Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Mapping of Human DNA Replication by Optical Replication Mapping Supports a Stochastic Model of Eukaryotic Replication

DNA replication is regulated by the location and timing of replication initiation. Therefore, much effort has been invested in identifying and analyzing the sites of human replication initiation. However, the heterogeneous nature of eukaryotic replication kinetics and the low efficiency of individual initiation site utilization in metazoans has made mapping the location and timing of replication initiation in human cells difficult. A potential solution to the problem of human replication mapping is single-molecule analysis. However, current approaches do not provide the throughput required for genome-wide experiments. To address this challenge, we have developed Optical Replication Mapping (ORM), a high-throughput single-molecule approach to map newly replicated DNA, and used it to map early initiation events in human cells. The single-molecule nature of our data, and a total of more than 2000-fold coverage of the human genome on 27 million fibers averaging ~300 kb in length, allow us to identify initiation sites and their firing probability with high confidence. In particular, for the first time, we are able to measure genome-wide the absolute efficiency of human replication initiation. We find that the distribution of human replication initiation is consistent with inefficient, stochastic initiation of heterogeneously distributed potential initiation complexes enriched in accessible chromatin. In particular, we find sites of human replication initiation are not confined to well-defined replication origins but are instead distributed across broad initiation zones consisting of many initiation sites. Furthermore, we find no correlation of initiation events between neighboring initiation zones. Although most early initiation events occur in early-replicating regions of the genome, a significant number occur in late-replicating regions. The fact that initiation sites in typically late-replicating regions have some probability of firing in early S phase suggests that the major difference between initiation events in early and late replicating regions is their intrinsic probability of firing, as opposed to a qualitative difference in their firing-time distributions. Moreover, modeling of replication kinetics demonstrates that measuring the efficiency of initiation-zone firing in early S phase suffices to predict the average firing time of such initiation zones throughout S phase, further suggesting that the differences between the firing times of early and late initiation zones are quantitative, rather than qualitative. These observations are consistent with stochastic models of initiation-timing regulation and suggest that stochastic regulation of replication kinetics is a fundamental feature of eukaryotic replication, conserved from yeast to humans.
Multivariate associative patterns between the gut microbiota and large-scale brain network connectivity

Research on the gut-brain axis has accelerated substantially over the course of the last years. Many reviews have outlined the important implications of understanding the relation of the gut microbiota with human brain function and behavior. One substantial drawback in integrating gut microbiome and brain data is the lack of integrative multivariate approaches that enable capturing variance in both modalities simultaneously. To address this issue, we applied a linked independent component analysis (LICA) to microbiota and brain connectivity data. We analyzed data from 58 healthy females (mean age = 21.5 years). Magnetic Resonance Imaging data were acquired using resting state functional imaging data. The assessment of gut microbial composition from feces was based on sequencing of the V4 16S rRNA gene region. We used the LICA model to simultaneously factorize the subjects’ large-scale brain networks and microbiome relative abundance data into 10 independent components of spatial and abundance variation. LICA decomposition resulted in four components with non-marginal contribution of the microbiota data. The default mode network featured strongly in three components, whereas the two-lateralized fronto-parietal attention networks contributed to one component. The executive-control (with the default mode) network was associated to another component. We found the abundance of Prevotella genus was associated to the strength of expression of all networks, whereas Bifidobacterium was associated with the default mode and frontoparietal-attention networks. We provide the first exploratory evidence for multivariate associative patterns between the gut microbiota and brain network connectivity in healthy humans, taking into account the complexity of both systems.
Zoonotic viruses in three species of voles (Microtus spp.) from Poland

Rodents are known to be reservoir hosts for a plethora of zoonotic viruses and therefore play a significant role in the dissemination of these pathogens. We trapped three vole species (Microtus arvalis, M. oeconomus and M. agrestis) in N.E. Poland, all of which are widely distributed species in Europe, and, using immunofluorescence assays, we assessed serum samples for the presence of antibodies to hantaviruses, arenaviruses and cowpox viruses (CPXV). We detected antibodies against CPXV and Puumala virus (PUUV), overall seroprevalence of combined viral infections of 18.2% [10.5-29.3] and mostly attributed to CPXV. Antibodies to Tula hantavirus, typical for Microtus voles, are known to cross-react strongly with the PUUV antigen used in PUUV screening, but we detected only one PUUV/TULV cross-reaction in Microtus arvalis (1.3% [0.1-7.9]). We found antibodies against CPXV in all three Microtus spp. Seroprevalence was similar in all vole species. There were no significant differences in seroprevalence between the sexes and among host age categories. Our results contribute to the increasing understanding of CPXV abundance in voles in Europe, and confirm that CPXV circulates also in Microtus spp. voles in NE Poland.
Cell-line-specific network models of ER+ breast cancer identify PI3Kα inhibitor sensitivity factors and drug combinations

