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HCCDB v2.0:Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

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genomics, Proteomics & bioinformatics 2024年第1期22卷 131-142页

作者： Ziming Jiang Yanhong Wu Yuxin Miao Kaige Deng Fan Yang Shuhuan Xu Yupeng Wang Renke You Lei Zhang Yuhan Fan Wenbo Guo Qiuyu Lian Lei Chen Xuegong Zhang Yongchang Zheng Jin Gu Eight-Year Program of Clinical Medicine Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100006China MOE Key Laboratory of bioinformatics BNRIST Bioinformatics DivisionInstitute for Precision Medicine&Department of AutomationTsinghua UniversityBeijing 100084China Department of Liver Surgery Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Fuzhou Institute for Data Technology Fuzhou 350207China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai 200240China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China International Cooperation Laboratory on Signal Transduction Eastern Hepatobiliary Surgery InstituteSecond Military Medical UniversityShanghai 200438China National Center for Liver Cancer Shanghai 201805China

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma(HCC).Integrated 15 transcriptomic datasets of HCC clinical samples,the first version of HCC database(HCCDB v1.0)was released in *** the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets,it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and *** four years having passed,the database now needs integration of recently published ***,the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial ***,we present HCCDB v2.0,an updated version that combines bulk,single-cell,and spatial transcriptomic data of HCC clinical *** dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples,thereby enhancing the reliability of transcriptomic meta-analysis.A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections,respectively.A novel single-cell level and 2-dimension(sc-2D)metric is proposed as well to summarize cell type-specific and dysregulated gene expression *** are all graphically visualized in our online portal,allowing users to easily retrieve data through a user-friendly interface and navigate between different *** extensive clinical phenotypes and transcriptomic data in the database,we show two applications for identifying prognosis-associated cells and tumor *** v2.0 is available at http://***/database/hccdb2.

关键词： Hepatocellular carcinoma Database Integrative analysis Single-cell RNA sequencing Spatial transcriptomics

Highly Regional Genes:graph-based gene selection for single-cell RNA-seq data

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Journal of Genetics and genomics 2022年第9期49卷 891-899页

作者： Yanhong Wu Qifan Hu Shicheng Wang Changyi Liu Yiran Shan Wenbo Guo Rui Jiang Xiaowo Wang Jin Gu MOE Key Laboratory of bioinformatics BNRIST Bioinformatics DivisionDepartment of AutomationTsinghua UniversityBeijing 100084China

Gene selection is an indispensable step for analyzing noisy and high-dimensional single-cell RNA-seq(scRNA-seq)*** with the commonly used variance-based methods,by mimicking the human maker selection in the 2D visualization of cells,a new feature selection method called HRG(Highly Regional Genes)is proposed to find the informative genes,which show regional expression patterns in the cell-cell similarity *** mathematically find the optimal expression patterns that can maximize the proposed scoring *** comparison with several unsupervised methods,HRG shows high accuracy and robustness,and can increase the performance of downstream cell clustering and gene correlation ***,it is applicable for selecting informative genes of sequencing-based spatial transcriptomic data.

关键词： Single-cell RNA-sequencing Feature selection Spatially resolved transcriptomic data Regional patterns Graphical models

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

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genomics, Proteomics & bioinformatics 2018年第5期16卷 320-331页

作者： Dongfang Wang Jin Gu MOE Key Laboratory of bioinformatics BNRIST Bioinformatics Division & Center for Synthetic and Systems BiologyDepartment of Automation Tsinghua University

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.

关键词： Single cell RNA sequencing Deep variational autoencoder Dimension reduction Visualization Dropout

Genetic characterization of Northeast Asian cattle based on sequence polymorphisms in the complete mitochondrial genome

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Open Journal of Animal Sciences 2012年第4期2卷 217-223页

作者： Jeongsoo Lee Kyung-Tai Lee Sungmin Ahn Seunghwan Lee Dajeong Lim Young-Ju Kim Eun-Seok Cho Kyung-Seok Kim Hailu Dadi Tae-Hun Kim Animal genomics and bioinformatics division National Institute of Animal Science Suwon Korea Animal genomics and bioinformatics division National Institute of Animal Science Suwon Korea College of Veterinary Medicine Seoul National University Seoul Korea Department of Animal Science Chungbuk National University Cheongju Korea Lee Gil Ya Cancer and Diabetes Institute Gachon University of Medicine and Science Incheon Korea nimal genomics and bioinformatics division National Institute of Animal Science Suwon Korea

