丽江2.4米望远镜TCS Sequencer程序的设计与开发

介绍了丽江2.4 m望远镜TCS Sequencer程序设计及开发的过程,并且对程序的调试和运行情况进行了总结;同时还介绍了在该程序开发过程中学习到的Linux系统下编程的一些方法和经验。

Rapid and Accurate Sequencing of Enterovirus Genomes Using MinION Nanopore Sequencer

Objective Knowledge of an enterovirus genome sequence is very important in epidemiological investigation to identify transmission patterns and ascertain the extent of an outbreak. The MinION sequencer is increasingly used to sequence various viral pathogens in many clinical situations because of its long reads, portability, real-time accessibility of sequenced data, and very low initial costs. However, information is lacking on MinION sequencing of enterovirus genomes. Methods In this proof-of-concept study using Enterovirus 71 （EV71） and Coxsackievirus A16 （CA16） strains as examples, we established an amplicon-based whole genome sequencing method using MinION. We explored the accuracy, minimum sequencing time, discrimination and high-throughput sequencing ability of MinION, and compared its performance with Sanger sequencing. Results Within the first minute （min） of sequencing, the accuracy of MinION was 98.5% for the single EV71 strain and 94.12%-97.33% for 10 genetically-related CA16 strains. In as little as 14 min, 99% identity was reached for the single EV71 strain, and in 17 min （on average）, 99% identity was achieved for 10 CA16 strains in a single run. Conclusion MinION is suitable for whole genome sequencing of enteroviruses with sufficient accuracy and fine discrimination and has the potential as a fast, reliable and convenient method for routine use.

A complete genome assembly of Glaciecola mesophila sp. nov. sequenced by using BIGIS-4 sequencer system

Using a pyrosequencing-based custom-made sequencer BIGIS-4, we sequenced a Gram-negative bacterium Glaciecola mesophila sp. nov. (Gmn) isolated from marine invertebrate specimens. We generated 152043 sequencing reads with a mean high-quality length of 406 bp, and assembled them using the BIGIS-4 post-processing module. No systematic low-quality data was detected beyond expected homopolymer-derived errors. The assembled Gmn genome is 5144318 bp in length and harbors 4303 annotated genes. A large number of metabolic genes correspond to various nutrients from surface marine invertebrates. Its abundant cold-tolerant and cellular signaling and related genes reveal a fundamental adaptation to low-temperature marine environment.

Perilipin-2 mediates ferroptosis in oligodendrocyte progenitor cells and myelin injury after ischemic stroke

Differentiation of oligodendrocyte progenitor cells into mature myelin-forming oligodendrocytes contributes to remyelination.Failure of remyelination due to oligodendrocyte progenitor cell death can result in severe nerve damage.Ferroptosis is an iron-dependent form of regulated cell death caused by membrane rupture induced by lipid peroxidation,and plays an important role in the pathological process of ischemic stroke.However,there are few studies on oligodendrocyte progenitor cell ferroptosis.We analyzed transcriptome sequencing data from GEO databases and identified a role of ferroptosis in oligodendrocyte progenitor cell death and myelin injury after cerebral ischemia.Bioinformatics analysis suggested that perilipin-2(PLIN2)was involved in oligodendrocyte progenitor cell ferroptosis.PLIN2 is a lipid storage protein and a marker of hypoxia-sensitive lipid droplet accumulation.For further investigation,we established a mouse model of cerebral ischemia/reperfusion.We found significant myelin damage after cerebral ischemia,as well as oligodendrocyte progenitor cell death and increased lipid peroxidation levels around the infarct area.The ferroptosis inhibitor,ferrostatin-1,rescued oligodendrocyte progenitor cell death and subsequent myelin injury.We also found increased PLIN2 levels in the peri-infarct area that co-localized with oligodendrocyte progenitor cells.Plin2 knockdown rescued demyelination and improved neurological deficits.Our findings suggest that targeting PLIN2 to regulate oligodendrocyte progenitor cell ferroptosis may be a potential therapeutic strategy for rescuing myelin damage after cerebral ischemia.

