TY - JOUR A1 - Lopez-Arboleda, William Andres A1 - Reinert, Stephan A1 - Nordborg, Magnus A1 - Korte, Arthur T1 - Global genetic heterogeneity in adaptive traits JF - Molecular Biology and Evolution N2 - Understanding the genetic architecture of complex traits is a major objective in biology. The standard approach for doing so is genome-wide association studies (GWAS), which aim to identify genetic polymorphisms responsible for variation in traits of interest. In human genetics, consistency across studies is commonly used as an indicator of reliability. However, if traits are involved in adaptation to the local environment, we do not necessarily expect reproducibility. On the contrary, results may depend on where you sample, and sampling across a wide range of environments may decrease the power of GWAS because of increased genetic heterogeneity. In this study, we examine how sampling affects GWAS in the model plant species Arabidopsis thaliana. We show that traits like flowering time are indeed influenced by distinct genetic effects in local populations. Furthermore, using gene expression as a molecular phenotype, we show that some genes are globally affected by shared variants, whereas others are affected by variants specific to subpopulations. Remarkably, the former are essentially all cis-regulated, whereas the latter are predominately affected by trans-acting variants. Our result illustrate that conclusions about genetic architecture can be extremely sensitive to sampling and population structure. KW - evolutionary genomics KW - GWAS KW - regulation of gene expression KW - genetic architecture Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-270410 VL - 38 IS - 11 ER - TY - THES A1 - Lewerentz, Anne F. T1 - Spatiotemporal dynamics of freshwater macrophytes in Bavarian lakes under environmental change T1 - Raum-zeitliche Dynamik der Makrophyten in bayerischen Seen unter sich ändernden Umweltbedingungen N2 - Macrophytes are key components of freshwater ecosystems because they provide habitat, food, and improve the water quality. Macrophyte are vulnerable to environmental change as their physiological processes depend on changing environmental factors, which themselves vary within a geographical region and along lake depth. Their spatial distribution is not well understood and their importance is publicly little-known. In this thesis, I have investigated the spatiotemporal dynamics of freshwater macrophytes in Bavarian lakes to understand their diversity pattern along different scales and to predict and communicate potential consequences of global change on their richness. In the introduction (Chapter 1), I provide an overview of the current scientific knowledge of the species richness patterns of macrophytes in freshwater lakes, the influences of climate and land-use change on macrophyte growth, and different modelling approaches of macrophytes. The main part of the thesis starts with a study about submerged and emergent macrophyte species richness in natural and artificial lakes of Bavaria (Chapter 2). By analysing publicly available monitoring data, I have found a higher species richness of submerged macrophytes in natural lakes than in artificial lakes. Furthermore, I showed that the richness of submerged species is better explained by physio-chemical lake parameters than the richness of emergent species. In Chapter 3, I considered that submerged macrophytes grow along a depth gradient that provides a sharp environmental gradient on a short spatial scale. This study is the first comparative assessment of the depth diversity gradient (DDG) of macrophytes. I have found a hump-shaped pattern of different diversity components. Generalised additive mixed-effect models indicate that the shape of the DDG is influenced mainly by light quality, light quantity, layering depth, and lake area. I could not identify a general trend of the DDG within recent years, but single lakes show trends leading into different directions. In Chapter 4, I used a mechanistic eco-physiological model to explore changes in the distribution of macrophyte species richness under different scenarios of environmental conditions across lakes and with depths. I could replicate the hump-shaped pattern of potential species richness along depth. Rising temperature leads to increased species richness in all lake types, and depths. The effect of turbidity and nutrient change depends on depth and lake type. Traits that characterise “loser species” under increased turbidity and nutrients are a high light consumption and a high sensibility to disturbances. “Winner species” can be identified by a high biomass production. In Chapter 5, I discuss the image problem of macrophytes. Unawareness, ignorance, and the poor accessibility of macrophytes can lead to conflicts of use. I assumed that an increased engagement and education could counteract this. Because computer games can transfer knowledge interactively while creating an immersive experience, I