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A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data.

ABSTRACT: Genomic imprinting is a phenomenon that arises when the expression of genes depends on the parental origin of alleles. Epigenetic mechanisms may induce the full or partial suppression of maternal or paternal alleles, thereby leading to different types of imprinting. However, imprinting effects have received little consideration in animal breeding programmes, although their relevance to some agricultural important traits has been demonstrated. A recently proposed model (imprinting model) with two path-of-transmission (male and female)-specific breeding values for each animal accounts for all types of imprinting simultaneously (paternal, maternal, full and partial). Imprinting effects (or more generally: parent-of-origin effects (POE)) are determined by taking the difference between the two genetic effects in each animal. However, the computation of their prediction error variance (PEV) is laborious; thus, we propose a new model that is equivalent to the aforementioned imprinting model, which facilitates the direct estimation of imprinting effects instead of taking the differences and the PEV is readily obtained. We applied the new model to slaughterhouse data for Brown Swiss cattle, among which imprinting has never been investigated previously. Data were available for up to 173 051 fattening bulls, where the pedigrees contained up to 428 710 animals representing the entire Brown Swiss population of Austria and Germany. The traits analysed comprised the net BW gain, fat score, EUROP class and killing out percentage. The analysis demonstrated that the net BW gain, fat score and EUROP class were influenced significantly by POE. After estimating the POE, the new model yielded estimates with reliabilities ranging between 0.4 and 0.9. On average, the imprinting variances accounted for 9.6% of the total genetic variance, where the maternal gamete was the main contributor. Moreover, our results agreed well with those obtained using linear models when the EUROP class and fat score were treated as categorical traits by applying a GLMM with a logit link function.

SUBMITTER: Blunk I

PROVIDER: S-EPMC5488768 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data.

Blunk I I Mayer M M Hamann H H Reinsch N N

Animal : an international journal of animal bioscience 20161206 7

Genomic imprinting is a phenomenon that arises when the expression of genes depends on the parental origin of alleles. Epigenetic mechanisms may induce the full or partial suppression of maternal or paternal alleles, thereby leading to different types of imprinting. However, imprinting effects have received little consideration in animal breeding programmes, although their relevance to some agricultural important traits has been demonstrated. A recently proposed model (imprinting model) with two ...[more]

PMID: 27919305

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Project description:BACKGROUND:Little is known about the genetic architecture of economically important traits in Brown Swiss cattle because only few genome-wide association studies (GWAS) have been carried out in this breed. Moreover, most GWAS have been performed for single traits, thus not providing detailed insights into potentially existing pleiotropic effects of trait-associated loci. RESULTS:To compile a comprehensive catalogue of large-effect quantitative trait loci (QTL) segregating in Brown Swiss cattle, we carried out association tests between partially imputed genotypes at 598,016 SNPs and daughter-derived phenotypes for more than 50 economically important traits, including milk production, growth and carcass quality, body conformation, reproduction and calving traits in 4578 artificial insemination bulls from two cohorts of Brown Swiss cattle (Austrian-German and Swiss populations). Across-cohort multi-trait meta-analyses of the results from the single-trait GWAS revealed 25 quantitative trait loci (QTL; P?<?8.36?×?10-?8) for economically relevant traits on 17 Bos taurus autosomes (BTA). Evidence of pleiotropy was detected at five QTL located on BTA5, 6, 17, 21 and 25. Of these, two QTL at BTA6:90,486,780 and BTA25:1,455,150 affect a diverse range of economically important traits, including traits related to body conformation, calving, longevity and milking speed. Furthermore, the QTL at BTA6:90,486,780 seems to be a target of ongoing selection as evidenced by an integrated haplotype score of 2.49 and significant changes in allele frequency over the past 25?years, whereas either no or only weak evidence of selection was detected at all other QTL. CONCLUSIONS:Our findings provide a comprehensive overview of QTL segregating in Brown Swiss cattle. Detected QTL explain between 2 and 10% of the variation in the estimated breeding values and thus may be considered as the most important QTL segregating in the Brown Swiss cattle breed. Multi-trait association testing boosts the power to detect pleiotropic QTL and assesses the full spectrum of phenotypes that are affected by trait-associated variants.

