A genome‐wide scan for signatures of recent selection in Holstein cattle

Qanbari, Saber; Pimentel, E.C.G.; Tetens, Jens; Thaller, Georg; Lichtner, Peter; Sharifi, AR; Simianer, Henner

doi:10.1111/j.1365-2052.2009.02016.x

Cited by 157 publications

(202 citation statements)

References 65 publications

(117 reference statements)

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“…Within the remaining 38 intervals with a high proportion of Chief alleles in the current population of Australian Holsteins, we detected two genes, ARL4 and BMP4 (Fig. 2 A and B), that had been identified previously as candidate genes for QTL (21,22). Other functional candidates are given in Table 2.…”

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confidence: 74%

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle

Larkin

Daetwyler²,

Hernandez

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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Using a combination of whole-genome resequencing and highdensity genotyping arrays, genome-wide haplotypes were reconstructed for two of the most important bulls in the history of the dairy cattle industry, Pawnee Farm Arlinda Chief ("Chief") and his son Walkway Chief Mark ("Mark"), each accounting for ∼7% of all current genomes. We aligned 20.5 Gbp (∼7.3× coverage) and 37.9 Gbp (∼13.5× coverage) of the Chief and Mark genomic sequences, respectively. More than 1.3 million high-quality SNPs were detected in Chief and Mark sequences. The genome-wide haplotypes inherited by Mark from Chief were reconstructed using ∼1 million informative SNPs. Comparison of a set of 15,826 SNPs that overlapped in the sequence-based and BovineSNP50 SNPs showed the accuracy of the sequence-based haplotype reconstruction to be as high as 97%. By using the BovineSNP50 genotypes, the frequencies of Chief alleles on his two haplotypes then were determined in 1,149 of his descendants, and the distribution was compared with the frequencies that would be expected assuming no selection. We identified 49 chromosomal segments in which Chief alleles showed strong evidence of selection. Candidate polymorphisms for traits that have been under selection in the dairy cattle population then were identified by referencing Chief's DNA sequence within these selected chromosome blocks. Eleven candidate genes were identified with functions related to milk-production, fertility, and diseaseresistance traits. These data demonstrate that haplotype reconstruction of an ancestral proband by whole-genome resequencing in combination with high-density SNP genotyping of descendants can be used for rapid, genome-wide identification of the ancestor's alleles that have been subjected to artificial selection.

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mentioning

confidence: 74%

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle

Larkin

Daetwyler²,

Hernandez

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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“…Therefore, the long runs of homozygosity observed in these regions are unlikely to be due to low recombination rates, but rather reflect selection pressures. Qanbari et al (2010) used SNPs of the Illumina Bovine SNP50 BeadChip and the REHH test to evaluate LD and the decay of haplotype homozygosity in some candidate regions harboring major genes related to milk production and quality in Holstein-Friesian cattle. In general, the authors found high values of LD and slow decay of haplotype homozygosity, indicating the validity of the approach for the identification of selection signatures.…”

Section: Resultsmentioning

confidence: 99%

“…The positive correlation of 0.34 between the two approaches demonstrated that the LRH test was able to detect haplotypes that suffered significant and recent changes in their frequency, indicating signatures of selection. Using EHH statistics to identify genome-wide selection signatures in Holstein-Friesian cattle, Qanbari et al (2010) found 161 regions (P < 0.01) that showed signs of recent positive selection. The larger number of regions indicative of positive selection identified by these authors, who used an SNP chip of the same density and the same significance criteria for the REHH test as in the present study, suggests more diverse (for different economically important traits) and intense selection in dairy cattle when compared with Quarter Horse racing, one of the most recently domesticated large animal species (Aberle and Distl, 2004).…”

