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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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At least 163 records · Page 9Linked to original sources
bioRxiv2021

Progressive domain segregation in early embryonic development and underlying correlation to genetic and epigenetic changes

The author has withdrawn this manuscript due to a duplicate posting of manuscript number BIORXIV/2019/521401. Therefore, the author does not wish this work to be cited as a reference for the project. Please cite and refer to the preprint BIORXIV/2019/521401 if necessary. If you have any questions, please contact the corresponding author (gaoyq@pku.edu.cn).

developmental biology↗
bioRxiv2021

Using machine learning and big data to explore the drug resistance landscape in HIV

The authors have withdrawn this manuscript due to a duplicate posting of manuscript number 435621. Therefore, the author does not wish this work to be cited as reference for the project. Please cite and refer to the preprint 435621 (DOI: https://doi.org/10.1101/2021.03.16.435621). If you have any questions, please contact the corresponding authors.

bioinformatics↗
bioRxiv2021

Fitness Landscapes Reveal Context-Dependent Benefits of Oviposition Choice

Resource choice behaviour has enormous fitness consequences and can drive niche expansion. However, individual behavioural choices are often mediated by context, determined by past experience. Are such context-dependent behaviours adaptive? Using Tribolium castaneum (the red flour beetle), we demonstrate that context-dependent oviposition choice reflects distinct, context-specific local fitness peaks. Manipulating female egg allocation in a habitat containing optimal and suboptimal resource patches, we measured offspring fitness to generate fitness landscapes as a function of all possible oviposition behaviours (i.e., combinations of fecundity and resource preference). Females from different age and competition contexts exhibit distinct behaviours which optimize different fitness components that are linked in a tradeoff. With increasing age and prior exposure to competition, they produce few but fast-developing offspring that are advantageous under high resource competition. In contrast, young naive females produce many slow-developing offspring, beneficial under weak competition. Systematically mapping complete context-dependent fitness landscapes is thus critical to infer behavioural optimality and offers predictive power in novel contexts. Preprint available at - https://www.biorxiv.org/content/10.1101/2021.05.27.445916v1.full Citation - Vrinda Ravi Kumar, Gaurav Agavekar, Deepa Agashe; bioRxiv 2021.05.27.445916; doi: https://doi.org/10.1101/2021.05.27.445916

ecology↗
bioRxiv2021

We are not ready yet: limitations of transfer learning for Disease Named Entity Recognition

Intense research has been done in the area of biomedical natural language processing. Since the breakthrough of transfer learning-based methods, BERT models are used in a variety of biomedical and clinical applications. For the available data sets, these models show excellent results - partly exceeding the inter-annotator agreements. However, biomedical named entity recognition applied on COVID-19 preprints shows a performance drop compared to the results on available test data. The question arises how well trained models are able to predict on completely new data, i.e. to generalize. Based on the example of disease named entity recognition, we investigate the robustness of different machine learning-based methods - thereof transfer learning - and show that current state-of-the-art methods work well for a given training and the corresponding test set but experience a significant lack of generalization when applying to new data. We therefore argue that there is a need for larger annotated data sets for training and testing.

bioinformatics↗
bioRxiv2021

Can AlphaFold2 predict protein-peptide complex structures accurately?

AO_SCPLOWBSTRACTC_SCPLOWIn this preprint, we investigated whether AlphaFold2, AF2, can predict protein-peptide complex structures only with sequence information. We modeled the structures of 203 protein-peptide complexes from the PepBDB DB and 183 from the PepSet. The structures were modeling with concatenated sequences of receptors and peptides via poly-glycine linker. We found that for more than half of the test cases, AF2 predicted the bound structures of peptides with good accuracy, C-RMSD of a peptide < 3.0 [A]. For about 40% of cases, the peptide structures were modeled with an accuracy of C-RMSD < 2.0 [A]. Our benchmark results clearly show that AF2 has a great potential to be applied to various higher-order structure prediction tasks.

