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Qian, X.

Publications and source records attributed to Qian, X..

At least 73 records · Page 4Linked to original sources

Imaging Microglia Surveillance during Sleep-wake Cycles in Freely Behaving Mice

Microglia surveillance manifests itself as dynamic changes in cell morphology and functional remodeling. Whether and how microglia surveillance is coupled to brain state switches during natural sleep-wake cycles remain unclear. To address this question, we used miniature two-photon microscopy (mTPM) to acquire time-lapse high-resolution microglia images of the somatosensory cortex, along with EEG/EMG recordings and behavioral video, in freely-behaving mice. We uncovered fast and robust brain state-dependent changes in microglia surveillance, occurring in parallel with sleep dynamics and early-onset phagocytic microglial contraction during sleep deprivation stress. We also detected local norepinephrine fluctuation occurring in a sleep state-dependent manner. We showed that the locus coeruleus-norepinephrine system, which is crucial to sleep homeostasis, is required for both sleep state-dependent and stress-induced microglial responses and {beta}2-adrenergic receptor signaling plays a significant role in this process. These results provide direct evidence that microglial surveillance is exquisitely tuned to signals and stressors that regulate sleep dynamics and homeostasis so as to adjust its varied roles to complement those of neurons in the brain. In vivo imaging with mTPM in freely behaving animals, as demonstrated here, opens a new avenue for future investigation of microglia dynamics and sleep biology in freely behaving animals.

neuroscience↗

Systematic assessment of the contribution of structural variants to inherited retinal diseases

Despite increasing success in determining genetic diagnosis for patients with inherited retinal diseases (IRDs), mutations in about 30% of the IRD cases remain unclear or unsettled after targeted gene panel or whole exome sequencing. In this study, we aimed to investigate the contributions of structural variants (SVs) to settling the molecular diagnosis of IRD with whole-genome sequencing (WGS). A cohort of 755 IRD patients whose pathogenic mutations remain undefined was subjected to WGS. Four SV calling algorithms including include MANTA, DELLY, LUMPY, and CNVnator were used to detect SVs throughout the genome. All SVs identified by any one of these four algorithms were included for further analysis. AnnotSV was used to annotate these SVs. SVs that overlap with known IRD-associated genes were examined with sequencing coverage, junction reads, and discordant read pairs. PCR followed by Sanger sequencing was used to further confirm the SVs and identify the breakpoints. Segregation of the candidate pathogenic alleles with the disease was performed when possible. In total, sixteen candidate pathogenic SVs were identified in sixteen families, including deletions and inversions, representing 2.1% of patients with previously unsolved IRDs. Autosomal dominant, autosomal recessive, and X-linked inheritance of disease-causing SVs were observed in 12 different genes. Among these, SVs in CLN3, EYS, PRPF31 were found in multiple families. Our study suggests that the contribution of SVs detected by short-read WGS is about 0.25% of our IRD patient cohort and is significantly lower than that of single nucleotide changes and small insertions and deletions.

genetics↗

Homotopic local-global parcellation of the human cerebral cortex from resting-state functional connectivity

Resting-state fMRI is commonly used to derive brain parcellations, which are widely used for dimensionality reduction and interpreting human neuroscience studies. We previously developed a model that integrates local and global approaches for estimating areal-level cortical parcellations. The resulting local-global parcellations are often referred to as the Schaefer parcellations. However, the lack of homotopic correspondence between left and right Schaefer parcels has limited their use for brain lateralization studies. Here, we extend our previous model to derive homotopic areal-level parcellations. Using resting-fMRI and task-fMRI across diverse scanners, acquisition protocols, preprocessing and demographics, we show that the resulting homotopic parcellations are as homogeneous as the Schaefer parcellations, while being more homogeneous than five publicly available parcellations. Furthermore, weaker correlations between homotopic parcels are associated with greater lateralization in resting network organization, as well as lateralization in language and motor task activation. Finally, the homotopic parcellations agree with the boundaries of a number of cortical areas estimated from histology and visuotopic fMRI, while capturing sub-areal (e.g., somatotopic and visuotopic) features. Overall, these results suggest that the homotopic local- global parcellations represent neurobiologically meaningful subdivisions of the human cerebral cortex and will be a useful resource for future studies. Multi-resolution parcellations estimated from 1479 participants are publicly available (GITHUB_LINK).

