Biology subjects

Zhu, R.

Publications and source records attributed to Zhu, R..

101 records · Page 6Linked to original sources

bioRxiv2019

A new strategy for selection of crop cultivated varieties based on yield factors driving and meteorological prediction

Meteorological conditions, as an uncontrollable factor, have a direct impact on the growth and yield of crops in the field. Its particularly important to choose the cultivated varieties suitable for environmental change. As for this problem, a new strategy for selection of crop cultivated varieties is proposed in this paper. The experiment selected Harbin pilot (Heilongjiang, China) and Changchun pilot (Jilin, China). In the experiment, the cultivated varieties suitable for forecasting meteorological conditions in 2015 could be provided according to the meteorological data of 2005-2014 years and the yield data of different soybean varieties in Harbin pilot. The same method was also taken in Changchun pilot. The results showed that the recommended varieties of Harbin pilot and Changchun pilot had 70% and 50% probability respectively for selection of soybean cultivated varieties when the yield evaluation trait was 100-seed-weight. As for seed weight per plant, the possibility of more than 60% of the recommended varieties in two pilots is to provide prejudgment. Therefore, this method can help to improve the current situation of the impact of uncontrollable meteorological conditions on crop yield and also can be applied to the selection of any other crops cultivated varieties under a certain environment.

plant biology↗

bioRxiv2019

Discovering Differences and Similarities among Species Based on Numeric Features of microRNAs

Numeric features of microRNA (miRNA) are different from the other RNAs and play a key role in the course of miRNA recognition. Are there significant differences about such numeric features between different species? Are there some species specific about it? In order to answer questions, we implemented the Kolmogorov-Smirnov test for 32 species based on 132 numeric features of miRNAs. Results demonstrate that almost all kinds of miRNA secondary structures matching frequencies show highly similar, and this means that such secondary structure tend to be specific to miRNAs. Length of pre-miRNA, minimal free energy (MFE), and number of stacks show bigger difference between different species, and this means that such features tend to be species-specific. In order to discover differences and similarities among species based on numeric features of miRNAs, we design two tools-species difference map and feature difference map. By species difference map, we find that numeric features of miRNAs can represent class attribute of species and the map basically describe relationship between different species. By feature difference map, we find that there are huge difference about difference of every numeric feature between different species, and this means that strength of such difference is not uniform. Meantime, it means that numeric feature of miRNAs can represent different attributes of corresponding species. Our study present relationship between different species by brand new style-numeric features of miRNAs.

bioinformatics↗

bioRxiv2019

Trajectories from Snapshots: Integrated proteomic and metabolic single-cell assays reveal multiple independent adaptive responses to drug tolerance in a BRAF-mutant melanoma cell line

The determination of individual cell trajectories through a high-dimensional cell-state space is an outstanding challenge, with relevance towards understanding biological changes ranging from cellular differentiation to epigenetic (adaptive) responses of diseased cells to drugging. We report on a combined experimental and theoretic method for determining the trajectories that specific highly plastic BRAFV600E mutant patient-derived melanoma cancer cells take between drug-naive and drug-tolerant states. Recent studies have implicated non-genetic, fast-acting resistance mechanisms are activated in these cells following BRAF inhibition. While single-cell highly multiplex omics tools can yield snapshots of the cell state space landscape sampled at any given time point, individual cell trajectories must be inferred from a kinetic series of snapshots, and that inference can be confounded by stochastic cell state switching. Using a microfludic-based single-cell integrated proteomic and metabolic assay, we assayed for a panel of signaling, phenotypic, and metabolic regulators at four time points during the first five days of drug treatment. Dimensional reduction of the resultant data set, coupled with information theoretic analysis, uncovered a complex cell state landscape and identified two distinct paths connecting drug-naive and drug-tolerant states. Cells are shown to exclusively traverse one of the two pathways depending on the level of the lineage restricted transcription factor MITF in the drug-naive cells. The two trajectories are associated with distinct signaling and metabolic susceptibilities, and are independently druggable. Our results update the paradigm of adaptive resistance development in an isogenic cell population and offer insight into the design of more effective combination therapies.

bioengineering↗

bioRxiv2019

Anomalous phylogenetic behavior of ribosomal proteins in metagenome assembled genomes

