable resource for the Drosophila community and serves as a reference to study genetic perturbations and disease models at single-cell resolution.