Ontology highlight
ABSTRACT:
PROVIDER: PRJNA507978 | ENA |
REPOSITORIES: ENA
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Project description:Complex multicellular organisms have evolved numerous cell types with many different functions. Comparative transcriptomic data yields valuable insights into cell type, tissue, and organ evolution. However, interpreting this data requires understanding how transcriptomes evolve. A particularly difficult problem is that cell type transcriptomes may not evolve independently, a key assumption of most evolutionary analyses. Non-independence of cell types can occur when cell types share regulatory mechanisms. This leads to concerted evolution in gene expression across different cell types, confounding efforts to unravel the history of cell type evolution, and identify cell type-specific patterns of expression. Here we present a statistical model to estimate the level of concerted transcriptome evolution and apply it to published and new data. The results indicate that tissues undergo pervasive concerted evolution in gene expression. Tissues related by morphology or developmental lineage exhibit higher levels of concerted evolution. Concerted evolution also causes tissues from the same species to be more similar in gene expression to each other than to homologous tissues in another species. This result may explain why some tissue transcriptomes cluster by species rather than homology. Our analysis of bird skin appendages data suggests levels of concerted evolution also varies with phylogenetic age of the tissue. Our study illustrates the importance of accounting for concerted evolution when interpreting comparative transcriptome data, and should serve as a foundation for future investigations of cell type evolution.
2017-10-13 | GSE89040 | GEO
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.
2011-10-12 | E-GEOD-30352 | biostudies-arrayexpress
Project description:Two genetic selection systems that couple metabolite hydroxylation or methylation of small molecules to growth of Escherichia coli are presented in this study. One system targets pterin-dependent hydroxylation (tBPt) while another focuses on S-adenosylmethionine-dependent methylation (SAM). Using adaptive laboratory evolution with growth selection, these two systems are demonstrated to not only achieve in vivo directed evolution of enzymes involved in human hormone biosynthesis but also reveal non-intuitive host factors that elude existing synthetic biology approaches. Raw sequencing data for the relevant strains generated in this study are presented here.
2019-01-30 | E-MTAB-6779 | biostudies-arrayexpress
Project description:To test the conservation and evolution of long non-coding RNAs across multiple rodent species by transcriptome sequencing and histone modification mapping. Part of experiment series: E-MTAB-867 RNA-Seq, E-MTAB-959 ChIP-Seq.
2012-04-01 | E-MTAB-959 | biostudies-arrayexpress
Project description:This experiment contains the subset of data corresponding to rhesus macaque RNA-Seq data from experiment E-GEOD-30352 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-30352/), which goal is to understand the dynamics of mammalian transcriptome evolution. 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.
2011-10-12 | E-MTAB-3717 | biostudies-arrayexpress
Project description:This experiment contains the subset of data corresponding to gray short-tailed opossum RNA-Seq data from experiment E-GEOD-30352 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-30352/), which goal is to understand the dynamics of mammalian transcriptome evolution. 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.
2011-10-12 | E-MTAB-3719 | biostudies-arrayexpress
Project description:This experiment contains the subset of data corresponding to mouse RNA-Seq data from experiment E-GEOD-30352 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-30352/), which goal is to understand the dynamics of mammalian transcriptome evolution. 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.
2011-10-12 | E-MTAB-3718 | biostudies-arrayexpress
Project description:This experiment contains the subset of data corresponding to human RNA-Seq data from experiment E-GEOD-30352 (http://www.ebi.ac.uk/arrayexpress/experiments/E-GEOD-30352/), which goal is to understand the dynamics of mammalian transcriptome evolution. 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.
2011-10-12 | E-MTAB-3716 | biostudies-arrayexpress
Project description:This is a genomic analysis of breast cancer metastasis using array based CGH and is part of a large study investigating the patterns and evolution of metastases from breast cancer using autopsy material accumulated over the last 50 years from a single institution. The samples used in the genomic profiling comprise the primary breast tumour and multiple matched metastases from each patient. The data demonstrate both the clonal nature of metastatic progression and the role of clonal evolution during progression.
2013-11-11 | GSE46826 | GEO
Project description:Transcriptome analysis of isolated mutants using the method Visualizing Evolution in Real-Time (VERT) for the study of n-butanol tolerance. The samples were isolated from an evolution experiment picking samples at different times based in the evolution dynamics obtained with VERT. Mutants were grown in chemostats at 0.8% (v/v) of n-butanol and compared with the expression of wild-type to the same concentration of solvent.
2012-03-31 | GSE30005 | GEO