Biology subjects

Wang, K.

Publications and source records attributed to Wang, K..

539 records · Page 30Linked to original sources

bioRxiv2017

Hi-TOM: a platform for high-throughput tracking of mutations induced by CRISPR/Cas systems

The CRISPR/Cas system has been extensively applied to make precise genetic modifications in various organisms. Despite its importance and widespread use, large-scale mutation screening remains time-consuming, labour-intensive and costly. Here, we describe a cheap, practicable and high-throughput screening strategy that allows parallel screening of 96 x N (N denotes the number of targets) genome-modified sites. The strategy simplified and streamlined the process of next-generation sequencing (NGS) library construction by fixing the bridge sequences and barcoding primers. We also developed Hi-TOM (available at http://www.hi-tom.net/hi-tom/), an online tool to track the mutations with precise percentage. Analysis of the samples from rice, hexaploid wheat and human cells reveals that the Hi-TOM tool has high reliability and sensitivity in tracking various mutations, especially complex chimeric mutations that frequently induced by genome editing. Hi-TOM does not require specially design of barcode primers, cumbersome parameter configuration or additional data analysis. Thus, the streamlined NGS library construction and comprehensive result output make Hi-TOM particularly suitable for high-throughput identification of all types of mutations induced by CRISPR/Cas systems.

bioinformatics↗

bioRxiv2017

TNER: A Novel Bayesian Background Error Suppression Method for Mutation Detection in Circulating Tumor DNA

The use of ultra-deep, next generation sequencing of circulating tumor DNA (ctDNA) holds great promise for early detection of cancer as well as a tool for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection. To achieve high accuracy of variant calling via better distinguishing low frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. It significantly enhances the specificity for downstream ctDNA mutation detection without sacrificing sensitivity. Results on both simulated and real healthy subjects data demonstrate that the proposed algorithm consistently outperforms a current, state of the art, position-specific error polishing model, particularly when the sample size of healthy subjects is small. TNER is publicly available at https://github.com/ctDNA/TNER.

bioinformatics↗

bioRxiv2017

Gene expression in patient-derived neural progenitors provide insights into neurodevelopmental aspects of schizophrenia

BACKGROUNDGWAS of schizophrenia demonstrated that variations in the non-coding regions are responsible for most of common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Thus, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease. In this study we use Cultured Neural progenitor cells derived from Olfactory Neuroepithelium (CNON) as a genetically unaltered cellular model to elucidate the neurodevelopmental aspects of schizophrenia.\n\nMETHODSWe performed a gene expression study using RNA-Seq of CNON from 111 controls and 144 individuals with schizophrenia. Differentially expressed (DEX) genes were identified with DESeq2, using covariates to correct for sex, age, library batches and one surrogate variable component.\n\nRESULTS80 genes were DEX (FDR<10%), showing enrichment in cell migration, cell adhesion, developmental process, synapse assembly, cell proliferation and related gene ontology categories. Cadherin and Wnt signaling pathways were positive in overrepresentation test, and, in addition, many genes are specifically involved in Wnt5A signaling. The DEX genes were significantly, enriched in the genes overlapping SNPs with genome-wide significant association from the PGC GWAS of schizophrenia (PGC SCZ2). We also found substantial overlap with genes associated with other psychiatric disorders or brain development, enrichment in the same GO categories as genes with mutations de novo in schizophrenia, and studies of iPSC-derived neural progenitor cells.\n\nCONCLUSIONSCNON cells are a good model of the neurodevelopmental aspects of schizophrenia and can be used to elucidate the etiology of the disorder.

genetics↗

bioRxiv2017

Base-resolution mapping reveals distinct m1A methylome in nuclear- and mitochondrial-encoded transcripts

Gene expression can be post-transcriptionally regulated via dynamic and reversible RNA modifications. N1-methyladenosine (m1A) is a recently identified mRNA modification; however, little is known about its precise location, regulation and function. Here, we develop a base-resolution m1A profiling method, based on m1A-induced misincorporation during reverse transcription, and report distinct classes of m1A methylome in the human transcriptome. m1A in 5-UTR, particularly those at the first nucleotide of mRNA, associate with increased translation efficiency. A different subset of m1A exhibit a GUUCRA tRNA-like motif, are evenly distributed in the transcriptome and are dependent on the methyltransferase TRMT6/61A. Additionally, we show for the first time that m1A is prevalent in the mitochondrial-encoded transcripts. Manipulation of m1A level via TRMT61B, a mitochondria-localizing m1A methyltransferase, demonstrates that m1A in mitochondrial mRNA interferes with translation. Collectively, our approaches reveal distinct classes of m1A methylome and provide a resource for functional studies of m1A-mediated epitranscriptomic regulation.

