Single‑cell RNA sequencing of t(8;21) acute myeloid leukemia for risk prediction

Single-cell RNA sequencing (scRNA-seq) of bone marrow or peripheral blood samples from patients with acute myeloid leukemia (AML) enables the characterization of heterogeneous malignant cells. A total of 87 cells from two patients with t(8;21) AML were analyzed using scRNA-seq. Clustering methods were used to separate leukemia cells into different sub-populations, and the expression patterns of specific marker genes were used to annotate these populations. Among the 31 differentially expressed genes in the cells of a patient who relapsed after hematopoietic stem cell transplantation, 13 genes were identified to be associated with leukemia. Furthermore, three genes, namely AT-rich interaction domain 2, lysine methyltransferase 2A and synaptotagmin binding cytoplasmic RNA interacting protein were validated as possible prognostic biomarkers using two bulk expression datasets. Taking advantage of scRNA-seq, the results of the present study may provide clinicians with several possible biomarkers to predict the prognostic outcomes of t(8;21) AML.

[Clinical features of 2019 novel coronavirus pneumonia in the early stage from a fever clinic in Beijing]

Objective: To summarize and analyze the clinical and imaging characteristics of patients with 2019 novel coronavirus pneumonia in the early stage in Beijing. Methods: A retrospective analysis of clinical and imaging data of 9 patients with 2019 novel coronavirus infection diagnosed in one fever clinicic in Beijing from January 18, 2020 to February 3, 2020. Results: 5 male and 4 female was included in those 9 patients, whose median age was 36 years, and the age range from 15 to 49 years. 8 of these patients had no underlying disease and one suffered from diabetes. 7 patients had a history of travel to Wuhan City or Hubei Province, and one patient was a medical staff. Two family clustered was found. The incubation period was 1 to 6 days. The clinical manifestations were fever in 8 cases (8/9) , dry cough in 5 cases (5/9) , pharyngalgia in 4 cases (4/9) , fatigue in 4 cases (4/9) , body soreness in 4 cases (4/9) , and blocked or watery nose in 1 case (1/9) . Six patients (6/9) had abnormal cell peripheral blood, of which 3 (3/9) had an increased monocyte count, 2 (2/9) had a reduced lymphocyte , and 1 (1/9) had an increased leukocyte count, while the 3 patients had normal cell blood routines. The median of CRP was 16.3 mg/L, including 5 patients with slightly elevated (5/9) , 4 patients with normal values (4/9) . the results of procalcitonin test were negative in5 patients. Three patients were examined by chest X-ray examination, one of which was normal, one case showed infiltrates of right upper lung, and another showed in right lower lung. All patients underwent chest HRCT. And 7 cases (7/9) showed multiple ground glass exudation, including 5 cases (5/7) involved bilateral lungs, 2 cases (2/7) involved unilateral lung, 3 cases (3/7) with patchy consolidation, and 2 cases (2/9) showed no abnormality. Conclusions: The patents with 2019 novel coronavirus pneumonia in this study generally have an epidemiological history. The clinical manifestations are fever and cough. Peripheral white blood cell counts were most normal And PCT were all negative. Chest HRCT manifested as multiple ground-glass opacities with partly consolidation. Some patients had normal chest radiographs but HRCT showed pneumonia. Some patients had no pneumonia on chest HRCT.

Dynamic Alternative Splicing During Mouse Preimplantation Embryo Development

The mechanism of alternative pre-mRNA splicing (AS) during preimplantation development is largely unknown. In order to capture the dynamic changes of AS occurring during embryogenesis, we carried out bioinformatics analysis based on scRNA-seq data over the time-course preimplantation development in mouse. We detected numerous previously-unreported differentially expressed genes at specific developmental stages and investigated the nature of AS at both minor and major zygotic genome activation (ZGA). The AS and differential AS atlas over preimplantation development were established. The differentially alternatively spliced genes (DASGs) are likely to be key splicing factors (SFs) during preimplantation development. We also demonstrated that there is a regulatory cascade of AS events in which some key SFs are regulated by differentially AS of their own gene transcripts. Moreover, 212 isoform switches (ISs) during preimplantation development were detected, which may be critical for decoding the mechanism of early embryogenesis. Importantly, we uncovered that zygotic AS activation (ZASA) is in conformity with ZGA and revealed that AS is coupled with transcription during preimplantation development. Our results may provide a deeper insight into the regulation of early embryogenesis.

SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles

Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task. Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering. Clusters are often assigned to different cell types based on the enriched canonical markers. However, this process is inefficient and arbitrary. In this study, we present a technical framework of training the expandable supervised-classifier in order to reveal the single-cell identities as soon as the single-cell expression profile is input. Using multiple scRNA-seq datasets we demonstrate the superior accuracy, robustness, compatibility and expandability of this new solution compared to the traditional methods. We use two examples of the model upgrade to demonstrate how the projected evolution of the cell-type classifier is realized.

Integrative molecular analysis of metastatic hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the major type of primary liver cancer. Intrahepatic metastasis, such as portal vein tumor thrombosis (PVTT), strongly indicates poor prognosis of HCC. But now, there are limited understandings of the molecular features and mechanisms of those metastatic HCCs.

Methods

To characterize the molecular alterations of the metastatic HCCs, we implemented an integrative analysis of the copy number variations (CNVs), DNA methylations and transcriptomes of matched adjacent normal, primary tumor and PVTT samples from 19 HCC patients.

Results

CNV analysis identified a frequently amplified focal region chr11q13.3 and a novel deletion peak chr19q13.41 containing three miRNAs. The integrative analysis with RNA-seq data suggests that CNVs and differential promoter methylations regulate distinct oncogenic processes. Then, we used individualized differential analysis to identify the differentially expressed genes between matched primary tumor and PVTT of each patient. Results show that 5 out of 19 studied patients acquire evidential progressive alterations of gene expressions (more than 1000 differentially expressed genes were identified in each patient). While, another subset of eight patients have nearly identical gene expressions between the corresponding matched primary tumor and PVTT. Twenty genes were found to be recurrently and progressively differentially expressed in multiple patients. These genes are mainly associated with focal adhesion, xenobiotics metabolism by cytochrome P450 and amino acid metabolism. For several differentially expressed genes in metabolic pathways, their expressions are significantly associated with overall survivals and vascular invasions of HCC patients. The following transwell assay experiments validate that they can regulate invasive phenotypes of HCC cells.

Conclusions

The metastatic HCCs with PVTTs have significant molecular alterations comparing with adjacent normal tissues. The recurrent alteration patterns are similar to several previously published general HCC cohorts, but usually with higher severity. By an individualized differential analysis strategy, the progressively differentially expressed genes between the primary tumor and PVTT were identified for each patient. A few patients aquire evidential progressive alterations of gene expressions. And, experiments show that several recurrently differentially expressed genes can strongly regulate HCC cell invasions.

