Biology subjects

Browse preprints

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.

At least 1,189 records · Page 66Linked to original sources

bioRxiv2018

Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression

Sequencing the genomes of individual cancer cells provides the highest resolution of intratumoral heterogeneity. To enable high throughput single cell DNA-Seq across thousands of individual cells per sample, we developed a droplet-based, automated partitioning technology for whole genome sequencing. We applied this approach on a set of gastric cancer cell lines and a primary gastric tumor. In parallel, we conducted a separate single cell RNA-Seq analysis on these same cancers and used copy number to compare results. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection - where the percentage of replicating cells per clone is higher than expected - indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology. SIGNIFICANCEWe conducted a massively parallel DNA sequencing analysis on a set of gastric cancer cell lines and a primary gastric tumor in combination with a joint single cell RNA-Seq analysis. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection where the percentage of replicating cells per clone is higher than expected indicating ongoing tumor evolution. Our study demonstrates that combining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.

genomics↗

bioRxiv2018

The mitochondrial DNA content can not predict the embryo viability

ObjectiveTo investigate whether the mitochondrial DNA content could predict the embryo viability\n\nDesignRetrospective analysis.\n\nSettingReproductive genetics laboratory\n\nPatient(s)A total of 421 biopsied samples obtained from 129 patients\n\nIntervention(s)Embryo biopsies samples underwent whole genome amplification (WGA) and were tested by next generation sequencing (NGS) and array Comparative Genomic Hybridization (aCGH), 30 samples were selected randomly to undergo quantitative real-time polymerase chain reaction (qPCR).\n\nMain Outcome Measure(s)Those embryos which obtained the consistent chromosome status determined both aCGH and NGS platform were further classified. We investigated the relationship of mtDNA content with several factors including female patient age, embryo morphology, chromosome status, and live birth rate of both blastocysts and blastomeres.\n\nResult(s)A total of 386 (110 blastomeres and 276 blastocysts) out of 399 embryos showed consistent chromosome status outcome. We found no statistically difference was observed in aneuploid and euploid blastocysts (p=0.14), the same phenomenon was observed in aneuploid and euploid blastomeres (p=0.89). Similarly, the mtDNA content was independent of female patient age, embryo morphology and live birth rate.\n\nConclusion(s)The mtDNA content did not provide a reliable prediction of the viability of blastocysts to initiate a pregnancy.

ecology↗

bioRxiv2018

Nitrogen starvation induces persister cell formation in Escherichia coli

To cope with fluctuations in their environment bacteria have evolved multiple adaptive stress responses. One such response is the nitrogen regulation stress response, which allows bacteria such as Escherichia coli to cope with and overcome conditions of nitrogen limitation. This response is directed by the two-component system NtrBC, where NtrC acts as the major transcriptional regulator to activate the expression of genes to mount the response. Recently we showed that NtrC directly regulates the expression of the relA gene, the major (p)ppGpp synthetase in E. coli, coupling the nitrogen regulation stress and stringent responses. As elevated levels of (p)ppGpp have been implicated in the formation persister cells, here we investigated whether nitrogen starvation promotes their formation and whether the NtrC-RelA regulatory cascade plays a role in this. The results reveal that both nitrogen starved E. coli form a higher percentage of persister cells than non-starved cells, and that both NtrC and RelA are important for this process. This provides novel insights into how the formation of persisters can be promoted in response to a nutritional stress.\n\nImportanceBacteria often reside in environments where nutrient availability is scarce and therefore they have evolved adaptive responses to rapidly cope with conditions of feast and famine. Understanding the mechanisms that underpin the regulation of how bacteria cope with this stress is a fundamentally important question in the wider context of understanding the biology of the bacterial cell and bacterial pathogenesis. Two major adaptive mechanisms to cope with starvation are the nitrogen regulation (ntr) stress and stringent responses. Here I describe how these bacterial stress responses are coordinated under conditions of nitrogen starvation to promote the formation of antibiotic tolerant persister cells by elevating levels of the secondary messenger (p)ppGpp.

microbiology↗

bioRxiv2018

Nuclear actin interactome analysis links actin to KAT14 histone acetyl transferase and mRNA splicing

