Biology subjects

Xie, J.

Publications and source records attributed to Xie, J..

At least 253 records · Page 14Linked to original sources

bioRxiv2019

Membrane dynamics promote sensitivity of epithelial cancer targets to pro-necrotic activity of Natural Killer cells

Natural Killer (NK) cells play an important role in cancer immunosurveillance and therapy. However, the target selectivity of NK cell activity is still poorly understood. Here we used live-cell reporters to unravel differential epithelial cancer target killing by primary human NK cells. We found highly variable fraction of killing by distinct NK cell cytotoxic modes that was not determined by NK ligand expression. Rather, epithelial plasma membrane dynamics driven by ROCK-mediated blebs and/or Rac1-mediated lamellipodia promoted necrotic mode in preference to apoptotic mode of killing. Inhibition of granzyme and key necroptosis regulators RIP1, RIP3 and MLKL significantly attenuated necrotic killing, revealing a novel NK cytotoxic pathway by granzyme-induced necroptosis that conferred target selectivity. Our results not only elucidate a new NK cell effector mechanism but also suggest tissue microenvironment and oncogenic signaling pathways that promote membrane dynamics, e.g., Rac1 and Rho/ROCK, could be exploited to enhance proinflammatory NK cell killing.

cell biology↗

bioRxiv2019

hFUT1-based live cell assay to profile α1-2-fucosides enhanced influenza A virus infection

Host cell-surface glycans play critical roles in influenza A virus (IAV) infection ranging from modulation of IAV attachment to membrane fusion and host tropism. Approaches for quick and sensitive profiling of the viral avidity towards a specific type of host-cell glycan can contribute to the understanding of tropism switching among different strains of IAV. In this study, we developed a method based on chemoenzymatic glycan engineering to investigate the possible involvement of 1-2-fucosides in IAV infections. Using a truncated human fucosyltransferase 1 (hFuT1), we were able to create 1-2-linked fucosides in situ on the host cell surface to assess their influence on the host cell binding to IAV hemagglutinin and the susceptibility of host cells toward IAV induced killing. We discovered that the newly added 1-2-fucosides on host cells enhanced the infection of several human pandemic IVA subtypes. These findings suggest that glycan epitopes other than sialic aicds should be taken into consideration for assessing the human pandemic risk of this viral pathogen.

biochemistry↗

bioRxiv2019

Energy Expenditure during Cell Spreading Induces AMPK Activation and Regulates the Mechanoresponse of Stem Cells

Cells respond to the mechanical properties of the extracellular matrix (ECM) through formation of focal adhesions (FAs), re-organization of the actin cytoskeleton and adjustment of cell contractility. These are energy-demanding processes, but a potential causality between mechanical cues (matrix stiffness) and cellular (energy) metabolism remains largely unexplored. Here, we culture human mesenchymal stem cells (hMSCs) on stiff (20 kPa) or soft (1 kPa) substrate and demonstrate that cytoskeletal reorganization and FA formation spreading on stiff substrates lead to a drop in intracellular ATP levels, correlates with the activation of AMP-activated protein kinase (AMPK). The resulting increase in ATP levels further facilitates cell spreading and reinforces cell tension of the steady state, and coincides with nuclear localization of YAP/TAZ and Runx2. While on soft substrates (1 kPa), lowered ATP levels limit these cellular mechanoresponses. Furthermore, genetic ablation of AMPK lowered cellular ATP levels on stiff substrate and strongly reduced responses to substrate stiffness. Together, these findings reveal a hitherto unidentified relationship between energy expenditure and the cellular mechanoresponse, and point to AMPK as a key mediator of stem cell fate in response to ECM mechanics.

cell biology↗

bioRxiv2019

A novel antiviral lncRNA EDAL shields a T309 O-GlcNAcylation site to promote EZH2 degradation