In this study, we analyzed complete mtDNA sequences variation and genetic relationship among taurine, indicine and Bison groups. In total, 107 sequences from different breeds, 45 European (45 Italian), 16 Middle East Asian (seven Iranian and nine Iraqi), 41 Northeast Asian (34 Korean and seven Japanese), two Nellore (Bos indicus) and two American Bison bison (Ame. bison) were obtained from Gen-Bank database. One Korean Hanwoo (Bos taurus) sequence was generated using the SOLiDTM System. In total, 1370 polymorphic sites, representing 8.39% of the complete 107 mtDNA sequences (16,338 bp) were detected and of these, 1186 parsimony informative polymorphic sites were identified. Neighbor-joining tree indicated that Korean, Japanese, Iranian, Iraqi, and Italian cattle were closely related to one another, but are separated from B. Bison. The B. taurus mtDNA polymorphism was greater in the D-loop than in the other regions. The ATP8, ND3, ND5, and ND6 regions were also quite parsimony informative, similar to Cyt b. In addition, this study revealed a distinct genetic difference between Korean cattle and B. indicus.

关键词： Bos taurus Complete Mitochondrial DNA Genome Phylogeny Polymorphism

A multilevel pan-cancer map links gene mutations to cancer hallmarks

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Chinese Journal of Cancer 2015年第10期34卷 439-449页

作者： Theo A.Knijnenburg Tycho Bismeijer Lodewyk F.A.Wessels llya Shmulevich Institute for Systems Biology bioinformatics and Statistics Division of Molecular CarcinogenesisNetherlands Cancer Institute

Background:A central challenge in cancer research is to create models that bridge the gap between the molecular level on which interventions can be designed and the cellular and tissue levels on which the disease phenotypes are *** study was undertaken to construct such a model from functional annotations and explore its use when integrated with large-scale cancer genomics ***:We created a map that connects genes to cancer hallmarks via signaling *** projected gene mutation and focal copy number data from various cancer types onto this *** performed statistical analyses to uncover mutually exclusive and co-occurring oncogenic aberrations within this ***:Our analysis showed that although the genetic fingerprint of tumor types could be very different,there were less variations at the level of hallmarks,consistent with the idea that different genetic alterations have similar functional ***,we showed how the multilevel map could help to clarify the role of infrequently mutated genes,and we demonstrated that mutually exclusive gene mutations were more prevalent in pathways,whereas many co-occurring gene mutations were associated with hallmark ***:Overlaying this map with gene mutation and focal copy number data from various cancer types makes it possible to investigate the similarities and differences between tumor samples systematically at the levels of not only genes but also pathways and hallmarks.

关键词： Cancer systems biology, Cancer hallmarks, Gene mutations, Multilevel model

Phylogenetic analysis and characterization of mitochondrial DNA for Korean native cattle

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Open Journal of Genetics 2013年第1期3卷 12-23页

作者： Hoyoung Chung Animal genomics & bioinformatics division National Institute of Animal Science Suwon Korea

This study was aimed to preserve mitochondria from liver tissues of Korean native cattle (KNC) as genetic resources and to analyze phylogenetic relationships among cattle breeds using the whole sequences of mtDNA. Mitochondria of KNC has been isolated with the alkaline lysis procedure using1 gof liver tissues, and measurements showed numbers of cells (2.64 × 1010), concentration (114.6 ug/ml), proteins (0.278 ug/ml), and absorbance (0.029) in 260 nm. Mitochondrial DNAs (mtDNA) were extracted from the isolated mitochondria to determine whole sequences that can be used to estimate genetic distances among cattle breeds. Designing of primers based on the bovine mtDNA sequence was resulted in 16 primer sets covering the whole mtDNA regions. The analysis of 40 KNC mtDNA sequences revealed 69 polymorphic sites that were less than the average number of SNP (single nucleotide polymorphism) for other populations (82 sites) in this study. As expected, the highest observation of SNPs was found in the D-loop region, and a total of 29 SNPs were shared between cattle populations. The haplotype analysis, which used 13 SNPs located in D-loop, COX2, ND5, CYTB, and non coding regions, revealed that KNC showed clearly different haplotypes that may be used to distinguish KNC from other breeds as well as to characterize individual identifications. The phylogenetic analysis revealed that KNC showed a relatively close genetic distance with Japanese black cattle (JBC) comparing with other breeds. Estimations of the average nucleotide diversity (0.0008) and the ratio of transition/ transversion (0.1050) of KNC were placed somewhere in the middle of genetic diversity among cattle breeds. The identified genetic variants and results of phylogenetic analysis will help understanding the phylogenetic relationships of KNC and provide useful genetic information for further studies regarding SNPs in mtDNA regions.