present in the chapter an interactive single-player game for children. Finally, I discuss the findings of this thesis in the light of their implications for ecological theory, their implications for conservation, and future research ideas (Chapter 6). The findings help to understand the regional distribution and the drivers of macrophyte species richness. By applying eco-physiological models, multiple environmental shaping factors for species richness were tested and scenarios of climate and land-use change were explored. N2 - Makrophyten sind wichtige Bestandteile des Lebensraums See. Sie schaffen Habitate und verbessern die Wasserqualität, sind in der Öffentlichkeit jedoch kaum bekannt. Makrophyten sind sehr anfällig für Umweltveränderungen, da ihre physiologischen Prozesse von Umweltfaktoren abhängen, die ihrerseits innerhalb einer geografischen Region und entlang der Seetiefe variieren. Diese Arbeit untersucht die räumlich-zeitliche Dynamik von Makrophyten in bayerischen Seen, um die Muster ihrer Artenvielfalt auf verschiedenen Skalen zu verstehen und um die Folgen von Klima- und Landnutzungswandel auf ihre Artenvielfalt zu untersuchen. Die Einleitung (Kapitel 1) gibt einen Überblick über den aktuellen Wissensstand zur Artenvielfalt von Makrophyten in Seen, zu Einflüssen von Klima- und Landnutzungswandel auf das Wachstum von Makrophyten, sowie zu verschiedenen Modellierungsansätzen von Makrophyten. Der Hauptteil der Arbeit beginnt mit der Analyse (Kapitel 2) der submersen und emergenten Makrophytenvielfalt in natürlichen und künstlichen Seen Bayerns. Mit Hilfe von öffentlich zugänglichen Monitoringdaten konnte gezeigt werden, dass es mehr submerser Makrophyten in natürlichen Seen als in künstlichen Seen gibt und dass sich die Anzahl an submersen Makrophyten je See besser mit physiko-chemischen Parametern erklären lässt als die von emergenten Arten. In Kapitel 3 wird die Verteilung der Artenvielfalt von submersen Makrophyten entlang des Tiefengradienten be-trachtet. Entlang der Tiefe ändern sich physikalisch-chemische Parameter auf einer kurzen räumli-chen Skala. Diese Studie ist die erste vergleichende Untersuchung des Tiefen-Diversitätsgradienten (DDG) von Makrophyten. Der DDG von verschiedenen Diversitätskomponenten verläuft buckelförmig. „Generalised additive mixed-effect models“ deuten darauf hin, dass die Form des DDG hauptsächlich von der Lichtqualität, der Lichtmenge, der Schichtungstiefe und der Fläche des Sees beeinflusst wird. Die Daten zeigen keine verallgemeinerbare Veränderung des höckerförmigen DDGs in den letzten Jahren. In einzelnen Seen gibt es jedoch Trends. In Kapitel 4 wird mit einem mechanistischen, ökophysiologischen Makrophyten-Wachstums-Modell (MGM) die potenziellen Veränderungen in der Verbreitung von Makrophyten unter verschiedenen Klima- und Landnutzungsszenarien untersucht. Durch die Anwendung von MGM konnte das höckerförmige Muster des DDG repliziert werden. Unterschiede zum kartierten Artenreichtum lassen sich wahrscheinlich durch nicht modellierte Prozesse wie Konkurrenz und Umweltheterogenität innerhalb des Sees erklären. Steigende Temperaturen führen zu einer Zunahme des Artenreichtums in allen Seetypen, Artengruppen und Tiefen. Die Auswirkungen von Trübungen und Nährstoffveränderungen hängen von der Tiefe und dem Seetyp ab. Merkmale, die unter erhöhter Trübung und Nährstoffgehalt "Verlierer-Arten" kennzeichnen, sind ein hoher Lichtverbrauch und eine hohe Störungsempfindlichkeit, während "Gewinner-Arten" diejenigen sind, die eine hohe Biomasseproduktion aufweisen. Kapitel 5 stellt das Imageproblem von Makrophyten dar. Unkenntnis, Unwissenheit und die schlechte Zugänglichkeit können zu Nutzungskonflikten führen. Es ist anzunehmen, dass ein verstärktes Engagement und Aufklärung dem entgegenwirken könnten. Da Computerspiele eine Möglichkeit sind, Wissen interaktiv zu transportieren und ein immersives Erlebnis zu schaffen, wird in diesem Kapitel das entwickelte Spiel bioDIVERsity vorgestellt. Abschließend werden die Ergebnisse im Hinblick auf ihre Bedeutung für ökologische Theorien, ihre Auswirkungen auf den Naturschutz und zukünftige Forschungsideen diskutiert (Kapitel 6). Die Ergebnisse dieser Arbeit tragen dazu bei, die regionale Verbreitung und die Treiber einer oft übersehenen Artengruppe zu verstehen. Durch die Anwendung öko-physiologischer Modelle konnten verschiedene Einflussfaktoren auf den Artenreichtum von Makrophyten getestet und Szenarien von Klima- und Landnutzungswandel erforscht werden. KW - Ökologie KW - Makrophyten KW - Biologisches Modell KW - Klimaänderung KW - Artenreichtum KW - Ecology KW - Macrophytes KW - Global change KW - Species richness KW - Mechanistic model Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-287700 ER - TY - JOUR A1 - Sahlol, Ahmed T. A1 - Kollmannsberger, Philip A1 - Ewees, Ahmed A. T1 - Efficient Classification of White Blood Cell Leukemia with Improved Swarm Optimization of Deep Features JF - Scientific Reports N2 - White Blood Cell (WBC) Leukaemia is caused by excessive production of leukocytes in the bone marrow, and image-based detection of malignant WBCs is important for its detection. Convolutional Neural Networks (CNNs) present the current state-of-the-art for this type of image classification, but their computational cost for training and deployment can be high. We here present an improved hybrid approach for efficient classification of WBC Leukemia. We first extract features from WBC images using VGGNet, a powerful CNN architecture, pre-trained on ImageNet. The extracted features are then filtered using a statistically enhanced Salp Swarm Algorithm (SESSA). This bio-inspired optimization algorithm selects the most relevant features and removes highly correlated and noisy features. We applied the proposed approach to two public WBC Leukemia reference datasets and achieve both high accuracy and reduced computational complexity. The SESSA optimization selected only 1 K out of 25 K features extracted with VGGNet, while improving accuracy at the same time. The results are among the best achieved on these datasets and outperform several convolutional network models. We expect that the combination of CNN feature extraction and SESSA feature optimization could be useful for many other image classification tasks. KW - Acute lymphocytic leukaemia KW - Computer science KW - Image processing Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-229398 VL - 10 IS - 1 ER - TY - JOUR A1 - Marquardt, André A1 - Solimando, Antonio Giovanni A1 - Kerscher, Alexander A1 - Bittrich, Max A1 - Kalogirou, Charis A1 - Kübler, Hubert A1 - Rosenwald, Andreas A1 - Bargou, Ralf A1 - Kollmannsberger, Philip A1 - Schilling, Bastian A1 - Meierjohann, Svenja A1 - Krebs, Markus T1 - Subgroup-Independent Mapping of Renal Cell Carcinoma — Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries JF - Frontiers in Oncology N2 - Background: Renal cell carcinoma (RCC) is divided into three major histopathologic groups—clear cell (ccRCC), papillary (pRCC) and chromophobe RCC (chRCC). We performed a comprehensive re-analysis of publicly available RCC datasets from the TCGA (The Cancer Genome Atlas) database, thereby combining samples from all three subgroups, for an exploratory transcriptome profiling of RCC subgroups. Materials and Methods: We used FPKM (fragments per kilobase per million) files derived from the ccRCC, pRCC and chRCC cohorts of the TCGA database, representing transcriptomic data of 891 patients. Using principal component analysis, we visualized datasets as t-SNE plot for cluster detection. Clusters were characterized by machine learning, resulting gene signatures were validated by correlation analyses in the TCGA dataset and three external datasets (ICGC RECA-EU, CPTAC-3-Kidney, and GSE157256). Results: Many RCC samples co-clustered according to histopathology. However, a substantial number of samples clustered independently from histopathologic origin (mixed subgroup)—demonstrating divergence between histopathology and transcriptomic data. Further analyses of mixed subgroup via machine learning revealed a predominant mitochondrial gene signature—a trait previously known for chRCC—across all histopathologic subgroups. Additionally, ccRCC samples from mixed subgroup presented an inverse correlation of mitochondrial and angiogenesis-related genes in the TCGA and in three external validation cohorts. Moreover, mixed subgroup affiliation was associated with a highly significant shorter overall survival for patients with ccRCC—and a highly significant longer overall survival for chRCC patients. Conclusions: Pan-RCC clustering according to RNA-sequencing data revealed a distinct histology-independent subgroup characterized by strengthened mitochondrial and weakened angiogenesis-related gene signatures. Moreover, affiliation to mixed subgroup went along with a significantly shorter overall survival for ccRCC and a longer overall survival for chRCC patients. Further research could offer a therapy stratification by specifically addressing the mitochondrial metabolism of such tumors and its microenvironment. KW - kidney cancer KW - pan-RCC KW - machine learning KW - mitochondrial DNA KW - mtDNA KW - mTOR Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232107 SN - 2234-943X VL - 11 ER - TY - JOUR A1 - Marquardt, André A1 - Landwehr, Laura-Sophie A1 - Ronchi, Cristina L. A1 - di Dalmazi, Guido A1 - Riester, Anna A1 - Kollmannsberger, Philip A1 - Altieri, Barbara A1 - Fassnacht, Martin A1 - Sbiera, Silviu T1 - Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning JF - Cancers N2 - Simple Summary Using a visual-based clustering method on the TCGA RNA sequencing data of a large adrenocortical carcinoma (ACC) cohort, we were able to classify these tumors in two distinct clusters largely overlapping with previously identified ones. As previously shown, the identified clusters also correlated with patient survival. Applying the visual