Biological Databases for Hematology Research

Qian ZhangNan DingLu ZhangXuetong ZhaoYadong Yang Hongzhu QuXiangdong Fang*g

1CAS Key Laboratory of Genome Sciences and Information,Beijing Institute of Genomics,Chinese Academy of Sciences, Beijing 100101,China

2University of Chinese Academy of Sciences,Beijing 100049,China

Biological Databases for Hematology Research

Qian Zhang1,a,Nan Ding1,b,Lu Zhang1,2,c,Xuetong Zhao1,2,d,Yadong Yang1,2,e, Hongzhu Qu1,f,Xiangdong Fang1,*,g

1CAS Key Laboratory of Genome Sciences and Information,Beijing Institute of Genomics,Chinese Academy of Sciences, Beijing 100101,China

2University of Chinese Academy of Sciences,Beijing 100049,China

Hematology;

Hematological diseases;

Omics data resources;

Database;

Bioinformatics

With the advances of genome-wide sequencing technologies andbioinformaticsapproaches,a large number of datasets of normal and malignant erythropoiesis have been generated 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 popularomics data resourcesof 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 publicdatabaseresources in thehematologyresearch.

Introduction

Blood is incredibly important in providing oxygen,protecting from infection,and healing after injury.Disorders of blood system lead to different kinds of hematological diseases in millions of people every year globally.Blood cells consist of three types of cells,namely erythrocytes(red blood cells,RBCs), leukocytes(white blood cells),and thrombocytes(platelets), all of which are differentiated and developed from hematopoietic stem cells(HSCs).Erythropoiesis normally produces functional RBCs[1],whereas erroneous erythropoiesis would lead to anemia,leukemia,and other blood diseases[2].

Recent advances in next-generation sequencing(NGS) technologies have provided outstanding platforms in blood research.In particular,single-cell sequencing technology makes it feasible to trace the HSC specifcation,cell fate decision,and differentiation into various cell types at single-cell resolution[3,4].In addition,high-throughput sequencing also allows genome-wide analysis of transcription factor binding and histone modifcations by chromatin immunoprecipitation sequencing(ChIP-seq)[5],identifcation of open regions of chromatin by DNase-Seq[5],as well as transcriptomic expression profles by RNA-Seq[5].Deeper understanding of the hematological processes of mammals has been driven by thedevelopment of these technologies[6].Large organizations, such as the National Center for Biotechnology Information (NCBI),and projects collaborated by international research groups,for example the Encyclopedia of DNA Elements (ENCODE),and a variety of individual laboratories have produced and released many genome-wide datasets to public[7]. Thanks to the increasingly deeper interpretation of the human genome and the development of bioinformatics databases,we have now appreciated the human erythropoiesis more.Here we collect the most popular omics data resources of normal and malignant hematopoiesis(Table 1).These data components and some integrated web tools for common analyses are introduced in this review.

European LeukemiaNet

Leukemia is a cancer of white blood cells with high incidence among all ages.To centralize the fragmented information of European leukemia,the European LeukemiaNet(ELN)was founded by the 6th Framework Program of the European Community in 2004[8].The website with friendly user interface delivers information about ongoing clinical trials to physicians and patients,as well as further information regarding leukemia research,such as via publishing study protocols.Meanwhile,ELN shares knowledge about study design and monitoring,as well as data management and analysis,and pushes forward the discussion on leukemia within Europe (http://www.leukemia-net.org/content/home/index_ eng.html).As many as 17 work packages work separately on information integration about research,diagnosis,and treatment of leukemia.Furthermore,ELN also provides information for patients and physicians to better understand the leukemia,the diagnostic methods,and different therapies available.

Red Cell Membrane Disorder Mutations Database

Red cellmembrane inherited disordersinvolveseither altered membrane structural organization or altered membrane transport function[9].The Red Cell Membrane Disorder Mutations Database(http://research.nhgri.nih.gov/ RBCmembrane/)contains the mutations associated with three major inherited blood disorders,namely hereditary spherocytosis,elliptocytosis,and pyropoikilocytosis,all of which are caused by the disorder of red cell membrane structural organization.The welcome page introduces the gene mutations associated with the three diseases,as well as the term linkages to the Online Mendelian Inheritance in Man(OMIM)database for related genes.This database provides detailed information of gene mutations occurring in one or more diseases in its submenu.In other submenus,users can also obtain additional detailed information about clinical research program and geneticcounselingfrom theNationalHuman Genome Research Institute(NHGRI),the United States.In addition, the submenus also provide the linkage to the University of California Santa Cruz(UCSC)database for some mutation genes.At the bottom of the menu,researchers can fnd the contact information if they have additions,updates,or descriptions of new mutations.

