Large scale genomic rearrangements in selected Arabidopsis thaliana T-DNA lines are caused by T-DNA insertion mutagenesis.

BACKGROUND: Experimental proof of gene function assignments in plants is based on mutant analyses. T-DNA insertion lines provided an invaluable resource of mutants and enabled systematic reverse genetics-based investigation of the functions of Arabidopsis thaliana genes during the last decades. RESULTS: We sequenced the genomes of 14 A. thaliana GABI-Kat T-DNA insertion lines, which eluded flanking sequence tag-based attempts to characterize their insertion loci, with Oxford Nanopore Technologies (ONT) long reads. Complex T-DNA insertions were resolved and 11 previously unknown T-DNA loci identified, resulting in about 2 T-DNA insertions per line and suggesting that this number was previously underestimated. T-DNA mutagenesis caused fusions of chromosomes along with compensating translocations to keep the gene set complete throughout meiosis. Also, an inverted duplication of 800 kbp was detected. About 10 % of GABI-Kat lines might be affected by chromosomal rearrangements, some of which do not involve T-DNA. Local assembly of selected reads was shown to be a computationally effective method to resolve the structure of T-DNA insertion loci. We developed an automated workflow to support investigation of long read data from T-DNA insertion lines. All steps from DNA extraction to assembly of T-DNA loci can be completed within days. CONCLUSIONS: Long read sequencing was demonstrated to be an effective way to resolve complex T-DNA insertions and chromosome fusions. Many T-DNA insertions comprise not just a single T-DNA, but complex arrays of multiple T-DNAs. It is becoming obvious that T-DNA insertion alleles must be characterized by exact identification of both T-DNA::genome junctions to generate clear genotype-to-phenotype relations.

Dataset supporting the use of nematodes as bioindicators of polluted sediments.

We provide the dataset supporting the research article "Nematodes as bioindicators of polluted sediments using metabarcoding and microscopic taxonomy" [1]. Nematodes are frequently used as bioindicators and the NemaSPEAR[%] is an validated index that is originally based on morphological data. The index was compared to molecular sequence data for the 28S rDNA, 18S rDNA and COI gene for 7 locations. This dataset includes chemical analyses of the sediments for 33 different substances. The sequence data for OTU-based analyses for the 28S rDNA, 18S rDNA and COI gene is given, together with the read distribution during bioinformatics processing. We furthermore include alternative ASV data, based on a cluster-independent approach. The morphological data is presented, including the biomass for each species, as well as an overview about whether the species is represented in the NCBI database. Furthermore, rarefaction analysis is given for the morphological data, and furthermore NMDS plots for the species and genus level based on morphological and molecular data. The correlation between the mean PEC-Q and the NemaSPEAR[%] values is given in order to compare the efficiency of the index, based on morphological and molecular data.

Nematodes as bioindicators of polluted sediments using metabarcoding and microscopic taxonomy.

The use of bioindicator species is a widely applied approach to evaluate ecological conditions, and several indices have been designed for this purpose. To assess the impact of pollution, especially in sediments, a pollution-sensitive index based on nematodes, one of the most abundant and species-rich groups of metazoa, was developed. The NemaSPEAR[%] index in its original form relies on the morphological inspection of nematode species. The application of a morphologically based NemaSPEAR[%] at the genus-level was previously validated. The present study evaluated a NemaSPEAR[%] index based on metabarcoding of nematode communities and tested the potential of fragments from the 28S rDNA, 18S rDNA and cytochrome c oxidase subunit I (COI) genes. In general, molecular-based results tended to show a poorer condition than morphology-based results for the investigated sites. At the genus level, NemaSPEAR[%] values based on morphological data strongly correlated with those based on molecular data for both the 28S rDNA and the 18S rDNA gene fragments (R2 = 0.86 and R2 = 0.74, respectively). Within the dominant genera (>3%) identified by morphology, 68% were detected by at least one of the two ribosomal markers. At the species level, however, concordance was less pronounced, as there were several deviations of the molecular from the morphological data. These differences could mostly be attributed to shortcomings in the reference database used in the molecular-based assignments. Our pilot study shows that a molecularly based, genus-level NemaSPEAR[%] can be successfully applied to evaluate polluted sediment. Future studies need to validate this approach further, e.g. with bulk extractions of whole meiofaunal communities in order to circumvent time-consuming nematode isolation. Further database curation with abundant NemaSPEAR[%] species will also increase the applicability of this approach.

Comparison of morphological, DNA barcoding, and metabarcoding characterizations of freshwater nematode communities.

