ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2016
Choice of models for QTL mapping with multiple families and design of the training set for prediction of Fusarium resistance traits in maize.
Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.
- Meta-analysis and co-expression analysis revealed stable QTL and candidate genes conferring resistances to Fusarium and Gibberella ear rots while reducing mycotoxin contamination in maize.Frontiers in plant science · 2022Pooled it
- Genomic loci associated with Fusarium stalk rot resistance and related agronomic traits in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- QTL mapping of Fusarium ear rot resistance using genotyping by target sequencing (GBTS) in maize.Journal of applied genetics · 2025Article
- Genome-wide association study and molecular marker development for susceptibility to Gibberella ear rot in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- A combination of joint linkage and genome-wide association study reveals putative candidate genes associated with resistance to northern corn leaf blight in tropical maize.Frontiers in plant science · 2024Article
- Modeling QTL-by-environment interactions for multi-parent populations.Frontiers in plant science · 2024Article
- Genomic prediction for fusiform rust disease incidence in a large cloned population of Pinus taeda.G3 (Bethesda, Md.) · 2021Article
- Heterotic quantitative trait loci analysis and genomic prediction of seedling biomass-related traits in maize triple testcross populations.Plant methods · 2021Article
- Exploiting genetic diversity in two European maize landraces for improving Gibberella ear rot resistance using genomic tools.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- The influence of QTL allelic diversity on QTL detection in multi-parent populations: a simulation study in sugar beet.BMC genomic data · 2021Article
- Intercontinental trials reveal stable QTL for Northern corn leaf blight resistance in Europe and in Brazil.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- Genomics-Assisted Breeding for Quantitative Disease Resistances in Small-Grain Cereals and Maize.International journal of molecular sciences · 2020Review
- Genomics-assisted breeding for ear rot resistances and reduced mycotoxin contamination in maize: methods, advances and prospects.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Review
- An experimental approach for estimating the genomic selection advantage for Fusarium head blight and Septoria tritici blotch in winter wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- Accuracy of within- and among-family genomic prediction for Fusarium head blight and Septoria tritici blotch in winter wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019Article
- Linkage Analysis and Association Mapping QTL Detection Models for Hybrids Between Multiparental Populations from Two Heterotic Groups: Application to Biomass Production in Maize (G3 (Bethesda, Md.) · 2017Article
- Article
- How do the type of QTL effect and the form of the residual term influence QTL detection in multi-parent populations? A case study in the maize EU-NAM population.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2017Article
- Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
key messageQTL analysis for Fusarium resistance traits with multiple connected families detected more QTL than single-family analysis. Prediction accuracy was tightly associated with the kinship of the validation and training set. ABSTRACT: QTL mapping has recently shifted from analysis of single families to multiple, connected families and several biometric models have been suggested. Using a high-density consensus map with 2472 marker loci, we performed QTL mapping with five connected bi-parental families with 639 doubled-haploid (DH) lines in maize for ear rot resistance and analyzed traits DON, Gibberella ear rot severity (GER), and days to silking (DS). Five biometric models differing in the assumption about the number and effects of alleles at QTL were compared. Model 2 to 5 performing joint analyses across all families and using linkage and/or linkage disequilibrium (LD) information identified all and even further QTL than Model 1 (single-family analyses) and generally explained a higher proportion pG of the genotypic variance for all three traits. QTL for DON and GER were mostly family specific, but several QTL for DS occurred in multiple families. Many QTL displayed large additive effects and most alleles increasing resistance originated from a resistant parent. Interactions between detected QTL and genetic background (family) occurred rarely and were comparatively small. Detailed analysis of three fully connected families yielded higher pG values for Model 3 or 4 than for Model 2 and 5, irrespective of the size NTS of the training set (TS). In conclusion, Model 3 and 4 can be recommended for QTL-based prediction with larger families. Including a sufficiently large number of full sibs in the TS helped to increase QTL-based prediction accuracy (rVS) for various scenarios differing in the composition of the TS.
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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.