GSA:Genome Sequence Archive

With the rapid development of sequencing technologies towards higher throughput and lower cost, sequence data are generated at an unprecedentedly explosive rate. To provide an efficient and easy-to-use platform for managing huge sequence data, here we present Genome Sequence Archive （GSA; http：//bigd.big.ac.cn/gsa or http：//gsa.big.ac.cn）, a data repository for archiving raw sequence data. In compliance with data standards and structures of the International Nucleotide Sequence Database Collaboration （INSDC）, GSA adopts four data objects （BioProject, BioSample, Experiment, and Run） for data organization, accepts raw sequence reads produced by a variety of sequencing platforms, stores both sequence reads and metadata submitted from all over the world, and makes all these data publicly available to worldwide scientific communities. In the era of big data, GSA is not only an important complement to existing INSDC members by alleviating the increasing burdens of handling sequence data deluge, but also takes the significant responsibility for global big data archive and provides free unrestricted access to all publicly available data in support of research activities throughout the world.

A Brief Review on the Human Encyclopedia of DNA Elements (ENCODE) Project

The ENCyclopedia Of DNA Elements （ENCODE） project is an international research consortium that aims to identify all functional elements in the human genome sequence. The second phase of the project comprised 1640 datasets from 147 different cell types, yielding a set of 30 publications across several journals. These data revealed that 80.4% of the human genome displays some functionality in at least one cell type. Many of these regulatory elements are physically asso- ciated with one another and further form a network or three-dimensional conformation to affect gene expression. These elements are also related to sequence variants associated with diseases or traits. All these findings provide us new insights into the organization and regulation of genes and genome, and serve as an expansive resource for understanding human health and disease.

Global transcriptome analysis for identification of interactions between coding and noncoding RNAs during human erythroid differentiation

Studies on coding genes, miRNAs, and lncRNAs during erythroid development have been performed in recent years. However, analysis focusing on the integration of the three RNA types has yet to be done. In the present study, we compared the dynamics of coding genes, miRNA, and IncRNA expression profiles. To explore dynamic changes in erythropoiesis and potential mechanisms that control these changes in the transcriptome level, we took advantage of high throughput sequencing technologies to obtain transcriptome data from cord blood hematopoietic stem cells and the following four erythroid differentiation stages, as well as from mature red blood cells. Results indicated that lncRNAs were promising cell marker candidates for erythroid differentiation. Clustering analysis classified the differentially expressed genes into four subtypes that corresponded to dynamic changes during sternness maintenance, mid-differentiation, and maturation. Integrated analysis revealed that noncoding RNAs potentially participated in controlling blood cell maturation, and especially associated with heine metabolism and responses to oxygen species and DNA damage. These regulatory interactions were displayed in a comprehensive network, thereby inferring correlations between RNAs and their associated functions. These data provided a substantial resource for the study of normal erythropoiesis, which will permit further investigation and understanding of erythroid development and acquired erythroid disorders.

Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome

To unravel the genetic mechanisms of disease and physiological traits,it requires comprehensive sequencing analysis of large sample size in Chinese populations.Here,we report the primary results of the Chinese Academy of Sciences Precision Medicine Initiative(CASPMI)project launched by the Chinese Academy of Sciences,including the de novo assembly of a northern Han reference genome(NH1.0)and whole genome analyses of 597 healthy people coming from most areas in China.Given the two existing reference genomes for Han Chinese(YH and HX1)were both from the south,we constructed NH1.0,a new reference genome from a northern individual,by combining the sequencing strategies of PacBio,10×Genomics,and Bionano mapping.Using this integrated approach,we obtained an N50 scaffold size of 46.63 Mb for the NH1.0 genome and performed a comparative genome analysis of NH1.0 with YH and HX1.In order to generate a genomic variation map of Chinese populations,we performed the whole-genome sequencing of 597 participants and identified 24.85 million(M)single nucleotide variants(SNVs),3.85 M small indels,and 106,382 structural variations.In the association analysis with collected phenotypes,we found that the T allele of rs1549293 in KAT8 significantly correlated with the waist circumference in northern Han males.Moreover,significant genetic diversity in MTHFR,TCN2,FADS1,and FADS2,which associate with circulating folate,vitamin B12,or lipid metabolism,was observed between northerners and southerners.Especially,for the homocysteine-increasing allele of rs1801133(MTHFR 677T),we hypothesize that there exists a “comfort”zone for a high frequency of 677T between latitudes of 35–45 degree North.Taken together,our results provide a high-quality northern Han reference genome and novel population-specific data sets of genetic variants for use in the personalized and precision medicine.

