Plant Genome DataBase Japan (PGDBj)

Nakaya, Akihiro; Ichihara, Hisako; Asamizu, Erika; Shirasawa, Sachiko; Nakamura, Yasukazu; Tabata, Satoshi; Hirakawa, Hideki

doi:10.1007/978-1-4939-6658-5_3

Cited by 12 publications

(6 citation statements)

References 36 publications

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“…Some databases also provide gene homology information and computational tools for comparative genomic analysis (Martinez, 2016). However, analysis tools implemented in such databases are typically limited, static, and can only be used to analyze existing data (Tomcal et al, 2013; Sundell et al, 2015; Spannagl et al, 2016; Nakaya et al, 2017; Tello-Ruiz et al, 2020). Some more recent databases contain flexible tools ( i .…”

Section: Introductionmentioning

confidence: 99%

PlantTribes2: tools for comparative gene family analysis in plant genomics

Wafula

Zhang

Kuster

et al. 2022

Preprint

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Plant genome-scale resources are being generated at an increasing rate as sequencing technologies continue to improve and raw data costs continue to fall; however, the cost of downstream analyses remains large. This has resulted in a considerable range of genome assembly and annotation qualities across plant genomes due to their varying sizes, complexity, and the technology used for the assembly and annotation. To effectively work across genomes, researchers increasingly rely on comparative genomic approaches that integrate across plant community resources and data types. Such efforts have aided the genome annotation process and yielded novel insights into the evolutionary history of genomes and gene families, including complex non-model organisms. The essential tools to achieve these insights rely on gene family analysis at a genome-scale, but they are not well integrated for rapid analysis of new data, and the learning curve can be steep. Here we present PlantTribes2, a scalable, easily accessible, highly customizable, and broadly applicable gene family analysis framework with multiple entry points including user provided data. It uses objective classifications of annotated protein sequences from existing, high-quality plant genomes for comparative and evolutionary studies. PlantTribes2 can improve transcript models and then sort them, either genome-scale annotations or individual gene coding sequences, into pre-computed orthologous gene family clusters with rich functional annotation information. Then, for gene families of interest, PlantTribes2 performs downstream analyses and customizable visualizations including, (1) multiple sequence alignment, (2) gene family phylogeny, (3) estimation of synonymous and non-synonymous substitution rates among homologous sequences, and (4) inference of large-scale duplication events. We give examples of PlantTribes2 applications in functional genomic studies of economically important plant families, namely transcriptomics in the weedy Orobanchaceae and a core orthogroup analysis (CROG) in Rosaceae. PlantTribes2 is freely available for use within the main public Galaxy instance and can be downloaded from GitHub or Bioconda. Importantly, PlantTribes2 can be readily adapted for use with genomic and transcriptomic data from any kind of organism.

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Section: Introductionmentioning

confidence: 99%

PlantTribes2: tools for comparative gene family analysis in plant genomics

Wafula

Zhang

Kuster

et al. 2022

Preprint

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“…Further, the Sol Genomics Network (SGN) [12] provides genomic, genetic and phenotypic information for members of the Solanaceae family. Plant Genome DataBase Japan (PGDBj) [26] is an integrated web resource for plant genome-related information from literature and public databases. However, the TAIR, SGN, and PGDBj do not distribute their data in a semantically interoperable (RDF) format.…”

Section: Introductionmentioning

confidence: 99%

Linked Data Platform for Solanaceae Species

Singh

Kuzniar

Brouwer³

et al. 2020

Applied Sciences

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Genetics research is increasingly focusing on mining fully sequenced genomes and their annotations to identify the causal genes associated with traits (phenotypes) of interest. However, a complex trait is typically associated with multiple quantitative trait loci (QTLs), each comprising many genes, that can positively or negatively affect the trait of interest. To help breeders in ranking candidate genes, we developed an analytical platform called pbg-ld that provides semantically integrated geno- and phenotypic data on Solanaceae species. This platform combines both unstructured data from scientific literature and structured data from publicly available biological databases using the Linked Data approach. In particular, QTLs were extracted from tables of full-text articles from the Europe PubMed Central (PMC) repository using QTLTableMiner++ (QTM), while the genomic annotations were obtained from the Sol Genomics Network (SGN), UniProt and Ensembl Plants databases. These datasets were transformed into Linked Data graphs, which include cross-references to many other relevant databases such as Gramene, Plant Reactome, InterPro and KEGG Orthology (KO). Users can query and analyze the integrated data through a web interface or programmatically via the SPARQL and RESTful services (APIs). We illustrate the usability of pbg-ld by querying genome annotations, by comparing genome graphs, and by two biological use cases in Jupyter Notebooks. In the first use case, we performed a comparative genomics study using pbg-ld to compare the difference in the genetic mechanism underlying tomato fruit shape and potato tuber shape. In the second use case, we developed a seamlessly integrated workflow that uses genomic data from pbg-ld knowledge graphs and prioritization pipelines to predict candidate genes within QTL regions for metabolic traits of tomato.

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“…We performed synteny analysis using Plant Genome Database Japan (Asamizu et al 2014, Nakaya et al 2017. We constructed two synteny maps of 12 chromosomes of Oryza sativa L. ssp.…”

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confidence: 99%

Computational Synteny Analysis Promotes a Better Understanding of Chromosome Evolution

Matsunaga

Nakaya

2017

CYTOLOGIA

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Synteny is modernly used to describe the conservation of homologous genomic regions between chromosomes among different species, although the term was first introduced to mean the gene location on the same chromosomes. Using database of whole genome sequences and web-tools for computational comparative analyses, we can find synteny blocks at high resolution and analyze chromosomal rearrangement among different species. Our constructed synteny maps between Oryza sativa and Arabidopsis thaliana or Zea mays reflected the evolutionary lineages of the plants. These computational synteny analyses contribute to the understanding of chromosome evolution and the discovery of the quantitative trait locus between related species. Future synteny analysis will include information of epigenome and three-dimensional chromatin organization.

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Plant Genome DataBase Japan (PGDBj)

Cited by 12 publications

References 36 publications

PlantTribes2: tools for comparative gene family analysis in plant genomics

PlantTribes2: tools for comparative gene family analysis in plant genomics

Linked Data Platform for Solanaceae Species

Computational Synteny Analysis Promotes a Better Understanding of Chromosome Evolution

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