The impact of single nucleotide polymorphism selection on prediction of genomewide breeding values

The study focuses on the impact of different sets of single nucleotide polymorphisms (SNPs) selected from the available data set on prediction of genomewide breeding values (GBVs) of animals. Correlations between breeding values estimated as additive polygenic effects (EBVs) and GBVs as well as correlations between true breeding values (TBVs) and GBVs are used as major criteria for the comparison of different SNP selection schemes and GBV estimation models

Evaluating markers in selected genes for association with functional longevity of dairy cattle

<p>Abstract</p> <p>Background</p> <p>Longevity expressed as the number of days between birth and death is a trait of great importance for both human and animal populations. In our analysis we use dairy cattle to demonstrate how the association of Single Nucleotide Polymorphisms (SNPs) located within selected genes with longevity can be modeled. Such an approach can be extended to any genotyped population with time to endpoint information available. Our study is focused on selected genes in order to answer the question whether genes, known to be involved into the physiological determination of milk production, also influence individual's survival.</p> <p>Results</p> <p>Generally, the highest risk differences among animals with different genotypes are observed for polymorphisms located within the leptin gene. The polymorphism with a highest effect on functional longevity is LEP-R25C, for which the relative risk of culling for cows with genotype CC is 3.14 times higher than for the heterozygous animals. Apart from LEP-R25C, also FF homozygotes at the LEP-Y7F substitution attribute 3.64 times higher risk of culling than the YY homozygotes and VV homozygotes at LEP-A80V have 1.83 times higher risk of culling than AA homozygotes. Differences in risks between genotypes of polymorphisms within the other genes (the butyrophilin subfamily 1 member A1 gene, BTN1A1; the acyl-CoA:diacylglycerol acyltransferase 1 gene, DGAT1; the leptin receptor gene, LEPR; the ATP-binding cassette sub-family G member 2, ABCG2) are much smaller.</p> <p>Conclusions</p> <p>Our results indicate association between LEP and longevity and are very well supported by results of other studies related to dairy cattle. In view of the growing importance of functional traits in dairy cattle, LEP polymorphisms should be considered as markers supporting selection decisions. Furthermore, since the relationship between both LEP polymorphism and its protein product with longevity in humans is well documented, with our result we were able to demonstrate that livestock with its detailed records of family structure, genetic, and environmental factors as well as extensive trait recording can be a good model organism for research aspects related to humans.</p

Tissue localization of tumor antigen-loaded mouse dendritic cells applied as an anti-tumor vaccine and their influence on immune response.

The recognition, internalization and intracellular processing of antigen are the main functions of dendritic cells (DCs). In the course of these processes, DCs differentiate and acquire the ability to produce cytokines responsible for polarization of the immunological response. Therefore, vaccination with tumor antigen-loaded DCs is one of the most promising approaches to induce tumor-specific immune response. The purpose of this study was to analyze the migratory abilities, from an injection site to tumor-draining lymph nodes (tLN), of DCs applied as an anti-tumor vaccine and their capacity for immune response activation. Mouse DCs of the established JAWS II cell line transduced with EGFP gene or ex vivo bone marrow-isolated DCs (BM-DCs) stained with intravital CFDA dye were loaded with MC38 colon carcinoma tumor lysate (TAg) and then administered peritumorally to MC38 tumor-bearing C57BL/6 mice. On the first, third, fifth and seventh days after injection the tumors, tLNs and spleens were examined. The TAg-loaded DCs migrated more effectively to the tLNs than did the unloaded control DCs; however, the majority of them remained in the tumor vicinity. Immunohistological analysis of the tumor tissues demonstrated that only TAg-loaded DCs activated an immune response. Seven days after DCs vaccine administration, numerous necrotic areas and some apoptotic bodies were observed in the tumor tissue. However, the anti-MC38 tumor cytotoxic activity of spleen and tLN cells from mice treated with both TAg-loaded and unloaded DCs reached a maximum on the fifth day after DC injection. Concluding, TAg-loaded DCs migrated more efficiently to tLNs and were more effective activators of local (but not systemic) cellular immune response than were unloaded DCs. We hypothesize that only the application of TAg-loaded DCs to tumor-bearing mice as an adjuvant supporting chemotherapy may activate a more effective anti-tumor response

Bioinformatic modelling of SARS-CoV-2 pandemic with a focus on country-specific dynamics

