Conservation of core gene expression in vertebrate tissues

Department of Molecular Genetics, University of Toronto, 160 College Street, Toronto, Ontario, Canada.
Journal of Biology 05/2009; 8(3):33. DOI: 10.1186/jbiol130
Source: PubMed


Vertebrates share the same general body plan and organs, possess related sets of genes, and rely on similar physiological mechanisms, yet show great diversity in morphology, habitat and behavior. Alteration of gene regulation is thought to be a major mechanism in phenotypic variation and evolution, but relatively little is known about the broad patterns of conservation in gene expression in non-mammalian vertebrates.
We measured expression of all known and predicted genes across twenty tissues in chicken, frog and pufferfish. By combining the results with human and mouse data and considering only ten common tissues, we have found evidence of conserved expression for more than a third of unique orthologous genes. We find that, on average, transcription factor gene expression is neither more nor less conserved than that of other genes. Strikingly, conservation of expression correlates poorly with the amount of conserved nonexonic sequence, even using a sequence alignment technique that accounts for non-collinearity in conserved elements. Many genes show conserved human/fish expression despite having almost no nonexonic conserved primary sequence.
There are clearly strong evolutionary constraints on tissue-specific gene expression. A major challenge will be to understand the precise mechanisms by which many gene expression patterns remain similar despite extensive cis-regulatory restructuring.

Download full-text


Available from: Andrew Wilde, Oct 01, 2015
18 Reads
  • Source
    • "We used high-throughput Illumina sequencing (RNA-seq) to identify transcribed genes in the endometrium during pregnancy in five Eutherian mammals (dog, cow, horse, pig, and armadillo), a marsupial (short-tailed opossum), and a Monotreme (platypus) and combined these data with existing gene expression data from the decidualized Rhesus monkey endometrium (Liu et al., 2012), decidualized mouse endometrium (McConaha et al., 2011), pregnant lizard uterus (Brandley et al., 2012), chicken uterus (Chan et al., 2010), and frog uterus (Chan et al., 2009). We also used RNA-seq to identify transcribed genes in human decidualized endometrial stromal cells (DSCs) in culture and combined these data with existing gene expression data from human decidual natural killer (dNK) cells (Hanna et al., 2006), decidual macrophage cells (dMP) (Svensson et al., 2011), and decidual endothelial cells (dECs). "
    [Show abstract] [Hide abstract]
    ABSTRACT: A major challenge in biology is determining how evolutionarily novel characters originate; however, mechanistic explanations for the origin of new characters are almost completely unknown. The evolution of pregnancy is an excellent system in which to study the origin of novelties because mammals preserve stages in the transition from egg laying to live birth. To determine the molecular bases of this transition, we characterized the pregnant/gravid uterine transcriptome from tetrapods to trace the evolutionary history of uterine gene expression. We show that thousands of genes evolved endometrial expression during the origins of mammalian pregnancy, including genes that mediate maternal-fetal communication and immunotolerance. Furthermore, thousands of cis-regulatory elements that mediate decidualization and cell-type identity in decidualized stromal cells are derived from ancient mammalian transposable elements (TEs). Our results indicate that one of the defining mammalian novelties evolved from DNA sequences derived from ancient mammalian TEs co-opted into hormone-responsive regulatory elements distributed throughout the genome. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Cell Reports 01/2015; 10(4). DOI:10.1016/j.celrep.2014.12.052 · 8.36 Impact Factor
  • Source
    • "Comparative expression studies provide important insights into biological processes and can lead to the discovery of unknown regulation patterns. While evolutionary constraints on tissue-specific gene expression patterns have been extensively investigated [7-9,75,76], the constitutive regulation of RBP-mediated interactions is still poorly understood [11,12]. It has been previously observed that cellular localization and gene expression levels impose stringent conditions on the physicochemical properties of both protein and RNA sequences [77,78], but large-scale computational analyses of constitutive RBP-mediated regulatory networks have never been attempted before. "
    [Show abstract] [Hide abstract]
    ABSTRACT: RNA-binding proteins regulate a number of cellular processes, including synthesis, folding, translocation, assembly and clearance of RNAs. Recent studies have reported that an unexpectedly large number of proteins are able to interact with RNA, but partners of many RNA-binding proteins are still uncharacterized. We combined prediction of ribonucleoprotein interactions, based on catRAPID calculations, with analysis of protein and RNA expression profiles from human tissues. We found strong interaction propensities for both positively- and negatively-correlated expression patterns. Our integration of in silico and ex vivo data unraveled two major types of protein-RNA interactions, with positively-correlated patterns related to cell cycle control and negatively-correlated patterns related to survival, growth and differentiation. To facilitate the investigation of protein-RNA interaction and expression networks, we developed the catRAPID express webserver. Our analysis sheds light on the role of RNA-binding proteins in regulating proliferation and differentiation processes, and we provide a data exploration tool to aid the design of future experimental studies.
    Genome biology 01/2014; 15(1):R13. DOI:10.1186/gb-2014-15-1-r13 · 10.81 Impact Factor
  • Source
    • "In fact, most of the data used in earlier comparative studies were limited either to a relatively small number of tissue types (e.g. [5,7,16]), or to a larger but only partly overlapping set of tissues between human and mouse [6]. Nevertheless, our results are in conjunction with some of the earlier studies [6,16] and can be attributed to the conservation of functionally fundamental biological processes. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Predicting molecular responses in human by extrapolating results from model organisms requires a precise understanding of the architecture and regulation of biological mechanisms across species. Here, we present a large-scale comparative analysis of organ and tissue transcriptomes involving the three mammalian species human, mouse and rat. To this end, we created a unique, highly standardized compendium of tissue expression. Representative tissue specific datasets were aggregated from more than 33,900 Affymetrix expression microarrays. For each organism, we created two expression datasets covering over 55 distinct tissue types with curated data from two independent microarray platforms. Principal component analysis (PCA) revealed that the tissue-specific architecture of transcriptomes is highly conserved between human, mouse and rat. Moreover, tissues with related biological function clustered tightly together, even if the underlying data originated from different labs and experimental settings. Overall, the expression variance caused by tissue type was approximately 10 times higher than the variance caused by perturbations or diseases, except for a subset of cancers and chemicals. Pairs of gene orthologs exhibited higher expression correlation between mouse and rat than with human. Finally, we show evidence that tissue expression profiles, if combined with sequence similarity, can improve the correct assignment of functionally related homologs across species. The results demonstrate that tissue-specific regulation is the main determinant of transcriptome composition and is highly conserved across mammalian species.
    BMC Genomics 10/2013; 14(1):716. DOI:10.1186/1471-2164-14-716 · 3.99 Impact Factor
Show more