D24–D33 Nucleic Acids Research, 2020, Vol. 48, Database issue Published online 8 November 2019
doi: 10.1093/nar/gkz913
Database Resources of the National Genomics Data
Center in 2020
National Genomics Data Center Members and Partners*,†
Received September 15, 2019; Revised September 30, 2019; Editorial Decision October 01, 2019; Accepted October 02, 2019
ABSTRACT
The National Genomics Data Center (NGDC) provides
a suite of database resources to support worldwide
research activities in both academia and industry.
With the rapid advancements in higher-throughput
and lower-cost sequencing technologies and accordingly
the huge volume of multi-omics data generated
at exponential scales and rates, NGDC is continually
expanding, updating and enriching its core database
resources through big data integration and valueadded
curation. In the past year, efforts for update
have been mainly devoted to BioProject, BioSample,
GSA, GWH, GVM, NONCODE, LncBook, EWAS
Atlas and IC4R. Newly released resources include
three human genome databases (PGG.SNV, PGG.Han
and CGVD), eLMSG, EWAS Data Hub, GWAS Atlas,
iSheep and PADS Arsenal. In addition, four web services,
namely, eGPS Cloud, BIG Search, BIG Submission
and BIG SSO, have been significantly improved
and enhanced. All of these resources along
with their services are publicly accessible at https:
//bigd.big.ac.cn.
INTRODUCTION
The National Genomics Data Center (NGDC), officially
approved by the Ministry of Science & Technology and the
Ministry of Finance of the People’s Republic of China in
June 2019, is a national-level center dedicated to advancing
life and health sciences by archiving, managing and processing
a wide range of genomics related data. NGDC is established
based on the BIG Data Center (1–3) at Beijing Institute
of Genomics (BIG) of Chinese Academy of Sciences
(CAS), jointly in close collaboration with two CAS institutions,
namely, Institute of Biophysics (IBP) and Shanghai
Institute of Nutrition and Health (SINH). Considering the
rapid advancements in higher-throughput and lower-cost
sequencing technologies, huge amounts of multi-omics data
are generated at ever-growing rates and scales. Therefore,
the primary mission of NGDC is to build archive platforms
and information systems, develop advanced algorithms and
tools to translate big data into big discovery, and provide
open access to a suite of database resources in support of
research activities of global users from both academia and
industry.
During the past year, NGDC has expanded, updated
and enriched the amount and type of data through big
data integration and value-added curation, particularly
by close collaboration with IBP and SINH, with significant
improvements and advances over the previous release.
In terms of data attribute and curation intensity,
database resources in NGDC can be generally divided into
three categories: Data––raw sequence data and metadata,
Information––value-added standardized information, and
Knowledge––curated knowledge and knowledge graphs.
Here, we provide a brief summary of new developments
and recent updates, and describe the core resources and services
of NGDC (Figure 1). All resources, along with their
services, are publicly accessible through the home page of
NGDC at https://bigd.big.ac.cn.
NEW DEVELOPMENTS
Human genome resources
PGG.SNV (http://www.pggsnv.org) (4) is a human genome
database, which gives much higher weight to previously
under-investigated indigenous populations in Asia, as these
genomes harbor an enormous number of variants that have
not been observed in the extensively studied populations
of European ancestry. In the current version, PGG.SNV
archives 265 million single nucleotide variants (SNVs)
across 220 147 present-day human genomes and 1018 ancient
genomes and estimates their frequencies in 977 diverse
populations, including 1009 newly sequenced genomes rep*To
whom correspondence should be addressed: Zhang Zhang. Tel: +86 10 84097261; Fax: +86 10 84097720; Email: zhangzhang@big.ac.cn
Correspondence may also be addressed to Wenming Zhao. Email: zhaowm@big.ac.cn
Correspondence may also be addressed to Jingfa Xiao. Email: xiaojingfa@big.ac.cn
Correspondence may also be addressed to Yiming Bao. Email: baoym@big.ac.cn
Correspondence may also be addressed to Shunmin He. Email: heshunmin@ibp.ac.cn
Correspondence may also be addressed to Guoqing Zhang. Email: gqzhang@picb.ac.cn
Correspondence may also be addressed to Yixue Li. Email: yxli@sibs.ac.cn
Correspondence may also be addressed to Guoping Zhao. Email: gpzhao@sibs.ac.cn
Correspondence may also be addressed to Runsheng Chen. Email: crs@sun5.ibp.ac.cn
†
Full list provided in the Appendix.
