Biology subjects

Tang, S.

Publications and source records attributed to Tang, S..

171 records · Page 10Linked to original sources

bioRxiv2018

Convolutional neural network models of V1 responses to complex patterns

In this study, we evaluated the convolutional neural network (CNN) method for modeling V1 neurons of awake macaque monkeys in response to a large set of complex pattern stimuli. CNN models outperformed all the other baseline models, such as Gabor-based standard models for V1 cells and various variants of generalized linear models. We then systematically dissected different components of the CNN and found two key factors that made CNNs outperform other models: thresholding nonlinearity and convolution. In addition, we fitted our data using a pre-trained deep CNN via transfer learning. The deep CNNs higher layers, which encode more complex patterns, outperformed lower ones, and this result was consistent with our earlier work on the complexity of V1 neural code. Our study systematically evaluates the relative merits of different CNN components in the context of V1 neuron modeling.

neuroscience↗

bioRxiv2018

N-hydroxy-pipecolic acid is a mobile signal that induces systemic disease resistance in Arabidopsis

Systemic acquired resistance (SAR) is a global response in plants induced at the site of infection that leads to long-lasting and broad-spectrum disease resistance at distal, uninfected tissues. Despite the importance of this priming mechanism, the identity of the mobile defense signal that moves systemically throughout plants to initiate SAR has remained elusive. In this paper, we describe a new metabolite, N-hydroxy-pipecolic acid (N-OH-Pip), and provide evidence that this molecule is a mobile signal that plays a central role in initiating SAR signal transduction in Arabidopsis thaliana. We demonstrate that FLAVIN-DEPENDENT MONOOXYGENASE 1 (FMO1), a key regulator of SAR-associated defense priming, can synthesize N-OH-Pip from pipecolic acid in planta, and exogenously applied N-OH-PIP moves systemically in Arabidopsis and can rescue the SAR-deficiency of fmo1 mutants. We also demonstrate that N-OH-Pip treatment causes systemic changes in the expression of pathogenesis-related genes and metabolic pathways throughout the plant, and enhances resistance to a bacterial pathogen. This work provides new insight into the chemical nature of a mobile signal for SAR and also suggests that the N-OH-Pip pathway is a promising target for metabolic engineering to enhance disease resistance.

plant biology↗

bioRxiv2018

Long-term all-optical interrogation of cortical neurons in awake-behaving non-human primates

Whereas optogenetic techniques have proven successful in their ability to manipulate neuronal populations in species ranging from insects to rodents--with high spatial and temporal fidelity--significant obstacles remain in their application to non-human primates (NHPs). Robust optogenetics-activated behavior and long-term noninvasive monitoring of target neurons, have been challenging in NHPs. Here we present a method for all-optical interrogation (AOI), integrating optical stimulation and simultaneous two-photon imaging of neuronal populations in the primary visual cortex (V1) of awake rhesus macaques. A red-shifted channel-rhodopsin transgene (C1V1) and genetically-encoded calcium indicators (GCaMP5 or GCaMP6s) were delivered by AAVs, and subsequently expressed in V1 neuronal populations for months with high stability. We achieved optogenetic stimulation using both single-photon (1P) activation of neuronal populations and two-photon (2P) activation of single-cells, while simultaneously recording 2P calcium imaging in awake monkeys. Optogenetic manipulations of V1 neuronal populations produced reliable artificial visual percepts. Together, our advances show the feasibility of precise and stable all-optical interrogation of cortical neurons in awake NHPs, which may facilitate broad applications in high-level cognition and pre-clinical testing studies.

neuroscience↗

bioRxiv2018

A catalog of microbial genes from the bovine rumen reveals the determinants of herbivory

