Evidence map›Paper›PMID 28620209›Full record

ArticleScientific reports2017

Using variable importance measures to identify a small set of SNPs to predict heading date in perennial ryegrass.

Stephen L Byrne, Patrick Conaghan, Susanne Barth, Sai Krishna Arojju, Michael Casler, Thibauld Michel, Janaki Velmurugan, Dan Milbourne

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
6.1field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 24 citations in OpenAlex.

  1. Estimation of ryegrass (Frontiers in plant science · 2025
    Article
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  9. Genetic characterization of worldwideHorticulture research · 2019
    Article
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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

8 authors at 2 institutions in 2 countries.

Stephen L ByrneTeagasc, Crop Science Department, Oak Park, Carlow, Ireland. stephen.byrne@teagasc.ie.ORCID 0000-0002-1179-2272
Patrick ConaghanTeagasc, Animal and Grassland Research and Innovation Centre, Oak Park, Carlow, Ireland.
Susanne BarthTeagasc, Crop Science Department, Oak Park, Carlow, Ireland.
Sai Krishna ArojjuTeagasc, Crop Science Department, Oak Park, Carlow, Ireland.
Michael CaslerDepartment of Agronomy, University of Wisconsin-Madison, Madison, WI, 53706, USA.
Thibauld MichelTeagasc, Crop Science Department, Oak Park, Carlow, Ireland.
Janaki VelmuruganTeagasc, Crop Science Department, Oak Park, Carlow, Ireland.
Dan MilbourneTeagasc, Crop Science Department, Oak Park, Carlow, Ireland.
Teagasc - The Irish Agriculture and Food Development Authority · IEUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prior knowledge on heading date enables the selection of parents of synthetic cultivars that are well matched with respect to time of heading, which is essential to ensure plants put together will cross pollinate. Heading date of individual plants can be determined via direct phenotyping, which has a time and labour cost. It can also be inferred from family means, although the spread in days to heading within families demands roguing in first generation synthetics. Another option is to predict heading date from molecular markers. In this study we used a large training population consisting of individual plants to develop equations to predict heading date from marker genotypes. Using permutation-based variable selection measures we reduced the marker set from 217,563 to 50 without impacting the predictive ability. Opportunities exist to develop a cheap assay to sequence a small number of regions in linkage disequilibrium with heading date QTL in thousands of samples. Simultaneous use of these markers in non-linkage based marker-assisted selection approaches, such as paternity testing, should enhance the utility of such an approach.

Indexed as

Evolution, MolecularPolymorphism, Single NucleotideAlgorithmsGenetics, PopulationGenome-Wide Association StudyGenotypeLoliumModels, GeneticPhenotypeQuantitative Trait Loci

Identifiers

PMID28620209
PMCPMC5472636
OpenAlexW2624434972

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.