ArticleHeredity2015
Genomic prediction in biparental tropical maize populations in water-stressed and well-watered environments using low-density and GBS SNPs.
Article in Heredity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 97 papers.
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.
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.
Who cites it
97 citing papers in PubMed.
- Dissecting genetic variance structure and evaluating genomic prediction models for single-cross hybrids derived from Stiff Stalk and Non-Stiff Stalk maize heterotic groups.G3 (Bethesda, Md.) · 2026Article
- Experimental evaluation of effectiveness of genomic selection for resistance to northern corn leaf blight in maize.Journal of applied genetics · 2025Article
- Leveraging genetic resources and genomic prediction to enhance flavonol content in cranberry fruit.The plant genome · 2025Article
- GWAS and GS analysis revealed the selection and prediction efficiency for yield, plant morphological, and fiber quality in Gossypium barbadense.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Genomic Prediction for Germplasm Improvement Through Inter-Heterotic-Group Line Crossing in Maize.International journal of molecular sciences · 2025Article
- Improvement in genomic prediction of maize with prior gene ontology information depends on traits and environmental conditions.The plant genome · 2025Article
- Genome-wide association mapping and genomic prediction analyses reveal the genetic architecture of grain yield and agronomic traits under drought and optimum conditions in maize.BMC plant biology · 2025Article
- Assessment of the potential for genomic selection to improve resistance to fusarium stalk rot in maize.Frontiers in plant science · 2025Article
- Genome-wide association analysis and genomic selection for leaf-related traits of maize.PloS one · 2025Article
- Genomic selection optimization in blueberry: Data-driven methods for marker and training population design.The plant genome · 2024Article
- Ability of Genomic Prediction to Bi-Parent-Derived Breeding Population Using Public Data for Soybean Oil and Protein Content.Plants (Basel, Switzerland) · 2024Article
- Exploiting genomic tools for genetic dissection and improving the resistance to Fusarium stalk rot in tropical maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Integrating Association Mapping, Linkage Mapping, Fine Mapping with RNA Seq Conferring Seedling Vigor Improvement for Successful Crop Establishment in Deep Sown Direct-Seeded Rice.Rice (New York, N.Y.) · 2023Article
- Identification and Functional Analysis of Drought-Responsive Long Noncoding RNAs in Maize Roots.International journal of molecular sciences · 2023Article
- Hybrid breeding for fall armyworm resistance: Combining ability and hybrid prediction.Plant breeding = Zeitschrift fur Pflanzenzuchtung · 2023Article
- The Era of Plant Breeding: Conventional Breeding to Genomics-assisted Breeding for Crop Improvement.Current genomics · 2023Review
- Discovery of genomic regions associated with grain yield and agronomic traits in Bi-parental populations of maize (Frontiers in genetics · 2023Article
- Impacts of salinity stress on crop plants: improving salt tolerance through genetic and molecular dissection.Frontiers in plant science · 2023Review
- Genomic versus phenotypic selection to improve corn borer resistance and grain yield in maize.Frontiers in plant science · 2023Article
- Mapping of QTLs for morphophysiological and yield traits under water-deficit stress and well-watered conditions in maize.Frontiers in plant science · 2023Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the most important applications of genomic selection in maize breeding is to predict and identify the best untested lines from biparental populations, when the training and validation sets are derived from the same cross. Nineteen tropical maize biparental populations evaluated in multienvironment trials were used in this study to assess prediction accuracy of different quantitative traits using low-density (~200 markers) and genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs), respectively. An extension of the Genomic Best Linear Unbiased Predictor that incorporates genotype × environment (GE) interaction was used to predict genotypic values; cross-validation methods were applied to quantify prediction accuracy. Our results showed that: (1) low-density SNPs (~200 markers) were largely sufficient to get good prediction in biparental maize populations for simple traits with moderate-to-high heritability, but GBS outperformed low-density SNPs for complex traits and simple traits evaluated under stress conditions with low-to-moderate heritability; (2) heritability and genetic architecture of target traits affected prediction performance, prediction accuracy of complex traits (grain yield) were consistently lower than those of simple traits (anthesis date and plant height) and prediction accuracy under stress conditions was consistently lower and more variable than under well-watered conditions for all the target traits because of their poor heritability under stress conditions; and (3) the prediction accuracy of GE models was found to be superior to that of non-GE models for complex traits and marginal for simple traits.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.