Project description:Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear. To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth. We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific. Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators. Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling. Tissue transcriptomes from 9 tissues from 5 species, 3 individuals per species, were sequenced and compared (two samples for mouse_heart). <br> Curation note: E-GEOD-41637 (9 tissues, 5 organisms) has been split into five artefactual ArrayExpress experiments, one experiment per species for inclusion in Expression Atlas. Each artefactual experiment omits the processed data files (which are still available via the original E-GEOD-41637 records). Chicken: E-MTAB-2797; Cow: E-MTAB-2798; Rhesus monkey: E-MTAB-2799; Rat: E-MTAB-2800; Mouse: E-MTAB-2801
Project description:Most mammalian genes produce multiple distinct mRNAs through alternative splicing, but the extent of splicing conservation is not clear. To assess tissue-specific transcriptome variation across mammals, we sequenced cDNA from 9 tissues from 4 mammals and one bird in biological triplicate, at unprecedented depth. We find that while tissue-specific gene expression programs are largely conserved, alternative splicing is well conserved in only a subset of tissues and is frequently lineage-specific. Thousands of novel, lineage-specific and conserved alternative exons were identified; widely conserved alternative exons had signatures of binding by MBNL, PTB, RBFOX, STAR and TIA family splicing factors, implicating them as ancestral mammalian splicing regulators. Our data also indicates that alternative splicing is often used to alter protein phosphorylatability, delimiting the scope of kinase signaling.
Project description:Whole genome sequencing data of low risk neuroblastoma tumors and matching controls used to study the evolutionary dynamics of neuroblastoma.
Project description:Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals. Our transcriptome data provide a valuable resource for functional and evolutionary analyses of mammalian genomes. To study mammalian transcriptome evolution at high resolution, we generated RNA-Seq data (∼3.2 billion Illumina Genome Analyser IIx reads of 76 base pairs) for the polyadenylated RNA fraction of brain (cerebral cortex or whole brain without cerebellum), cerebellum, heart, kidney, liver and testis (usually from one male and one female per somatic tissue and two males for testis) from nine mammalian species: placental mammals (great apes, including humans; rhesus macaque; mouse), marsupials (gray short-tailed opossum) and monotremes (platypus). Corresponding data (∼0.3 billion reads) were generated for a bird (red jungle fowl, a non-domesticated chicken) and used as an evolutionary outgroup.
Project description:Long-term laboratory evolution experiments provide a controlled record of evolutionary dynamics and metabolic change in microorganisms. Nevertheless, the correspondence between genetic mutation and phenotypic adaptation remains elusive, partly because of the overwhelming number of genetic changes that accrue after tens-of-thousands of generations. Using a coarse-grained characterization of bacterial physiology applied to Lenski's laboratory-evolved strains of Escherichia coli, we identify an intermediate measure between genotype and phenotype that provides insight into the dynamics of adaptation.
Project description:Characterizing the evolutionary history of a gene’s expression profile is a critical component for understanding the relationship between genotype, expression, and phenotype. However, it is not well-established how best to distinguish the different evolutionary forces acting on gene expression. Here, we use RNA-seq across 7 tissues from 17 mammalian species to show that expression evolution across mammals is accurately modeled by the Ornstein-Uhlenbeck (OU) process. This stochastic process models expression trajectories across time as Gaussian distributions whose variance is parameterized by the rate of genetic drift and strength of stabilizing selection. We use these mathematical properties to identify expression pathways under neutral, stabilizing, and directional selection, quantify the extent of selective pressure on a gene’s expression, and detect deleterious expression levels outside expected evolutionary distributions in single patients. Our work provides a statistical framework for interpreting expression data across species and in disease.