1,721,065 research outputs found

    Genomic assessment of reproduction traits in Holstein dairy cattle across 3 lactations using additive genetic models and post hoc random forest analysis

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    http://dx.doi.org/10.13039/501100003385 Georg-August-Universität Göttingenhttp://dx.doi.org/10.13039/501100001659 Deutsche Forschungsgemeinschaf

    Evaluating the most suitable nonlinear growth model for turbot (Scophthalmus maximus) in aquaculture 2 (weight application): Multi-criteria model selection and growth prediction

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    Seeking the most suitable model to describe the growth of turbot, we analysed growth data of two different turbot (Scophthalmus maximus) strains reared communally in a recirculating aquaculture system. We fitted 10 different nonlinear growth models to individual weight gain data (n = 2,010) during the grow‐out phase. Analyses were carried out for each strain, for sexes within strains and for a pooled data set containing both strains and sexes. To assess the model performance, three different criteria are used. Further, a growth‐simulation was performed to evaluate the shape of the generated curve. This way we could assess the capability of the models to predict future growth. The 3‐parametric Gompertz model achieved the best fit in 42.9% of all cases tested and the lowest Bayesian information criterion in 100% of cases. The model produced realistically shaped curves and asymptotic values matching the biological attributes of the species. In contrast, 5‐parametric functions projected unrealistically shaped curves and predicted improbable mature sizes. Our results show that increasing number of parameters do not lead to increasing goodness of fit, but tend to result in overfitting, and demonstrate the advantages of the 3‐parametric Gompertz model for describing the growth of turbot

    Genomic dominance variance analysis of health and milk production traits in German Holstein cattle

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    Genomic analyses commonly explore the additive genetic variance of traits. The non-additive variance, however, is usually small but often significant in dairy cattle. This study aimed at dissecting the genetic variance of eight health traits that recently entered the total merit index in Germany and the somatic cell score (SCS), as well as four milk production traits by analysing additive and dominance variance components. The heritabilities were low for all health traits (between 0.033 for mastitis and 0.099 for SCS), and moderate for the milk production traits (between 0.261 for milk energy yield and 0.351 for milk yield). For all traits, the contribution of dominance variance to the phenotypic variance was low, varying between 0.018 for ovarian cysts and 0.078 for milk yield. Inbreeding depression, inferred from the SNP-based observed homozygosity, was significant only for the milk production traits. The contribution of dominance variance to the genetic variance was larger for the health traits, ranging from 0.233 for ovarian cysts to 0.551 for mastitis, encouraging further studies that aim at discovering QTLs based on their additive and dominance effects.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/50110000165

    A genomic assessment of the correlation between milk production traits and claw and udder health traits in Holstein dairy cattle

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    ABSTRACT: Claw diseases and mastitis represent the most important disease traits in dairy cattle with increasing incidences and a frequently mentioned connection to milk yield. Yet, many studies aimed to detect the genetic background of both trait complexes via fine-mapping of quantitative trait loci. However, little is known about genomic regions that simultaneously affect milk production and disease traits. For this purpose, several tools to detect local genetic correlations have been developed. In this study, we attempted a detailed analysis of milk production and disease traits as well as their interrelationship using a sample of 34,497 50K genotyped German Holstein cows with milk production and claw and udder disease traits records. We performed a pedigree-based quantitative genetic analysis to estimate heritabilities and genetic correlations. Additionally, we generated GWAS summary statistics, paying special attention to genomic inflation, and used these data to identify shared genomic regions, which affect various trait combinations. The heritability on the liability scale of the disease traits was low, between 0.02 for laminitis and 0.19 for interdigital hyperplasia. The heritabilities for milk production traits were higher (between 0.27 for milk energy yield and 0.48 for fat-protein ratio). Global genetic correlations indicate the shared genetic effect between milk production and disease traits on a whole genome level. Most of these estimates were not significantly different from zero, only mastitis showed a positive one to milk (0.18) and milk energy yield (0.13), as well as a negative one to fat-protein ratio (−0.07). The genomic analysis revealed significant SNPs for milk production traits that were enriched on Bos taurus autosome 5, 6, and 14. For digital dermatitis, we found significant hits, predominantly on Bos taurus autosome 5, 10, 22, and 23, whereas we did not find significantly trait-associated SNPs for the other disease traits. Our results confirm the known genetic background of disease and milk production traits. We further detected 13 regions that harbor strong concordant effects on a trait combination of milk production and disease traits. This detailed investigation of genetic correlations reveals additional knowledge about the localization of regions with shared genetic effects on these trait complexes, which in turn enables a better understanding of the underlying biological pathways and putatively the utilization for a more precise design of breeding schemes