The central nervous system (CNS) is vulnerable for viral infection, yet few host factors in the CNS are known to defend invasion by neurotropic viruses. We report here that multiple neurotropic viruses, including rabies virus (RABV), vesicular stomatitis virus (VSV), Semliki Forest virus (SFV) and herpes simplex virus 1 (HSV-1), elicit the neuronal expression of a host-encoded lncRNA EDAL. EDAL inhibits the replication of these neurotropic viruses in neuronal cells and RABV infection in mouse brains. EDAL binds to the conserved histone methyltransferase enhancer of zest homolog 2 (EZH2) and specifically causes EZH2 degradation via lysosomes, reducing the cellular H3K27me3 level. The antiviral function of EDAL resides in a 56-nt antiviral substructure through which its 18-nt helix-loop intimately contacts multiple EZH2 sites surrounding T309, a known O-GlcNAcylation site. EDAL positively regulate the transcription of Pcp4l1 encoding a 10 kDa peptide, which inhibits the replication of mutiple neurotropic viruses. Our findings proposed a model in which a neuronal lncRNA can exert an effective antiviral function via blocking a specific O-GlcNAcylation that determines EZH2 lysosomal degradation.

microbiology↗

bioRxiv2019

Mechanistic insights into NAD synthase NMNAT chaperoning phosphorylated Tau from pathological aggregation

Tau hyper-phosphorylation and deposition into neurofibrillary tangles have been found in brains of patients with Alzheimers disease (AD) and other tauopathies. Molecular chaperones are involved in regulating the pathological aggregation of phosphorylated Tau (pTau) and modulating disease progression. Here, we report that nicotinamide mononucleotide adenylyltransferase (NMNAT), a well-known NAD synthase, serves as a chaperone of pTau to prevent its amyloid aggregation in vitro as well as mitigate its pathology in a fly tauopathy model. By combining NMR spectroscopy, crystallography, single-molecule and computational approaches, we revealed that NMNAT adopts its enzymatic pocket to specifically bind the phosphorylated sites of pTau, which can be competitively disrupted by the enzymatic substrates of NMNAT. Moreover, we found that NMNAT serves as a co-chaperone of Hsp90 for the specific recognition of pTau over Tau. Our work uncovers a dedicated chaperone of pTau and suggests NMNAT as a key node between NAD metabolism and Tau homeostasis in aging and neurodegeneration.

biochemistry↗

bioRxiv2019

RNAPosers: Machine Learning Classifiers For RNA-Ligand Poses

Determining the 3-dimensional (3D) structures of ribonucleic acid (RNA)-small molecule complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA-small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used to rank poses tend to misclassify non-native poses as native, and vice versa. This misclassification of non-native poses severely limits the utility of computer docking in the context pose prediction, as well as in virtual screening. Here, we use machine learning to train a set of pose classifiers that estimate the relative \"nativeness\" of a set of RNA-ligand poses. At the heart of our approach is the use of a pose \"fingerprint\" that is a composite of a set of atomic fingerprints, which individually encode the local \"RNA environment\" around ligand atoms. We found that by ranking poses based on the classification scores from our machine learning classifiers, we were able to recover native-like poses better than when we ranked poses based on their docking scores. With a leave-one-out training and testing approach, we found that one of our classifiers could recover poses that were within 2.5 [A] of the native poses in [~]80% of the 88 cases we examined, and similarly, on a separate validation set, we could recover such poses in [~]70% of the cases. Our set of classifiers, which we refer to as RNAPosers, should find utility as a tool to aid in RNA-ligand pose prediction and so we make RNAPosers open to the academic community via https://github.com/atfrank/RNAPosers.

biophysics↗

bioRxiv2019

Conditional, inducible gene silencing in dopamine neurons reveals a sex-specific role for Rit2 GTPase in acute cocaine response and striatal function

Dopamine (DA) signaling is critical for movement, motivation, and addictive behavior. The neuronal GTPase, Rit2, is enriched in DA neurons (DANs), binds directly to the DA transporter (DAT), and is implicated in several DA-related neuropsychiatric disorders. However, it remains unknown whether Rit2 plays a role in either DAergic signaling and/or DA-dependent behaviors. Here, we leveraged the TET-OFF system to conditionally silence Rit2 in Pitx3IRES2-tTA mouse DANs. Following DAergic Rit2 knockdown (Rit2-KD), mice displayed an anxiolytic phenotype, with no change in baseline locomotion. Further, males exhibited increased acute cocaine sensitivity, whereas DAergic Rit2-KD suppressed acute cocaine sensitivity in females. DAergic Rit2-KD did not affect presynaptic TH and DAT protein levels in females, nor was TH was affected in males; however, DAT was significantly diminished in males. Paradoxically, despite decreased DAT levels in males, striatal DA uptake was enhanced, but was not due to enhanced DAT surface expression in either dorsal or ventral striatum. Finally, patch recordings in nucleus accumbens (NAcc) medium spiny neurons (MSNs) revealed reciprocal changes in spontaneous EPSP (sEPSP) frequency in male and female D1+ and D2+ MSNs following DAergic Rit2-KD. In males, sEPSP frequency was decreased in D1+, but not D2+, MSNs, whereas in females sEPSP frequency decreased in D2+, but not D1+, MSNs. Moreover, DAergic Rit2-KD abolished the ability of cocaine to reduce sEPSP frequency in D1+, but not D2+, male MSNs. Taken together, our studies are among the first to acheive AAV-mediated, conditional and inducible DAergic knockdown in vivo. Importantly, our results provide the first evidence that DAergic Rit2 expression differentially impacts striatal function and DA-dependent behaviors in males and females.

