Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland

Meredith, B; Kearney, F.; Finlay, Emma K.; Bradley, Daniel G.; Fahey, Alan G.; Berry, D.P.; Lynn, David J.

doi:10.1186/1471-2156-13-21

Cited by 139 publications

(120 citation statements)

References 51 publications

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“…A similar number of associated SNPs was obtained in analogue studies developed by using common GWAS approaches Jiang et al 2010;Mai et al 2010). The distribution of SNPs across the 29 autosomes and their positions was generally in agreement with results reported in literature (Jiang et al 2010;Meredith et al 2012). The number of significant markers detected for each trait seems to reflect the known genetic architecture of traits: a higher number of significant SNPs were found for yield compared to composition traits.…”

Section: Discussionsupporting

confidence: 76%

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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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Section: Discussionsupporting

confidence: 76%

“…Many association studies identified QTLs affecting FY and FP in the centromeric region of BTA14 Jiang et al 2010;Meredith et al 2012). The DGAT1 locus is an enzyme that catalyses the synthesis of diacylglycerols involved in several biological processes (Mai et al 2010).…”

Section: Discussionmentioning

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 reasons for this result are clear; nevertheless, the low variation in FP due to the limited number of genotyped individuals and analyzed markers seems to be the most probable explanation. In Holstein-Friesian cows in Ireland, Meredith et al (2012) identified 370, 370, and 385 SNPs significantly (P < 0.05) associated with MY, FY, and PY, respectively. In buffaloes, Venturini et al (2014) reported that among 15 745 SNPs analyzed, only 1562 revealed significant (P < 0.01) influence and 4742 showed significant (P < 0.05) effect on all the traits studied.…”

Section: Resultsmentioning

confidence: 96%

Association between microsatellite markers and milk production traits in Egyptian buffaloes

Rushdi¹,

Moghaieb²,

Abdel-Shafy³

et al. 2017

CZECH J ANIM SCI

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Rushdi H.E., Moghaieb R.E.A., Abdel-Shafy H., Ibrahim M. A.M. (2017): Association between microsatellite markers and milk production traits in Egyptian buffaloes. Czech J. Anim. Sci, 62, 384-391.The objectives were to evaluate polymorphism in ten microsatellite markers and to demonstrate their association with milk production traits in the Egyptian buffaloes, based on the cross-species transferability of microsatellites from cattle to buffalo. A total of 17 439 daily milk records from the first five lactations were subjected to analyses, in which records from 5 to 290 days in milk were only included. The analysis revealed that eight out of the ten bovine markers analyzed were polymorphic. The means of the number of alleles, effective number of alleles, and fixation index within markers were 4.125, 2.479, and 0.062, respectively. The means of the observed and expected heterozygosity were 0.491 and 0.527 per marker, respectively. The eight polymorphic microsatellites (BM1706, BMS711, BM143, BM415, BM6438, ETH131, BM1443, ETH2) showed significant (P < 0.001) associations with average daily milk yield deviation. Protein percentage was significantly associated with microsatellites BM6438 (P < 0.01) and ETH131 (P < 0.001). Only marker BM415 had a significant (P < 0.05) influence on protein yield. None of the analyzed markers revealed significant effect on fat yield and percentage. The results obtained support future application of the polymorphic microsatellites for detailed studies of the Egyptian buffalo genome.

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“…Genomic selection requires genotypes for all loci so therefore 'missing' genotypes are not acceptable. The existence of missing genotypes for individual animals may, however, not be problematic in some algorithms used in genome-wide association studies, for example, when single SNPs are individually included in a regression model (Meredith et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes

Berry

McParland

Kearney

et al. 2014

Animal

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The objective of this study was to quantify the accuracy of imputing the genotype of parents using information on the genotype of their progeny and a family-based and population-based imputation algorithm. Two separate data sets were used, one containing both dairy and beef animals (n = 3122) with high-density genotypes (735 151 single nucleotide polymorphisms (SNPs)) and the other containing just dairy animals (n = 5489) with medium-density genotypes (51 602 SNPs). Imputation accuracy of three different genotype density panels were evaluated representing low (i.e. 6501 SNPs), medium and high density. The full genotypes of sires with genotyped half-sib progeny were masked and subsequently imputed. Genotyped half-sib progeny group sizes were altered from 4 up to 12 and the impact on imputation accuracy was quantified. Up to 157 and 258 sires were used to test the accuracy of imputation in the dairy plus beef data set and the dairy-only data set, respectively. The efficiency and accuracy of imputation was quantified as the proportion of genotypes that could not be imputed, and as both the genotype concordance rate and allele concordance rate. The median proportion of genotypes per animal that could not be imputed in the imputation process decreased as the number of genotyped half-sib progeny increased; values for the medium-density panel ranged from a median of 0.015 with a half-sib progeny group size of 4 to a median of 0.0014 to 0.0015 with a half-sib progeny group size of 8. The accuracy of imputation across different paternal half-sib progeny group sizes was similar in both data sets. Concordance rates increased considerably as the number of genotyped half-sib progeny increased from four (mean animal allele concordance rate of 0.94 in both data sets for the medium-density genotype panel) to five (mean animal allele concordance rate of 0.96 in both data sets for the medium-density genotype panel) after which it was relatively stable up to a half-sib progeny group size of eight. In the data set with dairy-only animals, sufficient sires with paternal half-sib progeny groups up to 12 were available and the withinanimal mean genotype concordance rates continued to increase up to this group size. The accuracy of imputation was worst for the low-density genotypes, especially with smaller half-sib progeny group sizes but the difference in imputation accuracy between density panels diminished as progeny group size increased; the difference between high and medium-density genotype panels was relatively small across all half-sib progeny group sizes. Where biological material or genotypes are not available on individual animals, at least five progeny can be genotyped (on either a medium or high-density genotyping platform) and the parental alleles imputed with, on average, ⩾96% accuracy.

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Genome-wide associations for milk production and somatic cell score in Holstein-Friesian cattle in Ireland

Cited by 139 publications

References 51 publications

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

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

Association between microsatellite markers and milk production traits in Egyptian buffaloes

Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes

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