Genome-wide identification of major genes and genomic prediction using high-density and text-mined gene-based SNP panels in Hanwoo (Korean cattle).
PLoS One
; 15(12): e0241848, 2020.
Article
em En
| MEDLINE
| ID: mdl-33264312
ABSTRACT
It was hypothesized that single-nucleotide polymorphisms (SNPs) extracted from text-mined genes could be more tightly related to causal variant for each trait and that differentially weighting of this SNP panel in the GBLUP model could improve the performance of genomic prediction in cattle. Fitting two GRMs constructed by text-mined SNPs and SNPs except text-mined SNPs from 777k SNPs set (exp_777K) as different random effects showed better accuracy than fitting one GRM (Im_777K) for six traits (e.g. backfat thickness +â
0.002, eye muscle area + 0.014, Warner-Bratzler Shear Force of semimembranosus and longissimus dorsi + 0.024 and + 0.068, intramuscular fat content of semimembranosus and longissimus dorsi + 0.008 and +â
0.018). These results can suggest that attempts to incorporate text mining into genomic predictions seem valuable, and further study using text mining can be expected to present the significant results.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Genoma
/
Locos de Características Quantitativas
/
Estudo de Associação Genômica Ampla
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Animals
/
Humans
País/Região como assunto:
Asia
Idioma:
En
Revista:
PLoS One
Assunto da revista:
CIENCIA
/
MEDICINA
Ano de publicação:
2020
Tipo de documento:
Article