Fungi.guru: comparative genomic and transcriptomic database 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; Zhao, Margaret Xuan; Chan, Tong Ling; Rodrigues, Edbert Edric; Kairon, Ryan; Chee, Natasha Cassandra; Low, Ann Don; Xin, Zoe Chen Hui; Lim, Shan Chun; Lunardi, Vanessa; Choy, Fong Tuck; Chua, Cherlyn Xin'Er; Sween, Kenny Koh Ting; Ng, Jonathan Wei Xiong; Mutwil, Marek

doi:10.1101/2020.06.26.174581

Cited by 3 publications

(2 citation statements)

References 60 publications

(64 reference statements)

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“…The exploitation of these transcriptomic analyses to elucidate the human genome has proved instrumental in understanding and treating endogenous disease (Lowe et al, 2017;Wirka et al, 2018), but has not been utilized to the same effect in exogenous diseases caused by bacteria and other pathogens. As case in point, only one bacterial coexpression web-base, COLOMBOS (Moretto et al, 2016; http://www.colombos.net/), is available for use at present, whereas numerous such resources have been developed for alike quantities of eukaryotic organisms (Hruz et al, 2008;Lim et al, 2020;Mutwil et al, 2011;Obayashi et al, 2018Obayashi et al, , 2019Rao and Dixon, 2019;Tseng et al, 2020;van Dam et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

Lim

Davey

Wee

et al. 2022

Journal of Molecular Biology

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Section: Introductionmentioning

confidence: 99%

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

Lim

Davey

Wee

et al. 2022

Journal of Molecular Biology

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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

Preprint

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SummaryThere 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. 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 and implementationLSTrAP-Kingdom is available from: https://github.com/wirriamm/plants-pipeline and is fully implemented in Python and Bash.

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Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP

et al. 2021

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Background Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called “field pathogenomics”. As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. Results Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser (http://www.rust-expression.com). This enables for the first time simultaneous ‘point-and-click’ access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. Conclusions The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.

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Fungi.guru: comparative genomic and transcriptomic database for the Fungi kingdom

Cited by 3 publications

References 60 publications

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens

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

Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP

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