Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle

Nayeri, Shadi; Sargolzaei, Mehdi; Abo-Ismail, Mohammed; May, N.; Miller, Stephen; Moore, S. S.; Stothard, Paul

doi:10.1186/s12863-016-0386-1

Cited by 131 publications

(115 citation statements)

References 70 publications

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“…O'Brien et al (2014) showed that r 2 values above 0.3 were required to give sufficient power in genome wide association studies (GWAS). In the current study, r 2 values above 0.2 were achieved at a distance less than 70 kb between adjacent markers, indicating that using BovineSNP50K BeadChip with marker interval 67.8 kb is inconsistent for achieving a high accuracy of genomic breeding values and Recently, high density (HD) chips have been used in GWAS (Mokry et al 2014;O'Brien et al 2014;Nayeri et al 2016) and a marker interval of 5 kb can be obtained from such SNP density provided that r 2 reaches 0.59 in taurine species (O'Brien et al 2014). Consequently, the HD chip could be more appropriate for GWAS than the 50K chip.…”

Section: Resultsmentioning

confidence: 64%

Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle

Salem¹,

Thompson²,

Chen³

et al. 2018

Czech J. Anim. Sci.

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Salem M.M.I., Thompson G., Chen S., Beja-Pereira A., Carvalheira J. (2018): Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle. Czech J. Anim. Sci., 63, 61-69.The objectives of this study were to estimate linkage disequilibrium (LD), describe and scan a haplotype block for the presence of genes that may affect milk production traits in Portuguese Holstein cattle. Totally 526 animals were genotyped using the Illumina BovineSNP50 BeadChip, which contained a total of 52 890 single nucleotide polymorphisms (SNPs). The final set of markers remaining after considering quality control standards consisted of 37 031 SNPs located on 29 autosomes. The LD parameters historical recombinations through allelic association (D') and squared correlation coefficient between locus alleles frequencies ( r 2 ) were estimated and haplotype block analyses were performed using the Haploview software. The averages of D' and r 2 values were 0.628 and 0.122, respectively. The LD value decreased with increasing physical distance. The D' and r 2 values decreased respectively from 0.815 and 0.283 at the distance of 0-30 kb to 0.578 and 0.090 at the distance of 401-500 kb. The identified total number of blocks was 969 and consisted of 4259 SNPs that covered 159.06 Mb (6.24% of the total genome) on 29 autosomes. Several genes inside the haplotype blocks were detected; CSN1S2 gene in haplotype block 51 on BTA 6, IL6 and B4GALT1 genes in haplotype blocks 6 and 33 on BTA 8, IL1B and ID2 genes in haplotype blocks 19 and 29 on BTA 11, and DGAT1 gene in haplotype block 1 on BTA 14. The extension of LD using BovineSNP50 BeadChip did not exceed 500 kb and its parameters r 2 and D' were less than 0.2 and 0.70, respectively, after 70-100 kb. Consequently, the 50K BeadChip would have a poor power in genome wide association studies at distances between adjacent markers lower than 70 kb.

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Section: Resultsmentioning

confidence: 64%

Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle

Salem¹,

Thompson²,

Chen³

et al. 2018

Czech J. Anim. Sci.

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“…For example, a QTL with a major effect on milk yield and composition has been identified on the centromeric end of the chromosome 14, and involves the DGAT1 gene [49]. Figure 2 shows a strong association of SNPs with milk production on chromosome 14 close to the DGAT1 gene in a genome-wide association study done on Canadian Holstein dairy cattle [111]. Similarly, linkage disequilibrium (LD) analysis highlighted a chromosomal region on bovine chromosome 20 harbouring the GHR gene which affects milk yield and composition [2,18,44].…”

Section: Candidate Genes Identified In the Key Tissues Through Associmentioning

confidence: 99%

“…Milk production and fertility traits are polygenic, affected by many genes and variants, each with a small effect on the observed phenotype [111,139]. GWAS studies of different production and fertility traits in dairy cattle have identified shared quantitative regions and candidate genes-regions that appear to influence multiple traits [27,56,111,127].…”

Section: Genomic Regions and Genes Affecting Multiple Traits In Dairymentioning

confidence: 99%

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Tissues, Metabolic Pathways and Genes of Key Importance in Lactating Dairy Cattle

