Biology subjects

Lin, Z.

Publications and source records attributed to Lin, Z..

270 records · Page 15Linked to original sources

bioRxiv2019

Decoding WW Domain Tandem-mediated Target Recognitions in Tissue Growth and Cell Polarity

WW domain tandem-containing proteins such as KIBRA, YAP, and MAGI play critical roles in cell growth and polarity via binding to and positioning target proteins in specific subcellular regions. An immense disparity exists between promiscuity of WW domain-mediated target bindings and specific roles of WW domain scaffold proteins in cell growth regulation. Here, we discovered that WW domain tandems of KIBRA and MAGI, but not YAP, bind to specific target proteins with extremely high affinity and exquisite specificity. Via systematic structural biology and biochemistry approaches, we decoded the target binding rules of WW domain tandems from cell growth regulatory proteins and uncovered a list of previously unknown WW tandem binding proteins such as {beta}-Dystroglycan, JCAD, and PTPN21. The WW tandem-mediated target recognition mechanisms elucidated here can guide functional studies of WW domain proteins in cell growth and polarity as well as in other cellular processes including neuronal synaptic signaling.

biophysics↗

bioRxiv2019

Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA

Chemical modification of transcripts with 5 caps occurs in all organisms. Here we report a systems-level mass spectrometry-based technique, CapQuant, for quantitative analysis of the cap epitranscriptome in any organism. The method was piloted with 21 canonical caps - m7GpppN, m7GpppNm, GpppN, GpppNm, and m2,2,7GpppG - and 5 \"metabolite\" caps - NAD, FAD, UDP-Glc, UDP-GlcNAc, and dpCoA. Applying CapQuant to RNA from purified dengue virus, Escherichia coli, yeast, mice, and humans, we discovered four new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and surprisingly high proportions of caps lacking 2-O-methylation, such as m7Gpppm6A in mammals and m7GpppA in dengue virus, and we did not detect cap m1A/m1Am in humans. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps. The mystery around cap m1A/m1Am analysis remains unresolved.

systems biology↗

bioRxiv2019

Label-retention expansion microscopy

Expansion microscopy (ExM) increases the effective resolving power of any microscope by expanding the sample with swellable hydrogel. Since its invention, ExM has been successfully applied to a wide range of cell, tissue and animal samples. Still, fluorescence signal loss during polymerization and digestion limits molecular-scale imaging using ExM. Here we report the development of label-retention ExM (LR-ExM) with a set of trifunctional anchors that not only prevent signal loss but also enable high-efficiency labeling using SNAP and CLIP tags. We have demonstrated multicolor LR-ExM for a variety of subcellular structures. Combining LR-ExM with super-resolution Stochastic Optical Reconstruction Microscopy (STORM), we have achieved molecular resolution in the visualization of polyhedral lattice of clathrin-coated pits in situ.

bioengineering↗

bioRxiv2019

Massively parallel single-cell B-cell receptor sequencing enables rapid discovery of diverse antigen-reactive antibodies

Using high-throughput single-cell B-cell receptor sequencing (scBCR-seq) we obtained accurately paired full-length heavy- and light-chain variable domains from thousands of individual B cells in a massively parallel fashion. We sequenced more than 250,000 B cells from rat, mouse and human repertoires to characterize their lineages and expansion. In addition, we immunized rats with chicken ovalbumin and profiled antigen-reactive B cells from lymph nodes of immunized animals. The scBCR-seq data recovered 81% (n = 56/69) of B-cell lineages identified from hybridomas generated from the same set of B cells that were subjected to scBCR-seq. Importantly, scBCR-seq identified an additional 710 candidate lineages that were not recovered as hybridomas. We synthesized, expressed and tested 93 clones from the identified lineages and found that 99% (n = 92/93) of the clones were antigen-reactive. Our results establish scBCR-seq as a powerful tool for antibody discovery.

immunology↗

bioRxiv2019

Neuronal hyperexcitability drives TDP43 pathology by upregulating shortened TDP43 protein isoforms

