Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,081 bioRxiv papers from 318,277 authors.
Most tweeted bioRxiv papers, last 7 days
732 results found. For more information, click each entry to expand.
43 tweets genomics
Dilated cardiomyopathy (DCM) is an important cause of heart failure and the leading indication for heart transplantation. Many rare genetic variants have been associated with DCM, but common variant studies of the disease have yielded few associated loci. As structural changes in the heart are a defining feature of DCM, we conducted a genome-wide association study (GWAS) of cardiac magnetic resonance imaging (MRI)-derived left ventricular measurements in 29,041 UK Biobank participants. 26 novel loci were associated with cardiac structure and function. These loci were found near 17 genes previously shown to cause Mendelian cardiomyopathies. A polygenic score of left ventricular end systolic volume was associated with incident DCM in previously disease-free individuals (hazard ratio = 1.54 per one standard deviation increase in the polygenic score, P = 2.1 × 10-16). Even among carriers of truncating mutations in TTN, the polygenic score influenced the size and function of the heart. These results further implicate common genetic polymorphisms in DCM pathogenesis.
42 tweets genomics
Estimates of correlation between pairs of genes in co-expression analysis are commonly used to construct networks among genes using gene expression data. Here, we show that the distribution of such correlations depend on the expression level of the involved genes, which we refer to this as a mean-correlation relationship in RNA-seq data, both bulk and single-cell. This dependence introduces a bias in co-expression analysis whereby highly expressed genes are more likely to be highly correlated. Such a relationship is not observed in protein-protein interaction data, suggesting that it is not reflecting biology. Ignoring this bias can lead to missing potentially biologically relevant pairs of genes that are lowly expressed, such as transcription factors. To address this problem, we introduce spatial quantile normalization (SpQN), a method for normalizing local distributions in a correlation matrix. We show that spatial quantile normalization removes the mean-correlation relationship and corrects the expression bias in network reconstruction.
40 tweets genomics
Genotype-based diagnostics for antibiotic resistance represent a promising alternative to empiric therapy, reducing inappropriate and ineffective antibiotic use. However, because such assays infer resistance phenotypes based on the presence or absence of known genetic markers, their utility will wane in response to the emergence of novel resistance. Maintenance of these diagnostics will therefore require surveillance designed to ensure early detection of novel resistance variants, but efficient strategies to do so remain to be defined. Here, we evaluate the efficiency of targeted sampling approaches informed by patient and pathogen characteristics in detecting genetic variants associated with antibiotic resistance or diagnostic escape in Neisseria gonorrhoeae, focusing on this pathogen because of its high burden of disease, the imminent threat of treatment resistance, and the use and ongoing development of genotype-based diagnostics. We show that incorporating patient characteristics, such as demographics, geographic regions, or anatomical sites of isolate collection, into sampling approaches is not a reliable strategy for increasing variant detection efficiency. In contrast, sampling approaches informed by pathogen characteristics, such as genomic diversity and genomic background, are significantly more efficient than random sampling in identifying genetic variants associated with antibiotic resistance and diagnostic escape.
39 tweets neuroscience
The global neuronal workspace (GNW) model has inspired over two decades of hypothesis driven research on the neural basis consciousness. However, recent studies have reported findings that appear inconsistent with the predictions of the model. Further, the macroanatomical focus of current GNW research has limited the specificity of predictions afforded by the model. In this paper we present a neurocomputational model, based on the active inference framework, that captures central architectural elements of the GNW and that can address these limitations. The resulting predictive global workspace casts neuronal dynamics as approximating Bayesian inference, allowing precise, testable predictions at both the behavioural and neural levels of description. We report simulations demonstrating the model's ability to reproduce: 1) the electrophysiological and behaviour results observed in previous studies of inattentional blindness, and 2) the previously described four-way taxonomy predicted by the GNW, which describes the relationship between consciousness, attention, and sensory signal strength. We then illustrate how our model can reconcile/explain (apparently) conflicting findings, extend the GNW taxonomy to include the influence of prior expectations, and inspire novel paradigms to test associated behavioural and neural predictions.