BackgroundThe rumen microbiota provides essential services to its host and, through its role in ruminant production, contributes to human nutrition and food security. A thorough knowledge of the genetic potential of rumen microbes will provide opportunities for improving the sustainability of ruminant production systems. The availability of gene reference catalogs from gut microbiomes has advanced the understanding of the role of the microbiota in health and disease in humans and other mammals. In this work, we established a catalog of reference prokaryote genes from the bovine rumen.\n\nResultsUsing deep metagenome sequencing we identified 13,825,880 non-redundant prokaryote genes from the bovine rumen. Compared to human, pig and mouse gut metagenome catalogs, the rumen is larger and richer in functions and microbial species associated with the degradation of plant cell wall material and production of methane. Genes encoding enzymes catalyzing the breakdown of plant polysaccharides showed a particularly high richness that is otherwise impossible to infer from available genomes or shallow metagenomics sequencing. The catalog expands by several folds the dataset of carbohydrate-degrading enzymes described in the rumen. Using an independent dataset from a group of 77 cattle fed 4 common dietary regimes, we found that only <0.1% of genes were shared by all animals, which contrast with a large overlap for functions, i.e. 63% for KEGG functions. Different diets induced differences in the relative abundance rather than the presence or absence of genes explaining the great adaptability of cattle to rapidly adjust to dietary changes.\n\nConclusionsThese data bring new insights into functions, carbohydrate-degrading enzymes and microbes of the rumen that is complementing the available information on microbial genomes. The catalog is a significant biological resource enabling deeper understanding of phenotypes and biological processes and will be expanded as new data is made available.

microbiology↗

bioRxiv2018

Large-scale two-photon imaging revealed super-sparse population codes in V1 superficial layer of awake monkeys

Efficient coding has been proposed as a general principle for the sensory systems. The efficient coding hypothesis predicts that neuronal population responses should be sparse, but limited by the measurement techniques, the precise estimates of the population sparseness of visual cortical neurons are still uncertain. Here, we employed large-scale two-photon calcium imaging to examine the neuronal population activities in V1 superficial layers of awake macaques in response to a large set of natural images. We found that only 0.5% of these neurons on average responded strongly to any given natural image with response strength above half of their individual peak responses, which is more than tenfold sparse over those reported by early studies. We further showed that these sparse population activities contain sufficient information for discriminating images with high accuracy. This study provided the first accurate measure of sparseness in V1 neuronal population responses, which support super-sparse neural codes in primates.

neuroscience↗

bioRxiv2017

Improved Prokaryotic Gene Prediction Yields Insights into Transcription and Translation Mechanisms on Whole Genome Scale

In a conventional view of the prokaryotic genome organization promoters precede operons and RBS sites with Shine-Dalgarno consensus precede genes. However, recent experimental research suggesting a more diverse view motivated us to develop an algorithm with improved gene-finding accuracy. We describe GeneMarkS-2, an ab initio algorithm that uses a model derived by self-training for finding species-specific (native) genes, along with an array of pre-computed heuristic models designed to identify harder-to-detect genes (likely horizontally transferred). Importantly, we designed GeneMarkS-2 to identify several types of distinct sequence patterns (signals) involved in gene expression control, among them the patterns characteristic for leaderless transcription as well as non-canonical RBS patterns. To assess the accuracy of GeneMarkS-2 we used genes validated by COG annotation, proteomics experiments, and N-terminal protein sequencing. We observed that GeneMarkS-2 performed better on average in all accuracy measures when compared with the current state-of-the-art gene prediction tools. Furthermore, the screening of [~]5,000 representative prokaryotic genomes made by GeneMarkS-2 predicted frequent leaderless transcription in both archaea and bacteria. We also observed that the RBS sites in some species with leadered transcription did not necessarily exhibit the Shine-Dalgarno consensus. The modeling of different types of sequence motifs regulating gene expression prompted a division of prokaryotic genomes into five categories with distinct sequence patterns around the gene starts.\n\n[Supplemental material is available for this article].

genomics↗

bioRxiv2017

neoantigenR: An annotation based pipeline for tumor neoantigen identification from sequencing data

