Daniel Fischer

Oral Samples as Non-Invasive Proxies for Assessing the Composition of the Rumen Microbial Community

Microbial community analysis was carried out on ruminal digesta obtained directly via rumen fistula and buccal fluid, regurgitated digesta (bolus) and faeces of dairy cattle to assess if non-invasive samples could be used as proxies for ruminal digesta. Samples were collected from five cows receiving grass silage based diets containing no additional lipid or four different lipid supplements in a 5 x 5 Latin square design. Extracted DNA was analysed by qPCR and by sequencing 16S and 18S rRNA genes or the fungal ITS1 amplicons. Faeces contained few protozoa, and bacterial, fungal and archaeal communities were substantially different to ruminal digesta. Buccal and bolus samples gave much more similar profiles to ruminal digesta, although fewer archaea were detected in buccal and bolus samples. Bolus samples overall were most similar to ruminal samples. The differences between both buccal and bolus samples and ruminal digesta were consistent across all treatments. It can be concluded that either proxy sample type could be used as a predictor of the rumen microbial community, thereby enabling more convenient large-scale animal sampling for phenotyping and possible use in future animal breeding programs aimed at selecting cattle with a lower environmental footprint.

Taxon abundance, diversity, co-occurrence and network analysis of the ruminal microbiota in response to dietary changes in dairy cows

The ruminal microbiome, comprising large numbers of bacteria, ciliate protozoa, archaea and fungi, responds to diet and dietary additives in a complex way. The aim of this study was to investigate the benefits of increasing the depth of the community analysis in describing and explaining responses to dietary changes. Quantitative PCR, ssu rRNA amplicon based taxa composition, diversity and co-occurrence network analyses were applied to ruminal digesta samples obtained from four multiparous Nordic Red dairy cows fitted with rumen cannulae. The cows received diets with forage:concentrate ratio either 35:65 (diet H) or 65:35 (L), supplemented or not with sunflower oil (SO) (0 or 50 g/kg diet dry matter), supplied in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments and four 35-day periods. Digesta samples were collected on days 22 and 24 and combined. QPCR provided a broad picture in which a large fall in the abundance of fungi was seen with SO in the H but not the L diet. Amplicon sequencing showed higher community diversity indices in L as compared to H diets and revealed diet specific taxa abundance changes, highlighting large differences in protozoal and fungal composition. Methanobrevibacter ruminantium and Mbb. gottschalkii dominated archaeal communities, and their abundance correlated negatively with each other. Co-occurrence network analysis provided evidence that no microbial domain played a more central role in network formation, that some minor-abundance taxa were at nodes of highest centrality, and that microbial interactions were diet specific. Networks added new dimensions to our understanding of the diet effect on rumen microbial community interactions.

ARLTS1 and Prostate Cancer Risk - Analysis of Expression and Regulation

Prostate cancer (PCa) is a heterogeneous trait for which several susceptibility loci have been implicated by genome-wide linkage and association studies. The genomic region 13q14 is frequently deleted in tumour tissues of both sporadic and familial PCa patients and is consequently recognised as a possible locus of tumour suppressor gene(s). Deletions of this region have been found in many other cancers. Recently, we showed that homozygous carriers for the T442C variant of the ARLTS1 gene (ADP-ribosylation factor-like tumour suppressor protein 1 or ARL11, located at 13q14) are associated with an increased risk for both unselected and familial PCa. Furthermore, the variant T442C was observed in greater frequency among malignant tissue samples, PCa cell lines and xenografts, supporting its role in PCa tumourigenesis. In this study, 84 PCa cases and 15 controls were analysed for ARLTS1 expression status in blood-derived RNA. A statistically significant (p = 0.0037) decrease of ARLTS1 expression in PCa cases was detected. Regulation of ARLTS1 expression was analysed with eQTL (expression quantitative trait loci) methods. Altogether fourteen significant cis-eQTLs affecting the ARLTS1 expression level were found. In addition, epistatic interactions of ARLTS1 genomic variants with genes involved in immune system processes were predicted with the MDR program. In conclusion, this study further supports the role of ARLTS1 as a tumour suppressor gene and reveals that the expression is regulated through variants localised in regulatory regions.