Toward understanding the role of genomic repeat elements in neurodegenerative diseases

Neurodegenerative diseases cause great medical and economic burdens for both patients and society;however, the complex molecular mechanisms thereof are not yet well understood. With the development of high-coverage sequencing technology, researchers have started to notice that genomic repeat regions, previously neglected in search of disease culprits, are active contributors to multiple neurodegenerative diseases. In this review, we describe the association between repeat element variants and multiple degenerative diseases through genome-wide association studies and targeted sequencing. We discuss the identification of disease-relevant repeat element variants, further powered by the advancement of long-read sequencing technologies and their related tools, and summarize recent findings in the molecular mechanisms of repeat element variants in brain degeneration, such as those causing transcriptional silencing or RNA-mediated gain of toxic function. Furthermore, we describe how in silico predictions using innovative computational models, such as deep learning language models, could enhance and accelerate our understanding of the functional impact of repeat element variants. Finally, we discuss future directions to advance current findings for a better understanding of neurodegenerative diseases and the clinical applications of genomic repeat elements.

Mutual regulation of microglia and astrocytes after Gas6 inhibits spinal cord injury

Invasive inflammation and excessive scar formation are the main reasons for the difficulty in repairing nervous tissue after spinal cord injury.Microglia and astrocytes play key roles in the spinal cord injury micro-environment and share a close interaction.However,the mechanisms involved remain unclear.In this study,we found that after spinal cord injury,resting microglia(M0)were polarized into pro-inflammatory phenotypes(MG1 and MG3),while resting astrocytes were polarized into reactive and scar-forming phenotypes.The expression of growth arrest-specific 6(Gas6)and its receptor Axl were significantly down-regulated in microglia and astrocytes after spinal cord injury.In vitro experiments showed that Gas6 had negative effects on the polarization of reactive astrocytes and pro-inflammatory microglia,and even inhibited the cross-regulation between them.We further demonstrated that Gas6 can inhibit the polarization of reactive astrocytes by suppressing the activation of the Yes-associated protein signaling pathway.This,in turn,inhibited the polarization of pro-inflammatory microglia by suppressing the activation of the nuclear factor-κB/p65 and Janus kinase/signal transducer and activator of transcription signaling pathways.In vivo experiments showed that Gas6 inhibited the polarization of pro-inflammatory microglia and reactive astrocytes in the injured spinal cord,thereby promoting tissue repair and motor function recovery.Overall,Gas6 may play a role in the treatment of spinal cord injury.It can inhibit the inflammatory pathway of microglia and polarization of astrocytes,attenuate the interaction between microglia and astrocytes in the inflammatory microenvironment,and thereby alleviate local inflammation and reduce scar formation in the spinal cord.

Spatial transcriptomics combined with single-nucleus RNA sequencing reveals glial cell heterogeneity in the human spinal cord

Glial cells play crucial roles in regulating physiological and pathological functions,including sensation,the response to infection and acute injury,and chronic neurodegenerative disorders.Glial cells include astrocytes,microglia,and oligodendrocytes in the central nervous system,and satellite glial cells and Schwann cells in the peripheral nervous system.Despite the greater understanding of glial cell types and functional heterogeneity achieved through single-cell and single-nucleus RNA sequencing in animal models,few studies have investigated the transcriptomic profiles of glial cells in the human spinal cord.Here,we used high-throughput single-nucleus RNA sequencing and spatial transcriptomics to map the cellular and molecular heterogeneity of astrocytes,microglia,and oligodendrocytes in the human spinal cord.To explore the conservation and divergence across species,we compared these findings with those from mice.In the human spinal cord,astrocytes,microglia,and oligodendrocytes were each divided into six distinct transcriptomic subclusters.In the mouse spinal cord,astrocytes,microglia,and oligodendrocytes were divided into five,four,and five distinct transcriptomic subclusters,respectively.The comparative results revealed substantial heterogeneity in all glial cell types between humans and mice.Additionally,we detected sex differences in gene expression in human spinal cord glial cells.Specifically,in all astrocyte subtypes,the levels of NEAT1 and CHI3L1 were higher in males than in females,whereas the levels of CST3 were lower in males than in females.In all microglial subtypes,all differentially expressed genes were located on the sex chromosomes.In addition to sex-specific gene differences,the levels of MT-ND4,MT2A,MT-ATP6,MT-CO3,MT-ND2,MT-ND3,and MT-CO_(2) in all spinal cord oligodendrocyte subtypes were higher in females than in males.Collectively,the present dataset extensively characterizes glial cell heterogeneity and offers a valuable resource for exploring the cellular basis of spinal cordrelated illnesses,including chronic pain,amyotrophic lateral sclerosis,and multiple sclerosis.

