Biology subjects

Zhang, R.

Publications and source records attributed to Zhang, R..

At least 505 records · Page 28Linked to original sources

bioRxiv2020

TranSuite: a software suite for accurate translation and characterization of transcripts

Protein translation programs often select the longest open reading frame (ORF) in a transcript leading to numerous inaccurate and mis-annotated ORFs in databases. Unproductive transcript isoforms containing premature termination codons (PTCs) are potential substrates for nonsense-mediated decay (NMD). These transcripts often contain truncated ORFs but are incorrectly annotated due to selection of a long ORF beginning at an AUG downstream of the PTC despite the transcript containing the authentic translation start AUG. In gene expression and alternative splicing analyses, it is important to identify transcript isoforms which code for different protein variants and to distinguish these from potential NMD substrates. Here, we present TranSuite, a pipeline of bioinformatics tools that address these challenges by performing accurate translations, characterizing alternative ORFs and identifying NMD and other features of transcripts in newly assembled and existing transcriptomes. Directly comparing ORFs defined by TranSuite and TransDecoder for the Arabidopsis transcriptome AtRTD2 identified ORF mis-calling in over 16k (27%) of transcripts by TransDecoder.

bioinformatics↗

bioRxiv2020

Multiscale and integrative single-cell Hi-C analysis with Higashi

The advent of single-cell Hi-C (scHi-C) technologies offers an unprecedented opportunity to unveil cell-to-cell variability of 3D genome organization. However, the development of computational methods that can effectively enhance scHi-C data quality and extract 3D genome features in single cells remains a major challenge. Here, we report Higashi, a new algorithm that achieves state-of-the-art analysis of scHi-C data based on hypergraph representation learning. Extensive evaluations demonstrate that Higashi significantly outperforms existing methods for embedding and imputation of scHi-C data. Higashi is uniquely able to identify multiscale 3D genome features (such as compartmentalization and TAD-like domain boundaries) in single cells, allowing markedly refined delineation of cell-to-cell variability of 3D genome features. By applying to a scHi-C dataset from human prefrontal cortex, Higashi reveals complex cell types as well as new connections between 3D genome features and cell type-specific gene regulation. Higashi provides an end-to-end solution to scHi-C data analysis and is applicable to studying single-cell 3D genomes in a wide range of biological contexts.

bioinformatics↗

bioRxiv2020

A novel cell culture system modeling the SARS-CoV-2 life cycle

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the global pandemic of COVID-19, and no effective antiviral agents and vaccines are available. SARS-CoV-2 is classified as a biosafety level-3 (BLS-3) agent, impeding the basic research into its biology and the development of effective antivirals. Here, we developed a biosafety level-2 (BSL-2) cell culture system for production of transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP). This trVLP expresses a reporter gene (GFP) replacing viral nucleocapsid gene (N), which is required for viral genome packaging and virion assembly (SARS-CoV-2-GFP/{Delta}N trVLP). The complete viral life cycle can be achieved and exclusively confined in the cells ectopically expressing SARS-CoV or SARS-CoV-2 N proteins, but not MERS-CoV N. Genetic recombination of N supplied in trans into viral genome was not detected, as evidenced by sequence analysis after one-month serial passages in the N-expressing cells. Moreover, intein-mediated protein trans-splicing approach was utilized to split the viral N gene into two independent vectors, and the ligated viral N protein could function in trans to recapitulate entire viral life cycle, further securing the biosafety of this cell culture model. Based on this BSL-2 SARS-CoV-2 cell culture model, we developed a 96-well format high throughput screening for antivirals discovery. We identified salinomycin, tubeimoside I, monensin sodium, lycorine chloride and nigericin sodium as potent antivirals against SARS-CoV-2 infection. Collectively, we developed a convenient and efficient SARS-CoV-2 reverse genetics tool to dissect the virus life cycle under a BSL-2 condition. This powerful tool should accelerate our understanding of SARS-CoV-2 biology and its antiviral development.

microbiology↗

bioRxiv2020

AlphaTracker: A Multi-Animal Tracking and Behavioral Analysis Tool

The advancement of behavioral analysis in neuroscience has been aided by the development of computational tools1,2. Specifically, computer vision algorithms have emerged as a powerful tool to elevate behavioral research3,4. Yet fully automatic analysis of social behavior remains challenging in two ways. First, existing tools to track and analyze behavior often focus on single animals, not multiple, interacting animals. Second, many available tools are not developed for novice users and require programming experience to run. Here, we unveil a computer vision pipeline called AlphaTracker, which requires minimal hardware requirements and produces reliable tracking of multiple unmarked animals. An easy-to-use user interface further enables manual inspection and curation of results. We demonstrate the practical, real-time advantages of AlphaTracker through the study of multiple, socially-interacting mice.