dbRBC

The dbRBC database is one of the NCBI database resources that provides an integrated and freely-accessible platform for DNA sequencing data and clinical data associated with the human RBCs(http://www.ncbi.nlm.nih.gov/projects/gv/ rbc/main.fcgi?cmd=init).It integrates the data from the Blood Group Antigen Gene Mutation Database(BGMUT) that records variations in genes encoding antigens for human blood groups from the NCBI[10].Users could obtain the data from the download menu that directly links to the page of fle transfer protocol.dbRBC homepage also offers the linkage to the parallel resources,such as dbMHC for data related to the human major histocompatibility complex (MHC)and dbLRC for resource available for human leukocyte receptor complex(LRC).These 3 public resources make up the database cluster for routine clinical applications[11], such as the ABO genotyping technology.Some additional practical tools are also provided,such as the Alignment Viewer and Primer Resource.

CODEX

CODEX(http://codex.stemcells.cam.ac.uk/)is a database of mouse and human NGS experiments.The aim of CODEX is to provide an open-resource of NGS experiments processed by uniform procedures.In this database,metadata of human and mouse samples from hematological experiments are collected and sequencing data are uniformly processed and vetted [12].CODEX also provides access to processed and curated NGS experiments,including ChIP-seq,RNA-seq,and DNase-seq.The main data sources of CODEX are NGS repositories,for instance,the Gene Expression Omnibus (GEO)and ArrayExpress.Besides,CODEX also provides a private site hosting non-published data.Furthermore,processed datasets can be analyzed online or downloaded. CODEX now covers data on 133 hematopoietic cells and embryonic stem cells,and 269 factors associated with these cells.

The Erythron Database

The Erythron Database(ErythronDB;http://www.cbil.upenn. edu/ErythronDB)was built to facilitate access to erythroid expression data and the analysis results in murine primitive and defnitive erythroid cells[13].ErythronDB allows users to identify differentially-expressed genes and custom-made downstream analysis in the strategy module.Users are also permitted to save and share strategies with other registered users.The database integrates global gene expression profle data of primitive,fetal liver defnitive,and adult bone marrow defnitive erythroid using Affymetrix array for each maturation stage.ErythronDB supports complex investigations on expression parameters,as well as the Gene Ontology(GO) and the Kyoto Encyclopedia of Genes and Genomes(KEGG) annotations.To ensure abundant knowledge on mouse genes, ErythronDB displays links to external databases,including the Mouse Genome Informatics(MGI).

Hembase

Hembase(http://hembase.niddk.nih.gov)provides genomebased access to human genes transcribed during erythropoiesis.By sequencing several thousand expressed sequence tags(ESTs)of human erythroid cells,including progenitor cells,precursor cells,and mature RBCs,the Hembase integrated these data to provide users a friendly browser and the genome portal.To date,the database contained 15,752 entries of ESTs and 380 genes associated with erythropoiesis[1]. Hembase provides cytogenetic band position as well as a unique name as concise annotations for each search entry. Users can search by gene name,keywords,or cytogenetic location.All the sequencing information in Hembase can be used without registration,and all ESTs can be downloaded from the NCBI UniGene Library Browser[14].

BloodSpot

BloodSpot(http://www.bloodspot.eu)is a database including gene expression profles of healthy and malignant hematopoiesis in humans or mice,which had been generated by oligonucleotide microarray chips and RNA sequencing[15].This platform is an improvement and expansion of HemaExplorer and encompasses more than 5000 samples in total[16].For each query gene or gene signature,BloodSpot provides three concomitant levels of visualization—gene expression,survival plot,and hierarchical tree of samples.Besides,BloodSpot also contains other built-in tools such as exploring the top correlated genes and calculating the student t-test signifcance between pairs of populations in the default expression plot. Another feature of BloodSpot is BloodPool,an assembled and integrated database collecting the results of multiple studies with more than 2000 samples focusing on acute myeloid leukemia(AML).