Section: Resultsmentioning

confidence: 99%

“…It was specified that each core region should contain a minimum of 3 and a maximum of 20 SNPs. According to Qanbari et al (2010), core regions are defined as regions of interest in the genome characterized by strong LD between SNPs and that involve a set of core haplotypes. The EHH test was applied at a distance of 1 cm on both sides of the core region and to determine the significance of REHH values, that is, EHH values corrected for each ECA, the Sweep 1.1 program divides the haplotypes into 20 classes of frequency and compares the REHH value for each haplotype with other equally frequent haplotypes.…”

Section: Methodsmentioning

confidence: 99%

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Prospection of genomic regions divergently selected in racing line of Quarter Horses in relation to cutting line

Meira

Curi

Farah

et al. 2014

Animal

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Selection of Quarter Horses for different purposes has led to the formation of lines, including racing and cutting horses. The objective of this study was to identify genomic regions divergently selected in racing line of Quarter Horses in relation to cutting line applying relative extended haplotype homozygosity (REHH) analysis, an extension of extended haplotype homozygosity (EHH) analysis, and the fixation index ( F ST ) statistic. A total of 188 horses of both sexes, born between 1985 and 2009 and registered at the Brazilian Association of Quarter Horse Breeders, including 120 of the racing line and 68 of the cutting line, were genotyped using single nucleotide polymorphism arrays. On the basis of 27 genomic regions identified as selection signatures by REHH and F ST statistics, functional annotations of genes were made in order to identify those that could have been important during formation of the racing line and that could be used subsequently for the development of selection tools. Genes involved in muscle growth (n = 8), skeletal growth (n = 10), muscle energy metabolism (n = 15), cardiovascular system (n = 14) and nervous system (n = 23) were identified, including the FKTN, INSR, GYS1, CLCN1, MYLK, SYK, ANG, CNTFR and HTR2B.

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“…in Linkage Disequilibrium; LD) with an unknown causal variant and, in consequence, the study of such markers in a particular region of the genome can highlight the presence of polymorphisms influencing traits or diseases. In cattle breeds, the detection of such genetic differences is particularly interesting due to the strong artificial selection they have been subjected over the last 60 years (Qanbari et al 2010). Many genome-wide association studies (GWAS) identified associations between markers and productive or functional traits in dairy cattle breeds .…”

Section: Introductionmentioning

confidence: 99%

Maximum difference analysis: a new empirical method for genome-wide association studies

Cellesi

Dimauro

Sorbolini

et al. 2016

Italian Journal of Animal Science

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The availability of high-density single nucleotide polymorphism (SNPs) panels for humans and, recently, for several livestock species has given a great impulse to genome-wide association studies towards the identification of genes associated with complex traits and diseases. The frequentist and the Bayesian approach are commonly used to investigate marker associations with traits of interest. Briefly, the former is the most widely used method, being intuitive and easily to apply, whereas the latter requires deeper statistical knowledge, but has the advantage to include prior information to obtain a posterior probability of association. Both methods, however, require parameters or distributions to be set a priori by the researcher. In this work, we suggest a new empirical method for genome-wide studies (GWAS), which verifies marker-trait associations using the bootstrap resampling and Chebyshev's inequality. This method, called Maximum Difference Analysis (MDA), was tested on a real dataset of 2093 Italian Holstein bulls with the objective of finding associations between SNPs and milk, fat and protein yield and fat and protein percentage. Results of the MDA method were compared with those obtained to a genome-wide association analysis performed using the R package GenABEL. In addition, we assessed the bovine annotated genes related to the traits under study. The MDA method was able to locate known important loci for milk productive traits, such as the DGAT1, PRLR, GHR and SCD. Moreover, some new putative candidate genes were detected. The python script of MDA procedure is available at www.animalbreeding.uniss.it. ARTICLE HISTORY

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A genome‐wide scan for signatures of recent selection in Holstein cattle

Cited by 157 publications

References 65 publications

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle

Whole-genome resequencing of two elite sires for the detection of haplotypes under selection in dairy cattle

Prospection of genomic regions divergently selected in racing line of Quarter Horses in relation to cutting line

Maximum difference analysis: a new empirical method for genome-wide association studies

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