ArticleMolecular genetics and genomics : MGG2020
Evaluation of genomic selection methods for predicting fiber quality traits in Upland cotton.
Article in Molecular genetics and genomics : MGG, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Water stress tolerance, genomic selection and identification of genomic regions in a MAGIC population of eggplant.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Accelerating genetic gain through integrated genomic selection in crop plants.Journal of applied genetics · 2026Review
- Integration of inter-simple sequence repeats with machine learning approach for diversity analysis and authentication of Iranian cotton cultivars.Biochemistry and biophysics reports · 2026Article
- Enhancing prediction accuracy of key biomass partitioning traits in wheat using multi-kernel genomic prediction models integrating secondary traits and environmental covariates.The plant genome · 2025Article
- Assessment of the potential for genomic selection to improve resistance to fusarium stalk rot in maize.Frontiers in plant science · 2025Article
- Identification of favorable alleles from exotic Upland cotton lines for fiber quality improvement using multiple association models.Frontiers in plant science · 2025Article
- Genome-wide association study and genomic prediction of leaf spot (Frontiers in plant science · 2025Article
- Genome resources for three modern cotton lines guide future breeding efforts.Nature plants · 2024Article
- Genomic selection of soybean (Glycine max) for genetic improvement of yield and seed composition in a breeding context.The plant genome · 2023Article
- Genomic prediction of optimal cross combinations to accelerate genetic improvement of soybean (Frontiers in plant science · 2023Article
- A first look at the ability to use genomic prediction for improving the ratooning ability of sugarcane.Frontiers in plant science · 2023Article
- Genomic prediction of cotton fibre quality and yield traits using Bayesian regression methods.Heredity · 2022Article
- Outlook for Implementation of Genomics-Based Selection in Public Cotton Breeding Programs.Plants (Basel, Switzerland) · 2022Article
- Multi-trait genomic prediction using in-season physiological parameters increases prediction accuracy of complex traits in US wheat.BMC genomics · 2022Article
- Cotton Breeding in Australia: Meeting the Challenges of the 21st Century.Frontiers in plant science · 2022Review
- Population-tailored mock genome enables genomic studies in species without a reference genome.Molecular genetics and genomics : MGG · 2022Article
- Resequencing worldwide spinach germplasm for identification of field resistance QTLs to downy mildew and assessment of genomic selection methods.Horticulture research · 2022Article
- Mapping and selection of downy mildew resistance in spinach cv. whale by low coverage whole genome sequencing.Frontiers in plant science · 2022Article
- Leveraging a graft collection to develop metabolome-based trait prediction for the selection of tomato rootstocks with enhanced salt tolerance.Horticulture research · 2022Article
- Assessing combining abilities, genomic data, and genotype × environment interactions to predict hybrid grain sorghum performance.The plant genome · 2021Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of genomic selection (GS) has stimulated a new way to utilize molecular markers in breeding for complex traits in the absence of phenotypic data. GS can potentially decrease breeding cycle by selecting the progeny in the early stages. The objective of this study was to experimentally evaluate the potential value of genomic selection in Upland cotton breeding. Six fiber quality traits were obtained in 3 years of replicated field trials in Starkville, MS. Genotyping-by-sequencing-based genotyping was performed using 550 recombinant inbred lines of the multi-parent advanced generation inter-cross population, and 6292 molecular markers were used for the GS analysis. Several methods were compared including genomic BLUP (GBLUP), ridge regression BLUP (rrBLUP), BayesB, Bayesian LASSO, and reproducing kernel hilbert spaces (RKHS). The average heritability (h
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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.