Single-cell stochastic gene expression kinetics with coupled positive-plus-negative feedback

Here we investigate single-cell stochastic gene expression kinetics in a minimal coupled gene circuit with positive-plus-negative feedback. A triphasic stochastic bifurcation is observed upon increasing the ratio of the positive and negative feedback strengths, which reveals a strong synergistic interaction between positive and negative feedback loops. We discover that coupled positive-plus-negative feedback amplifies gene expression mean but reduces gene expression noise over a wide range of feedback strengths when promoter switching is relatively slow, stabilizing gene expression around a relatively high level. In addition, we study two types of macroscopic limits of the discrete chemical master equation model: the Kurtz limit applies to proteins with large burst frequencies and the Lévy limit applies to proteins with large burst sizes. We derive the analytic steady-state distributions of the protein abundance in a coupled gene circuit for both the discrete model and its two macroscopic limits, generalizing the results obtained by Liu et al. [Chaos 26, 043108 (2016)CHAOEH1054-150010.1063/1.4947202]. We also obtain the analytic time-dependent protein distribution for the classical Friedman-Cai-Xie random bursting model [Friedman, Cai, and Xie, Phys. Rev. Lett. 97, 168302 (2006)PRLTAO0031-900710.1103/PhysRevLett.97.168302]. Our analytic results are further applied to study the structure of gene expression noise in a coupled gene circuit, and a complete decomposition of noise in terms of five different biophysical origins is provided.

Activities of key enzymes in the C4 pathway and anatomy of sugarcane infected by Leifsonia xyli subsp. xyli

AIMS

Ratoon stunting disease caused by Leifsonia xyli subsp. xyli (Lxx) is a bacterial disease that has plagued sugarcane-planting countries for a long time. This study mainly analysed Lxx localization and its effects on sugarcane leaf.

METHODS AND RESULTS

Badila were inocultated by bacteria of Lxx. It was noted that the number of Lxx cells were rapidly enriched in sugarcane leaves from the 150th to the 210th days of post inoculation (dpi). Lxx infection disrupted the integrity of vascular bundle sheath cells (BSC) in the 'Kranz anatomy' of leaves, resulting in irregular accumulation of starch in vascular BSC of leaves. In situ PCR showed that the Lxx localized in the xylem vessels, mesophyll cell (MC) and BSC as described before in sugarcane leaf, a new niche within the host tissues in the phloem of sugarcane stem. The gene expression and activities of phosphoenolpyruvate carboxylase (PEPC), pyruvate, orthophosphate dikinase (PPDK) and NADP-malic enzyme (NADP-ME) enzymes were lower in Lxx-inoculated sugarcane plants as compared to the MI group.

CONCLUSION

Lxx infection not only disrupted the structure of vascular BSC in the C4 'Kranz anatomy' of sugarcane leaves, but also affected the activities and gene expression of the key enzymes PEPC, PPDK and NADP-ME in the C4 cycle of sugarcane suggesting a reduction in CO₂ fixation.

SIGNIFICANCE AND IMPACT OF THE STUDY

The effect of Leifsonia xyli subsp. xyli (Lxx) infection on the photosynthetic physiology of sugarcane is currently limited to the evaluation of photosynthetic parameters. This study assessed the impact of Lxx infection on the mechanism of C4 cycle CO₂ fixation and to accompanying plant anatomy.

Web3DMol: interactive protein structure visualization based on WebGL

A growing number of web-based databases and tools for protein research are being developed. There is now a widespread need for visualization tools to present the three-dimensional (3D) structure of proteins in web browsers. Here, we introduce our 3D modeling program—Web3DMol—a web application focusing on protein structure visualization in modern web browsers. Users submit a PDB identification code or select a PDB archive from their local disk, and Web3DMol will display and allow interactive manipulation of the 3D structure. Featured functions, such as sequence plot, fragment segmentation, measure tool and meta-information display, are offered for users to gain a better understanding of protein structure. Easy-to-use APIs are available for developers to reuse and extend Web3DMol. Web3DMol can be freely accessed at http://web3dmol.duapp.com/, and the source code is distributed under the MIT license.

HiCDB: a sensitive and robust method for detecting contact domain boundaries

Contact domains are closely linked to gene regulation and lineage commitment, while current understanding of contact domains and their boundaries is still limited. Here, we present a novel method HiCDB, which is constructively based on local relative insulation metric and multi-scale aggregation approach to detect contact domain boundaries (CDBs) on Hi-C maps. Compared with other ‘state-of-art’ methods, HiCDB shows improved sensitivity and specificity in determining CDBs at various Hi-C resolutions. The superiority of HiCDB enabled us to study the epigenetic features of detected CDBs and showed enrichment of architectural proteins and cell-type-specific transcription factor binding sites at CDBs. The further comparison of GM12878 and IMR90 Hi-C datasets suggested that cell-type-specific CDBs are marked by active regulatory signals and correlate with activation of nearby cell identity genes.

Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription

Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.

Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes

The new advances in various experimental techniques that provide complementary information about the spatial conformations of chromosomes have inspired researchers to develop computational methods to fully exploit the merits of individual data sources and combine them to improve the modeling of chromosome structure. Here we propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model. Comprehensive tests on a set of chromosomes, for which both Hi-C and FISH data are available, demonstrate that GEM-FISH can outperform previous chromosome structure modeling methods and accurately capture the higher order spatial features of chromosome conformations. Moreover, our reconstructed 3D models of chromosomes revealed interesting patterns of spatial distributions of super-enhancers which can provide useful insights into understanding the functional roles of these super-enhancers in gene regulation.

MTGIpick allows robust identification of genomic islands from a single genome

Genomic islands (GIs) that are associated with microbial adaptations and carry sequence patterns different from that of the host are sporadically distributed among closely related species. This bias can dominate the signal of interest in GI detection. However, variations still exist among the segments of the host, although no uniform standard exists regarding the best methods of discriminating GIs from the rest of the genome in terms of compositional bias. In the present work, we proposed a robust software, MTGIpick, which used regions with pattern bias showing multiscale difference levels to identify GIs from the host. MTGIpick can identify GIs from a single genome without annotated information of genomes or prior knowledge from other data sets. When real biological data were used, MTGIpick demonstrated better performance than existing methods, as well as revealed potential GIs with accurate sizes missed by existing methods because of a uniform standard. Software and supplementary are freely available at http://bioinfo.zstu.edu.cn/MTGI or https://github.com/bioinfo0706/MTGIpick.