39 tweets neuroscience
David Deutsch, Diego Armando Pacheco, Lucas Jose Encarnacion-Rivera, T.D. Pereira, Ramie Fathy, Adam John Calhoun, Elise Claire Eireland, Austin Taylor Burke, Sven Dorkenwald, Claire McKellar, Thomas Macrina, Ran Lu, Kisuk Lee, Nico Kemnitz, Dodam Ih, Manuel Castro, Akhilesh Halageri, Chris Jordan, William Silversmith, Jingpeng Wu, Hyunjune Sebastian Seung, Mala Murthy
Sustained changes in mood or action require persistent changes in neural activity, but it has been difficult to identify and characterize the neural circuit mechanisms that underlie persistent activity and contribute to long-lasting changes in behavior. Here, we focus on changes in the behavioral state of Drosophila females that persist for minutes following optogenetic activation of a single class of central brain neurons termed pC1. We find that female pC1 neurons drive a variety of persistent behaviors in the presence of males, including increased receptivity, shoving, and chasing. By reconstructing cells in a volume electron microscopic image of the female brain, we classify 7 different pC1 cell types and, using cell type specific driver lines, determine that one of these, pC1-Alpha, is responsible for driving persistent female shoving and chasing. Using calcium imaging, we locate sites of minutes-long persistent neural activity in the brain, which include pC1 neurons themselves. Finally, we exhaustively reconstruct all synaptic partners of a single pC1-Alpha neuron, and find recurrent connectivity that could support the persistent neural activity. Our work thus links minutes-long persistent changes in behavior with persistent neural activity and recurrent circuit architecture in the female brain.
37 tweets evolutionary biology
Even after decades of research, the evolution of sex remains an enigma in evolutionary biology. Typically, research addresses the costs of sex and asexuality to characterize the circumstances in which one reproductive system is more favorable. Yet surprisingly few studies address the influence of common traits that are obligately correlated with asexuality, including hybridization and polyploidy; even though these traits have substantial impacts on selective patterns. In particular, hybridization is well-known to alter trait expression; these alterations may themselves represent a cost of sex. We examined the role of reproductive isolation in the formation of de novo hybrid lineages between two widespread species in the ecological model system Boechera . Of 664 crosses between Boechera stricta and Boechera retrofracta , 17% of crosses produced F1 fruits. This suggests that postmating prezygotic barriers, i.e. pollen-pistil interactions, form the major barrier to hybrid success in this system. These interactions are asymmetrical, with 110 F1 fruits produced when B. stricta was the maternal parent. This asymmetry was confirmed using a chloroplast phylogeny of wild-collected B. stricta , B. retrofracta , and hybrids, which showed that most hybrids have a B. stricta chloroplast haplotype. We next compared fitness of F2 hybrids and selfed parental B. stricta lines, finding that F2 fitness was reduced by substantial hybrid sterility. Our results suggest that multiple reproductively isolating barriers likely influence the formation and fitness of hybrid lineages in the wild, and that these costs of hybridization likely have profound impacts on the costs of sex in the natural environment.
36 tweets synthetic biology
SSHELs are synthetic bacterial spore-like particles wherein the cell surface of the spore is partially reconstituted around 1 μm-diameter silica beads coated with a lipid bilayer. Via a unique cysteine engineered in one of the surface proteins, the surface of SSHELs may be covalently decorated with molecules of interest. Here, we modified SSHELs with an affibody directed against HER2, a cell surface protein overexpressed in some breast and ovarian cancer cells, and loaded them with the chemotherapeutic agent doxorubicin. Drug-loaded SSHELs reduced tumor growth with lower toxicity in a mouse tumor xenograft model compared to free drug by specifically binding to HER2-positive cancer cells. We show that SSHELs bound to target cells are taken up and trafficked to acidic compartments, whereupon the cargo is released in a pH-dependent manner. Finally, we demonstrate that SHELLs can clear small tumor lesions in a complex tumor microenvironment in a zebrafish model of brain metastasis. We propose that SSHELs represent a versatile strategy for targeted drug delivery.
36 tweets bioinformatics
RNA-seq is a modular experimental and computational approach that aims in identifying and quantifying RNA molecules. The modularity of the RNA-seq technology enables adaptation of the protocol to develop new ways to explore RNA biology, but this modularity also brings forth the importance of methodological thoroughness. Liberty of approach comes with the responsibility of choices, and such choices must be informed. Here, we present an approach that identifies gene group specific quantification biases in currently used RNA-seq software and references by processing sequenced datasets using a wide variety of RNA-seq computational pipelined, and by decomposing these expression datasets using an independent component analysis matrix factorisation method. By exploring the RNA-seq pipeline using a systemic approach, we highlight the yet inadequately characterized central importance of genome annotations in quantification results. We also show that the different choices in RNA-seq methodology are not independent, through interactions between genome annotations and quantification software. Genes were mainly found to be affected by differences in their sequence, by overlapping genes and genes with similar sequence. Our approach offers an explanation for the observed biases by identifying the common features used differently by the software and references, therefore providing leads for the betterment of RNA-seq methodology.