关键词： mtDNA Cattle SNP Haplotype Genetic Distance

Associations of Single Nucleotide Polymorphisms in the Bovine <i>FADS</i>6 Gene with Fatty Acid Composition in Hanwoo (Korean Cattle)

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Open Journal of Genetics 2015年第4期5卷 137-144页

作者： Krishnamoorthy Srikanth Anam Kwan Eunjin Lee Seonkwan Kim Youngjo Lim Hoyoung Chung Animal genomics and bioinformatics division National Institute of Animal Science Jeonju South Korea

The bovine fatty acid desaturase (FADS) gene cluster consists of FADS1, FADS2, FADS3, and FADS6, which acts as key enzymes in fatty acid metabolism. Of these, the genetics effects of variants in FADS1, FADS2 and FADS3 have been previously studied. However, the genetic effects of variants of FADS6 gene have not been studied. The aim of this study was to identify genetic variants in the bovine fatty acid desaturase 6 (FADS6) gene and study their association with fatty acid composition in Hanwoo cattle. Six genetic variants were observed, three each in intron 2 and exon 6 by DNA sequencing analyses. The association of genetic variants with fatty acid composition was evaluated in 90 Hanwoo steers. The variants were confirmed and the animals were genotyped by RFLP (Restriction Fragment Length Polymorphism) and AS-PCR (Allele Specific PCR) analyses. The analysis revealed that palmitoleic acid (C16:1n7) was associated with g.3391G > A, g.3660A > C and g.15657C > T, and stearic acid (C18:0) showed highly significant association with g.3660A > C segments. Both g.3391G > A, g.3660A > C also had strong additive and dominance effect for Palmitoleic acid, while g.3660A > C also had a strong dominance effect for stearic acid. These results could be useful for modulating fatty acid composition in beef and produce meat with higher monounsaturated fatty acid to saturated fatty acid ratio (MUFA/SFA), which had been shown to have positive health effect in humans.

关键词： Fatty Acid Composition Beef FADS6 Genetic Association SNP

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients

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genomics, Proteomics & bioinformatics 2016年第5期14卷 314-324页

作者： Lianshuo Li Zicheng Wang Peng He Shining Ma Jie Du Rui Jiang MOE Key Laboratory of bioinformatics and bioinformatics division TNLIST/Department of Automation Tsinghua University Beijing Anzhen Hospital Capital Medical UniversityBeijing Institute of HeartLungand Blood Vessel Diseases

Although networks of microbial species have been widely used in the analysis of 16S rRNA sequencing data of a microbiome, the construction and analysis of a complete microbial gene network are in general problematic because of the large number of microbial genes in metagenomics studies. To overcome this limitation, we propose to map microbial genes to functional units, including KEGG orthologous groups and the evolutionary genealogy of genes： Non-supervised Orthologous Groups （eggNOG） orthologous groups, to enable the construction and analysis of a microbial functional network. We devised two statistical methods to infer pairwise relationships between microbial functional units based on a deep sequencing dataset of gut microbiome from type 2 diabetes （T2D） patients as well as healthy controls. Networks containing such functional units and their significant interactions were constructed subsequently. We conducted a variety of analyses of global properties, local properties, and functional modules in the resulting functional networks. Our data indicate that besides the observations consistent with the current knowledge, this study provides novel biological insights into the gut microbiome associated with T2D.

关键词： Functional networkMicrobiome Type 2 diabetes Metagenomics Network motif

Computational Identification of 99 Insect MicroRNAs Using Comparative genomics

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Tsinghua Science and Technology 2008年第4期13卷 425-432页

作者：何涛李非古槿李瑞强李飞 bioinformatics division Tsinghua National Laboratory for Information Science and Technology (TNLIST) Department of Automation Tsinghua University Beijing 100084 China Beijing genomics Institute Chinese Academy of Sciences Beijing 100084 China bioinformatics division Tsinghua National Laboratory for Information Science and Technology (TNLIST) Department of Automation Tsinghua University Beijing 100084 China Department of Entomology College of Plant Pro-tection Nanjing Agricultural University Nanjing 210095 China

In recent years, much effort has been made in identifying microRNA （miRNA） genes from mammals insects, worms, plants, and viruses. Continuing the search for more miRNA genes is still important but difficult. This paper presents a computational strategy based on comparative genomics analysis. The algorithm was used to scan four invertebrate genomes, Drosophila melangoster, Bombyx mori, Apis mellifera, and Anopheles gambiae, which are either model organisms or medically/economically important insects. 99 new miRNA genes were predicted from the four insect species which can be grouped into 17 miRNA gene families, of which 10 of the miRNA families are insect-specific. Sequence similarity analysis showed that 16 of the newly predicted insect miRNAs belong to the K-box, GY-box, and Brd-box miRNA families which are important participators in Notch-related pathways. To test the validity of the algorithm, 39 predicted insect miRNA genes from D. melangoster and A. mellifera were selected for further biological validation. 34 （87%） predicted miRNA genes＇ transcripts were successfully detected by reverse transcription-polymerase chain reaction experiments. Thus, this strategy can be used to efficiently screen for miRNA genes conserved cross species.

关键词： microRNA (miRNA) insect comparative genomics reverse transcription-polymerase chain reaction