Comparative transcriptome profiling of the human and mouse dorsal root ganglia: an RNA-seq-based resource for pain and sensory neuroscience research

Molecular neurobiological insight into human nervous tissues is needed to generate next-generation therapeutics for neurological disorders such as chronic pain. We obtained human dorsal root ganglia (hDRG) samples from organ donors and performed RNA-sequencing (RNA-seq) to study the hDRG transcriptional landscape, systematically comparing it with publicly available data from a variety of human and orthologous mouse tissues, including mouse DRG (mDRG). We characterized the hDRG transcriptional profile in terms of tissue-restricted gene coexpression patterns and putative transcriptional regulators, and formulated an information-theoretic framework to quantify DRG enrichment. Relevant gene families and pathways were also analyzed, including transcription factors, G-protein-coupled receptors, and ion channels. Our analyses reveal an hDRG-enriched protein-coding gene set (∼140), some of which have not been described in the context of DRG or pain signaling. Most of these show conserved enrichment in mDRG and were mined for known drug-gene product interactions. Conserved enrichment of the vast majority of transcription factors suggests that the mDRG is a faithful model system for studying hDRG, because of evolutionarily conserved regulatory programs. Comparison of hDRG and tibial nerve transcriptomes suggests trafficking of neuronal mRNA to axons in adult hDRG, and are consistent with studies of axonal transport in rodent sensory neurons. We present our work as an online, searchable repository (https://www.utdallas.edu/bbs/painneurosciencelab/sensoryomics/drgtxome), creating a valuable resource for the community. Our analyses provide insight into DRG biology for guiding development of novel therapeutics and a blueprint for cross-species transcriptomic analyses.

CGmapTools improves the precision of heterozygous SNV calls and supports allele-specific methylation detection and visualization in bisulfite-sequencing data

Motivation

DNA methylation is important for gene silencing and imprinting in both plants and animals. Recent advances in bisulfite sequencing allow detection of single nucleotide variations (SNVs) achieving high sensitivity, but accurately identifying heterozygous SNVs from partially C-to-T converted sequences remains challenging.

Results

We designed two methods, BayesWC and BinomWC, that substantially improved the precision of heterozygous SNV calls from ∼80% to 99% while retaining comparable recalls. With these SNV calls, we provided functions for allele-specific DNA methylation (ASM) analysis and visualizing the methylation status on reads. Applying ASM analysis to a previous dataset, we found that an average of 1.5% of investigated regions showed allelic methylation, which were significantly enriched in transposon elements and likely to be shared by the same cell-type. A dynamic fragment strategy was utilized for DMR analysis in low-coverage data and was able to find differentially methylated regions (DMRs) related to key genes involved in tumorigenesis using a public cancer dataset. Finally, we integrated 40 applications into the software package CGmapTools to analyze DNA methylomes. This package uses CGmap as the format interface, and designs binary formats to reduce the file size and support fast data retrieval, and can be applied for context-wise, gene-wise, bin-wise, region-wise and sample-wise analyses and visualizations.

Availability and implementation

The CGmapTools software is freely available at https://cgmaptools.github.io/.

Contact

guoweilong@cau.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Polarization-based super-resolution imaging of surface-enhanced Raman scattering nanoparticles with orientational information

Raman scattering provides key information of the biological environment through light-molecule interaction; yet, it is generally very weak to detect. Surface-enhanced Raman scattering (SERS) can boost the Raman signal by several orders-of-magnitude, and thus is highly attractive for biochemical sensing. However, conventional super-resolution imaging of SERS is challenging as the Raman signal is generated from the virtual state which cannot be easily modulated as fluorescence. Here, we demonstrate super-resolution microscopy with a surface-enhanced Raman scattering (SERS) signal, with a resolution of approximately 50 nm. By modulating the polarization angle of the excitation laser, the SERS nanorods display a dramatic anisotropy effect, allowing nanoscale orientation determination of multiple dipoles with dense concentration. Furthermore, a well-established defocused analysis was performed to reconfirm the orientation accuracy of super-resolved SERS nanorods. Sub-diffraction resolution was achieved in the imaging of SERS nanorod labeled vesicles in fixed macrophages. Finally, we demonstrate dynamic SERS nanorod tracking in living macrophages, which provides not only the particle trajectory with high spatial resolution but also the rotational changes at the nanometer scale. This pioneering study paves a new way for subcellular super-resolution imaging with the SERS effect, shedding light on wider biological applications.

Global transcriptional activity dynamics reveal functional enhancer RNAs

Active enhancers of the human genome generate long noncoding transcripts known as enhancer RNAs (eRNAs). How dynamic transcriptional changes of eRNAs are physically and functionally linked with target gene transcription remains unclear. To investigate the dynamic functional relationships among eRNAs and target promoters, we obtained a dense time series of GRO-seq and ChIP-seq data to generate a time-resolved enhancer activity map of a cell undergoing an innate antiviral immune response. Dynamic changes in eRNA and pre-mRNA transcription activities suggest distinct regulatory roles of enhancers. Using a criterion based on proximity and transcriptional inducibility, we identified 123 highly confident pairs of virus-inducible enhancers and their target genes. These enhancers interact with their target promoters transiently and concurrently at the peak of gene activation. Accordingly, their physical disassociation from the promoters is likely involved in post-induction repression. Functional assessments further establish that these eRNAs are necessary for full induction of the target genes and that a complement of inducible eRNAs functions together to achieve full activation. Lastly, we demonstrate the potential for eRNA-targeted transcriptional reprogramming through targeted reduction of eRNAs for a clinically relevant gene, TNFSF10, resulting in a selective control of interferon-induced apoptosis.

Inhibiting the integrated stress response pathway prevents aberrant chondrocyte differentiation thereby alleviating chondrodysplasia

The integrated stress response (ISR) is activated by diverse forms of cellular stress, including endoplasmic reticulum (ER) stress, and is associated with diseases. However, the molecular mechanism(s) whereby the ISR impacts on differentiation is incompletely understood. Here, we exploited a mouse model of Metaphyseal Chondrodysplasia type Schmid (MCDS) to provide insight into the impact of the ISR on cell fate. We show the protein kinase RNA-like ER kinase (PERK) pathway that mediates preferential synthesis of ATF4 and CHOP, dominates in causing dysplasia by reverting chondrocyte differentiation via ATF4-directed transactivation of Sox9. Chondrocyte survival is enabled, cell autonomously, by CHOP and dual CHOP-ATF4 transactivation of Fgf21. Treatment of mutant mice with a chemical inhibitor of PERK signaling prevents the differentiation defects and ameliorates chondrodysplasia. By preventing aberrant differentiation, titrated inhibition of the ISR emerges as a rationale therapeutic strategy for stress-induced skeletal disorders.

