Evidence map›Paper›PMID 26599762›Full record

ArticlePloS one2015

Evolutionary Quantitative Genomics of Populus trichocarpa.

Ilga Porth, Jaroslav Klápště, Athena D McKown, Jonathan La Mantia, Robert D Guy, Pär K Ingvarsson, Richard Hamelin, Shawn D Mansfield, Jürgen Ehlting, Carl J Douglas and 1 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Genetic adaptation of Tibetan poplar (Ecology and evolution · 2020
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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

11 authors.

Ilga PorthDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Jaroslav KlápštěDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Athena D McKownDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Jonathan La MantiaDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Robert D GuyDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Pär K IngvarssonDepartment of Ecology and Environmental Science, Umeå University, Umeå, SE-901 87, Sweden.
Richard HamelinDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Shawn D MansfieldDepartment of Wood Science, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Jürgen EhltingDepartment of Biology and Centre for Forest Biology, University of Victoria, Victoria, BC V8W 3N5, Canada.
Carl J DouglasDepartment of Botany, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
Yousry A El-KassabyDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forest trees generally show high levels of local adaptation and efforts focusing on understanding adaptation to climate will be crucial for species survival and management. Here, we address fundamental questions regarding the molecular basis of adaptation in undomesticated forest tree populations to past climatic environments by employing an integrative quantitative genetics and landscape genomics approach. Using this comprehensive approach, we studied the molecular basis of climate adaptation in 433 Populus trichocarpa (black cottonwood) genotypes originating across western North America. Variation in 74 field-assessed traits (growth, ecophysiology, phenology, leaf stomata, wood, and disease resistance) was investigated for signatures of selection (comparing QST-FST) using clustering of individuals by climate of origin (temperature and precipitation). 29,354 SNPs were investigated employing three different outlier detection methods and marker-inferred relatedness was estimated to obtain the narrow-sense estimate of population differentiation in wild populations. In addition, we compared our results with previously assessed selection of candidate SNPs using the 25 topographical units (drainages) across the P. trichocarpa sampling range as population groupings. Narrow-sense QST for 53% of distinct field traits was significantly divergent from expectations of neutrality (indicating adaptive trait variation); 2,855 SNPs showed signals of diversifying selection and of these, 118 SNPs (within 81 genes) were associated with adaptive traits (based on significant QST). Many SNPs were putatively pleiotropic for functionally uncorrelated adaptive traits, such as autumn phenology, height, and disease resistance. Evolutionary quantitative genomics in P. trichocarpa provides an enhanced understanding regarding the molecular basis of climate-driven selection in forest trees and we highlight that important loci underlying adaptive trait variation also show relationship to climate of origin. We consider our approach the most comprehensive, as it uncovers the molecular mechanisms of adaptation using multiple methods and tests. We also provide a detailed outline of the required analyses for studying adaptation to the environment in a population genomics context to better understand the species' potential adaptive capacity to future climatic scenarios.

Indexed as

Biological EvolutionGenomicsBritish ColumbiaClimateGenome, PlantGenotypeGeographyOregonPolymorphism, Single NucleotidePopulusPrincipal Component AnalysisQuantitative Trait, HeritableSelection, Genetic

Identifiers

PMID26599762
PMCPMC4658102

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.