animal behavior and cognition↗

bioRxiv2020

Species-resolved sequencing of low-biomass microbiomes by 2bRAD-M

Microbiome samples with low microbial biomass or severe DNA degradation remain challenging for amplicon-based (e.g., 16S/18S-rRNA) or whole-metagenome sequencing (WMS) approaches. Here, we introduce 2bRAD-M, a highly reduced and cost-effective metagenome-sequencing strategy which only sequences ~1% of metagenome and can simultaneously produce species-level bacterial, archaeal, and fungal profiles for low-biomass and highly degraded samples. For mock communities, 2bRAD-M can accurately generate species-level taxonomic profiles for otherwise hard-to-sequence samples with (i) low biomass of merely 1 pg of total DNA, (ii) high host DNA contamination (99%), and (iii) severely fragmented DNA (50-bp) from degraded samples. Tests of 2bRAD-M on stool, skin and environment-surface samples deliver successful reconstruction of comprehensive, high-resolution microbial profiles with agreement across 16S-rRNA, WMS and existing literature. In addition, it enables microbial profiling in formalin-fixed paraffin-embedded (FFPE) cervical tissue samples which were recalcitrant to conventional approaches due to the low amount and heavy degradation of microbial DNA, and discriminated healthy tissue, pre-invasive cancer and invasive cancer via species-level microbial profiles with 91.1% accuracy. Therefore, 2bRAD-M greatly expands the reach of microbiome sequencing.

microbiology↗

bioRxiv2020

DANGO: Predicting higher-order genetic interactions

Higher-order genetic interactions, which have profound implications for understanding the molecular mechanisms of phenotypic variation, remain poorly characterized. Most studies to date have focused on pairwise interactions, as designing high-throughput experimental screenings for the vast combinatorial search space of higher-order molecular interactions is dauntingly challenging. Here, we develop DO_SCPLOWANGOC_SCPLOW, a computational method based on a self-attention hypergraph neural network, designed to effectively predict higher-order genetic interaction among groups of genes. As a proof-of-concept, we provide comprehensive predictions for over 400 million trigenic interactions in the yeast S. cerevisiae, significantly expanding the quantitative characterization of such interactions. Our results demonstrate that DO_SCPLOWANGOC_SCPLOW accurately predicts trigenic interactions, uncovering both known and novel biological functions related to cell growth. We further incorporate protein embeddings and model uncertainty scoring to enhance the biological relevance and interpretability of the predicted interactions. Moreover, the predicted interactions can serve as powerful genetic markers for growth response under diverse conditions. Together, DO_SCPLOWANGOC_SCPLOW enables a more complete map of complex genetic interactions that impinge upon phenotypic diversity.

bioinformatics↗

bioRxiv2020

scPretrain: Multi-task self-supervised learning for cell type classification

Rapidly generated scRNA-seq datasets enable us to understand cellular differences and the function of each individual cell at single-cell resolution. Cell type classification, which aims at characterizing and labeling groups of cells according to their gene expression, is one of the most important steps for single-cell analysis. To facilitate the manual curation process, supervised learning methods have been used to automatically classify cells. Most of the existing supervised learning approaches only utilize annotated cells in the training step while ignoring the more abundant unannotated cells. In this paper, we proposed scPretrain, a multi-task self-supervised learning approach that jointly considers annotated and unannotated cells for cell type classification. scPretrain consists of a pre-training step and a fine-tuning step. In the pre-training step, scPretrain uses a multi-task learning framework to train a feature extraction encoder based on each datasets pseudo-labels, where only unannotated cells are used. In the fine-tuning step, scPretrain fine-tunes this feature extraction encoder using the limited annotated cells in a new dataset. We evaluated scPretrain on 60 diverse datasets from different technologies, species and organs, and obtained a significant improvement on both cell type classification and cell clustering. Moreover, the representations obtained by scPretrain in the pre-training step also enhanced the performance of conventional classifiers such as random forest, logistic regression and support vector machines. scPretrain is able to effectively utilize the massive amount of unlabelled data and be applied to annotating increasingly generated scRNA-seq datasets. Availabilityhttps://github.com/ruiyi-zhang/scPretrain\

