Biology subjects

Liu, P.

Publications and source records attributed to Liu, P..

At least 325 records · Page 18Linked to original sources

bioRxiv2019

Unpaired Data Empowers Association Tests

To achieve a holistic view of the underlying mechanisms of human diseases, the biomedical research community is moving toward harvesting retrospective data available in Electronic Healthcare Records (EHRs). The first step for causal understanding is to perform association tests between types of potentially high-dimensional biomedical data, such as genetic, blood biomarkers, and imaging data. To obtain a reasonable power, current methods require a substantial sample size of individuals with both data modalities. This prevents researchers from using much larger EHR samples that include individuals with at least one data type, limits the power of the association test, and may result in higher false discovery rate. We present a new method called the Semi-paired Association Test (SAT) that makes use of both paired and unpaired data. In contrast to classical approaches, incorporating unpaired data allows SAT to produce better control of false discovery and, under some conditions, improve the association test power. We study the properties of SAT theoretically and empirically, through simulations and application to real studies in the context of Chronic Obstructive Pulmonary Disease. Our method identifies an association between the high-dimensional characterization of Computed Tomography (CT) chest images and blood biomarkers as well as the expression of dozens of genes involved in the immune system.

bioinformatics↗

bioRxiv2019

Escape from nonsense mediated decay associates with anti-tumor immunogenicity

Frameshift insertion/deletions (fs-indels) are an infrequent but potentially highly immunogenic mutation subtype. Although fs-indel transcripts are susceptible to degradation through the non-sense mediated decay (NMD) pathway, we hypothesise that some fs-indels escape degradation and lead to an increased abundance of tumor specific neoantigens, that are highly distinct from self. We analysed matched DNA and RNA sequencing data from TCGA, and five separate melanoma cohorts treated with immunotherapy. Using allele-specific expression analysis we show that expressed fs-indels were enriched in genomic positions predicted to escape NMD, and associated with higher protein expression, consistent with degradation escape ("NMD-escape"). Across four independent cohorts, fs-indel NMD-escape mutations were found to be significantly associated with clinical benefit to checkpoint inhibitor (CPI) therapy (Pmeta=0.0039), a stronger association than either nsSNV (Pmeta=0.073) or fs-indel (Pmeta=0.064) count. NMD-escape mutations were additionally shown to have independent predictive power in the "low-TMB" setting, and may serve as a biomarker to rescue patients judged ineligible for CPI based on overall TMB, but still with a high chance of response (low-TMB cohort: NMD-escape-positive % clinical benefit=53%, NMD-escape-negative % clinical benefit=16%, P=0.0098). Furthermore, in an adoptive cell therapy (ACT) treated cohort, NMD-escape mutation count was the most significant biomarker associated with clinical benefit (P=0.021). Analysis of functional T-cell reactivity screens from recent personalized vaccine and CPI studies shows direct evidence of fs-indel derived neoantigens eliciting patient anti-tumor immune response (n=15). We additionally observe a subset of fs-indel mutations, with highly elongated neo open reading frames, which are found to be significantly enriched for immunogenic reactivity in these patient studies (P=0.0032). Finally, consistent with the potency of NMD-escape derived neo-antigens and ongoing immune-editing, NMD-escape fs-indels appear to be under negative selective pressure in untreated TCGA cases. Given the strongly immunogenic potential, and relatively rare nature of NMD-escape fs-indels, these alterations may be attractive candidates in immunotherapy biomarker optimisation and neoantigen ACT or vaccine strategies.

cancer biology↗

bioRxiv2019

De novo EIF2AK1 and EIF2AK2 variants are associated with developmental delay, leukoencephalopathy, and neurologic decompensation

