Evidence map›Paper›PMID 31892954›Full record

ArticleEvolutionary applications2020

Cyberinfrastructure and resources to enable an integrative approach to studying forest trees.

Jill L Wegrzyn, Taylor Falk, Emily Grau, Sean Buehler, Risharde Ramnath, Nic Herndon

Abstract read
In one paragraph

Article in Evolutionary applications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jill L WegrzynDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.ORCID https://orcid.org/0000-0001-5923-0888
Taylor FalkDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.
Emily GrauDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.
Sean BuehlerDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.
Risharde RamnathDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.
Nic HerndonDepartment of Ecology and Evolutionary Biology University of Connecticut Storrs Connecticut.ORCID https://orcid.org/0000-0001-9712-148X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sequencing technologies and bioinformatic approaches are now available to resolve the challenges associated with complex and heterozygous genomes. Increased access to less expensive and more effective instrumentation will contribute to a wealth of high-quality plant genomes in the next few years. In the meantime, more than 370 tree species are associated with public projects in primary repositories that are interrogating expression profiles, identifying variants, or analyzing targeted capture without a high-quality reference genome. Genomic data from these projects generates sequences that represent intermediate assemblies for transcriptomes and genomes. These data contribute to forest tree biology, but the associated sequence remains trapped in supplemental files that are poorly integrated in plant community databases and comparative genomic platforms. Successful implementation of life science cyberinfrastructure is improving data standards, ontologies, analytic workflows, and integrated database platforms for both model and non-model plant species. Unique to forest trees with large populations that are long-lived, outcrossing, and genetically diverse, the phenotypic and environmental metrics associated with georeferenced populations are just as important as the genomic data sampled for each individual. To address questions related to forest health and productivity, cyberinfrastructure must keep pace with the magnitude of genomic and phenomic sampling of larger populations. This review examines the current landscape of cyberinfrastructure, with an emphasis on best practices and resources to align community data with the Findable, Accessible, Interoperable, and Reusable (FAIR) guidelines.

Indexed as

cyberinfrastructureFAIRphenomicsplant ontologiespopulation geneticstree databasestree genomicsworkflows

Identifiers

PMID31892954
PMCPMC6935593

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.