neuroscience↗

bioRxiv2019

Distinct and overlapping functions of Miscanthus sinensis MYB transcription factors SCM1 and MYB103 in lignin biosynthesis

Cell wall recalcitrance is a major constraint for the exploitation of lignocellulosic biomass as renewable resource for energy and bio-based products. Transcriptional regulators of the lignin biosynthetic pathway represent promising targets for tailoring lignin content and composition in plant secondary cell walls. A wealth of research in model organisms has revealed that transcriptional regulation of secondary cell wall formation is orchestrated by a hierarchical transcription factor (TF) network with NAC TFs as master regulators and MYB factors in the lower tier regulators. However, knowledge about the transcriptional regulation of lignin biosynthesis in lignocellulosic feedstocks, such as Miscanthus, is limited. Here, we characterized two Miscanthus MYB TFs, MsSCM1 and MsMYB103, and compared their transcriptional impact with that of the master regulator MsSND1. In Miscanthus leaves MsSCM1 and MsMYB103 are expressed at growth stages associated with lignification. Ectopic expression of MsSCM1 and MsMYB103 in tobacco leaves was sufficient to trigger secondary cell wall deposition with distinct sugar and lignin composition. Moreover, RNA-seq analysis revealed that the transcriptional responses to MsSCM1 and MsMYB103 overexpression showed extensive overlap with the response to MsSND1, but were distinct from each other, underscoring the inherent complexity of secondary cell wall formation. Together, MsSCM1 and MsMYB103 represent interesting targets for manipulations of lignin content and composition in Miscanthus towards tailored biomass.

plant biology↗

bioRxiv2019

Multilayered N-glycoproteomics reveals impaired N-glycosylation promoting Alzheimer’s disease

Alzheimers disease (AD) is one of the most common neurodegenerative diseases that currently lacks clear pathogenesis and effective treatment. Protein glycosylation is ubiquitous in brain tissue and site-specific analysis of N-glycoproteome, which is technically challenging, can advance our understanding of the glycoproteins role in AD. In this study, we profiled the multilayered variations in proteins, N-glycosites, N-glycans, and in particular site-specific N-glycopeptides in the APP/PS1 and wild type mouse brain through combining pGlyco 2.0 strategy with other quantitative N-glycoproteomic strategies. The comprehensive brain N-glycoproteome landscape was constructed, and rich details of the heterogeneous site-specific protein N-glycosylations were exhibited. Quantitative analyses explored generally downregulated N-glycosylation involving proteins such as glutamate receptors, as well as fucosylated and oligo-mannose type glycans in APP/PS1 mice versus wild type mice. Moreover, our preliminary functional study revealed that N-glycosylation was crucial for the membrane localization of NCAM1 and for maintaining the excitability and viability of neuron cells. Our work offered a panoramic view of the N-glycoproteomes in Alzheimers disease and revealed that generally impaired N-glycosylation promotes Alzheimers disease progression.

systems biology↗

bioRxiv2019

Bacterial and Archaeal Communities in Recycling Effluents from a Bauxite Flotation Plant