bioinformatics↗
bioRxiv2021

Evaluation of ChIC-based data requires normalization that properly retains signal-to-noise ratios

Several chromatin immunocleavage-based (ChIC) methods using Tn5 transposase have been developed to profile histone modifications and transcription factors bindings1-5. A recent preprint by Wang et al. raised potential concerns that these methods are prone to open chromatin bias6. While the authors are appreciated for alerting the community for this issue, it has been previously described and discussed by Henikoff and colleagues in the original CUT&Tag paper3,7. However, as described for CUT&Tag3, the signal-to-noise ratio is essential for Tn5-based profiling methods and all antibody-based enrichment assays. Based on this notion, we would like to point out a major analysis issue in Wang et al. that caused a complete loss or dramatic reduction of enrichment at true targets for datasets generated by Tn5-based methods, which in turn artificially enhanced the relative enrichment of potential open chromatin bias. Such analysis issue is caused by distinct background normalizations used towards ChIP-based (chromatin immunoprecipitation) data and Tn5-based data in Wang et al. Only the normalization for Tn5-based data, but not ChIP-seq based data, yielded such effects. Distortion of such signal-to-noise ratio would consequently lead to misleading results.

bioinformatics↗
bioRxiv2021

ProteInfer: deep networks for protein functional inference

Predicting the function of a protein from its amino acid sequence is a long-standing challenge in bioinformatics. Traditional approaches use sequence alignment to compare a query sequence either to thousands of models of protein families or to large databases of individual protein sequences. Here we instead employ deep convolutional neural networks to directly predict a variety of protein functions - EC numbers and GO terms - directly from an unaligned amino acid sequence. This approach provides precise predictions which complement alignment-based methods, and the computational efficiency of a single neural network permits novel and lightweight software interfaces, which we demonstrate with an in-browser graphical interface for protein function prediction in which all computation is performed on the users personal computer with no data uploaded to remote servers. Moreover, these models place full-length amino acid sequences into a generalised functional space, facilitating downstream analysis and interpretation. To read the interactive version of this paper, please visit https://google-research.github.io/proteinfer/ O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/461077v2_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@74f8f1org.highwire.dtl.DTLVardef@183ae0borg.highwire.dtl.DTLVardef@1754f3org.highwire.dtl.DTLVardef@1ca54f5_HPS_FORMAT_FIGEXP M_FIG C_FIG QR code for the interactive version of this preprint at https://google-research.github.io/proteinfer/

bioinformatics↗
bioRxiv2021

Sunk cost sensitivity in mice, rats, and humans on the Restaurant Row and WebSurf tasks cannot be explained by attrition biases alone

In a recent bioRxiv preprint, Ott et al. argue that sensitivities to sunk costs that have been reported in two serial foraging tasks (the Restaurant Row task in mice and rats, and the Web-Surf task in humans) may be due to simple consequences of the way that subjects perform these tasks and not due to an actual sensitivity to sunk costs. However, several variants of these tasks have been studied, in which the sensitivity to sunk costs changes. In order to test the Ott et al. model against these experimental observations, we simulated the model under these additional experimental conditions. We find that it is incompatible with the actual data. While we applaud the simplicity of the Ott et al. model, we must reject it as an explanation for the observed sensitivity to sunk costs seen in these tasks. We thus conclude that the alternative explanation - that mice, rats, and humans are sensitive to actual sunk costs in these tasks - is a better explanation for the data.

neuroscience↗
bioRxiv2021

Age-related change in task-evoked amygdala-prefrontal circuitry: a multiverse approach with an accelerated longitudinal cohort aged 4-22 years