36 tweets genomics
Background: Barley ( Hordeum vulgare ) is one of the most important crops worldwide and is also considered a research model for the large-genome small grain temperate cereals. Despite genomic resources improving all the time, they are limited for the cv. Golden Promise, the most efficient genotype for genetic transformation. Findings: We have developed a barley cv. Golden Promise reference assembly integrating Illumina paired-end reads, long mate-pair reads, Dovetail Chicago in vitro proximity ligation libraries and chromosome conformation capture sequencing (Hi-C) libraries into a contiguous reference assembly. The assembled genome of 7 chromosomes and 4.13Gb in size, has a super-scaffold N50 after Chicago libraries of 4.14Mb and contains only 2.2% gaps. Using BUSCO (benchmarking universal single copy orthologous genes) as evaluation the genome assembly contains 95.2% of complete and single copy genes from the plant database. Conclusions: A high-quality Golden Promise reference assembly will be useful and utilised by the whole barley research community but will prove particularly useful for CRISPR-Cas9 experiments.
36 tweets cancer biology
Radiotherapy is a pillar of cancer care and augments the response to immunotherapies. However, little is known regarding the relationships between the tumor immune ecosystem (TIES) and intrinsic radiosensitivity, and a pressing question in oncology is how to optimize radiotherapy to improve patient responses to immune therapies. To address this challenge, we profiled over 10,000 primary tumors for their metrics of radiosensitivity and immune cell infiltrate (ICI), and applied a new integrated in silico model that mimics the dynamic relationships between tumor growth, ICI flux and the response to radiation. We then validated this model with a separate cohort of 59 lung cancer patients treated with radiotherapy. These analyses explain radiation response based on its effect on the TIES and quantifies the likelihood that radiation can promote a shift to anti-tumor immunity. Dynamic modeling of the relationship between tumor radiosensitivity and the TIES may provide opportunity to personalize combined radiation and immunotherapy approaches.
35 tweets genomics
Patterson's D, also known as the ABBA-BABA statistic, and related statistics such as the f4-ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations require custom file formats and are impractical to evaluate all gene flow hypotheses across datasets with many populations or species. Dsuite is a fast C++ implementation, allowing genome scale calculations of the D and f4-ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Furthermore, the program can provide evidence of whether introgression is confined to specific loci and aid in interpretation of a system of f4-ratio results by implementing the 'f-branch' method. Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than other comparable programs, and presents a novel suite of tools and statistics, including some not previously available in any software package. Thus, Dsuite facilitates assessment of evidence for gene flow, especially across large genomic datasets.
33 tweets cancer biology
Early cancer detection aims to find tumors before they progress to an uncurable stage. Prospective studies with tens of thousands of healthy participants are ongoing to determine whether asymptomatic cancers can be accurately detected by analyzing circulating tumor DNA (ctDNA) from blood samples. We developed a stochastic mathematical model of tumor evolution and ctDNA shedding to investigate the potential and the limitations of ctDNA based cancer early detection tests. We inferred ctDNA shedding rates of early stage lung cancers and calculated that a 15 mL blood sample contains on average only 1.5 genome equivalents of ctDNA for lung tumors with 1 billion cells (size of ~1 cm3). We considered two clinically different scenarios: cancer screening and cancer relapse detection. For monthly relapse testing with a sequencing panel covering 20 tumor specific mutations, we found a median detection size of 0.24 cm3 corresponding to a lead time of 160 days compared to imaging based relapse detection. For annual screening, we found a median detection size of 2.8-4.8 cm3 depending on the sequencing panel size and on the mutation frequency. The expected detection sizes correspond to lead times of 390-520 days compared to current median lung tumor sizes at diagnosis. This quantitative framework provides a mechanistic interpretation of ctDNA based cancer detection approaches and helps to optimize cancer early detection strategies.
31 tweets genomics
For most biological processes, organisms must respond to extrinsic cues, while maintaining essential gene expression programs. Although studied extensively in single cells, it is still unclear how variation is controlled in multicellular organisms. Here, we used a machine-learning approach to identify genomic features that are predictive of genes with high versus low variation in their expression across individuals, using bulk data to remove stochastic cell-to-cell variation. Using embryonic gene expression across 75 Drosophila isogenic lines, we identify features predictive of expression variation, while controlling for expression level. Genes with low variation fall into two classes, indicating they employ different mechanisms to maintain a robust expression. In contrast, genes with high variation seem to lack both types of stabilizing mechanisms. Applying the framework to human tissues from GTEx revealed similar predictive features, indicating that promoter architecture is an ancient mechanism to control expression variation. Remarkably, expression variation features could also predict differential expression upon stress in both Drosophila and human. Differential gene expression signatures may therefore be partially explained by genetically encoded gene-specific features, unrelated to the studied treatment.