Fine-mapping the 2q37 and 17q11.2-q22 loci for novel genes and sequence variants associated with a genetic predisposition to prostate cancer

The 2q37 and 17q12‐q22 loci are linked to an increased prostate cancer (PrCa) risk. No candidate gene has been localized at 2q37 and the HOXB13 variant G84E only partially explains the linkage to 17q21‐q22 observed in Finland. We screened these regions by targeted DNA sequencing to search for cancer‐associated variants. Altogether, four novel susceptibility alleles were identified. Two ZNF652 (17q21.3) variants, rs116890317 and rs79670217, increased the risk of both sporadic and hereditary PrCa (rs116890317: OR = 3.3–7.8, p = 0.003–3.3 × 10−5; rs79670217: OR = 1.6–1.9, p = 0.002–0.009). The HDAC4 (2q37.2) variant rs73000144 (OR = 14.6, p = 0.018) and the EFCAB13 (17q21.3) variant rs118004742 (OR = 1.8, p = 0.048) were overrepresented in patients with familial PrCa. To map the variants within 2q37 and 17q11.2‐q22 that may regulate PrCa‐associated genes, we combined DNA sequencing results with transcriptome data obtained by RNA sequencing. This expression quantitative trait locus (eQTL) analysis identified 272 single‐nucleotide polymorphisms (SNPs) possibly regulating six genes that were differentially expressed between cases and controls. In a modified approach, prefiltered PrCa‐associated SNPs were exploited and interestingly, a novel eQTL targeting ZNF652 was identified. The novel variants identified in this study could be utilized for PrCa risk assessment, and they further validate the suggested role of ZNF652 as a PrCa candidate gene. The regulatory regions discovered by eQTL mapping increase our understanding of the relationship between regulation of gene expression and susceptibility to PrCa and provide a valuable starting point for future functional research.

MiRNA Profiles in Lymphoblastoid Cell Lines of Finnish Prostate Cancer Families.

Background Heritable factors are evidently involved in prostate cancer (PrCa) carcinogenesis, but currently, genetic markers are not routinely used in screening or diagnostics of the disease. More precise information is needed for making treatment decisions to distinguish aggressive cases from indolent disease, for which heritable factors could be a useful tool. The genetic makeup of PrCa has only recently begun to be unravelled through large-scale genome-wide association studies (GWAS). The thus far identified Single Nucleotide Polymorphisms (SNPs) explain, however, only a fraction of familial clustering. Moreover, the known risk SNPs are not associated with the clinical outcome of the disease, such as aggressive or metastasised disease, and therefore cannot be used to predict the prognosis. Annotating the SNPs with deep clinical data together with miRNA expression profiles can improve the understanding of the underlying mechanisms of different phenotypes of prostate cancer. Results In this study microRNA (miRNA) profiles were studied as potential biomarkers to predict the disease outcome. The study subjects were from Finnish high risk prostate cancer families. To identify potential biomarkers we combined a novel non-parametrical test with an importance measure provided from a Random Forest classifier. This combination delivered a set of nine miRNAs that was able to separate cases from controls. The detected miRNA expression profiles could predict the development of the disease years before the actual PrCa diagnosis or detect the existence of other cancers in the studied individuals. Furthermore, using an expression Quantitative Trait Loci (eQTL) analysis, regulatory SNPs for miRNA miR-483-3p that were also directly associated with PrCa were found. Conclusion Based on our findings, we suggest that blood-based miRNA expression profiling can be used in the diagnosis and maybe even prognosis of the disease. In the future, miRNA profiling could possibly be used in targeted screening, together with Prostate Specific Antigene (PSA) testing, to identify men with an elevated PrCa risk.

The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci

BACKGROUND AND OBJECTIVES We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (exploratory) Quantitative Trait Loci analysis that overcomes some of the limitations of other popular (e)QTL approaches. Popular (e)QTL approaches that use linear models or ANOVA are often based on over-simplified models that have weak statistical properties and which are not robust against outlying observations. METHOD The algorithm to calculate the MDR is well established. To speed up its calculation in R, we implemented it in C++. Further, our implementation also supports the combination of several MDR results to an MDR ensemble classifier. The (e)QTL test procedure is based on a generalized Mann-Whitney test that is tailored for directional alternatives, as they are present in an (e)QTL analysis. RESULTS Our package GenomicTools provides functions to determine SNP combinations that have the highest accuracy for a MDR classification problem. It also provides functions to combine the best MDR results to a joined ensemble classifier for improved classification results. Further, the (e)QTL analysis is based on a solid statistical theory. In addition, informative visualizations of the results are provided. CONCLUSION The here presented new class of tests and methods have an easy to apply syntax, so that also researchers inexperienced in R are able to apply our proposed methods and implementations. The package creates publication ready Figures and hence could be a valuable tool for genomic data analysis.

A splice site variant in INPP5E causes diffuse cystic renal dysplasia and hepatic fibrosis in dogs

Ciliopathies presenting as inherited hepatorenal fibrocystic disorders are rare in humans and in dogs. We describe here a novel lethal ciliopathy in Norwich Terrier puppies that was diagnosed at necropsy and characterized as diffuse cystic renal disease and hepatic fibrosis. The histopathological findings were typical for cystic renal dysplasia in which the cysts were located in the straight portion of the proximal tubule, and thin descending and ascending limbs of Henle’s loop. The pedigree of the affected puppies was suggestive of an autosomal recessive inheritance and therefore, whole exome sequencing and homozygosity mapping were used for identification of the causative variant. The analyses revealed a case-specific homozygous splice donor site variant in a cilia related gene, INPP5E: c.1572+5G>A. Association of the variant with the defect was validated in a large cohort of Norwich Terriers with 3 cases and 480 controls, the carrier frequency being 6%. We observed that the identified variant introduces a novel splice site in INPP5E causing a frameshift and formation of a premature stop codon. In conclusion, our results suggest that the INPP5E: c.1572+5G>A variant is causal for the ciliopathy in Norwich Terriers. Therefore, genetic testing can be carried out in the future for the eradication of the disease from the breed.