CAPTURE: In Situ Analysis of Chromatin Composition of Endogenous Genomic Loci by Biotinylated dCas9

Cis-regulatory elements (CREs) play a pivotal role in spatiotemporal control of tissue-specific gene expression, yet the molecular composition of the vast majority of CREs in native chromatin remains unknown. In this article, we describe the clustered regularly interspaced short palindromic repeats (CRISPR) affinity purification in situ of regulatory elements (CAPTURE) approach to simultaneously identify locus-specific chromatin-regulating protein complexes and long-range DNA interactions. Using an in vivo biotinylated nuclease-deficient Cas9 (dCas9) protein and programmable single guide RNAs (sgRNAs), this approach allows for high-resolution and locus-specific isolation of protein complexes and long-range chromatin looping associated with single copy CREs in mammalian cells. Unbiased analysis of the compositional structure of developmentally regulated or disease-associated CREs identifies new features of transcriptional regulation. Hence, CAPTURE provides a versatile platform to study genomic locus-regulating chromatin composition in a mammalian genome. © 2018 by John Wiley & Sons, Inc.

DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes

Motivation

5-Methylcytosine and 5-Hydroxymethylcytosine in DNA are major epigenetic modifications known to significantly alter mammalian gene expression. High-throughput assays to detect these modifications are expensive, labor-intensive, unfeasible in some contexts and leave a portion of the genome unqueried. Hence, we devised a novel, supervised, integrative learning framework to perform whole-genome methylation and hydroxymethylation predictions in CpG dinucleotides. Our framework can also perform imputation of missing or low quality data in existing sequencing datasets. Additionally, we developed infrastructure to perform in silico, high-throughput hypotheses testing on such predicted methylation or hydroxymethylation maps.

Results

We test our approach on H1 human embryonic stem cells and H1-derived neural progenitor cells. Our predictive model is comparable in accuracy to other state-of-the-art DNA methylation prediction algorithms. We are the first to predict hydroxymethylation in silico with high whole-genome accuracy, paving the way for large-scale reconstruction of hydroxymethylation maps in mammalian model systems. We designed a novel, beam-search driven feature selection algorithm to identify the most discriminative predictor variables, and developed a platform for performing integrative analysis and reconstruction of the epigenome. Our toolkit DIRECTION provides predictions at single nucleotide resolution and identifies relevant features based on resource availability. This offers enhanced biological interpretability of results potentially leading to a better understanding of epigenetic gene regulation.

Availability and implementation

http://www.pradiptaray.com/direction, under CC-by-SA license.

Contacts

pradiptaray@gmail.com or mchen@utdallas.edu or michael.zhang@utdallas.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Synergistic co-regulation and competition by a SOX9-GLI-FOXA phasic transcriptional network coordinate chondrocyte differentiation transitions

The growth plate mediates bone growth where SOX9 and GLI factors control chondrocyte proliferation, differentiation and entry into hypertrophy. FOXA factors regulate hypertrophic chondrocyte maturation. How these factors integrate into a Gene Regulatory Network (GRN) controlling these differentiation transitions is incompletely understood. We adopted a genome-wide whole tissue approach to establish a Growth Plate Differential Gene Expression Library (GP-DGEL) for fractionated proliferating, pre-hypertrophic, early and late hypertrophic chondrocytes, as an overarching resource for discovery of pathways and disease candidates. De novo motif discovery revealed the enrichment of SOX9 and GLI binding sites in the genes preferentially expressed in proliferating and prehypertrophic chondrocytes, suggesting the potential cooperation between SOX9 and GLI proteins. We integrated the analyses of the transcriptome, SOX9, GLI1 and GLI3 ChIP-seq datasets, with functional validation by transactivation assays and mouse mutants. We identified new SOX9 targets and showed SOX9-GLI directly and cooperatively regulate many genes such as Trps1, Sox9, Sox5, Sox6, Col2a1, Ptch1, Gli1 and Gli2. Further, FOXA2 competes with SOX9 for the transactivation of target genes. The data support a model of SOX9-GLI-FOXA phasic GRN in chondrocyte development. Together, SOX9-GLI auto-regulate and cooperate to activate and repress genes in proliferating chondrocytes. Upon hypertrophy, FOXA competes with SOX9, and control toward terminal differentiation passes to FOXA, RUNX, AP1 and MEF2 factors.

In the development of the mammalian growth plate, while several transcription factors are individually well known for their key roles in regulating phases of chondrocyte differentiation, there is little information on how they interact and cooperate with each other. We took an unbiased genome wide approach to identify the transcription factors and signaling pathways that play dominant roles in the chondrocyte differentiation cascade. We developed a searchable library of differentially expressed genes, GP-DGEL, which has fine spatial resolution and global transcriptomic coverage for discovery of processes, pathways and disease candidates. Our work identifies a novel regulatory mechanism that integrates the action of three transcription factors, SOX9, GLI and FOXA. SOX9-GLI auto-regulate and cooperate to activate and repress genes in proliferating chondrocytes. Upon entry into prehypertrophy, FOXA competes with SOX9, and control of hypertrophy passes to FOXA, RUNX, AP1 and MEF2 factors.

Co-inhibitory Molecule B7 Superfamily Member 1 Expressed by Tumor-Infiltrating Myeloid Cells Induces Dysfunction of Anti-tumor CD8+ T Cells

The molecular mechanisms whereby CD8⁺ T cells become "exhausted" in the tumor microenvironment remain unclear. Programmed death ligand-1 (PD-L1) is upregulated on tumor cells and PD-1-PD-L1 blockade has significant efficacy in human tumors; however, most patients do not respond, suggesting additional mechanisms underlying T cell exhaustion. B7 superfamily member 1 (B7S1), also called B7-H4, B7x, or VTCN1, negatively regulates T cell activation. Here we show increased B7S1 expression on myeloid cells from human hepatocellular carcinoma correlated with CD8⁺ T cell dysfunction. B7S1 inhibition suppressed development of murine tumors. Putative B7S1 receptor was co-expressed with PD-1 but not T cell immunoglobulin and mucin-domain containing-3 (Tim-3) at an activated state of early tumor-infiltrating CD8⁺ T cells, and B7S1 promoted T cell exhaustion, possibly through Eomes overexpression. Combinatorial blockade of B7S1 and PD-1 synergistically enhanced anti-tumor immune responses. Collectively, B7S1 initiates dysfunction of tumor-infiltrating CD8⁺ T cells and may be targeted for cancer immunotherapy.

A novel epigenetic AML1-ETO/THAP10/miR-383 mini-circuitry contributes to t(8;21) leukaemogenesis

DNA methylation patterns are frequently deregulated in t(8;21) acute myeloid leukaemia (AML), but little is known of the mechanisms by which specific gene sets become aberrantly methylated. Here, we found that the promoter DNA methylation signature of t(8;21)⁺ AML blasts differs from that of t(8;21)^- AMLs. This study demonstrated that a novel hypermethylated zinc finger-containing protein, THAP10, is a target gene and can be epigenetically suppressed by AML1-ETO at the transcriptional level in t(8;21) AML. Our findings also show that THAP10 is a bona fide target of miR-383 that can be epigenetically activated by the AML1-ETO recruiting co-activator p300. In this study, we demonstrated that epigenetic suppression of THAP10 is the mechanistic link between AML1-ETO fusion proteins and tyrosine kinase cascades. In addition, we showed that THAP10 is a nuclear protein that inhibits myeloid proliferation and promotes differentiation both in vitro and in vivo Altogether, our results revealed an unexpected and important epigenetic mini-circuit of AML1-ETO/THAP10/miR-383 in t(8;21) AML, in which epigenetic suppression of THAP10 predicts a poor clinical outcome and represents a novel therapeutic target.