    GWAS Hits for Bilateral Convergent Strabismus with Exophthalmos in Holstein Cattle Using Imputed Sequence Level Genotypes

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    Bilateral convergent strabismus with exophthalmos (BCSE) is a malformation of the eyes and is recognized as a mild but progressive disorder that affects cattle in the first two years of life. This most likely inherited disorder is rarely described in cattle resembling autosomal dominantly inherited forms of human progressive external ophthalmoplegia (PEO). In German Braunvieh cattle, two linked genome regions were found that could be responsible for the development and/or progression of BCSE. The goal of this study was to phenotypically characterize BCSE in Holstein cattle from Germany and Switzerland as well as to identify associated genome regions by GWAS. The clinicopathological phenotype of 52 BCSE-affected Holstein cattle was in accordance with the phenotype described in German Braunvieh cattle, but in addition, signs of degeneration and cellular infiltration in the eye muscles were found. By using imputed sequence level genotype data, three genome-wide significant GWAS hits were revealed on different chromosomes that were not detected by initial GWAS based on high density SNP array data highlighting the usefulness of this approach for mapping studies. The associated genome regions include the ABCC4 gene as well as markers adjacent to the NCOR2 and DNAJC3 genes all illustrating possible functional candidate genes. Our results challenge a monogenic mode of inheritance and indicate a more complex inheritance of BCSE in Holstein cattle. Furthermore, in comparison to previous results from German Braunvieh cattle, it illustrates an obvious genetic heterogeneity causing BSCE in cattle. Subsequent whole genome sequencing (WGS)-based analyses might elucidate pathogenic variants in the future

    Structural variants and tandem repeats in the founder individuals of four F(2) pig crosses and implications to F(2) GWAS results

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    BACKGROUND: Structural variants and tandem repeats are relevant sources of genomic variation that are not routinely analyzed in genome wide association studies mainly due to challenging identification and genotyping. Here, we profiled these variants via state-of-the-art strategies in the founder animals of four F(2) pig crosses using whole-genome sequence data (20x coverage). The variants were compared at a founder level with the commonly screened SNPs and small indels. At the F(2) level, we carried out an association study using imputed structural variants and tandem repeats with four growth and carcass traits followed by a comparison with a previously conducted SNPs and small indels based association study. RESULTS: A total of 13,201 high confidence structural variants and 103,730 polymorphic tandem repeats (with a repeat length of 2-20 bp) were profiled in the founders. We observed a moderate to high (r from 0.48 to 0.57) level of co-localization between SNPs or small indels and structural variants or tandem repeats. In the association step 56.56% of the significant variants were not in high LD with significantly associated SNPs and small indels identified for the same traits in the earlier study and thus presumably not tagged in case of a standard association study. For the four growth and carcass traits investigated, many of the already proposed candidate genes in our previous studies were confirmed and additional ones were identified. Interestingly, a common pattern on how structural variants or tandem repeats regulate the phenotypic traits emerged. Many of the significant variants were embedded or nearby long non-coding RNAs drawing attention to their functional importance. Through which specific mechanisms the identified long non-coding RNAs and their associated structural variants or tandem repeats contribute to quantitative trait variation will need further investigation. CONCLUSIONS: The current study provides insights into the characteristics of structural variants and tandem repeats and their role in association studies. A systematic incorporation of these variants into genome wide association studies is advised. While not of immediate interest for genomic prediction purposes, this will be particularly beneficial for elucidating biological mechanisms driving the complex trait variation. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08716-0
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