TADeus2: a web server facilitating the clinical diagnosis by pathogenicity assessment of structural variations disarranging 3D chromatin structure.

In recent years great progress has been made in identification of structural variants (SV) in the human genome. However, the interpretation of SVs, especially located in non-coding DNA, remains challenging. One of the reasons stems in the lack of tools exclusively designed for clinical SVs evaluation acknowledging the 3D chromatin architecture. Therefore, we present TADeus2 a web server dedicated for a quick investigation of chromatin conformation changes, providing a visual framework for the interpretation of SVs affecting topologically associating domains (TADs). This tool provides a convenient visual inspection of SVs, both in a continuous genome view as well as from a rearrangement's breakpoint perspective. Additionally, TADeus2 allows the user to assess the influence of analyzed SVs within flaking coding/non-coding regions based on the Hi-C matrix. Importantly, the SVs pathogenicity is quantified and ranked using TADA, ClassifyCNV tools and sampling-based P-value. TADeus2 is publicly available at https://tadeus2.mimuw.edu.pl.

Data-driven case fatality rate estimation for the primary lineage of SARS-CoV-2 in Poland.

After more than one and a half year since the COVID-19 pandemics outbreak the scientific world is constantly trying to understand its dynamics. In this paper of the case fatality rates (CFR) for COVID-19 we study the historic data regarding mortality in Poland during the first six months of pandemic, when no SARS-CoV-2 variants of concern were present among infected. To this end, we apply competing risk models to perform both uni- and multivariate analyses on specific subpopulations selected by different factors including the key indicators: age, sex, hospitalization. The study explores the case fatality rate to find out its decreasing trend in time. Furthermore, we describe the differences in mortality among hospitalized and other cases indicating a sudden increase of mortality among hospitalized cases at the end of the 2020 spring season. Exploratory and multivariate analysis revealed the real impact of each variable and besides the expected factors indicating increased mortality (age, comorbidities) we track more non-obvious indicators. Recent medical care as well as the identification of the source contact, independently of the comorbidities, significantly impact an individual mortality risk. As a result, the study provides a twofold insight into the COVID-19 mortality in Poland. On one hand we explore mortality in different groups with respect to different variables, on the other we indicate novel factors that may be crucial in reducing mortality. The later can be coped, e.g. by more efficient contact tracing and proper organization and management of the health care system to accompany those who need medical care independently of comorbidities or COVID-19 infection.

Revised time estimation of the ancestral human chromosome 2 fusion.

BACKGROUND: The reduction of the chromosome number from 48 in the Great Apes to 46 in modern humans is thought to result from the end-to-end fusion of two ancestral non-human primate chromosomes forming the human chromosome 2 (HSA2). Genomic signatures of this event are the presence of inverted telomeric repeats at the HSA2 fusion site and a block of degenerate satellite sequences that mark the remnants of the ancestral centromere. It has been estimated that this fusion arose up to 4.5 million years ago (Mya). RESULTS: We have developed an enhanced algorithm for the detection and efficient counting of the locally over-represented weak-to-strong (AT to GC) substitutions. By analyzing the enrichment of these substitutions around the fusion site of HSA2 we estimated its formation time at 0.9 Mya with a 95% confidence interval of 0.4-1.5 Mya. Additionally, based on the statistics derived from our algorithm, we have reconstructed the evolutionary distances among the Great Apes (Hominoidea). CONCLUSIONS: Our results shed light on the HSA2 fusion formation and provide a novel computational alternative for the estimation of the speciation chronology.

Low Entropy Sub-Networks Prevent the Integration of Metabolomic and Transcriptomic Data.

