Biology subjects

Ankenbrand, M. J.

Publications and source records attributed to Ankenbrand, M. J..

7 recordsLinked to original sources

bioRxiv2025

Visualizing the transcription and replication of influenza A viral RNAs in cells by multiple direct RNA padlock probing and in-situ sequencing (mudRapp-seq)

Influenza A viruses (IAV) contain eight negative-sense single-stranded viral RNA (vRNA) molecules, which are transcribed into mRNA and replicated via complementary RNA (cRNA). These processes are tightly regulated, but the precise molecular mechanisms governing the switch from transcription to replication remain elusive. Here, we introduce multiple direct-RNA assisted padlock probing in combination with in situ sequencing (mudRapp-seq) to visualize the transcription and replication of all eight IAV vRNA and mRNA molecules at the single-cell level. We demonstrate that direct RNA padlock probing is three times more efficient than conventional probes that target cDNA. Individual probes showed variations in efficiency, partly due to the RNA structure of the target, which was mitigated by employing multiple padlock probes per target. Applying mudRapp-seq to an infection time course, we observed early mRNA expression, followed by vRNA accumulation approximately 3 hours later. Individual viral segments exhibited differential expression, particularly in the mRNA population. Both bulk and single-cell analyses revealed a correlation between the expression of M mRNA and the onset of the transcription-to-replication switch. Our findings demonstrate that mudRapp-seq offers significant potential for elucidating viral replication mechanisms and may be applicable to studying other RNA viruses and cellular RNA processes.

microbiology↗

bioRxiv2023

Opportunistic bacteria of grapevine crown galls are equipped with the genomic repertoire for opine utilization

Young grapevines (Vitis vinifera) suffer and eventually can die from the crown gall (CG) disease caused by the plant pathogen Allorhizobium vitis (Rhizobiaceae). Virulent members of A. vitis harbour a tumor-inducing (Ti) plasmid and induce formation of crown galls (CGs) due to the oncogenes encoded on the transfer-DNA (T-DNA). Expression of oncogenes in transformed host cells induce unregulated cell proliferation, metabolic and physiological changes. The CG produces opines uncommon to plants, which provide an important nutrient source for A. vitis harbouring opine catabolism enzymes. CGs host a distinct bacterial community and the mechanisms establishing a CG-specific bacterial community are currently unknown. Thus, we were interested in whether genes homologous to those of the Ti-plasmid coexist in the genomes of the microbial species coexisting in CGs. We isolated eight bacterial strains from grapevine CGs, sequenced their genomes and tested their virulence and opine utilization ability in bioassays. In addition, the eight genome sequences were compared to 34 published bacterial genomes, including closely related plant associated bacteria not from CGs. Homologous genes for virulence and opine anabolism were only present in the virulent Rhizobiaceae. By contrast, homologs of the opine catabolism genes were present in all strains including the non-virulent members of the Rhizobiaceae and non-Rhizobiaceae. Gene neighbourhood and sequence identity of the opine degradation cluster of virulent and non-virulent strains together with the results of the opine utilization assay support the important role of opine utilization for co-colonization in CGs, thereby shaping the CG community. Significance statementVirulent Allorhizobium vitis causes crown galls on grapevines which reduce plant vigour, yield, and cannot be cured. Non-virulent agrobacteria have been used as biocontrol agents to reduce the virulence potential within a crown gall and disease symptoms. We wanted to know if and how in nature this biocontrol concept is accomplished. We found virulent Allorhizobium along with non-virulent Agrobacterium, or Pseudomonas in the same tumours. Both harboured the catabolism genes in their genomes and metabolized the quorum sensing molecule opine. Thus, in nature it seems common that virulent and non-virulent species coexist in a crown gall and that the avirulent members control the virulence potential of the crown gall community by reducing the opine levels.

genomics↗

bioRxiv2022

Efficient Permutation-based Genome-wide Association Studies for Normal and Skewed Phenotypic Distributions

MotivationGenome-wide Association Studies (GWAS) are an integral tool for studying the architecture of complex genotype and phenotype relationships. Linear Mixed Models (LMMs) are commonly used to detect associations between genetic markers and the trait of interest, while at the same time allowing to account for population structure and cryptic relatedness. Assumptions of LMMs include a normal distribution of the residuals and that the genetic markers are independent and identically distributed - both assumptions are often violated in real data. Permutation-based methods can help to overcome some of these limitations and provide more realistic thresholds for the discovery of true associations. Still, in practice they are rarely implemented due to its high computational complexity. ResultsWe propose permGWAS, an efficient linear mixed model reformulation based on 4D-tensors that can provide permutation-based significance thresholds. We show that our method outperforms current state-of-the-art LMMs with respect to runtime and that a permutation-based threshold has a lower false discovery rate for skewed phenotypes compared to the commonly used Bonferroni threshold. Furthermore, using permGWAS we re-analysed more than 500 Arabidopsis thaliana phenotypes with 100 permutations each in less than eight days on a single GPU. Our re-analyses suggest that applying a permutation-based threshold can improve and refine the interpretation of GWAS results. AvailabilitypermGWAS is open-source and publicly available on GitHub for download: https://github.com/grimmlab/permGWAS.

