Faculty Opinions recommendation of The evolution of gene regulation underlies a morphological difference between two Drosophila sister species.

2008 ◽  
Author(s):  
Yoav Gilad
Keyword(s):  
Gene Regulation ◽  
Morphological Difference ◽  
Sister Species ◽  
Evolution Of Gene Regulation

scholarly journals The Evolution of Gene Regulation Underlies a Morphological Difference between Two Drosophila Sister Species

Cell ◽  
2008 ◽  
Vol 132 (5) ◽  
pp. 783-793 ◽  
Author(s):  
Sangyun Jeong ◽  
Mark Rebeiz ◽  
Peter Andolfatto ◽  
Thomas Werner ◽  
John True ◽  
...  
Keyword(s):  
Gene Regulation ◽  
Morphological Difference ◽  
Sister Species ◽  
Evolution Of Gene Regulation

scholarly journals Evolution of gene regulation between ascidian species

2017 ◽  
Vol 145 ◽  
pp. S108-S109
Author(s):  
Alicia Madgwick ◽  
Damien Gailly ◽  
Marta Silvia Magri ◽  
José-Luis Gomez-Skarmeta ◽  
Patrick Lemaire
Keyword(s):  
Gene Regulation ◽  
Ascidian Species ◽  
Evolution Of Gene Regulation

scholarly journals Evolution of Gene Regulation: Hybrid Networks Breed Diversity

2012 ◽  
Vol 22 (23) ◽  
pp. R1009-R1011
Author(s):  
Andrea I. Ramos ◽  
Scott Barolo
Keyword(s):  
Gene Regulation ◽  
Hybrid Networks ◽  
Evolution Of Gene Regulation

scholarly journals Coexpression reveals conserved mechanisms of transcriptional cell identity

2020 ◽  
Author(s):  
Megan Crow ◽  
Hamsini Suresh ◽  
John Lee ◽  
Jesse Gillis
Keyword(s):  
Gene Regulation ◽  
Cell Types ◽  
Regulatory Evolution ◽  
Closely Related Species ◽  
Cell Identity ◽  
Gene Coexpression ◽  
Evolution Of Gene Regulation ◽  
Orthology Prediction ◽  
Species Specific ◽  
Coexpression Networks

ABSTRACTWhat makes a mouse a mouse, and not a hamster? The answer lies in the genome, and more specifically, in differences in gene regulation between the two organisms: where and when each gene is expressed. To quantify differences, a typical study will either compare functional genomics data from homologous tissues, limiting the approach to closely related species; or compare gene repertoires, limiting the resolution of the analysis to gross correlations between phenotypes and gene family size. As an alternative, gene coexpression networks provide a basis for studying the evolution of gene regulation without these constraints. By incorporating data from hundreds of independent experiments, meta-analytic coexpression networks reflect the convergent output of species-specific transcriptional regulation.In this work, we develop a measure of regulatory evolution based on gene coexpression. Comparing data from 14 species, we quantify the conservation of coexpression patterns 1) as a function of evolutionary time, 2) across orthology prediction algorithms, and 3) with reference to cell- and tissue-specificity. Strikingly, we uncover deeply conserved patterns of gradient-like expression across cell types from both the animal and plant kingdoms. These results suggest that ancient genes contribute to transcriptional cell identity through mechanisms that are independent of duplication and divergence.

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