Abstract
Comparative functional genomics aims to measure and compare genome-wide functional data such as transcriptomes, proteomes, and epigenomes across multiple species to study the conservation and divergence patterns of such quantitative measurements. However, computational methods to systematically compare these quantitative genomic profiles across multiple species are in their infancy. We developed Arboretum, a novel algorithm to identify modules of co-expressed genes and trace their evolutionary history across multiple species from a complex phylogeny. To interpret the results from Arboretum we developed several measures to examine the extent of conservation and divergence in modules and their relationship to species lifestyle, cis-regulatory elements, and gene duplication. We applied Arboretum to study the evolution of modular transcriptional regulatory programs controlling transcriptional response to different environmental stresses in the yeast Ascomycota phylogeny. We found that modules of similar patterns of expression captured the transcriptional responses to different stresses across species; however, the genes exhibiting these patterns were not the same. Divergence in module membership was associated with changes in lifestyle and specific clades and that gene duplication was a major factor contributing to the divergence of module membership.
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References
Jensen LJ, Jensen TS, de Lichtenberg U, Brunak S, Bork P (2006) Co-evolution of transcriptional and post-translational cell-cycle regulation. Nature 443:594–597
Gasch AP (2007) Comparative genomics of the environmental stress response in ascomycete fungi. Yeast (Chichester, England) 24:961–976
Wohlbach DJ, Thompson DAA, Gasch AP, Regev A (2009) From elements to modules: regulatory evolution in Ascomycota fungi. Curr Opin Genet Dev 19:571–578
Romero IG, Ruvinsky I, Gilad Y (2012) Comparative studies of gene expression and the evolution of gene regulation. Nat Rev Genet 13:505–516
Thompson DAA, Regev A (2009) Fungal regulatory evolution: cis and trans in the balance. FEBS Lett 583:3959–3965
Brawand D et al (2011) The evolution of gene expression levels in mammalian organs. Nature 478:343–348
Schmidt D et al (2010) Five-vertebrate ChIP-seq reveals the evolutionary dynamics of transcription factor binding. Science 328:1036–1040
Xiao S et al (2012) Comparative epigenomic annotation of regulatory DNA. Mol Cell 149:1381–1392
Barbosa-Morais NL et al (2012) The evolutionary landscape of alternative splicing in vertebrate species. Science 338:1587–1593
Merkin J, Russell C, Chen P, Burge CB (2012) Evolutionary dynamics of gene and isoform regulation in mammalian tissues. Science 338:1593–1599
Tanay A, Regev A, Shamir R (2005) Conservation and evolvability in regulatory networks: the evolution of ribosomal regulation in yeast. Proc Natl Acad Sci U S A 102:7203–7208
Waltman P et al (2010) Multi-species integrative biclustering. Genome Biol 11:R96+
Kuo D et al (2010) Evolutionary divergence in the fungal response to fluconazole revealed by soft clustering. Genome Biol 11:R77
Hittinger CT, Carroll SB (2007) Gene duplication and the adaptive evolution of a classic genetic switch. Nature 449:677–681
Thompson DA et al (2013) Evolutionary principles of modular gene regulation in yeasts. eLife 2, e00603. doi:10.7554/eLife.00603
Roy S et al (2013) Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules. Genome Res 23(6):1039–1050. doi:10.1101/gr.146233.112
O’Brien KP, Remm M, Sonnhammer ELL (2005) Inparanoid: a comprehensive database of eukaryotic orthologs. Nucleic Acids Res 33:D476–D480
Hastie T, Tibshirani R, Friedman JH (2003) The elements of statistical learning. Springer, New York
Ashburner M et al (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet 25:25–29
Habib N, Wapinski I, Margalit H, Regev A, Friedman N (2012) A functional selection model explains evolutionary robustness despite plasticity in regulatory networks. Mol Syst Biol 8:619
Wapinski I, Pfeffer A, Friedman N, Regev A (2007) Automatic genome-wide reconstruction of phylogenetic gene trees. Bioinformatics 23:i549–i558
Edgar RC (2004) MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5:113
Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24:1586–1591
Acknowledgements
S.R. is supported in part by a NSF ABI CAREER award (DBI-1350677). S.K. is supported by an NLM training grant to the Computation and Informatics in Biology and Medicine Training Program (NLM5T15LM007359). This work was also supported by NIH grant 2R01CA119176-01 and a SPARC grant from the Broad Institute.
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Knaack, S.A., Thompson, D.A., Roy, S. (2016). Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum. In: Devaux, F. (eds) Yeast Functional Genomics. Methods in Molecular Biology, vol 1361. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3079-1_21
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DOI: https://doi.org/10.1007/978-1-4939-3079-1_21
Publisher Name: Humana Press, New York, NY
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