FIND: difFerential chromatin INteractions Detection using a spatial Poisson process

Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio.

Alterations of specific chromatin conformation affect ATRA-induced leukemia cell differentiation

Chromatin conformation plays a key role in regulating gene expression and controlling cell differentiation. However, the whole-genome chromatin conformation changes that occur during leukemia cell differentiation are poorly understood. Here, we characterized the changes in chromatin conformation, histone states, chromatin accessibility, and gene expression using an all-trans retinoic acid (ATRA)-induced HL-60 cell differentiation model. The results showed that the boundaries of topological associated domains (TADs) were stable during differentiation; however, the chromatin conformations within several specific TADs were obviously changed. By combining H3K4me3, H3K27ac, and Hi-C signals, we annotated the differential gene-regulatory chromatin interactions upon ATRA induction. The gains and losses of the gene-regulatory chromatin interactions are significantly correlated with gene expression and chromatin accessibility. Finally, we found that the loss of GATA2 expression and DNA binding are crucial for the differentiation process, and changes in the chromatin structure around the GATA2 regulate its expression upon ATRA induction. This study provided both statistical insights and experimental details regarding the relationship between chromatin conformation changes and transcription regulation during leukemia cell differentiation, and the results suggested that the chromatin conformation is a new type of potential drug target for cancer therapy.

Emergent Lévy behavior in single-cell stochastic gene expression

Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman et al., Phys. Rev. Lett. 97, 168302 (2006)PRLTAO0031-900710.1103/PhysRevLett.97.168302. Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.

NONCODEV5: a comprehensive annotation database for long non-coding RNAs

NONCODE (http://www.bioinfo.org/noncode/) is a systematic database that is dedicated to presenting the most complete collection and annotation of non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs). Since NONCODE 2016 was released two years ago, the amount of novel identified ncRNAs has been enlarged by the reduced cost of next-generation sequencing, which has produced an explosion of newly identified data. The third-generation sequencing revolution has also offered longer and more accurate annotations. Moreover, accumulating evidence confirmed by biological experiments has provided more comprehensive knowledge of lncRNA functions. The ncRNA data set was expanded by collecting newly identified ncRNAs from literature published over the past two years and integration of the latest versions of RefSeq and Ensembl. Additionally, pig was included in the database for the first time, bringing the total number of species to 17. The number of lncRNAs in NONCODEv5 increased from 527 336 to 548 640. NONCODEv5 also introduced three important new features: (i) human lncRNA-disease relationships and single nucleotide polymorphism-lncRNA-disease relationships were constructed; (ii) human exosome lncRNA expression profiles were displayed; (iii) the RNA secondary structures of NONCODE human transcripts were predicted. NONCODEv5 is also accessible through http://www.noncode.org/.

Network embedding-based representation learning for single cell RNA-seq data

Single cell RNA-seq (scRNA-seq) techniques can reveal valuable insights of cell-to-cell heterogeneities. Projection of high-dimensional data into a low-dimensional subspace is a powerful strategy in general for mining such big data. However, scRNA-seq suffers from higher noise and lower coverage than traditional bulk RNA-seq, hence bringing in new computational difficulties. One major challenge is how to deal with the frequent drop-out events. The events, usually caused by the stochastic burst effect in gene transcription and the technical failure of RNA transcript capture, often render traditional dimension reduction methods work inefficiently. To overcome this problem, we have developed a novel Single Cell Representation Learning (SCRL) method based on network embedding. This method can efficiently implement data-driven non-linear projection and incorporate prior biological knowledge (such as pathway information) to learn more meaningful low-dimensional representations for both cells and genes. Benchmark results show that SCRL outperforms other dimensional reduction methods on several recent scRNA-seq datasets.

Allelic reprogramming of 3D chromatin architecture during early mammalian development

In mammals, chromatin organization undergoes drastic reprogramming after fertilization. However, the three-dimensional structure of chromatin and its reprogramming in preimplantation development remain poorly understood. Here, by developing a low-input Hi-C (genome-wide chromosome conformation capture) approach, we examined the reprogramming of chromatin organization during early development in mice. We found that oocytes in metaphase II show homogeneous chromatin folding that lacks detectable topologically associating domains (TADs) and chromatin compartments. Strikingly, chromatin shows greatly diminished higher-order structure after fertilization. Unexpectedly, the subsequent establishment of chromatin organization is a prolonged process that extends through preimplantation development, as characterized by slow consolidation of TADs and segregation of chromatin compartments. The two sets of parental chromosomes are spatially separated from each other and display distinct compartmentalization in zygotes. Such allele separation and allelic compartmentalization can be found as late as the 8-cell stage. Finally, we show that chromatin compaction in preimplantation embryos can partially proceed in the absence of zygotic transcription and is a multi-level hierarchical process. Taken together, our data suggest that chromatin may exist in a markedly relaxed state after fertilization, followed by progressive maturation of higher-order chromatin architecture during early development.

PAF1 regulation of promoter-proximal pause release via enhancer activation

Gene expression in metazoans is regulated by RNA polymerase II (Pol II) promoter-proximal pausing and its release. Previously, we showed that Pol II-associated factor 1 (PAF1) modulates the release of paused Pol II into productive elongation. Here, we found that PAF1 occupies transcriptional enhancers and restrains hyperactivation of a subset of these enhancers. Enhancer activation as the result of PAF1 loss releases Pol II from paused promoters of nearby PAF1 target genes. Knockout of PAF1-regulated enhancers attenuates the release of paused Pol II on PAF1 target genes without major interference in the establishment of pausing at their cognate promoters. Thus, a subset of enhancers can primarily modulate gene expression by controlling the release of paused Pol II in a PAF1-dependent manner.

In Situ Capture of Chromatin Interactions by Biotinylated dCas9

Cis-regulatory elements (CREs) are commonly recognized by correlative chromatin features, yet the molecular composition of the vast majority of CREs in chromatin remains unknown. Here, we describe a CRISPR affinity purification in situ of regulatory elements (CAPTURE) approach to unbiasedly identify locus-specific chromatin-regulating protein complexes and long-range DNA interactions. Using an in vivo biotinylated nuclease-deficient Cas9 protein and sequence-specific guide RNAs, we show high-resolution and selective isolation of chromatin interactions at a single-copy genomic locus. Purification of human telomeres using CAPTURE identifies known and new telomeric factors. In situ capture of individual constituents of the enhancer cluster controlling human β-globin genes establishes evidence for composition-based hierarchical organization. Furthermore, unbiased analysis of chromatin interactions at disease-associated cis-elements and developmentally regulated super-enhancers reveals spatial features that causally control gene transcription. Thus, comprehensive and unbiased analysis of locus-specific regulatory composition provides mechanistic insight into genome structure and function in development and disease.