Exosomes originating from neural stem cells undergoing necroptosis participate in cellular communication by inducing TSC2 upregulation of recipient cells following spinal cord injury

We previously demonstrated that inhibiting neural stem cells necroptosis enhances functional recovery after spinal cord injury.While exosomes are recognized as playing a pivotal role in neural stem cells exocrine function,their precise function in spinal cord injury remains unclear.To investigate the role of exosomes generated following neural stem cells necroptosis after spinal cord injury,we conducted singlecell RNA sequencing and validated that neural stem cells originate from ependymal cells and undergo necroptosis in response to spinal cord injury.Subsequently,we established an in vitro necroptosis model using neural stem cells isolated from embryonic mice aged 16-17 days and extracted exosomes.The results showed that necroptosis did not significantly impact the fundamental characteristics or number of exosomes.Transcriptome sequencing of exosomes in necroptosis group identified 108 differentially expressed messenger RNAs,104 long non-coding RNAs,720 circular RNAs,and 14 microRNAs compared with the control group.Construction of a competing endogenous RNA network identified the following hub genes:tuberous sclerosis 2(Tsc2),solute carrier family 16 member 3(Slc16a3),and forkhead box protein P1(Foxp1).Notably,a significant elevation in TSC2 expression was observed in spinal cord tissues following spinal cord injury.TSC2-positive cells were localized around SRY-box transcription factor 2-positive cells within the injury zone.Furthermore,in vitro analysis revealed increased TSC2 expression in exosomal receptor cells compared with other cells.Further assessment of cellular communication following spinal cord injury showed that Tsc2 was involved in ependymal cellular communication at 1 and 3 days post-injury through the epidermal growth factor and midkine signaling pathways.In addition,Slc16a3 participated in cellular communication in ependymal cells at 7 days post-injury via the vascular endothelial growth factor and macrophage migration inhibitory factor signaling pathways.Collectively,these findings confirm that exosomes derived from neural stem cells undergoing necroptosis play an important role in cellular communication after spinal cord injury and induce TSC2 upregulation in recipient cells.

Pan-TRK positive uterine sarcoma in immunohistochemistry without neurotrophic tyrosine receptor kinase gene fusions:A case report

BACKGROUND The classification of uterine sarcomas is based on distinctive morphological and immunophenotypic characteristics,increasingly supported by molecular genetic diagnostics.Data on neurotrophic tyrosine receptor kinase(NTRK)gene fusionpositive uterine sarcoma,potentially aggressive and morphologically similar to fibrosarcoma,are limited due to its recent recognition.Pan-TRK immunohistochemistry(IHC)analysis serves as an effective screening tool with high sensitivity and specificity for NTRK-fusion malignancies.CASE SUMMARY We report a case of a malignant mesenchymal tumor originating from the uterine cervix,which was pan-TRK IHC-positive but lacked NTRK gene fusions,accompanied by a brief literature review.A 55-year-old woman presented to the emergency department with abdominal pain and distension,exhibiting significant ascites and multiple solid pelvic masses.Pelvic examination revealed a tumor encompassing the uterine cervix,extending to the vagina and uterine corpus.A punch biopsy of the cervix indicated NTRK sarcoma with positive immunochemical pan-TRK stain.However,subsequent next generation sequencing revealed no NTRK gene fusion,leading to a diagnosis of poorly differentiated,advanced-stage sarcoma.CONCLUSION The clinical significance of NTRK gene fusion lies in potential treatment with TRK inhibitors for positive sarcomas.Identifying such rare tumors is crucial due to the potential applicability of tropomyosin receptor kinase inhibitor treatment.