Characterization of miRNomes in Acute and Chronic Myeloid Leukemia Cell Lines

Myeloid leukemias are highly diverse diseases and have been shown to be associated with microRNA（miRNA） expression aberrations. The present study involved an in-depth miRNome analysis of two human acute myeloid leukemia（AML） cell lines, HL-60 and THP-1, and one human chronic myeloid leukemia（CML） cell line, K562, via massively parallel signature sequencing. mRNA expression profiles of these cell lines that were established previously in our lab facilitated an integrative analysis of miRNA and mRNA expression patterns. miRNA expression profiling followed by differential expression analysis and target prediction suggested numerous miRNA signatures in AML and CML cell lines. Some miRNAs may act as either tumor suppressors or oncomiRs in AML and CML by targeting key genes in AML and CML pathways. Expression patterns of cell type-specific miRNAs could partially reflect the characteristics of K562, HL-60 and THP-1 cell lines, such as actin filament-based processes, responsiveness to stimulus and phagocytic activity. miRNAs may also regulate myeloid differentiation, since they usually suppress differentiation regulators. Our study provides a resource to further investigate the employment of miRNAs in human leukemia subtyping, leukemogenesis and myeloid development. In addition, the distinctive miRNA signatures may be potential candidates for the clinical diagnosis, prognosis and treatment of myeloid leukemias.

An RNA-seq-based Gene Expression Profiling of Radiation-induced Tumorigenic Mammary Epithelial Cells

Immortality and tumorigenicity are two distinct characteristics of cancers. Immortalization has been suggested to precede tumorigenesis. To understand the molecular mechanisms of tumorigenicity and cancer progression in mammary epithelium, we established a tumori- genic cell model by means of heavy-ion radiation of an immortal cell model, which was created by overexpressing the human telomerase reverse transcriptase （hTERT） in normal human mammary epithelial cells. We examined the expression profile of this tumorigenic cell line （T hMEC） using the hTERT-overexpressing immortal cell line （IhMEC） as a control. In-depth RNA-seq data was generated by using the next-generation sequencing （NGS） platform （Life Technologies SOLID3）. We found that house-keeping （HK） and tissue-spe- cific （TS） genes were differentially regulated during the tumorigenic process. HK genes tended to be activated while TS genes tended to be repressed. In addition, the HK genes and TS genes tended to contribute differentially to the variation of gene expression at different RPKM （gene expression in reads per exon kilobase per million mapped sequence reads） levels. Based on transcriptome analysis of the two cell lines, we defined 7053 differentially-expressed genes （DEGs） between immortality and tumorigenicity. Differential expression of 20 manually-selected genes was further validated using qRT-PCR. Our observations may help to further our understanding of cellular mechanism（s） in the transition from immortalization to tumorigenesis.

Mapping Human Pluripotent Stem Cell-derived Erythroid Differentiation by Single-cell Transcriptome Analysis

There is an imbalance between the supply and demand of functional red blood cells(RBCs)in clinical applications.This imbalance can be addressed by regenerating RBCs using several in vitro methods.Induced pluripotent stem cells(iPSCs)can handle the low supply of cord blood and the ethical issues in embryonic stem cell research,and provide a promising strategy to eliminate immune rejection.However,no complete single-cell level differentiation pathway exists for the iPSC-derived erythroid differentiation system.In this study,we used iPSC line BC1 to establish a RBC regeneration system.The 10X Genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectory on day 14 of the regeneration system.We observed that iPSC differentiation was not synchronized during embryoid body(EB)culture.The cells(on day 14)mainly consisted of mesodermal and various blood cells,similar to the yolk sac hematopoiesis.We identified six cell classifications and characterized the regulatory transcription factor(TF)networks and cell-cell contacts underlying the system.iPSCs undergo two transformations during the differentiation trajectory,accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes.We identified erythroid cells at different stages,such as burst-forming unit erythroid(BFU-E)and orthochromatic erythroblast(ortho-E)cells,and found that the regulation of TFs(e.g.,TFDP1 and FOXO3)is erythroid-stage specific.Immune erythroid cells were identified in our system.This study provides systematic theoretical guidance for optimizing the iPSC-derived erythroid differentiation system,and this system is a useful model for simulating in vivo hematopoietic development and differentiation.

Transcriptome Analysis of Monozygotic Twin Brothers with Childhood Primary Myelofibrosis

Primary myelofibrosis （PMF） is a chronic myeloproliferative disorder in human bone marrow. Over 50% of patients with myelofibrosis have mutations in JAK2, MPL, or CALR. However, these mutations are rarely detected in children, suggesting a difference in the pathogenesis of childhood PMF. In this study, we investigated the response to drug treatment of a monozygotic twin pair with typical childhood PMF. The twin exhibited different clinical outcomes despite following

Biomarker Profiling for Lupus Nephritis

Lupus nephritis （LN） is one of the most severe manifestations of systemic lupus erythematosus （SLE）, which is associated with significant morbidity and mortality of SLE patients. The pathogenesis of LN involves multiple factors, including genetic predisposition, epigenetic regulation and environmental interaction. Over the last decade, omics-based techniques have been extensively utilized for biomarker screening and a wide variety of variations which are associated with SLE and LN have been identified at the levels of genomics, transcriptomics and proteomics. These studies and discoveries have expanded our understanding of the molecular basis of the disease and are important for identification of potential therapeutic targets for disease prediction and early treat- ment. In this review, we summarize some of the recent studies targeted at the identification of LN-associated biomarkers using genomics and proteomic approaches.

