Evidence map›Paper›PMID 19363603›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2009

Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials.

Andrea Michaela Bauer, F Hoti, M von Korff, K Pillen, J Léon, M J Sillanpää

Open access · hybridAbstract readEvaluation Study
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.0field-weighted citation impact, top 9% 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

12 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Identification of QTLs for wheat heading time across multiple-environments.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  3. Major flowering time genes of barley: allelic diversity, effects, and comparison with wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Mapping QTL for agronomic traits in breeding populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2012
    Review
  11. Mapping QTL main and interaction influences on milling quality in elite US rice germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2011
    Article
  12. Mixed model approaches for the identification of QTLs within a maize hybrid breeding program.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2010
    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

6 authors at 5 institutions in 2 countries.

Andrea Michaela BauerInstitute of Crop Science and Resource Conservation, University of Bonn, Bonn, Germany. a.bauer@uni-bonn.de
F Hoti
M von Korff
K Pillen
J Léon
M J Sillanpää
University of Bonn · DEFinnish Institute for Health and Welfare · FIMartin Luther University Halle-Wittenberg · DEMax Planck Institute for Plant Breeding Research · DEUniversity of Helsinki · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A common difficulty in mapping quantitative trait loci (QTLs) is that QTL effects may show environment specificity and thus differ across environments. Furthermore, quantitative traits are likely to be influenced by multiple QTLs or genes having different effect sizes. There is currently a need for efficient mapping strategies to account for both multiple QTLs and marker-by-environment interactions. Thus, the objective of our study was to develop a Bayesian multi-locus multi-environmental method of QTL analysis. This strategy is compared to (1) Bayesian multi-locus mapping, where each environment is analysed separately, (2) Restricted Maximum Likelihood (REML) single-locus method using a mixed hierarchical model, and (3) REML forward selection applying a mixed hierarchical model. For this study, we used data on multi-environmental field trials of 301 BC(2)DH lines derived from a cross between the spring barley elite cultivar Scarlett and the wild donor ISR42-8 from Israel. The lines were genotyped by 98 SSR markers and measured for the agronomic traits "ears per m(2)," "days until heading," "plant height," "thousand grain weight," and "grain yield". Additionally, a simulation study was performed to verify the QTL results obtained in the spring barley population. In general, the results of Bayesian QTL mapping are in accordance with REML methods. In this study, Bayesian multi-locus multi-environmental analysis is a valuable method that is particularly suitable if lines are cultivated in multi-environmental field trials.

Indexed as

Bayes TheoremEnvironmentInbreedingLikelihood FunctionsModels, GeneticChromosome MappingChromosomes, PlantComputer SimulationGenetic VariationHordeumQuantitative Trait Loci

Identifiers

PMID19363603
PMCPMC2755740
OpenAlexW1983757584

What OpenQuestion holds

Textmetadata
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.