基于Single—Sequence布图规划线长约束问题的研究

布图规划是VLSI设计中非常重要的步骤。Single—Sequenc是一种非常有用的表示布图的编码方法。在实际的布图规划中，由于线长对芯片性能有较大的影响，因此为了使芯片的整体性能达到最优，考虑线长因素，使线长尽可能短。该论文提出了在用模拟退火算法寻求最优布图的同时，通过对算法加以改进，考虑线长约束条件，有效地解决了布图规划的线长约束问题。

Single-cell analyses of circulating tumor cells

Circulating tumor cells(CTCs) are a population of tumor cells mediating metastasis, which results in most of the cancer related deaths. The number of CTCs in the peripheral blood of patients is rare, and many platforms have been launched for detection and enrichment of CTCs. Enumeration of CTCs has already been used as a prognosis marker predicting the survival rate of cancer patients. Yet CTCs should be more potential. Studies on CTCs at single cell level may help revealing the underlying mechanism of tumorigenesis and metastasis. Though far from developed, this area of study holds much promise in providing new clinical application and deep understanding towards metastasis and cancer development.

Single-cell transcriptomic dissection of the cellular and molecular events underlying the triclosan-induced liver fibrosis in mice

Background: Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol, TCS], a common antimicrobial additive in many personal care and health care products, is frequently detected in human blood and urine. Therefore, it has been considered an emerging and potentially toxic pollutant in recent years. Long-term exposure to TCS has been suggested to exert endocrine disruption effects, and promote liver fibrogenesis and tumorigenesis. This study was aimed at clarifying the underlying cellular and molecular mechanisms of hepatotoxicity effect of TCS at the initiation stage.Methods: C57BL/6 mice were exposed to different dosages of TCS for 2 weeks and the organ toxicity was evaluated by various measurements including complete blood count, histological analysis and TCS quantification. Single cell RNA sequencing(scRNA-seq) was then carried out on TCS-or mock-treated mice livers to delineate the TCS-induced hepatotoxicity. The acquired single-cell transcriptomic data were analyzed from different aspects including differential gene expression, transcription factor(TF) regulatory network, pseudotime trajectory, and cellular communication, to systematically dissect the cellular and molecular events after TCS exposure. To verify the TCS-induced liver fibrosis,the expression levels of key fibrogenic proteins were examined by Western blotting, immunofluorescence, Masson’s trichrome and Sirius red stainings. In addition, normal hepatocyte cell MIHA and hepatic stellate cell LX-2 were used as in vitro cell models to experimentally validate the effects of TCS by immunological, proteomic and metabolomic technologies.Results: We established a relatively short term TCS exposure murine model and found the TCS mainly accumulated in the liver. The scRNA-seq performed on the livers of the TCS-treated and control groups profiled the gene expressions of > 76,000 cells belonging to 13 major cell types. Among these types, hepatocytes and hepatic stellate cells(HSCs)were significantly increased in TCS-treated group. We found that TCS promoted fibrosis-associated proliferation of hepatocytes, in which Gata2 and Mef2c are the key driving TFs. Our data also suggested that TCS induced the proliferation and activation of HSCs, which was experimentally verified in both liver tissue and cell model. In addition,other changes including the dysfunction and capillarization of endothelial cells, an increase of fibrotic characteristics in B plasma cells, and M2 phenotype-skewing of macrophage cells, were also deduced from the scRNA-seq analysis, and these changes are likely to contribute to the progression of liver fibrosis. Lastly, the key differential ligand-receptor pairs involved in cellular communications were identified and we confirmed the role of GAS6_AXL interactionmediated cellular communication in promoting liver fibrosis.Conclusions: TCS modulates the cellular activities and fates of several specific cell types(including hepatocytes, HSCs,endothelial cells, B cells, Kupffer cells and liver capsular macrophages) in the liver, and regulates the ligand-receptor interactions between these cells, thereby promoting the proliferation and activation of HSCs, leading to liver fibrosis.Overall, we provide the first comprehensive single-cell atlas of mice livers in response to TCS and delineate the key cellular and molecular processes involved in TCS-induced hepatotoxicity and fibrosis.

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.