Metagenomic studies have claimed the existence of novel lineages with unprecedented properties never before observed in prokaryotes. Such lineages include Asgard archaea1-3, which are purported to represent archaea with eukaryotic cell complexity, and the Candidate Phyla Radiation (CPR), a novel domain level taxon erected solely on the basis of metagenomic data4. However, it has escaped the attention of most biologists that these metagenomic sequences are not assembled into genomes by sequence overlap, as for cultured archaea and bacteria. Instead, short contigs are sorted into computer files by a process called binning in which they receive taxonomic assignment on the basis of sequence properties like GC content, dinucleotide frequencies, and stoichiometric co-occurrence across samples. Consequently, they are not genome sequences as we know them, reflecting the gene content of real organisms. Rather they are metagenome assembled genomes (MAGs). Debates that Asgard data are contaminated with individual eukaryotic sequences5-7 are overshadowed by the more pressing issue that no evidence exists to indicate that any sequences in binned Asgard MAGs actually stem from the same chromosome, as opposed to simply stemming from the same environment. Here we show that Asgard and CPR MAGs fail spectacularly to meet the most basic phylogenetic criterion8 fulfilled by genome sequences of all cultured prokaryotes investigated to date: the ribosomal proteins of Asgard and CPR MAGs do not share common evolutionary histories. Their phylogenetic behavior is anomalous to a degree never observed with genomes of real organisms. CPR and Asgard MAGs are binning artefacts, assembled from environments where up to 90% of the DNA is from dead cells9-12. Asgard and CPR MAGs are unnatural constructs, genome-like patchworks of genes that have been stitched together into computer files by binning.

evolutionary biology↗

bioRxiv2019

Mitochondria branch within Alphaproteobacteria

It is well accepted that mitochondria originated from an alphaproteobacterial-like ancestor. However, the phylogenetic relationship of the mitochondrial endosymbiont to extant alphaproteobacteria remains a subject of discussion. The focus of much debate is whether the affiliation between mitochondria and fast-evolving alphaproteobacterial lineages reflects true homology or artifacts. Approaches such as protein-recoding and site-exclusion have been claimed to mitigate compositional heterogeneity between taxa but this comes at the cost of information loss and the reliability of such methods is so far unjustified. Here we demonstrate that site-exclusion methods produce erratic phylogenetic estimates of mitochondrial origin. We applied alternative strategies to reduce phylogenetic noise by taxon replacement and selective exclusion while keeping site substitution information intact. Cross-validation based on a series of trees placed mitochondria robustly within Alphaproteobacteria.

evolutionary biology↗

bioRxiv2019

Large particle fluorescence-activated cell sorting enables high quality single cell RNA-sequencing and functional analysis of adult cardiomyocytes

RationaleSingle cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to profile the transcriptome at single cell resolution, enabling comprehensive analysis of cellular trajectories and heterogeneity during development and disease. However, the use of scRNA-seq remains limited in cardiac pathology owing to technical difficulties associated with the isolation of single adult cardiomyocytes (CMs).\n\nObjectiveWe investigated the capability of large-particle fluorescence-activated cell sorting (LP-FACS) for isolation of viable single adult CMs.\n\nMethods and ResultsWe found that LP-FACS readily outperforms conventional FACS for isolation of struturally competent CMs, including large CMs. Additionally, LP-FACS enables isolation of fluorescent CMs from mosaic models. Importantly, the sorted CMs allow generation of high-quality scRNA-seq libraries. Unlike CMs isolated via previously utilized fluidic or manual methods, LP-FAC-isolated CMs generate libraries exhibiting normal levels of mitochondrial transcripts. Moreover, LP-FACS isolated CMs remain functionally competent and can be studied for contractile properties.\n\nConclusionsOur study enables high quality dissection of adult CM biology at single-cell resolution.

cell biology↗

bioRxiv2019

Semantic Integration of Clinical Laboratory Tests from Electronic Health Records for Deep Phenotyping and Biomarker Discovery

Electronic Health Record (EHR) systems typically define laboratory test results using the Laboratory Observation Identifier Names and Codes (LOINC) and can transmit them using Fast Healthcare Interoperability Resource (FHIR) standards. LOINC has not yet been semantically integrated with computational resources for phenotype analysis. Here, we provide a method for mapping LOINC-encoded laboratory test results transmitted in FHIR standards to the Human Phenotype Ontology (HPO) terms. We annotated the medical implications of 2421 commonly used laboratory tests with HPO terms. Using these annotations, a software assesses laboratory test results and converts each into an HPO term. We validated our approach with EHR data from 15,681 patients with respiratory complaints and identified known biomarkers for asthma. Finally, we provide a freely available SMART on FHIR application that can be used within EHR systems. Our approach allows reusing readily available laboratory tests in EHR for deep phenotyping and using the hierarchical structure of HPO for association studies with medical outcomes and genomics.\n\nOne Sentence SummaryWe present an approach to semantically integrating LOINC-encoded laboratory data with the Human Phenotype Ontology and show that the integrated LOINC data can be used to identify biomarkers for asthma from electronic health record data.