The constantly and rapidly increasing amount of the biological data gained from many different high-throughput experiments opens up new possibilities for data- and model-driven inference. Yet, alongside, emerges a problem of risks related to data integration techniques. The latter are not so widely taken account of. Especially, the approaches based on the flux balance analysis (FBA) are sensitive to the structure of a metabolic network for which the low-entropy clusters can prevent the inference from the activity of the metabolic reactions. In the following article, we set forth problems that may arise during the integration of metabolomic data with gene expression datasets. We analyze common pitfalls, provide their possible solutions, and exemplify them by a case study of the renal cell carcinoma (RCC). Using the proposed approach we provide a metabolic description of the known morphological RCC subtypes and suggest a possible existence of the poor-prognosis cluster of patients, which are commonly characterized by the low activity of the drug transporting enzymes crucial in the chemotherapy. This discovery suits and extends the already known poor-prognosis characteristics of RCC. Finally, the goal of this work is also to point out the problem that arises from the integration of high-throughput data with the inherently nonuniform, manually curated low-throughput data. In such cases, the over-represented information may potentially overshadow the non-trivial discoveries.

Molecular and clinical analyses of 16q24.1 duplications involving FOXF1 identify an evolutionarily unstable large minisatellite.

BACKGROUND: Point mutations or genomic deletions of FOXF1 result in a lethal developmental lung disease Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins. However, the clinical consequences of the constitutively increased dosage of FOXF1 are unknown. METHODS: Copy-number variations and their parental origin were identified using a combination of array CGH, long-range PCR, DNA sequencing, and microsatellite analyses. Minisatellite sequences across different species were compared using a gready clustering algorithm and genome-wide analysis of the distribution of minisatellite sequences was performed using R statistical software. RESULTS: We report four unrelated families with 16q24.1 duplications encompassing entire FOXF1. In a 4-year-old boy with speech delay and a café-au-lait macule, we identified an ~15 kb 16q24.1 duplication inherited from the reportedly healthy father, in addition to a de novo ~1.09 Mb mosaic 17q11.2 NF1 deletion. In a 13-year-old patient with autism and mood disorder, we found an ~0.3 Mb duplication harboring FOXF1 and an ~0.5 Mb 16q23.3 duplication, both inherited from the father with bipolar disorder. In a 47-year old patient with pyloric stenosis, mesenterium commune, and aplasia of the appendix, we identified an ~0.4 Mb duplication in 16q24.1 encompassing 16 genes including FOXF1. The patient transmitted the duplication to her daughter, who presented with similar symptoms. In a fourth patient with speech and motor delay, and borderline intellectual disability, we identified an ~1.7 Mb FOXF1 duplication adjacent to a large minisatellite. This duplication has a complex structure and arose de novo on the maternal chromosome, likely as a result of a DNA replication error initiated by the adjacent large tandem repeat. Using bioinformatic and array CGH analyses of the minisatellite, we found a large variation of its size in several different species and individuals, demonstrating both its evolutionarily instability and population polymorphism. CONCLUSIONS: Our data indicate that constitutional duplication of FOXF1 in humans is not associated with any pediatric lung abnormalities. We propose that patients with gut malrotation, pyloric or duodenal stenosis, and gall bladder agenesis should be tested for FOXF1 alterations. We suggest that instability of minisatellites greater than 1 kb can lead to structural variation due to DNA replication errors.

PhaseDancer: a novel targeted assembler of segmental duplications unravels the complexity of the human chromosome 2 fusion going from 48 to 46 chromosomes in hominin evolution.

Resolving complex genomic regions rich in segmental duplications (SDs) is challenging due to the high error rate of long-read sequencing. Here, we describe a targeted approach with a novel genome assembler PhaseDancer that extends SD-rich regions of interest iteratively. We validate its robustness and efficiency using a golden-standard set of human BAC clones and in silico-generated SDs with predefined evolutionary scenarios. PhaseDancer enables extension of the incomplete complex SD-rich subtelomeric regions of Great Ape chromosomes orthologous to the human chromosome 2 (HSA2) fusion site, informing a model of HSA2 formation and unravelling the evolution of human and Great Ape genomes.