Recycling effluent has become a bottleneck and an environmental risk associated with the regular production of bauxite via flotation and the sustainable development of the aluminum industry in China. To find a practical direction for biotreatment, the bacterial and archaeal communities in recycling effluents containing concentrate and tailings from bauxite flotation plants were investigated by a metagenomic sequencing method in association with the evaluated geochemical properties. The results showed that Paracoccus, Desulfomicrobium, Exiguobacterium, Tindallia, Ercella and Anoxynatronum were the primary bacterial genera and Methanothrix, Methanobacterium, Nitrososphaera and Methanosarcina were the dominant archaeal genera. Upon combining the microbial diversity and the geochemical properties of the two sample types, the microbial community containing Desulfomicrobium, Paracoccus, Tindallia, Methanobacterium, Methanothrix and Nitrososphaera was better adapted to the biodegradation of flotation collectors, and the microbial community consisting of Paracoccus, Exiguobacterium, Methanothrix and Methanobacterium was more efficient at hydrolyzed polyacrylamide (HPAM) biodegradation. In addition, a large proportion of unclassified OTUs has indicated that recycling effluent is a worthy resource for isolating new strains from the Firmicutes phylum.

microbiology↗

bioRxiv2019

Gene Panel Sequencing in a Chinese High-risk Breast Cancer Cohort

Currently, over 20 genes have been defined that can confer susceptibility for high-risk breast cancer. Although research has proved the utility of multiple-gene sequencing in the assessment of breast cancer risk, there is little data from China patients. Here, we use a multiple-gene sequencing panel to identify the variant spectrum in Chinese high-risk breast cancer subjects.\n\nA total of 829 Chinese high-risk breast cancer patients participated in the research. The coding regions of 115 hereditary cancer susceptibility genes were sequenced using a next generation sequencing platform. In total, 193 pathogenic variants were identified in 45 genes from 177 patients. The pathogenic variant carrier rate is 21.4%: with 10.5% patients carrying a BRCA1 or BRCA2 mutation only, 10.0% of patients carried non-BRCA gene mutations only, while 1.0% of patients carried both a BRCA1/2 and a non-BRCA gene mutation. Variants of uncertain significance (VUS) totaling 2632 were identified in 115 genes from 787 of 829 patients: 82.5% patients carried more than one VUS, and only 5.1% patients did not carry any VUS. Families carrying pathogenic variants were tracked and adenoma was founded in three of them. Our data provide a comprehensive analysis of potential susceptibility variations of high-risk for breast cancer in a Chinese population. This data will be useful for the comparison of the susceptibility variation spectrum between different populations and to discover potential pathogenic variants to improve the prevention and treatment of high-risk breast cancer.

cancer biology↗

bioRxiv2018

Categorical encoding of decision variables in orbitofrontal cortex

A fundamental and recurrent question in systems neuroscience is that of assessing what variables are encoded by a given population of neurons. Such assessments are often challenging because neurons in one brain area may encode multiple variables, and because neuronal representations might be categorical (different neurons encoding different variables) or mixed (individual neurons encoding a combination of variables). These issues are particularly pertinent to the representation of decision variables in the orbitofrontal cortex (OFC) - an area implicated in economic choices. Here we present a new algorithm to assess whether a neuronal representation is categorical or mixed, and to identify the encoded variables if the representation is indeed categorical. The algorithm is based on two clustering procedures, one variable-independent and the other variable-based. The two partitions are then compared through adjusted mutual information. The present algorithm overcomes limitations of previous approaches and is widely applicable. We tested the algorithm on synthetic data and then used it to examine neuronal data recorded in the primate OFC during economic decisions. Confirming previous assessments, we found the neuronal representation in OFC to be categorical in nature. We also found that neurons in this area encode the value of individual offers, the binary choice outcome and the chosen value. In other words, during economic choice, neurons in the primate OFC encode decision variables in a categorical way.\n\nAuthor SummaryMental functions such as sensory perception or decision making ultimately rely on the activity of neuronal populations in different brain regions. Much research in neuroscience is devoted to understanding how different groups of neurons support specific brain functions by representing behaviorally relevant variables. In this respect, one important question is whether individual neurons represent single variables, or linear combination of variables. Here we developed a new algorithm to assess this general issue. We then used the algorithm to examine neurons in the orbitofrontal cortex (OFC) recorded while non-human primates performed economic decisions. We found that different neurons represent different variables (categorical encoding). Specifically, neurons in the OFC encoded the value of individual offers, the binary choice outcome, and the chosen value. The present results support the hypothesis that economic decisions are formed within the OFC.

neuroscience↗

bioRxiv2018

Comparative analysis of sequencing technologies platforms for single-cell transcriptomics

