Literature DB >> 17301236

Tissue-driven hypothesis of genomic evolution and sequence-expression correlations.

Xun Gu1, Zhixi Su.   

Abstract

To maintain normal physiological functions, different tissues may have different developmental constraints on expressed genes. Consequently, the evolutionary tolerance for genomic evolution varies among tissues. Here, we formulate this argument as a "tissue-driven hypothesis" based on the stabilizing selection model. Moreover, several predicted genomic correlations are tested by the human-mouse microarray data. Our results are as follows. First, between the human and mouse, we have elaborated the among-tissue covariation between tissue expression distance (E(ti)) and tissue sequence distance (D(ti)). This highly significant E(ti) - D(ti) correlation emerges when the expression divergence and protein sequence divergence are under the same tissue constraints. Second, the tissue-driven hypothesis further explains the observed significant correlation between the tissue expression distance (between the human and mouse) and the duplicate tissue distance (T(dup)) between human (or mouse) paralogous genes. In other words, between-duplicate and interspecies expression divergences covary among tissues. Third, for genes with the same expression broadness, we found that genes expressed in more stringent tissues (e.g., neurorelated) generally tend to evolve more slowly than those in more relaxed tissues (e.g., hormone-related). We conclude that tissue factors should be considered as an important component in shaping the pattern of genomic evolution and correlations.

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Year:  2007        PMID: 17301236      PMCID: PMC1815258          DOI: 10.1073/pnas.0610797104

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  29 in total

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3.  Divergence in the spatial pattern of gene expression between human duplicate genes.

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4.  Estimating the distribution of fitness effects from DNA sequence data: implications for the molecular clock.

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Journal:  Proc Natl Acad Sci U S A       Date:  2003-08-18       Impact factor: 11.205

Review 5.  Natural selection on gene expression.

Authors:  Yoav Gilad; Alicia Oshlack; Scott A Rifkin
Journal:  Trends Genet       Date:  2006-06-27       Impact factor: 11.639

6.  Determinants of substitution rates in mammalian genes: expression pattern affects selection intensity but not mutation rate.

Authors:  L Duret; D Mouchiroud
Journal:  Mol Biol Evol       Date:  2000-01       Impact factor: 16.240

7.  Intra- and interspecific variation in primate gene expression patterns.

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Journal:  Science       Date:  2002-04-12       Impact factor: 47.728

8.  Mammalian housekeeping genes evolve more slowly than tissue-specific genes.

Authors:  Liqing Zhang; Wen-Hsiung Li
Journal:  Mol Biol Evol       Date:  2003-10-31       Impact factor: 16.240

9.  Elevated gene expression levels distinguish human from non-human primate brains.

Authors:  Mario Cáceres; Joel Lachuer; Matthew A Zapala; John C Redmond; Lili Kudo; Daniel H Geschwind; David J Lockhart; Todd M Preuss; Carrolee Barlow
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-13       Impact factor: 11.205

Review 10.  Induced gene expression in human brain after the split from chimpanzee.

Authors:  Jianying Gu; Xun Gu
Journal:  Trends Genet       Date:  2003-02       Impact factor: 11.639

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  31 in total

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2.  Evolutionary rate and gene expression across different brain regions.

Authors:  Tamir Tuller; Martin Kupiec; Eytan Ruppin
Journal:  Genome Biol       Date:  2008       Impact factor: 13.583

3.  Genome factor and gene pleiotropy hypotheses in protein evolution.

Authors:  Yanwu Zeng; Xun Gu
Journal:  Biol Direct       Date:  2010-05-24       Impact factor: 4.540

4.  Differences in duplication age distributions between human GPCRs and their downstream genes from a network prospective.

Authors:  Yong Huang; Ying Zheng; Zhixi Su; Xun Gu
Journal:  BMC Genomics       Date:  2009-07-07       Impact factor: 3.969

5.  Organ evolution in angiosperms driven by correlated divergences of gene sequences and expression patterns.

Authors:  Ruolin Yang; Xiangfeng Wang
Journal:  Plant Cell       Date:  2013-01-22       Impact factor: 11.277

6.  Divergent and nonuniform gene expression patterns in mouse brain.

Authors:  John A Morris; Joshua J Royall; Darren Bertagnolli; Andrew F Boe; Josh J Burnell; Emi J Byrnes; Cathy Copeland; Tsega Desta; Shanna R Fischer; Jeff Goldy; Katie J Glattfelder; Jolene M Kidney; Tracy Lemon; Geralyn J Orta; Sheana E Parry; Sayan D Pathak; Owen C Pearson; Melissa Reding; Sheila Shapouri; Kimberly A Smith; Chad Soden; Beth M Solan; John Weller; Joseph S Takahashi; Caroline C Overly; Ed S Lein; Michael J Hawrylycz; John G Hohmann; Allan R Jones
Journal:  Proc Natl Acad Sci U S A       Date:  2010-10-18       Impact factor: 11.205

7.  Gene age predicts the strength of purifying selection acting on gene expression variation in humans.

Authors:  Konstantin Y Popadin; Maria Gutierrez-Arcelus; Tuuli Lappalainen; Alfonso Buil; Julia Steinberg; Sergey I Nikolaev; Samuel W Lukowski; Georgii A Bazykin; Vladimir B Seplyarskiy; Panagiotis Ioannidis; Evgeny M Zdobnov; Emmanouil T Dermitzakis; Stylianos E Antonarakis
Journal:  Am J Hum Genet       Date:  2014-12-04       Impact factor: 11.025

8.  Evolution of vertebrate tissues driven by differential modes of gene duplication.

Authors:  Masanobu Satake; Masakado Kawata; Aoife McLysaght; Takashi Makino
Journal:  DNA Res       Date:  2012-04-05       Impact factor: 4.458

9.  Assessing the evolution of gene expression using microarray data.

Authors:  Owen Z Woody; Andrew C Doxey; Brendan J McConkey
Journal:  Evol Bioinform Online       Date:  2008-04-24       Impact factor: 1.625

10.  Flagellated algae protein evolution suggests the prevalence of lineage-specific rules governing evolutionary rates of eukaryotic proteins.

Authors:  Ting-Yan Chang; Ben-Yang Liao
Journal:  Genome Biol Evol       Date:  2013       Impact factor: 3.416

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