Background Lacerta viridis and Lacerta bilineata are sister species of European green lizards (eastern and western clades, respectively) that, until recently, were grouped together as the L. viridis complex. Genetic incompatibilities were observed between lacertid populations through crossing experiments, which led to the delineation of two separate species within the L. viridis complex. The population history of these sister species and processes driving divergence are unknown. We constructed the first high-quality de novo genome assemblies for both L. viridis and L. bilineata through Illumina and PacBio sequencing, with annotation support provided from transcriptome sequencing of several tissues. To estimate gene flow between the two species and identify factors involved in reproductive isolation, we studied their evolutionary history, identified genomic rearrangements, detected signatures of selection on non-coding RNA, and on protein-coding genes. Findings Here we show that gene flow was primarily unidirectional from L. bilineata to L. viridis after their split at least 1.15 million years ago. We detected positive selection of the non-coding repertoire; mutations in transcription factors; accumulation of divergence through inversions; selection on genes involved in neural development, reproduction, and behavior, as well as in ultraviolet-response, possibly driven by sexual selection, whose contribution to reproductive isolation between these lacertid species needs to be further evaluated. Conclusion The combination of short and long sequence reads resulted in one of the most complete lizard genome assemblies. The characterization of a diverse array of genomic features provided valuable insights into the demographic history of divergence among European green lizards, as well as key species differences, some of which are candidates that could have played a role in speciation. In addition, our study generated valuable genomic resources that can be used to address conservation-related issues in lacertids.

B-cell maturation occurs in several steps and requires constant stimulus for its continuing development. From the emergence of the pre-B-cell receptor, signal transduction stimulates and supports B-cell development. Current viewpoints indicate that both positive selection pressure for autoantigens and tonic signaling constitutively stimulate B-cell maturation. In this work, we tested for the presence of a putative DNA binding site in a variable gene segment in a germline configuration, independently of VDJ recombination. After a survey of the public antibody databases, we chose a single mouse heavy variable gene segment that is highly represented in anti-nucleic acid antibodies and tested it for ssDNA binding. A phage display approach was used to search for intrinsic binding to oligo deoxythymidine. The results revealed that binding to an antigen can be influenced by the use of a specific DNA binding V gene segment. Our data support the idea that some variable genes have intrinsic reactivity towards specific types of endogenous autoantigens, and this property may contribute to the establishment of the immature B-cell repertoire.

With the discovery of increasingly more functional noncoding RNAs (ncRNAs), it becomes eminent to more strongly consider them as important players during species evolution. Although tests for negative selection of ncRNAs already exist since the beginning of this century, the SSS-test is the first one for also investigating positive selection. When analyzing selection in ncRNAs, it should be taken into account that selection pressures can independently act on sequence and structure. We applied the SSS-test to explore the evolution of ncRNAs in primates and identified more than 100 long noncoding RNAs (lncRNAs) that might evolve under positive selection in humans. With this test, it is now possible to more thoroughly include ncRNAs into evolutionary studies.

BackgroundLong non-coding RNAs (lncRNAs) play an important role in regulating gene expression and are thus important for determining phenotypes. Most attempts to measure selection in lncRNAs have focused on the primary sequence. The majority of small RNAs and at least some parts of lncRNAs must fold into specific structures to perform their biological function. Comprehensive assessments of selection acting on RNAs therefore must also encompass structure. Selection pressures acting on the structure of non-coding genes can be detected within multiple sequence alignments. Approaches of this type, however, have so far focused on negative selection. Thus, a computational method for identifying ncRNAs under positive selection is needed.ResultsWe introduce the SSS-test (test for Selection on Secondary Structure) to identify positive selection and thus adaptive evolution. Benchmarks with biological as well as synthetic controls yield coherent signals for both negative and positive selection, demonstrating the functionality of the test. A survey of a lncRNA collection comprising 15,443 families resulted in 110 candidates that appear to be under positive selection in human. In 26 lncRNAs that have been associated with psychiatric disorders we identified local structures that have signs of positive selection in the human lineage.ConclusionsIt is feasible to assay positive selection acting on RNA secondary structures on a genome-wide scale. The detection of human-specific positive selection in lncRNAs associated with cognitive disorder provides a set of candidate genes for further experimental testing and may provide insights into the evolution of cognitive abilities in humans.AvailabilityThe SSS-test and related software is available at: https://github.com/waltercostamb/SSS-test. The databases used in this work are available at: http://www.bioinf.uni-leipzig.de/Software/SSS-test/.Electronic supplementary materialThe online version of this article (10.1186/s12859-019-2711-y) contains supplementary material, which is available to authorized users.