bioinformatics↗

bioRxiv2020

ORF3a mediated-incomplete autophagy facilitates SARS-CoV-2 replication

SARS-CoV-2 is the causative agent for the COVID-19 pandemic and there is an urgent need to understand the cellular response to SARS-CoV-2 infection. Beclin-1 is an essential scaffold autophagy protein that forms two distinct subcomplexes with modulators Atg14 and UVRAG, responsible for autophagosome formation and maturation, respectively. In the present study, we found that SARS-CoV-2 infection triggers an incomplete autophagy response, elevated autophagosome formation but impaired autophagosome maturation, and declined autophagy by genetic knockout of essential autophagic genes reduces SARS-CoV-2 replication efficiency. By screening 28 viral proteins of SARS-CoV-2, we demonstrated that expression of ORF3a alone is sufficient to induce incomplete autophagy. Mechanistically, SARS-CoV-2 ORF3a interacts with autophagy regulator UVRAG to facilitate Beclin-1-Vps34-Atg14 complex but selectively inhibit Beclin-1-Vps34-UVRAG complex. Interestingly, although SARS-CoV ORF3a shares 72.7% amino acid identity with the SARS-CoV-2 ORF3a, the former had no effect on cellular autophagy response. Thus, our findings provide the mechanistic evidence of possible takeover of host autophagy machinery by ORF3a to facilitate SARS-CoV-2 replication and raises the possibility of targeting the autophagic pathway for the treatment of COVID-19.

microbiology↗

bioRxiv2020

Live poultry feeding and trading network and the transmission of avian influenza A(H5N6) virus in a large city in China, 2014-2015

To understand clearly the mechanism of H5N6 transmission, the role of a live poultry feeding and trading network should be explored deeply. However, there is little data to show the network in an area. In this study, we performed a field epidemiological investigation to collect the numbers of farms, wholesale markets, and live poultry retail markets, and the numbers of purchased (from where) and sold (to where) live birds in Changsha City, China in 2014. We also collected samples from the network in the city from January 2014 to March 2015, including the LPMs visited by the patient known to be infected with A(H5N6) virus, and sequenced the genomes of 10 A(H5N6) viral strains isolated from these environmental samples, to determine the source of virus that infected the patient reported in Changsha. Additionally, we collected and analyzed A(H5N6) virus genome sequence isolated from humans, poultry, and LPMs registered in National Center for Biotechnology Information (NCBI; NIH, Bethesda, MD, USA) 14, to determine the source of other human infections with A(H5N6) virus reported in China. Changsha City in China has a large live poultry feeding and trading network (LPFTN) which had 665 farms, 5 wholesale markets, and 223 live poultry retail markets in 2014. The network covered nine provinces and purchased and sold more than 150000 live birds every day. About 840 environmental samples collected from the LPFTN network from January 2014 to March 2015. About 8.45% (71/840) environmental samples were shown to be positive for N6 and 10 full genome sequences of H5N6 virus were analyzed. We performed phylogenetic analyses and virus characterization, which demonstrated that the H5N6 viral strains isolated from Chinese patients were closely related to those isolated from the poultry and environmental samples obtained from the LPFTN network. This indicates that the network with a large volume of live poultry provides a platform for the transmission of H5N6, and provides an infectious pool which makes the people in high risk. ImportanceAvian influenza A(H5N6) virus is an emerging threat to public health. With several human cases reported in recent years, it has become a dominant avian influenza virus (AIV) subtype in China. Live poultry feeding and trading network (LPFTN) contributes to the presence of novel AIV. By a field epidemiological investigation in the complex LPFTN in Changsha, we demonstrated that the H5N6 viral strains isolated from Chinese patients were closely related to those isolated from the poultry and environmental samples obtained from the network, suggesting the LPFTN with a large volume of live poultry provides a platform for the transmission of H5N6 and creates an infectious pool which makes people in high risk. Considering the wide circulation and dynamic reassortment of this highly pathogenic avian influenza H5N6 virus, it should be carefully monitored in poultry and humans due to the pandemic potential.

