Evidence map›Paper›PMID 33193595›Full record

ArticleFrontiers in genetics2020

Marker Selection in Multivariate Genomic Prediction Improves Accuracy of Low Heritability Traits.

Jaroslav Klápště, Heidi S Dungey, Emily J Telfer, Mari Suontama, Natalie J Graham, Yongjun Li, Russell McKinley

Abstract read
In one paragraph

Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
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  4. Heritability of theFrontiers in plant science · 2026
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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

7 authors.

Jaroslav KlápštěScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Heidi S DungeyScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Emily J TelferScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Mari SuontamaScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Natalie J GrahamScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Yongjun LiScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.
Russell McKinleyScion (New Zealand Forest Research Institute Ltd.), Rotorua, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multivariate analysis using mixed models allows for the exploration of genetic correlations between traits. Additionally, the transition to a genomic based approach is simplified by substituting classic pedigrees with a marker-based relationship matrix. It also enables the investigation of correlated responses to selection, trait integration and modularity in different kinds of populations. This study investigated a strategy for the construction of a marker-based relationship matrix that prioritized markers using Partial Least Squares. The efficiency of this strategy was found to depend on the correlation structure between investigated traits. In terms of accuracy, we found no benefit of this strategy compared with the all-marker-based multivariate model for the primary trait of diameter at breast height (DBH) in a radiata pine (

Indexed as

Eucalyptus nitensgenomic predictionmultivariate mixed modelPinus radiataPLSvariable selection

Identifiers

PMID33193595
PMCPMC7662070

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.