neuroscience↗

Transcriptionally defined morphological subtypes of pancreatic ductal adenocarcinoma

Tumour heterogeneity remains a major obstacle to effective and precise therapy for pancreatic ductal adenocarcinoma (PDAC), the most common pancreatic cancer. Several transcriptional subtypes of PDAC with differential prognosis have been described, but they co-occur within tumours and are difficult to distinguish in routine clinical workflows. To investigate the relationship between transcriptional PDAC subtypes, local tissue morphology and the tumour microenvironment, we employed in situ sequencing to profile single cells in their spatial tissue context. We identify five transcriptional subtypes of PDAC cells occurring in three distinct morphological patterns, including secretory tumour cell monolayers, invasive tumour cells with high expression of cell adhesion molecules CEACAM5 and CEACAM6, and spatially distributed tumour cells associated with inflammatory-type fibroblasts. Analysis of bulk RNA-sequencing datasets of the TCGA-PAAD and PACA-AU cohorts according to these spatio-transcriptional subtypes confirmed their prognostic significance. Our results thus indicate an automatable substratification based on spatially-resolved transcriptomics of PDAC and identify distinct subtypes of classical PDAC, representing most cases of this devastating malignancy.

cancer biology↗

Sensitivity analysis of genome-scale metabolic flux prediction

TRIMER, Transcription Regulation Integrated with MEtabolic Regulation, is a genome-scale modeling pipeline targeting at metabolic engineering applications. Using TRIMER, regulated metabolic reactions can be effectively predicted by integrative modeling of metabolic reactions with Transcription Factor (TF)-gene regulatory network (TRN), where the TRN is modeled via Bayesian network (BN). In this paper, we focus on sensitivity analysis of metabolic flux prediction considering potential model uncertainty in TRIMER. We propose a computational strategy to construct the uncertainty class of TRN models based on the inferred regulatory order uncertainty when learning from given transcriptomic expression data and analyze the prediction sensitivity of the TRIMER pipeline for the metabolite yield of interest. The obtained sensitivity analyses can provide a useful guidance for Optimal Experimental Design (OED) to help acquire new data that can enhance TRN modeling and effectively achieve specific metabolic engineering objectives, including metabolite yield alterations. We have performed simulation experiments to demonstrate the effectiveness of our developed sensitivity analysis strategy and its potential to effectively guide OED. ACM Reference FormatPuhua Niu, Maria J. Soto, Shuai Huang, Byung-Jun Yoon, Edward R. Dougherty,, Francis J. Alexander, Ian Blaby, Xiaoning Qian. 2018. Sensitivity analysis of genome-scale metabolic flux prediction. In Proceedings of Make sure to enter the correct conference title from your rights confirmation email (CNB-MAC 2022). ACM, New York, NY, USA, 9 pages. https://doi.org/XXXXXXX.XXXXXXX

bioinformatics↗

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

BackgroundLarge-scale neuronal network breakdown underlies memory impairment in Alzheimers disease (AD). However, the differential trajectories of the relationships between network organization and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods708 participants from the Alzheimers Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F]fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. ResultsWe showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode network metabolism on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. ConclusionsOur findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage.

neuroscience↗

Improving functional recovery after severe spinal cord injury by a noninvasive dual functional approach of neuroprotection and neuromodulation

Despite tremendous unmet medical needs, there is no effective pharmacological treatment to promote functional recovery after spinal cord injury (SCI). Although multiple pathological events have been implicated in SCI, the development of a noninvasive pharmacological approach to simultaneously target the different mechanisms involved in SCI remains a formidable challenge. In this study, we report the development of a noninvasive nanodrug delivery system that consists of ROS-responsive amphiphilic copolymers and an encapsulated neurotransmitter-conjugated KCC2 agonist. We show that upon intravenous administration, the nanodrugs were able to enter the injured spinal cord due to blood spinal cord barrier disruption and ROS-responsive disassembly. Remarkably, once in the injured spinal cord, these nanodrugs exhibited dual functions: scavenging ROS accumulated in the lesion to protect spared connections and increasing neuronal excitability in the injured spinal cord through targeted delivery of the KCC2 agonist to inhibitory neurons. Thus, the noninvasive treatment led to significant functional recovery in the rats with contusive SCI. Together, these findings provide a much-needed translational pharmacological approach for treating severe SCI.

