scholarly journals Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels

2012 ◽  
Vol 95 (7) ◽  
pp. 4114-4129 ◽  
Author(s):  
M. Erbe ◽  
B.J. Hayes ◽  
L.K. Matukumalli ◽  
S. Goswami ◽  
P.J. Bowman ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Dairy Cattle ◽  
High Density ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Cattle Breeds ◽  
Improving Accuracy ◽  
Genomic Predictions

scholarly journals Selection signatures in two oldest Russian native cattle breeds revealed using high-density single nucleotide polymorphism analysis

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242200
Author(s):  
Natalia Anatolievna Zinovieva ◽  
Arsen Vladimirovich Dotsev ◽  
Alexander Alexandrovich Sermyagin ◽  
Tatiana Evgenievna Deniskova ◽  
Alexandra Sergeevna Abdelmanova ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Candidate Genes ◽  
High Density ◽  
Fixation Index ◽  
Nucleotide Polymorphism ◽  
Selection Signatures ◽  
Single Nucleotide ◽  
Cattle Breeds ◽  
Native Cattle ◽  
Genomic Regions

Native cattle breeds can carry specific signatures of selection reflecting their adaptation to the local environmental conditions and response to the breeding strategy used. In this study, we comprehensively analysed high-density single nucleotide polymorphism (SNP) genotypes to characterise the population structure and detect the selection signatures in Russian native Yaroslavl and Kholmogor dairy cattle breeds, which have been little influenced by introgression with transboundary breeds. Fifty-six samples of pedigree-recorded purebred animals, originating from different breeding farms and representing different sire lines, of the two studied breeds were genotyped using a genome-wide bovine genotyping array (Bovine HD BeadChip). Three statistical analyses—calculation of fixation index (FST) for each SNP for the comparison of the pairs of breeds, hapFLK analysis, and estimation of the runs of homozygosity (ROH) islands shared in more than 50% of animals—were combined for detecting the selection signatures in the genome of the studied cattle breeds. We confirmed nine and six known regions under putative selection in the genomes of Yaroslavl and Kholmogor cattle, respectively; the flanking positions of most of these regions were elucidated. Only two of the selected regions (localised on BTA 14 at 24.4–25.1 Mbp and on BTA 16 at 42.5–43.5 Mb) overlapped in Yaroslavl, Kholmogor and Holstein breeds. In addition, we detected three novel selection sweeps in the genome of Yaroslavl (BTA 4 at 4.74–5.36 Mbp, BTA 15 at 17.80–18.77 Mbp, and BTA 17 at 45.59–45.61 Mbp) and Kholmogor breeds (BTA 12 at 82.40–81.69 Mbp, BTA 15 at 16.04–16.62 Mbp, and BTA 18 at 0.19–1.46 Mbp) by using at least two of the above-mentioned methods. We expanded the list of candidate genes associated with the selected genomic regions and performed their functional annotation. We discussed the possible involvement of the identified candidate genes in artificial selection in connection with the origin and development of the breeds. Our findings on the Yaroslavl and Kholmogor breeds obtained using high-density SNP genotyping and three different statistical methods allowed the detection of novel putative genomic regions and candidate genes that might be under selection. These results might be useful for the sustainable development and conservation of these two oldest Russian native cattle breeds.

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