biochemistry↗

bioRxiv2017

Structured illumination to spatially map chromatin motions

We describe a simple optical method that creates structured illumination of a photoactivatable probe and apply this method to characterize chromatin motions in the nuclei of live cells. A laser beam coupled to a diffractive optical element at the back focal plane of an excitation objective generates an array of near diffraction-limited beamlets with FWHM of 340{+/-}30 nm, which simultaneously photoactivate a 7x7 matrix pattern of GFP-labeled histones, with spots 1.70 m apart. From the movements of the photoactivated spots, we map chromatin diffusion coefficients at multiple microdomains of the cell nucleus. The results show correlated motions of nearest chromatin microdomain neighbors, whereas chromatin movements are uncorrelated at the global scale of the nucleus. The method also reveals DNA damage-dependent decrease in chromatin diffusion. The DOE instrumentation can easily and cheaply be implemented on commercial inverted fluorescence microscopes to analyze adherent cell culture models. A protocol to measure chromatin motions in non-adherent human hematopoietic stem and progenitor cells is also described. We anticipate that the method will contribute to the identification of the mechanisms regulating chromatin mobility, which influences most genomic processes and may underlie the biogenesis of genomic translocations associated with hematologic malignancies.

cell biology↗

bioRxiv2017

Structural and functional MRI from a cross-sectional Southwest University Adult lifespan Dataset (SALD)

Recently, the field of developmental neuroscience has aimed to uncover the developmental trajectory of the human brain and understand the changes that occur as a function of aging. Here we present an adult lifespan dataset of functional magnetic resonance imaging (fMRI) data including structural MRI and resting-state functional MRI. 494 healthy adults (age range: 19-80 years; Males=187) were recruited and completed two multi-modal MRI scan sessions in the Brain Imaging Central of Southwest University, Chongqing, China. The goals of the dataset are to give researchers the opportunity to map the developmental trajectory of structural and functional changes of human brain and to replicate previous findings.

neuroscience↗

bioRxiv2017

N6-Methyladenine DNA Modification in Human Genome

DNA N6-methyladenine (6mA) modification is the most prevalent DNA modification in prokaryotes, but whether it exists in human cells and whether it plays a role in human diseases remain enigmatic. Here, we showed that 6mA is extensively present in human genome, and we cataloged 881,240 6mA sites accounting for [~]0.051% of the total adenines. [G/C]AGG[C/T] was the most significantly associated motif with 6mA modification. 6mA sites were enriched in the coding regions and mark actively transcribed genes in human cells. We further found that DNA N6-methyladenine and N6-demethyladenine modification in human genome were mediated by methyltransferase N6AMT1 and demethylase ALKBH1, respectively. The abundance of 6mA was significantly lower in cancers, accompaning with decreased N6AMT1 and increased ALKBH1 levels, and down-regulation of 6mA modification levels promoted tumorigenesis. Collectively, our results demonstrate that DNA 6mA modification is extensively present in human cells and the decrease of genomic DNA 6mA promotes human tumorigenesis.

genomics↗

bioRxiv2017

Bioengineered intestinal muscularis complexes with long-term spontaneous and periodic contractions

