Biology subjects

Scholz, S.

Publications and source records attributed to Scholz, S..

8 recordsLinked to original sources

bioRxiv2026

Unraveling emotional signatures: comparing physiological methods and algorithm-based recognition of spontaneous emotional facial expressions

Recognizing others emotions is central to social interaction. Traditional biological psychology infers emotional responding via laboratory measures, whereas contemporary computer vision algorithms claim to identify emotions unobtrusively from facial video. However, the validity of such algorithms for classifying spontaneous emotional responses occurring without explicit communicative intent remains debated. We compared established psychophysiological measures (EEG, facial EMG, EDA activity) with the open-source facial behavior toolkit OpenFace for classifying participants spontaneous responses during free viewing of happiness-inducing, disgust-inducing, and neutral pictures. Participants provided valence and arousal ratings and later selected the basic emotion that best matched their reaction which served as the classification criterion. Using within-participants single-trial support vector machine (SVM) classification, EEG achieved the highest accuracy (40%), followed by facial EMG (37%); OpenFace reached 36%. All methods except EDA exceeded chance performance (33.3%) and were lower compared to human raters (48%). Predictions declined slightly for across-participants SVMs, being at chance for OpenFace and EDA. The results indicate that in principle both, psychophysiological measures and video-derived facial action units, can capture diagnostically relevant aspects of emotional responding during picture viewing, but that their performance is limited when expressions are spontaneous and not produced for communicative purposes. Inter-individual variability in expressivity and physiological responding likely contributes to these limitations and should be considered when deploying automatic emotion recognition in research or applied settings.

neuroscience↗

bioRxiv2025

Trait-dependent diversification and spatio-ecological limits drive angiosperm diversity unevenness across the Canary Islands archipelago

Island biotas often show highly uneven species richness among lineages, influenced by clade age, diversification rates, and/or spatio-ecological limits. However, disentangling these drivers has been challenging due to the lack of comprehensive datasets across multiple lineages in the same geographical arena. The flora of the Canary Islands includes hundreds of plant lineages with contrasting species richness and harbours the highest number of species that evolved their woodiness in-situ ("insular woodiness"). Here, we present a phylogenomic reconstruction for Canary Island angiosperms and show that diversity unevenness in the flora is not driven by lineage age but by trait-dependent diversification and spatio-ecological limits. Our phylogenomic dataset, based on 1,244 newly generated and 501 published DNA sequences for 669 Canary Island species and 771 closely related mainland taxa, allows us to simultaneously study 435 plant lineages ([~]50% of total). Applying dynamic stochastic modelling, we find the flora is shaped by high extinction and colonisation rates, maintaining a macroevolutionary equilibrium. Additionally, insular woody lineages exhibit higher diversification rates than the remaining flora. Our results suggest the uneven diversity of a highly dynamic insular region can be explained by the interaction of trait evolution and ecological constraints, providing insights into island biodiversity dynamics.

evolutionary biology↗

bioRxiv2024

Integer programming framework for pangenome-based genome inference

Affordable genotyping methods are essential in genomics. Commonly used genotyping methods primarily support single nucleotide variants and short indels but neglect structural variants. Additionally, accuracy of read alignments to a reference genome is unreliable in highly polymorphic and repetitive regions, further impacting genotyping performance. Recent works highlight the advantage of haplotype-resolved pangenome graphs in addressing these challenges. Building on these developments, we propose a rigorous alignment-free genotyping framework. Our formulation seeks a path through the pangenome graph that maximizes the matches between the path and substrings of sequencing reads (e.g., k-mers) while minimizing recombination events (haplotype switches) along the path. We prove that this problem is NP-Hard and develop efficient integer-programming solutions. We benchmarked the algorithm using downsampled short-read datasets from homozygous human cell lines with coverage ranging from 0.1x to 10x. Our algorithm accurately estimates complete major histocompatibility complex (MHC) haplotype sequences with small edit distances from the ground-truth sequences, providing a significant advantage over existing methods on low-coverage inputs. Although our algorithm is designed for haploid samples, we discuss future extensions to diploid samples. Implementationhttps://github.com/at-cg/PHI

bioinformatics↗

bioRxiv2024

Leveraging zebrafish embryo phenotypic observations to advance data-driven analyses in toxicology

Zebrafish have emerged as a central model organism in toxicological research. Zebrafish embryos are exempt from certain animal testing regulations which facilitates their use in toxicological testing. Next to the zebrafish embryo acute toxicity test (ZFET) according to the OECD TG 236, fish embryos are used in mechanistic investigations, chemical screenings, in ecotoxicology, and drug development. However, inconsistencies in the applied test protocols and the monitored endpoints in addition to a lack of standardized data formats, impede comprehensive meta-analyses and cross-study comparisons. To address these challenges, we developed the Integrated Effect Database for Toxicological Observations (INTOB), a comprehensive data management tool that standardizes collection of metadata and phenotypic observations using a controlled vocabulary. By incorporating data from more than 600 experiments into the database and subsequent comprehensive data analyses, we demonstrate its utility in improving the comparability and interoperability of toxicity data. Our results show that the ZFET can detect toxicity spanning seven orders of magnitude at the scale of effect concentrations. We also highlight the potential of read-across analyses based on morphological fingerprints and their connection to chemical modes of action, provide information on control variability of the ZFET, and highlight the importance of time for mechanistic understanding in chemical exposure-effect assessments. We provide the full FAIR dataset as well as the analysis workflow and demonstrate how professional data management, as enabled with INTOB, marks a significant advancement by offering a comprehensive framework for the systematic use of zebrafish embryo toxicity data, thus paving the way for more reliable, data-driven chemical risk assessment. SynopsisThis article shows how a novel data management tool for zebrafish embryo toxicity data advances comparative chemical risk assessment by enhancing data and metadata standardization, comparability, and cross-study analyses.