Review of General Algorithmic Features for Genome Assemblers for Next Generation Sequencers

In the realm of bioinformatics and computational biology, the most rudimentary data upon which all the analysis is built is the sequence data of genes, proteins and RNA. The sequence data of the entire genome is the solution to the genome assembly problem. The scope of this contribution is to provide an overview on the art of problem-solving applied within the domain of genome assembly in the next- generation sequencing （NGS） platforms. This article discusses the major genome assemblers that were proposed in the literature during the past decade by outlining their basic working principles. It is intended to act as a qualitative, not a quantitative, tutorial to all working on genome assemblers pertaining to the next generation of sequencers. We discuss the theoretical aspects of various genome assemblers, identifying their working schemes. We also discuss briefly the direction in which the area is headed towards along with discussing core issues on software simplicity.

改进灰狼算法优化GBDT在PM_(2.5)预测中的应用

针对灰狼算法易陷入局部最优解和全局搜索能力不足的问题,通过霍尔顿序列(Halton Sequence)搜索算法初始化狼群位置,避免灰狼算法陷入局部最优解和重复运算;引入莱维飞行和随机游动策略对灰狼算法的寻优过程进行优化,以增加算法的全局搜索能力;利用粒子群算法模拟灰狼种群得出的最佳适应度以用于惩罚项改进灰狼算法中的头狼更新策略。使用改进算法优化的梯度提升树(Gradient Boosting Decision Trees,GBDT)模型对北京市大气污染物监测数据中PM_(2.5)质量浓度进行预测,采用3种评估函数对各模型以及混合模型预测效果得分进行评估。结果显示,本文改进的灰狼算法对梯度提升树的优化效果优于其他算法,均方根误差E RMS为6.65μg/m^(3),平均绝对值误差E MA为3.20μg/m^(3),拟合优度(R^(2))为99%,比传统灰狼算法优化结果的均方根误差减少了19.19μg/m^(3),平均绝对值误差降低了10.03μg/m^(3),拟合优度增加了9百分点;与霍尔顿序列和莱维飞行改进的(Levy Flight-Halton Sequence,LHGWO)相比,改进的灰狼算法预测得分的均方根误差降低了10.39μg/m^(3),平均绝对值误差减小了6.71μg/m^(3),拟合优度提高了5百分点。研究表明了预测模型优化的有效性,为未来城市改善空气质量提供了科学依据和技术支持。

基于改进狼群算法优化LSTM网络的舆情演化预测

为提高预测舆情演化趋势的能力,提出了一种基于改进狼群算法(IWPA)优化长短期记忆(LSTM)神经网络的舆情演化预测模型。采用Halton Sequence进行初始化,提高种群多样性;设计步长因子进行高斯-正弦扰动变换,提高狼群探索开发能力;结合鲸鱼优化算法中的螺旋改进围攻机制,增强狼群的局部搜索能力;引入记忆力机制,使用双向记忆种群增加狼群协同合作能力,将改进后的狼群算法应用到LSTM神经网络的超参数预测。采用“新冠疫情”和“食品安全”等关键词作为实例,证明了IWPA-LSTM神经网络舆情演化预测模型具有良好的准确性和普适性,适用于多种舆情演化的预测。

Screening biomarkers for spinal cord injury using weighted gene co-expression network analysis and machine learning

Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).

Mitochondrial targeting sequence of magnetoreceptor MagR:More than just targeting

Iron-sulfur clusters(ISC)are essential cofactors for proteins involved in various biological processes,such as electron transport,biosynthetic reactions,DNA repair,and gene expression regulation.ISC assembly protein IscA1(or MagR)is found within the mitochondria of most eukaryotes.Magnetoreceptor(MagR)is a highly conserved A-type iron and iron-sulfur cluster-binding protein,characterized by two distinct types of iron-sulfur clusters,[2Fe-2S]and[3Fe-4S],each conferring unique magnetic properties.MagR forms a rod-like polymer structure in complex with photoreceptive cryptochrome(Cry)and serves as a putative magnetoreceptor for retrieving geomagnetic information in animal navigation.Although the N-terminal sequences of MagR vary among species,their specific function remains unknown.In the present study,we found that the N-terminal sequences of pigeon MagR,previously thought to serve as a mitochondrial targeting signal(MTS),were not cleaved following mitochondrial entry but instead modulated the efficiency with which iron-sulfur clusters and irons are bound.Moreover,the N-terminal region of MagR was required for the formation of a stable MagR/Cry complex.Thus,the N-terminal sequences in pigeon MagR fulfil more important functional roles than just mitochondrial targeting.These results further extend our understanding of the function of MagR and provide new insights into the origin of magnetoreception from an evolutionary perspective.

