ArticleThe plant genome2024
Effects of SNP marker density and training population size on prediction accuracy in alfalfa (Medicago sativa L.) genomic selection.
Article in The plant genome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed, 13 citations in OpenAlex.
- Efficiency under epistasis of haplotype-based genomic selection for pure line breeding.Heredity · 2026Article
- Enhancing alfalfa breeding through genomic prediction with exotic germplasm resources.BMC plant biology · 2026Article
- Article
- Article
- GWAS-assisted genomic selection for achieving high-precision early sex prediction in Populus deltoides.The plant genome · 2026Article
- Crop phenotype prediction using SNP context and whole-genome feature embedding based on DNABERT-2.Plant methods · 2026Article
- Implications of morphological and molecular distinctness on the registration of alfalfa candidate varieties issued by a breeding program: a case study.Frontiers in plant science · 2026Article
- Genetic parameters estimation and optimization of genomic selection in mud crab (Scylla paramamosain): a case study for growth-related traits.BMC genomics · 2025Article
- Optimization of high-throughput marker systems for genomic prediction in alfalfa family bulks.The plant genome · 2025Article
- Assessment of Genetic Diversity in Alfalfa Using DNA Polymorphism Analysis and Statistical Tools.Plants (Basel, Switzerland) · 2024Article
- Effects of SNP marker density and training population size on prediction accuracy in alfalfa (Medicago sativa L.) genomic selection.The plant genome · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Effects of individual single-nucleotide polymorphism (SNP) markers and the size of "training" and "test" populations affect prediction accuracy in genomic selection (GS). This study evaluated 11 subsets of 4932 SNPs using six genetic additive methods to understand marker density in GS prediction in alfalfa (Medicago sativa L.). In the GS methods, the effect of "training" to "test" population size was also evaluated. Fourteen alfalfa populations sampled from long-term grazing sites were genotyped using genotyping by sequencing for the identification of SNPs. These populations were also phenotyped for six agromorphological and three nutritive traits from 2018 to 2020. The accuracy of GS prediction improved across six GS methods when the ratio of "training" to "test" population size increased. However, the prediction accuracy of the six GS methods reduced to a range of -0.27 to 0.11 when random, uninformative SNPs were used. In this study, five Bayesian methods and ridge-regression best linear unbiased prediction (rrBLUP) method had similar GS accuracies for "training" sets, but rrBLUP tended to outperform Bayesian methods in independent "test" sets when SNP subsets with high mean-squared-estimated-marker effect were used. These findings can enhance the application of GS in alfalfa genetic improvement.
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.