Risk assessment of COVID-19 epidemic resurgence in relation to SARS-CoV-2 variants and vaccination passes.

The introduction of COVID-19 vaccination passes (VPs) by many countries coincided with the Delta variant fast becoming dominant across Europe. A thorough assessment of their impact on epidemic dynamics is still lacking. Here, we propose the VAP-SIRS model that considers possibly lower restrictions for the VP holders than for the rest of the population, imperfect vaccination effectiveness against infection, rates of (re-)vaccination and waning immunity, fraction of never-vaccinated, and the increased transmissibility of the Delta variant. Some predicted epidemic scenarios for realistic parameter values yield new COVID-19 infection waves within two years, and high daily case numbers in the endemic state, even without introducing VPs and granting more freedom to their holders. Still, suitable adaptive policies can avoid unfavorable outcomes. While VP holders could initially be allowed more freedom, the lack of full vaccine effectiveness and increased transmissibility will require accelerated (re-)vaccination, wide-spread immunity surveillance, and/or minimal long-term common restrictions.

National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.

BACKGROUND: During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland for the period from January through April 2021. METHODS: We evaluate probabilistic real-time predictions of confirmed cases and deaths from COVID-19 in Germany and Poland. These were issued by 15 different forecasting models, run by independent research teams. Moreover, we study the performance of combined ensemble forecasts. Evaluation of probabilistic forecasts is based on proper scoring rules, along with interval coverage proportions to assess calibration. The presented work is part of a pre-registered evaluation study. RESULTS: We find that many, though not all, models outperform a simple baseline model up to four weeks ahead for the considered targets. Ensemble methods show very good relative performance. The addressed time period is characterized by rather stable non-pharmaceutical interventions in both countries, making short-term predictions more straightforward than in previous periods. However, major trend changes in reported cases, like the rebound in cases due to the rise of the B.1.1.7 (Alpha) variant in March 2021, prove challenging to predict. CONCLUSIONS: Multi-model approaches can help to improve the performance of epidemiological forecasts. However, while death numbers can be predicted with some success based on current case and hospitalization data, predictability of case numbers remains low beyond quite short time horizons. Additional data sources including sequencing and mobility data, which were not extensively used in the present study, may help to improve performance.

We compare forecasts of weekly case and death numbers for COVID-19 in Germany and Poland based on 15 different modelling approaches. These cover the period from January to April 2021 and address numbers of cases and deaths one and two weeks into the future, along with the respective uncertainties. We find that combining different forecasts into one forecast can enable better predictions. However, case numbers over longer periods were challenging to predict. Additional data sources, such as information about different versions of the SARS-CoV-2 virus present in the population, might improve forecasts in the future.

Harvest time affects antioxidant capacity, total polyphenol and flavonoid content of Polish St John's wort's (Hypericum perforatum L.) flowers.

The polyphenol content and antioxidant capacity of hyperforin and hypericin-standardized H. perforatum L. extracts may vary due to the harvest time. In this work, ethanol and ethanol-water extracts of air-dried and lyophilized flowers of H. perforatum L., collected throughout a vegetation season in central Poland, were studied. Air-dried flowers extracts had higher polyphenol (371 mg GAE/g) and flavonoid (160 mg CAE/g) content, DPPH radical scavenging (1672 mg DPPH/g), ORAC (5214 µmol TE/g) and FRAP (2.54 mmol Fe2+/g) than lyophilized flowers extracts (238 mg GAE/g, 107 mg CAE/g, 1287 mg DPPH/g, 3313 µmol TE/g and 0.31 mmol Fe2+/g, respectively). Principal component analysis showed that the collection date influenced the flavonoid and polyphenol contents and FRAP of ethanol extracts, and DPPH and ORAC values of ethanol-water extracts. The ethanol extracts with the highest polyphenol and flavonoid content protected human erythrocytes against bisphenol A-induced damage. Both high field and benchtop NMR spectra of selected extracts, revealed differences in composition caused by extraction solvent and raw material collection date. Moreover, we have shown that benchtop NMR can be used to detect the compositional variation of extracts if the assignment of signals is done previously.

