Biology subjects

Meng, G.

Publications and source records attributed to Meng, G..

43 records · Page 3Linked to original sources

bioRxiv2018

MitoZ: A toolkit for mitochondrial genome assembly, annotation and visualization

Mitochondrial genome (mitogenome) plays important roles in evolutionary and ecological studies. It becomes routine to utilize multiple genes on mitogenome or the entire mitogenomes to investigate phylogeny and biodiversity of focal groups with the onset of High Throughput Sequencing technologies. We developed a mitogenome toolkit MitoZ, consisting of independent modules of de novo assembly, findMitoScaf, annotation and visualization, that can generate mitogenome assembly together with annotation and visualization results from HTS raw reads. We evaluated its performance using a total of 50 samples of which mitogenomes are publicly available. The results showed that MitoZ can recover more full-length mitogenomes with higher accuracy compared to the other available mitogenome assemblers. Overall, MitoZ provides a one-click solution to construct the annotated mitogenome from HTS raw data and will facilitate large scale ecological and evolutionary studies. MitoZ is free open source software distributed under GPLv3 license and available at https://github.com/linzhi2013/MitoZ.

bioinformatics↗

bioRxiv2018

TSD: A computational tool to study the complex structural variants using PacBio targeted sequencing data

The PacBio sequencing is a powerful approach to study the DNA or RNA sequences in a longer scope. It is especially useful in exploring the complex structural variants generated by random integration or multiple rearrangement of internal or external sequences. However, there is still no tool designed to uncover their structural organization in the host genome. Here, we present a tool, TSD, for complex structural variant discovery using PacBio targeted sequencing data. It allows researchers to identify and visualize the genomic structures of targeted sequences by unlimited splitting, alignment and assembly of long PacBio reads. Application to the sequencing data derived from an HBV integrated human cell line(PLC/PRF/5) indicated that TSD could recover the full profile of HBV integration events, especially for the regions with the complex human-HBV genome integrations and multiple HBV rearrangements. Compared to other long read analysis tools, TSD showed a better performance for detecting complex genomic structural variants. TSD is publicly available at: https://github.com/menggf/tsd

bioinformatics↗

bioRxiv2018

TransgeneR: a one-stop tool for transgene integration and rearrangement discovery using sequencing data

Genetically modified organisms are widely used in lifescience research, agriculture and in commercial products. However, in most cases, the genetic modification in the host genome is often less well characterized with respect to integration location, copy number and host gene expression. The application of next generation sequencing technologies has enabled the characterization of transgene events but still limited by the lack of computational tools. We present a one-stop R tool, transgeneR, as a general computational tool for discovering transgene integration and rearrangement in the host genome. It especially considers the properties of transgene events, such as the homologous transgene sequences, complex genetic structure and multiple copies of transgene insertion. Using this tool, we have successfully mapped the chromosomal transgene integration loci and transgene rearrangements in an artificially simulated MAPT transgene mice genome as well as in a newly generated human tau (MAPT, 0N4R) transgene mice. When unbiased sequencing data such as the whole genome sequencing data, were provided as input, transgeneR integrated multiple information, including integration location, direction, split- and nonsplit-reads, to predict the transgene fragments and their copy number. Overall, our initial evaluation indicates that the transgeneR package is an effective tool for the identification and characterization of transgene integration and rearrangements events, especially in transgene genome with complex genetic structure. TransgeneR is publicly available: https://github.com/menggf/transgeneR

bioinformatics↗

bioRxiv2018

Adopting Literature-based Discovery on Rehabilitation Therapy Repositioning for Stroke

Stroke is a common disabling disease severely affecting the daily life of the patients. There is evidence that rehabilitation therapy can improve the movement function. However, there are no clear guidelines that identify specific, effective rehabilitation therapy schemes, and the development of new rehabilitation techniques has been fairly slow. One informatics translational approach, called ABC model in Literature-based Discovery, was used to mine an existing rehabilitation candidate which is most likely to be repositioned for stroke. As in the classic ABC model originated from Don Swanson, we built the internal links of stroke (A), assessment scales (B), rehabilitation therapies (C) in PubMed relating to upper limb function measurements for stroke patients. In the first step, with E-utility we retrieved both stroke related assessment scales and rehabilitation therapies records, and complied two datasets called Stroke_Scales and Stroke_Therapies, respectively. In the next step, we crawled all rehabilitation therapies co-occurred with the Stroke_Theapies, named as All_Therapies. Therapies that were already included in Stroke_Therapies were deleted from All_Therapies, so that the remaining therapies were the potential rehabilitation therapies, which could be repositioned for stroke after subsequent filtration by manual check. We identified the top ranked repositioning rehabilitation therapy following by subsequent clinical validation. Hand-arm bimanual intensive training (HABIT) ranked the first in our repositioning rehabilitation therapies list, with the most interaction links with Stroke_Scales. HABIT showed a significant improvement in clinical scores on assessment scales of Fugl-Meyer Assessment and Action Research Arm Test in the clinical validation on upper limb function for acute stroke patients. Based on the ABC model and clinical validation of the results, we put forward that HABIT as a promising rehabilitation therapy for stroke, which shows that the ABC model is an effective text mining approach for rehabilitation therapy repositioning. The results seem to be promoted in clinical knowledge discovery.\n\nAuthor SummaryIn the present study, we proposed a text mining approach to mining terms related to disease, rehabilitation therapy, and assessment scale from literature, with a subsequent ABC inference analysis to identify relationships of these terms across publications. The clinical validation demonstrated that our approach can be used to identify potential repositioning rehabilitation therapy strategies for stroke. Specifically, we identified a promising rehabilitation method called HABIT previously used in pediatric congenital hemiplegia. A subsequent clinical trial confirmed this as a highly promising rehabilitation therapy for stroke.