Nayeri

Stothard

2016

Springer Science Reviews

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Milk and dairy products are valuable sources of food for humans. Increased milk yield and changes in milk composition in dairy cows have been achieved through a variety of means including better nutrition, management and genetic selection. This selection can be performed without consideration of the specific genes and genetic variation involved. However, association analysis using dense SNP genotyping panels provides an approach for identifying genomic regions affecting milk production. Coupling physiological and metabolic information with association analysis results can provide greater insight into the specific genetic variants and molecular mechanisms affecting production traits as well as the potential effects of these variants on fertility in dairy cattle. To this end, this review highlights key tissues, metabolic pathways and genes of importance in lactating dairy cattle, particularly early in lactation. Physiological and metabolic adaptations in three key tissues (adipose, mammary gland and liver) are discussed, followed by the important endocrine adaptations during negative energy balance. Key genes mediating metabolic and endocrine adaptations are also highlighted. Finally, genes that account for variation in production traits are presented in relation to the tissues and processes described. Knowledge of the genes and pathways involved will be important for ongoing efforts aimed at finding other genes and variants that contribute to milk production and fertility traits. Also, a better understanding of the molecular basis of these traits may lead to more accurate genomic predictions.

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“…In livestock and companion animals, GWA studies have identified multiple genomic regions for health and disease related traits (Bermingham et al, 2014;Karlsson et al, 2013), fertility related traits (Nayeri et al, 2016;Schneider et al, 2015;Hoglund et al, 2014), production traits (Nayeri et al, 2016;Wolc et al, 2012) among other examples. GWA studies have also led to discovery of causative mutations for several traits in dogs and cattle as reviewed in Goddard and Hayes (2009).…”

Section: Genome-wide Association Studymentioning

confidence: 99%

Genetics of equine insect bite hypersensitivity and genetic diversity in horses

Shrestha¹

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Genetic variation contributing to the phenotypic variation was utilized in this thesis to understand the genetic background of a complex trait IBH, and to understand genetic diversity and relationships between various horse populations.IBH is the most common skin allergic disorder in horses, caused by bites of midges, predominantly Culicoides species. It affects various horse breeds worldwide. With no effective treatment, IBH degrades horse health and causes economic loss. In this thesis, we used genome-wide SNPs to identify regions contributing to genetic variance of IBH susceptibility. We also investigated influence of increased number of horses and dense SNPs on identification of genomic regions associated to IBH susceptibility. Multiple genomic regions with small effects were observed in Studies I-III. Interesting genomic regions in the Icelandic horse population across the studies I and II, was observed on chromosomes 1, 7, 10, 15 and 17. The percentage of the genetic variance explained by top ten windows increased from 3.07% (Study I) to 6.56% (Study II). Novel genomic regions were identified when number of Icelandic horses was increased in Study II. Using dense SNPs on the Exmoor pony population we identified novel genomic regions, on chr 8, associated to IBH susceptibility, though with borderline significance.In Study IV, pre-conceived understanding about evolutionary history of horse populations matched obtained results from investigation of genetic relationships within Dutch warmblood populations (pairwise mean FST ≤ 0.070), and within pony-like populations (pairwise mean FST ≤ 0.078). Horse populations with similar genetic background might share similar genetic components for IBH susceptibility. The Friesian horse population had lowest diversity (mean inbreeding coefficients: fi: 30.4%, fiROH= 22.2%) in Study IV and was genetically distinct (FST ranged from 0.13 to 0.17). This might be a result of a history of several population bottlenecks and selection on a closed breeding scheme. Low diversity in immunity related genes, observed in the Friesian horse population, might have led to increased prevalence of IBH. Similarly, low susceptibility of IBH in a warmblood population, KWPN sport horse population might be due to high genetic diversity ( i f =-6.9%). High genetic diversity in KWPN sport horse population might be a result of an open breeding scheme and interbreeding with other warmblood populations.

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Genome-wide association for milk production and female fertility traits in Canadian dairy Holstein cattle

Cited by 131 publications

References 70 publications

Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle

Linkage disequilibrium and haplotype block structure in Portuguese Holstein cattle

Tissues, Metabolic Pathways and Genes of Key Importance in Lactating Dairy Cattle

Genetics of equine insect bite hypersensitivity and genetic diversity in horses

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