Databases and Web Tools for Cancer Genomics Study

Publicly-accessible resources have promoted the advance of scientific discovery. The era of genomics and big data has brought the need for collaboration and data sharing in order to make effective use of this new knowledge. Here, we describe the web resources for cancer genomics research and rate them on the basis of the diversity of cancer types, sample size, omics data comprehensiveness, and user experience. The resources reviewed include data repository and analysis tools; and we hope such introduction will promote the awareness and facilitate the usage of these resources in the cancer research community.

Big Data and the Brain: Peeking at the Future

The era of brain science across the world The human brain is the most complex organ in the human body.It comprises billions of neurons and supporting cells in a complex network,managing everything from physical functions to thoughts and feelings of humans.Dysfunctions of the complex network caused by both genetic and environmental factors result in many brain disorders.Several large brain projects have been launched,aiming to understand how the brain works in health and disease,including the Human Brain Project of the European Union,the Brain Research through Advancing Innovative Neurotechnologies(BRAIN)Initiative of the United States,and the Brain Mapping by Integrated Neurotechnologies for Disease Studies(Brain/MIND)project of Japan.

GliomaDB: A Web Server for Integrating Glioma Omics Data and Interactive Analysis

Gliomas are one of the most common types of brain cancers.Numerous efforts have been devoted to studying the mechanisms of glioma genesis and identifying biomarkers for diagnosis and treatment.To help further investigations,we present a comprehensive database named GliomaDB.GliomaDB includes 21,086 samples from 4303 patients and integrates genomic,transcriptomic,epigenomic,clinical,and gene-drug association data regarding glioblastoma multiforme(GBM)and low-grade glioma(LGG)from The Cancer Genome Atlas(TCGA),Gene Expression Omnibus(GEO),the Chinese Glioma Genome Atlas(CGGA),the Memorial Sloan Kettering Cancer Center Integrated Mutation Profiling of Actionable Cancer Targets(MSK-IMPACT),the US Food and Drug Administration(FDA),and Pharm GKB.GliomaDB offers a user-friendly interface for two main types of functionalities.The first comprises queries of(i)somatic mutations,(ii)gene expression,(iii)microRNA(miRNA)expression,and(iv)DNA methylation.In addition,queries can be executed at the gene,region,and base level.Second,GliomaDB allows users to perform survival analysis,coexpression network visualization,multi-omics data visualization,and targeted drug recommendations based on personalized variations.GliomaDB bridges the gap between glioma genomics big data and the delivery of integrated information for end users,thus enabling both researchers and clinicians to effectively use publicly available data and empowering the progression of precision medicine in glioma.GliomaDB is freely accessible at http://bigd.big.ac.cn/glioma DB.

Gene Regulatory Networks in the Genomics Era

The precise regulation of gene expression is critical to the nor- mal development and biological function of all organisms. Dysregulation of gene expression during early development can result in a spectrum of failures ranging from minor defects to the termination of development. In adult life, dysregulation can lead to the uncontrolled cell proliferation of cancer or pro- grammed cell death leading to neurodegenerative diseases. The regulation of gene expression is controlled by multiple systems with more being discovered. The immediate regulators are transcription factors which bind to specific sequences in the promoter or enhancer regions of individual genes. The activity of transcription factors can be regulated by the presence of other transcription factors and cofactors, methylation status of the promoter or enhancer region,

Long noncoding RNA PCED1B-AS1 promotes erythroid differentiation coordinating with GATA1 and chromatin remodeling

Erythropoiesis is a complex and sophisticated multi-stage process regulated by a variety of factors,including the transcription factor GATA1 and non-coding RNA.GATA1 is regarded as an essential transcriptional regulator promoting transcription of erythroidspecific genes—such as long non-coding RNAs(lncRNA).Here,we comprehensively screened lncRNAs that were potentially regulated by GATA1 in erythroid cells.We identified a novel lncRNA—PCED1B-AS1—and verified its role in promoting erythroid differentiation of K562 erythroid cells.We also predicted a model in which PCED1B-AS1 participates in erythroid differentiation via dynamic chromatin remodeling involving GATA1.The relationship between lncRNA and chromatin in the process of erythroid differentiation remains to be revealed,and in our study we have carried out preliminary explorations.

Biological Databases for Hematology Research

With the advances of genome-wide sequencing technologies and bioinformatics approaches, a large number of datasets of normal and malignant erythropoiesis have been gener- ated and made public to researchers around the world. Collection and integration of these datasets greatly facilitate basic research and clinical diagnosis and treatment of blood disorders. Here we provide a brief introduction of the most popular omics data resources of normal and malignant hematopoiesis, including some integrated web tools, to help users get better equipped to perform common analyses. We hope this review will promote the awareness and facilitate the usage of public