Studies indicate that more than 90% of human genes are alternatively spliced, suggesting the complexity of the transcriptome assembly and analysis. The splicing process is often disrupted, resulting in both functional and non-functional end-products (Sveen et al. 2016) in many cancers. Harnessing the immune system to fight against malignant cancers carrying aberrantly mutated or spliced products is becoming a promising approach to cancer therapy. Advances in immune checkpoint blockade have elicited adaptive immune responses with promising clinical responses to treatments against human malignancies (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Emerging data suggest that recognition of patient-specific mutation-associated cancer antigens (i.e. from alternative splicing isoforms) may allow scientists to dissect the immune response in the activity of clinical immunotherapies (Schumacher and Schreiber 2015). The advent of high-throughput sequencing technology has provided a comprehensive view of both splicing aberrations and somatic mutations across a range of human malignancies, allowing for a deeper understanding of the interplay of various disease mechanisms.\n\nMeanwhile, studies show that the number of transcript isoforms reported to date may be limited by the short-read sequencing due to the inherit limitation of transcriptome reconstruction algorithms, whereas long-read sequencing is able to significantly improve the detection of alternative splicing variants since there is no need to assemble full-length transcripts from short reads. The analysis of these high-throughput long-read sequencing data may permit a systematic view of tumor specific peptide epitopes (also known as neoantigens) that could serve as targets for immunotherapy (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017).\n\nCurrently, there is no software pipeline available that can efficiently produce mutation-associated cancer antigens from raw high-throughput sequencing data on patient tumor DNA (The Problem with Neoantigen Prediction 2017). In addressing this issue, we introduce a R package that allows the discoveries of peptide epitope candidates, which are the tumor-specific peptide fragments containing potential functional neoantigens. These peptide epitopes consist of structure variants including insertion, deletions, alternative sequences, and peptides from nonsynonymous mutations. Analysis of these precursor candidates with widely used tools such as netMHC allows for the accurate in-silico prediction of neoantigens. The pipeline named neoantigeR is currently hosted in https://github.com/ICBI/neoantigeR.

bioinformatics↗

bioRxiv2017

Gene family information facilitates variant interpretation and identification of disease-associated genes

Differentiating risk-conferring from benign missense variants, and therefore optimal calculation of gene-variant burden, represent a major challenge in particular for rare and genetic heterogeneous disorders. While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes are paralogs and belong to gene families. It has not been thoroughly investigated how gene family information can be utilized for disease gene discovery and variant interpretation. We developed a paralog conservation score to empirically evaluate whether paralog conserved or nonconserved sites of in-human paralogs are important for protein function. Using this score, we demonstrate that disease-associated missense variants are significantly enriched at paralog conserved sites across all disease groups and disease inheritance models tested. Next, we assessed whether gene family information could assist in discovering novel disease-associated genes. We subsequently developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in more than 10k neurodevelopmental disorder patients. 33 gene family enriched genes represent novel candidate genes which are brain expressed and variant constrained in neurodevelopmental disorders.

genetics↗

bioRxiv2017

The Spectrum Of De Novo Variants In Neurodevelopmental Disorders With Epilepsy

Epilepsy is a frequent feature of neurodevelopmental disorders (NDD) but little is known about genetic differences between NDD with and without epilepsy. We analyzed de novo variants (DNV) in 6753 parent-offspring trios ascertained for different NDD. In the subset of 1942 individuals with NDD with epilepsy, we identified 33 genes with a significant excess of DNV, of which SNAP25 and GABRB2 had previously only limited evidence for disease association. Joint analysis of all individuals with NDD also implicated CACNA1E as a novel disease gene. Comparing NDD with and without epilepsy, we found missense DNV, DNV in specific genes, age of recruitment and severity of intellectual disability to be associated with epilepsy. We further demonstrate to what extent our results impact current genetic testing as well as treatment, emphasizing the benefit of accurate genetic diagnosis in NDD with epilepsy.

genetics↗