Fungi.guru: Comparative genomic and transcriptomic resource for the fungi kingdom

Lim, Jolyn Jia Jia; Koh, Jace; Moo, Jia Rong; Villanueva, Erielle Marie Fajardo; Putri, Dhira Anindya; Lim, Yuen Shan; Seetoh, Wei Song; Mulupuri, Sriya; Ng, Janice Wan Zhen; Nguyen, Nhi; Reji, Rinta; Foo, Herman; Zhao, Margaret Xuan; Chan, Tong Ling; Rodrigues, Edbert Edric; Kairon, Ryanjit Singh; Hee, Ker Min; Chee, Natasha Cassandra; Low, Ann Don; Chen, Zoe Hui Xin; Lim, Shan Chun; Lunardi, Vanessa; Fong, Tuck Choy; Chua, Cherlyn Xin'Er; Koh, Kenny Ting Sween; Julca, Irene; Ponti, Riccardo Delli; Ng, Jonathan Wei Xiong; Mutwil, Marek

doi:10.1016/j.csbj.2020.11.019

Cited by 9 publications

(4 citation statements)

References 71 publications

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“…An initial assessment of gene expression pro les for G5K and Ack marked the primary analysis to ascertain target effectiveness. Leveraging publicly available RNA sequencing data from the Sequence Read Archive (SRA), we subjected 191 quality-controlled samples to analysis using the Fungi.guru tool (Lim et al, 2020). The gene expression pro les of both G5K and Ack exhibited peak levels at 3-and 9-hours post-inoculation (hpi) time points (Fig.…”

Section: Target Prioritizationmentioning

confidence: 99%

“…To predict the e cacy of the selected targets, a comprehensive analysis was conducted encompassing gene expression pro les, protein-protein interactions (PPI), and network enrichment, including molecular function, KEGG pathways, and biological processes. Gene expression pro les of the target proteins were meticulously examined utilizing the fungi.guru tool (https://fungi.sbs.ntu.edu.sg) (Lim et al, 2020). The interaction landscape of the target proteins was explored through the STRING database (https://string-db.org), facilitating the analysis of protein-protein interactions, molecular functions, and KEGG pathways.…”

Section: Target E Cacy Predictionmentioning

confidence: 99%

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Comparative Omics Analysis for Novel Target Discovery in Plant Pathogens: A Case Study for Magnaporthe oryzae

Luthfi,

Piapukiew,

Pandey

et al. 2023

Preprint

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The central concern surrounding chemical pesticide application is its potential adverse effects on non-target organisms. For fungal pathogens, the search for specific targets has been complicated by the similarities in pathways shared between these pathogens and humans. We present a comprehensive strategy, integrating comparative omics and bioinformatics, to pinpoint precise targets for fungicides effective against the fungal pathogen Magnaporthe oryzae(M. oryzae), responsible for rice blast disease. Our approach involves subtractive metabolic pathways, homology screening and target prioritization. Through subtractive metabolic analysis, we identified three unique M. oryzaepathways, distinct from human and rice. Non-redundant protein sequences were subsequently subjected to BLASTP screening against human and rice, as well as other databases from diverse organisms. Target subcellular localization was predicted using eight tools, including Artificial Intelligence and a deep learning method. A comprehensive examination of biological processes was conducted, including gene expression, protein-protein interactions, network enrichment, broad-spectrum activity, and physicochemical analysis. Glutamate 5-kinase (G5K) emerged as the prime candidate for targeted fungicide development, promising progress in precision-oriented solutions.