neuroscience↗

Mapping the allosteric effects that define functional activity of SARS-CoV-2 specific antibodies

Previous studies on the structural relationship between human antibodies and SARS-CoV-2 have focused on generating static snapshots of antibody complexes with the Spike trimer. However, antibody-antigen interactions are dynamic, with significant binding-induced allosteric effects on conformations of antibody and its target antigen. In this study, we employ hydrogen-deuterium exchange mass spectrometry, in vitro assays, and molecular dynamics simulations to investigate the allosteric perturbations linked to binding events between a group of human antibodies with differential functional activities, and the Spike trimer from SARS-CoV-2. Our investigations have revealed key dynamic features that define weakly or moderately neutralizing antibodies versus those with strong neutralizing activity. These results provide mechanistic insights into the functional modes of human antibodies against COVID-19, and provide a rationale for effective antiviral strategies. TeaserDifferent neutralizing antibodies induce site-specific allosteric effects across SARS-CoV-2 Spike protein

biochemistry↗

Diverse pathogens activate the host RIDD pathway to subvert BLOS1-directed immune defense

The phagocytosis and destruction of pathogens in lysosomes constitute central elements of innate immune defense. Here, we show that Brucella, the causative agent of brucellosis, the most prevalent bacterial zoonosis globally, subverts this immune defense pathway by activating regulated IRE1-dependent decay (RIDD) of mRNAs encoding BLOS1, a protein that promotes endosome-lysosome fusion. RIDD-deficient cells and mice harboring a RIDD-incompetent variant of IRE1 were resistant to infection. Non-functional Blos1 struggled to assemble the BLOC-1-related complex (BORC), resulting in differential recruitment of BORC-related lysosome trafficking components, perinuclear trafficking of Brucella-containing vacuoles (BCVs), and enhanced susceptibility to infection. The RIDD-resistant Blos1 variant maintains the integrity of BORC and a higher-level association of BORC-related components that promote centrifugal lysosome trafficking, resulting in enhanced BCV peripheral trafficking and lysosomal-destruction, and resistance to infection. These findings demonstrate that host RIDD activity on BLOS1 regulates Brucella intracellular parasitism by disrupting BORC-directed lysosomal trafficking. Notably, coronavirus MHV also subverted the RIDD-BLOS1 axis to promote intracellular replication. Our work therefore establishes BLOS1 as a novel immune defense factor whose activity is hijacked by diverse pathogens.

microbiology↗

Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq data

Cardiovascular and cerebrovascular diseases are leading causes of death worldwide, accounting for more than 40% of all deaths in China. Acute myocardial infarction (AMI) is a common cardiovascular disease and traditionally divided into ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI), which are known with different prognoses and treatment strategies. However, key regulatory genes and pathways involved in AMI that may be used as potential biomarker for prognosis are unknown. In this study, we constructed weighted gene co-expression networks for differential expressed genes between STEMI and NSTEMI patients based on whole-blood RNA-seq transcriptomics. Network topological attributes (e.g., node degree, betweenness) were analyzed to identify key genes involved in different functional network modules. Furthermore, we used single-cell RNA-seq data to construct multilayer signaling network to infer regulatory mechanisms of the above key genes. PLAUR (receptor for urokinase plasminogen activator) was found to play a vital role in transducing inter-cellular signals from endothelial cells and fibroblast cells to intra-cellular pathways of myocardial cells, leading to gene expression involved in cellular response to hypoxia. Our study sheds lights on identifying molecular biomarkers for diagnosis and prognosis of AMI, and provides candidate key regulatory genes for further experimental validation.

bioinformatics↗

Lung adenocarcinoma cell-derived exosomal miR-328 promote osteoclastogenesis by targeting Nrp2

