Mastitis, the most common and expensive disease in dairy cows, implies significant losses in the dairy industry worldwide. Many efforts have been made to improve genetic mastitis resistance in dairy populations, but low heritability of this trait made this process not as effective as desired. The purpose of this study was to identify genomic regions explaining genetic variation of somatic cell count using copy number variations (CNVs) as markers in the Holstein population, genotyped with the Illumina BovineHD BeadChip. We found 24 and 47 copy number variation regions significantly associated with estimated breeding values for somatic cell score (SCS_EBVs) using SVS 8.3.1 and PennCNV-CNVRuler software, respectively. The association analysis performed with these two software allowed the identification of 18 candidate genes (TERT, NOTCH1, SLC6A3, CLPTM1L, PPARα, BCL-2, ABO, VAV2, CACNA1S, TRAF2, RELA, ELF3, DBH, CDK5, NF2, FASN, EWSR1 and MAP3K11) that result classified in the same functional cluster. These genes are also part of two gene networks, whose genes share the 'stress', 'cell death', 'inflammation' and 'immune response' GO terms. Combining CNV detection/association analysis based on two different algorithms helps towards a more complete identification of genes linked to phenotypic variation of the somatic cell count.
Genome-wide association study for milk somatic cell score in holstein cattle using copy number variation as markers / M. Durán Aguilar, S.I. Roman Ponce, F.J. Ruiz López, E. González Padilla, C.G. Vásquez Peláez, A. Bagnato, M.G. Strillacci. - In: JOURNAL OF ANIMAL BREEDING AND GENETICS. - ISSN 0931-2668. - 134:1(2017), pp. 49-59.
Genome-wide association study for milk somatic cell score in holstein cattle using copy number variation as markers
S.I. Roman Ponce;A. Bagnato;M.G. Strillacci
2017
Abstract
Mastitis, the most common and expensive disease in dairy cows, implies significant losses in the dairy industry worldwide. Many efforts have been made to improve genetic mastitis resistance in dairy populations, but low heritability of this trait made this process not as effective as desired. The purpose of this study was to identify genomic regions explaining genetic variation of somatic cell count using copy number variations (CNVs) as markers in the Holstein population, genotyped with the Illumina BovineHD BeadChip. We found 24 and 47 copy number variation regions significantly associated with estimated breeding values for somatic cell score (SCS_EBVs) using SVS 8.3.1 and PennCNV-CNVRuler software, respectively. The association analysis performed with these two software allowed the identification of 18 candidate genes (TERT, NOTCH1, SLC6A3, CLPTM1L, PPARα, BCL-2, ABO, VAV2, CACNA1S, TRAF2, RELA, ELF3, DBH, CDK5, NF2, FASN, EWSR1 and MAP3K11) that result classified in the same functional cluster. These genes are also part of two gene networks, whose genes share the 'stress', 'cell death', 'inflammation' and 'immune response' GO terms. Combining CNV detection/association analysis based on two different algorithms helps towards a more complete identification of genes linked to phenotypic variation of the somatic cell count.File | Dimensione | Formato | |
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