C The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License
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Nucleic Acids Research, 2020, Vol. 48, Database issue D25
Figure 1. The National Genomics Data Center’s core data resources. Three
categories, namely, data, information and knowledge, are adopted to represent
resources that are typically to deposit raw data/metadata (archives),
house value-added information (databases) and integrate validated knowledge
through literature curation (knowledgebases), respectively. It is noted
that there are several databases that are not introduced in this report,
namely, BioCode––Biological Tool Codes, GEN––Gene Expression Nebulas,
iDog––Integrated Resource for Dog. A full list of data resources,
which contains links to each resource, is available at https://bigd.big.ac.
cn/databases.
resenting 16 indigenous populations living in unusual environments
(e.g. tropical forests and highlands) in East Asia
and Southeast Asia. For each variant, PGG.SNV provides
various approaches to query SNV information and nine
types of annotations. In addition, PGG.SNV offers usersfriendly
interfaces for data browsing and search and is
equipped with an online tool for estimation of population
genetic diversity and evolutionary parameters.
PGG.Han (http://www.pgghan.org) (detailed in (5) in this
issue) is a population genome database, which serves as
the central repository of genomic data of the Han Chinese
Genomes Initiative (Phase I). PGG.Han archives wholegenome
sequencing or high-density genome-wide SNVs of
114 783 Han Chinese individuals (a.k.a. the Han100K),
representing geographical sub-populations covering 33 of
the 34 administrative divisions of China, as well as Singapore.
PGG.Han provides: (i) an interactive interface for visualization
of the fine-scale genetic structure of the Han
Chinese population; (ii) genome-wide allele frequency of
hierarchical sub-populations; (iii) ancestry inference for
individual samples and controlling population stratification
based on nested ancestry informative marker panels;
(iv) a population-structure-aware shared control for
genotype–phenotype association studies and (v) a HanChinese-specific
reference panel for genotype imputation.
Computational tools are implemented in PGG.Han and an
online user-friendly interface is provided for data analysis
and visualization.
The Chinese Genomic Variation Database (CGVD; https:
//bigd.big.ac.cn/cgvd) (detailed in (6) in this issue) is a genomic
variation database for Chinese populations. CGVD
is a sub-project of the CAS Precision Medicine Initiative
project (CASPMI) (7), with the aim to establish the CAS
professional cohort with whole-genome deep sequencing
(25–30×) and build precise reference genomes for different
Chinese sub-populations. In comparison with PGG.Han,
CGVD features high-coverage sequencing data of 991 individuals
of the CASPMI cohort and 301 Chinese individuals
from the 1000 Genome Project (1KGP). Accordingly, it
houses genomic variations of 48.30 million SNVs and 5.77
million small indels; in contrast to dbSNP (8), 28.49 million
(46.67%) SNVs and 2.25 million (31.88%) indels are novel,
indicating the advantage of deeper whole-genome sequencing
coverage or/and the heterogeneity of genetic background
in Chinese populations. Moreover, CGVD provides
star-allele frequencies of drug metabolism related genes that
are essential for pharmacogenomics studies in CASPMI
and 1KGP related populations. It also integrates curated
knowledge of genomic variation impacts on drug absorption,
distribution, metabolism, excretion and toxicity.
GWAS Atlas
GWAS Atlas (https://bigd.big.ac.cn/gwas) (detailed in (9)
in this issue) is a manually curated resource of genomewide
variant-trait associations in plants and animals. In
the current version, GWAS Atlas contains 75 467 varianttrait
associations for 614 traits across seven cultivated plants
(cotton, Japanese apricot, maize, rapeseed, rice, sorghum
and soybean) and two domesticated animals (goat and pig),
which were manually extracted and curated from 254 publications.
More importantly, associations and traits are annotated
and presented based on a set of ontologies (Plant
Trait Ontology, Animal Trait Ontology for Livestock, etc.).
Taken together, GWAS Atlas integrates high-quality curated
GWAS associations for animals and plants and accordingly
serves as a valuable resource for genetic research
of important traits and breeding application.
