Biology subjects

Fu, R.

Publications and source records attributed to Fu, R..

60 records · Page 4Linked to original sources

bioRxiv2020

Integrated decoding hematopoiesis and leukemogenesis at single-cell resolution and its clinical implication

Integrated analyses of hematopoiesis and leukemogenesis could provide new biological and clinical insights1,2. Here we constructed a comprehensive cell atlas using [~]100,000 single cell transcriptomes of bone marrow mononuclear cells and its subsets from 5 healthy samples and 13 leukemia samples. Trajectory analysis showed hematopoietic stem cells continuously differentiated through tree-like structure into 7 lineages. Although our single cell analyses showed the major cellular heterogeneity were inter-patients, there were distinct leukemia cell subpopulations within patient. We developed counterpart composite index (CCI) for projecting leukemia cell subpopulation into reference hematopoietic cells, to identify their healthy counterparts that could predict leukemia subtype and clinical outcome. Interestingly, we found the trajectories of leukemogenesis were similar to that of their healthy counterparts, indicating lineage relationship of leukemia cell subpopulations. Single cell analyses of leukemia patient at diagnosis, refractory, remission and relapse vividly presented dynamics of cell population and the underlying genes. Single cell transcriptomic variants analyses showed the relapsed leukemia cells, whose healthy counterparts were closer to the root of hematopoietic tree, were derived from an early minor leukemia cell population. This study not only increased our understanding of hematopoiesis and leukemogenesis, but also provided an approach for leukemia classification and clinical outcome prediction.

genomics↗

bioRxiv2019

clustifyr: An R package for automated single-cell RNA sequencing cluster classification

BackgroundIn single-cell RNA sequencing (scRNA-seq) analysis, assignment of likely cell types remains a time-consuming, error-prone, and biased process. Current packages for identity assignment use limited types of reference data, and often have rigid data structure requirements. As such, a more flexible tool, capable of handling multiple types of reference data and data structures, would be beneficial. FindingsTo address difficulties in cluster identity assignment, we developed the clustifyr R package. The package leverages external datasets, including gene expression profiles from scRNA-seq, bulk RNA-seq, microarray expression data, and/or signature gene lists, to assign likely cell types. We benchmark various parameters of a correlation-based approach, and also implement a variety of gene list enrichment methods. By providing tools for exploratory data analysis, we demonstrate the feasibility of a simple and effective data-driven approach for cell type assignment in scRNA-seq cell clusters. Conclusionsclustifyr is a lightweight and effective cell type assignment tool developed for compatibility with various scRNA-seq analysis workflows. clustifyr is publicly available at https://github.com/rnabioco/clustifyr

bioinformatics↗

bioRxiv2019

Exploring the Mechanism of Olfactory Recognition at the Initial Stage by Modeling the Emission Spectrum of Electron Transfer

Olfactory sense remains elusive regarding the primary reception mechanism. Some studies suggest that olfaction is a spectral sense, the olfactory event is triggered by electron transfer (ET) across the odorants at the active sites of odorant receptors (ORs). Herein we present a Donor-Bridge-Acceptor model, proposing that the ET process can be viewed as an electron hopping from the donor molecule to the odorant molecule (Bridge), then hopping off to the acceptor molecule, making the electronic state of the odorant molecule change along with vibrations (vibronic transition). The odorant specific parameter, Huang-Rhys factor can be derived from ab initio calculations, which make the simulation of ET spectra achievable. In this study, we revealed that the emission spectra (after Gaussian convolution) can be acted as odor characteristic spectra. Using the emission spectrum of ET, we were able to reasonably interpret the similar bitter-almond odors among hydrogen cyanide, benzaldehyde and nitrobenzene. In terms of isotope effects, we succeeded in explaining why subjects can easily distinguish cyclopentadecanone from its fully deuterated analogue cyclopentadecanone-d28 but not distinguishing acetophenone from acetophenone-d8.

biophysics↗

bioRxiv2019

De novo Identification of Essential Protein Domains from CRISPR/Cas9 Tiling-sgRNA Knockout Screens

