Biology subjects

Guo, Q.

Publications and source records attributed to Guo, Q..

11 recordsLinked to original sources

bioRxiv2018

Specification of diverse cell types during early neurogenesis of the mouse cerebellum

We applied single-cell RNA sequencing to profile genome-wide gene expression in about 9,400 individual cerebellar cells from the mouse embryo at embryonic day 13.5. Reiterative clustering identified the major cerebellar cell types and subpopulations of different lineages. Through pseudotemporal ordering to reconstruct developmental trajectories, we identified novel transcriptional programs controlling cell fate specification of populations arising from the ventricular zone and the anterior rhombic lip, two distinct germinal zones of the embryonic cerebellum. Together, our data revealed cell-specific markers for studying the cerebellum, important specification decisions, and a number of previously unknown subpopulations that may play an integral role in the formation and function of the cerebellum. Importantly, we identified a potential mechanism of vermis formation, which is affected by multiple congenital cerebellar defects. Our findings will facilitate new discovery by providing insights into the molecular and cell type diversity in the developing cerebellum.

developmental biology↗

bioRxiv2018

Osteoblastic PLEKHO1 contributes to joint inflammation in rheumatoid arthritis

Osteoblasts participating in the inflammation regulation gradually obtain concerns. However, its role in joint inflammation of rheumatoid arthritis (RA) is largely unknown. Pleckstrin homology domain-containing family O member 1 (PLEKHO1) was previously identified as a negative regulator of osteogenic lineage activity. Here we demonstrated that PLEKHO1 was highly expressed in osteoblasts of articular specimens from RA patients and inflammatory arthritis mice. Genetic deletion of osteoblastic Plekho1 ameliorated joint inflammation in mice with collagen-induced arthritis (CIA) and K/BxN serum-transfer arthritis (STA), whereas overexpressing Plekho1 only within osteoblasts in CIA and STA mice demonstrated exacerbated local inflammation. Further in vitro studies indicated that PLEKHO1 was required for TRAF2-mediated RIP1 ubiquitination to activate NF-kB for inducing inflammatory cytokines production in osteoblasts. Moreover, osteoblastic PLEKHO1 inhibition improved joint inflammation and attenuated bone formation reduction in CIA mice and non-human primate arthritis model. These data strongly suggest that highly expressed PLEKHO1 in osteoblast mediates joint inflammation in RA. Targeting osteoblastic PLEKHO1 may exert dual therapeutic action of alleviating joint inflammation and promoting bone formation in RA.

cell biology↗

bioRxiv2018

The permeabilized SecY protein-translocation channel can serve as a nonspecific sugar transporter

As the initial step in carbohydrate catabolism in cells, the substrate-specific transporters via active transport and facilitated diffusion play a decisive role in passage of sugars through the plasma membrane into the cytoplasm. The SecY complex (SecYEG) in bacteria forms a membrane channel responsible for protein translocation. This work demonstrates that weakening the sealability of the SecY channel allowed free diffusion of sugars, including glucose, fructose, mannose, xylose, arabinose, and lactose, into the engineered cells, facilitating its rapid growth on a wide spectrum of monosaccharides and bypassing/reducing stereospecificity, transport saturation, competitive inhibition, and carbon catabolite repression (CCR), which are usually encountered with the specific sugar transporters. The SecY channel is structurally conserved in prokaryotes, thus it may be engineered to serve as a unique and universal transporter for bacteria to passage sugars as demonstrated in Escherichia coli and Clostridium acetobutylicum.

bioengineering↗

bioRxiv2018

The Portal Project: a long-term study of a Chihuahuan desert ecosystem

This is a data paper for the Portal Project, a long-term ecological study of rodents, plants, and ants located in southeastern Arizona, U.S.A. This paper contains an overview of methods and information about the structure of the data files and the relational structure among the files. This is a living data paper and will be updated with new information as major changes or additions are made to the data. All data - along with more detailed data collection protocols and site information - is archived at: https://doi.org/10.5281/zenodo.1215988.

ecology↗

bioRxiv2018

Molecular Detection of H.pylori Antibiotic-Resistant Genes and Bioinformatics Predictive Analysis