In addition to its essential functions within the cytoskeleton, actin also localizes to the cell nucleus, where it is linked to many important nuclear processes from gene expression to maintenance of genomic integrity. However, the molecular mechanisms by which actin operates in the nucleus remain poorly understood. Here we have used two complementary mass spectrometry (MS) techniques, AP-MS and BioID-MS, to identify binding partners for nuclear actin. Common high-confidence interactions highlight the role of actin in chromatin remodeling complexes and identify the hATAC histone modifier as a novel actin-containing nuclear complex. Further analysis demonstrates that actin binds directly to the hATAC subunit KAT14, and modulates its histone acetyl transferase activity in vitro and in cells. BioID-MS, which can detect also transient interactions, links actin to several steps of transcription as well as to RNA processing. Alterations in nuclear actin levels disturb alternative exon skipping of the SMN2 minigene, suggesting also a functional role for actin in RNA splicing. This interactome analysis thus identifies both novel direct binding partners and functional roles for nuclear actin, as well as forms a platform for further mechanistic studies on how actin operates during essential nuclear processes.

cell biology↗

bioRxiv2018

Identifying and classifying shared selective sweeps from multilocus data

Positive selection causes beneficial alleles to rise to high frequency, resulting in a selective sweep of the diversity surrounding the selected sites. Accordingly, the signature of a selective sweep in an ancestral population may still remain in its descendants. Identifying genomic regions under selection in the ancestor is important to contextualize the timing of a sweep, but few methods exist for this purpose. To uncover genomic regions under shared positive selection across populations, we apply the theory of the expected haplotype homozygosity statistic H12, which detects recent hard and soft sweeps from the presence of high-frequency haplotypes. Our statistic, SS-H12, is distinct from other statistics that detect shared sweeps because it requires a minimum of only two populations, and properly identifies independent convergent sweeps and true ancestral sweeps, with high power. Furthermore, we can apply SS-H12 in conjunction with the ratio of a different set of expected haplotype homozygosity statistics to further classify identified shared sweeps as hard or soft. Finally, we identified both previously-reported and novel shared sweep candidates from whole-genome sequences of global human populations. Previously-reported candidates include the well-characterized ancestral sweeps at LCT and SLC24A5 in Indo-European populations, as well as GPHN worldwide. Novel candidates include an ancestral sweep at RGS18 in sub-Saharan African populations involved in regulating the platelet response and implicated in sudden cardiac death, and a convergent sweep at C2CD5 between European and East Asian populations that may explain their different insulin responses.

evolutionary biology↗

bioRxiv2018

Smed-egfr-4 is required for planarian eye regeneration

Planarians are amazing animals that can regenerate a whole body from a tiny piece of them thanks to their pluripotent stem cells, the neoblasts. Planarian neoblasts include both pluripotent stem cells and specialized lineage-committed progenitors that give rise to all the mature cell types during regeneration and homeostatic cell turnover in these plastic animals. Little is known, however, about the mechanisms that regulate neoblast differentiation. Recently, it has been shown that Smed-egfr-1, a homologue of the epidermal growth factor receptor (EGFR) family is required for the final differentiation of the gut progenitors into mature cells but not for their specification. As planarians have several EGFR homologues it has been proposed that they could have diverged functionally to regulate the differentiation of the different cell types found in these animals. Here, we report on the function of Smed-egfr-4 on eye regeneration. The silencing of this gene by RNAi results in animals regenerating smaller eyes compared to controls. The numbers of both eye mature cell types, photoreceptor neurons and eye-cup pigment cells, are significantly decreased in the Smed-egfr-4(RNAi) animals. In contrast, the number of eye progenitor cells expressing the specific markers Smed-ovo and Smed-sp6-9 is increased. These results suggest that Smed-egfr-4 would be required not for the specification of eye progenitor cells but rather for their final differentiation and support the idea that in planarians the EGFR pathway could play a general role regulating the differentiation of lineage-committed progenitors.

developmental biology↗

bioRxiv2018

A mixed-model approach for powerful testing of genetic associations with cancer risk incorporating tumor characteristics