Durable control of invasive solid tumors necessitates identifying therapeutic resistance mechanisms and effective drug combinations. A promising approach to tackle the cancer drug resistance problem is to build mechanistic mathematical models of the signaling network of cancer cells, and explicitly model the dynamics of information flow through this network under distinct genetic conditions and in response to perturbations. In this work, we use a network-based mathematical model to identify sensitivity factors and drug combinations for the PI3Kα inhibitor Alpelisib, which was recently approved for ER+ PIK3CA mutant breast cancer. We experimentally validate the model-predicted efficacious combination of Alpelisib and BH3 mimetics (e.g. MCL1 inhibitors), and the reduced sensitivity to Alpelisib caused by FOXO3 knockdown, which is a novel potential resistance mechanism. Our experimental results showed cell-line-specific sensitivity to the combination of Alpelisib and BH3 mimetics, which was driven by the choice of BH3 mimetics. We find that cell lines were sensitive to the addition of either MCL1 inhibitor S63845 alone or in combination with BCL-XL/BCL-2 inhibitor Navitoclax, and that the need for the combination of both BH3 mimetics was predicted by the expression of BCL-XL. Based on these results, we developed cell-line specific network models that are able to recapitulate the observed differential response to Alpelisib and BH3 mimetics, and also incorporate the most recent knowledge on resistance and response to PI3Kα inhibitors. In conclusion, we present an approach based on the development, experimental testing, and refining of mathematical models, which we apply to the context of PI3Kα inhibitor drug resistance in breast cancer. Our approach predicted and validated PI3Kα inhibitor sensitivity factors (FOXO3 knockdown) and drug combinations (BH3 mimetics), and illustrates that network-based mathematical models can contribute to overcoming the challenge of cancer drug resistance.
Musashi regulates follicle stem cell maintenance and epithelial niche homeostasis in the Drosophila ovary

The Musashi (Msi) family of RNA-binding proteins regulate maintenance and differentiation of stem cells in multiple tissues of different species. Here, we use the powerful system of the Drosophila ovary to uncover an intrinsic requirement for Msi in both the maintenance of the follicle stem cell population and regulation of the architecture of the follicle stem cell niche. Further, we demonstrate an associated G2 lag of cycling somatic cells within the niche when Msi function is abrogated. Additionally, we show that Msi interaction with the Wnt pathway influences differentiation of anterior germarial escort cells from cells within the follicle stem cell niche region. This provides further evidence that escort cells can be derived from follicle stem/precursor cells and that Msi regulates lineage differentiation of follicle stem cell daughters.
Leptin signaling regulates physiological damage and host-pathogen cooperation

To combat infections, hosts employ a combination of antagonistic and cooperative defense strategies. The former refers to pathogen killing mediated by resistance mechanisms, while the latter refers to physiological defense mechanisms that promote host health during infection independent of pathogen killing, leading to an apparent cooperation between the host and the pathogen. Previous work has shown that leptin, a pleiotropic hormone that plays a central role in regulating appetite and energy metabolism, is indispensable for resistance mechanisms, while a role for leptin signaling in cooperative host-pathogen interactions remains unknown. Using a mouse model of Yersinia pseudotuberculosis (Yptb) infection, the causative agent of Far East scarlet-like fever, we unexpectedly found that genetic inhibition of leptin signaling conferred protection from Yptb infection due to increased host-pathogen cooperation rather than greater resistance defenses. The protection against Yptb infection was not due to differences in food consumption, lipolysis or fat mass. Furthermore, we found that the survival advantage was associated with increased liver damage and dysfunction. Our work reveals an additional level of complexity for the role of leptin in infection defense and suggests that in some contexts, in addition to tolerating the pathogen, tolerating organ damage and dysfunction is more beneficial for survival than preventing the damage.
Factors influencing the accuracy and precision in dating single gene trees

Molecular dating is the estimation of time from genetic sequences. Knowing the time of appearance of a taxon sets the evolutionary context by connecting it with past ecosystems and species. Genomes are made of thousands of genes which can be duplicated or horizontally transfered, thereby providing new material for adaptation. Knowing the time of appearance of genes would provide a context to understand adaptation at the genomic level. However, molecular clock inference faces uncertainty due to the variability of the rate of substitution between species, between genes and between sites within genes. While speciation dating can cope with this variability by concatenating multiple genes and using fossil calibrations, such solutions cannot be applied to date gene-specific events. This study aims at benchmarking the accuracy of molecular dating applied to single gene trees, and identify how it is affected by gene tree characteristics. We analyze 5204 alignments of genes from 21 Primates in which no duplication or loss is observed, as well as simulated alignments based on characteristics from Primates. The relaxed log-normal clock dating was performed with the bayesian program Beast2. From the empirical dataset, we find that the precision of dating decreases with shorter alignments, high rate heterogeneity between branches and low average rate, features that underlie the amount of dating information in alignments, hence statistical power. The best precision is associated with core biological functions such as ATP binding, cellular organization and anatomical development. We then investigated the accuracy of dating on simulated alignments, by controlling the three above parameters separately. It confirmed the factors of precision, but also revealed a systematic bias when branch rates are highly heterogeneous. This suggests that the relaxed log-normal clock model is not statistically consistent when calibrations are lacking and rate heterogeneity is high. Our study finally provides a general scale of parameters that influences the dating precision and accuracy, which can be generalized to other taxa. To tackle molecular dating events like gene duplications, future models should overcome the lack of power due to limited information from single genes.
A home and rescue gene drive forces its inheritance stably persisting in populations