To explore the mutation characteristics of H.pylori resistance-related genes to antibiotics of clarithromycin, levofloxacin and metronidazole. 23S rRNA, gyrA, gyrB, rdxA and frxA genes were amplified and sequenced, respectively. Their structural alteration after mutation was predicted using bioinformatics software. In the clarithromycin-resistant strains, the mutation rate in site A2143G was 74.2% (n=23). The mutations in sites C1883T, C2131T and T2179G might cause structural alteration. In the levofloxacin-resistant strains, the mutation rates in 87 (N to K/I) and 91 (D to N/Y/G) of gyrA were 28.6% (n=16) and 12.5% (n =7), respectively. Meanwhile, one of the mutation strains in site 91 was accompanied by D99N variation. Additionally, a D143E mutation was found in one drug-resistant strain. Some changes of tertiary structure occurred after these mutations. The mutation types of RdxA protein consisted of protein truncation caused by premature stop codons (n=26, 33.3%), frameshift mutations (n=8, 10.3%), FMN-binding sites (n=16, 20.5%) and the others (n=11, 14.1%). Predictive analysis showed that mutations in the first three groups and the A118S of the last group could lead to structural alteration. Our study suggested the clarithromycin-resistant sites of H.pylori were mainly located in A2143G of 23S rRNA. C1883T, C2131T and T2179G might also be related to resistance. Levofloxacin resistance was mainly based on the amino acid changes in 87 and 91 sites of gyrA. The new sites D99N and D143E might also be associated with resistance. Metronidazole resistance was related to RdxA protein truncation, frameshift, and FMN binding. The new site A118S might also be linked to drug resistance.

microbiology↗

bioRxiv2018

Functional connectivity alterations of the temporal lobe and hippocampus in semantic dementia and Alzheimer’s disease

The severe semantic memory impairments in semantic dementia have been attributed to a pronounced atrophy and functional disruption of the anterior temporal lobes. In contrast, the medial and posterior temporal lobe damage predominantly found in patients with Alzheimers disease has been associated with episodic memory disturbance. However, the two dementia subtypes share hippocampal deterioration, despite a relatively spared episodic memory in semantic dementia. To gain more insight into the mutual and divergent functional alterations seen in Alzheimers disease and semantic dementia, we assessed the differences in intrinsic functional connectivity between temporal lobe regions in patients with Alzheimers disease (n = 16), semantic dementia patients from two international sites (n = 23), and healthy controls (n = 17). In an exploratory study, we used a functional parcellation of the temporal cortex to extract time series. The Alzheimers disease group showed a single connection with reduced functional connectivity as compared to the controls. This connection was located between the right orbitofrontal cortex and the right anterior temporal lobe. In contrast, functional connectivity was decreased in the semantic dementia group in six connections, mainly involving the hippocampus, lingual gyrus, temporal pole, and orbitofrontal cortex. We identified a common pathway with semantic dementia, since the functional connectivity between the right anterior temporal lobe and the right orbitofrontal cortex was reduced in both types of dementia. This might be related to social knowledge deficits as part of semantic memory decline. However, such interpretations are preferably made in the context of all disease-specific semantic impairments and functional connectivity changes. Despite some limitations owed to the two database sites, this study provides a first preliminary picture of the brains functional dysconnectivity in Alzheimers disease and semantic dementia. Future studies are needed to replicate findings of such a common pathway with matched diagnosis, neuropsychological, and data MRI acquisition procedures.

neuroscience↗

bioRxiv2017

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

Discovery of cancer drivers has traditionally focused on the identification of protein-coding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the landscape of non-coding driver mutations in cancer genomes, confirming a few previously reported elements and raising doubts about others, while identifying novel candidate elements across 27 cancer types. Novel recurrent events were found in the promoters or 5UTRs of TP53, RFTN1, RNF34, and MTG2, in the 3UTRs of NFKBIZ and TOB1, and in the non-coding RNA RMRP. We provide evidence that the previously reported non-coding RNAs NEAT1 and MALAT1 may be subject to a localized mutational process. Perhaps the most striking finding is the relative paucity of point mutations driving cancer in non-coding genes and regulatory elements. Though we have limited power to discover infrequent non-coding drivers in individual cohorts, combined analysis of promoters of known cancer genes show little excess of mutations beyond TERT.