A spatiotemporal deep learning method for excavation-induced wall deflections

Data-driven approaches such as neural networks are increasingly used for deep excavations due to the growing amount of available monitoring data in practical projects.However,most neural network models only use the data from a single monitoring point and neglect the spatial relationships between multiple monitoring points.Besides,most models lack flexibility in providing predictions for multiple days after monitoring activity.This study proposes a sequence-to-sequence(seq2seq)two-dimensional(2D)convolutional long short-term memory neural network(S2SCL2D)for predicting the spatiotemporal wall deflections induced by deep excavations.The model utilizes the data from all monitoring points on the entire wall and extracts spatiotemporal features from data by combining the 2D convolutional layers and long short-term memory(LSTM)layers.The S2SCL2D model achieves a long-term prediction of wall deflections through a recursive seq2seq structure.The excavation depth,which has a significant impact on wall deflections,is also considered using a feature fusion method.An excavation project in Hangzhou,China,is used to illustrate the proposed model.The results demonstrate that the S2SCL2D model has superior prediction accuracy and robustness than that of the LSTM and S2SCL1D(one-dimensional)models.The prediction model demonstrates a strong generalizability when applied to an adjacent excavation.Based on the long-term prediction results,practitioners can plan and allocate resources in advance to address the potential engineering issues.

The evolution of cancer genomic medicine in Japan and the role of the National Cancer Center Japan

The journey to implement cancer genomic medicine(CGM)in oncology practice began in the 1980s,which is considered the dawn of genetic and genomic cancer research.At the time,a variety of activating oncogenic alterations and their functional significance were unveiled in cancer cells,which led to the development of molecular targeted therapies in the 2000s and beyond.Although CGM is still a relatively new discipline and it is difficult to predict to what extent CGM will benefit the diverse pool of cancer patients,the National Cancer Center(NCC)of Japan has already contributed considerably to CGM advancement for the conquest of cancer.Looking back at these past achievements of the NCC,we predict that the future of CGM will involve the following:1)A biobank of paired cancerous and non-cancerous tissues and cells from various cancer types and stages will be developed.The quantity and quality of these samples will be compatible with omics analyses.All biobank samples will be linked to longitudinal clinical information.2)New technologies,such as whole-genome sequencing and artificial intelligence,will be introduced and new bioresources for functional and pharmacologic analyses(e.g.,a patient-derived xenograft library)will be systematically deployed.3)Fast and bidirectional translational research(bench-to-bedside and bedside-to-bench)performed by basic researchers and clinical investigators,preferably working alongside each other at the same institution,will be implemented;4)Close collaborations between academia,industry,regulatory bodies,and funding agencies will be established.5)There will be an investment in the other branch of CGM,personalized preventive medicine,based on the individual's genetic predisposition to cancer.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis data.Meanwhile,deep learning predictions of sea ice thickness(SIT)have yet to receive ample attention.In this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/observations.These models enable monthly predictions of Arctic SIT without considering the complex physical processes involved.Through comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT anomalies.Regarding the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most cases.The models also demonstrate robust performances in predicting SIT and SIE during extreme events.The effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

Helicobacter pylori infection alters gastric microbiota structure and biological functions in patients with gastric ulcer or duodenal ulcer