Although critical for studies of gut motility and intestinal regeneration, the in vitro culture of intestinal muscularis with peristaltic function remains a significant challenge. Periodic contractions of intestinal muscularis result from the coordinated activity of smooth muscle cells (SMC), the enteric nervous system (ENS), and interstitial cells of Cajal (ICC). Reproducing this activity requires the preservation of all these cells in one system. Here we report the first serum-free culture methodology that consistently maintains spontaneous and periodic contractions of murine and human intestinal muscularis cells for months. In this system, SMC expressed the mature marker myosin heavy chain, and multipolar/dipolar ICC, uniaxonal/multipolar neurons and glial cells were present. Furthermore, drugs affecting ENS, ICC or SMC altered the contractions. Combining this method with scaffolds, contracting cell sheets were formed with organized architecture. With the addition of intestinal epithelial cells, this platform enabled at least 9 types of cells from mucosa and muscularis to coexist and function. The method constitutes a powerful tool for mechanistic studies of gut motility disorders and the regeneration of full-thickness engineered intestine.\n\nIn the small intestine, the mucosa processes partially digested food and absorbs nutrients while the muscularis actuates the peristaltic flow to transport luminal content aborally. Gut motility is central to its digestive and absorptive function. The intestinal muscularis contains various types of cells: of these, smooth muscle cells, the enteric nervous system (ENS)1,2, and the pacemaker interstitial cells of Cajal (ICC)3 are three important players involved in the development of gut motility. Recent studies on intestinal tissue engineering have highlighted the importance of regenerating the functional intestinal muscularis4-9. A variety of systems derived from different cell sources, including pluripotent stem cells (PSC)4-6, embryonic stem cells (ESC)7 and primary tissue8,9, have been established to accomplish this goal and different contractile activities were developed in these systems. Notably, spontaneous contractions have been generated in culture systems that contained both ICC and smooth muscle cells4,6,10-13. In addition, electrical-induced neurogenic contractions were also successfully produced4,5,8 when ENS was introduced into culture. In one of the most recent studies, both spontaneous contractions and electrical-induced neurogenic contractions were developed in a PSC-based culture system4.

bioengineering↗

bioRxiv2017

Draft genome of the Reindeer (Rangifer tarandus)

AbstractO_ST_ABSBackgroundC_ST_ABSReindeer (Rangifer tarandus) is the only fully domesticated species in the Cervidae family, and is the only cervid with a circumpolar distribution. Unlike all other cervids, female reindeer regularly grow cranial appendages (antlers, the defining characteristics of cervids), as well as males. Moreover, reindeer milk contains more protein and less lactose than bovids milk. A high quality reference genome of this specie will assist efforts to elucidate these and other important features in the reindeer.\n\nFindingsWe obtained 723.2 Gb (Gigabase) of raw reads by an Illumina Hiseq 4000 platform, and a 2.64 Gb final assembly, representing 95.7% of the estimated genome (2.76 Gb according to k-mer analysis), including 92.6% of expected genes according to BUSCO analysis. The contig N50 and scaffold N50 sizes were 89.7 kilo base (kb) and 0.94 mega base (Mb), respectively. We annotated 21,555 protein-coding genes and 1.07 Gb of repetitive sequences by de novo and homology-based prediction. Homology-based searches detected 159 rRNA, 547 miRNA, 1,339 snRNA and 863 tRNA sequences in the genome of R. tarandus. The divergence time between R. tarandus, and ancestors of Bos taurus and Capra hircus, is estimated to be 29.55 million years ago (Mya).\n\nConclusionsOur results provide the first high-quality reference genome for the reindeer, and a valuable resource for studying evolution, domestication and other unusual characteristics of the reindeer.

genomics↗

bioRxiv2017

Positional effects revealed in Illumina Methylation Array and the impact on analysis

With the evolution of rapid epigenetic research, Illumina Infinium HumanMethylation BeadChips have been widely used to study DNA methylation. However, in evaluating the accuracy of this method, we found that the commonly used Illumina HumanMethylation BeadChips are substantially affected by positional effects; the DNA samples location in a chip affects the measured methylation levels. We analyzed three HumanMethylation450 and three HumanMethylation27 datasets by using four methods to prove the existence of positional effects. Three datasets were analyzed further for technical replicate analysis or differential methylation CpG sites analysis. The pre- and post-correction comparisons indicate that the positional effects could alter the measured methylation values and downstream analysis results. Nevertheless, ComBat, linear regression and functional normalization could all be used to minimize such artifact. We recommend performing ComBat to correct positional effects followed by the correction of batch effects in data preprocessing as this procedure slightly outperforms the others. In addition, randomizing the sample placement should be a critical laboratory practice for using such experimental platforms. Code for our method is freely available at: https://github.com/ChuanJ/posibatch.