Homing based gene drives, engineered using CRISPR/Cas9, have been proposed to spread desirable genes into target populations. However, spread of such drives can be hindered by the accumulation of resistance alleles. To overcome this significant obstacle, we engineer a population modification Home-and-Rescue (HomeR) drive in Drosophila melanogaster that, by creative design, limits the accumulation of such alleles. We demonstrate that HomeR can achieve nearly ~100% transmission enabling it to persist at genotypic fixation in several multi-generational population cage experiments, underscoring its long term stability. Finally, we conduct mathematical modeling determining HomeR can outperform contemporary gene drive architectures for population modification over wide ranges of fitness and transmission rates. Given its straightforward design, HomeR could be universally adapted to a wide range of species.
The Multivariate Genome-wide Architecture of Interrelated Literacy, Language and Working Memory Skills Reveals Distinct Etiologies

There is genetic overlap between many measures of literacy, language and phonological working memory (PWM) though our knowledge of multivariate genetic architectures is incomplete. Here, we directly modeled genetic trait interrelationships in unrelated UK youth (8-13 years, N=6,453), as captured by genome-wide relationship matrices, using novel structural equation modeling techniques. We identified, besides shared genetic factors across different domains (explaining 91-97% genetic variance in literacy-related measures such as passage reading fluency, spelling, phonemic awareness, 44% in oral language and 53% in PWM), evidence for distinct cognitive abilities; trait-specific genetic influences ranged between 47% for PWM to 56% for oral language. Among reading fluency measures (non-word, word and passage reading), single-word reading was genetically most diverse. Multivariate genetic and residual covariance patterns showed concordant effect directionality, except for near-zero residual correlations between oral language and literacy-related abilities. These findings suggest differences in etiological mechanisms and trait modifiability even among genetically highly correlated skills.
FUS-dependent liquid-liquid phase separation is an early event in double-strand break repair

RNA-binding proteins (RBPs) are emerging as important effectors of the cellular DNA damage response (DDR). The RBP FUS is implicated in RNA metabolism and DNA repair, and it undergoes reversible liquid-liquid phase separation (LLPS) in vitro. Here, we demonstrate that FUS-dependent LLPS is necessary for the initiation of the DDR. Using laser microirradiation in FUS-knockout cells, we show that FUS is required for the recruitment to DNA damage sites of the DDR factors KU80, NBS1, 53BP1, and of SFPQ, another RBP implicated in the DDR. The relocation of KU80, NBS1, and SFPQ is similarly impaired by LLPS inhibitors, or LLPS-deficient FUS variants. We also show that LLPS is necessary for efficient γH2AX foci formation. Finally, using super-resolution structured illumination microscopy, we demonstrate that the absence of FUS impairs the proper arrangement of γH2AX nano-foci into higher-order clusters. These findings demonstrate the early requirement for FUS-dependent LLPS in the activation of the DDR and the proper assembly of DSBs repair complexes.
Molecular Contribution to Embryonic Aneuploidy and Genotypic Complexity During Initial Cleavage Divisions of Mammalian Development

Embryonic aneuploidy is highly complex, often leading to developmental arrest, implantation failure, or spontaneous miscarriage in both natural and assisted reproduction. Despite our knowledge of mitotic mis-segregation in somatic cells, the molecular pathways regulating chromosome fidelity during the error-prone cleavage-stage of mammalian embryogenesis remain largely undefined. Using bovine embryos and live-cell fluorescent imaging, we observed frequent micro-/multi-nucleation of anaphase lagging or mis-segregated chromosomes in initial mitotic divisions that underwent unilateral inheritance, re-fused with the primary nucleus, or formed a chromatin bridge with neighboring cells. A correlation between a lack of maternal and paternal pronuclei fusion (syngamy), multipolar cytokinesis, and uniparental genome segregation was also revealed and single-cell DNA-seq showed propagation of primarily non-reciprocal mitotic errors in embryonic blastomeres. Depletion of the mitotic checkpoint protein, BUB1B/BUBR1, resulted in micro-/multi-nuclei formation, atypical cytokinesis, chaotic aneuploidy, and disruption of the kinase-substrate network regulating mitotic progression and exit, culminating in embryo arrest prior to genome activation. This demonstrates that embryonic micronuclei sustain multiple fates, provides a mechanism for blastomeres with uniparental origins, and substantiates the contribution of defective checkpoint signaling and/or the inheritance of other maternally-derived factors to the high genotypic complexity afflicting preimplantation development in higher-order mammals.
Spatially Explicit Modeling of Community Occupancy using Markov Random Field Models with Imperfect Observation: Mesocarnivores in Apostle Islands National Lakeshore