bioinformatics↗

bioRxiv2020

Novel integrative elements and genomic plasticity in ocean ecosystems

Horizontal gene transfer accelerates microbial evolution, promoting diversification and adaptation. The globally abundant marine cyanobacterium Prochlorococcus has a highly streamlined genome with frequent gene exchange reflected in its extensive pangenome. The source of its genomic variability, however, remains elusive since most cells lack the common mechanisms that enable horizontal gene transfer, including conjugation, transformation, plasmids and prophages. Examining 623 genomes, we reveal a diverse system of mobile genetic elements - cargo-carrying transposons we named tycheposons - that shape Prochlorococcus genomic plasticity. The excision and integration of tycheposons at seven tRNA genes drive the remodeling of larger genomic islands containing most of Prochlorococcus flexible genes. Most tycheposons carry genes important for niche differentiation through nutrient acquisition; others appear similar to phage parasites. Tycheposons are highly enriched in extracellular vesicles and phage particles in ocean samples, suggesting efficient routes for their dispersal, transmission and propagation. Supported by evidence for similar elements in other marine microbes, our work underpins the role of vesicle- and virus-mediated transfer of mobile genetic elements in the diversification and adaptation of microbes in dilute aquatic environments - adding a significant piece to the puzzle of what governs microbial evolution in the planets largest habitat.

microbiology↗

bioRxiv2019

GWAS-Flow: A GPU accelerated framework for efficient permutation based genome-wide association studies

MotivationGenome-wide association studies (GWAS) are one of the most commonly used methods to detect associations between complex traits and genomic polymorphisms. As both genotyping and phenotyping of large populations has become easier, typical modern GWAS have to cope with massive amounts of data. Thus, the computational demand for these analyses grew remarkably during the last decades. This is especially true, if one wants to implement permutation-based significance thresholds, instead of using the naive Bonferroni threshold. Permutation-based methods have the advantage to provide an adjusted multiple hypothesis correction threshold that takes the underlying phenotypic distribution into account and will thus remove the need to find the correct transformation for non Gaussian phenotypes. To enable efficient analyses of large datasets and the possibility to compute permutation-based significance thresholds, we used the machine learning framework TensorFlow to develop a linear mixed model (GWAS-Flow) that can make use of the available CPU or GPU infrastructure to decrease the time of the analyses especially for large datasets.\n\nResultsWe were able to show that our application GWAS-Flow outperforms custom GWAS scripts in terms of speed without loosing accuracy. Apart from p-values, GWAS-Flow also computes summary statistics, such as the effect size and its standard error for each individual marker. The CPU-based version is the default choice for small data, while the GPU-based version of GWAS-Flow is especially suited for the analyses of big data.\n\nAvailabilityGWAS-Flow is freely available on GitHub (https://github.com/Joyvalley/GWAS_Flow) and is released under the terms of the MIT-License.

bioinformatics↗

bioRxiv2019

The landscape of chloroplast genome assembly tools

BackgroundChloroplasts are intracellular organelles that enable plants to conduct photosynthesis. They arose through the symbiotic integration of a prokaryotic cell into an eukaryotic host cell and still contain their own genomes with distinct genomic information. Plastid genomes accommodate essential genes and are regularly utilized in biotechnology or phylogenetics. Different assemblers that are able to assess the plastid genome have been developed. These assemblers often use data of whole genome sequencing experiments, which usually contain reads from the complete chloroplast genome. ResultsThe performance of different assembly tools has never been systematically compared. Here we present a benchmark of seven chloroplast assembly tools, capable of succeeding in more than 60% of known real data sets. Our results show significant differences between the tested assemblers in terms of generating whole chloroplast genome sequences and computational requirements. The examination of 105 data sets from species with unknown plastid genomes leads to the assembly of 20 novel chloroplast genomes. ConclusionsWe create docker images for each tested tool that are freely available for the scientific community and ensure reproducibility of the analyses. These containers allow the analysis and screening of data sets for chloroplast genomes using standard computational infrastructure. Thus, large scale screening for chloroplasts within genomic sequencing data is feasible.

bioinformatics↗

bioRxiv2017

FENNEC - Functional Exploration of Natural Networks and Ecological Communities

O_LISpecies composition assessment of ecological communities and networks is an important aspect of biodiversity research. Yet often ecological traits of organisms in a community are more informative than scientific names only. Furthermore, other properties like threat status, invasiveness, or human usage are relevant for many studies, but cannot be evaluated from taxonomy alone. Despite public databases collecting such information, it is still a tedious manual task to enrich community analyses with such, especially for large-scaled data.\nC_LIO_LIThus we aimed to develop a public and free tool that eases bulk trait mapping of community data in a web browser, implemented with current standard web and database technologies.\nC_LIO_LIHere we present the FO_SCPLOWENNECC_SCPLOW, a workbench that eases the process of mapping publicly available trait data to the users communities in an automated process. Usage is either by a local self-hosted or a public instance (https://fennec.molecular.eco) covering exemplary traits. Alongside the software we also provide usage and hosting documentation as well as online tutorials.\nC_LIO_LIThe FO_SCPLOWENNECC_SCPLOW aims to motivate public trait data submission and its reuse in meta-analyses. Further, it is an open-source development project with the code freely available to use and open for community contributions (https://github.com/molbiodiv/fennec).\nC_LI

ecology↗