Peter Sørensen

Aarhus University | AU · Department of Molecular Biology and Genetics

Type 2 diabetes mellitus (T2DM) is continuously rising with more disease cases every year. T2DM is a chronic disease with many severe comorbidities and therefore remains a burden for the patient and the society. Disease prevention, early diagnosis, and stratified treatment are important elements in slowing down the increase in diabetes prevalence....

The ability to accurately predict complex trait phenotypes from genetic and genomic data is critical for the implementation of personalized medicine and precision agriculture; however, prediction accuracy for most complex traits is currently low. Here, we used data on whole genome sequences, deep RNA sequencing, and high quality phenotypes for thre...

Genomics has been forecasted to revolutionise human health by improving medical treatment through a better understanding of the molecular mechanisms of human diseases. Despite great successes of the last decade’s genome-wide association studies (GWAS), the results have to a limited extent been translated to genomic medicine. We propose, that one ro...

Whole genome sequencing of 217 animals from three Danish commercial pig breeds (Duroc, Landrace, and Yorkshire) was performed. Twenty-six million single nucleotide polymorphisms (SNPs) and 8 million insertions or deletions (indels) were uncovered. Among the SNPs, 493,099 variants were located in coding sequences, and 29,430 were predicted to have a...

Here, we present the R package qgg, which provides an environment for large-scale genetic analyses of quantitative traits and diseases. The qgg package provides an infrastructure for efficient processing of large-scale genetic data and functions for estimating genetic parameters, and performing single and multiple marker association analyses and ge...

Fatty acids (FA) in bovine milk derive through body mobilization, de novo synthesis or from the feed via the blood stream. To be able to digest feedstuff, the cow depends on its rumen microbiome. The relative abundance of the microbes has been shown to differ between cows. To date, there is little information on the impact of the microbiome on the...

An important challenge in genetics is to be able to predict complex traits accurately. Despite recent advances, prediction accuracy for most complex traits remains low. Here, we used the Drosophila Genetic Reference Panel (DGRP), a collection of 200 lines with whole-genome sequences and deep RNA sequencing data, to evaluate the usefulness of using...

Knowledge of the genetic basis underlying variation in response to environmental exposures or treatment is important in many research areas. For example, knowing the set of causal genetic variants for drug response could revolutionize personalized medicine. We used Drosophila melanogaster to investigate the genetic signature underlying behavioral v...

Studies of complex traits and diseases are strongly dependent on the availability of user-friendly software designed to handle large-scale genetic and phenotypic data. Here, we present the R package qgg, which provides an environment for large-scale genetic analyses of quantitative traits and disease phenotypes. The qgg package provides an infrastr...

Background: Genomic models that link phenotypes to dense genotype information are increasingly being used for infering variance parameters in genetics studies. The variance parameters of these models can be inferred using restricted maximum likelihood, which produces consistent, asymptotically normal estimates of variance components under the true...

Most organisms experience variable and sometimes suboptimal environments in their lifetime. While stressful environmental conditions are normally viewed as a strong selective force, they can also impact directly on the genetic basis of traits such as through environment-dependent gene action. Here, we used the Drosophila melanogaster Genetic Refere...

MicroRNAs (miRNA) are key modulators of gene expression and so act as putative fine-tuners of complex phenotypes. Here, we hypothesized that causal variants of complex traits are enriched in miRNAs and miRNA-target networks. First, we conducted a genome-wide association study (GWAS) for seven functional and milk production traits using imputed sequ...

Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait variability to pinpoint loci that contribute to the qu...

Genomic models that incorporate dense SNP genotypes are increasingly being used and studied for inference of variance parameters and narrow-sense heritability. The variance parameters of a linear mixed model linking a phenotype to SNP genotypes can be inferred using restricted maximum likelihood, which produces consistent, asymptotically normal est...

Trait variation is normally separated into genetic and environmental components, yet genetic factors also control the expression of environmental variation, encompassing plasticity across environmental gradients and within-environment responses. We defined four components of environmental variation: plasticity across environments, variability in pl...

Background A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of “Gene Ont...

Human psychiatric disorders such as schizophrenia, bipolar disorder and attention-deficit/hyper-activity disorder often include adverse behaviors including increased aggressiveness. Individuals with psychiatric disorders often exhibit social withdrawal, which can further increase the probability of conducting a violent act. Here, we used the inbred...

Background: A better understanding of the genetic architecture of complex traits can contribute to improve genomic prediction. We hypothesized that genomic variants associated with mastitis and milk production traits in dairy cattle are enriched in hepatic transcriptomic regions that are responsive to intra-mammary infection (IMI). Genomic markers...

The genomic best linear unbiased prediction (GBLUP) model has proven to be useful for prediction of complex traits as well as estimation of population genetic parameters. Improved inference and prediction accuracy of GBLUP may be achieved by identifying genomic regions enriched for causal genetic variants. We aimed at searching for patterns in GBLU...

