Literature DB >> 24786077

Genomic signatures of specialized metabolism in plants.

Lee Chae1, Taehyong Kim, Ricardo Nilo-Poyanco, Seung Y Rhee.   

Abstract

All plants synthesize basic metabolites needed for survival (primary metabolism), but different taxa produce distinct metabolites that are specialized for specific environmental interactions (specialized metabolism). Because evolutionary pressures on primary and specialized metabolism differ, we investigated differences in the emergence and maintenance of these processes across 16 species encompassing major plant lineages from algae to angiosperms. We found that, relative to their primary metabolic counterparts, genes coding for specialized metabolic functions have proliferated to a much greater degree and by different mechanisms and display lineage-specific patterns of physical clustering within the genome and coexpression. These properties illustrate the differential evolution of specialized metabolism in plants, and collectively they provide unique signatures for the potential discovery of novel specialized metabolic processes.

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Mesh:

Year:  2014        PMID: 24786077     DOI: 10.1126/science.1252076

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  89 in total

Review 1.  Something Old, Something New: Conserved Enzymes and the Evolution of Novelty in Plant Specialized Metabolism.

Authors:  Gaurav D Moghe; Robert L Last
Journal:  Plant Physiol       Date:  2015-08-14       Impact factor: 8.340

2.  A Revolution in Plant Metabolism: Genome-Enabled Pathway Discovery.

Authors:  Jeongwoon Kim; C Robin Buell
Journal:  Plant Physiol       Date:  2015-07-29       Impact factor: 8.340

3.  Expression Atlas of Selaginella moellendorffii Provides Insights into the Evolution of Vasculature, Secondary Metabolism, and Roots.

Authors:  Camilla Ferrari; Devendra Shivhare; Bjoern Oest Hansen; Asher Pasha; Eddi Esteban; Nicholas J Provart; Friedrich Kragler; Alisdair Fernie; Takayuki Tohge; Marek Mutwil
Journal:  Plant Cell       Date:  2020-01-27       Impact factor: 11.277

4.  Characterization of Trichome-Expressed BAHD Acyltransferases in Petunia axillaris Reveals Distinct Acylsugar Assembly Mechanisms within the Solanaceae.

Authors:  Satya Swathi Nadakuduti; Joseph B Uebler; Xiaoxiao Liu; A Daniel Jones; Cornelius S Barry
Journal:  Plant Physiol       Date:  2017-07-12       Impact factor: 8.340

5.  A chromosome-scale genome assembly of Isatis indigotica, an important medicinal plant used in traditional Chinese medicine : An Isatis genome.

Authors:  Minghui Kang; Haolin Wu; Qiao Yang; Li Huang; Quanjun Hu; Tao Ma; Zaiyun Li; Jianquan Liu
Journal:  Hortic Res       Date:  2020-02-01       Impact factor: 6.793

6.  ePlant: Visualizing and Exploring Multiple Levels of Data for Hypothesis Generation in Plant Biology.

Authors:  Jamie Waese; Jim Fan; Asher Pasha; Hans Yu; Geoffrey Fucile; Ruian Shi; Matthew Cumming; Lawrence A Kelley; Michael J Sternberg; Vivek Krishnakumar; Erik Ferlanti; Jason Miller; Chris Town; Wolfgang Stuerzlinger; Nicholas J Provart
Journal:  Plant Cell       Date:  2017-08-14       Impact factor: 11.277

7.  A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants.

Authors:  Jennifer H Wisecaver; Alexander T Borowsky; Vered Tzin; Georg Jander; Daniel J Kliebenstein; Antonis Rokas
Journal:  Plant Cell       Date:  2017-04-13       Impact factor: 11.277

Review 8.  Bioinformatics tools for the identification of gene clusters that biosynthesize specialized metabolites.

Authors:  Arvind K Chavali; Seung Y Rhee
Journal:  Brief Bioinform       Date:  2018-09-28       Impact factor: 11.622

9.  Genome-Wide Prediction of Metabolic Enzymes, Pathways, and Gene Clusters in Plants.

Authors:  Pascal Schläpfer; Peifen Zhang; Chuan Wang; Taehyong Kim; Michael Banf; Lee Chae; Kate Dreher; Arvind K Chavali; Ricardo Nilo-Poyanco; Thomas Bernard; Daniel Kahn; Seung Y Rhee
Journal:  Plant Physiol       Date:  2017-02-22       Impact factor: 8.340

10.  METACLUSTER-an R package for context-specific expression analysis of metabolic gene clusters.

Authors:  Michael Banf; Kangmei Zhao; Seung Y Rhee
Journal:  Bioinformatics       Date:  2019-09-01       Impact factor: 6.937

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