bioinformatics↗

bioRxiv2017

Accuracy, Reproducibility And Bias Of Next Generation Sequencing For Quantitative Small RNA Profiling: A Multiple Protocol Study Across Multiple Laboratories

Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.

genomics↗

bioRxiv2017

Reverse Engineering of Trascriptional Networks Uncovers Candidate Master Regulators Governing Neuropathology of Schizophrenia

Tissue-specific reverse engineering of transcriptional networks has uncovered master regulators (MRs) of cellular networks in various cancers, yet the application of this method to neuropsychiatric disorders is largely unexplored. Here, using RNA-Seq data on postmortem dorsolateral prefrontal cortex (DLPFC) from schizophrenia (SCZ) patients and control subjects, we deconvolved the transcriptional network to identify MRs that mediate expression of a large body of target genes. Together with an independent RNA-Seq data on cultured cells derived from olfactory neuroepithelium, we identified TCF4, a leading SCZ risk locus implicated by genome-wide association studies, as one of the top candidate MRs that may be potentially dysregulated in SCZ. We validated the dysregulated TCF4-related transcriptional network through examining the transcription factor binding footprints inferred from human induced pluripotent stem cell (hiPSC)-derived neuronal ATAC-Seq data, as well as direct binding sites obtained from ChIP-seq data in SH-SY5Y cells. The predicted TCF4 transcriptional targets were enriched for genes showing transcriptomic changes upon knockdown of TCF4 in hiPSC-derived neural progenitor cells (NPC) and glutamatergic neurons (Glut_N), based on observations from three separate cell lines. The altered TCF4 gene network perturbations in NPC, as compared to that in Glut_N, was more similar to the expression differences in the TCF4 gene network observed in the DLPFC of individuals with SCZ. Moreover, TCF4-associated gene expression changes in NPC were more enriched than Glut_N for pathways involved in neuronal activity, genome-wide significant SCZ risk genes, and SCZ-associated de novo mutations. Our results suggest that TCF4 may potentially serve as a MR of a gene network that confers susceptibility to SCZ at early stage of neurodevelopment, highlighting the importance of network dysregulation involving core genes and many hundreds of peripheral genes in conferring susceptibility to neuropsychiatric diseases.

neuroscience↗

bioRxiv2017

Rapid Whole Brain Imaging Of Neural Activities In Freely Behaving Larval Zebrafish

The internal brain dynamics that link sensation and action are arguably better studied during natural animal behaviors. Here we report on a novel volume imaging and 3D tracking technique that monitors whole brain neural activity in freely swimming larval zebrafish (Danio rerio). We demonstrated the capability of our system through functional imaging of neural activity during visually evoked and prey capture behaviors in larval zebrafish.

neuroscience↗

bioRxiv2017

The Calcineurin-FoxO-MuRF1 Signaling Pathway Regulates Myofibril Integrity in Cardiomyocytes

Altered Ca2+ handling is often present in diseased hearts undergoing structural remodeling and functional deterioration. The influences of Ca2+ signaling on cardiac function have been examined extensively, but whether Ca2+ directly regulates sarcomere structure has remained elusive. Using a mutant zebrafish model lacking NCX1 activity in the heart, we explored the impacts of impaired Ca2+ homeostasis on myofibril integrity. Gene expression profiling analysis revealed that the E3 ubiquitin ligase MuRF1 is upregulated in ncx1-deficient hearts. Intriguingly, knocking down MuRF1 activity or inhibiting proteasome activity preserved myofibril integrity in ncx1 deficient hearts, revealing a MuRF1-mediated proteasome degradation mechanism that is activated in response to abnormal Ca2+ homeostasis. Furthermore, we detected an accumulation of the MuRF1 regulator FoxO in the nuclei of ncx1-deficient cardiomyocytes. Overexpression of FoxO in wild type cardiomyocytes induced MuRF1 expression and caused myofibril disarray, whereas inhibiting Calcineurin activity attenuated FoxO-mediated MuRF1 expression and protected sarcomeres from degradation in ncx1-deficient hearts. Together, our findings reveal a novel mechanism by which Ca2+ overload disrupts the myofibril integrity in heart muscle cells by activating a Calcineurin-FoxO-MuRF1-proteosome signaling pathway.