bioinformatics↗

bioRxiv2018

Myricetin Attenuates LPS-induced Inflammation in RAW 264.7 Macrophages and Mouse Models

BackgroundMyricetin has been demonstrated to inhibit inflammation in a variety of diseases, but little is known about its characters in acute lung injury (ALI). In this study, we aimed to investigate the protective effects of myricetin on inflammation in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells and a LPS-induced lung injury model.\n\nMethodsSpecifically, we investigated its effects on lung edema and histological damage by lung W/D weight ratio, HE staining and Evans Blue dye. Then macrophage activation was detected by evaluating the TNF-, IL-6 and IL-1{beta} mRNA and protein iNOS and COX-2. Myricetin was used to detect the impact on the inflammatory responses in LPS-induced RAW264.7 cells with the same manners in mouse model. Finally, NF-{kappa}B and MAPK signaling pathways were investigated with Western blot assay in LPS-induced RAW264.7 cells.\n\nResultsMyricetin significantly inhibited the production of the pro-inflammatory cytokines in vitro and in vivo. The in vivo experiments showed that pretreatment with Myricetin markedly attenuated the development of pulmonary edema, histological severities and macrophage activation in mice with ALI. The underlying mechanisms were further demonstrated in vitro that myricetin exerted an anti-inflammatory effect through suppressing the NF-{kappa}B p65 and AKT activation in NF-{kappa}B pathway and JNK, p-ERK and p38 in mitogen-activated protein kinases signaling pathway.\n\nConclusionMyricetin alleviated ALI by inhibiting macrophage activation, and inhibited inflammation in vitro and in vivo. It may be a potential therapeutic candidate for the prevention of inflammatory diseases.

cell biology↗

bioRxiv2017

Transcriptional dysregulation study reveals a core network involving the genesis for Alzheimer’s disease

BackgroundThe pathogenesis of Alzheimers disease is associated with dysregulation at different levels from transcriptome to cellular functioning. Such complexity necessitates investigations of disease etiology to be carried out considering multiple aspects of the disease and the use of independent strategies. The established works more emphasized on the structural organization of gene regulatory network while neglecting the internal regulation changes.\n\nMethodsApplying a strategy different from popularly used co-expression network analysis, this study investigated the transcriptional dysregulations during the transition from normal to disease states.\n\nResults97 genes were predicted as dysregulated genes, which were also associated with clinical outcomes of Alzheimers disease. Both the co-expression and differential co-expression analysis suggested these genes to be interconnected as a core network and that their regulations were strengthened during the transition to disease states. Functional studies suggested the dysregulated genes to be associated with aging and synaptic function. Further, we checked the evolutionary conservation of the gene co-expression and found that human and mouse brain might have divergent transcriptional co-regulation even when they had conserved gene expression profiles.\n\nConclusionOverall, our study reveals a profile of transcriptional dysregulation in the genesis of Alzheimers disease by forming a core network with altered regulation; the core network is associated with Alzheimers diseases by affecting the aging and synaptic functions related genes; the gene regulation in brain may not be conservative between human and mouse.

systems biology↗

bioRxiv2017

Applying expression profile similarity for discovery of patient-specific functional mutations

The progress of cancer genome sequencing projects yields unprecedented information of mutations for numerous patients. However, the complexity of mutation profiles of patients hinders the further understanding of mechanisms of oncogenesis. One basic question is how to uncover mutations with functional impacts. In this work, we introduce a computational method to predict functional somatic mutations for each of patient by integrating mutation recurrence with similarity of expression profiles of patients. With this method, the functional mutations are determined by checking the mutation enrichment among a group of patients with similar expression profiles. We applied this method to three cancer types and identified the functional mutations. Comparison of the predictions for three cancer types suggested that most of the functional mutations were cancer-type-specific with one exception to p53. By checking prediction results, we found that our method effectively filtered non-functional mutations resulting from large protein sizes. In addition, this methods can also perform functional annotation to each patient to describe their association with signalling pathways or biological processes. In breast cancer, we predicted \"cell adhesion\" and other mutated gene associated terms to be significantly enriched among patients.

bioinformatics↗