AO_SCPLOWBSTRACTC_SCPLOWCancers are routinely classified into subtypes according to various features, including histopathological characteristics and molecular markers. Previous genome-wide association studies have reported heterogeneous associations between loci and cancer subtypes. However, it is not evident what is the optimal modeling strategy for handling correlated tumor features, missing data, and increased degrees-of-freedom in the underlying tests of associations. We propose to test for genetic associations using a mixed-effect two-stage polytomous model score test (MTOP). In the first stage, a standard polytomous model is used to specify all possible sub-types defined by the cross-classification of the tumor characteristics. In the second stage, the subtype-specific case-control odds ratios are specified using a more parsimonious model based on the case-control odds ratio for a baseline subtype, and the case-case parameters associated with tumor markers. Further, to reduce the degrees-of-freedom, we specify case-case parameters for additional exploratory markers using a random-effect model. We use the Expectation-Maximization (EM) algorithm to account for missing data on tumor markers. Through simulations across a range of realistic scenarios and data from the Polish Breast Cancer Study (PBCS), we show MTOP outperforms alternative methods for identifying heterogeneous associations between risk loci and tumor subtypes. The proposed methods have been implemented in a user-friendly and high-speed R statistical package called TOP (https://github.com/andrewhaoyu/TOP).

genetics↗

bioRxiv2018

IsoProt: A fully reproducible one-stop-shop for the analysis of iTRAQ/TMT data

Reproducibility has become a major concern in biomedical research. In proteomics, bioinformatic workflows can quickly consist of multiple software tools each with its own set of parameters. Their usage involves the definition of often hundreds of parameters as well as data operations to ensure tool interoperability. Hence a manuscripts methods section is often insufficient to completely describe and reproduce a data analysis workflow. Here we present IsoProt: A complete and reproducible bioinformatic workflow deployed on a portable container environment to analyse data from isobarically-labeled, quantitative proteomics experiments. The workflow uses only open source tools and provides a user-friendly and interactive browser interface to configure and execute the different operations. Once the workflow is executed, the results including the R code to perform statistical analyses can be downloaded as an HTML or PDF document providing a complete record of the performed analyses. IsoProt therefore represents a reproducible bioinformatics workflow that will yield identical results on any computer platform.

bioinformatics↗

bioRxiv2018

A two-step mechanism for the inactivation of microtubule organizing center function at the centrosome

SummaryDuring mitosis, the centrosome acts as a microtubule organizing center (MTOC), orchestrating microtubules into the mitotic spindle through its pericentriolar material (PCM). This activity is biphasic, cycling through assembly and disassembly during the cell cycle. Although hyperactive centrosomal MTOC activity is a hallmark of some cancers, little is known about how the centrosome is inactivated as an MTOC. Analysis of endogenous PCM proteins in C. elegans revealed that the PCM is composed of distinct protein territories that are removed from the centrosome at different rates and using different behaviors. Inhibition of PP2A phosphatases stabilized the PCM and perturbation of cortical pulling forces altered the timing and behavior by which proteins were removed from the centrosome. These data indicate that PCM disassembly is a two-step process, beginning with a phosphatase-dependent dissolution of PCM proteins followed by the ejection of ruptured PCM by cortical forces, ultimately inactivating MTOC function at the centrosome.

cell biology↗

bioRxiv2018

Single-Cell Transcriptomics Unveils Gene Regulatory Network Plasticity

SUMMARYSingle-cell RNA sequencing (scRNA-seq) plays a pivotal role in our understanding of cellular heterogeneity. Current analytical workflows are driven by categorizing principles that consider cells as individual entities and classify them into complex taxonomies. We have devised a conceptually different computational framework based on a holistic view, where single-cell datasets are used to infer global, large-scale regulatory networks. We developed correlation metrics that are specifically tailored to single-cell data, and then generated, validated and interpreted single-cell-derived regulatory networks from organs and perturbed systems, such as diabetes and Alzheimers disease. Using advanced tools from graph theory, we computed an unbiased quantification of a genes biological relevance, and accurately pinpointed key players in organ function and drivers of diseases. Our approach detected multiple latent regulatory changes that are invisible to single-cell workflows based on clustering or differential expression analysis. In summary, we have established the feasibility and value of regulatory network analysis using scRNA-seq datasets, which significantly broadens the biological insights that can be obtained with this leading technology.

genomics↗

bioRxiv2018

An empirical evaluation of multivariate lesion behaviour mapping using support vector regression

