ArticleGenetics2013
Genetic mapping and genomic selection using recombination breakpoint data.
Article in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Reversible jumps for the joint modeling of the dimension of pseudo-functional models in chromosomal windows in genome-wide selection.BMC genomics · 2026Article
- Article
- Genome-wide association study and genomic selection of flax powdery mildew in Xinjiang Province.Frontiers in plant science · 2024Article
- A genome-wide association study and genomic prediction forFrontiers in plant science · 2023Article
- Digitalizing breeding in plants: A new trend of next-generation breeding based on genomic prediction.Frontiers in plant science · 2023Review
- Genetic Dissection of Phosphorus Use Efficiency and Genotype-by-Environment Interaction in Maize.International journal of molecular sciences · 2022Article
- Uncontrolled transposition following RNAi loss causes hypermutation and antifungal drug resistance in clinical isolates of Cryptococcus neoformans.Nature microbiology · 2022Article
- PIP-SNP: a pipeline for processing SNP data featured as linkage disequilibrium bin mapping, genotype imputing and marker synthesizing.NAR genomics and bioinformatics · 2021Article
- Pleiotropy and epistasis within and between signaling pathways defines the genetic architecture of fungal virulence.PLoS genetics · 2021Article
- Accelerating Tomato Breeding by Exploiting Genomic Selection Approaches.Plants (Basel, Switzerland) · 2020Review
- Current status of genomic evaluation.Journal of animal science · 2020Review
- Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.G3 (Bethesda, Md.) · 2020Article
- Genome-wide association studies using binned genotypes.Heredity · 2020Article
- Identification of Quantitative Trait Loci for Component Traits of Flowering Capacity Across Temperature inG3 (Bethesda, Md.) · 2019Article
- A Gaussian process model and Bayesian variable selection for mapping function-valued quantitative traits with incomplete phenotypic data.Bioinformatics (Oxford, England) · 2019Article
- Functional models in genome-wide selection.PloS one · 2019Article
- Evaluation of GBLUP, BayesB and elastic net for genomic prediction in Chinese Simmental beef cattle.PloS one · 2019Article
- Recursive Algorithms for Modeling Genomic Ancestral Origins in a Fixed Pedigree.G3 (Bethesda, Md.) · 2018Article
- Controlling the Overfitting of Heritability in Genomic Selection through Cross Validation.Scientific reports · 2017Article
- Prediction and association mapping of agronomic traits in maize using multiple omic data.Heredity · 2017Article
Corrections and comments
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Authors and funding
1 author.
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No grant is acknowledged in the PubMed record.
Abstract
The correct models for quantitative trait locus mapping are the ones that simultaneously include all significant genetic effects. Such models are difficult to handle for high marker density. Improving statistical methods for high-dimensional data appears to have reached a plateau. Alternative approaches must be explored to break the bottleneck of genomic data analysis. The fact that all markers are located in a few chromosomes of the genome leads to linkage disequilibrium among markers. This suggests that dimension reduction can also be achieved through data manipulation. High-density markers are used to infer recombination breakpoints, which then facilitate construction of bins. The bins are treated as new synthetic markers. The number of bins is always a manageable number, on the order of a few thousand. Using the bin data of a recombinant inbred line population of rice, we demonstrated genetic mapping, using all bins in a simultaneous manner. To facilitate genomic selection, we developed a method to create user-defined (artificial) bins, in which breakpoints are allowed within bins. Using eight traits of rice, we showed that artificial bin data analysis often improves the predictability compared with natural bin data analysis. Of the eight traits, three showed high predictability, two had intermediate predictability, and two had low predictability. A binary trait with a known gene had predictability near perfect. Genetic mapping using bin data points to a new direction of genomic data analysis.
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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.