Single-cell RNA sequencing in cornea research:Insights into limbal stem cells and their niche regulation

The corneal epithelium is composed of stratified squamous epithelial cells on the outer surface of the eye,which acts as a protective barrier and is critical for clear and stable vision.Its continuous renewal or wound healing depends on the proliferation and differentiation of limbal stem cells(LSCs),a cell population that resides at the limbus in a highly regulated niche.Dysfunction of LSCs or their niche can cause limbal stem cell deficiency,a disease that is manifested by failed epithelial wound healing or even blindness.Nevertheless,compared to stem cells in other tissues,little is known about the LSCs and their niche.With the advent of single-cell RNA sequencing,our understanding of LSC characteristics and their microenvironment has grown considerably.In this review,we summarized the current findings from single-cell studies in the field of cornea research and focused on important advancements driven by this technology,including the heterogeneity of the LSC population,novel LSC markers and regulation of the LSC niche,which will provide a reference for clinical issues such as corneal epithelial wound healing,ocular surface reconstruction and interventions for related diseases.

COVID-19 Related Research by Data Mining in Single Cell Transcriptome Profiles

The outbreak of coronavirus disease 2019(COVID-2019)has drawn public attention all over the world.As a newly emerging area,single cell sequencing also exerts its power in the battle over the epidemic.In this review,the up-to-date knowledge of COVID-19 and its receptor is summarized,followed by a collection of the mining of single cell transcriptome profiling data for the information in aspects of the vulnerable cell types in humans and the potential mechanisms of the disease.

Single cell RNA sequencing reveals mesenchymal heterogeneity and critical functions of Cd271 in tooth development

BACKGROUND Accumulating evidence suggests that the maxillary process,to which cranial crest cells migrate,is essential to tooth development.Emerging studies indicate that Cd271 plays an essential role in odontogenesis.However,the underlying mechanisms have yet to be elucidated.AIM To establish the functionally heterogeneous population in the maxillary process,elucidate the effects of Cd271 deficiency on gene expression differences.METHODS p75NTR knockout(Cd271-/-)mice(from American Jackson laboratory)were used to collect the maxillofacial process tissue of p75NTR knockout mice,and the wildtype maxillofacial process of the same pregnant mouse wild was used as control.After single cell suspension,the cDNA was prepared by loading the single cell suspension into the 10x Genomics Chromium system to be sequenced by NovaSeq6000 sequencing system.Finally,the sequencing data in Fastq format were obtained.The FastQC software is used to evaluate the quality of data and CellRanger analyzed the data.The gene expression matrix is read by R software,and Seurat is used to control and standardize the data,reduce the dimension and cluster.We search for marker genes for subgroup annotation by consulting literature and database;explore the effect of p75NTR knockout on mesenchymal stem cells(MSCs)gene expression and cell proportion by cell subgrouping,differential gene analysis,enrichment analysis and protein-protein interaction network analysis;understand the interaction between MSCs cells and the differentiation trajectory and gene change characteristics of p75NTR knockout MSCs by cell communication analysis and pseudo-time analysis.Last we verified the findings single cell sequencing in vitro.RESULTS We identified 21 cell clusters,and we re-clustered these into three subclusters.Importantly,we revealed the cell–cell communication networks between clusters.We clarified that Cd271 was significantly associated with the regulation of mineralization.CONCLUSION This study provides comprehensive mechanistic insights into the maxillary-process-derived MSCs and demonstrates that Cd271 is significantly associated with the odontogenesis in mesenchymal populations.

A SARS-CoV-2 neutralizing antibody discovery by single cell sequencing and molecular modeling

Although vaccines have been developed,mutations of SARS-CoV-2,especially the dominant B.1.617.2(delta)and B.1.529(omicron)strains with more than 30 mutations on their spike protein,have caused a significant decline in prophylaxis,calling for the need for drug improvement.Antibodies are drugs preferentially used in infectious diseases and are easy to get from immunized organisms.The current study combined molecular modeling and single memory B cell sequencing to assess candidate sequences before experiments,providing a strategy for the fabrication of SARS-CoV-2 neutralizing antibodies.A total of 128 sequences were obtained after sequencing 196 memory B cells,and 42 sequences were left after merging extremely similar ones and discarding incomplete ones,followed by homology modeling of the antibody variable region.Thirteen candidate sequences were expressed,of which three were tested positive for receptor binding domain recognition but only one was confirmed as having broad neutralization against several SARS-CoV-2 variants.The current study successfully obtained a SARS-CoV-2 antibody with broad neutralizing abilities and provided a strategy for antibody development in emerging infectious diseases using single memory B cell BCR sequencing and computer assistance in antibody fabrication.