genomics↗

bioRxiv2017

Deficit in parietal memory network underlies auditory hallucination: a longitudinal study

Auditory hallucination is a prominent and common symptom in schizophrenia. Previous neuroimaging studies have yielded mixed results of its brain network deficits. We proposed a novel hypothesis that parietal memory network, centered at the precuneus, plays a critical role in auditory hallucination. This network is adjacent and partially overlaps with the default mode network, and has been associated with brain function of familiarity labelling in memory processing. Using a longitudinal design and a large cohort of first-episode, drug-naive schizophrenia patients, we examined this hypothesis and further investigated whether the functional connectivity patterns of the parietal memory network can serve as a neuroimaging marker for auditory hallucination and help to predict future treatment effects. Resting-state scans from 59 first-episode drug-naive schizophrenic patients (27 with and 32 without hallucination) and 53 healthy control subjects were acquired at the baseline test, and 56 of them were scanned again after two months. Functional connectivity strength within the parietal memory network and between this network and memory hubs was across the three groups at baseline and follow-up scans. Results showed that decreased functional connectivity strength within the parietal memory network was specific to the auditory hallucination group (p = 0.009, compare to the healthy subjects; p = 0.029, compare to the patients without hallucination), with the precuneus representing the largest group difference. The intra-network connectivity strength of the precuneus negatively correlated with the severity of hallucination at the baseline scan (r = -0.437, p = 0.029), and it was significantly increased after two-month medication (p = 0.039). Logistic regression analysis and crossvalidation test demonstrated that the functional connectivity strength of the precuneus and precuneus-hippocampus connectivity could differentiate patients with or without auditory hallucination with a sensitivity of 0.750 and a specificity of 0.708. Moreover, crossvalidation test showed that these imaging features at the baseline scan well predicted the extents of positive symptom improvement in the hallucination group after the two-month medication (R2 = 0.433, p = 0.022). Our results provide evidence for a critical role of the parietal memory network underlying auditory hallucination, and further propose a novel neuroimaging marker for identifying patients, accessing severity, and prognosis of treatment effect for auditory hallucination.\n\nAbbreviations

neuroscience↗

bioRxiv2017

The whole-genome panorama of cancer drivers

The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.

cancer biology↗

bioRxiv2017

A Site Specific Model And Analysis Of The Neutral Somatic Mutation Rate In Whole-Genome Cancer Data

BackgroundDetailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration.\n\nResultsTo take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures.\n\nConclusionWe find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

bioinformatics↗

bioRxiv2017

Identifying drivers of parallel evolution: A regression model approach

This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http://dx.doi.org/10.24072/pci.evolbiol.100045). Parallel evolution, defined as identical changes arising in independent populations, is often attributed to similar selective pressures favoring the fixation of identical genetic changes. However, some level of parallel evolution is also expected if mutation rates are heterogeneous across regions of the genome. Theory suggests that mutation and selection can have equal impacts on patterns of parallel evolution, however empirical studies have yet to jointly quantify the importance of these two processes. Here, we introduce several statistical models to examine the contributions of mutation and selection heterogeneity to shaping parallel evolutionary changes at the gene-level. Using this framework we analyze published data from forty experimentally evolved Saccharomyces cerevisiae populations. We can partition the effects of a number of genomic variables into those affecting patterns of parallel evolution via effects on the rate of arising mutations, and those affecting the retention versus loss of the arising mutations (i.e. selection). Our results suggest that gene-to-gene heterogeneity in both mutation and selection, associated with gene length, recombination rate, and number of protein domains drive parallel evolution at both synonymous and nonsynonymous sites. While there are still a number of parallel changes that are not well described, we show that allowing for heterogeneous rates of mutation and selection can provide improved predictions of the prevalence and degree of parallel evolution.\n\nData archival locationDryad, doi to be included later

evolutionary biology↗