Biomonitoring approaches and investigations of many ecological questions require assessments of the biodiversity of a given habitat. Small organisms, ranging from protozoans to metazoans, are of great ecological importance and comprise a major share of the planet's biodiversity but they are extremely difficult to identify, due to their minute body sizes and indistinct structures. Thus, most biodiversity studies that include small organisms draw on several methods for species delimitation, ranging from traditional microscopy to molecular techniques. In this study, we compared the efficiency of these methods by analyzing a community of nematodes. Specifically, we evaluated the performances of traditional morphological identification, single-specimen barcoding (Sanger sequencing), and metabarcoding in the identification of 1500 nematodes from sediment samples. The molecular approaches were based on the analysis of the 28S ribosomal large and 18S small subunits (LSU and SSU). The morphological analysis resulted in the determination of 22 nematode species. Barcoding identified a comparable number of operational taxonomic units (OTUs) based on 28S rDNA (n = 20) and fewer OTUs based on 18S rDNA (n = 12). Metabarcoding identified a higher OTU number but fewer amplicon sequence variants (AVSs) (n = 48 OTUs, n = 17 ASVs for 28S rDNA, and n = 31 OTUs, n = 6 ASVs for 18S rDNA). Between the three approaches (morphology, barcoding, and metabarcoding), only three species (13.6%) were shared. This lack of taxonomic resolution hinders reliable community identifications to the species level. Further database curation will ensure the effective use of molecular species identification.

The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR.

The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF). The de.NBI provides (i) service, (ii) training, and (iii) cloud computing to users in life sciences research and biomedicine in Germany and Europe and (iv) fosters the cooperation of the German bioinformatics community with international network structures. The de.NBI members also run the German node (ELIXIR-DE) within the European ELIXIR infrastructure. The de.NBI / ELIXIR-DE training platform, also known as special interest group 3 (SIG 3) 'Training & Education', coordinates the bioinformatics training of de.NBI and the German ELIXIR node. The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers. Life scientists learn how to handle and analyze biological big data more effectively by applying tools, standards and compute services provided by de.NBI. Since 2015, more than 300 training courses were carried out with about 6,000 participants and these courses received recommendation rates of almost 90% (status as of July 2020). In addition to face-to-face training courses, online training was introduced on the de.NBI website in 2016 and guidelines for the preparation of e-learning material were established in 2018. In 2016, ELIXIR-DE joined the ELIXIR training platform. Here, the de.NBI / ELIXIR-DE training platform collaborates with ELIXIR in training activities, advertising training courses via TeSS and discussions on the exchange of data for training events essential for quality assessment on both the technical and administrative levels. The de.NBI training program trained thousands of scientists from Germany and beyond in many different areas of bioinformatics.

Bioinformatics for NGS-based metagenomics and the application to biogas research.

Metagenomics has proven to be one of the most important research fields for microbial ecology during the last decade. Starting from 16S rRNA marker gene analysis for the characterization of community compositions to whole metagenome shotgun sequencing which additionally allows for functional analysis, metagenomics has been applied in a wide spectrum of research areas. The cost reduction paired with the increase in the amount of data due to the advent of next-generation sequencing led to a rapidly growing demand for bioinformatic software in metagenomics. By now, a large number of tools that can be used to analyze metagenomic datasets has been developed. The Bielefeld-Gießen center for microbial bioinformatics as part of the German Network for Bioinformatics Infrastructure bundles and imparts expert knowledge in the analysis of metagenomic datasets, especially in research on microbial communities involved in anaerobic digestion residing in biogas reactors. In this review, we give an overview of the field of metagenomics, introduce into important bioinformatic tools and possible workflows, accompanied by application examples of biogas surveys successfully conducted at the Center for Biotechnology of Bielefeld University.

Omics Fusion - A Platform for Integrative Analysis of Omics Data.

We present Omics Fusion, a new web-based platform for integrative analysis of omics data. Omics Fusion provides a collection of new and established tools and visualization methods to support researchers in exploring omics data, validating results or understanding how to adjust experiments in order to make new discoveries. It is easily extendible and new visualization methods are added continuously. It is available for free under: https://fusion.cebitec.uni-bielefeld.de/.

GABI-DUPLO: a collection of double mutants to overcome genetic redundancy in Arabidopsis thaliana.

Owing to duplication events in its progenitor, more than 90% of the genes in the Arabidopsis thaliana genome are members of multigene families. A set of 2108 gene families, each consisting of precisely two unlinked paralogous genes, was identified in the nuclear genome of A. thaliana on the basis of sequence similarity. A systematic method for the creation of double knock-out lines for such gene pairs, designated as DUPLO lines, was established and 200 lines are now publicly available. Their initial phenotypic characterisation led to the identification of seven lines with defects that emerge only in the adult stage. A further six lines display seedling lethality and 23 lines were lethal before germination. Another 14 lines are known to show phenotypes under non-standard conditions or at the molecular level. Knock-out of gene pairs with very similar coding sequences or expression profiles is more likely to produce a mutant phenotype than inactivation of gene pairs with dissimilar profiles or sequences. High coding sequence similarity and highly similar expression profiles are only weakly correlated, implying that promoter and coding regions of these gene pairs display different degrees of diversification.