31 tweets biochemistry
Using mRNA-Seq and de novo transcriptome assembly, we identified, cloned and characterized nine previously undiscovered fluorescent protein (FP) homologs from Aequorea victoria and a related Aequorea species, with most sequences highly divergent from avGFP. Among these FPs are the brightest GFP homolog yet characterized and a reversibly photochromic FP that responds to UV and blue light. Beyond green emitters, Aequorea species express purple- and blue-pigmented chromoproteins (CPs) with absorbances ranging from green to far-red, including two that are photoconvertible. X-ray crystallography revealed that Aequorea CPs contain a chemically novel chromophore with an unexpected crosslink to the main polypeptide chain. Because of the unique attributes of several of these newly discovered FPs, we expect that Aequorea will, once again, give rise to an entirely new generation of useful probes for bioimaging and biosensing.
30 tweets neuroscience
Uros Topalovic, Zahra M. Aghajan, Diane Villaroman, Sonja Hiller, Leonardo Christov-Moore, Tyler J. Wishard, Matthias Stangl, Nicholas R Hasulak, Cory S Inman, Tony A Fields, Dawn Eliashiv, Itzhak Fried, Nanthia A Suthana
Current implantable devices that allow for recording and stimulation of brain activity in humans are not inherently designed for research and thus lack programmable control and integration with wearable sensors. We developed a platform that enables wireless and programmable intracranial electroencephalographic recording and deep brain stimulation integrated with wearable technologies. This methodology, when used in freely moving humans with implanted neural devices, can provide an ecologically valid environment conducive to elucidating the neural mechanisms underlying naturalistic behaviors and developing viable therapies for neurologic and psychiatric disorders.
30 tweets plant biology
Warm temperature is postulated to induce plant thermomorphogenesis through a signaling mechanism similar to shade, as both destabilize the active form of the photoreceptor and thermosensor phytochrome B (phyB). At the cellular level, shade antagonizes phyB signaling by triggering phyB disassembly from photobodies. Here we report temperature-dependent photobody localization of fluorescent protein-tagged phyB (phyB-FP) in the epidermal cells of Arabidopsis hypocotyl and cotyledon. Our results demonstrate that warm temperature operates through different photobody dynamics from shade. Increases in temperature from 12°C to 27°C incrementally reduce photobody number by stimulating phyB-FP disassembly from selective thermo-unstable photobodies. The thermostability of photobodies relies on phyB's photosensory module. Surprisingly, elevated temperatures inflict opposite effects on phyB's functions in the hypocotyl and cotyledon despite inducing similar photobody dynamics, indicative of tissue/organ-specific temperature signaling circuitry downstream of photobody dynamics. Our results thus provide direct cell biology evidence supporting an early temperature signaling mechanism via dynamic assembly/disassembly of individual photobodies possessing distinct thermostabilities.
29 tweets neuroscience
It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Moreover, little is known about how such preferences are actually constructed in the brain. Here we developed and tested a computational framework to gain an understanding of how the human brain constructs aesthetic value. We show that it is possible to explain human preferences for a piece of art based on an analysis of features present in the image. This was achieved by analyzing the visual properties of drawings and photographs by multiple means, ranging from image statistics extracted by computer vision tools, subjective human ratings about attributes, to a deep convolutional neural network. Crucially, it is possible to predict subjective value ratings not only within but also across individuals, speaking to the possibility that much of the variance in human visual preference is shared across individuals. Neuroimaging data revealed that preference computations occur in the brain by means of a graded hierarchical representation of lower and higher level features in the visual system. These features are in turn integrated to compute an overall subjective preference in the parietal and prefrontal cortex. Our findings suggest that rather than being idiosyncratic, human preferences for art can be explained at least in part as a product of a systematic neural integration over underlying visual features of an image. This work not only advances our understanding of the brain-wide computations underlying value construction but also brings new mechanistic insights to the study of visual aesthetics and art appreciation.