Multivariate lesion behaviour mapping based on machine learning algorithms has recently been suggested to complement the methods of anatomo-behavioural approaches in cognitive neuroscience. Several studies applied and validated support vector regression-based lesion symptom mapping (SVR-LSM) to map anatomo-behavioural relations. However, this promising method, as well as the multivariate approach per se, still bears many open questions. By using large lesion samples in three simulation experiments, the present study empirically tested the validity of several methodological aspects. We found that i) correction for multiple comparisons is required in the current implementation of SVR-LSM, ii) that sample sizes of at least 100 to 120 subjects are required to optimally model voxel-wise lesion location in SVR-LSM, and iii) that SVR-LSM is susceptible to misplacement of statistical topographies along the brains vasculature to a similar extent as mass-univariate analyses.

neuroscience↗

bioRxiv2018

Glass confers rhabdomeric photoreceptor identity in Drosophila, but not across all metazoans

Across metazoans, visual systems employ different types of photoreceptor neurons to detect light. These include rhabdomeric PRs, which exist in distantly related phyla and possess an evolutionarily conserved phototransduction cascade. While the development of rhabdomeric PRs has been thoroughly studied in the fruit fly Drosophila melanogaster, we still know very little about how they form in other species. To investigate this question, we tested whether the transcription factor Glass, which is crucial for instructing rhabdomeric PR formation in Drosophila, may play a similar role in other metazoans. Glass homologues exist throughout the animal kingdom, indicating that this protein evolved prior to the metazoan radiation. Interestingly, our work indicates that glass is not expressed in rhabdomeric photoreceptors in the planarian Schmidtea mediterranea nor in the annelid Platynereis dumerilii. Combined with a comparative analysis of the Glass DNA-binding domain, our data suggest that the fate of rhabdomeric PRs is controlled by Glass-dependent and Glass-independent mechanisms in different animal clades.

developmental biology↗

bioRxiv2018

Quantitative insights into the cyanobacterial cell economy

Phototrophic microorganisms are promising resources for green biotechnology. Compared to heterotrophic microorganisms, however, the cellular economy of phototrophic growth is still insufficiently understood. We provide a quantitative analysis of light-limited, light-saturated, and light-inhibited growth of the cyanobacterium Synechocystis sp. PCC 6803 using a reproducible cultivation setup. We report key physiological parameters, including growth rate, cell size, and photosynthetic activity over a wide range of light intensities. Intracellular proteins were quantified to monitor proteome allocation as a function of growth rate. Among other physiological adaptations, we identify an upregulation of the translational machinery and downregulation of light harvesting components with increasing light intensity and growth rate. The resulting growth laws are discussed in the context of a coarse-grained model of phototrophic growth and available data obtained by a comprehensive literature search. Our insights into quantitative aspects of cyanobacterial adaptations to different growth rates have implications to understand and optimize photosynthetic productivity.

microbiology↗

bioRxiv2018

Stepwise evolution and convergent recombination underlie the global dissemination of carbapenemase-producing Escherichia coli

Carbapenem-resistant Enterobacteriaceae are considered by WHO as \"critical\" priority pathogens for which novel antibiotics are urgently needed. The dissemination of carbapenemase-producing Escherichia coli (CP-Ec) in the community is a major public health concern. However, the global molecular epidemiology of CP-Ec isolates, as well as the genetic bases for the emergence and global dissemination of specific lineages, remain largely unknown. Here, by combining a thorough genomic and evolutionary analysis of Ec ST410 isolates with a broad analysis of 12,584 E. coli and Shigella genomes, we showed that the fixation of carbapenemase genes depends largely on a combination of mutations in ftsI encoding the penicillin binding protein 3 and in the porin genes ompC and ompF. Mutated ftsI genes and a specific ompC allele inducing reduced susceptibility to diverse {beta}-lactams spread across the species by recombination. The selection of CP-Ec lineages able to disseminate is more complex than the mere acquisition of carbapenemase genes.

