TreeGenes: A Forest Tree Genome Database

Wegrzyn, Jill L.; Lee, Jennifer M.; Tearse, Brandon R.; Neale, David B.

doi:10.1155/2008/412875

Cited by 96 publications

(76 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These factors may have had an impact in this study since the rate of predicted genes from the set of assembled contigs was low (83,468 genes were predicted from 355,287 assembled contigs). Even though genomic information for several conifer species has been generated, and compiled in the TreeGenes database [60], the number of genomic resources for maritime pine remains limited, which is another relevant factor that may have contributed to the low rate of predicted genes. When a reference genome is not available, the genetic description contained in the assembled transcripts can only be successfully identified by homology if the protein products have homologies in different protein databases, giving a set of predicted genes.…”

Section: Discussionmentioning

confidence: 99%

Expression Profiling in Pinus pinaster in Response to Infection with the Pine Wood Nematode Bursaphelenchus xylophilus

Gaspar

Trindade

Usié

et al. 2017

Forests

View full text Add to dashboard Cite

Abstract:Forests are essential resources on a global scale, not only for the ecological benefits, but also for economical and landscape purposes. However, in recent years, a large number of forest species have suffered a serious decline, with maritime pine being one of the most affected. In Portugal, the maritime pine forest has been devastated by the pine wood nematode (PWN), the causal agent of pine wilt disease. In this study, RNA-Seq data was used to characterize the maritime pine response to infection with PWN, by determining the differentially expressed genes and identifying the regulatory networks and pathways associated. The analyses showed clear differences between an early response that occurs immediately after inoculation and a late response that is observed seven days after inoculation. Moreover, differentially expressed genes related to secondary metabolism, oxidative stress and defense against pathogen infection were identified over different time points. These results provide new insights about the molecular mechanisms and metabolic pathways involved in the response of Pinus pinaster against PWN infection, which will be a useful resource in follow-up studies and for future breeding programs to select plants with lower susceptibility to this disease.

show abstract

Section: Discussionmentioning

confidence: 99%

Expression Profiling in Pinus pinaster in Response to Infection with the Pine Wood Nematode Bursaphelenchus xylophilus

Gaspar

Trindade

Usié

et al. 2017

Forests

View full text Add to dashboard Cite

show abstract

“…For insight into host responses, the TreeGenes database (Wegrzyn et al, 2008), Phytozome database (http://phytozome.jgi.doe.gov) (Goodstein et al, 2012), The Plant Genome Integrative Explorer (PlantGenIE; www.plantgenie.org) (Sundell et al, 2015), and Gramene (www.gramene.org) (Liang et al, 2008) provide tools for analyses and visualization. Gramene contains the Plant Reactome database, which can be used to identify plant metabolic and regulatory pathways (Tello-Ruiz et al, 2016).…”

Section: Downstream Analysismentioning

confidence: 99%

Dual RNA-Sequencing to Elucidate the Plant-Pathogen Duel

Naidoo¹,

Visser²,

Zwart³

et al. 2018

Current Issues in Molecular Biology

View full text Add to dashboard Cite

RNA-sequencing technology has been widely adopted to investigate host responses during infection with pathogens. Dual RNA-sequencing (RNA-seq) allows the simultaneous capture of pathogen-specific transcripts during infection, providing a more complete view of the interaction. In this review, we focus on the design of dual RNAseq experiments and the application of downstream data analysis to gain biological insight into both sides of the interaction. Recent literature in this area demonstrates the power of the dual RNA-seq approach and shows that it is not limited to model systems where genomic resources are available. Sequencing costs continue to decrease and single cell transcriptomics is becoming more feasible. In combination with proteomics and metabolomics studies, these technological advances are likely to contribute to our understanding of the temporal and spatial aspects of dynamic plant-pathogen interactions. A dual approach in plantaThe interaction between plants and pathogens is an active and dynamic process that can be likened to a duel. Plants have complex defence mechanisms that can be rendered ineffective when pathogens interfere with one of the various processes required for host defence. These processes include penetration resistance, recognition by Pattern Recognition Receptors (PRRs), phytohormone signalling pathways, secretory pathways, secondary metabolite production, and plant cell death (Dou and Zhou, 2012). Until recently, transcriptomic approaches have been applied in the host and pathogen separately to obtain the gene expression profile of each organism and gain insight into infection biology or host defence mechanisms.RNA sequencing (RNA-seq) is a powerful technology that does not rely on any prior knowledge of transcripts and can generate vast quantities of data with much smaller costs involved than for older techniques such as microarrays (Pareek et al., 2011;Wilhelm and Landry, 2009). An advantage of RNA-seq in the field of plant-pathogen interactions is that both plant and pathogen transcripts can be detected simultaneously and accurately in the same sample. This tactic, known as dual RNAseq, in planta RNA-seq, simultaneous RNA-seq, or comparative RNA-seq, is a relatively new technique both in the plant and medical fields. In plants, it allows for the study of plant-pathogen interactions in herbaceous crops Kunjeti et al., 2012;Lowe et al., 2014) as well as trees (Hayden et al., 2014;Liang et al., 2014;Teixeira et al., 2014). This review outlines technical considerations for dual RNA-seq experiments, summarizes recent insights drawn from such approaches in plant-pathogen interactions, and provides an

show abstract

“…The TreeGenes database (http://treegenesdb.org, Wegrzyn et al (2008Wegrzyn et al ( , 2012) currently hosts 13 genome assemblies, transcriptome resources for 262 species, 95 genetic maps, over 110 million genotypes, and nearly 200,000 phenotypic evaluations. While TreeGenes hosts data for over 1,200 species, the most substantial genotype and phenotype resources have been curated for conifer species.…”

Section: Cartogratree Datamentioning

confidence: 99%

CartograTree: Enabling landscape genomics for forest trees

Herndon

Grau

Batra

et al. 2016

Preprint

View full text Add to dashboard Cite

Forest trees cover just over 30% of the earth's surface and are studied by researchers around the world for both their conservation and economic value. With the onset of high throughput technologies, tremendous phenotypic and genomic data sets have been generated for hundreds of species. These long-lived and immobile individuals serve as ideal models to assess population structure and adaptation to environment. Despite the availability of comprehensive data, researchers are challenged to integrate genotype, phenotype, and environment in one place. Towards this goal, CartograTree was designed and implemented as an open repository and open-source analytic framework for genomic, phenotypic, and environmental data for forest trees. One of its key components, the integration of geospatial data, allows the display of environmental layers and acquisition of environmental metrics relative to the positions of georeferenced individuals. Currently, CartograTree uses the Google Maps API to load environmental data. Limitations inherent to this API are driving new development with a focus on functionality to provide efficient queries of numerous environmental metrics.

show abstract

TreeGenes: A Forest Tree Genome Database

Cited by 96 publications

References 16 publications

Expression Profiling in Pinus pinaster in Response to Infection with the Pine Wood Nematode Bursaphelenchus xylophilus

Expression Profiling in Pinus pinaster in Response to Infection with the Pine Wood Nematode Bursaphelenchus xylophilus

Dual RNA-Sequencing to Elucidate the Plant-Pathogen Duel

CartograTree: Enabling landscape genomics for forest trees

Contact Info

Product

Resources

About