Project description:BACKGROUND:Calving difficulty or dystocia has a great economic impact in the US dairy industry. Reported risk factors associated with calving difficulty are feto-pelvic disproportion, gestation length and conformation. Different dairy cattle breeds have different incidence of calving difficulty, with Holstein having the highest dystocia rates and Jersey the lowest. Genomic selection becomes important especially for complex traits with low heritability, where the accuracy of conventional selection is lower. However, for complex traits where a large number of genes influence the phenotype, genome-wide association studies showed limitations. Biological networks could overcome some of these limitations and better capture the genetic architecture of complex traits. In this paper, we characterize Holstein, Brown Swiss and Jersey breed-specific dystocia networks and employ them in genomic predictions. RESULTS:Marker association analysis identified single nucleotide polymorphisms explaining the largest average proportion of genetic variance on BTA18 in Holstein, BTA25 in Brown Swiss, and BTA15 in Jersey. Gene networks derived from the genome-wide association included 1272 genes in Holstein, 1454 genes in Brown Swiss, and 1455 genes in Jersey. Furthermore, 256 genes in Holstein network, 275 genes in the Brown Swiss network, and 253 genes in the Jersey network were within previously reported dystocia quantitative trait loci. The across-breed network included 80 genes, with 9 genes being within previously reported dystocia quantitative trait loci. The gene-gene interactions in this network differed in the different breeds. Gene ontology enrichment analysis of genes in the networks showed Regulation of ARF GTPase was very significant (FDR ≤ 0.0098) on Holstein. Neuron morphogenesis and differentiation was the term most enriched (FDR ≤ 0.0539) on the across-breed network. Genomic prediction models enriched with network-derived relationship matrices did not outperform regular GBLUP models. CONCLUSIONS:Regions identified in the genome were in the proximity of previously described quantitative trait loci that would most likely affect calving difficulty by altering the feto-pelvic proportion. Inclusion of identified networks did not increase prediction accuracy. The approach used in this paper could be extended to any instance with asymmetric distribution of phenotypes, for example, resistance to disease data.

Project description:BackgroundThe genome-wide association study (GWAS) is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program.ResultGWASs were performed using 50?k SNP chip data and deregressed estimated breeding values (DEBVs) for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY), fat yield (FY), protein yield (PY), lactating cow's ability to recycle after calving (CRC), angularity (ANG), body depth (BDE), stature (STA), milk somatic cell score (SCS) and milk speed (MSP). Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations.ConclusionsOur study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other populations and molecular dissection to explore the potential economic impact and the genetic mechanisms underlying these production traits in cattle.

Project description:BackgroundMilkability is a complex trait that is characterized by milk flow traits including average milk flow rate, maximum milk flow rate and total milking time. Milkability has long been recognized as an economically important trait that can be improved through selection. By improving milkability, management costs of milking decrease through reduced labor and improved efficiency of the automatic milking system, which has been identified as an important factor affecting net profit. The objective of this study was to identify markers associated with electronically measured milk flow traits, in the Italian Brown Swiss population that could potentially improve selection based on genomic predictions.ResultsSires (n = 1351) of cows with milk flow information were genotyped for 33,074 single nucleotide polymorphism (SNP) markers distributed across 29 Bos taurus autosomes (BTA). Among the six milk flow traits collected, ascending time, time of plateau, descending time, total milking time, maximum milk flow and average milk flow, there were 6,929 (time of plateau) to 14,585 (maximum milk flow) significant SNP markers identified for each trait across all BTA. Unique regions were found for each of the 6 traits providing evidence that each individual milk flow trait offers distinct genetic information about milk flow. This study was also successful in identifying functional processes and genes associated with SNPs that influences milk flow.ConclusionsIn addition to verifying the presence of previously identified milking speed quantitative trait loci (QTL) within the Italian Brown Swiss population, this study revealed a number of genomic regions associated with milk flow traits that have never been reported as milking speed QTL. While several of these regions were not associated with a known gene or QTL, a number of regions were associated with QTL that have been formerly reported as regions associated with somatic cell count, somatic cell score and udder morphometrics. This provides further evidence of the complexity of milk flow traits and the underlying relationship it has with other economically important traits for dairy cattle. Improved understanding of the overall milking pattern will aid in identification of cows with lower management costs and improved udder health.

Project description:The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs.We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle.The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants.

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A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data.

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A new model for parent-of-origin effect analyses applied to Brown Swiss cattle slaughterhouse data.

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