molecular biology↗

bioRxiv2020

Cortical Spikes use Analog Sparse Coding

Quantifying the message communicated by neurons in the cortex by averaging action potentials over repeated trials of a given stimulus can reveal neuronal tuning features. For example, simple cells in the visual cortex have been characterized by reverse correlation based on the detailed structure of their oriented receptive fields. This structure, in turn, has been modeled using large libraries of such receptive fields to allow the simultaneous coding of visual stimuli with small numbers of appropriate combinations of cells selected from the library. This strategy, known as sparse coding, has been shown to produce excellent approximations for natural visual inputs. In concert with this mathematical development has been the discovery of cells use of oscillations in the gamma frequency range for general coding tasks, such as a mechanism for synchronizing distal networks of neurons. More recently, spikes timed with oscillations have been shown to exhibit local phase delays within a single gamma cycle, but such delays have resisted a behavioral functional interpretation. We show here that a specific coordinate system for the gamma cycle allows resultant phase delays to be interpreted quantitatively in classical terms. Specifically, extracted phase delays from mice viewing oriented sinusoidal grating images are shown to have the same distributions as those from a computer sparse coding model using natural images, suggesting for the first time a direct link between experimentally measured phase delays and model receptive fields. Significance StatementNetworks of pyramidal cells in the cortex exhibit action potentials (spikes) that are characterized by randomness and low firing rates. Spike averaging methods have been ordinarily useful in dealing with these features to reveal behavioral task structure, but the randomness and slowness so far prevented the specification of a satisfactory generative spike model. We show that a spike can be analyzed using the context of a specific phase of the gamma component of its membrane potential. The result is each spike can be can be assigned a scalar, which makes it immediately useful for network models.

neuroscience↗

bioRxiv2020

Structural and biochemical characterization of bifunctional XynA

Xylan and cellulose are the two major constituents in numerous types of lignocellulosic biomass, representing a promising resource for biofuels and other biobased industries. The efficient degradation of lignocellulose requires the synergistic actions of cellulase and xylanase. Thus, bifunctional enzyme incorporated xylanase/cellulase activity has attracted considerable attention since it has great cost savings potential. Recently, a novel GH10 family enzyme XynA identified from Bacillus sp. is found to degrade both cellulose and xylan. To understand its molecular catalytic mechanism, here we first solve the crystal structure of XynA at 2.3 [A]. XynA is characterized with a classic (/{beta})8 TIM-barrel fold (GH10 domain) flanked by the flexible N-terminal domain and C-terminal domain. Circular dichroism, protein thermal shift and enzyme activity assays reveal that conserved residues Glu182 and Glu280 are both important for catalytic activities of XynA, which is verified by the crystal structure of XynA with E182A/E280A double mutant. Molecular docking studies of XynA with xylohexaose and cellohexaose as well as site-directed mutagenesis and enzyme activity assay demonstrat that Gln250 and His252 are indispensible to cellulase and bifunctional activity, separately. These results elucidate the structural and biochemical features of XynA, providing clues for further modification of XynA for industrial application.

molecular biology↗

bioRxiv2020

Spike development inhibition in the ftin mutant is associated with multiple phenotypes and regulated by multiple biological pathways

Spike development of wheat line 3558M was strongly inhibited by low temperature stress in spring. The fertile tiller inhibition (ftin) gene in the wheat line 3558M is associated with multiple phenotypes, including the production of fewer tillers, delayed floral transition, and death of the shoot apical meristem. We systematically investigated the genes and pathways underlying the differences using ITRAQ proteomics and RNA-sequencing technologies and found multiple biological pathways including to the cold acclimation pathway and multiple defence responses (e.g. reactive oxygen species-mediated hypersensitive response, salicylic acid-mediated systemic acquired resistance) are activated and led to tillers death of the wheat line 3558M under cold stress. Meanwhile, the cold acclimation pathway inhibited the SVP-SCO1-LFY flowering pathway and led to delayed floral transition. Particularly, two TaPIN proteins were significantly downregulated, and multiple auxin signalling genes were also differentially expressed. Knocking down the two TaPIN genes using RNAi technology significantly reduced the tiller number. The cold stress inhibited the auxin transport to reduce the tillers of 3558M. Taken together, the ftin gene might be a cold-sensitive mutation and that is the cause of multiple biological pathways and phenotypic changes.