Copy number variations in two Finnish pig breeds

AIM Identify signals of fat deposition and adaptation through genome-wide scan of the Barbaresca fat-tail sheep. ANIMALS Barbaresca in an ancient Sicilian fat-tail sheep, highly endangered at present. Of the 35 000 heads of 1980, abour 1 300 are left nowadays in 20 flocks. The breed originated from crosses between Barbary sheep from North Africa and the Pinzirita breed at times of the Arab settling in Sicily (9th century). The breed is reared in a very restricted area in central Sicily on smalland medium-sized farms under a semi-extensive farming system. It is a dual-purpose breed: milk for cheese and meat. Barbaresca is one of the only two fat-tail sheep of Italy. METHODS Genotypic data were obtained with the OvineSNP50K array. Fst values of differentiation for 43072 markers were calculated in pairwise comparisons of Barbaresca with each of 13 Italian thin tail breeds. Fat-tail sheep still represent twenty-five percent of the world sheep population; they are predominant in pastoral, transhumant and low input systems. In Western countries and in high input systems they are generally endangered. Fat-tail sheep preserved genetic variability for functional adaptation. The identification of the genes with a role in the fat-tail phenotype contributes to the understanding of the physiology of fat deposition as well as the mechanisms of adaptation and is essential for maintaining future breeding options. Heritability estimates for the 1st litter size, pregnancy rate and whelping success were low (0.05-0.14)  Grading size and quality had moderate heritability estimates 0.27 and 0.21, respectively  Genetic correlations between animal grading size and fertility traits were unfavourable (from -0.15 to -0.53)  Grading quality and guard hair coverage had antagonistic relationships with all the studied fertility traits (from -0.21 to -0.54) Genetic parameters of fertility and grading traits in Finnish blue foxTrabajo presentado al: 68th Annual Meeting of the European Federation of Animal Science (EAAP). (Tallin, Estonia. 28 agosto - 2 septiembre).Trabajo presentado al: 68th Annual Meeting of the European Federation of Animal Science (EAAP). (Tallin, Estonia. 28 agosto - 2 septiembre).

Expressional profiling of prostate cancer risk SNPs at 11q13.5 identifies DGAT2 as a new target gene.

A total of nine non‐coding variants on 11q13.5 predispose men to prostate cancer (PrCa). rs200331695 within the EMSY intron is associated with aggressive PrCa and two high linkage disequilibrium (LD) groups of single‐nucleotide polymorphisms (SNPs) in the intergenic region are associated with PrCa death. Here, the cis‐effect of the SNPs on gene expression using expression quantitative trait loci analysis was investigated. The regulatory potential was screened in prostate tumors (n = 41) and in whole blood (n = 99). The results were validated in a second tumor set (n = 41), in lymphoblastoid cell lines (LCLs) (n = 38), and using the GTEx Portal. The effects of haplotypes were analyzed in the whole blood. The high LD SNPs (rs143975731, rs12277366, rs2155225, and rs2155222) were associated with DGAT2 expression in both tumors sets (screening P = 0.035–0.043; validation P = 0.005–0.018). The PrCa death‐associated alleles decreased the expression by two‐fold. rs200331695 decreased DGAT2 expression in LCLs (P = 0.006). The findings of SNPs regulating CAPN5 (P = 0.026–0.046) and AP001189.4 (P = 0.03–0.039) in the whole blood were not observed in LCLs, but the association with AP001189.4 expression was validated via the GTEx Portal (P = 8.7 × 10−5 to 4.3 × 10−4), which suggests that the high LD intergenic SNPs exert a tissue‐dependent effect on the expression of two genes. No haplotypes including the risk SNPs at 11q13.5 were associated with gene expression and PrCa. The findings indicate the functionality of the PrCa death‐predisposing SNPs rs143975731, rs12277366, rs2155225, and rs2155222 as DGAT2 regulators in prostate tumors.

Publication and Coauthorship Networks of Hannu Oja

In this paper we review Hannu Oja’s publications and form coauthor networks based on them. Applying community detection methods to the network formed by all of Hannu’s publications shows that his coauthors can be classified into 13 clusters, where two large clusters refer to his methodological research. The network concerning this methodological work is then extended to cover all statistical publications written by Hannu’s coauthors. The analysis of the extended network shows that Hannu’s coauthors do not form a closed community, but Hannu is involved in many different fields of statistics.