EIF2AK1 and EIF2AK2 encode members of the Eukaryotic Translation Initiation Factor 2 Alpha Kinase (EIF2AK) family that inhibits protein synthesis in response to physiologic stress conditions. EIF2AK2 is also involved in innate immune response and the regulation of signal transduction, apoptosis, cell proliferation, and differentiation. Despite these findings, human disorders associated with deleterious variants in EIF2AK1 and EIF2AK2 have not been reported. Here, we describe the identification of eight unrelated individuals with heterozygous de novo missense variants in EIF2AK1 (1/8) or EIF2AK2 (7/8). Features seen in these eight individuals include white matter alterations (8/8), developmental delay (8/8), impaired language (8/8), cognitive impairment (7/8), ataxia (6/8), dysarthria in probands with verbal ability (6/6), hypotonia (6/8), hypertonia (5/8), and involuntary movements (3/8). Individuals with EIF2AK2 variants also exhibit neurological regression in the setting of febrile illness or infection. We use mammalian cell lines and patient-derived fibroblasts to further confirm the pathogenicity of variants in these genes and found reduced kinase activity. EIF2AKs phosphorylate Eukaryotic Translation Initiation Factor 2 Subunit 1, (EIF2S1, also known as EIF2), which then inhibits EIF2B activity. Deleterious variants in genes encoding EIF2B proteins cause childhood ataxia with central nervous system hypomyelination/vanishing white matter disease (CACH/VWM), a leukoencephalopathy characterized by neurologic regression in the setting of febrile illness and other stressors. Our findings indicate that EIF2AK2 missense variants cause a neurodevelopmental syndrome that may share phenotypic and pathogenic mechanisms with CACH/VWM.

genetics↗

bioRxiv2019

Multi-Region Brain Stimulation Optimization Using Transcranial Direct Current Stimulation

Transcranial direct current stimulation (tDCS) is a type of noninvasive transcranial electrical brain stimulation. By optimizing the current distribution of each electrode on the scalp, the stimulation can be guided to a target brain region using a tDCS dense electrode array system. However, previous studies have yielded simple results using optimization schemes in single target stimulation cases. The detailed parameter settings for each optimization scheme and the associated simulation results have not been comprehensively assessed. In this study, we investigated parameter settings of optimization schemes in detail in both single target and multi-target cases. Two optimization schemes, minimum least squares (MLS) and maximum electrical field strength (ME), were examined in this study. MLS minimizes the squared errors between the expected electrical field and the estimated electrical field, whereas ME maximizes the electrical field strength in the target region. We constructed a five layer finite-element head model with 64 electrodes placed on the scalp according to the EEG 10/10 system for simulation. We evaluated the effects of stimulation using these two schemes under three conditions, 1) single target stimulation, 2) multi-target stimulation, and 3) multi-target stimulation under specific task activation, which shown that directly using MLS and ME scheme in multi-target stimulation case may lead to a wrong result. We also reported the improved results fixed by our proposed weighted MLS and weighted ME schemes which take detailed parameter settings into consideration. Our results indicate that the parameter settings in each optimization scheme greatly affected the final stimulation results, especially in the case of multi-target stimulation, and thus, indicate that the parameter settings of each optimization scheme should be carefully considered according to the expected stimulation mode. Our results also suggest that, by calculating the parameters through our proposed methods, the weighted ME and weighted MLS scheme can precisely distribute energy into each target brain region.

bioengineering↗

bioRxiv2019

High-throughput experimental evolution using barcoded strains of Saccharomyces cerevisiae

BackgroundExperimental evolution of microbes can be used to empirically address a wide range of questions about evolution and is increasingly employed to study complex phenomena ranging from genetic evolution to evolutionary rescue. Regardless of experimental aims, fitness assays are a central component of this type of research, and low-throughput often limits the scope and complexity of experimental evolution studies. We created an experimental evolution system in Saccharomyces cerevisiae that utilizes genetic barcoding to overcome this challenge. ResultsWe first confirm that barcode insertions do not alter fitness and that barcode sequencing can be used to efficiently detect fitness differences via pooled competition-based fitness assays. Next, we examine the effects of ploidy, chemical stress, and population bottleneck size on the evolutionary dynamics and fitness gains (adaptation) in a total of 76 experimentally evolving, asexual populations by conducting 1,216 fitness assays and analyzing 532 longitudinal-evolutionary samples collected from the evolving populations. In our analysis of these data we describe the strengths of this experimental evolution system and explore sources of error in our measurements of fitness and evolutionary dynamics. ConclusionsOur experimental treatments generated distinct fitness effects and evolutionary dynamics, respectively quantified via multiplexed fitness assays and barcode lineage tracking. These findings demonstrate the utility of this new resource for designing and improving high-throughput studies of experimental evolution. The approach described here provides a framework for future studies employing experimental designs that require high-throughput multiplexed fitness measurements.