29 tweets genomics
Michiel J. Thiecke, Gordana Wutz, Matthias Muhar, Wen Tang, Stephen Bevan, Valeriya Malysheva, Roman Stocsits, Tobias Neumann, Johannes Zuber, Peter Fraser, Stefan Schoenfelder, Jan-Michael Peters, Mikhail Spivakov
It is currently assumed that 3D chromosomal organisation plays a central role in transcriptional control. However, recent evidence shows that steady-state transcription of only a minority of genes is affected by depletion of architectural proteins such as cohesin and CTCF. Here, we have used Capture Hi-C to interrogate the dynamics of chromosomal contacts of all human gene promoters upon rapid architectural protein degradation. We show that promoter contacts lost in these conditions tend to be long-range, with at least one interaction partner localising in the vicinity of topologically associated domain (TAD) boundaries. In contrast, many shorter-range chromosomal contacts, particularly those that connect active promoters with each other and with active enhancers remain unaffected by cohesin and CTCF depletion. We demonstrate that the effects of cohesin depletion on nascent transcription can be explained by changes in the connectivity of their enhancers. Jointly, these results provide a mechanistic explanation to the limited, but consistent effects of cohesin and CTCF on steady-state transcription and point towards the existence of alternative enhancer-promoter pairing mechanisms that are independent of these proteins.
28 tweets biochemistry
Elda Cannavo, Aurore Sanchez, Roopesh Anand, Lepakshi Ranjha, Jannik Hugener, Celine Adam, Ananya Acharya, Nicolas Weyland, Xavier Aran-Guiu, Jean-Baptiste Charbonnier, Eva R Hoffman, Valerie Borde, Joao Matos, Petr Cejka
During prophase of the first meiotic division, cells deliberately break their DNA. These DNA breaks are repaired by homologous recombination, which facilitates proper chromosome segregation and enables reciprocal exchange of DNA segments between homologous chromosomes, thus promoting genetic diversity in the progeny. A successful completion of meiotic recombination requires nucleolytic processing of recombination intermediates. Genetic and cellular data implicated a pathway dependent on the putative MLH1-MLH3 (MutLγ) nuclease in generating crossovers, but mechanisms that lead to its activation were unclear. Here, we have biochemically reconstituted key elements of this pro-crossover pathway. First, we show that human MSH4-MSH5 (MutSγ), which was known to support crossing over, binds branched recombination inter-mediates and physically associates with MutLγ. This helps stabilize the ensemble at joint molecule structures and adjacent dsDNA. Second, we show that MutSγ directly stimulates DNA cleavage by the MutLγ endonuclease, which demonstrates a novel and unexpected function for MutSγ in triggering crossing-over. Third, we find that MutLγ activity is further stimulated by EXO1, but only when MutSγ is present. Fourth, we also identify the replication factor C (RFC) and the proliferating cell nuclear antigen (PCNA) as additional compo-nents of the nuclease ensemble, and show that S. cerevisiae strains expressing PIP box-mutated MutLγ present striking defects in forming crossovers. Finally, we show that the MutLγ-MutSγ-EXO1-RFC-PCNA nuclease ensemble preferentially cleaves DNA with Holliday junctions, but shows no canonical resolvase activity. Instead, the multilayered nuclease ensemble likely processes meiotic recombination intermediates by nicking dsDNA adjacent to junction points. Since DNA nicking by MutLγ is dependent on its co-factors, the asymmetric distribution of MutSγ and RFC/PCNA on meiotic recombination intermediates may drive biased DNA cleavage. This unique mode of MutLγ nuclease activation might explain crossover-specific processing of Holliday junctions within the meiotic chromosomal context.
27 tweets molecular biology
Cells adjust to nutrient deprivation by reversible translational shut down. This is accompanied by maintaining inactive ribosomes in a hibernation state, where they are bound by proteins with inhibitory and protective functions. In eukaryotes, such a function was attributed to Stm1 (SERBP1 in mammals), and recently Lso2 (CCDC124 in mammals) was found to be involved in translational recovery after starvation from stationary phase. Here, we present cryo-electron microscopy (cryo-EM) structures of translationally inactive yeast and human ribosomes. We found Lso2/CCDC124 accumulating on idle ribosomes in the non-unrotated state, in contrast to Stm1/SERBP1-bound ribosomes, which display a rotated state. Lso2/CCDC124 bridges the decoding sites of the small with the GTPase-activating center of the large subunit. This position allows accommodation of the Dom34-dependent ribosome recycling system, which splits Lso2-containing but not Stm1-containing ribosomes. We propose a model in which Lso2 facilitates rapid translation reactivation by stabilizing the recycling-competent state of inactive ribosomes.
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