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Characterizing a region on BTA11 affecting β-lactoglobulin content of milk using high-density genotyping and haplotype grouping

BACKGROUND: Milk β-lactoglobulin (β-LG) content is of interest as it is associated with nutritional and manufacturing properties. It is known that milk β-LG content is strongly affected by genetic factors. In cattle, most of the genetic differences are associated with a chromosomal region on BTA11,...

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Detalles Bibliográficos
Autores principales: Bedere, Nicolas, Bovenhuis, Henk
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5320657/
https://www.ncbi.nlm.nih.gov/pubmed/28222684
http://dx.doi.org/10.1186/s12863-017-0483-9
Descripción
Sumario:BACKGROUND: Milk β-lactoglobulin (β-LG) content is of interest as it is associated with nutritional and manufacturing properties. It is known that milk β-LG content is strongly affected by genetic factors. In cattle, most of the genetic differences are associated with a chromosomal region on BTA11, which contains the β-LG gene. The aim of this study was to characterize this region using 777 k SNP data (BovineHDbeadChip) and perform a haplotype-based association study. A statistical approach was developed to build haplotypes that capture the genetic variation associated with this genomic region. RESULTS: The SNP with the most significant effect on β-lactoglobulin content was one of the 2 causal mutations responsible for the β-lactoglobulin protein variants A/B. Haplotypes based on 2 to 5 selected lead SNP were clustered in groups with different effects on β-lactoglobulin content. Four different groups were identified suggesting that β-lactoglobulin variant A and B can be further refined in A(1), A(2), B(1) and B(2). CONCLUSIONS: This study showed that β-lactoglobulin protein variants A/B do not explain all genetic variation associated with the tail part of BTA11 but this region contains more than one mutation with an effect on β-lactoglobulin content. These findings can be used for selection of cows with higher cheese yield, which is desirable for the dairy industry.