plant biology↗

bioRxiv2020

Sequence- and structure-selective mRNA m5C methylation by NSUN6 in animals

mRNA m5C, which has recently been implicated in the regulation of mRNA mobility, metabolism, and translation, plays important regulatory roles in various biological events. Two types of m5C sites are found in mRNAs. Type I m5C sites, which contain a downstream G-rich triplet motif and are computationally predicted to locate in the 5 end of putative hairpin structures, are methylated by NSUN2. Type II m5C sites contain a downstream UCCA motif and are computationally predicted to locate in the loops of putative hairpin structures. However, their biogenesis remains unknown. Here we identified NSUN6, a methyltransferase that is known to methylate C72 of tRNAThr and tRNACys, as an mRNA methyltransferase that targets Type II m5C sites. Combining the RNA secondary structure prediction, miCLIP, and results from a high-throughput mutagenesis analysis, we determined the RNA sequence and structural features governing the specificity of NSUN6-mediated mRNA methylation. Integrating these features into an NSUN6-RNA structural model, we identified an NSUN6 variant that largely loses tRNA methylation but retains mRNA methylation ability. Finally, we revealed a negative correlation between m5C methylation and translation efficiency. Our findings uncover that mRNA m5C is tightly controlled by an elaborate two-enzyme system, and the protein-RNA structure analysis strategy established may be applied to other RNA modification writers to distinguish the functions of different RNA substrates of a writer protein.

molecular biology↗

bioRxiv2020

A novel small molecule LLL12B inhibits STAT3 signaling and sensitizes ovarian cancer cell to paclitaxel and cisplatin

Ovarian cancer is the fifth most common cause of cancer deaths among American women. Platinum and taxane combination chemotherapy represents the first-line approach for ovarian cancer, but treatment success is often limited by chemoresistance. Therefore, it is necessary to find new drugs to sensitize ovarian cancer cells to chemotherapy. Persistent activation of Signal Transducer and Activator of Transcription 3 (STAT3) signaling plays an important role in oncogenesis. Using a novel approach called advanced multiple ligand simultaneous docking (AMLSD), we developed a novel nonpeptide small molecule, LLL12B, which targets the STAT3 pathway. In this study, LLL12B inhibited STAT3 phosphorylation (tyrosine 705) and the expression of its downstream targets, which are associated with cancer cell proliferation and survival. We showed that LLL12B also inhibits cell viability, migration, and proliferation in human ovarian cancer cells. LLL12B combined with either paclitaxel or with cisplatin demonstrated synergistic inhibitory effects relative to monotherapy in inhibiting cell viability and LLL12B-paclitaxel or LLL12B-cisplatin combination exhibited greater inhibitory effects than cisplatin- paclitaxel combination in ovarian cancer cells. Furthermore, LLL12B-paclitaxel or LLL12B-cisplatin combination showed more significant in inhibiting cell migration and growth than monotherapy in ovarian cancer cells. In summary, our results support the novel small molecule LLL12B as a potent STAT3 inhibitor in human ovarian cancer cellsand suggest that LLL12B in combination with the current front-line chemotherapeutic drugs cisplatin and paclitaxel may represent a promising approach for ovarian cancer therapy.

molecular biology↗

bioRxiv2020

Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry

Coronavirus interaction with its viral receptor is a primary genetic determinant of host range and tissue tropism. SARS-CoV-2 utilizes ACE2 as the receptor to enter host cell in a species-specific manner. We and others have previously shown that ACE2 orthologs from New World monkey, koala and mouse cannot interact with SARS-CoV-2 to mediate viral entry, and this defect can be restored by humanization of the restrictive residues in New World monkey ACE2. To better understand the genetic determinants behind the ability of ACE2 orthologs to support viral entry, we compared koala and mouse ACE2 sequences with that of human and identified the key residues in koala and mouse ACE2 that restrict viral receptor activity. Humanization of these critical residues rendered both koala and mouse ACE2 capable of binding the spike protein and facilitating viral entry. The single mutation that allowed for mouse ACE2 to serve as a viral receptor provides a potential avenue for the development of SARS-CoV-2 mouse model.

microbiology↗

bioRxiv2020

Efficient cooperation of chloroplasts and mitochondria enhances ATP and sucrose production

Efficient photosynthesis requires a balance of ATP and NADPH production/consumption in chloroplasts and the exportation of reducing equivalents from chloroplasts is important for balancing stromal ATP/NADPH ratio. Here we showed that the overexpression of purple acid phosphatase 2 on the outer membranes of chloroplasts and mitochondria can streamline the production and consumption of reducing equivalents in these two organelles, respectively. A higher capacity of consumption of reducing equivalents in mitochondria can indirectly help chloroplasts to balance the ATP/NADPH ratio in stroma and recycle NADP+, the electron acceptors of the linear electron flow. A higher rate of ATP and NADPH production from the linear electron flow, a higher capacity of carbon fixation by the Calvin-Benson-Bassham cycle and a greater consumption of NADH in mitochondria, enhance photosynthesis in the chloroplasts, ATP production in the mitochondria, sucrose synthesis in the cytosol, and eventually boosting plant growth and seed yields in the overexpression lines.