Insights into the genetic architecture of congenital heart disease from animal modeling

Congenital heart disease(CHD)is observed in up to 1%of live births and is one of the leading causes of mortality from birth defects.While hundreds of genes have been implicated in the genetic etiology of CHD,their role in CHD pathogenesis is still poorly understood.This is largely a reflection of the sporadic nature of CHD,as well as its variable expressivity and incomplete penetrance.We reviewed the monogenic causes and evidence for oligogenic etiology of CHD,as well as the role of de novo mutations,common variants,and genetic modifiers.For further mechanistic insight,we leveraged single-cell data across species to investigate the cellular expression characteristics of genes implicated in CHD in developing human and mouse embryonic hearts.Understanding the genetic etiology of CHD may enable the application of precision medicine and prenatal diagnosis,thereby facilitating early intervention to improve outcomes for patients with CHD.

Sequence Information on Simple Sequence Repeats and Single Nucleotide Polymorphisms through Transcriptome Analysis of Mungbean

Mungbean （Vigna radiata （L.） Wilczek） is a unique species in its ability to fix atmospheric nitrogen, with early maturity, and relatively good drought resistance. We used 454 sequencing technology for transcriptome sequencing. A total of 150 159 and 142 993 reads produced 5 254 and 6 374 large contigs （〉_500 bp） with an average length of 833 and 853 for Sunhwa and Jangan, respectively. Functional annotation to known sequences yielded 41.34% and 41.74% unigenes for Jangan and Sunhwa. A higher number of simple sequence repeat （SSR） motifs was identified in Jangan （1 630） compared with that of Sunhwa （1 334）. A similar SSR distribution pattern was observed in both varieties. A total of 8 249 single nucleotide polymorphisms （SNPs） and indels with 2 098 high-confidence candidates were identified in the two mungbean varieties. The average distance between individual SNPs was -860 bp. Our report demonstrates the utility of transcriptomic data for implementing a functional annotation and development of genetic markers. We also provide large resource sequence data for mungbean improvement programs.

基于SS序列集成电路不规则模块布图算法

针对Single-Sequence的集成电路布图,在SS编解码应用对芯片中各单元的摆放进行优化,从而达到芯片面积利用率最大化。重点介绍了利用SS序列解决不规则模块摆放问题,使得SS布图功能更灵活多变。

基于SS序列集成电路布线技术

集成电路（IC）是在半导体基片上形成的完整的电子线路。当前芯片里的电路与系统日趋复杂，超大规模集成电路（VLSI）设计技术水平也在逐渐提高。VLSI设计中一般采用分级设计的方法。布图设计过程是整个VLSI分级设计中非常关键的步骤之一。基于Single-Sequence的集成电路布图就是在SS编解码的应用下对芯片中各单元的摆放进行优化从而达到芯片面积利用率最大化。本文重点介绍了在SS序列生成版图后各单元间连线的设计以及如何根据水平／垂直约束图提取版图中各单元的坐标。并根据要连模块的位置关系对其连线经过的模块进行有条件加线宽的处理。

FSPAM:A Feature Construction Method to Identifying Cell Populations in ScRNA-seq Data

The emergence of single-cell RNA-sequencing(scRNA-seq)technology has introduced new information about the structure of cells,diseases,and their associated biological factors.One of the main uses of scRNA-seq is identifying cell populations,which sometimes leads to the detection of rare cell populations.However,the new method is still in its infancy and with its advantages comes computational challenges that are just beginning to address.An important tool in the analysis is dimensionality reduction,which transforms high dimensional data into a meaningful reduced subspace.The technique allows noise removal,visualization and compression of high-dimensional data.This paper presents a new dimensionality reduction approach where,during an unsupervised multistage process,a feature set including high valuable markers is created which can facilitate the isolation of cell populations.Our proposed method,called fusion of the Spearman and Pearson affinity matrices(FSPAM),is based on a graph-based Gaussian kernel.Use of the graph theory can be effective to overcome the challenge of the nonlinear relations between cellular markers in scRNA-seq data.Furthermore,with a proper fusion of the Pearson and Spearman correlation coefficient criteria,it extracts a set of the most important features in a new space.In fact,the FSPAM aggregates the various aspects of cell-to-cell similarity derived from the Pearson and Spearman metrics,and reveals new aspects of cell-to-cell similarity,which can be used to extract new features.The results of the identification of cell populations via k-means++clustering method based on the features extracted from the FSPAM and different datasets of scRNA-seq suggested that the proposed method,regardless of the characteristics that govern each dataset,enjoys greater accuracy and better quality compared to previous methods.