[A major histocompatibility complex class Ⅱ deficiency case report and literature review]

OBJECTIVE

To summarize and report the clinical characteristics and laboratory results of a case and those reported in literature with MHC class Ⅱ deficiency.

METHOD

The clinical features, laboratory results and gene mutation analysis of an infant with MHC class Ⅱ deficiency, who was diagnosed and treated in Peking Union Medical College Hospital since December 2013, were retrospectively analyzed."Major histocompatibility complex class Ⅱ deficiency"or"bare lymphocyte syndrome"were used as keywords in order to retrieve reports from CNKI (from its establishment to October 2015) and Wanfang Database (from its establishment to October 2015), PubMed Database (from its establishment to October 2015) was searched. The characteristics, diagnosis, treatment and prognosis were summarized by reviewing related articles.

RESULT

The patient was a 8-month-old boy. Since the fourth month of life, he started to have repeated fever, susceptible to a variety of pathogens, immune hemolytic anemia, severe malnutrition, and finally diagnosed as MHC class Ⅱ deficiency disease when he was 20-month-old.No related reports were retrieved from CNKI and Wanfang database, there were 20 articles and 179 patients were reported worldwide in the past 10 years. Patients exhibit an extreme vulnerability to infections(resptratory infection(82%, 146/178), inpection of gastroin testinal(76%, 135/178)). The common laboratory examinations showed hypogammaglobulinemia, CD4(+) lymphopenia(93%, 107/115) etc. Diagnosis relies on the flow-cytometric analysis and genetic analysis.

CONCLUSION

It is considered necessary for patients with young onset age, manifestation of clinically opportunistic infection as immune deficient disease, including the MHC class Ⅱ deficiency disease, especially long-term diarrhea, poor development and cryptosporidium infection. This disease could coexist with autoimmune disorders.

Reconstructing cell cycle pseudo time-series via single-cell transcriptome data

Single-cell mRNA sequencing, which permits whole transcriptional profiling of individual cells, has been widely applied to study growth and development of tissues and tumors. Resolving cell cycle for such groups of cells is significant, but may not be adequately achieved by commonly used approaches. Here we develop a traveling salesman problem and hidden Markov model-based computational method named reCAT, to recover cell cycle along time for unsynchronized single-cell transcriptome data. We independently test reCAT for accuracy and reliability using several data sets. We find that cell cycle genes cluster into two major waves of expression, which correspond to the two well-known checkpoints, G1 and G2. Moreover, we leverage reCAT to exhibit methylation variation along the recovered cell cycle. Thus, reCAT shows the potential to elucidate diverse profiles of cell cycle, as well as other cyclic or circadian processes (e.g., in liver), on single-cell resolution.

In single-cell RNA sequencing data of heterogeneous cell populations, cell cycle stage of individual cells would often be informative. Here, the authors introduce a computational model to reconstruct a pseudo-time series from single cell transcriptome data, identify the cell cycle stages, identify candidate cell cycle-regulated genes and recover the methylome changes during the cell cycle.

Super-resolution imaging of a 2.5 kb non-repetitive DNA in situ in the nuclear genome using molecular beacon probes

High-resolution visualization of short non-repetitive DNA in situ in the nuclear genome is essential for studying looping interactions and chromatin organization in single cells. Recent advances in fluorescence in situ hybridization (FISH) using Oligopaint probes have enabled super-resolution imaging of genomic domains with a resolution limit of 4.9 kb. To target shorter elements, we developed a simple FISH method that uses molecular beacon (MB) probes to facilitate the probe-target binding, while minimizing non-specific fluorescence. We used three-dimensional stochastic optical reconstruction microscopy (3D-STORM) with optimized imaging conditions to efficiently distinguish sparsely distributed Alexa-647 from background cellular autofluorescence. Utilizing 3D-STORM and only 29–34 individual MB probes, we observed 3D fine-scale nanostructures of 2.5 kb integrated or endogenous unique DNA in situ in human or mouse genome, respectively. We demonstrated our MB-based FISH method was capable of visualizing the so far shortest non-repetitive genomic sequence in 3D at super-resolution.

DOI:http://dx.doi.org/10.7554/eLife.21660.001

HCSGD: An integrated database of human cellular senescence genes

Cellular senescence is an irreversible cell cycle arrest program in response to various exogenous and endogenous stimuli like telomere dysfunction and DNA damage. It has been widely accepted as an anti-tumor program and is also found closely related to embryo development, tissue repair, organismal aging and age-related degenerative diseases. In the past decades, numerous efforts have been made to uncover the gene regulatory mechanisms of cellular senescence. There is a strong demand to integrate these data from various resources into one open platform. To facilitate researchers on cellular senescence, we have developed Human Cellular Senescence Gene Database (HCSGD) by integrating multiple online published data sources into a comprehensive senescence gene annotation platform (http://bioinfo.au.tsinghua.edu.cn/member/xwwang/HCSGD). Potential Human Cellular Senescence Genes (HCSGS) were collected by combining information from published literatures, gene expression profiling data and Protein-Protein Interaction networks. Additionally, genes are annotated with gene ontology annotation and microRNA/drug/compound target information. HCSGD provides a valuable resource to visualize cellular senescence gene networks, browse annotated functional information, and retrieve senescence-associated genes with a user-friendly web interface.

Recurrently deregulated lncRNAs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) cells often invade the portal venous system and subsequently develop into portal vein tumour thrombosis (PVTT). Long noncoding RNAs (lncRNAs) have been associated with HCC, but a comprehensive analysis of their specific association with HCC metastasis has not been conducted. Here, by analysing 60 clinical samples' RNA-seq data from 20 HCC patients, we have identified and characterized 8,603 candidate lncRNAs. The expression patterns of 917 recurrently deregulated lncRNAs are correlated with clinical data in a TCGA cohort and published liver cancer data. Matched array data from the 60 samples show that copy number variations (CNVs) and alterations in DNA methylation contribute to the observed recurrent deregulation of 235 lncRNAs. Many recurrently deregulated lncRNAs are enriched in co-expressed clusters of genes related to cell adhesion, immune response and metabolic processes. Candidate lncRNAs related to metastasis, such as HAND2-AS1, were further validated using RNAi-based loss-of-function assays. Thus, we provide a valuable resource of functional lncRNAs and biomarkers associated with HCC tumorigenesis and metastasis.

Long noncoding-RNAs have been linked to hepatocellular carcinoma (HCC) and some can be used as prognostic markers. Here the authors, by analysing RNA-seq in 60 clinical samples from 20 patients, provide a resource of functional lncRNAs and biomarkers associated with HCC tumorigenesis and metastasis.