How species organize spatially is one of ecology’s most motivating questions. Multiple theories have been advanced and various models developed to account for the environment, interactions among species, and spatial drivers. However, relative importance comparisons of explanatory phenomena generally are neglected in these analyses. We developed a spatially explicit community occupancy model based on Markov random fields that accounts for spatial auto-correlation and interspecific interactions in occupancy while also accounting for interspecific interaction in detection. Simulations demonstrated that the model can distinguish different mechanisms of environmental sorting, such as competition and spatial-autocorrelation. We applied our model to camera trap data from a fisher (Pekania pennanti)-marten (Martes americana) and coyote (Canis latrans)-fox (Vulpes vulpes) system in Apostle Island National Lakeshore (Wisconsin, USA). Model results indicated that the observed partitioning pattern between marten and fisher distributions could be explained best by a flipped mainland-island source-sink pattern rather than by competition. For the coyote-fox system, we determined that, in addition to a mainland-island source-sink pattern, there was a positive association between fox and coyote that deserved further study. Our model could be readily applied to other landscapes (island and non-island systems), enhancing our understanding of species coexistence patterns.
Environmental morphing enables informed dispersal of the dandelion diaspore

Animal migration is highly sensitised to environmental cues, but plant dispersal is considered largely passive. The common dandelion, Taraxacum officinale, bears an intricate haired pappus facilitating flight. The pappus enables the formation of a separated vortex ring during flight; however, the pappus structure is not static but reversibly changes shape by closing in response to moisture. We hypothesised that this leads to changed dispersal properties in response to environmental conditions. Using wind tunnel experiments for flow visualisation, particle image velocimetry, and flight tests we characterised the fluid mechanics effects of the pappus morphing. We also modelled dispersal to understand the impact of pappus morphing on diaspore distribution. Pappus morphing dramatically alters the fluid mechanics of diaspore flight. We found that when the pappus closes in moist conditions, the drag coefficient decreases and thus the falling velocity is greatly increased. Detachment of diaspores from the parent plant also substantially decreases. The change in detachment when the pappus closes increases dispersal distances by reducing diaspore release when wind speeds are low. We propose that moisture-dependent pappus-morphing is a form of informed dispersal allowing rapid responses to changing conditions.
Primary Epiploic Appendagitis: Solving the Puzzle of a Benign Acute Abdomen

Epiploic appendages are visceral peritoneal out-pouching of colon containing fat and blood vessels Epiploic appendages are pedunculated, leaf-like fat structures wrapped by serosa. The colon has approximately 50 to 100 and 2–5 cm long epiploic appendages. They protrude from the anterior and posterior portions of the large intestine along the tenia, libera. Although their role is not precisely understood, they are believed to play a protective role as cushions, localized prevention against infection and as energy reservoirs during starvation [1].
Computational Properties of General Indices on Random Networks

We perform a detailed (computational) scaling study of well-known general indices (the first and second variable Zagreb indices, M1α(G) and M2α(G), and the general sum-connectivity index, χα(G)) as well as of general versions of indices of interest: the general inverse sum indeg index ISIα(G) and the general first geometric-arithmetic index GAα(G) (with α∈R). We apply these indices on two models of random networks: Erdös–Rényi (ER) random networks GER(nER,p) and random geometric (RG) graphs GRG(nRG,r). The ER random networks are formed by nER vertices connected independently with probability p∈[0,1]; while the RG graphs consist of nRG vertices uniformly and independently distributed on the unit square, where two vertices are connected by an edge if their Euclidean distance is less or equal than the connection radius r∈[0,2]. Within a statistical random matrix theory approach, we show that the average values of the indices normalized to the network size scale with the average degree k of the corresponding random network models, where kER=(nER−1)p and kRG=(nRG−1)(πr2−8r3/3+r4/2). That is, X(GER)/nER≈X(GRG)/nRG if kER=kRG, with X representing any of the general indices listed above. With this work, we give a step forward in the scaling of topological indices since we have found a scaling law that covers different network models. Moreover, taking into account the symmetries of the topological indices we study here, we propose to establish their statistical analysis as a generic tool for studying average properties of random networks. In addition, we discuss the application of specific topological indices as complexity measures for random networks.