The amygdala and its connections with medial prefrontal cortex (mPFC) play central roles in the development of emotional processes. While several studies have suggested that this circuitry exhibits functional changes across the first two decades of life, findings have been mixed - perhaps resulting from differences in analytic choices across studies. Here we used multiverse analyses to examine the robustness of task-based amygdala-mPFC function findings to analytic choices within the context of an accelerated longitudinal design (4-22 years- old; N=98; 183 scans; 1-3 scans/participant). Participants, recruited from the greater Los Angeles area, completed an event-related emotional face (fear, neutral) task. Parallel analyses varying in preprocessing and modeling choices found that age-related change estimates for amygdala reactivity were more robust than task-evoked amygdala-mPFC functional connectivity to varied analytical choices. Specification curves indicated evidence for age-related decreases in amygdala reactivity to faces, though within-participant changes in amygdala reactivity could not be differentiated from between-participant differences. In contrast, amygdala--mPFC functional connectivity results varied across methods much more, and evidence for age-related change in amygdala-mPFC connectivity was not consistent. Generalized psychophysiological interaction (gPPI) measurements of connectivity were especially sensitive to whether a deconvolution step was applied. Our findings demonstrate the importance of assessing the robustness of findings to analysis choices, although the age-related changes in our current work cannot be overinterpreted given low test-retest reliability. Together, these findings highlight both the challenges in estimating developmental change in longitudinal cohorts and the value of multiverse approaches in developmental neuroimaging for assessing robustness of results. (Preprint: https://www.biorxiv.org/content/10.1101/2021.10.08.463601v1). Key PointsO_LIMultiverse analyses applied to fMRI data are valuable for determining the robustness of findings to varied analytical choices C_LIO_LIIn the current study, age-related change estimates for amygdala reactivity were relatively robust to analytical decisions, though gPPI functional connectivity analyses were much more sensitive, leading some estimates to flip sign C_LIO_LIBoth test-retest reliability and robustness to analytical choices are important considerations for developmental research C_LI

neuroscience↗
bioRxiv2021

Dietary adaptation in Neandertal, Denisovan and Sapiens revealed by gene copy number variation

Dietary adaptation involves evolving an efficient system to digest food available in an ecosystem. The diet of archaic humans is traditionally reconstructed by isotopic analyses of human remains combined with the faunal assemblages found on the sites, and, recently, from metagenomic analyses of dental calculus. Here, we propose a new computational approach to find the genetic basis for human dietary adaptation. We searched 15 genomes from Neandertal, Denisovan and Early Sapiens for food digestion genes that tend to have more or fewer copies than the modern human reference genome. We identify 50 genes, including 10 gene clusters, with discernible copy number variation (CNV) trends at the population level, from an analysis of the full set of 20,000 human genes. The genomic variation of 19 of these genes shows how metabolic pathways for carbohydrates, lipids, liver lipids and brown fat in archaic humans adapted to metabolize food from animal or plant sources. The remaining 31 genes are all highly expressed in tissues of the digestive apparatus and are involved in immune response, environmental response and obesity. Analysis of the CNV profiles, compared to 64 modern human individuals belonging to distinct ethnic groups in Eurasia, Africa, Oceania, suggests that Homo sapiens may have had an evolutionary advantage compared to Neandertal and Denisovan in adapting to cold and temperate ecosystems. Significance StatementUnderstanding dietary strategies and foraging behaviors of past populations are among the goals of paleoanthropological and prehistoric studies. Based on a new computational approach, we seek for the genetic basis for human dietary adaptation. Gene copy number variation (CNV) is a major type of structural genome variation that we used as indicator of efficient metabolic processes for food digestion. By analysing billions of short sequences from 15 archaic human genomes and 64 modern human ones, across the full set of 20,000 human genes, we identify 50 genes whose population-wide discernable CNV trends point to lipid metabolism as being crucial for Neandertal, the efficiency in carbohydrate metabolism for Sapiens diet, and the importance of lipid metabolism and brown fat metabolism for both Neandertal and early Sapiens compared to modern humans. Preprint availability: an early version, where the CNV analysis of ancient genomes was conducted on the human reference genome hg19, was deposited on BioRxiv on November 2, 2021 (DOI: 10.1101/2021.10.30.466563). The current version, which utilises CNV estimates based on the human reference genome hg38 and includes comparisons with modern human populations, was deposited in BioRxiv in November 2024.

