Biology subjects

Fischer, J.

Publications and source records attributed to Fischer, J..

78 records · Page 5Linked to original sources

bioRxiv2019

Long-tailed macaques extract statistical information from repeated types of events to make rational decisions under uncertainty

Human children and apes are proficient intuitive statisticians when making predictions from populations of objects to randomly drawn samples, whereas monkeys seem not to be. Statistical reasoning can also be investigated in tasks in which the probabilities of different possibilities must be inferred from relative frequencies of events, but little is known about the performance of nonhuman primates in such tasks. In the current study, we investigated whether long-tailed macaques extract statistical information from repeated types of events to make predictions under uncertainty. In each experiment, monkeys first experienced the probability of rewards associated with different factors separately. In a subsequent test trial, monkeys could then choose between the different factors presented simultaneously. In Experiment 1, we tested whether long-tailed macaques relied on probabilities and not on a comparison of absolute quantities to make predictions. In Experiment 2 and 3 we varied the nature of the predictive factors and the complexity of the covariation structure between rewards and factors. Results indicate that long-tailed macaques extract statistical information from repeated types of events to make predictions and rational decisions under uncertainty, in more or less complex scenarios. These findings suggest that, given the right input information, monkeys are intuitive statisticians.

animal behavior and cognition↗

bioRxiv2018

Integrative analysis of single cell expression data reveals distinct regulatory states in bidirectional promoters

BackgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single cell technologies are not yet established, in the context of BPs.\n\nResultsWe performed integrative analyses of novel human single cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.\n\nConclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

genomics↗

bioRxiv2018

Do long-tailed macaques engage in intuitive statistics?

Human infants, apes and capuchins have been found to engage in intuitive statistics, generating predictions from populations to samples based on proportional information. This suggests that statistical reasoning might depend on some core knowledge that is shared with other species. Here, we investigated whether such intuitive statistical reasoning is also present in a species of Old World monkeys, to aid in the reconstruction of the evolution of this capacity. In a series of 7 test conditions, 11 long-tailed macaques were offered different pairs of populations containing varying proportions of preferred vs. neutral food items. One population always contained a higher proportion of preferred items than the other. An experimenter simultaneously drew one item out of each population, hid them in her fists and presented them to the monkey to choose. Results revealed that at least one individual seemed to make systematic population-to-sample inferences and consistently chose the sample from the population with the more favorable distribution of preferred vs. neutral food items. While it is not clear whether she used relative or absolute quantities of food, she seemed to understand the difference between a correct choice and a favorable draw and thus some basic principles of intuitive statistics.

animal behavior and cognition↗

bioRxiv2017

Three-way clustering of multi-tissue multi-individual gene expression data using constrained tensor decomposition

The advent of next generation sequencing methods has led to an increasing availability of large, multi-tissue datasets which contain gene expression measurements across different tissues and individuals. In this setting, variation in expression levels arises due to contributions specific to genes, tissues, individuals, and interactions thereof. Classical clustering methods are illsuited to explore these three-way interactions, and struggle to fully extract the insights into transcriptome complexity and regulation contained in the data. Thus, to exploit the multi-mode structure of the data, new methods are required. To this end, we propose a new method, called MultiCluster, based on constrained tensor decomposition which permits the investigation of transcriptome variation across individuals and tissues simultaneously. Through simulation and application to the GTEx RNA-seq data, we show that our tensor decomposition identifies three-way clusters with higher accuracy, while being 11x faster, than the competing Bayesian method. For several age-, race-, or gender-related genes, the tensor projection approach achieves increased significance over single-tissue analysis by two orders of magnitude. Our analysis finds gene modules consistent with existing knowledge while further detecting novel candidate genes exhibiting either tissue-, individual-, or tissue-by-individual specificity. These identified genes and gene modules offer bases for future study, and the uncovered multi-way specificities provide a finer, more nuanced snapshot of transcriptome variation than previously possible.