EWAS Data Hub
Over the past decade, a large amount of epigenetic
data, especially those sourced from DNA methylation
array, has been accumulated as a result of numerous
EWAS (epigenome-wide association study) projects. Hence,
we present EWAS Data Hub (https://bigd.big.ac.cn/ewas/
datahub) (detailed in (10) in this issue), a data hub for collecting
and normalizing DNA methylation array data as
well as archiving associated metadata. The current release
of EWAS Data Hub integrates a comprehensive collection
of DNA methylation array data from 75 344 samples. Based
on an effective normalization method to remove batch effects
among different datasets, EWAS Data Hub provides
high-quality reference DNA methylation profiles in terms
of different contexts, involving 81 tissues/cell types (that
contain 25 brain parts and 25 blood cell types), six ancestry
categories, and 67 diseases (including 39 cancers).
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D26 Nucleic Acids Research, 2020, Vol. 48, Database issue
iSheep
iSheep (https://bigd.big.ac.cn/isheep) is a specialized genomics
resource for sheep (Ovis aries), providing a wealth
of information on genotype and phenotype association,
domestication and climatic adaptation of domestic sheep
as well as their wild relatives. The current version of
iSheep houses 70 390 968 unique SNPs and 12 318 530
indels obtained from 2777 samples (including 355 samples
with whole-genome sequences, 1512 samples with 50KBeadChip
and 911 samples with 600K-BeadChip) and
provides comprehensive phenotypic information of 1459
worldwide sheep breeds. Meanwhile, iSheep offers an online
tool to investigate the variations between individuals
or among populations. Collectively, iSheep is a valuable genomics
resource for the sheep research community, helpful
to promote molecular breeding and farming industry for
improved production traits.
eLMSG
eLMSG (eLibrary of Microbial Systematics and Genomics;
http://www.biosino.org/elmsg) is a web microbial library
that integrates not only taxonomic information, but also genomic
information and phenotypic information (including
morphology, physiology, biochemistry and enzymology).
The taxonomic system of eLMSG is manually curated and
composed of all validly and some effectively published taxa.
For each taxon, the Latin name, taxon ID (NCBI taxonomy),
etymology, rank, lineage, the dates of effective and/or
valid publication, feature descriptions, nomenclature type
and references for the proposal and emendations during
the history of the taxon are presented. Besides these data,
the species taxa contain information about 16S rRNA gene
and/or genome sequences. All publicly available genome
data of each type species including both type and non-type
strains were collected, and if needed, re-annotated using the
standardized analysis pipeline. Furthermore, pan-genomic
data analyses were conducted for species with ≥5 genome
sequences available. Finally, for all type species, taxonomically
relevant phenotypic data were extracted and curated
from literatures, which were further indexed into eLMSG
as searchable and analyzable data records. Taken together,
eLMSG is a comprehensive web platform for studying microbial
systematics and genomics, potentially useful for better
understanding microbial taxonomy, natural evolutionary
processes and ecological relationships.
PADS Arsenal
PADS Arsenal (https://bigd.big.ac.cn/padsarsenal) (detailed
in this issue) is a comprehensive public database of
prokaryotic defense systems related genes (PADS). To address
the challenges of ever-increasing prokaryotic genomic
data and the progressive discovery of novel defense systems,
we develop PADS Arsenal for browsing, searching,
and analyzing various defense system genes. In the current
version, PADS Arsenal integrates 6 600 264 defense systems
genes, which belong to 18 defense systems, 63 701
genomes and 33 390 species of archaea and bacteria. In addition,
it supports defense system gene analysis by equipping
with an interactive online pipeline that includes sequence
homology search, multiple sequence alignment and
phylogenetic analysis. Meanwhile, PADS Arsenal provides
a presence-absence variation (PAV) analysis function to visualize
the dynamic variation of defense system genes. Collectively,
PADS Arsenal integrates a comprehensive collection
of defense system genes in archaea and bacteria and
thus provides valuable resources to facilitate development
of novel genome editing, engineering and regulation tools.
RECENT UPDATES
BioProject and BioSample
BioProject (https://bigd.big.ac.cn/bioproject) and BioSample
(https://bigd.big.ac.cn/biosample), designed in compliance
with INSDC (International Nucleotide Sequence
Database Collaboration; a joint initiative by DDBJ, EMBLEBI
and NCBI) standards, are two public repositories
of biological projects and biological samples, respectively.