Characterization and Antibacterial Activity of Oil-In-Water Nano-Emulsion Formulation Against Candidatus Liberibacter asiaticus

Nano-emulsion is a promising delivery system for increasing pesticide use and enhancing the therapeutic efficiency against pathogens. The pathogen Candidatus Liberibacter asiaticus (Las) that causes destructive citrus huanglongbing (HLB) resides in citrus phloem, which makes it difficult to treat with chemicals. Based on various physiochemical characteristics of oils, surfactants, and organic solvents, an oil-in-water (O/W) nano-emulsion formulation was developed and optimized to combat citrus HLB. The nano-emulsion was formulated through a spontaneous emulsification method for efficient delivery of ampicillin into the citrus phloem using bark application. The nano-emulsion that was prepared from Cremophor EL (viscous oil), acetone (water miscibility organic solvent), and Span 80/Tween 80 (surfactant) formed a small droplet size (17.33 ± 0.52 nm) and exhibited an improved absorption rate. Peak concentration was detected at 2 days posttreatment and the maximum concentration (C_max) and relative bioavailability (RBA) of ampicillin in HLB-affected citrus were 71.86 ± 35.38 ng/g and 267.25% ± 44.1%, respectively. The peak concentration of Amp appeared at 6 days posttreatment in the citrus trees that were treated with Amp alone and their C_max and RBA were 56.44 ± 32.59 ng/g and 100%, respectively. The same nano-emulsion was used to deliver five different antimicrobials to control citrus HLB through bark application. We found that the droplet size of the antimicrobials in the nano-emulsion was significantly reduced and the nano-emulsion also enhanced the therapeutic efficiency of validoxylamine A alone and in combination with actidione as well as sulfadimoethoxine sodium against Las. Therefore, this study provides an efficient bark application nano-emulsion formulation for citrus HLB control.

Long non-coding RNA expression profiles of hepatitis C virus-related dysplasia and hepatocellular carcinoma

Recently, long non-coding RNAs (lncRNAs) were found to be implicated in cancer progression. However, the contributions of lncRNAs to Hepatitis C virus-related hepatocellular carcinoma (HCC) remain largely unknown. Here, we characterized lncRNA expression in 73 tissue samples from several different developmental stages of HCV-related hepatocarcinogenesis by repurposing microarray data sets. We found that the expression of 7 lncRNAs in preneoplastic lesions and HCC was significantly different. Among these significantly differently expressed lncRNAs, the lncRNA LINC01419 transcripts were expressed at higher levels in early stage HCC compared to dysplasia and as compared with early stage HCC, lncRNA AK021443 level increase in advanced stage HCC while lncRNA AF070632 level decrease in advanced stage HCC. Using quantitative real-time reverse-transcription PCR, we validated that LINC01419 was significantly overexpressed in HBV-related and HCV-related HCC when compared with matched non-tumor liver tissues. Moreover, functional predictions suggested that LINC01419 and AK021443 regulate cell cycle genes, whereas AF070632 is associated with cofactor binding, oxidation-reduction and carboxylic acid catabolic process. These findings provide the first large-scale survey of lncRNAs associated with the development of hepatocarcinogenesis and may offer new diagnostic biomarkers and therapeutic targets for HCV-related HCC.

Super-resolution dipole orientation mapping via polarization demodulation

Fluorescence polarization microscopy (FPM) aims to detect the dipole orientation of fluorophores and to resolve structural information for labeled organelles via wide-field or confocal microscopy. Conventional FPM often suffers from the presence of a large number of molecules within the diffraction-limited volume, with averaged fluorescence polarization collected from a group of dipoles with different orientations. Here, we apply sparse deconvolution and least-squares estimation to fluorescence polarization modulation data and demonstrate a super-resolution dipole orientation mapping (SDOM) method that resolves the effective dipole orientation from a much smaller number of fluorescent molecules within a sub-diffraction focal area. We further apply this method to resolve structural details in both fixed and live cells. For the first time, we show that different borders of a dendritic spine neck exhibit a heterogeneous distribution of dipole orientation. Furthermore, we illustrate that the dipole is always perpendicular to the direction of actin filaments in mammalian kidney cells and radially distributed in the hourglass structure of the septin protein under specific labelling. The accuracy of the dipole orientation can be further mapped using the orientation uniform factor, which shows the superiority of SDOM compared with its wide-field counterpart as the number of molecules is decreased within the smaller focal area. Using the inherent feature of the orientation dipole, the SDOM technique, with its fast imaging speed (at sub-second scale), can be applied to a broad range of fluorescently labeled biological systems to simultaneously resolve the valuable dipole orientation information with super-resolution imaging.

ChIA-PET2: a versatile and flexible pipeline for ChIA-PET data analysis

ChIA-PET2 is a versatile and flexible pipeline for analyzing different types of ChIA-PET data from raw sequencing reads to chromatin loops. ChIA-PET2 integrates all steps required for ChIA-PET data analysis, including linker trimming, read alignment, duplicate removal, peak calling and chromatin loop calling. It supports different kinds of ChIA-PET data generated from different ChIA-PET protocols and also provides quality controls for different steps of ChIA-PET analysis. In addition, ChIA-PET2 can use phased genotype data to call allele-specific chromatin interactions. We applied ChIA-PET2 to different ChIA-PET datasets, demonstrating its significantly improved performance as well as its ability to easily process ChIA-PET raw data. ChIA-PET2 is available at https://github.com/GuipengLi/ChIA-PET2.

Analysis of C. elegans muscle transcriptome using trans-splicing-based RNA tagging (SRT)

Current approaches to profiling tissue-specific gene expression in C. elegans require delicate manipulation and are difficult under certain conditions, e.g. from dauer or aging worms. We have developed an easy and robust method for tissue-specific RNA-seq by taking advantage of the endogenous trans-splicing process. In this method, transgenic worms are generated in which a spliced leader (SL) RNA gene is fused with a sequence tag and driven by a tissue-specific promoter. Only in the tissue of interest, the tagged SL RNA gene is transcribed and then trans-spliced onto mRNAs. The tag allows enrichment and sequencing of mRNAs from that tissue only. As a proof of principle, we profiled the muscle transcriptome, which showed high coverage and efficient enrichment of muscle specific genes, with low background noise. To demonstrate the robustness of our method, we profiled muscle gene expression in dauer larvae and aging worms, revealing gene expression changes consistent with the physiology of these stages. The resulting muscle transcriptome also revealed 461 novel RNA transcripts, likely muscle-expressed long non-coding RNAs. In summary, the splicing-based RNA tagging (SRT) method provides a convenient and robust tool to profile trans-spliced genes and identify novel transcripts in a tissue-specific manner, with a low false positive rate.

