ArticleGenetics2017
Accuracy of Genomic Prediction in Synthetic Populations Depending on the Number of Parents, Relatedness, and Ancestral Linkage Disequilibrium.
Article in Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 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
44 citing papers in PubMed.
- Restructuring breeding programs 1: Integration of diversity.Genetics, selection, evolution : GSE · 2026Article
- Integrating genomic predictions into an applied Central European wheat breeding program.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Genomic prediction for grain yield and biotic stress resistance in field pea (Frontiers in plant science · 2026Article
- Rapid cycling genomic selection in maize landraces: a step toward closing the yield gap.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Leveraging genetic resources and genomic prediction to enhance flavonol content in cranberry fruit.The plant genome · 2025Article
- Optimization of recurrent rapid cycle breeding in maize for sustained long-term genetic improvement via stochastic simulations.G3 (Bethesda, Md.) · 2025Article
- Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.Plant biotechnology journal · 2025Article
- Improving wheat grain yield genomic prediction accuracy using historical data.G3 (Bethesda, Md.) · 2025Article
- Multi-population GWAS detects robust marker associations in a newly established six-rowed winter barley breeding program.Heredity · 2025Article
- Multi-trait ridge regression BLUP withFrontiers in plant science · 2025Article
- Genome-wide association study and genomic selection of brace root traits related to lodging resistance in maize.Scientific reports · 2024Article
- Genomic and phenomic predictions help capture low-effect alleles promoting seed germination in oilseed rape in addition to QTL analyses.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Genomic prediction within and across maize landrace derived populations using haplotypes.Frontiers in plant science · 2024Article
- Genomic prediction in hybrid breeding: I. Optimizing the training set design.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2023Article
- Genome-wide genotyping data renew knowledge on genetic diversity of a worldwide alfalfa collection and give insights on genetic control of phenology traits.Frontiers in plant science · 2023Article
- Theoretical and experimental assessment of genome-based prediction in landraces of allogamous crops.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Unraveling the potential of phenomic selection within and among diverse breeding material of maize (Zea mays L.).G3 (Bethesda, Md.) · 2022Article
- Genomic Prediction of Complex Traits in an Allogamous Annual Crop: The Case of Maize Single-Cross Hybrids.Methods in molecular biology (Clifton, N.J.) · 2022Article
- High-resolution association mapping with libraries of immortalized lines from ancestral landraces.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022Article
- Impact of early genomic prediction for recurrent selection in an upland rice synthetic population.G3 (Bethesda, Md.) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Synthetics play an important role in quantitative genetic research and plant breeding, but few studies have investigated the application of genomic prediction (GP) to these populations. Synthetics are generated by intermating a small number of parents ([Formula: see text] and thereby possess unique genetic properties, which make them especially suited for systematic investigations of factors contributing to the accuracy of GP. We generated synthetics in silico from [Formula: see text]2 to 32 maize (Zea mays L.) lines taken from an ancestral population with either short- or long-range linkage disequilibrium (LD). In eight scenarios differing in relatedness of the training and prediction sets and in the types of data used to calculate the relationship matrix (QTL, SNPs, tag markers, and pedigree), we investigated the prediction accuracy (PA) of Genomic best linear unbiased prediction (GBLUP) and analyzed contributions from pedigree relationships captured by SNP markers, as well as from cosegregation and ancestral LD between QTL and SNPs. The effects of training set size [Formula: see text] and marker density were also studied. Sampling few parents ([Formula: see text]) generates substantial sample LD that carries over into synthetics through cosegregation of alleles at linked loci. For fixed [Formula: see text], [Formula: see text] influences PA most strongly. If the training and prediction set are related, using [Formula: see text] parents yields high PA regardless of ancestral LD because SNPs capture pedigree relationships and Mendelian sampling through cosegregation. As [Formula: see text] increases, ancestral LD contributes more information, while other factors contribute less due to lower frequencies of closely related individuals. For unrelated prediction sets, only ancestral LD contributes information and accuracies were poor and highly variable for [Formula: see text] due to large sample LD. For large [Formula: see text], achieving moderate accuracy requires large [Formula: see text], long-range ancestral LD, and high marker density. Our approach for analyzing PA in synthetics provides new insights into the prospects of GP for many types of source populations encountered in plant breeding.
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.