genomics↗
bioRxiv2021

The cardiac lncRNA Chantico directly regulates Cxcl1 chemokine transcription

Withdrawal StatementThe corresponding author has withdrawn this preprint owing to inability to reproduce some of the data, instances of inappropriate data exclusion, and loss of much of the primary experimental records/data. Specifically, Figures 2B,E,H; 3; 4; 5A,B,D; 6; S2A,C; S4A; S5; and S6A,B and attendant text contain analyses for which the primary record and/or raw data no longer exist; the analyses, where still available, suffer from inappropriate data exclusion and thus should not be construed to be an accurate reflection of the experiments. Attempts by others in the lab to repeat several of the experiments in these indicated panels have failed reproduce the presented effects, despite showing much greater precision. Therefore the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

molecular biology↗
bioRxiv2022

Analysis of SARS-CoV-2 Omicron Neutralization Data up to 2021-12-22

The rapid spread of the Omicron BA.1 (B.1.1.529.1) SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) variant in 2021 resulted in international efforts to quickly assess its escape from immunity generated by vaccines and previous infections. Numerous laboratories published BA.1 neutralization data as preprints and reports. We collated this data in real time and regularly presented updates of the aggregated results in US, European and WHO research and advisory settings. Here, we retrospectively analyzed the accuracy of these aggregations from 85 different sources published during a time period from 2021/12/08 up to 2022/08/14. We found that the mean titer fold change from wild type-like variants to BA.1, a standard measure of a variants immune escape, remained stable after the first 15 days of data reporting in people who were twice vaccinated, and incoming data increased the confidence in this quantity. Further, it is possible to build reliable, stable antigenic maps from this collated data already after one month of incoming data. We here demonstrate that combining early reports from variable, independent sources can rapidly indicate a new virus variants immune escape and can therefore be of immense benefit for public health.

immunology↗
bioRxiv2022

Wildlife and Marine Mammal Spatial Observatory: Observation and automated detection of Southern Right Whales in multispectral satellite imagery

The Wildlife and Marine Mammal Spatial Observatory is a joint research effort for the census of wildlife and particularly of marine mammals in satellite imagery. In that context, this paper illustrates the development of a high accuracy algorithm for the detection of right whales in sub-meter resolution multispectral satellite imagery with the constraint of a relatively small sample support of 580 southern right whale images. A significant space is devoted to exploratory data analysis to describe the statistical structure of right whale pixels and ocean surface pixels across multispectral bands. Observations of southern right whale in satellite imagery are divided into typical and atypical right whale forms and the first observations of right whale mother and calf pairs in satellite imagery are presented. Measurements of whales are furthermore automatically extracted from whale observations (major axis length, minor axis length, etc). A significant space is also devoted to statistical data exploration, a step frequently overlooked in machine learning solutions, that yet offers interesting insight into the structure of animal detection in satellite imagery. The extracted statistics can readily be used by researchers to develop detection solutions even with low sample support. The adopted solution for detection consists of feature extraction with a convolutional neural network followed by classification with a support vector machine. 20 different convolutional neural networks were tested for feature extraction. Biostatistics parameters (accuracy, sensitivity, specificity and precision) were measured for comparison. Most architectures generally achieved high performance with low false positive and false negative rates. 100% accuracy is achieved in the case of 2 convolutional neural networks, Nasnet Large and Inception V3, and only with a specific selection of multispectral bands. NB: This is a preprint that does not include satellite imagery due recent reviews

bioinformatics↗
bioRxiv2022

Single-cell perspectives on the function and development of deep-sea mussel bacteriocytes

The authors have withdrawn their manuscript because the authors need to re-organize the data and writing, meanwhile more experimental evidence from more RNA-seq replications, immunofluorescence assay and in vivo knock-down assays will be added to support the viewpoints. In this preprint, only one individual of decolonized mussel was employed for transcriptome sequencing while combined data from single cell transcriptomics with in situ hybridization is not enough convincing to draw some of the conclusion. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

molecular biology↗