bioinformatics↗

bioRxiv2018

Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data

Calcium imaging has revolutionized systems neuroscience, providing the ability to image large neural populations with single-cell resolution. The resulting datasets are quite large (with scales of TB/hour in some cases), which has presented a barrier to routine open sharing of this data, slowing progress in reproducible research. State of the art methods for analyzing this data are based on non-negative matrix factorization (NMF); these approaches solve a non-convex optimization problem, and are highly effective when good initializations are available, but can break down e.g. in low-SNR settings where common initialization approaches fail.\n\nHere we introduce an improved approach to compressing and denoising functional imaging data. The method is based on a spatially-localized penalized matrix decomposition (PMD) of the data to separate (low-dimensional) signal from (temporally-uncorrelated) noise. This approach can be applied in parallel on local spatial patches and is therefore highly scalable, does not impose non-negativity constraints or require stringent identifiability assumptions (leading to significantly more robust results compared to NMF), and estimates all parameters directly from the data, so no hand-tuning is required. We have applied the method to a wide range of functional imaging data (including one-photon, two-photon, three-photon, widefield, somatic, axonal, dendritic, calcium, and voltage imaging datasets): in all cases, we observe ~2-4x increases in SNR and compression rates of 20-300x with minimal visible loss of signal, with no adjustment of hyperparameters; this in turn facilitates the process of demixing the observed activity into contributions from individual neurons. We focus on two challenging applications: dendritic calcium imaging data and voltage imaging data in the context of optogenetic stimulation. In both cases, we show that our new approach leads to faster and much more robust extraction of activity from the video data.

neuroscience↗

bioRxiv2018

EZH2 co-opts gain-of-function p53 mutants to promote cancer growth and metastasis

With the unfolding of more and more cancer-driven gain-of-function (GOF) mutants of p53, it is important to define a common mechanism to systematically target different mutants rather than develop strategies tailored to inhibit each mutant individually. Here, using RNA immunoprecipitation sequencing (RIP-seq) we identified EZH2 as a p53 mRNA-binding protein. EZH2 bound to the internal ribosome entry site (IRES) in the 5 untranslated region (5UTR) of p53 mRNA and enhanced p53 protein translation in a methyltransferase-independent manner. EZH2 augmented p53 GOF mutant-mediated cancer growth and metastasis by increasing p53 GOF mutant protein level. EZH2 overexpression associated with the worse outcome only in patients with p53-mutated cancer. Depletion of EZH2 by antisense oligonucleotides inhibited p53 GOF mutant-mediated cancer growth. Our findings reveal a non-methyltransferase function of EZH2 that controls protein translation of p53 GOF mutants, inhibition of which causes synthetic lethality in cancer cells expressing p53 GOF mutants.

cancer biology↗

bioRxiv2018

Complete guide RNA design for CRISPR-mediated regulation of human long noncoding RNA transcription

Transcription inhibition and activation of long noncoding RNAs (lncRNAs) mediated by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 technology provides potential advantages in high-throughput functional genomics studies over RNA interference or overexpression platforms. In this work, we identify over 90,000 lncRNA transcription start sites (TSSs) based on the MiTranscriptome human genome annotation and design single guide RNA (sgRNA) libraries with strong predicted activities and low off-target effects for CRISPR-mediated inhibition and activation (CRISPRi/a) of their transcription. A large fraction of these TSSs correspond to putative genes that are not annotated in common reference genome annotations and have never been functionally studied. Our CRISPRi/a libraries, or their context-dependent subsets, are potentially useful in genome-scale functional studies of human lncRNAs.

bioengineering↗

bioRxiv2017

Relevance of host cell surface glycan structure for cell specificity of influenza A virus

Influenza A viruses (IAV) initiate infection via binding of the viral hemagglutinin (HA) to sialylated glycan receptors on host cells. HAs receptor specificity towards sialic acid (SA) is well studied and clearly critical for virus infection, but the contribution of the highly complex cellular plasma membrane to the cellular specificity remains elusive. In addition, some studies indicated that other host cell factors such as the epidermal growth factor receptor might contribute to the initial virus-cell contact and further downstream signaling1.\n\nHere we use two complementary methods, glycan arrays and single-virus force spectroscopy (SVFS) to compare influenza virus receptor specificity with actual host cell binding. Unexpectedly, our study reveals that HAs receptor binding preference does not necessarily reflect virus-cell specificity. We propose SVFS as a tool to elucidate the cell binding preference of IAV thereby including the complex environment of sialylated receptors within the plasma membrane of living cells.

microbiology↗