cell biology↗

bioRxiv2017

HadoopCNV: A Dynamic Programming Imputation Algorithm To Detect Copy Number Variants From Sequencing Data

BACKGROUNDWhole-genome sequencing (WGS) data may be used to identify copy number variations (CNVs). Existing CNV detection methods mostly rely on read depth or alignment characteristics (paired-end distance and split reads) to infer gains/losses, while neglecting allelic intensity ratios and cannot quantify copy numbers. Additionally, most CNV callers are not scalable to handle a large number of WGS samples.\n\nMETHODSTo facilitate large-scale and rapid CNV detection from WGS data, we developed a Dynamic Programming Imputation (DPI) based algorithm called HadoopCNV, which infers copy number changes through both allelic frequency and read depth information. Our implementation is built on the Hadoop framework, enabling multiple compute nodes to work in parallel.\n\nRESULTSCompared to two widely used tools - CNVnator and LUMPY, HadoopCNV has similar or better performance on both simulated data sets and real data on the NA12878 individual. Additionally, analysis on a 10-member pedigree showed that HadoopCNV has a Mendelian precision that is similar or better than other tools. Furthermore, HadoopCNV can accurately infer loss of heterozygosity (LOH), while other tools cannot. HadoopCNV requires only 1.6 hours for a human genome with 30X coverage, on a 32-node cluster, with a linear relationship between speed improvement and the number of nodes. We further developed a method to combine HadoopCNV and LUMPY result, and demonstrated that the combination resulted in better performance than any individual tools.\n\nCONCLUSIONSThe combination of high-resolution, allele-specific read depth from WGS data and Hadoop framework can result in efficient and accurate detection of CNVs.

bioinformatics↗

bioRxiv2016

Genetic footprint of population fragmentation and contemporary collapse in a freshwater cetacean

Understanding demographic trends and patterns of gene flow in an endangered species is crucial for devising conservation strategies. Here, we examined the extent of population structure and recent evolution of the critically endangered Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis). By analysing genetic variation at the mitochondrial and nuclear microsatellite loci for 148 individuals, we identified three populations along the Yangtze River, each one connected to a group of admixed ancestry. Each population displayed extremely low genetic diversity, consistent with extremely small effective size ([≤]92 individuals). Habitat degradation and distribution gaps correlated with highly asymmetric gene-flow that was inefficient in maintaining connectivity between populations. Genetic inferences of historical demography revealed that the populations in the Yangtze descended from a small number of founders colonizing the river from the sea during the last Ice Age. The colonization was followed by a rapid population split during the last millennium predating the Chinese Modern Economy Development. However, genetic diversity showed a clear footprint of population contraction over the last 50 years leaving only ~2% of the pre-collapsed size, consistent with the population collapses reported from field studies. This genetic perspective provides background information for devising mitigation strategies to prevent this species from extinction.

evolutionary biology↗

bioRxiv2016

Evaluation on Efficient Detection of Structural Variants at Low Coverage by Long-Read Sequencing

BackgroundStructural variants (SVs) in human genomes are implicated in a variety of human diseases. Long-read sequencing delivers much longer read lengths than short-read sequencing and may greatly improve SV detection. However, due to the relatively high cost of long-read sequencing, it is unclear what coverage is needed and how to optimally use the aligners and SV callers.\n\nResultsIn this study, we developed NextSV, a meta-caller to perform SV calling from low coverage long-read sequencing data. NextSV integrates three aligners and three SV callers and generates two integrated call sets (sensitive/stringent) for different analysis purposes. We evaluated SV calling performance of NextSV under different PacBio coverages on two personal genomes, NA12878 and HX1. Our results showed that, compared with running any single SV caller, NextSV stringent call set had higher precision and balanced accuracy (F1 score) while NextSV sensitive call set had a higher recall. At 10X coverage, the recall of NextSV sensitive call set was 93.5% to 94.1% for deletions and 87.9% to 93.2% for insertions, indicating that ~10X coverage might be an optimal coverage to use in practice, considering the balance between the sequencing costs and the recall rates. We further evaluated the Mendelian errors on an Ashkenazi Jewish trio dataset.\n\nConclusionsOur results provide useful guidelines for SV detection from low coverage whole-genome PacBio data and we expect that NextSV will facilitate the analysis of SVs on long-read sequencing data.

genomics↗