Bone metastasis of lung cancer and detailed mechanisms are still elusive, and the roles of exosomes derived from lung adenocarcinoma cells in this process have attracted much attention. In this study, we found that A549 cell-derived exosomes (A549-Exos) promoted osteogenesis and bone resorption in vitro. Furthermore, A549-Exos target bone in vivo and promoted bone resorption in vivo. Mechanistically, A549-Exosomal miR-328 promoted bone resorption by targeting Nrp2 and A549-ExosmiR-328 Inhibitors inhibited bone resorption in vivo. Thus, A549-Exosomal miR-328 promote osteoclastogenesis by targeting Nrp2 and A549-ExosmiR-328 Inhibitors may serve as a potential nanomedicine for the treatment of bone metastasis.

cancer biology↗

Single domain antibodies against enteric pathogen virulence factors are active as curli fiber fusions on probiotic E. coli Nissle 1917

Enteric microbial pathogens, including Escherichia coli, Shigella and Cryptosporidium species, take a particularly heavy toll in low-income countries and are highly associated with infant mortality. We describe here a means to display anti-infective agents on the surface of a probiotic bacterium. Because of their stability and versatility, VHHs, the variable domains of camelid heavy-chain-only antibodies, have potential as components of novel agents to treat or prevent enteric infectious disease. We isolated and characterized VHHs targeting several enteropathogenic Escherichia.coli (EPEC) virulence factors: flagellin (Fla), which is required for bacterial motility and promotes colonization; both intimin and the translocated intimin receptor (Tir), which together play key roles in attachment to enterocytes; and E. coli secreted protein A (EspA), an essential component of the type III secretion system (T3SS) that is required for virulence. Several VHHs that recognize Fla, intimin, or Tir blocked function in vitro. The probiotic strain E. coli Nissle 1917 (EcN) produces on the bacterial surface curli fibers, which are the major proteinaceous component of E. coli biofilms. A subset of Fla-, intimin-, or Tir-binding VHHs, as well as VHHs that recognize either a T3SS of another important bacterial pathogen (Shigella flexneri), a soluble bacterial toxin (Shiga toxin or Clostridioides difficile toxin TcdA), or a major surface antigen of an important eucaryotic pathogen (Cryptosporidium parvum) were fused to CsgA, the major curli fiber subunit. Scanning electron micrographs indicated CsgA-VHH fusions were assembled into curli fibers on the EcN surface, and Congo Red binding indicated that these recombinant curli fibers were produced at high levels. Ectopic production of these VHHs conferred on EcN the cognate binding activity and, in the case of anti-Shiga toxin, was neutralizing. Taken together, these results demonstrate the potential of the curli-based pathogen sequestration strategy described herein and contribute to the development of novel VHH-based gut therapeutics. Author SummaryEnteric pathogens are the causative agents of diarrheal disease - a leading cause of infant morbidity and mortality worldwide. While treatment and prevention options such as drugs or vaccines exist for some pathogens, their efficacy and availability are often limited. New therapeutic strategies are therefore needed, especially inexpensive agents in low-income countries where enteric disease burdens are highest. One promising avenue for novel treatments uses VHHs - highly stable, well-expressed, antibody domains derived from camelid species such as llamas and alpacas. The small size, high stability and simple structure of these antibody fragments enables their streamlined production by bacteria such as E. coli, potentially reducing cost and improving scalability. In this work, we describe the development of VHHs targeting multiple virulence factor proteins of pathogenic E. coli and other leading causes of diarrheal disease. These VHHs provide new tools for the research community and may serve as promising components of agents that prevent or treat pathogen infections. Towards that goal, we engineered a novel system in which the probiotic, mucus-establishing bacterial strain E. coli Nissle 1917 (EcN) is used to express and display VHHs at high density on its surface. By demonstrating the ability of these engineered EcN to bind to pathogens, we provide a first step toward using such probiotics as a cheap, simple, and effective treatment for enteric pathogen infections.

microbiology↗

Retinal organoids derived from rhesus macaque iPSCs undergo accelerated differentiation compared to human stem cells