Cortical hyperexcitability and mislocalization of the RNA-binding protein TDP43 are highly-conserved features in amyotrophic lateral sclerosis (ALS). Nevertheless, the relationship between these phenomena remains poorly defined. Here, we showed that hyperexcitability recapitulates TDP43 pathology by upregulating shortened (s) TDP43 splice isoforms. These truncated isoforms accumulated in the cytoplasm and formed insoluble inclusions that sequestered full-length TDP43 via preserved N-terminal interactions. Consistent with these findings, sTDP43 overexpression was toxic to mammalian neurons, suggesting neurodegeneration arising from complementary gain- and loss-of-function mechanisms. In humans and mice, sTDP43 transcripts were enriched in vulnerable motor neurons, and we observed a striking accumulation of sTDP43 within neurons and glia of ALS patients. Collectively, these studies uncover a pathogenic role for alternative TDP43 isoforms in ALS, and implicate sTDP43 as a key contributor to the susceptibility of motor neurons in this disorder.

neuroscience↗

bioRxiv2019

EPIC: MHC-I epitope prediction integrating mass spectrometry derived motifs and tissue-specific expression profiles

BackgroundAccurate prediction of epitopes presented by human leukocyte antigen (HLA) is crucial for personalized cancer immunotherapies targeting T cell epitopes. Mass spectrometry (MS) profiling of eluted HLA ligands, which provides high-throughput measurements of HLA associated peptides in vivo, can be used to faithfully model the presentation of epitopes on the cell surface. In addition, gene expression profiles measured by RNA-seq data in a specific cell/tissue type can significantly improve the performance of epitope presentation prediction. However, although large amount of high-quality MS data of HLA-bound peptides is being generated in recent years, few provide matching RNA-seq data, which makes incorporating gene expression into epitope prediction difficult. MethodsWe collected publicly available HLA peptidome and matching RNA-seq data of 34 cell lines derived from various sources. We built position score specific matrixes (PSSMs) for 21 HLA-I alleles based on these MS data, then used logistic regression (LR) to model the relationship among PSSM score, gene expression and peptide length to predict whether a peptide could be presented in each of the cell line. We further built a universal LR model, termed Epitope Presentation Integrated Prediction (EPIP), based on more than 180,000 unique HLA ligands collected from public sources and ~3,000 HLA ligands generated by ourselves, to predict epitope presentation for 66 common HLA-I alleles. ResultsWhen evaluating EPIP on large, independent HLA eluted ligand datasets, it performed substantially better than other popular methods, including MixMHCpred (v2.0), NetMHCpan (v4.0), and MHCflurry (v1.2.2), with an average 0.1% positive predictive value (PPV) of 52.01%, compared to 37.24%, 36.96%, 24.90% and 23.76% achieved by MixMHCpred, NetMHCpan-4.0 (EL), NetMHCpan-4.0 (BA) and MHCflurry, respectively. It is also comparable to EDGE, a recent deep learning-based model that is not publicly available, on predicting epitope presentation and selecting immunogenic cancer neoantigens. However, the simplicity and flexibility of EPIP makes it easier to be applied in diverse situations, and we demonstrated this by generating MS data for the HCC4006 cell line and adding the support of HLA-A*33:03 to EPIP. EPIP is publicly available as a web tool < http://epip.genomics.cn/>. Conclusionswe have developed an easy to use, publicly available epitope prediction tool, EPIP, that incorporates information from both MS and RNA-seq data, and demonstrated its superior performance over existing public methods.

bioinformatics↗

bioRxiv2019

Loss of tau and Fyn reduces compensatory effects of MAP2 for tau and reveals a Fyn-independent effect of tau on glutamate-induced Ca2+ response

Microtubule-associated protein tau associates with Src family tyrosine kinase Fyn. A tau-Fyn double knockout (DKO) mouse was generated to investigate the role of the complex. DKO mice resembled Fyn KO in cognitive tasks and resembled tau KO mice in motor tasks and protection from pentylenetetrazole-induced seizures. In Ca2+ response, Fyn KO was decreased relative to WT and DKO had a greater reduction relative to Fyn KO, suggesting that tau may have a Fyn-independent role. Since tau KO resembled WT in its Ca2+ response, we investigated whether MAP2 served to compensate for tau, since its level was increased in tau KO but decreased in DKO mice. We found that like tau, MAP2 increased Fyn activity. Moreover, tau KO neurons had increased density of dendritic MAP2-Fyn complexes relative to WT neurons. Therefore, we hypothesize that in the tau KO, the absence of tau would be compensated by MAP2, especially in the dendrites, where tau-Fyn complexes are of critical importance. In the DKO, decreased levels of MAP2 made compensation more difficult, thus revealing the effect of tau in the Ca2+ response.\n\nSummary StatementThe downstream effect of the interaction between microtubule-associated protein tau and Src family non-receptor tyrosine kinase Fyn was investigated with a tau/Fyn double KO mouse. We demonstrate that tau has a Fyn-independent role in glutamate-induced calcium response and that MAP2 can compensate for tau in interacting with Fyn in dendrites.

