Literature DB >> 28228535

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

Pascal Schläpfer1,2, Peifen Zhang1,2, Chuan Wang1,2, Taehyong Kim1,2, Michael Banf1,2, Lee Chae1,2, Kate Dreher1,2, Arvind K Chavali1,2, Ricardo Nilo-Poyanco1,2, Thomas Bernard1,2, Daniel Kahn1,2, Seung Y Rhee3,4.   

Abstract

Plant metabolism underpins many traits of ecological and agronomic importance. Plants produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have not yet been elucidated. To engineer and improve metabolic traits, we need comprehensive and accurate knowledge of the organization and regulation of plant metabolism at the genome scale. Here, we present a computational pipeline to identify metabolic enzymes, pathways, and gene clusters from a sequenced genome. Using this pipeline, we generated metabolic pathway databases for 22 species and identified metabolic gene clusters from 18 species. This unified resource can be used to conduct a wide array of comparative studies of plant metabolism. Using the resource, we discovered a widespread occurrence of metabolic gene clusters in plants: 11,969 clusters from 18 species. The prevalence of metabolic gene clusters offers an intriguing possibility of an untapped source for uncovering new metabolite biosynthesis pathways. For example, more than 1,700 clusters contain enzymes that could generate a specialized metabolite scaffold (signature enzymes) and enzymes that modify the scaffold (tailoring enzymes). In four species with sufficient gene expression data, we identified 43 highly coexpressed clusters that contain signature and tailoring enzymes, of which eight were characterized previously to be functional pathways. Finally, we identified patterns of genome organization that implicate local gene duplication and, to a lesser extent, single gene transposition as having played roles in the evolution of plant metabolic gene clusters.
© 2017 American Society of Plant Biologists. All Rights Reserved.

Mesh:

Substances:

Year:  2017        PMID: 28228535      PMCID: PMC5373064          DOI: 10.1104/pp.16.01942

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  81 in total

1.  KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research.

Authors:  Farit Mochamad Afendi; Taketo Okada; Mami Yamazaki; Aki Hirai-Morita; Yukiko Nakamura; Kensuke Nakamura; Shun Ikeda; Hiroki Takahashi; Md Altaf-Ul-Amin; Latifah K Darusman; Kazuki Saito; Shigehiko Kanaya
Journal:  Plant Cell Physiol       Date:  2011-11-28       Impact factor: 4.927

Review 2.  Secondary metabolic gene clusters: evolutionary toolkits for chemical innovation.

Authors:  Anne Osbourn
Journal:  Trends Genet       Date:  2010-08-24       Impact factor: 11.639

Review 3.  The rise of chemodiversity in plants.

Authors:  Jing-Ke Weng; Ryan N Philippe; Joseph P Noel
Journal:  Science       Date:  2012-06-29       Impact factor: 47.728

4.  High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource.

Authors:  Samuel M D Seaver; Svetlana Gerdes; Océane Frelin; Claudia Lerma-Ortiz; Louis M T Bradbury; Rémi Zallot; Ghulam Hasnain; Thomas D Niehaus; Basma El Yacoubi; Shiran Pasternak; Robert Olson; Gordon Pusch; Ross Overbeek; Rick Stevens; Valérie de Crécy-Lagard; Doreen Ware; Andrew D Hanson; Christopher S Henry
Journal:  Proc Natl Acad Sci U S A       Date:  2014-06-09       Impact factor: 11.205

5.  Investigation of terpene diversification across multiple sequenced plant genomes.

Authors:  Alexander M Boutanaev; Tessa Moses; Jiachen Zi; David R Nelson; Sam T Mugford; Reuben J Peters; Anne Osbourn
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-10       Impact factor: 11.205

6.  A gene cluster for secondary metabolism in oat: implications for the evolution of metabolic diversity in plants.

Authors:  X Qi; S Bakht; M Leggett; C Maxwell; R Melton; A Osbourn
Journal:  Proc Natl Acad Sci U S A       Date:  2004-05-17       Impact factor: 11.205