High-throughput CRISPR/Cas9 knockout screens using a tiling-sgRNA design permit in situ evaluation of protein domain function. To facilitate de novo identification of essential protein domains from such screens, we developed ProTiler, a computational method for the robust mapping of CRISPR knockout hyper-sensitive (CKHS) regions, which refers to the protein regions that are associated with strong sgRNA dropout effect in the screens. We used ProTiler to analyze a published CRISPR tiling screen dataset, and identified 175 CKHS regions in 83 proteins. Of these CKHS regions, more than 80% overlapped with annotated Pfam domains, including all of the 15 known drug targets in the dataset. ProTiler also revealed unannotated essential domains, including the N-terminus of the SWI/SNF subunit SMARCB1, which we validated experimentally. Surprisingly, the CKHS regions were negatively correlated with phosphorylation and acetylation sites, suggesting that protein domains and post-translational modification sites have distinct sensitivities to CRISPR/Cas9 mediated amino acids loss.

bioinformatics↗

bioRxiv2018

Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries

Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries often prevents full characterization of transcriptomes from individual cells. To extract more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. We applied the method in cell-centric and gene-centric modes to isolate cDNA fragments from scRNA-seq libraries. First, we resampled the transcriptomes of rare, single megakaryocytes from a complex mixture of lymphocytes and analyzed them in a second round of DNA sequencing, yielding up to 20-fold greater sequencing depth per cell and increasing the number of genes detected per cell from a median of 1,313 to 2,002. We similarly isolated mRNAs from targeted T cells to improve the reconstruction of their VDJ-rearranged immune receptor mRNAs. Second, we isolated CD3D mRNA fragments expressed across cells in a scRNA-seq library prepared from a clonal T cell line, increasing the number of cells with detected CD3D expression from 59.7% to 100%. Transcriptome resampling is a general approach to recover targeted gene expression information from single-cell RNA sequencing libraries that enhances the utility of these costly experiments, and may be applicable to the targeted recovery of molecules from other single-cell assays.

genomics↗

bioRxiv2017

Worldwide Population Structure Of Escherichia coli Reveals Two Major Subspecies

Recombination is one of the most important mechanisms of prokaryotic species evolution but its exact roles are still in debate. Here we try to infer genome-wide recombination events within a species uti-lizing a dataset of 104 complete genomes of Escherichia coli from diverse origins, among which 45 from world-wide animal-hosts are in-house sequenced using SMRT (single-molecular real time) technology.Two major clades are identified based on evidences of ecological and physiological characteristics, as well as distinct genomic features implying scarce inter-clade genetic exchange. By comparing the synteny of identical fragments genome-widely searched for each genome pair, we achieve a fine-scale map of re-combination within the population. The recombination is rather extensive within clade, which is able to break linkages between genes but does not interrupt core genome framework and primary metabolic port-folios possibly due to natural selection for physiological compatibility and ecological fitness. Meanwhile,the recombination between clades declines drastically as the phylogenetic distance increases, generally 10-fold reduced than those of the intra-clade, which establishes genetic barrier between clades. These empirical data of recombination suggest its critical role in the early stage of speciation, where recombina-tion rate differs according to phylogentic distance. The extensive intra-clade recombination coheres sister strains into a quasi-sexual group and optimizes genes or alleles to streamline physiological activities,whereas shapely declined inter-clade recombination split the population into clades adaptive to divergent ecological niches.\n\nSignificance StatementRoles of recombination in species evolution have been debated for decades due to difficulties in inferring recombination events during the early stage of speciation, especially when recombination is always complicated by frequent gene transfer events of bacterial genomes. Based on 104 high-quality complete E. coli genomes, we infer gene-centric dynamics of recombination in the formation of two E. coli clades or subpopulations, and recombination is found to be rather intensive in a within-clade fashion, which forces them to be quasi-sexual. The recombination events can be mapped among individual genomes in the context of genes and their variations; decreased between-clade and increased intra-claderecombination engender a genetic barrier that further encourages clade-specific secondary metabolic portfolios for better environmental adaptation. Recombination is thus a major force that accelerates bacterial evolution to fit ecological diversity.

microbiology↗