Identification and differential expression of microRNAs in the ovaries of pigs (Sus scrofa) with high and low litter sizes

Litter size affects profitability in the swine industry. Mammalian ovaries play important roles during reproduction, including ovulation and hormone secretion, which are tightly regulated by specific microRNAs (miRNAs). In this study, we investigated the effects of specific miRNAs on porcine litter size. We compared the ovarian miRNAs of Yorkshire pigs with high (YH) and low (YL) litter sizes using Solexa sequencing technology. We identified 327 and 320 miRNAs in the ovaries of YH and YL pigs respectively. A total of 297 miRNAs were co-expressed; 30 and 23 miRNAs respectively were specifically expressed in the two libraries. A total of 83 novel miRNAs were predicted; 37 specific miRNAs were obtained, of which 21 miRNAs were upregulated and 16 miRNAs were downregulated in YH compared with YL. Additionally, 19 628 and 19 250 target genes were predicted in the two libraries respectively. The results revealed that specific miRNAs (i.e., miR-224, miR-99a, let-7c, miR-181c, miR-214 and miR-21) may affect porcine litter size. The results of this study will help in gaining understanding of the role of miRNAs in porcine litter size regulation.

Abstract 773: Analysis of oncogene affected networks in tumorigenesis of lung cancer

Genetic abnormality is one of major causes of tumorigenesis by driving the progressive transformation of normal human cells into highly malignant derivatives. Tracing the downstream pathways through which and how the effects of the oncogenic-activating mutations are transmitted is an important and challenging problem in studying disease mechanisms, diagnoses and treatments. In this study, we designed a network-based computational method, called MAXMAP, to not only predict mutation downstream affected pathways, but also quantitatively measure the dynamics of the pathway genes.

We first constructed a heterogeneous network by integrating protein-protein interaction networks and signaling and regulatory networks from available up-to-date curated databases, as well as RNASeq expression data. The RNAseq dataset of these mutated cell lines has 18,096 genes whereas the Protein Protein Interaction and Signalling, regulation dataset has 14,864 genes. We then used the maximal information flow method to globally optimize the effects from the mutations to target downstream genes. The method was applied to analyze the biological network dynamics that is caused by single (TP53), double (TP53+KRAS) and triple (TP53+KRAS+STK11) mutations of HBEC30KT, an immortalized lung cell line, and revealed the core dynamical subnetworks of these mutations. Only the triple mutant is known to have tumor-like properties and as shown in earlier studies these sequential mutation accumulations lead to tumorigenesis in mouse xenograft models. The experimental validation of a small subnetwork was performed using transient knock down of the pathway genes and expression was verified using qPCR.

We showed the dynamical subnetworks through which a gene, SLC7A5 was affected by sequential single, double or triple mutations. We have experimentally validated the predicted small subnetwork for SLC7A5 which is an important transporter of neutral amino acids. It is associated with bladder and bile duct adeno carcinomas and overexpressed in lung cancers. We selected the subnetwork affected due to the single mutation (TP53) for validation, including THBS1, TNFRSF11B and MAPK1 and SLC7A5.

Hence, using the MAXMAP method we have successfully identified a dynamical subnetwork affected by changes in the known network of genes. These results suggest that this computational method may allow us to predict drug targets or biomarkers or to study interesting alternative paths and predict the most likely path leading to certain phenotypic outcomes.

Citation Format: Adwait Sathe, Yong Chen, Hyuntae Yoo, Michael Q. Zhang. Analysis of oncogene affected networks in tumorigenesis of lung cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 773.

[Follistatin-like 1-engineered mesenchymal stem cells prevent myocardial ischemic reperfusion injury]

OBJECTIVE

To investigate the role of follistatin-like protein 1 (FSTL1) on bone marrow mesenchymal stem cells (BM-MSCs)-mediated cardioprotection during myocardial ischemia/reperfusion injury.

METHODS

Rat bone marrow mesenchymal stem cells were isolated by whole bone marrow adherence method in vitro. A total of 60 Wistar rats were randomly divided into 4 groups: control group, ischemic /reperfusion injury (IRI) group, ischemia/reperfusion injury group treated with natural BM-MSCs (IRI+ MSC group), ischemia/reperfusion injury group treated with BM-MSCs which did not contain FSTL1 (IRI+ MSC FSTL1 siRNA group). Survival analysis was used to analyze survival time of rats, besides, expression of FSTL1 was detected by Western blotting. Myocardial pathological changes were detected by Hematoxylin and Eosin (HE) staining. Terminal-deoxynucleoitidyl transferase mediated nick end labeling (TUNEL) and enzyme-linked immunosorbent assay (ELISA) were used to determine the associated biomarkers and apoptosis 7 days after operation.

RESULTS

Compared with IRI group, rats in IRI+ MSC group had a higher survival rate and lived longer. Meanwhile, IRI+ MSC group had higher FSTL1 expression in blood and myocardial tissues than IRI group. Control group showed significantly lower apoptosis rate of myocardial cells[(1.4±0.1)% vs (29.8±4.5)%, P<0.05], less histological changes and infarction areas (0 vs 24.48±4.27, P<0.05) than IRI group. Compared with IRI group, IRI+ MSC group had an improvement of apoptosis rate[(4.2±0.3)% vs (29.8±4.5)%, P<0.05], less histological injury and infarction areas (15.12±3.82 vs 24.48±4.27, P<0.01). IRI+ MSC group had lower expression of LDH, MDA, CK and higher expression of SOD than IRI group (P<0.05). However, IRI+ MSC FSTL1 siRNA group showed weaker protection of myocardial cells than IRI+ MSC group after knockdown of FSTL1 (P<0.05).

CONCLUSION

FSTL1, which was secreted by BM-MSCs, plays a protective role in myocardial IRI.

FAT10 Is Critical in Influenza A Virus Replication by Inhibiting Type I IFN

The H5N1 avian influenza virus causes severe disease and high mortality, making it a major public health concern worldwide. The virus uses the host cellular machinery for several steps of its life cycle. In this report, we observed overexpression of the ubiquitin-like protein FAT10 following live H5N1 virus infection in BALB/c mice and in the human respiratory epithelial cell lines A549 and BEAS-2B. Further experiments demonstrated that FAT10 increased H5N1 virus replication and decreased the viability of infected cells. Total RNA extracted from H5N1 virus-infected cells, but not other H5N1 viral components, upregulated FAT10, and this process was mediated by the retinoic acid-induced protein I-NF-κB signaling pathway. FAT10 knockdown in A549 cells upregulated type I IFN mRNA expression and enhanced STAT1 phosphorylation during live H5N1 virus infection. Taken together, our data suggest that FAT10 was upregulated via retinoic acid-induced protein I and NF-κB during H5N1 avian influenza virus infection. And the upregulated FAT10 promoted H5N1 viral replication by inhibiting type I IFN.