7.  UniProt Knowledgebase: a hub of integrated protein data.

Authors:  Michele Magrane
Journal:  Database (Oxford)       Date:  2011-03-29       Impact factor: 3.451

8.  The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases.

Authors:  Ron Caspi; Tomer Altman; Kate Dreher; Carol A Fulcher; Pallavi Subhraveti; Ingrid M Keseler; Anamika Kothari; Markus Krummenacker; Mario Latendresse; Lukas A Mueller; Quang Ong; Suzanne Paley; Anuradha Pujar; Alexander G Shearer; Michael Travers; Deepika Weerasinghe; Peifen Zhang; Peter D Karp
Journal:  Nucleic Acids Res       Date:  2011-11-18       Impact factor: 16.971

9.  The evolution of fungal metabolic pathways.

Authors:  Jennifer H Wisecaver; Jason C Slot; Antonis Rokas
Journal:  PLoS Genet       Date:  2014-12-04       Impact factor: 5.917

10.  Ensembl Genomes 2016: more genomes, more complexity.

Authors:  Paul Julian Kersey; James E Allen; Irina Armean; Sanjay Boddu; Bruce J Bolt; Denise Carvalho-Silva; Mikkel Christensen; Paul Davis; Lee J Falin; Christoph Grabmueller; Jay Humphrey; Arnaud Kerhornou; Julia Khobova; Naveen K Aranganathan; Nicholas Langridge; Ernesto Lowy; Mark D McDowall; Uma Maheswari; Michael Nuhn; Chuang Kee Ong; Bert Overduin; Michael Paulini; Helder Pedro; Emily Perry; Giulietta Spudich; Electra Tapanari; Brandon Walts; Gareth Williams; Marcela Tello-Ruiz; Joshua Stein; Sharon Wei; Doreen Ware; Daniel M Bolser; Kevin L Howe; Eugene Kulesha; Daniel Lawson; Gareth Maslen; Daniel M Staines
Journal:  Nucleic Acids Res       Date:  2015-11-17       Impact factor: 16.971

View more
  92 in total

1.  Infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) mass spectrometry imaging analysis of endogenous metabolites in cherry tomatoes.

Authors:  M Caleb Bagley; Crystal L Pace; Måns Ekelöf; David C Muddiman
Journal:  Analyst       Date:  2020-08-10       Impact factor: 4.616

2.  Chasing Scattered Genes: Identifying Specialized Metabolite Pathway Genes through Global Coexpression Analysis.

Authors:  Jennifer Lockhart
Journal:  Plant Cell       Date:  2017-04-13       Impact factor: 11.277

3.  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 4.  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

5.  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

Review 6.  Computational Approaches to Design and Test Plant Synthetic Metabolic Pathways.

Authors:  Anika Küken; Zoran Nikoloski
Journal:  Plant Physiol       Date:  2019-01-15       Impact factor: 8.340

7.  Gene Balance Predicts Transcriptional Responses Immediately Following Ploidy Change in Arabidopsis thaliana.

Authors:  Michael J Song; Barney I Potter; Jeff J Doyle; Jeremy E Coate
Journal:  Plant Cell       Date:  2020-03-17       Impact factor: 11.277

Review 8.  Harnessing evolutionary diversification of primary metabolism for plant synthetic biology.

Authors:  Hiroshi A Maeda
Journal:  J Biol Chem       Date:  2019-09-26       Impact factor: 5.157

Review 9.  Multi-tissue to whole plant metabolic modelling.

Authors:  Rahul Shaw; C Y Maurice Cheung
Journal:  Cell Mol Life Sci       Date:  2019-11-20       Impact factor: 9.261

10.  The thick aleurone1 Gene Encodes a NOT1 Subunit of the CCR4-NOT Complex and Regulates Cell Patterning in Endosperm.

Authors:  Hao Wu; Bryan C Gontarek; Gibum Yi; Brandon D Beall; Anjanasree K Neelakandan; Bibechana Adhikari; Rumei Chen; Donald R McCarty; Andrew J Severin; Philip W Becraft
Journal:  Plant Physiol       Date:  2020-07-31       Impact factor: 8.340

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.