BloodChIP

The BloodChIP database (http://www.med.unsw.edu.au/ CRCWeb.nsf/page/BloodChIP) provides a user-friendly exploration and visualization of transcription factor(TF) binding sites in human CD34+and leukemia cells produced by TF ChIP-Seq platform[17].Users can enter the keywords about specifc gene(s)or genomic region(s)to retrieve TF binding profles.Users can also search all the target genes for a combination of selected TFs or for any selected TFs in specifc cell type(s).Currently,BloodChIP covers data on four cell types,i.e.,CD34+hematopoietic stem and progenitor cells (HSPCs),megakaryocytes,SKNO-1,and K562.To maximize the utility of these data,this database has been integrated with many public data for insights into the transcriptional regulation of query genes,such as gene expression data,histone ChIP-seq data,and DNase-seq data from the Human Epigenome Atlas and ENCODE database[7,18].

Leukemia Gene Atlas

Leukemia Gene Atlas(LGA)database is a public platform integrating diverse genomic data published in the leukemia feld[19].The LGA supports comprehensive research,analysis, and browse functions for more than 5800 leukemia and hematopoiesis samples sequenced by multiple platforms,such as microarray,DNA methylation,SNP,and otherhighthroughput sequencing manners.The database contains information on studies from various aspects,such as prediction of molecular subtypes of leukemia,human hematopoiesis,and TF binding sites imported from the GEO.LGA also has established quality control procedure to flter out qualifed data imported from other datasets.Results of each study include differentially-expressed genes,GO annotations,copy number alterations,and an extract of the Catalogue of Somatic Mutations in Cancer(COSMIC)database.The LGA database is freely accessible at http://www.leukemia-gene-atlas.org/ LGAtlas/.

Diamond-Blackfan anemia mutation database

Diamond-Blackfan anemia(DBA)is a hereditary bone marrow failure syndrome characterized by the marked heterogeneity of clinical symptom,such as anemia,developmental abnormalities,and an increased risk of malignancy[20-22]. The DBA mutation database was built aimed to help researchers and physicians to better understand the mutations found in patients.This database is based on the Leiden Open Variation Database(LOVD)system(http://www.dbagenes.unito.it).The database comprises of 27 published mutations in RPS11 gene, the main contributor to DBA.Each mutation is described in detail with both tables and graphs,including gene information, sequence information,and graphic displays from UCSC [23,24].The database provides information on changes in DNA,RNA,and protein,as well as the frequency of the mutations via a convenient search interface.Users are welcome to submit mutations after they register as a submitter.

Concluding remarks

Abnormal development of blood cells has been widely studied in the past several decades.Due to the recent technological advances,a large amount of data for erythrocyte differentiation has been generated,producing valuable resources for understanding pathogenesis.This review offers a brief introduction of multiple databases in the felds of hematopoiesis and blood diseases(Figure 1),all of which are freely available without any registration.The majority of databases,namely Red Cell Membrane Disorder Mutations Database,dbRBC, CODEX,ErythronDB,Hembase,BloodSpot,and BloodChIP focus on the normal erythrocyte development in humans and model organisms to provide transcriptomic and genomic data. On the other hand,ELN and LGA are databases in the feld of leukemia with clinical resources,whereas DBA mutation database is specifcally designed for DBA.Obviously,despite our efforts on hematopoiesis studies,the sample sizes covered in the databases reviewed in this article are still limited and there is also lack of databases for other blood diseases.Fortunately, benefting from big data programs across the globe,people are getting aware of the importance of biological data to public health,which makes it easier for researchers to obtain data generated from a large number of patients or donors. With the accumulation of knowledge and research progress,we are expecting to see a number of databases combined with clinical data available for biologists and clinicians in near future.

Figure 1 Integrated fgure of database in the felds of hematopoiesis and blood diseases

Competing interests

The authors declared that there are no competing interests.

Acknowledgments

This study was supported by the National Key Research and Development Program of China (Grant No. 2016YFC0901700),the National High-tech R&D Program of China(863 Program,GrantNos.2015AA020101 and 2015AA020108),the National‘12th Five-Year Plan”for Science& TechnologySupportofChina(GrantNo. 2013BAI01B09),and the National Natural Science Foundation of China(Grant Nos.31471115 and 81670109)awarded to XF.

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Received 29 September 2016;accepted 13 October 2016 Available online 11 December 2016

Handled by Ao Li

*Corresponding author.

E-mail:fangxd@big.ac.cn(Fang X).

aORCID:0000-0003-4580-171X.

bORCID:0000-0002-1045-1695.

cORCID:0000-0001-7313-4972.

dORCID:0000-0002-3019-8615.

eORCID:0000-0003-2936-1574.

fORCID:0000-0001-7013-8409.

gORCID:0000-0002-6628-8620.

Peer review under responsibility of Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China.

http://dx.doi.org/10.1016/j.gpb.2016.10.004

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