• Our aim is to advance our understanding of biological systems,

    ranging from single species to multi-species systems and ecosystems,

    based on data from large-scale bioanalytical methods.

  • We develop, improve and apply

    computational methods

    for the interpretation of molecular information in biology.

  • We establish and analyse

    quantitative mathematical models.

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Latest publications

Time-course expression QTL atlas of the global transcriptional response of wheat to Fusarium graminearum.

Fusarium head blight is a devastating disease of small grain cereals such as bread wheat (Triticum aestivum). The pathogen switches from a biotrophic to a nectrotrophic lifestyle in course of disease development forcing its host to adapt its defence strategies. Using a genetical genomics approach we illustrate genome-wide reconfigurations of genetic control over transcript abundances between two decisive time points after inoculation with the causative pathogen Fusarium graminearum. Whole transcriptome measurements have been recorded for 163 lines of a wheat doubled haploid population segregating for several resistance genes yielding 15 552 at 30 hours and 15 888 eQTL at 50 hours after inoculation. The genetic map saturated with transcript abundance-derived markers identified of a novel QTL on chromosome 6A, besides the previously reported QTL Fhb1 and Qfhs.ifa-5A. We find a highly different distribution of eQTL between time points with about 40% of eQTL being unique for the respective assessed time points. But also for more than 20% of genes governed by eQTL at either time point genetic control changes in time. These changes are reflected in the dynamic compositions of three major regulatory hotspots on chromosomes 2B, 4A and 5A. In particular control of defence-related biological mechanisms concentrated in the hotspot at 4A shift to hotspot 2B as the disease progresses. Hotspots do not colocalize with phenotypic QTL and within their intervals no higher than expected number of eQTL was detected. Thus, resistance conferred by either QTL is mediated by few or single genes. This article is protected by copyright. All rights reserved.

Samad-Zamini M, Schweiger W, Nussbaumer T, Mayer KF, Buerstmayr H
2017 - Plant Biotechnol. J., in press

Natural haplotypes of FLM non-coding sequences fine-tune flowering time in ambient spring temperatures in Arabidopsis.

Cool ambient temperatures are major cues determining flowering time in spring. The mechanisms promoting or delaying flowering in response to ambient temperature changes are only beginning to be understood. In Arabidopsis thaliana, FLOWERING LOCUS M (FLM) regulates flowering in the ambient temperature range and FLM is transcribed and alternatively spliced in a temperature-dependent manner. We identify polymorphic promoter and intronic sequences required for FLM expression and splicing. In transgenic experiments covering 69% of the available sequence variation in two distinct sites, we show that variation in the abundance of the FLM-ß splice form strictly correlate (R2 = 0.94) with flowering time over an extended vegetative period. The FLM polymorphisms lead to changes in FLM expression (PRO2+) but may also affect FLM intron 1 splicing (INT6+). This information could serve to buffer the anticipated negative effects on agricultural systems and flowering that may occur during climate change.

Lutz U, Nussbaumer T, Spannagl M, Diener J, Mayer KF, Schwechheimer C
2017 - Elife, in press

Variant profiling of evolving prokaryotic populations.

Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap. In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at.

Zojer M, Schuster LN, Schulz F, Pfundner A, Horn M, Rattei T
2017 - PeerJ, e2997