PurposeTo compare the timing and efficiency of the development of non-human primate (NHP) derived retinal organoids in comparison to those derived from human embryonic stem cells. MethodsHuman embryonic stem cells (hESCs) and induced-pluripotent stem cells (rhiPSCs) derived from non-human primates (Macaca mulatta) were differentiated into retinal organoids by using an established differentiation protocol. Briefly, embryoid bodies were formed from pluripotent stem cells and induced into a neural lineage with neural induction media with the addition of BMP4. Thereafter, self-formation of optic vesicles was allowed to form in a 2D culture in retinal differentiation media (RDM). Optic vesicles were then manually harvested and cultured in suspension in 3D-RDM media until analysis. Differences in the timing of differentiation and efficiency of retinal organoid development were assessed by light microscopy, electron microscopy, immunocytochemistry, and single-cell transcriptomics. ResultsGeneration of retinal organoids was achieved from both human and several NHP pluripotent stem cells lines. All rhiPSC lines resulted in retinal differentiation with the formation of optic vesicle-like structures similar to what has been observed in hESC retinal organoids. NHP retinal organoids had laminated structure and were composed of mature retinal cell types including cone and rod photoreceptors. Single cell RNA sequencing was conducted at two time points, which allowed identification of cell types and characterization of developmental trajectory in the developing organoid. Important differences between rhesus and human cells were measured regarding the timing and efficiency of retinal organoid differentiation. While the culture of NHP-derived iPSCs is relatively difficult compared to human stem cells, the generation of retinal organoids is feasible and may be less time consuming due to an intrinsically faster timing of retinal differentiation. ConclusionsRetinal organoids produced from iPSCs derived from Rhesus monkey using established protocols differentiate through the stages of organoid development faster than those derived from human stem cells. The production of NHP retinal organoids may be advantageous to reduce experimental time and cost for basic biology studies in retinogenesis as well as for preclinical trials in NHPs studying retinal allograft transplantation.

cell biology↗

TRIMER: Transcription Regulation Integrated with MEtabolic Regulation

Advances in bioengineering have enabled numerous bio-based commodities. Yet most traditional approaches do not extend beyond a single metabolic pathway and do not attempt to modify gene regulatory networks in order to buffer metabolic perturbations. This is despite access to near universal technologies allowing genome-scale engineering. To help overcome this limitation, we have developed a pipeline enabling analysis of Transcription Regulation Integrated with MEtabolic Regulation (TRIMER). TRIMER utilizes a Bayesian network (BN) inferred from transcriptomic data to model the transcription factor regulatory network. TRIMER then infers the probabilities of gene states that are of relevance to the metabolism of interest, and predicts metabolic fluxes resulting from deletion of transcription factors at the genome scale. Additionally, we have developed a simulation framework to mimic the TF-regulated metabolic network, capable of generating both gene expression states and metabolic fluxes, thereby providing a fair evaluation platform for benchmarking models and predictions. Here, we present this computational pipeline. We demonstrate TRIMERs applicability to both simulated and experimental data and show that it outperforms current approaches on both data types.

bioinformatics↗

Cytoplasmic and nuclear Sw-5b synergistically induce plant immune responses to inhibit different viral infection steps

O_LIPlant intracellular nucleotide binding-leucine-rich repeat (NLR) receptors play critical roles in mediating host immunity to pathogen attack. We use tomato Sw-5b::tospovirus as a model system to study the specific role of the compartmentalized plant NLR in dictating host defense against virus at different infection steps. C_LIO_LIWe demonstrated here that tomato NLR Sw-5b translocates to cytoplasm and nucleus, respectively, to play different roles in inducing host resistances against Tomato spotted wilt tospovirus (TSWV) infection. The cytoplasmic Sw-5b functions to induce a strong cell death response to inhibit TSWV replication. This host response is, however, insufficient to block viral intercellular and long-distance movement. The nucleus-localized Sw-5b triggers a host defense that weakly inhibits viral replication but strongly impedes virus intercellular and systemic movement. Furthermore, the cytoplasmic and nuclear Sw-5b act synergistically to dictate full host defense to TSWV infection. C_LIO_LIWe further demonstrated that the extended N-terminal Solanaceae domain (SD) of Sw-5b plays critical roles in cytoplasm/nucleus partitioning. Sw-5b nucleotide-binding leucine-rich repeat (NB-LRR) controls its cytoplasm localization. Strikingly, the SD but not coil-coil (CC) domain is crucial for Sw-5b receptor to translocate from cytoplasm to nucleus to trigger the immunity. The SD was found to interact with importins. Silencing both importin and {beta} expression disrupted Sw-5b nucleus translocation and host immunity against TSWV systemic infection. C_LIO_LICollectively, our findings suggest that Sw-5b bifurcates disease resistances by cytoplasm/nucleus partitioning to block different infection steps of TSWV. The findings also identified a new regulatory role of extra domain of a plant NLR in mediating host innate immunity. C_LI