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Section: Target Prioritizationmentioning

confidence: 99%

Section: Target E Cacy Predictionmentioning

confidence: 99%

Comparative Omics Analysis for Novel Target Discovery in Plant Pathogens: A Case Study for Magnaporthe oryzae

Luthfi,

Piapukiew,

Pandey

et al. 2023

Preprint

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show abstract

“…In the view of this, we are set to construct a co-expression analysis tool that can effectively mine predictive information on gene function and regulation from transcriptomic data. To this end, we utilize CoNekT (Co-expression Network Toolkit) (Proost and Mutwil, 2018), a popular framework that has been used to construct comparative transcriptomic databases for plants and species from other kingdoms (Ng et al, 2020; Tan and Mutwil, 2020; Lim et al, 2020; Lim et al, 2022; Villanueva et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Comparative transcriptome database forCamellia sinensisreveals genes important for flavonoid synthesis in tea plants

Zheng,

Mohd Ali,

Lim

et al. 2024

Preprint

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Tea, as one of the most popular beverages in the world, possesses a plethora of secondary metabolites that are beneficial to human health. Tea plants (Camellia sinensis) exhibit rich genetic diversity, where different cultivars can vary significantly in terms of yield, adaptability, morphology, and composition of secondary metabolites. Many tea cultivars have been the subject of much research interest, which have led to the accumulation of publicly available RNA-seq data. As such, it has become possible to systematically summarize the characteristics of different cultivars at the transcriptomic level, identify valuable functional genes, and infer gene functions through co-expression analysis. Here, the transcriptomes of 9 cultivars of Camellia sinensis were assembled and combined with the coding sequences of 13 cultivars of Camellia sinensis to study the differences and similarities of gene expression and biological functions among cultivars. To give access to this data, we present TeaNekT (https://teanekt.sbs.ntu.edu.sg/), a web resource that provides user-friendly tools and interactive visualizations that facilitates the prediction of gene functions of various tea cultivars. We used TeaNekT to perform cross-cultivar comparison of co-expressed gene neighborhoods, clusters, and tissue-specific gene expression. We show that the members of the chalcone synthase (CHS) gene family, important for flavonoid synthesis, exhibit the highest expression variability, specific expression in leaves and buds, and significant modulation by methyl jasmonate (MeJA) treatment. By using comparative co-expression tools of TeaNekT, we identified multiple conserved genes involved in flavonoid biosynthesis among cultivars that have not been previously studied, warranting further research.

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“…Furthermore, when combined with genomic information, comparative transcriptomic analyses across species allow the study of the function and evolution of genes from the perspective of gene expression (Ferrari et al, 2019;Wen Tan and Mutwil, 2019;Ferrari et al, 2020;Ng et al, 2019;Ferrari and Mutwil, 2019;Lim et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

LSTrAP-Kingdom: an automated pipeline to generate annotated gene expression atlases for kingdoms of life

Goh

Mutwil

2021

Bioinformatics

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Motivation There are now more than two million RNA sequencing experiments for plants, animals, bacteria and fungi publicly available, allowing us to study gene expression within and across species and kingdoms. However, the tools allowing the download, quality control and annotation of this data for more than one species at a time are currently missing. Results To remedy this, we present the Large-Scale Transcriptomic Analysis Pipeline in Kingdom of Life (LSTrAP-Kingdom) pipeline, which we used to process 134,521 RNA-seq samples, achieving ∼12,000 processed samples per day. Our pipeline generated quality-controlled, annotated gene expression matrices that rival the manually curated gene expression data in identifying functionally-related genes. Availability LSTrAP-Kingdom is available from: https://github.com/wirriamm/plants-pipeline and is fully implemented in Python and Bash. Supplementary information Supplementary data are available at Bioinformatics online.

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Fungi.guru: Comparative genomic and transcriptomic resource for the fungi kingdom

Abstract: Graphical abstract

Cited by 9 publications

References 71 publications

Comparative Omics Analysis for Novel Target Discovery in Plant Pathogens: A Case Study for Magnaporthe oryzae

Comparative Omics Analysis for Novel Target Discovery in Plant Pathogens: A Case Study for Magnaporthe oryzae

Comparative transcriptome database forCamellia sinensisreveals genes important for flavonoid synthesis in tea plants

LSTrAP-Kingdom: an automated pipeline to generate annotated gene expression atlases for kingdoms of life

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