Abstract Background One of the seminal events since 2019 has been the outbreak of the SARS-CoV-2 pandemic. Countries have adopted various policies to deal with it, but they also differ in their socio-geographical characteristics and public health care facilities. Our study aimed to investigate differences between epidemiological parameters across countries. Method The analysed data represents SARS-CoV-2 repository provided by the Johns Hopkins University. Separately for each country, we estimated recovery and mortality rates using the SIRD model applied to the first 30, 60, 150, and 300 days of the pandemic. Moreover, a mixture of normal distributions was fitted to the number of confirmed cases and deaths during the first 300 days. The estimates of peaks’ means and variances were used to identify countries with outlying parameters. Results For 300 days Belgium, Cyprus, France, the Netherlands, Serbia, and the UK were classified as outliers by all three outlier detection methods. Yemen was classified as an outlier for each of the four considered timeframes, due to high mortality rates. During the first 300 days of the pandemic, the majority of countries underwent three peaks in the number of confirmed cases, except Australia and Kazakhstan with two peaks. Conclusions Considering recovery and mortality rates we observed heterogeneity between countries. Liechtenstein was the “positive” outlier with low mortality rates and high recovery rates, at the opposite, Yemen represented a “negative” outlier with high mortality for all four considered periods and low recovery for 30 and 60 days

Heterogeneity in convergence behaviour of the single-step SNP-BLUP model across different effects and animal groups

Abstract Background The single-step model is becoming increasingly popular for national genetic evaluations of dairy cattle due to the benefits that it offers such as joint breeding value estimation for genotyped and ungenotyped animals. However, the complexity of the model due to a large number of correlated effects can lead to significant computational challenges, especially in terms of accuracy and efficiency of the preconditioned conjugate gradient method used for the estimation. The aim of this study was to investigate the effect of pedigree depth on the model's overall convergence rate as well as on the convergence of different components of the model, in the context of the single-step single nucleotide polymorphism best linear unbiased prediction (SNP-BLUP) model. Results The results demonstrate that the dataset with a truncated pedigree converged twice as fast as the full dataset. Still, both datasets showed very high Pearson correlations between predicted breeding values. In addition, by comparing the top 50 bulls between the two datasets we found a high correlation between their rankings. We also analysed the specific convergence patterns underlying different animal groups and model effects, which revealed heterogeneity in convergence behaviour. Effects of SNPs converged the fastest while those of genetic groups converged the slowest, which reflects the difference in information content available in the dataset for those effects. Pre-selection criteria for the SNP set based on minor allele frequency had no impact on either the rate or pattern of their convergence. Among different groups of individuals, genotyped animals with phenotype data converged the fastest, while non-genotyped animals without own records required the largest number of iterations. Conclusions We conclude that pedigree structure markedly impacts the convergence rate of the optimisation which is more efficient for the truncated than for the full dataset

Identification and annotation of breed-specific single nucleotide polymorphisms in Bos taurus genomes.

In Bos taurus the universality of the reference genome is biased towards genetic variation represented by only two related individuals representing the same Hereford breed. Therefore, results of genetic analyses based on this reference may not be reliable. The 1000 Bull Genomes resource allows for identification of breed-specific polymorphisms and for the construction of breed-specific reference genomes. Whole-genome sequences or 936 bulls allowed us to construct seven breed specific reference genomes of Bos taurus for Angus, Brown Swiss, Fleckvieh, Hereford, Jersey, Limousin and Simmental. In order to identify breed-specific variants all detected SNPs were filtered within-breed to satisfy criteria of the number of missing genotypes not higher than 7% and the alternative allele frequency equal to unity. The highest number of breed-specific SNPs was identified for Jersey (130,070) and the lowest-for the Simmental breed (197). Such breed-specific polymorphisms were annotated to coding regions overlapping with 78 genes in Angus, 140 in Brown Swiss, 132 in Fleckvieh, 100 in Hereford, 643 in Jersey, 10 in Limousin and no genes in Simmental. For most of the breeds, the majority of breed-specific variants from coding regions was synonymous. However, most of Fleckvieh-specific and Hereford-specific polymorphisms were missense mutations. Since the identified variants are characteristic for the analysed breeds, they form the basis of phenotypic differences observed between them, which result from different breeding programmes. Breed-specific reference genomes can enhance the accuracy of SNP driven inferences such as Genome-wide Association Studies or SNP genotype imputation