clustering method to a second dataset also including benign adrenocortical samples additionally revealed that one of the ACC clusters is more closely located to the benign samples, providing a possible explanation for the better survival of this ACC cluster. Furthermore, the subsequent use of machine learning identified new possible biomarker genes with prognostic potential for this rare disease, that are significantly differentially expressed in the different survival clusters and should be further evaluated. Abstract Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several “multiple-omics” studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC. KW - adrenocortical carcinoma KW - in silico analysis KW - machine learning KW - bioinformatic clustering KW - biomarker prediction Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-246245 SN - 2072-6694 VL - 13 IS - 18 ER - TY - JOUR A1 - Peters, Birte A1 - Keller, Alexander A1 - Leonhardt, Sara Diana T1 - Diets maintained in a changing world: Does land-use intensification alter wild bee communities by selecting for flexible generalists? JF - Ecology and evolution N2 - Biodiversity loss, as often found in intensively managed agricultural landscapes, correlates with reduced ecosystem functioning, for example, pollination by insects, and with altered plant composition, diversity, and abundance. But how does this change in floral resource diversity and composition relate to occurrence and resource use patterns of trap-nesting solitary bees? To better understand the impact of land-use intensification on communities of trap-nesting solitary bees in managed grasslands, we investigated their pollen foraging, reproductive fitness, and the nutritional quality of larval food along a land-use intensity gradient in Germany. We found bee species diversity to decrease with increasing land-use intensity irrespective of region-specific community compositions and interaction networks. Land use also strongly affected the diversity and composition of pollen collected by bees. Lack of suitable pollen sources likely explains the absence of several bee species at sites of high land-use intensity. The only species present throughout, Osmia bicornis (red mason bee), foraged on largely different pollen sources across sites. In doing so, it maintained a relatively stable, albeit variable nutritional quality of larval diets (i.e., protein to lipid (P:L) ratio). The observed changes in bee–plant pollen interaction patterns indicate that only the flexible generalists, such as O. bicornis, may be able to compensate the strong alterations in floral resource landscapes and to obtain food of sufficient quality through readily shifting to alternative plant sources. In contrast, other, less flexible, bee species disappear. KW - bee decline KW - biodiversity exploratories KW - foraging KW - metabarcoding KW - pollen nutrients KW - solitary bees Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-312786 SN - 2045-7758 VL - 12 IS - 5 ER - TY - JOUR A1 - Berger, Nathalie A1 - Demolombe, Vincent A1 - Hem, Sonia A1 - Rofidal, Valérie A1 - Steinmann, Laura A1 - Krouk, Gabriel A1 - Crabos, Amandine A1 - Nacry, Philippe A1 - Verdoucq, Lionel A1 - Santoni, Véronique T1 - Root membrane ubiquitinome under short-term osmotic stress JF - International Journal of Molecular Sciences N2 - Osmotic stress can be detrimental to plants, whose survival relies heavily on proteomic plasticity. Protein ubiquitination is a central post-translational modification in osmotic-mediated stress. In this study, we used the K-Ɛ-GG antibody enrichment method integrated with high-resolution mass spectrometry to compile a list of 719 ubiquitinated lysine (K-Ub) residues from 450 Arabidopsis root membrane proteins (58% of which are transmembrane proteins), thereby adding to the database of ubiquitinated substrates in plants. Although no ubiquitin (Ub) motifs could be identified, the presence of acidic residues close to K-Ub was revealed. Our ubiquitinome analysis pointed to a broad role of ubiquitination in the internalization and sorting of cargo proteins. Moreover, the simultaneous proteome and ubiquitinome quantification showed that ubiquitination is mostly not involved in membrane protein degradation in response to short osmotic treatment but that it is putatively involved in protein internalization, as described for the aquaporin PIP2;1. Our in silico analysis of ubiquitinated proteins shows that two E2 Ub-conjugating enzymes, UBC32 and UBC34, putatively target membrane proteins under osmotic stress. Finally, we revealed a positive role for UBC32 and UBC34 in primary root growth under osmotic stress. KW - aquaporin KW - mass spectrometry KW - osmotic stress KW - ubiquitination Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-284003 SN - 1422-0067 VL - 23 IS - 4 ER - TY - JOUR A1 - Vedder, Daniel A1 - Lens, Luc A1 - Martin, Claudia A. A1 - Pellikka, Petri A1 - Adhikari, Hari A1 - Heiskanen, Janne A1 - Engler, Jan O. A1 - Sarmento Cabral, Juliano T1 - Hybridization may aid evolutionary rescue of an endangered East African passerine JF - Evolutionary Applications N2 - Abstract Introgressive hybridization is a process that enables gene flow across species barriers through the backcrossing of hybrids into a parent population. This may make genetic material, potentially including relevant environmental adaptations, rapidly available in a gene pool. Consequently, it has been postulated to be an important mechanism for enabling evolutionary rescue, that is the recovery of threatened populations through rapid evolutionary adaptation to novel environments. However, predicting the likelihood of such evolutionary rescue for individual species remains challenging. Here, we use the example of Zosterops silvanus, an endangered East African highland bird species suffering from severe habitat loss and fragmentation, to investigate whether hybridization with its congener Zosterops flavilateralis might enable evolutionary rescue of its Taita Hills population. To do so, we employ an empirically parameterized individual‐based model to simulate the species' behaviour, physiology and genetics. We test the population's response to different assumptions of mating behaviour and multiple scenarios of habitat change. We show that as long as hybridization does take place, evolutionary rescue of Z. silvanus is likely. Intermediate hybridization rates enable the greatest long‐term population growth, due to trade‐offs between adaptive and maladaptive introgressed alleles. Habitat change did not have a strong effect on population growth rates, as Z. silvanus is a strong disperser and landscape configuration is therefore not the limiting factor for hybridization. Our results show that targeted gene flow may be a promising avenue to help accelerate the adaptation of endangered species to novel environments, and demonstrate how to combine empirical research and mechanistic modelling to deliver species‐specific predictions for conservation planning. KW - evolutionary rescue KW - habitat change KW - individual‐based model KW - introgressive hybridization KW - Taita Hills KW - Zosterops silvanus Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-287264 VL - 15 IS - 7 ER - TY - JOUR A1 - Marquardt, André A1 - Kollmannsberger, Philip A1 - Krebs, Markus A1 - Argentiero, Antonella A1 - Knott, Markus A1 - Solimando, Antonio Giovanni A1 - Kerscher, Alexander Georg T1 - Visual clustering of transcriptomic data from primary and metastatic tumors — dependencies and novel pitfalls JF - Genes N2 - Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n = 682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n = 616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters. KW - visual clustering KW - t-SNE KW - UMAP KW - transcriptomic analysis KW - cancer KW - metastasis Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-281872 SN - 2073-4425 VL - 13 IS - 8 ER - TY - JOUR A1 - Imhoff, Johannes F. A1 - Rahn, Tanja A1 - Künzel, Sven A1 - Keller, Alexander A1 - Neulinger, Sven C. T1 - Osmotic adaptation and compatible solute biosynthesis of phototrophic bacteria as revealed from genome analyses JF - Microorganisms N2 - Osmotic adaptation and accumulation of compatible solutes is a key process for life at high osmotic pressure and elevated salt concentrations. Most important solutes that can protect cell structures and metabolic processes at high salt concentrations are glycine betaine and ectoine. The genome analysis of more than 130 phototrophic bacteria shows that biosynthesis of glycine betaine is common among marine and halophilic phototrophic Proteobacteria and their chemotrophic relatives, as well as in representatives of Pirellulaceae and Actinobacteria, but are also found in halophilic Cyanobacteria and Chloroherpeton thalassium. This ability correlates well with the successful toleration of extreme salt concentrations. Freshwater bacteria in general lack the possibilities to synthesize and often also to take up these compounds. The biosynthesis of ectoine is found in the phylogenetic lines of phototrophic Alpha- and Gammaproteobacteria, most prominent in the Halorhodospira species and a number of Rhodobacteraceae. It is also common among Streptomycetes and Bacilli. The phylogeny of glycine-sarcosine methyltransferase (GMT) and diaminobutyrate-pyruvate aminotransferase (EctB) sequences correlate well with otherwise established phylogenetic groups. Most significantly, GMT sequences of cyanobacteria form two major phylogenetic branches and the branch of Halorhodospira species is distinct from all other Ectothiorhodospiraceae. A variety of transport systems for osmolytes are present in the studied bacteria. KW - genomes of photosynthetic bacteria KW - glycine betaine biosynthesis KW - ectoine biosynthesis KW - osmotic adaptation KW - phylogeny of osmolyte biosynthesis Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220161 SN - 2076-2607 VL - 9 IS - 1 ER -