neuroscience↗

bioRxiv2019

A Sequence Learning Model for Decision Making in the Brain

The brain makes flexible and adaptive responses in the complicated and ever-changing environment for the organisms survival. To achieve this, the brain needs to choose appropriate actions flexibly in response to sensory inputs. Moreover, the brain also has to understand how its actions affect future sensory inputs and what reward outcomes should be expected, and adapts its behavior based on the actual outcomes. A modeling approach that takes into account of the combined contingencies between sensory inputs, actions, and reward outcomes may be the key to understanding the underlying neural computation. Here, we train a recurrent neural network model based on sequence learning to predict future events based on the past event sequences that combine sensory, action, and reward events. We use four exemplary tasks that have been used in previous animal and human experiments to study different aspects of decision making and learning. We first show that the model reproduces the animals choice and reaction time pattern in a probabilistic reasoning task, and its units activities mimics the classical findings of the ramping pattern of the parietal neurons that reflects the evidence accumulation process during decision making. We further demonstrate that the model carries out Bayesian inference and may support meta-cognition such as confidence with additional tasks. Finally, we show how the network model achieves adaptive behavior with an approach distinct from reinforcement learning. Our work pieces together many experimental findings in decision making and reinforcement learning and provides a unified framework for the flexible and adaptive behavior of the brain.

neuroscience↗

bioRxiv2019

YeasTSS: An Integrative Web Database of Yeast Transcription Start Sites

The transcription initiation landscape of eukaryotic genes is complex and highly dynamic. In eukaryotes, genes can generate multiple transcript variants that differ in 5 boundaries due to usages of alternative transcription start sites (TSSs), and the abundance of transcript isoforms are highly variable. Due to a large number and complexity of the TSSs, it is not feasible to depict details of transcript initiation landscape of all genes using text-format genome annotation files. Therefore, it is necessary to provide data visualization of TSSs to represent quantitative TSS maps and the core promoters. In addition, the selection and activity of TSSs are influenced by various factors, such as transcription factors, chromatin remodeling, and histone modifications. Thus, integration and visualization of functional genomic data related to these features could provide a better understanding of the gene promoter architecture and regulatory mechanism of transcription initiation. Yeast species play important roles for the research and human society, yet no database provides visualization and integration of functional genomic data in yeast. Here, we generated quantitative TSS maps for twelve important yeast species, inferred their core promoters, and built a public database, YeasTSS (www.yeastss.org). YeasTSS was designed as a central portal for visualization and integration of the TSS maps, core promoters and functional genomic data related to transcription initiation in yeast. YeasTSS is expected to benefit the research community and public education for improving genome annotation, studies of promoter structure, regulated control of transcription initiation and inferring gene regulatory network.

bioinformatics↗

bioRxiv2018

A new massively parallel nanoball sequencing platform for whole exome research

BackgroundWhole exome sequencing (WES) has been widely used in human genetics research. BGISEQ-500 is a recently established next-generation sequencing platform. However, the performance of BGISEQ-500 on WES is not well studied. In this study, we evaluated the performance of BGISEQ-500 on WES by side-to-side comparison with Hiseq4000, on wellcharacterized human sample NA12878.\n\nResultsBGISEQ demonstrated similarly high reproducibility as Hiseq for variation detection. Also, the SNPs from BGISEQ data is highly consistent with Hiseq results (concordance 96.5%[~]97%). Variation detection accuracy was subsequently evaluated with data from the genome in a bottle project as the benchmark. Both platforms showed similar sensitivity and precision in SNP detection. While in indel detection, BGISEQ showed slightly higher sensitivity and lower precision. The impact of sequence depth and read length on variation detection accuracy was further analyzed, and showed that variation detection sensitivity still increasing when the sequence depth is larger than 100x, and the impact of read length is minor when using 100x data.\n\nConclusionsThis study suggested that BGISEQ-500 is a qualified sequencing platform for WES.