System analysis based on the T cell exhaustion‑related genes identifies CD38 as a novel therapy target for ovarian cancer

Ovarian cancer(OV)is highly heterogeneous tumor with a very poor prognosis.Studies increasingly show that T cell exhaustion is prognostically relevant in OV.The aim of this study was to dissect the heterogeneity of T cell subclusters in OV through single cell transcriptomic analysis.The single RNA-sequencing(scRNA-seq)data of five OV patients were analyzed,and six major cell clusters were identified after threshold screening.Further clustering of T cell-associated clusters revealed four subtypes.Pathways related to oxidative phosphorylation,G2M checkpoint,JAK-STAT and MAPK signaling were significantly activated,while the p53 pathway was inhibited in the CD8+exhausted T cells.The standard marker genes of CD8+T cell exhaustion were screened to develop a T-cell related gene score(TRS)based on random forest plots in TCGA cohort.The patients with low TRS have better prognosis compared to the patients with high TRS in both TCGA and GEO.In addition,most genes included in the TRS showed significant differences in expression levels between the high-and low-risk groups.Immune cell infiltration was analyzed using the MCPcounter and xCell algorithms,which revealed significant differences between the two risk groups,indicating that the different prognoses may stem from the respective immune landscapes.In addition,CD38 knockdown in OV cell lines increased apoptosis and inhibited invasion in vitro.Finally,we performed a drug sensitivity analysis and identified six potential drug candidates for OV.To summarize,we identified the heterogeneity and clinical significance of T cell exhaustion in OV and built a superior prognostic model based on T cell exhaustion genes,which can contribute to the development of more precise and effective therapies.

Full-length transcripts facilitates Portunus trituberculatus genome structure annotation

Portunus trituberculatus is an ide al model for elucidating crustacean genetic networks.Here we combined single molecule real-time(SMRT)sequencing and Illumina RNA-seq to characterize the coding genes,non-coding RNAs and pseudogenes and further to improve the genome annotation information of P.tritub erculatus.In this study,we assembled 9694 non-redundancy full-length transcripts,and 658737307-bp repetitive sequences were identified in the P.trituberculatus full-length transcriptome.We also predicted the P.tritub erculatus genome structure based on full-length transcripts,including 18602 genes,28686 non-coding RNAs,1407 pseudogenes,740 motif,and 26434 domain.Meanwhile,14460,10211,5412,7314,and 14448 genes had significant matches with sequences in the NR,KOG,GO,KEGG,and TrEMBL database,respectively.Overall,our work firstly provided the long-read transcriptome and we believed that these data are very necessary to improve the annotation information of P.trituberculatus genome structure,and useful information for the future studies on evolution and physiological regulation of P.trituberculatus.

Explore potential biomarkers to provide a theoretical basis for the treatment of liver fibrosis with pirfenidone

Background:Hepatic fibrosis is a common chronic liver disease in clinic,the purpose of our study is to explore potential biomarkers to provide a theoretical basis for the treatment of liver fibrosis with pirfenidone.Methods:We downloaded a gene-sequencing dataset and a single-cell dataset from the GEO database and pirfenidone target genes from three different databases.First,we performed GO,KEGG,and DO analysis on pirfenidone target genes.Then,we grouped the liver tissue sequencing data(GSE162694)in the sequencing data set(N-F0 group and F1-F4 group)and performed gene expression differential analysis on these two groups,weighted gene co-expression network analysis and gene Enrichment analysis.Finally,we intersected the significantly upregulated genes in the F1-F4 group with the pirfenidone target genes and performed PPI network analysis.In order to further explore the expression of both pirfenidone drug target genes and liver fibrosis disease genes(PDLFG)in different immune cells of liver tissue,we used the CD45+cell data in the GSE136103 data set for further analysis.Results:A subnetwork consisting of CDC42,HNF4A,BHLHE40,CCDC71L,NR1H3,TNF,MGLL,GPT,SCD and PLIN1 was screened out,and by analysis,we finally identified the SCD as PDLFG.In single-cell sequencing analysis,we found that SCD was highly expressed in M2-polarized macrophages.Conclusion:SCD may be an important target protein to inhibit the progression of liver fibrosis.

Single cell sequencing: technique, application,and future development

The progression of next generation sequencing is continuously changing the landscape of genomic, tran- scriptomic, and epigenomic studies. Particularly, advances in single cell manipulation and amplification techniques bring sequencing technology to the single-cell level. Single cell genome sequencing allows us to study tumor evolu- tion, gamete genesis, somatic mosaicism at genome-wide level; single cell transcriptome sequencing unveils the dynamic gene expression during early embryonic devel- opment, differentiation and reprogramming; single cell methylome sequencing is just taking off and shows great potential in cancer and stem cell studies. Lots of attempts are still being made in other dimensions of sequencing. The increasing need for single cell sequencing requires the future techniques with the following features： （1） high accuracy and fidelity; （2） able to perform multiple omics analyses in one cell; （3） high degree of automation and standardized pipeline. These progresses and improvements will lower the barrier for single cell sequencing to enter ordinary laboratories. The wide application of single cell sequencing techniques will substantially change biomedi- cal research in future.

VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder

Single-cell RNA sequencing(scRNA-seq) is a powerful technique to analyze the transcriptomic heterogeneities at the single cell level. It is an important step for studying cell subpopulations and lineages, with an effective low-dimensional representation and visualization of the original scRNA-Seq data. At the single cell level, the transcriptional fluctuations are much larger than the average of a cell population, and the low amount of RNA transcripts will increase the rate of technical dropout events. Therefore, scRNA-seq data are much noisier than traditional bulk RNA-seq data. In this study, we proposed the deep variational autoencoder for scRNA-seq data(VASC), a deep multi-layer generative model, for the unsupervised dimension reduction and visualization of scRNA-seq data. VASC can explicitly model the dropout events and find the nonlinear hierarchical feature representations of the original data. Tested on over 20 datasets, VASC shows superior performances in most cases and exhibits broader dataset compatibility compared to four state-of-the-art dimension reduction and visualization methods. In addition, VASC provides better representations for very rare cell populations in the 2D visualization. As a case study, VASC successfully re-establishes the cell dynamics in pre-implantation embryos and identifies several candidate marker genes associated with early embryo development. Moreover, VASC also performs well on a 10× Genomics dataset with more cells and higher dropout rate.

Biomonitoring for traditional herbal medicinal products using DNA metabarcoding and single molecule, real-time sequencing

Global concerns have been paid to the potential hazard of traditional herbal medicinal products(THMPs). Substandard and counterfeit THMPs, including traditional Chinese patent medicine, health foods, dietary supplements, etc. are potential threats to public health. Recent marketplace studies using DNA barcoding have determined that the current quality control methods are not sufficient for ensuring the presence of authentic herbal ingredients and detection of contaminants/adulterants. An efficient biomonitoring method for THMPs is of great needed. Herein, metabarcoding and single-molecule, realtime(SMRT) sequencing were used to detect the multiple ingredients in Jiuwei Qianghuo Wan(JWQHW), a classical herbal prescription widely used in China for the last 800 years. Reference experimental mixtures and commercial JWQHW products from the marketplace were used to confirm the method. Successful SMRT sequencing results recovered 5416 and 4342 circular-consensus sequencing(CCS) reads belonging to the ITS2 and psb A-trn H regions. The results suggest that with the combination of metabarcoding and SMRT sequencing, it is repeatable, reliable, and sensitive enough to detect species in the THMPs, and the error in SMRT sequencing did not affect the ability to identify multiple prescribed species and several adulterants/contaminants. It has the potential for becoming a valuable tool for the biomonitoring of multi-ingredient THMPs.

Single-cell transcriptome reveals core cell populations and androgen-RXFP2 axis involved in deer antler full regeneration

Deer antlers constitute a unique mammalian model for the study of both organ formation in postnatal life and annual full regeneration.Previous studies revealed that these events are achieved through the proliferation and differentiation of antlerogenic periosteum(AP)cells and pedicle periosteum(PP)cells,respectively.As the cells resident in the AP and the PP possess stem cell attributes,both antler generation and regeneration are stem cell-based processes.However,the cell composition of each tissue type and molecular events underlying antler development remain poorly characterized.Here,we took the approach of single-cell RNA sequencing(scRNA-Seq)and identified eight cell types(mainly THY1^(+)cells,progenitor cells,and osteochondroblasts)and three core subclusters of the THY1^(+)cells(SC2,SC3,and SC4).Endothelial and mural cells each are heterogeneous at transcriptional level.It was the proliferation of progenitor,mural,and endothelial cells in the activated antler-lineage-specific tissues that drove the rapid formation of the antler.We detected the differences in the initial differentiation process between antler generation and regeneration using pseudotime trajectory analysis.These may be due to the difference in the degree of stemness of the AP-THY1+and PP-THY1^(+)cells.We further found that androgen-RXFP2 axis may be involved in triggering initial antler full regeneration.Fully deciphering the cell composition for these antler tissue types will open up new avenues for elucidating the mechanism underlying antler full renewal in specific and regenerative medicine in general.