All single-cell RNA-seq protocols and technologies require library preparation prior to sequencing on a platform such as Illumina. Here, we present the first report to utilize the BGISEQ-500 platform for scRNA-seq, and compare the sensitivity and accuracy to Illumina sequencing. We generate a scRNA-seq resource of 468 unique single-cells and 1,297 matched single cDNA samples, performing SMARTer and Smart-seq2 protocols on mESCs and K562 cells with RNA spike-ins. We sequence these libraries on both BGISEQ-500 and Illumina HiSeq platforms using single- and paired-end reads. The two platforms have comparable sensitivity and accuracy in terms of quantification of gene expression, and low technical variability. Our study provides a standardised scRNA-seq resource to benchmark new scRNA-seq library preparation protocols and sequencing platforms.

genomics↗

bioRxiv2018

QUBIC2: A novel biclustering algorithm for large-scale bulk RNA-sequencing and single-cell RNA-sequencing data analysis

The combination of biclustering and large-scale gene expression data holds a promising potential for inference of the condition specific functional pathways/networks. However, existing biclustering tools do not have satisfied performance on high-resolution RNA-sequencing (RNA-Seq) data, majorly due to the lack of (i) a consideration of high sparsity of RNA-Seq data, e.g., the massive zeros or lowly expressed genes in the data, especially for single-cell RNA-Seq (scRNA-Seq) data, and (ii) an understanding of the underlying transcriptional regulation signals of the observed gene expression values. Here we presented a novel biclustering algorithm namely QUBIC2, for the analysis of large-scale bulk RNA-Seq and scRNA-Seq data. Key novelties of the algorithm include (i) used a truncated model to handle the unreliable quantification of genes with low or moderate expression, (ii) adopted the mixture Gaussian distribution and an information-divergency objective function to capture shared transcriptional regulation signals among a set of genes, (iii) utilized a Core-Dual strategy to identify biclusters and optimize relevant parameters, and (iv) developed a size-based P-value framework to evaluate the statistical significances of all the identified biclusters. Our method validation on comprehensive data sets of bulk and single cell RNA-seq data suggests that QUBIC2 had superior performance in functional modules detection and cell type classification compared with the other five widely-used biclustering tools. In addition, the applications of temporal and spatial data demonstrated that QUBIC2 can derive meaningful biological information from scRNA-Seq data. The source code for QUBIC2 can be freely accessed at https://github.com/maqin2001/qubic2.

bioinformatics↗

bioRxiv2018

Widespread separation of the polypyrimidine tract from 3’ AG by G tracts in association with alternative exons in metazoa and plants

At the end of introns, the polypyrimidine tract (Py) is often close to the 3 AG in a consensus (Y)20NCAGgt in humans. Interestingly, we have found that they could also be separated by purine-rich elements including G tracts in thousands of human genes. These regulatory elements between the Py and 3AG (REPA) mainly regulate alternative 3 splice sites (3SS) and intron retention. Here we show their widespread distribution and special properties across kingdoms. The purine-rich 3SS are found in up to about 60% of the introns among more than 1000 species/lineages by whole genome analysis, and up to 18% of these introns contain the REPA G tracts in about 2.4 millions of 3SS in total. In particular, they are significantly enriched over their 3SS and genome backgrounds in metazoa and plants, and highly associated with alternative splicing of genes in diverse functional clusters. They are also highly enriched (3-6 folds) in the canonical as well as aberrantly used 3 splice sites in cancer patients carrying mutations of the branch point factor SF3B1 or the 3AG binding factor U2AF35. Moreover, the REPA G tract-harbouring 3SS have significantly reduced occurrences of branch point (BP) motifs between the -24 and -4 positions, in particular absent from the -7 - -5 positions in several model organisms examined. The more distant branch points are associated with increased occurrences of alternative splicing in human and zebrafish. The branch points, REPA G tracts and associated 3SS motifs appear to have emerged differentially in a phylum- or species-specific way during evolution. Thus, there is widespread separation of the Py and 3AG by REPA G tracts, likely evolved among different species or branches of life. This special 3SS arrangement contributes to the generation of diverse transcript or protein isoforms in biological functions or diseases through alternative or aberrant splicing.

