* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Download ppt for
Oncogenomics wikipedia , lookup
Quantitative trait locus wikipedia , lookup
Transposable element wikipedia , lookup
History of genetic engineering wikipedia , lookup
Cancer epigenetics wikipedia , lookup
Koinophilia wikipedia , lookup
Gene nomenclature wikipedia , lookup
Gene desert wikipedia , lookup
Minimal genome wikipedia , lookup
Epigenetics in learning and memory wikipedia , lookup
Public health genomics wikipedia , lookup
Pathogenomics wikipedia , lookup
Epigenetics of neurodegenerative diseases wikipedia , lookup
Epigenetics of depression wikipedia , lookup
Gene therapy of the human retina wikipedia , lookup
Ridge (biology) wikipedia , lookup
Polycomb Group Proteins and Cancer wikipedia , lookup
Genome (book) wikipedia , lookup
X-inactivation wikipedia , lookup
Helitron (biology) wikipedia , lookup
Designer baby wikipedia , lookup
Epigenetics of human development wikipedia , lookup
Genomic imprinting wikipedia , lookup
Therapeutic gene modulation wikipedia , lookup
Long non-coding RNA wikipedia , lookup
Epigenetics of diabetes Type 2 wikipedia , lookup
Artificial gene synthesis wikipedia , lookup
Site-specific recombinase technology wikipedia , lookup
Genome evolution wikipedia , lookup
Microevolution wikipedia , lookup
Nutriepigenomics wikipedia , lookup
Gene expression profiling wikipedia , lookup
Mir-92 microRNA precursor family wikipedia , lookup
SHI Meng Abstract • 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 ofmammalian 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 inmammalswas 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. Background • Regulatory mutations affecting gene expression probably explain many or even most phenotypic differences between species • RNA-seq protocols now allows for accurate and sensitive assessments of expression levels Data • RNA-seq data – 3.2 billion Illumina Genome Analyser IIx reads of 76 base pairs • Tissues: – fraction of brain, cerebellum, heart, kidney, liver and testis • Species: – placental mammals: great apes, including humans; rhesus macaque; mouse – marsupials: grey short-tailed opossum – monotremes: platypus – bird: red jungle fowl Procedure • refined existing Ensembl genome annotations • remapped RNA-seq reads and resolved read mapping ambiguities • comparative analyses of expression levels of protein-coding genes RNA-seq and genome reannotation • • • • • modified boundaries for 31,000–44,500 exons 20,000–34,500 new exons 66,000–125,000 new splice junctions thousands of multi-exonic transcribed loci lower levels and significantly less conserved RNA-seq and genome reannotation • 11–30% of the total genomic length is covered by unambiguously mapped RNA-seq reads • 34–61% of amniote genomes are transcribed • ten amniote species: 5,636 1:1 orthologues • six primates: 13,277 1:1 orthologues Mammalian gene expression phylogenies Mammalian gene expression phylogenies • Neighbour-joining trees • distance: 1-ρ(Spearman’s correlation coefficient) Mammalian gene expression phylogenies • Primate expression phylogenies Rates of expression change in lineages and organs • The branch lengths from the common ancestor of all species to the tips of the tree are remarkably similar • the branches leading to mouse are significantly shorter in several tissues: strong purifying selection • total branch lengths of the trees vary widely among tissues Gene expression evolution on the X chromosome • compared rates of expression change for genes that are Xlinked in both eutherians and marsupials and autosomal genes • in the common ancestor of therian mammals: faster on the X chromosome • more recently: similar to that of autosomes Modular gene expression change • Modular: groups of genes that have coherent expression patterns over subsets of samples – 639 modules in the all-amniote data – 197 modules in the primate-specific data • 33 organ-specific modules with conserved expression levels among species – typical processes, define common primate/mammalian organ functions • 145 modules specific to an organ with distinct lineage-specific expression patterns – 25 nervous tissue modules Modular gene expression change • Internal branches of the mammalian phylogeny – 8 out of 32 modules in brain, cerebellumand/or testis are highly enriched with X-linked genes and became strongly down-regulated • Modular expression changes between mammals and chicken – neural tissues and in kidney and liver – 4 significantly enriched with X-linked genes • Humans only lineage with brain-specific expression modules in the primate data set – neuron insulation Modular gene expression change Expression shifts of individual genes • a maximum-likelihood framework for modelling gene expression evolution along a phylogeny • 9,255 significant expression changes • 63% tested amniote orthologues and 33% tested primate orthologues experienced at least one significant expression shift • the testis: largest number; the brain: few (except for the primate ancestral branch) Expression shifts of individual genes Conclusion • refines previous hypotheses • provides many new clues to the function and evolution of mammalian genomes • exploitation of the reported transcriptome data Thank you!