BACKGROUND Helicobacter pylori(H.pylori)infection is closely associated with gastrointestinal diseases.Our preliminary studies have indicated that H.pylori infection had a significant impact on the mucosal microbiome structure in patients with gastric ulcer(GU)or duodenal ulcer(DU).AIM To investigate the contributions of H.pylori infection and the mucosal microbiome to the pathogenesis and progression of ulcerative diseases.METHODS Patients with H.pylori infection and either GU or DU,and healthy individuals without H.pylori infection were included.Gastric or duodenal mucosal samples was obtained and subjected to metagenomic sequencing.The compositions of the microbial communities and their metabolic functions in the mucosal tissues were analyzed.RESULTS Compared with that in the healthy individuals,the gastric mucosal microbiota in the H.pylori-positive patients with GU was dominated by H.pylori,with signi-ficantly reduced biodiversity.The intergroup differential functions,which were enriched in the H.pylori-positive GU patients,were all derived from H.pylori,particularly those concerning transfer RNA queuosine-modification and the synthesis of demethylmenaquinones or menaquinones.A significant enrichment of the uibE gene was detected in the synthesis pathway.There was no significant difference in microbial diversity between the H.pylori-positive DU patients and healthy controls.CONCLUSION H.pylori infection significantly alters the gastric microbiota structure,diversity,and biological functions,which may be important contributing factors for GU.

The early life immune dynamics and cellular drivers at single-cell resolution in lamb forestomachs and abomasum

Background Four-chambered stomach including the forestomachs(rumen,reticulum,and omasum)and abomasum allows ruminants convert plant fiber into high-quality animal products.The early development of this four-chambered stomach is crucial for the health and well-being of young ruminants,especially the immune development.However,the dynamics of immune development are poorly understood.Results We investigated the early gene expression patterns across the four-chambered stomach in Hu sheep,at 5,10,15,and 25 days of age.We found that forestomachs share similar gene expression patterns,all four stomachs underwent widespread activation of both innate and adaptive immune responses from d 5 to 25,whereas the metabolic function were significantly downregulated with age.We constructed a cell landscape of the four-chambered stomach using single-cell sequencing.Integrating transcriptomic and single-cell transcriptomic analyses revealed that the immune-associated module hub genes were highly expressed in T cells,monocytes and macrophages,as well as the defense-associated module hub genes were highly expressed in endothelial cells in the four-stomach tissues.Moreover,the non-immune cells such as epithelial cells play key roles in immune maturation.Cell communication analysis predicted that in addition to immune cells,non-immune cells recruit immune cells through macrophage migration inhibitory factor signaling in the forestomachs.Conclusions Our results demonstrate that the immune and defense responses of four stomachs are quickly developing with age in lamb's early life.We also identified the gene expression patterns and functional cells associated with immune development.Additionally,we identified some key receptors and signaling involved in immune regulation.These results help to understand the early life immune development at single-cell resolution,which has implications to develop nutritional manipulation and health management strategies based on specific targets including key receptors and signaling pathways.

Genetic variation of circHIBADH enhances prostate cancer risk through regulating HNRNPA1-related RNA splicing

The current study aimed to investigate associations of circRNAs and related genetic variants with the risk of prostate cancer(PCa)as well as to elucidate biological mechanisms underlying the associations.We first compared expression levels of circRNAs between 25 paired PCa and adjacent normal tissues to identify riskassociated circRNAs by using the MiOncoCirc database.We then used logistic regression models to evaluate associations between genetic variants in candidate circRNAs and PCa risk among 4662 prostate cancer patients and 3114 healthy controls,and identified circHIBADH rs11973492 T>C as a significant risk-associated variant(odds ratio=1.20,95%confidence interval:1.08-1.34,P=7.06×10^(-4))in a dominant genetic model,which altered the secondary structure of the corresponding RNA chain.In the in silico analysis,we found that circHIBADH sponged and silenced 21 RNA-binding proteins(RBPs)enriched in the RNA splicing pathway,among which HNRNPA1 was identified and validated as a hub RBP using an external RNA-sequencing data as well as the in-house(four tissue samples)and publicly available single-cell transcriptomes.Additionally,we demonstrated that HNRNPA1 influenced hallmarks including MYC target,DNA repair,and E2F target signaling pathways,thereby promoting carcinogenesis.In conclusion,genetic variants in circHIBADH may act as sponges and inhibitors of RNA splicing-associated RBPs including HNRNPA1,playing an oncogenic role in PCa.