They collect and store descriptive metadata and information
about biological projects and biological materials
used for experiments. By providing a centralized access
to all public projects and reciprocal links to their related
data, BioProject supports various projects in terms of data
types, ranging from genomic, transcriptomic, epigenomic
and metagenomic sequencing projects to genome-wide association
studies (GWAS) and variation analyses. Similarly,
BioSample serves as a centralized access to all public samples
and reciprocal links to BioProject as well as other relevant
database resources. In the past year, BioSample has
been significantly upgraded by adding the batch submission
functionality and allowing users to submit information
of multiple samples in a single table, which consequently
had greatly improved the efficiency of data submission. As
of August 2019, BioProject houses a total of 1248 biological
projects submitted by 734 users from 219 organizations
and BioSample includes a total of 87 107 samples from 482
species, presenting a dramatic increase in data submission
(Figure 2).
Genome Sequence Archive
As a public data repository for archiving raw sequence
reads, the Genome Sequence Archive (GSA; https://bigd.
big.ac.cn/gsa) (11) accepts data submissions from all over
the world and provides free access to all publicly available
data for global scientific communities. Over the past
year, GSA has been significantly enhanced by upgrading the
metadata submission functionality to enable batch submission
of experiments and runs in a single table. Till August
2019, GSA has archived a total of 55 057 Experiments and
59 566 Runs and housed >1200 Terabytes of submitted raw
sequence data (Figure 2), showing the doubled volume by
comparison with the previous release last August (namely,
∼580 TB). According to the statistics (https://bigd.big.ac.
cn/gsa/statistics), data housed in GSA were submitted from
150 organizations and reported in >100 scientific journals,
including Cell, Genome Research, Genomics Proteomics
Bioinformatics, Nature, Plant Cell and PNAS. More importantly,
GSA has been designated as supported repository
for genes and gene expression data by Elsevier. All released
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Nucleic Acids Research, 2020, Vol. 48, Database issue D27
NumberofBioSamples
NumberofBioProjects
Feb.2016
Sept.2016
Apr.2017
Nov.2017
Jun.2018
Jan.2019
Aug.2019
BioProject BioSample
90000
72000
54000
36000
18000
0
1400
1120
840
560
280
0
A
FileSize(TB)
NumberofExperiments/Runs
Experiment Run File Size
Feb.2016
Sept.2016
Apr.2017
Nov.2017
Jun.2018
Jan.2019
Aug.2019
1300
1040
780
520
260
0
64000
51200
38400
25600
12800
0
B
Figure 2. Statistics of data submissions to BioProject, BioSample, and
GSA. (A) Data statistics of BioProject and BioSample. (B) Data statistics
of Experiments and Runs as well as submitted files’ size in GSA. All
statistics are frequently updated and publicly available at https://bigd.big.
ac.cn/bioproject, https://bigd.big.ac.cn/biosample and https://bigd.big.ac.
cn/gsa.
data in GSA are publicly accessible and downloadable at
ftp://download.big.ac.cn/gsa/.
Genome Warehouse
The Genome Warehouse (GWH; https://bigd.big.ac.cn/
gwh) is a public archival resource housing genome-scale
data for a wide range of species. For each collected genome
assembly, GWH incorporates detailed descriptive information,
including metadata of biological sample, genome assembly,
sequence data and genome annotation, and offers
standardized quality control for genome sequence
and genome annotation. Notably, in this version, the sequences
of the northern Han reference genome (NH1.0;
GWHAAAS00000000) has been deposited in GWH, which
was de novo assembled with a contig N50 size of 3.6 Mb
and a scaffold N50 size of 46.63 Mb (see (7) for details). In
addition, GWH has been significantly upgraded by accepting
updated submissions (including both genome sequence
and updates of genome annotation) and improving web services
for data submission, release and sharing. In particular,
GWH provides data visualization for both genome sequence
and genome annotation powered by JBrowse (12)
and offers statistics and charts in light of assembly, genome,
sequencing platform, assembly method, organization and
download. Till September 2019, GWH has accepted 649
data submissions from organizations both nationally and
internationally and covered a broad diversity of species,
e.g. animals, plants, fungi, bacteria, archaea and viruses.
Among them, 133 genome assemblies have been publicly released
and reported in 19 international journals.
Genome Variation Map
The Genome Variation Map (GVM; https://bigd.big.ac.cn/
gvm) (13) is a public database of genome variations, including
single nucleotide polymorphisms (SNP) and small insertions
and deletions (indel). Different from dbSNP that only
accepts human data submissions, GVM collects genome
variations for a wide range of species and accepts submissions
of different types of genome variations from all over
the world. In the current version, GVM incorporates a total
of ∼8.4 billion variants for 13 animals and 19 plants, including
7.2 billion SNPs and 1.2 billion indels. By comparison
with the previous version, it has been updated by integrating
47 million variants from two newly added species (diploid
wheat and cat). In addition, GVM has accepted 24 genome
variation data submissions involving 23 056 samples from
10 species.
