ArticleHeredity2015
Joint-multiple family linkage analysis predicts within-family variation better than single-family analysis of the maize nested association mapping population.
Article in Heredity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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Who cites it
40 citing papers in PubMed.
- An IRAT109 NAM population: Genetic characterization and mapping utility for trait dissection in japonica rice (Oryza sativa L.).The plant genome · 2026Article
- An ancient origin of the naked grains of maize.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- The population genetics of convergent adaptation in maize and teosinte is not locally restricted.eLife · 2025Article
- Identification of loci conferring resistance to 4 foliar diseases of maize.G3 (Bethesda, Md.) · 2024Article
- Mapping QTLs for blight resistance and morpho-phenological traits in inter-species hybrid families of chestnut (Frontiers in plant science · 2024Article
- Molecular characterization of doubled haploid lines derived from different cycles of the Iowa Stiff Stalk Synthetic (BSSS) maize population.Frontiers in plant science · 2023Article
- A divide-and-conquer approach for genomic prediction in rubber tree using machine learning.Scientific reports · 2022Article
- Modeling allelic diversity of multiparent mapping populations affects detection of quantitative trait loci.G3 (Bethesda, Md.) · 2022Article
- An IBD-based mixed model approach for QTL mapping in multiparental populations.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021Article
- The genomic ecosystem of transposable elements in maize.PLoS genetics · 2021Article
- Selective sorting of ancestral introgression in maize and teosinte along an elevational cline.PLoS genetics · 2021Article
- The genetic architecture of leaf stable carbon isotope composition in Zea mays and the effect of transpiration efficiency on leaf elemental accumulation.G3 (Bethesda, Md.) · 2021Article
- Molecular Parallelism Underlies Convergent Highland Adaptation of Maize Landraces.Molecular biology and evolution · 2021Article
- De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes.Science (New York, N.Y.) · 2021Article
- Eleven biosynthetic genes explain the majority of natural variation in carotenoid levels in maize grain.The Plant cell · 2021Article
- Selective Loss of Diversity in Doubled-Haploid Lines from European Maize Landraces.G3 (Bethesda, Md.) · 2020Article
- Quantitative Genomic Dissection of Soybean Yield Components.G3 (Bethesda, Md.) · 2020Article
- A Multi-Locus Association Model Framework for Nested Association Mapping With Discriminating QTL Effects in Various Subpopulations.Frontiers in genetics · 2020Article
- A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat.Plant biotechnology journal · 2019Article
- Detecting Adaptive Differentiation in Structured Populations with Genomic Data and Common Gardens.Genetics · 2019Article
Corrections and comments
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Quantitative trait locus (QTL) mapping has been used to dissect the genetic architecture of complex traits and predict phenotypes for marker-assisted selection. Many QTL mapping studies in plants have been limited to one biparental family population. Joint analysis of multiple biparental families offers an alternative approach to QTL mapping with a wider scope of inference. Joint-multiple population analysis should have higher power to detect QTL shared among multiple families, but may have lower power to detect rare QTL. We compared prediction ability of single-family and joint-family QTL analysis methods with fivefold cross-validation for 6 diverse traits using the maize nested association mapping population, which comprises 25 biparental recombinant inbred families. Joint-family QTL analysis had higher mean prediction abilities than single-family QTL analysis for all traits at most significance thresholds, and was always better at more stringent significance thresholds. Most robust QTL (detected in >50% of data samples) were restricted to one family and were often not detected at high frequency by joint-family analysis, implying substantial genetic heterogeneity among families for complex traits in maize. The superior predictive ability of joint-family QTL models despite important genetic differences among families suggests that joint-family models capture sufficient smaller effect QTL that are shared across families to compensate for missing some rare large-effect QTL.
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