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Record W2920809832 · doi:10.1111/nph.15777

Multitrait genome‐wide association analysis of <i>Populus trichocarpa</i> identifies key polymorphisms controlling morphological and physiological traits

2019· article· en· W2920809832 on OpenAlexaboutno aff
Hari Chhetri, David Macaya‐Sanz, David Kainer, Ajaya K. Biswal, Luke M. Evans, Jin‐Gui Chen, Cassandra Collins, Kimberly Hunt, Sushree S. Mohanty, Todd N. Rosenstiel, David Ryno, Kim Winkeler, Xiaohan Yang, Daniel Jacobson, Debra Mohnen, Wellington Muchero, Steven H. Strauss, Timothy J. Tschaplinski, Gerald A. Tuskan, Stephen DiFazio

Bibliographic record

VenueNew Phytologist · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsnot available
FundersBiological and Environmental ResearchNational Institute of Food and AgricultureUT-BattelleOak Ridge National LaboratoryJoint Genome InstituteBattelleCenter for Bioenergy InnovationOffice of ScienceU.S. Department of AgricultureU.S. Department of Energy
KeywordsBiologyGenome-wide association studySingle-nucleotide polymorphismPopulus trichocarpaGenetic associationGeneticsGenetic architectureHeritabilityQuantitative trait locusCandidate geneAssociation mappingGenePhenotypeTraitSNPMissing heritability problemGenomeGenotype

Abstract

fetched live from OpenAlex

Summary Genome‐wide association studies (GWAS) have great promise for identifying the loci that contribute to adaptive variation, but the complex genetic architecture of many quantitative traits presents a substantial challenge. We measured 14 morphological and physiological traits and identified single nucleotide polymorphism (SNP)‐phenotype associations in a Populus trichocarpa population distributed from California, USA to British Columbia, Canada. We used whole‐genome resequencing data of 882 trees with more than 6.78 million SNPs, coupled with multitrait association to detect polymorphisms with potentially pleiotropic effects. Candidate genes were validated with functional data. Broad‐sense heritability ( H 2 ) ranged from 0.30 to 0.56 for morphological traits and 0.08 to 0.36 for physiological traits. In total, 4 and 20 gene models were detected using the single‐trait and multitrait association methods, respectively. Several of these associations were corroborated by additional lines of evidence, including co‐expression networks, metabolite analyses, and direct confirmation of gene function through RNAi. Multitrait association identified many more significant associations than single‐trait association, potentially revealing pleiotropic effects of individual genes. This approach can be particularly useful for challenging physiological traits such as water‐use efficiency or complex traits such as leaf morphology, for which we were able to identify credible candidate genes by combining multitrait association with gene co‐expression and co‐methylation data.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.769

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.242
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations134
Published2019
Admission routes1
Has abstractyes

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