molecular biology↗

bioRxiv2018

The Big Five, Self-efficacy, and Self-control in Boxers

Inviting 210 boxers of national athletes in China as participants, this study applied the NEO Five-Factor Inventory and self-control and self-efficacy scales for athletes to examine the relationship between personality traits and self-control, as well as any effect of self-efficacy as a mediator between the two variables. The data analysis indicated that, firstly, the boxers overall level of self-control is high, and the higher the competitive level, the higher the level of self-control. Secondly, there were significant correlations among the Big Five, self-control, and self-efficacy. Thirdly, the mediation model showed that self-efficacy has a significant mediating effect between the Big Five and self-control. These results suggest that formulating training and intervention programs based on the personality traits of boxers and focusing on training their self-efficacy (1) to help them enhance their self-control ability, thereby improving athletic performance and promoting physical and mental health, and (2) to support the inclusion of personality traits, self-efficacy, and self-control among psychological indicators to be assessed in boxers.

scientific communication and education↗

bioRxiv2018

Bacterial Glycosyltransferase-mediated Cell-surface Chemoenzymatic Glycan Editing: Methods and Applications

AbstractChemoenzymatic glycan editing that modifies glycan structures directly on the cell surface has emerged as a complementary tool to metabolic oligosaccharide engineering. In this article, we report the discovery that three bacterial enzymes--Pasteurella multocida 2-3-sialyltransferase M144D mutant (Pm2,3ST-M144D), Photobacterium damsel 2-6-sialyltransferase (Pd2,6ST) and Helicobacter mustelae 1-2-fucosyltransferase (Hm1,2FT)--can serve as highly efficient tools for cell-surface glycan editing. Among these three enzymes, the two sialyltransferases were also found to be tolerant to large substituents introduced to the C-5 position of the cytidine monophosphate N-acetylneuraminic acid donor, including biotin and fluorescent dyes. Combining these enzymes with our previously discovered Helicobacter pylori 1-3-FT, we developed a live cell-based assay to probe host-cell glycan-mediated influenza A virus (IAV) infection including both wild-type and mutant strains of human H1N1 and H3N2 influenza subtypes. At high SiaNAc2-6-Gal levels, the ability of a viral strain to induce the host cell death is positively correlated with the SiaNAc2-6-Gal binding affinity of its haemagglutinin. Surprisingly, the creation of sLeX on the host cell surface via in situ 1-3-Fuc editing also exacerbated the killing induced by several wild-type IAV strains as well as a mutant known as HK68-MTA. Structural alignment of HAs from the wild-type HK68 and HK68-MTA revealed the formation of a putative hydrogen bond between Trp222 of HA-HK68-MTA and the C-4 hydroxyl group of the 1-3-linked fucose of sLeX. This interaction is likely to be responsible for the better binding affinity of HA-HK68-MTA to sLeX and accordingly the enhanced host-cell killing compared with the wild-type HK68.

biochemistry↗

bioRxiv2018

GeneQC: A quality control tool for gene expression estimation based on RNA-sequencing reads mapping

MotivationOne of the main benefits of using modern RNA-sequencing (RNA-Seq) technology is the more accurate gene expression estimations compared with previous generations of expression data, such as the microarray. However, numerous issues can result in the possibility that an RNA-Seq read can be mapped to multiple locations on the reference genome with the same alignment scores, which occurs in plant, animal, and metagenome samples. Such a read is so-called a multiple-mapping read (MMR). The impact of these MMRs is reflected in gene expression estimation and all downstream analyses, including differential gene expression, functional enrichment, etc. Current analysis pipelines lack the tools to effectively test the reliability of gene expression estimations, thus are incapable of ensuring the validity of all downstream analyses.\n\nResultsOur investigation into 95 RNA-Seq datasets from seven species (totaling 1,951GB) indicates an average of roughly 22% of all reads are MMRs for plant and animal species. Here we present a tool called GeneQC (Gene expression Quality Control), which can accurately estimate the reliability of each genes expression level. The underlying algorithm is designed based on extracted genomic and transcriptomic features, which are then combined using elastic-net regularization and mixture model fitting to provide a clearer picture of mapping uncertainty for each gene. GeneQC allows researchers to determine reliable expression estimations and conduct further analysis on the gene expression that is of sufficient quality. This tool also enables researchers to investigate continued re-alignment methods to determine more accurate gene expression estimates for those with low reliability.\n\nAvailabilityGeneQC is freely available at http://bmbl.sdstate.edu/GeneQC/home.html.\n\nContactqin.ma@sdstate.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