plant biology↗

SARS-CoV-2 S protein ACE2 interaction reveals novel allosteric targets

The Spike (S) protein is the main handle for SARS-CoV-2 to enter host cells through surface ACE2 receptors. How ACE2 binding activates proteolysis of S protein is unknown. Here, we have mapped the S:ACE2 interface and uncovered long-range allosteric propagation of ACE2 binding to sites critical for viral host entry. Unexpectedly, ACE2 binding enhances dynamics at a distal S1/S2 cleavage site and flanking protease docking site ~27 [A] away while dampening dynamics of the stalk hinge (central helix and heptad repeat) regions ~ 130 [A] away. This highlights that the stalk and proteolysis sites of the S protein are dynamic hotspots in the pre-fusion state. Our findings provide a mechanistic basis for S:ACE2 complex formation, critical for proteolytic processing and viral-host membrane fusion and highlight protease docking sites flanking the S1/S2 cleavage site, fusion peptide and heptad repeat 1 (HR1) as allosterically exposed cryptic hotspots for potential therapeutic development. One Sentence SummarySARS-CoV-2 spike protein binding to receptor ACE2 allosterically enhances furin proteolysis at distal S1/S2 cleavage sites

biochemistry↗

Machine Learning Maps Research Needs in COVID-19 Literature

SummaryManually assessing the scope of the thousands of publications on the COVID-19 (coronavirus disease 2019) pandemic is an overwhelming task. Shortcuts through metadata analysis (e.g., keywords) assume that studies are properly tagged. However, machine learning approaches can rapidly survey the actual text of coronavirus abstracts to identify research overlap between COVID-19 and other coronavirus diseases, research hotspots, and areas warranting exploration. We propose a fast, scalable, and reusable framework to parse novel disease literature. When applied to the COVID-19 Open Research Dataset (CORD-19), dimensionality reduction suggested that COVID-19 studies to date are primarily clinical-, modeling- or field-based, in contrast to the vast quantity of laboratory-driven research for other (non-COVID-19) coronavirus diseases. Topic modeling also indicated that COVID-19 publications have thus far focused primarily on public health, outbreak reporting, clinical care, and testing for coronaviruses, as opposed to the more limited number focused on basic microbiology, including pathogenesis and transmission.

scientific communication and education↗

Mis-annotated multi nucleotide variants in public cancer genomics datasets can lead to inaccurate mutation calls with significant implications

BackgroundNext generation sequencing is widely used in cancer to profile tumors and detect variants. Most somatic variant callers used in these pipelines identify variants at the lowest possible granularity - single nucleotide variants (SNVs). As a result, multiple adjacent SNVs are called individually instead of as a multi-nucleotide variant (MNV). The problem with this level of granularity is that the amino acid change from the individual SNVs within a codon could be different from the amino acid change based on the MNV that results from combining the SNVs. Most variant annotation tools do not account for this, leading to incorrect conclusions about the downstream effects of the variants. MethodHere, we used Variant Call Files (VCFs) from the TCGA Mutect2 caller, and developed a solution to merge SNVs to MNVs. Our custom script takes the phasing information from the SNV VCFs and based on a gene model, determines if SNVs are at the same codon and need to be merged into a MNV prior to variant annotation. ResultsWe analyzed 10,383 VCFs from TCGA and found 12,141 MNVs that were incorrectly annotated. Strikingly, the analysis of seven commonly mutated genes from 178 studies from cBioPortal revealed that MNVs were consistently missed in 20 of these studies, while they were correctly annotated in 15 more recent studies. The best and most common example of MNVs was found at the BRAF V600 locus, where several public datasets reported separate BRAF V600E and BRAF V600M variants, instead of a single merged V600K variant. ConclusionWhile some datasets merged MNVs correctly, many public datasets have not been corrected for this problem. As a best practice for variant calling, we recommend that MNVs be accounted for in NGS processing pipelines, thus improving analyses on the impact of somatic variants in cancer genomics.

genomics↗