microbiology↗

bioRxiv2018

Teaching methods shape neural tuning to visual words in beginning readers

The impact of global vs. phonics teaching methods for reading on the emergence of left hemisphere neural specialization for word recognition is unknown in children. We tested 42 first graders behaviorally and with electroencephalography with Fast Periodic Visual Stimulation to measure selective neural responses to letter strings. Letter strings were inserted periodically (1/5) in pseudofonts in 40sec sequences displayed at 6Hz and were either words globally taught at school, eliciting visual whole-word form recognition (global method), or control words/pseudowords eliciting grapheme-phoneme mappings (phonic method). Selective responses (F/5, 1.2Hz) were left lateralized for control stimuli but bilateral for globally taught words, especially in poor readers. These results show that global method instruction induces activation in the right hemisphere, involved in holistic processing and visual object recognition, rather than in the specialized left hemisphere for reading. Poor readers, given their difficulties in automatizing grapheme-phoneme mappings, mostly rely on this alternative inadequate strategy.

neuroscience↗

bioRxiv2018

PACS-1 and Adaptor Protein-1 Mediate ACTH Trafficking to the Regulated Secretory Pathway

The regulated secretory pathway is a specialized form of protein secretion found in endocrine and neuroendocrine cell types. Pro-opiomelanocortin (POMC) is a pro-hormone that utilizes this pathway to be trafficked to dense core secretory granules (DCSGs). Within this organelle, POMC is processed to multiple bioactive hormones that play key roles in cellular physiology. However, the complete set of cellular membrane trafficking proteins that mediate the correct sorting of POMC to DCSGs remain unknown. Here, we report the roles of the phosphofurin acidic cluster sorting protein - 1 (PACS-1) and the clathrin adaptor protein 1 (AP-1) in the targeting of POMC to DCSGs. Upon knockdown of PACS-1 and AP-1, POMC is readily secreted into the extracellular milieu and fails to be targeted to DCSGs.

cell biology↗

bioRxiv2018

Dynamic Brain Connectivity Alternation Detection via Matrix-variate Differential Network Model

MotivationNowadays brain connectivity analysis has attracted tremendous attention and has been at the foreground of neuroscience research. Brain functional connectivity reveals the synchronization of brain systems through correlations in neurophysiological measures of brain activity. Growing evidence now suggests that the brain connectivity network experiences alternations with the presence of numerous neurological disorders, thus differential brain network analysis may provides new insights into disease pathologies. For the matrix-valued data in brain connectivity analysis, existing graphical model estimation methods assume a vector normal distribution that in essence requires the columns of the matrix data to be independent. It is obviously not true, they have limited applications. Among the few solutions on graphical model estimation under a matrix normal distribution, none of them tackle the estimation of differential graphs across different populations. This motivates us to consider the differential network for matrix-variate data to detect the brain connectivity alternation.\n\nResultsThe primary interest is to detect spatial locations where the connectivity, in terms of the spatial partial correlation, differ across the two groups. To detect the brain connectivity alternation, we innovatively propose a Matrix-Variate Differential Network (MVDN) model. MVDN assumes that the matrix-variate data follows a matrix-normal distribution. We exploit the D-trace loss function and a Lasso-type penalty to directly estimate the spatial differential partial correlation matrix where the temporal information is fully excavated. We propose an ADMM algorithm for the Lasso penalized D-trace loss optimization problem. We investigate theoretical properties of the estimator. We show that under mild and regular conditions, the proposed method can identify all differential edges accurately with probability tending to 1 in high-dimensional setting where dimensions of matrix-valued data p, q and sample size n are all allowed to go to infinity. Simulation studies demonstrate that MVDN provides more accurate differential network estimation than that achieved by other state-of-the-art methods. We apply MVDN to Electroencephalography (EEG) dataset, which consists of 77 alcoholic individuals and 45 controls. The hub genes and differential interaction patterns identified are consistent with existing experimental studies.\n\nContactheyong@sdufe.edu.cn\n\nSupplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2018

The winner takes it all: how semelparous insects can become periodical

The aim of this short note is to give a simple explanation for the remarkable periodicity of Magicicada species, which appear as adults only every 13 or 17 years, depending on the region. We show that a combination of two types of density dependence may drive, for large classes of initial conditions, all but one year class to extinction. Competition for food leads to negative density dependence in the form of a uniform (i.e., affecting all age classes in the same way) reduction of the survival probability. Satiation of predators leads to positive density dependence within the reproducing age class. The analysis focuses on the full life cycle map derived by iteration of a semelparous Leslie matrix.

ecology↗