evolutionary biology↗

bioRxiv2019

Genetic and molecular mechanism for distinct clinical phenotypes conveyed by allelic truncating mutations implicated in FBN1

The molecular and genetic mechanisms by which different single nucleotide variant (SNV) alleles in specific genes, or at the same genetic locus, bring about distinct disease phenotypes often remain unclear. Allelic truncating mutations of fibrillin-1(FBN1) cause either classical Marfan syndrome (MFS) or a more severe phenotype associated with Marfanoid-progeroid-lipodystrophy syndrome (MPLS). A total of three Marfan syndrome/Marfanoid patients (2 singletons and 1 parent-offspring trio) were recruited. Targeted next-generation sequencing was performed on all the participants. We analyzed the molecular diagnosis, patient clinical features, and the potential molecular mechanism involved in the MPLS subject in our cohort. We investigated a small cohort, consisting of two classical MFS and one MPLS patient from China, whose clinical presentation included scoliosis potentially requiring surgical intervention. We provide evidence that most nonsense and frameshift mutations lead to FBN1 null alleles due to mutant mRNA transcript degradation. In contrast, the more severe disease phenotype, MPLS, is caused by mutant mRNAs that are predicted to escape the nonsense mediated decay (NMD) surveillance pathway, making a mutant protein that exerts a dominant negative interference effect to FBN1 thus generating a gain-of-function (GoF) rather than a loss-of-function (LoF) allele as in MFS. Overall, we provide direct evidence that a dominant negative interaction of FBN1 potentially explains the distinct clinical phenotype in MPLS patients through genetic and functional analysis of the first Chinese patient with MPLS. Moreover, our study expands the mutation spectrum of FBN1 and highlights the potential molecular mechanism for MPLS patients.

genetics↗

bioRxiv2019

Quantitative three-dimensional nondestructive imaging of whole anaerobic ammonium-oxidizing bacteria

Anaerobic ammonium-oxidizing (anammox) bacteria play a key role in the global nitrogen cycle and the treatment of nitrogenous wastewater. These functions are closely related to the unique biophysical structure of anammox bacteria. However, the research on the biophysical ultrastructure of intact anammox bacteria is lacking. In this study, in-situ three-dimensional nondestructive ultrastructure imaging of whole anammox cell was performed using synchrotron soft X-ray nano-computed tomography and the total variation-based simultaneous algebraic reconstruction technique (TV-SART). Statistical and quantitative analyses of the ultrastructures of intact anammox bacteria were performed. The linear absorption coefficient values of the ultrastructures of anammox bacteria were calculated and the asymmetric structure of the anammox bacteria was quantified. On this basis, the shape adaptation of the anammox bacteria responses to Fe2+ were explored, and the underlying regulation mechanism of Fe2+ on anammox bacteria was explored. Furthermore, a promising method to study the biophysical properties of cells in different environments and engineering processes was proposed.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=96 SRC=\"FIGDIR/small/709188v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@1994e5eorg.highwire.dtl.DTLVardef@1e80137org.highwire.dtl.DTLVardef@a7f418org.highwire.dtl.DTLVardef@8a77e5_HPS_FORMAT_FIGEXP M_FIG C_FIG Statement of SignificanceAnaerobic ammonium-oxidizing (anammox) bacteria play key role in global nitrogen cycle, and this physiological function depends on the unique morphology of anammox bacteria. In this study, synchrotron soft-X ray imaging technique coupled with simultaneous algebraic reconstruction technique with total variation (SART-TV) algorithm were performed to quantify the three-dimensional ultrastructure of the whole anammox bacteria for the first time. On this basis, the shape adaptation and mechanism of the anammox bacteria responses to Fe2+ were explored and a promising method for detecting the physiological properties of anammox bacteria was proposed.

cell biology↗

bioRxiv2019

Deep learning reveals hidden variables underlying NF-κB activation in single cells

