Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-8118
Main Title: Updating genome annotation for the microbial cell factory Aspergillus niger using gene co-expression networks
Author(s): Schäpe, Paul
Kwon, Min Jin
Baumann, Birgit
Gutschmann, Björn
Jung, Sascha
Lenz, Swantje
Nitsche, Benjamin
Paege, Norman
Schütze, Tabea
Cairns, Timothy C.
Meyer, Vera
Type: Article
Language Code: en
Abstract: A significant challenge in our understanding of biological systems is the high number of genes with unknown function in many genomes. The fungal genus Aspergillus contains important pathogens of humans, model organisms, and microbial cell factories. Aspergillus niger is used to produce organic acids, proteins, and is a promising source of new bioactive secondary metabolites. Out of the 14,165 open reading frames predicted in the A. niger genome only 2% have been experimentally verified and over 6,000 are hypothetical. Here, we show that gene co-expression network analysis can be used to overcome this limitation. A meta-analysis of 155 transcriptomics experiments generated co-expression networks for 9,579 genes (∼65%) of the A. niger genome. By populating this dataset with over 1,200 gene functional experiments from the genus Aspergillus and performing gene ontology enrichment, we could infer biological processes for 9,263 of A. niger genes, including 2,970 hypothetical genes. Experimental validation of selected co-expression sub-networks uncovered four transcription factors involved in secondary metabolite synthesis, which were used to activate production of multiple natural products. This study constitutes a significant step towards systems-level understanding of A. niger, and the datasets can be used to fuel discoveries of model systems, fungal pathogens, and biotechnology.
URI: https://depositonce.tu-berlin.de//handle/11303/9001
http://dx.doi.org/10.14279/depositonce-8118
Issue Date: 2018
Date Available: 18-Jan-2019
DDC Class: 570 Biowissenschaften; Biologie
Subject(s): computational methods
genomics
transcriptome mapping
monitoring
gene expression
Sponsor/Funder: DFG, TH 662/19-1, Open Access Publizieren 2017 - 2018 / Technische Universität Berlin
EC/FP7/607332/EU/Quantitative Biology for Fungal Secondary Metabolite Producers/QuantFung
License: https://creativecommons.org/licenses/by/4.0/
Journal Title: Nucleic Acids Research
Publisher: Oxford University Press
Publisher Place: Oxford
Volume: 47
Issue: 2
Publisher DOI: 10.1093/nar/gky1183
Page Start: 559
Page End: 569
EISSN: 1362-4962
ISSN: 0305-1048
Appears in Collections:FG Angewandte und Molekulare Mikrobiologie » Publications

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