ArticleFrontiers in genetics2020
Incorporating Genome Annotation Into Genomic Prediction for Carcass Traits in Chinese Simmental Beef Cattle.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Genomic Selection for Economic Traits in Inner Mongolia Cashmere Goats by Integrating GWAS Prior Information.Veterinary sciences · 2025Article
- Integrating multi-layered biological priors to improve genomic prediction accuracy in beef cattle.Biology direct · 2024Article
- Accuracy of Genomic Predictions Cross Populations with Different Linkage Disequilibrium Patterns.Genes · 2024Article
- Article
- Genomic prediction based on preselected single-nucleotide polymorphisms from genome-wide association study and imputed whole-genome sequence data annotation for growth traits in Duroc pigs.Evolutionary applications · 2024Article
- Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle.Foods (Basel, Switzerland) · 2023Article
- Expanding the application of haplotype-based genomic predictions to the wild: A case of antibody response against Teladorsagia circumcincta in Soay sheep.BMC genomics · 2023Article
- SNP- and haplotype-based single-step genomic predictions for body weight, wool, and reproductive traits in North American Rambouillet sheep.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2023Article
- Genomic prediction of carcass traits using different haplotype block partitioning methods in beef cattle.Evolutionary applications · 2022Article
- Integrative analyses of genomic and metabolomic data reveal genetic mechanisms associated with carcass merit traits in beef cattle.Scientific reports · 2022Article
- Transcriptome Analysis of Bovine Rumen Tissue in Three Developmental Stages.Frontiers in genetics · 2022Article
- Incorporating Omics Data in Genomic Prediction.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Runs of homozygosity analysis reveals consensus homozygous regions affecting production traits in Chinese Simmental beef cattle.BMC genomics · 2021Article
- Validation of the Prediction Accuracy for 13 Traits in Chinese Simmental Beef Cattle Using a Preselected Low-Density SNP Panel.Animals : an open access journal from MDPI · 2021Article
- Single-Trait and Multiple-Trait Genomic Prediction From Multi-Class Bayesian Alphabet Models Using Biological Information.Frontiers in genetics · 2021Article
- Genomic Prediction Using LD-Based Haplotypes Inferred From High-Density Chip and Imputed Sequence Variants in Chinese Simmental Beef Cattle.Frontiers in genetics · 2021Article
- A Comprehensive Comparison of Haplotype-Based Single-Step Genomic Predictions in Livestock Populations With Different Genetic Diversity Levels: A Simulation Study.Frontiers in genetics · 2021Article
- Genomic Prediction Based on SNP Functional Annotation Using Imputed Whole-Genome Sequence Data in Korean Hanwoo Cattle.Frontiers in genetics · 2020Article
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12 authors.
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Abstract
Various methods have been proposed for genomic prediction (GP) in livestock. These methods have mainly focused on statistical considerations and did not include genome annotation information. In this study, to improve the predictive performance of carcass traits in Chinese Simmental beef cattle, we incorporated the genome annotation information into GP. Single nucleotide polymorphisms (SNPs) were annotated to five genomic classes: intergenic, gene, exon, protein coding sequences, and 3'/5' untranslated region. Haploblocks were constructed for all markers and these five genomic classes by defining a biologically functional unit, and haplotype effects were modeled in both numerical dosage and categorical coding strategies. The first-order epistatic effects among SNPs and haplotypes were modeled using a categorical epistasis model. For all makers, the extension from the SNP-based model to a haplotype-based model improved the accuracy by 5.4-9.8% for carcass weight (CW), live weight (LW), and striploin (SI). For the five genomic classes using the haplotype-based prediction model, the incorporation of gene class information into the model improved the accuracies by an average of 1.4, 2.1, and 1.3% for CW, LW, and SI, respectively, compared with their corresponding results for all markers. Including the first-order epistatic effects into the prediction models improved the accuracies in some traits and genomic classes. Therefore, for traits with moderate-to-high heritability, incorporating genome annotation information of gene class into haplotype-based prediction models could be considered as a promising tool for GP in Chinese Simmental beef cattle, and modeling epistasis in prediction can further increase the accuracy to some degree.
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