Non-coding RNA Resources
NONCODE (http://www.noncode.org) (14) is an integrated
knowledgebase dedicated to the complete collection and annotation
of non-coding RNAs (ncRNA). Almost all the
types of ncRNAs (excluding tRNAs and rRNAs) were
filtered automatically from literatures and other public
databases and were later manually curated. The ncRNA
sequences and their related information (such as chromosomal
information, conservation, function, etc.) were
collected and recorded. BLAST alignment search service
and access through our custom UCSC Genome Browser
were also incorporated. In the current version (v5.0), 17
species are included in NONCODE (human, mouse, cow,
rat, chicken, fruit fly, zebrafish, nematode, yeast, Arabidopsis,
chimpanzee, gorilla, orangutan, rhesus macaque, opossum
platypus and pig). Consequently, NONCODE collects
a total of 548,640 long ncRNAs (lncRNA), coupled with
their expression profiles identified based on RNA-seq data
for human and mouse as well as their predicted functions.
Moreover, it also includes human lncRNA–disease relationships
and SNP–lncRNA–disease relationships, human exosome
lncRNA expression profiles and predicted RNA secondary
structures of human transcripts.
NPInter (http://bigdata.ibp.ac.cn/npinter) (15) is a
database that documents experimentally identified functional
interactions between ncRNAs (except tRNAs
and rRNAs), especially lncRNAs, and protein related
biomacromolecules (proteins, mRNAs or genomic DNAs).
NPInter provides the scientific community with a comprehensive
and integrated tool for efficient browsing
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D28 Nucleic Acids Research, 2020, Vol. 48, Database issue
and extraction of information on interactions between
ncRNAs and biomolecules. With the development of
high-throughput biotechnology, such as cross-linking
immunoprecipitation (CLIP-seq) and Chromatin Isolation
by RNA purification (ChIRP-seq), the number of known
ncRNA interactions, has grown rapidly in recent years. In
the current release, NPInter houses 609 020 RNA-RNA interactions,
488 315 RNA–protein interactions and 892 737
RNA–DNA interactions, and provides more user-friendly
interfaces and functional modules.
piRBase (http://www.regulatoryrna.org/database/
piRNA/) (16) is a comprehensive database of piRNA
sequences, which are a class of small RNAs that is mainly
expressed in animal germ line. piRBase integrates various
piRNA-related high-throughput data in multiple species,
leading to the largest collection of piRNAs and their annotations.
Since its launch in 2014, piRBase has incorporated
264 datasets from 21 organisms and accordingly housed
a total of ∼173 million piRNAs up to now. Furthermore,
piRBase provides comprehensive annotations of piRNA
sequences and genomic loci as well as piRNA targets
and disease-related piRNAs. In addition, epigenetic and
post-transcriptional regulation data were systematically
integrated to support piRNA functional study.
LncBook (17) (https://bigd.big.ac.cn/lncbook) and LncRNAWiki
(18) (https://bigd.big.ac.cn/lncrnawiki), are two
dedicated resources of human lncRNAs, through expert curation
and community curation, respectively. In the past
year, LncBook has been updated by removing 1196 redundant
lncRNA transcripts and updating genomic annotations
of 1046 lncRNA transcripts. As a result, LncBook
provides a high-quality collection of 268 848 nonredundant
lncRNA transcripts and 140 356 lncRNA genes.
Also, LncBook presents tissue-specific lncRNAs (TS lncRNAs)
for different tissues; among the 32 tissues, testis has
the largest number of TS lncRNAs (9024 lncRNAs) and
the following tissue is brain (2297 lncRNAs). In addition,
LncBook is equipped with an online tool for coding potential
prediction, which is able to accurately identify lncRNAs
in a wide range of species (19). On the other side,
LncRNAWiki (18), a wiki-based platform for community
curation of human lncRNAs, has been updated by curating
291 human lncRNAs with functional experiment evidence,
including 149 newly added lncRNAs and 142 existing
lncRNAs with updated publications. Also, 65 redundant
lncRNAs based on the approved and alias symbols
(https://www.genenames.org) were removed. Consequently,
in the current release, the number of functionally validated
human lncRNAs in LncRNAWiki has grown to 1951. Together,
LncBook and LncRNAWiki are of great potential
to achieve comprehensive integration of human lncRNAs
and their annotations (20).