genomics↗

bioRxiv2018

Pervasive and Dynamic Transcription Initiation in Saccharomyces cerevisiae

Transcription initiation is finely regulated to ensure the proper expression and function of these genes. The regulated transcription initiation in response to various environmental cues in the model organism Saccharomyces cerevisiae has not been systematically investigated. In this study, we generated quantitative maps of transcription start site (TSS) at a single-nucleotide resolution for S. cerevisiae grown in nine different conditions using no-amplification non-tagging Cap analysis of gene expression (nAnT-iCAGE) sequencing. Based on 337 million uniquely mapped CAGE tags, we mapped ~1 million well-supported TSSs, suggesting highly pervasive transcription initiation in the compact genome of yeast. The comprehensive TSS maps allowed us to identify core promoters for ~96% verified protein-coding genes and to revise the predicted translation start codon for 183 genes. We found that 56% of yeast genes have at least two core promoters and alternative usage of different core promoters in a gene is widespread in response to changing environments. More importantly, most core promoter shifts are coupled with differential gene expression, indicating that core promoter shift might play an important role in controlling transcriptional activity of yeast genes. Based on their dynamic activities, we divided yeast core promoters as constitutive core promoters (55%) and inducible core promoters (45%). The two classes of core promoters exhibit distinctive patterns in transcriptional abundance, chromatin structure, promoter shape, and sequence context. In summary, the quantitative TSS maps generated by this study improved the annotation of yeast genome, and revealed a highly pervasive and dynamic nature of transcription initiation in yeast.

genomics↗

bioRxiv2018

Value-based Decision Making Takes Place in the Action Domain in the Prefrontal Cortex

Value-based decision making is a process in which humans or animals maximize their gain by selecting appropriate options and performing the corresponding actions to acquire them. Whether the evaluation process of the options in the brain can be independent from their action contingency has been hotly debated. To address the question, we trained rhesus monkeys to make decisions by integrating evidence and studied whether the integration occurred in the stimulus or the action domain in the brain. After the monkeys learned the task, we recorded both from the orbitofrontal (OFC) and dorsolateral prefrontal (DLPFC) cortices. We found that the OFC neurons encoded the value associated with the single piece of evidence in the stimulus domain. Importantly, the representations of the value in the OFC was transient and the information was not integrated across time for decisions. The integration of evidence was observed only in the DLPFC and only in the action domain. We further used a neural network model to show how the stimulus-to-action transition of value information may be computed in the DLPFC. Our results indicated that the decision making in the brain is computed in the action domain without an intermediate stimulus-based decision stage.

neuroscience↗

bioRxiv2018

The expa1-1 mutant reveals a new biophysical lateral root organogenesis checkpoint

In plants, post-embryonic formation of new organs helps shape the adult organism. This requires the tight regulation of when and where a new organ is formed, and a coordination of the underlying cell divisions. To build a root system, new lateral roots are continuously developing, and this process requires asymmetric cell division in adjacent pericycle cells. Characterization of an expansin a1 (expa1) mutant has revealed a novel checkpoint during lateral root formation. Specifically, a minimal pericycle width was found to be necessary and sufficient to trigger asymmetric pericycle cell divisions during auxin-driven lateral root formation. We conclude that a localized radial expansion of adjacent pericycle cells is required to position the asymmetric cell divisions and generate a core of small daughter cells, which is a prerequisite for lateral root organogenesis.\n\nSIGNFICANCE STATEMENTOrgan formation is an essential process in plants and animals, driven by cell division and cell identity establishment. Root branching, where lateral roots form along the primary root axis, increases the root system and aids capture of water and nutrients. We have discovered that tight control of cell width is necessary to co-ordinate asymmetric cell divisions in cells that give rise to a new lateral root organ. While biomechanical processes have been shown to play a role in plant organogenesis, including lateral root formation, our data give new mechanistic insights into the cell size checkpoint during lateral root initiation.