The Human Accelerated Region 1 (HAR1) is the most rapidly evolving region in the human genome. It is part of two overlapping long non-coding RNAs, has a length of only 118 nucleotides and features 18 human specific changes compared to an ancestral sequence that is extremely well conserved across non-human primates. The human HAR1 forms a stable secondary structure that is strikingly different from the one in chimpanzee as well as other closely related species, again emphasizing its human-specific evolutionary history. This suggests that positive selection has acted to stabilize human-specific features in the ensemble of HAR1 secondary structures. To investigate the evolutionary history of the human HAR1 structure, we developed a computational model that evaluates the relative likelihood of evolutionary trajectories as a probabilistic version of a Hamiltonian path problem. The model predicts that the most likely last step in turning the ancestral primate HAR1 into the human HAR1 was exactly the substitution that distinguishes the modern human HAR1 sequence from that of Denisovan, an archaic human, providing independent support for our model. The MutationOrder software is available for download and can be applied to other instances of RNA structure evolution.

Bone-derived osteocalcin has been suggested to be a metabolic regulator. To scrutinize the relation between osteocalcin and peripheral insulin sensitivity, we analyzed changes in serum osteocalcin relative to changes in insulin sensitivity, low-grade inflammation, and bone mineral density following lifestyle-induced weight loss in individuals with metabolic syndrome (MetS). Participants with MetS were randomized to a weight loss program or to a control group. Before and after the 6-month intervention period, clinical and laboratory parameters and serum osteocalcin levels were determined. Changes in body composition were analyzed by dual-energy X-ray absorptiometry (DXA). In participants of the intervention group, weight loss resulted in improved insulin sensitivity and amelioration of inflammation. Increased serum levels of osteocalcin correlated inversely with BMI (r = −0.63; p< 0.001), total fat mass (r = −0.58, p < 0.001), total lean mass (r = −0.45, p < 0.001), C-reactive protein (CRP) (r = −0.37; p < 0.01), insulin (r = −0.4; p < 0.001), leptin (r = −0.53; p < 0.001), triglycerides (r = −0.42; p < 0.001), and alanine aminotransferase (ALAT) (r = −0.52; p < 0.001). Regression analysis revealed that osteocalcin was independently associated with changes in CRP but not with changes in insulin concentration, fat mass, or bone mineral density, suggesting that weight loss-induced higher serum osteocalcin is primarily associated with reduced inflammation.

Background Predicted RNA secondary structures are typically visualized using dot-plots for base pair binding probabilities and planar graphs for unique structures, such as the minimum free energy structure. These are however difficult to analyze simultaneously. Results This work introduces a compact unified view of the most stable conformation of an RNA secondary structure and its base pair probabilities, which is called the C ircular S econdary S tructure B ase P airs P robabilities Plot ( CS 2 BP 2 -Plot ). Along with our design we provide access to a web server implementation of our solution that facilitates pairwise comparison of short RNA (and DNA) sequences up to 200 base pairs. The web server first calculates the minimum free energy secondary structure and the base pair probabilities for up to 10 RNA or DNA sequences using RNAfold and then provides a two panel comparative view that includes CS 2 BP 2 -Plots along with the traditional graph, planar and circular diagrams obtained with VARNA. The CS 2 BP 2 -Plots include highlighting of the nucleotide differences between two selected sequences using ClustalW local alignments. We also provide descriptive statistics, dot-bracket secondary structure representations and ClustalW local alignments for compared sequences. Conclusions Using circular diagrams and colour and weight-coded arcs, we demonstrate how a single image can replace the state-of-the-art dual representations (dot-plots and minimum free energy structures) for base-pair probabilities of RNA secondary structures while allowing efficient exploration and comparison of different RNA conformations via a web server front end. With that, we provide the community, especially the biologically oriented, with an intuitive tool for ncRNA visualization. Web-server: https://nrcmonsrv01.nrc.ca/cs2bp2plot

Background Laboratory results are of central importance for clinical decision making. The time span between availability and review of results by clinicians is crucial to patient care. Clinical decision support systems (CDSS) are computational tools that can identify critical values automatically and help decrease treatment delay. Objective With this work, we aimed to implement and evaluate a CDSS that supports health care professionals and improves patient safety. In addition to our experiences, we also describe its main components in a general manner to make it applicable to a wide range of medical institutions and to empower colleagues to implement a similar system in their facilities. Methods Technical requirements must be taken into account before implementing a CDSS that performs laboratory diagnostics (labCDSS). These can be planned within the functional components of a reactive software agent, a computational framework for such a CDSS. Results We present AMPEL (Analysis and Reporting System for the Improvement of Patient Safety through Real-Time Integration of Laboratory Findings), a labCDSS that notifies health care professionals if a life-threatening medical condition is detected. We developed and implemented AMPEL at a university hospital and regional hospitals in Germany (University of Leipzig Medical Center and the Muldental Clinics in Grimma and Wurzen). It currently runs 5 different algorithms in parallel: hypokalemia, hypercalcemia, hyponatremia, hyperlactatemia, and acute kidney injury. Conclusions AMPEL enables continuous surveillance of patients. The system is constantly being evaluated and extended and has the capacity for many more algorithms. We hope to encourage colleagues from other institutions to design and implement similar CDSS using the theory, specifications, and experiences described in this work.