Truncated Robust Principal Component Analysis and Noise Reduction for Single Cell RNA Sequencing Data.

The development of single cell RNA sequencing (scRNA-seq) has enabled innovative approaches to investigating mRNA abundances. In our study, we are interested in extracting the systematic patterns of scRNA-seq data in an unsupervised manner; thus, we have developed two extensions of robust principal component analysis (RPCA). First, we present a truncated version of RPCA (tRPCA), which is much faster and memory efficient. Second, we introduce a noise reduction in tRPCA with L 2 regularization. Unlike RPCA that only considers a low-rank L and sparse S matrices, the proposed method can also extract a noise E matrix inherent in modern genomic data. We demonstrate its usefulness by applying our methods on the peripheral blood mononuclear cell scRNA-seq data. Particularly, the clustering of a low-rank L matrix showcases better classification of unlabeled single cells. Overall, the proposed variants are well suited for high-dimensional and noisy data that are routinely generated in genomics.

Inferring Molecular Processes Heterogeneity from Transcriptional Data.

RNA microarrays and RNA-seq are nowadays standard technologies to study the transcriptional activity of cells. Most studies focus on tracking transcriptional changes caused by specific experimental conditions. Information referring to genes up- and downregulation is evaluated analyzing the behaviour of relatively large population of cells by averaging its properties. However, even assuming perfect sample homogeneity, different subpopulations of cells can exhibit diverse transcriptomic profiles, as they may follow different regulatory/signaling pathways. The purpose of this study is to provide a novel methodological scheme to account for possible internal, functional heterogeneity in homogeneous cell lines, including cancer ones. We propose a novel computational method to infer the proportion between subpopulations of cells that manifest various functional behaviour in a given sample. Our method was validated using two datasets from RNA microarray experiments. Both experiments aimed to examine cell viability in specific experimental conditions. The presented methodology can be easily extended to RNA-seq data as well as other molecular processes. Moreover, it complements standard tools to indicate most important networks from transcriptomic data and in particular could be useful in the analysis of cancer cell lines affected by biologically active compounds or drugs.

Lethal lung hypoplasia and vascular defects in mice with conditional Foxf1 overexpression.

FOXF1 heterozygous point mutations and genomic deletions have been reported in newborns with the neonatally lethal lung developmental disorder, alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV). However, no gain-of-function mutations in FOXF1 have been identified yet in any human disease conditions. To study the effects of FOXF1 overexpression in lung development, we generated a Foxf1 overexpression mouse model by knocking-in a Cre-inducible Foxf1 allele into the ROSA26 (R26) locus. The mice were phenotyped using micro-computed tomography (micro-CT), head-out plethysmography, ChIP-seq and transcriptome analyses, immunohistochemistry, and lung histopathology. Thirty-five percent of heterozygous R26-Lox-Stop-Lox (LSL)-Foxf1 embryonic day (E)15.5 embryos exhibit subcutaneous edema, hemorrhages and die perinatally when bred to Tie2-cre mice, which targets Foxf1 overexpression to endothelial and hematopoietic cells. Histopathological and micro-CT evaluations revealed that R26Foxf1; Tie2-cre embryos have immature lungs with a diminished vascular network. Neonates exhibited respiratory deficits verified by detailed plethysmography studies. ChIP-seq and transcriptome analyses in E18.5 lungs identified Sox11, Ghr, Ednrb, and Slit2 as potential downstream targets of FOXF1. Our study shows that overexpression of the highly dosage-sensitive Foxf1 impairs lung development and causes vascular abnormalities. This has important clinical implications when considering potential gene therapy approaches to treat disorders of FOXF1 abnormal dosage, such as ACDMPV.