plant biology↗

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

Unsupervised Clustering And Epigenetic Classification Of Single Cells

Characterizing epigenetic heterogeneity at the cellular level is a critical problem in the modern genomics era. Assays such as single cell ATAC-seq (scATAC-seq) offer an opportunity to interrogate cellular level epigenetic heterogeneity through patterns of variability in open chromatin. However, these assays exhibit technical variability that complicates clear classification and cell type identification in heterogeneous populations. We present scABC, an R package for the unsupervised clustering of single cell epigenetic data, to classify scATAC-seq data and discover regions of open chromatin specific to cell identity.

bioinformatics↗

bioRxiv2017

A Neural Network Framework For The Orbitofrontal Cortex During Model-Based Reinforcement Learning

Reinforcement learning has been widely used in explaining animal behavior. In reinforcement learning, the agent learns the value of the states in the task, collectively constituting the task state space, and use the knowledge to choose actions and acquire desired outcomes. It has been proposed that the orbitofrontal cortex (OFC) encodes the task state space during reinforcement learning. However, it is not well understood how the OFC acquires and stores task state information. Here, we propose a neural network model based on reservoir computing. Reservoir networks exhibit heterogeneous and dynamic activity patterns that are suitable to encode task states. The information can be extracted by a linear readout trained with reinforcement learning. We demonstrate how the network acquires and stores the task structures. The network exhibits reinforcement learning behavior and its aspects resemble experimental findings of the OFC. Our study provides a theoretical explanation of how the OFC may contribute to reinforcement learning and a new approach to understanding the neural mechanism underlying reinforcement learning.

neuroscience↗

bioRxiv2017

Dynamic response to initial stage blindness in visual system development

Sensitive periods and experience-dependent plasticity have become core issues in visual system development. Converging evidence indicates that visual experience is an indispensable factor in establishing mature visual system circuitry during sensitive periods and the visual system exhibits substantial plasticity when facing deprivation. The mechanisms that underlie the environmental regulation of visual system development and plasticity are of great interest but need further exploration. Here, we investigated a unique sample of human infants who experienced initial stage blindness (beginning at birth and lasting 2 to 8 months) before the removal of bilateral cataracts. Retinal thickness, axial length, refractive status, visual grating acuity and genetic integrity were recorded during the preoperative period or at surgery, and then during follow-up. The results showed that the development of the retina is malleable and associated with external environment influences. Our work supported that the retina might play critical roles in the development of the experience-dependent visual system and its malleability might partly contribute to the sensitive period plasticity.\n\nSUMMARY STATEMENTThe follow-up investigation of a group of human infants, who experienced initial stage blindness before the removal of bilateral cataracts, revealed that retinal development is associated with environment influences and its malleability might be a potential basis of plasticity.

developmental biology↗

bioRxiv2017

Novel insights into the molecular heterogeneity of hepatocellularcarcinoma

Hepatocellular carcinoma (HCC) is influenced by numerous factors, which results in diverse genetic, epigenetic and transcriptional scenarios, thus posing obvious challenges for disease management. We scrutinized the molecular heterogeneity of HCC with a multi-omics approach in two small cohorts of resected and explanted livers. Whole-genome transcriptomics was conducted, including polyadenylated transcripts and micro (mi)-RNAs. Copy number variants (CNV) were inferred from whole genome low-pass sequencing data. Fifty-six cancer-related genes were screened using an oncology panel assay. HCC was associated with a dramatic transcriptional deregulation of hundreds of protein-coding genes suggesting downregulation of drugs catabolism, induction of inflammatory responses, and increased cell proliferation in resected livers. Moreover, several long non-coding RNAs and miRNAs not reported previously in the context of HCC were found deregulated. In explanted livers, downregulation of genes involved in energy-producing processes and upregulation of genes aiding in glycolysis were detected. Numerous CNV events were observed, with conspicuous hotspots on chromosomes 1 and 17. Amplifications were more common than deletions, and spanned regions containing genes potentially involved in tumorigenesis. CSF1R, FGFR3, FLT3, NPM1, PDGFRA, PTEN, SMO and TP53 were mutated in all tumors, while other 26 cancer-related genes were mutated with variable penetrance. Our results highlight a remarkable molecular heterogeneity between HCC tumors and reinforce the notion that precision medicine approaches are urgently needed for cancer treatment. We expect that our results will serve as a valuable dataset that will generate hypotheses for us or other researchers to evaluate to ultimately improve our understanding of HCC biology.

cancer biology↗