Whole blood stimulation assay (WBA) has been widely used to study production of the pro-inflammatory cytokine, tumor necrosis factor-alpha (TNF-α) and is considered a relatively good predictor for the in vivo release of TNF-α during endotoximia in dairy cattle. However, it requires a standardized and optimized dose of lipopolysaccharides (LPS) to s...

Connecting genome-wide association study (GWAS) to biological mechanisms underlying complex traits is a major challenge. Mastitis resistance and milk production are complex traits of economic importance in the dairy sector and are associated with intra-mammary infection (IMI). Here, we integrated IMI-relevant RNA-Seq data from Holstein cattle and s...

The expression correlations for all the profiled 358 known mature miRNAs between each pair of samples.

Differentially expressed genes (DEG) in Toll-like receptor signaling pathway. The colored genes are DEGs, the color-key corresponds to the log2(fold-change) of DEG.

The summary of the bioinformatics analyses strategy.

Differentially expressed genes (DEG) in JAK-STAT signaling pathway. The colored genes are DEGs, the color-key corresponds to the log2(fold-change) of DEG.

The distribution of differentially expressed genes (DEG) along the bovine genome. y-Axis is the chromosome number, x-axis is the base-pair position of DEG.

Background In animal breeding, genetic variance for complex traits is often estimated using linear mixed models that incorporate information from single nucleotide polymorphism (SNP) markers using a realized genomic relationship matrix. In such models, individual genetic markers are weighted equally and genomic variation is treated as a “black box....

Staphylococcus aureus (S. aureus) is problematic for lactating mammals and public health. Understanding of mechanisms by which the hosts respond to severe invasion of S. aureus remains elusive. In this study, the genome-wide expression of mRNAs and miRNAs in bovine mammary gland cells were interrogated at 24 h after intra-mammary infection (IMI) wi...

Our objective was to identify the biological response and the cross-talk between liver and mammary tissue after intramammary infection (IMI) with Escherichia coli (E. coli) using RNAseq technology. Sixteen cows were inoculated with live E. coli into one mammary quarter at ~4-6 weeks in lactation. For all cows, biopsies were performed at -144, 12 an...

Concentrations of alkaline phosphatase (A), N-acetyl-β-D-glucosaminidase (NAGase; B) and lactate dehydrogenase (LDH; C) in milk from cows (n = 16) after intramammary challenge during early lactation. *Differences (P < 0.05) when compared to h = 0. (DOCX)

Expression of genes coding for selected pro-inflammatory cytokines and positive and negative acute phase proteins (data as also reported in S5 Fig). (JPG)

Complete results of the predicted up-stream regulators by Ingenuity Pathway Analysis for both liver and mammary tissue. (XLSX)

Changes in daily feed intake (A) and milk yield (B) from cows (n = 16) after intramammary challenge during early lactation. *Differences (P < 0.05) when compared to h = 0. (DOCX)

Complete dataset with false discovery rate (FDR) for the overall time or treatment effect, expression ratio, and P-value between comparisons. (XLSX)

Dynamic Impact Approach of the KEGG pathways analysis for both liver and mammary tissue. Presented are the summary of the categories of pathways, the details of each pathway, and sorted in descending order of impact in each comparison. (XLSX)

Plasma concentrations of non-esterified fatty acids (NEFA; A), beta-hydroxybutyrate (BHBA; B), glucose (C) and cholesterol (D) from cows (n = 16) after intramammary challenge during early lactation. *Differences (P < 0.05) when compared to h = 0. (DOCX)

Results of the pathway and function analysis of Ingenuity Pathways Analysis for both liver and mammary tissue. (XLSX)

Schizophrenia is a psychiatric disorder with large personal and social costs, and understanding the genetic etiology is important. Such knowledge can be obtained by testing the association between a disease phenotype and individual genetic markers; however, such single marker methods have limited power to detect genetic markers with small effects....

Predicting individual quantitative trait phenotypes from high resolution genomic polymorphism data is important for personalized medicine in humans, plant and animal breeding and adaptive evolution. However, this is difficult for populations of unrelated individuals when the number of causal variants is low relative to the total number of polymorph...

The ability of natural populations to withstand environmental stresses relies partly on their adaptive ability. In this study, we used a subset of the Drosophila Genetic Reference Panel, a population of inbred, genome-sequenced lines derived from a natural population of Drosophila melanogaster, to investigate whether this population harbors genetic...

The supplementary material contain information of which DGRP lines assessed, additional experimental design informations (Table S1), and the phenotypic line means for the traits assayed (Table S2). The supplementary information also contains the likelihood ratio test for the fixed effects (Table S3), overview of GOs with a p<0.005 (Table S4) and GO...

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the ove...