Individual cells show great heterogeneity when responding to environmental cues. For example, under cytokine stimulation some cells activate immune signaling pathways while others completely ignore the signal. The underlying sources of cellular variability have been inaccessible due to the destructive nature of experiments. Here we apply deep learning, live-cell analysis, and mechanistic modeling to uncover hidden variables controlling NF-{kappa}B activation in single-cells. Our computer-vision algorithm accurately predicts cells that will respond to pro-inflammatory TNF stimulation and shows that single-cell activation is pre-determined by minute amounts of \"leaky\" nuclear NF-{kappa}B localization before stimulation. Theoretical analysis predicts and experiments confirm that the ratio of NF-{kappa}B to its inhibitor I{kappa}B determines the activation probability of a given cell. Our results demonstrate how computer vision can study living-cells without the use of destructive measurements and settles the question of whether heterogenous NF-{kappa}B activation is controlled by pre-existing deterministic variables or purely stochastic ones.

systems biology↗

bioRxiv2019

Chromosome level draft genomes of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), an alien invasive pest in China

The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith) is a severely destructive pest native to the Americas, but has now become an alien invasive pest in China, and causes significant economic loss. Therefore, in order to make effective management strategies, it is highly essential to understand genomic architecture and its genetic background. In this study, we assembled two chromosome scale genomes of the fall armyworm, representing one male and one female individual procured from Yunnan province of China. The genome sizes were identified as 542.42 Mb with N50 of 14.16 Mb, and 530.77 Mb with N50 of 14.89 Mb for the male and female FAW, respectively. We predicted about 22,201 genes in the male genome. We found the expansion of cytochrome P450 and glutathione s-transferase gene families, which are functionally related to the intensified detoxification and pesticides tolerance. Further population analyses of corn strain (C strain) and rice strain (R strain) revealed that the Chinese fall armyworm was most likely invaded from Africa. These strain information, genome features and possible invasion source described in this study will be extremely important for making effective strategies to manage the fall armyworms.

genomics↗

bioRxiv2019

Arabidopsis Proteome and the Mass Spectral Assay Library

Arabidopsis is an important model organism and the first plant with its genome sequenced. Knowledge from studying this species has either direct or indirect applications to agriculture and human health. Quantitative proteomics by data-independent acquisition (SWATH/DIA-MS) was recently developed and considered as a high-throughput targetedlike approach for accurate proteome quantitation. In this approach, a high-quality and comprehensive library is a prerequisite. Here, we generated a protein expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We subsequently applied DIA-mass spectrometry using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups with 1,787 of them being differentially expressed which includes 65 proteins known to respond to abscisic acid stress. Mass spectrometry data are available via ProteomeXchange with identifier PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1a3f799org.highwire.dtl.DTLVardef@1d4711dorg.highwire.dtl.DTLVardef@4e3f73org.highwire.dtl.DTLVardef@127a9a4org.highwire.dtl.DTLVardef@f254bb_HPS_FORMAT_FIGEXP M_TBL C_TBL

plant biology↗

bioRxiv2019

PRAM: a novel pooling approach for discovering intergenic transcripts from large-scale RNA sequencing experiments

Publicly available RNA-seq data is routinely used for retrospective analysis to elucidate new biology. Novel transcript discovery enabled by joint examination of large collections of RNA-seq datasets has emerged as one such analysis. Current methods for transcript discovery rely on a 2-Step approach where the first step encompasses building transcripts from individual datasets, followed by the second step that merges predicted transcripts across datasets. To increase the power of transcript discovery from large collections of RNA-seq datasets, we developed a novel 1-Step approach named Pooling RNA-seq and Assembling Models (PRAM) that builds transcript models from pooled RNA-seq datasets. We demonstrate in a computational benchmark that 1-Step outperforms 2-Step approaches in predicting overall transcript structures and individual splice junctions, while performing competitively in detecting exonic nucleotides. Applying PRAM to 30 human ENCODE RNA-seq datasets identified unannotated transcripts with epigenetic and RAMPAGE signatures similar to those of recently annotated transcripts. In a case study, we discovered and experimentally validated new transcripts through the application of PRAM to mouse hematopoietic RNA-seq datasets. Notably, we uncovered new transcripts that share a differential expression pattern with a neighboring gene Pik3cg implicated in human hematopoietic phenotypes, and we provided evidence for the conservation of this relationship in human. PRAM is implemented as an R/Bioconductor package and is available at https://bioconductor.org/packages/pram.

