Evidence map›Paper›PMID 35298481›Full record

ArticlePloS one2022

Integrating genomic information and productivity and climate-adaptability traits into a regional white spruce breeding program.

Eduardo P Cappa, Jennifer G Klutsch, Jaime Sebastian-Azcona, Blaise Ratcliffe, Xiaojing Wei, Letitia Da Ros, Yang Liu, Charles Chen, Andy Benowicz, Shane Sadoway and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
5.5field-weighted citation impact, top 4% of its field
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

6 citing papers in PubMed, 21 citations in OpenAlex.

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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

14 authors at 5 institutions in 3 countries.

Eduardo P CappaInstituto de Recursos Biológicos, Centro de Investigación en Recursos Naturales, Instituto Nacional de Tecnología Agropecuaria (INTA), Hurlingham, Buenos Aires, Argentina.ORCID 0000-0002-6234-2263
Jennifer G KlutschDepartment of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada.
Jaime Sebastian-AzconaDepartment of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada.
Blaise RatcliffeDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada.
Xiaojing WeiDepartment of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada.
Letitia Da RosDepartment of Wood Science, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada.
Yang LiuDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada.
Charles ChenDepartment of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, Oklahoma, United States of America.
Andy BenowiczForest Stewardship and Trade Branch, Alberta Agriculture and Forestry, Edmonton, Alberta, Canada.
Shane SadowayBlue Ridge Lumber Inc., West Fraser Mills Ltd, Blue Ridge, Alberta, Canada.
Shawn D MansfieldDepartment of Wood Science, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada.ORCID 0000-0002-0175-554X
Nadir ErbilginDepartment of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada.
Barb R ThomasDepartment of Renewable Resources, University of Alberta, Edmonton, Alberta, Canada.
Yousry A El-KassabyDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, British Columbia, Canada.
University of Alberta · CAUniversity of British Columbia · CAConsejo Nacional de Investigaciones Científicas y Técnicas · AROklahoma State University · USWest Fraser (Canada) · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tree improvement programs often focus on improving productivity-related traits; however, under present climate change scenarios, climate change-related (adaptive) traits should also be incorporated into such programs. Therefore, quantifying the genetic variation and correlations among productivity and adaptability traits, and the importance of genotype by environment interactions, including defense compounds involved in biotic and abiotic resistance, is essential for selecting parents for the production of resilient and sustainable forests. Here, we estimated quantitative genetic parameters for 15 growth, wood quality, drought resilience, and monoterpene traits for Picea glauca (Moench) Voss (white spruce). We sampled 1,540 trees from three open-pollinated progeny trials, genotyped with 467,224 SNP markers using genotyping-by-sequencing (GBS). We used the pedigree and SNP information to calculate, respectively, the average numerator and genomic relationship matrices, and univariate and multivariate individual-tree models to obtain estimates of (co)variance components. With few site-specific exceptions, all traits examined were under genetic control. Overall, higher heritability estimates were derived from the genomic- than their counterpart pedigree-based relationship matrix. Selection for height, generally, improved diameter and water use efficiency, but decreased wood density, microfibril angle, and drought resistance. Genome-based correlations between traits reaffirmed the pedigree-based correlations for most trait pairs. High and positive genetic correlations between sites were observed (average 0.68), except for those pairs involving the highest elevation, warmer, and moister site, specifically for growth and microfibril angle. These results illustrate the advantage of using genomic information jointly with productivity and adaptability traits, and defense compounds to enhance tree breeding selection for changing climate.

Indexed as

PiceaGenomicsGenotypePhenotypePlant BreedingPolymorphism, Single Nucleotide

Identifiers

PMID35298481
PMCPMC8929621
OpenAlexW4221054298

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.