pharmacology and toxicology↗

bioRxiv2022

Complete sequences of six Major Histocompatibility Complex haplotypes, including all the major MHC class II structures

Accurate and comprehensive immunogenetic reference panels are key to the successful implementation of population-scale immunogenomics. The 5Mbp Major Histocompatibility Complex (MHC) is the most polymorphic region of the human genome and associated with multiple immune-mediated diseases, transplant matching and therapy responses. Analysis of MHC genetic variation is severely complicated by complex patterns of sequence variation, linkage disequilibrium and a lack of fully resolved MHC reference haplotypes, increasing the risk of spurious findings on analyzing this medically important region. Integrating Illumina and ultra-long Nanopore sequencing as well as bespoke bioinformatics, we completed five of the alternative MHC reference haplotypes of the current (B38) build of the human reference genome and added one other. The six assembled MHC haplotypes encompass the DR1 and DR4 haplotype structures in addition to the previously completed DR2 and DR3, as well as six distinct classes of the structurally variable C4 region. Analysis of the assembled haplotypes showed that MHC class II sequence structures, including repeat element positions, are generally conserved within the DR haplotype supergroups, and that sequence diversity peaks in three regions around HLA-A, HLA-B+C, and the HLA class II genes. Demonstrating the potential for improved short-read analysis, the number of proper read pairs recruited to the MHC was found to be increased by 0.32% - 0.69% in a 1000 Genomes Project read re-mapping experiment with seven diverse samples. Furthermore, the assembled haplotypes can serve as references for the community and provide the basis of a structurally accurate genotyping graph of the complete MHC region.

genomics↗

bioRxiv2022

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Recent experiments have shown that in addition to control by cis regulatory elements, the local chromosomal context of a gene also has a profound impact on its transcription. Although this chromosome-position dependent expression variation has been empirically mapped at high-resolution, the underlying causes of the variation have not been elucidated. Here, we demonstrate that 1 kb of flanking, non-coding synthetic sequences with a low frequency of guanosine and cytosine (GC) can dramatically reduce reporter expression compared to neutral and high GC-content flanks in E. coli. Despite the strong reduction in the maximal expression level from the fully-induced reporter, low GC synthetic flanks do not affect the time required to reach the maximal expression level after induction. Expression of the reporter construct is also affected by proximity to highly expressed ribosomal RNA operons depending on the relative orientation of transcription despite being insulated by strong transcriptional terminators, in a manner consistent with supercoiling competition. Overall, we demonstrate key determinants of transcriptional propensity that appear to act as tunable modulators of transcription, independent of regulatory sequences such as the promoter. These findings provide insight into the regulation of naturally occurring genes and specific rules for optimizing control of synthetic biology constructs.

systems biology↗

bioRxiv2018

The AGC protein kinase UNICORN controls planar growth by attenuating PDK1 in Arabidopsis thaliana

Tissue morphogenesis critically depends on the coordination of cellular growth patterns. In plants, many organs consist of clonally distinct cell layers, such as the epidermis, whose cells undergo divisions that are oriented along the plane of the layer. The developmental control of such planar growth is poorly understood. We have previously identified the Arabidopsis AGCVIII-class protein kinase UNICORN (UCN) as a central regulator of this process. Plants lacking UCN activity show spontaneous formation of ectopic multicellular protrusions in integuments and malformed petals indicating that UCN suppresses uncontrolled growth in those tissues. In the current model UCN regulates planar growth of integuments in part by directly repressing the putative transcription factor ABERRANT TESTA SHAPE (ATS). Here we report on the identification of 3-PHOSPHOINOSITIDE-DEPENDENT PROTEIN KINASE 1 (PDK1) as a novel factor involved in UCN-mediated growth control. PDK1 constitutes a basic component of signaling mediated by AGC protein kinases throughout eukaryotes. Arabidopsis PDK1 is implied in stress responses and growth promotion. Here we show that loss-of-function mutations in PDK1 suppress aberrant growth in integuments and petals of ucn mutants. Additional genetic, in vitro, and cell biological data support the view that UCN functions by repressing PDK1. Furthermore, our data indicate that PDK1 is indirectly required for deregulated growth caused by ATS overexpression. Our findings support a model proposing that UCN suppresses ectopic growth in integuments through two independent processes: the attenuation of the protein kinase PDK1 in the cytoplasm and the repression of the transcription factor ATS in the nucleus.\n\nAuthor SummaryPlant organs, such as petals or roots, are composites of distinct cell layers. As a rule, cells making up a layer, for example the epidermis, the outermost layer of a tissue, divide \"within the plane\" of the layer. This cellular behavior results in the two-dimensional sheet-like or planar growth of the cell layer. The mechanism orchestrating such a growth pattern is poorly understood. In particular, it is unclear how uncontrolled and \"out-of-plane\" growth is avoided. Here we provide insight into this process. Our data indicate that higher than normal activity of a central regulator of growth and stress responses results in wavy and malformed petals and in protrusion-like aberrant outgrowths in the tissue that will develop into the seed coat. It is therefore important to keep this factor in check to allow proper formation of those tissues. We further show that a protein called UNICORN attenuates the activity of this regulator thereby ensuring the sheet-like growth of young petals or the developing seed coat.

plant biology↗

bioRxiv2018

Heritability and genetic variance of dementia with Lewy bodies

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinsons disease (PD) or Alzheimers disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

neuroscience↗