bioinformatics↗

bioRxiv2019

Quantitative insights into age-associated DNA-repair inefficiency in single cells

The double strand break (DSB) is a highly toxic form of DNA damage that is thought to be both a driver and consequence of age-related dysfunction. Although DSB repair is essential for a cells survival, little is known about how DSB repair mechanisms are affected by cellular age. Here we characterize the impact of cellular aging on the efficiency of single-strand annealing (SSA), a repair mechanism for DSBs occurring between direct repeats. Using a single-cell reporter of SSA repair, we measure SSA repair efficiency in young and old cells, and report a 23.4% decline in repair efficiency. This decline is not due to increased usage of non-homologous end joining (NHEJ). Instead, we identify increased G1-phase duration in old cells as a factor responsible for the decreased SSA repair efficiency. We further explore how SSA repair efficiency is affected by sequence heterology and find that heteroduplex rejection remains high in old cells. Our work provides novel quantitative insights into the links between cellular aging and DSB repair efficiency at single-cell resolution in replicatively aging cells.

systems biology↗

bioRxiv2019

Inhibition of GMP synthesis extends yeast replicative lifespan

Aging, the time-dependent accumulation of molecular damage, is the primary limiting factor of human lifespan. Slowing down damage accumulation or its prevention therefore represents a promising therapeutic paradigm to combat aging-related disease and death. While several chemical compounds extend lifespan in model organisms, their mechanism of action is often unknown, reducing their therapeutic potential. Using a systematic approach, here we show that inhibition of GMP synthesis is a novel lifespan extension mechanism in yeast. We further discover that proteasome activation extends lifespan in part through GMP insufficiency. GMP synthesis inhibition exerts its lifespan extension effect independently of the canonical nutrient-sensing and sirtuin pathways regulating lifespan. Exposing longitudinally aging yeast cells to GMP synthesis inhibition in an age-dependent manner, we demonstrate that the lifespan extension by GMP insufficiency is facilitated by slowing, rather than reversing, the aging process in cells. While GMP and its downstream metabolites are involved in many cellular processes in cells, our results rule out the combined effect of global transcription and translation on cellular lifespan. These findings elucidate the involvement of nucleotide metabolism in the aging process. The existence of clinically-approved GMP synthesis inhibitors elicits the potential of a new class of therapeutics for aging-related disorders.

systems biology↗

bioRxiv2019

The preparation of cyclopentadecanone and cyclopentadecanolide from Malania oleifera Chum oil

The macrocyclic musks are of central importance in the fragrance industry. The preparation of cyclopentadecanone and cyclopentadecanolide from Malania oleifera Chum oil were investigated. Preparation method of cyclopentadecanone is three steps process: first fatty acid double bonds of Malania oleifera Chum oil are cut off by ozonolysis; second ozonides are converted into methyl esters by esterification; afterwards cyclopentadecanone was achieved from through acyloin condensation, reduction and separation with 38.5 % overall yield. The preparation coyfclopentadecanolide is two step process: first by ozonolysis triglycerides of {omega}-hydroxycarboxylic acids synthesized from malania oleifera chum oil by ozonolysis; and it were catalytically transformed to macrocyctic lactones, and a 63% yield of cyclopentadecanolide was obtained. The effect of different ester groups on cyclization of ,{omega}-difatty acid alkyl ester, and effect of catalysts on cyclization of {omega}-hydroxycarboxylic acid triglyceride were investigated.

scientific communication and education↗

bioRxiv2019

Static and Dynamic Functional Connectivity Analysis of Cerebrovascular Reactivity: An fMRI Study