plant biology↗

bioRxiv2020

Adaptive dating and fast proposals: revisiting the phylogenetic relaxed clock model

Uncorrelated relaxed clock models enable estimation of molecular substitution rates across lineages and are widely used in phylogenetics for dating evolutionary divergence times. In this article we delved into the internal complexities of the relaxed clock model in order to develop efficient MCMC operators for Bayesian phylogenetic inference. We compared three substitution rate parameterisations, introduced an adaptive operator which learns the weights of other operators during MCMC, and we explored how relaxed clock model estimation can benefit from two cutting-edge proposal kernels: the AVMVN and Bactrian kernels. This work has produced an operator scheme that is up to 65 times more efficient at exploring continuous relaxed clock parameters compared with previous setups, depending on the dataset. Finally, we explored variants of the standard narrow exchange operator which are specifically designed for the relaxed clock model. In the most extreme case, this new operator traversed tree space 40% more efficiently than narrow exchange. The methodologies introduced are adaptive and highly effective on short as well as long alignments. The results are available via the open source optimised relaxed clock (ORC) package for BEAST 2 under a GNU licence (https://github.com/jordandouglas/ORC). Author summaryBiological sequences, such as DNA, accumulate mutations over generations. By comparing such sequences in a phylogenetic framework, the evolutionary tree of lifeforms can be inferred. With the overwhelming availability of biological sequence data, and the increasing affordability of collecting new data, the development of fast and efficient phylogenetic algorithms is more important than ever. In this article we focus on the relaxed clock model, which is very popular in phylogenetics. We explored how a range of optimisations can improve the statistical inference of the relaxed clock. This work has produced a phylogenetic setup which can infer parameters related to the relaxed clock up to 65 times faster than previous setups, depending on the dataset. The methods introduced adapt to the dataset during computation and are highly efficient when processing long biological sequences.

genetics↗

bioRxiv2020

MicroRNA variants and HLA-miRNA interactions are novel rheumatoid arthritis susceptibility factors

ObjectiveAlthogh Genome-wide association studies have identified >100 variants for rheumatoid arthritis (RA),the reported genetic variants only explain <40% of RA heritability. We conducted a systemic association study between common East-Asian miRNA SNPs with RA in a large Han Chinese cohort to explain missing heritability and identify miRNA epistatic interactions. Methods4 HLA SNPs (HLA-DRB1, HLA-DRB9, HLA-DQB1 and TNFAIP3) and 225 common SNPs located in miRNA which might influence the miRNA target binding or pre-miRNA stability were genotyped in 1,607 rheumatoid arthritis and 1,580 matched normal individuals. A meta-analysis with previous GWAS studies (4,873 RA cases and 17,642 controls) was performed to discovery another novel miRNA RA-associated SNPs. Results2 novel SNPs including rs1414273 (miR-548ac, OR=0.84, P=8.26x10-4) and rs2620381 (miR-627, OR=0.77, P=2.55x10-3) conferred significant association with RA. Individuals carried 8 risk alleles showed 15.38 (95%CI: 4.69-50.49, P<1.0x10-6) times more risk to be affected by RA. In addition, rs5997893 (miR-3928) showed significant epistasis effect with rs4947332 (HLA-DRB1, OR=4.23, P=0.04) and rs2967897 (miR-5695) with rs7752903 (TNFAIP3, OR=4.43, P=0.03). Finally, we demonstrated targets of the significant miRNAs showed enrichment in immune related genes (P=2.0x10-5) and FDA approved drug target genes (P=0.014). Conclusions6 novel miRNA SNPs including rs1414273 (miR-548ac, P=8.26x10-4), rs2620381 (miR-627, P=2.55x10-3), rs4285314 (miR-3135b, P=1.10x10-13), rs28477407 (miR-4308, P=3.44x10-5), rs5997893 (miR-3928, P=5.9x10-3) and rs45596840 (miR-4482, P=6.6x10-3) were confirmed to be significantly associated with RA in a Chinese population. Our study suggests that miRNAs might be interesting targets to accelerate the understanding of the pathogenesis and drug development for rheumatoid arthritis.

genetics↗