genomics↗

bioRxiv2017

Bacterium-triggered remodeling of chromatin identifies BasR, a novel regulator of fungal natural product biosynthesis

The eukaryotic epigenetic machinery is targeted by bacteria to reprogram the response of eukaryotes during their interaction with microorganisms. In line, we discovered that the bacterium Streptomyces rapamycinicus triggered increased chromatin acetylation and thus activation of the silent secondary metabolism ors gene cluster leading to the production of orsellinic acid in the fungus Aspergillus nidulans. Using this model we aim at understanding molecular mechanisms of communication between bacteria and eukaryotic microorganisms based on bacteria-triggered chromatin modification. By genome-wide ChIP-seq analysis of acetylated histone H3 (H3K9ac, H3K14ac) we uncovered the unique chromatin landscape in A. nidulans upon co-cultivation with S. rapamycinicus. Genome-wide acetylation of H3K9 correlated with increased gene expression, whereas H3K14 appears to function in transcriptional initiation by providing a docking side for regulatory proteins. In total, histones belonging to six secondary metabolism gene clusters showed higher acetylation during co-cultivation including the ors, aspercryptin, cichorine, sterigmatocystin, anthrone and 2,4-dihydroxy-3-methyl-6-(2-oxopropyl)benzaldehyde gene cluster with the emericellamide cluster being the only one with reduced acetylation and expression. Differentially acetylated histones were also detected in genes involved in amino acid and nitrogen metabolism, signaling, and genes encoding transcription factors. In conjunction with LC-MS/MS and MALDI-MS imaging, molecular analyses revealed the cross-pathway control and Myb-like transcription factor BasR as regulatory nodes for transduction of the bacterial signal in the fungus. The presence of basR in other fungal species allowed forecasting the inducibility of ors-like gene clusters by S. rapamycinicus in these fungi, and thus their effective interaction with activation of otherwise silent gene clusters.

microbiology↗

bioRxiv2017

Bayesian inference and simulation approaches improve the assessment of Elo-scores in the analysis of social behaviour

O_LIThe construction of rank hierarchies based on agonistic interactions between two individuals (\"dyads\") is an important component in the characterization of the social structure of groups. To this end, winner-loser matrices are typically created, which collapse the outcome of dyadic interactions over time, resulting in the loss of all information contained in the temporal domain. Methods that track changes in the outcome of dyadic interactions (such as \"Elo-scores\") are receiving increasing interest. Critically, individual scores are not just based on the succession of wins and losses, but depend on the values of starting scores and an update (\"tax\") coefficient. Recent studies improved existing methods by introducing a point estimation of these auxiliary parameters on the basis of a maximum likelihood (ML) approach. For a sound assessment of the rank hierarchies generated this way, we argue that measures of uncertainty of the estimates, as well as a quantification of the robustness of the methods, are also needed.\nC_LIO_LIWe introduce a Bayesian inference (BI) approach using partial pooling\", which rests on the assumption that all starting scores are samples from the same distribution. We compare the outcome of the ML approach to that of the BI approach using real-world data. In addition, we simulate different scenarios to explore in which way the Elo-score responds to social events (such as rank changes), and low numbers of observations.\nC_LIO_LIEstimates of the starting scores based on partial pooling\" are more robust than those based on ML, also in scenarios where some individuals have only few observations. Our simulations show that assumed rank differences may fall well within the uncertain\" range, and that low sampling density, unbalanced designs, and coalitionary leaps involving several individuals within the hierarchy may yield unreliable results.\nC_LIO_LIOur results support the view that Elo rating can be a powerful tool in the analysis of social behaviour, when the data meet certain criteria. Assessing the uncertainty greatly aids in the interpretation of results. We advocate running simulation approaches to test how well Elo scores reflect the (simulated) true structure and how sensitive the score is to true changes in the hierarchy.\nC_LI

animal behavior and cognition↗