The human brain, as a finely-tuned system, needs a constant flow of oxygen to function properly. To accomplish this, the cerebrovascular system ensures a steady stream of oxygenation to brain cells. One tool that the cerebrovascular system uses is cerebrovascular reactivity (CVR), which is the systems ability to react to vasoactive stimuli. Understanding CVR can provide unique information about cerebrovascular diseases and general brain function. CVR can be evaluated by scanning subjects with blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) while they periodically inhale room air and CO2-enriched gas, a powerful and widely-used vasodilator. Our goal is to understand the effect of vasodilation on individual intrinsic connectivity networks (ICNs), as well as how functional network connectivity (FNC) adapts to the same vasodilation. To achieve this goal, we first developed an innovative metric to measure the effect of CVR on ICNs, which contrasts to the commonly used voxel-wise CVR. Furthermore, for the first time, we studied static (sFNC) and dynamic (dFNC) FNC in the context of CVR. Our results show that network connectivity is generally weaker during vascular dilation, and these results are more pronounced in dFNC analysis. dFNC analysis reveals that participants did not return to the pre-CO2 inhalation state, suggesting that the one-minute period of room-air inhalation is not enough for the CO2 effect to fully dissipate in humans. Overall, we see new relationships between CVR and ICNs, as well as how FNC adapts to vascular system changes.

neuroscience↗

bioRxiv2019

The Gag Protein PEG10 Binds to RNA and Regulates Trophoblast Stem Cell Lineage Specification.

Peg10 (paternally expressed gene 10) is an imprinted gene that is essential for placental development. It is thought to derive from a Ty3-gyspy LTR (long terminal repeat) retrotransposon and retains Gag and Pol-like domains. Here we show that the Gag domain of PEG10 can promote vesicle budding similar to the HIV p24 Gag protein. Expressed in a subset of mouse endocrine organs in addition to the placenta, PEG10 was identified as a substrate of the deubiquitinating enzyme USP9X. Consistent with PEG10 having a critical role in placental development, PEG10-deficient trophoblast stem cells (TSCs) exhibited impaired differentiation into placental lineages. PEG10 expressed in wild-type, differentiating TSCs was bound to many cellular RNAs including Hbegf (Heparin-binding EGF-like growth factor), which is known to play an important role in placentation. Expression of Hbegf was reduced in PEG10-deficient TSCs suggesting that PEG10 might bind to and stabilize RNAs that are critical for normal placental development.

molecular biology↗

bioRxiv2019

A semi-parametric Bayesian approach, iSBA, for differential expression analysis of RNA-seq data

RNA sequencing (RNA-seq) technologies have been popularly applied to study gene expression in recent years. Identifying differentially expressed (DE) genes across treatments is one of the major steps in RNA-seq data analysis. Most differential expression analysis methods rely on parametric assumptions, and it is not guaranteed that these assumptions are appropriate for real data analysis. In this paper, we develop a semi-parametric Bayesian approach for differential expression analysis. More specifically, we model the RNA-seq count data with a Poisson-Gamma mixture model, and propose a Bayesian mixture modeling procedure with a Dirichlet process as the prior model for the distribution of fold changes between the two treatment means. We develop Markov chain Monte Carlo (MCMC) posterior simulation using Metropolis Hastings algorithm to generate posterior samples for differential expression analysis while controlling false discovery rate. Simulation results demonstrate that our proposed method outperforms other popular methods used for detecting DE genes.

genomics↗

bioRxiv2019

Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing

The libraries generated by high-throughput single cell RNA-sequencing platforms such as the Chromium from 10X Genomics require considerable amounts of sequencing, typically due to the large number of cells. The ability to use this data to address biological questions is directly impacted by the quality of the sequence data. Here we have compared the performance of the Illumina NextSeq 500 and NovaSeq 6000 against the BGI MGISEQ-2000 platform using identical Single Cell 3 libraries consisting of over 70,000 cells. Our results demonstrate a highly comparable performance between the NovaSeq 6000 and MGISEQ-2000 in sequencing quality, and cell, UMI, and gene detection. However, compared with the NextSeq 500, the MGISEQ-2000 platform performs consistently better, identifying more cells, genes, and UMIs at equalised read depth. We were able to call an additional 1,065,659 SNPs from sequence data generated by the BGI platform, enabling an additional 14% of cells to be assigned to the correct donor from a multiplexed library. However, both the NextSeq 500 and MGISEQ-2000 detected similar frequencies of gRNAs from a pooled CRISPR single cell screen. Our study provides a benchmark for high capacity sequencing platforms applied to high-throughput single cell RNA-seq libraries.

genomics↗