RNA Editing Resources
Editome Disease Knowledgebase (EDK; https://bigd.big.
ac.cn/edk) (21) and Plant Editosome Database (PED; https:
//bigd.big.ac.cn/ped) (22) are two RNA editing resources
for human and plants, respectively. In the updated version,
EDK incorporates two new diseases associated with 51 experimentally
validated abnormal editing events located in
six mRNAs, and 10 aberrant activities involved with two
editing enzymes. Furthermore, to provide an easy-to-use
and downloadable reference for further functional investigation
on individual RNA editing event, EDK incorporates
detailed structured annotation information for each
editing site, including gene, specific gene region, molecular
effect, editing enzyme, associated disease and/or phenotype.
As a featured database of RNA editosome in plants
(22,23), PED has been updated by integrating two more
editing factors, which had been recently verified to be involved
in RNA editing processes and related to important
phenotypes in Arabidopsis and new maize variety. Collectively,
EDK and PED integrate more valuable information
of editing enzymes (factors) and/or editing events associated
with phenotypes, so as to help users facilitate systematic
investigations on RNA editing machinery in both human
and plants.
MethBank
The Methylation Bank (MethBank; https://bigd.big.ac.cn/
methbank) (24,25) is a databank of genome-wide DNA
methylomes across a variety of species, with particular focus
on human health and aging, animal embryonic development
and plant growth and development. In the current
version, MethBank offers 43 consensus reference methylomes
(CRM) for human owing to large-scale DNA methylation
array data public available, which are sourced from
10 healthy human tissues including 4577 peripheral blood
samples, 26 prostate samples, 241 saliva samples, 322 skin
samples, 98 breast samples, 38 colon samples, 206 kidney
samples, 50 liver samples, 150 lung samples and 56 thyroid
samples. In addition to CRMs, MethBank provides
single-base resolution methylomes (SRM) based on wholegenome
bisulfite sequencing data from human, plants and
animals. Up to now, MethBank includes 40 SRMs from 26
healthy human tissues, 336 from different developmental
stages in five economical plants and 18 from gametes and
early embryos in two model animals. In addition, MethBank
provides useful information on methylation data analysis
tools, helpful for users to easily find any tool of interest.
EWAS Atlas
EWAS Atlas (https://bigd.big.ac.cn/ewas) (26) is a curated
knowledgebase of epigenome-wide association studies.
During the past year, it has been enriched by adding a
total of 121 156 EWAS associations manually extracted and
curated from 191 publications. It is noted that the MethylationEPIC
(850K/EPIC) array becomes increasingly popular,
so that the number of 850K-based publications in
EWAS Atlas has increased accordingly. In addition, the online
trait enrichment tool was further enhanced and EWAS
knowledge graph (https://bigd.big.ac.cn/ewas/network) was
newly developed to visualize and explore trait-gene networks.
Till September 2019, EWAS Atlas has integrated
450 328 high-quality EWAS associations derived from 1003
studies in 401 publications, including 135 tissues/cell lines,
409 traits, 2689 cohorts and 409 ontology entities.
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Nucleic Acids Research, 2020, Vol. 48, Database issue D29
Information Commons for Rice
Information Commons for Rice (IC4R; http://ic4r.org)
(27,28) is a comprehensive resource dedicated to integrating
multi-omics data for rice. To improve the completeness
of gene structure and identify novel genes, the current
implementation of IC4R incorporates a new gene annotation
system IC4R-2.0 that is built based on a large number
of 1503 public RNA-seq datasets, accordingly achieving
higher integrity and quality by comparison with previous
annotation systems. Specifically, IC4R-2.0 contains
56,221 protein-coding gene loci corresponding to 80 039
mRNAs, among which more than 27 000 gene loci are substantially
improved with structural modification, 456 novel
genes are identified, and 3215 lncRNAs and 4373 circular
RNAs are annotated. In addition, although IC4R offers a
high-density rice variation map of ∼18 million SNPs, these
raw SNPs are not readily usable for population genetics,
evolutionary analysis, association studies or genomic breeding
in rice. To satisfy various needs of rice researchers on
data mining of the integrated genotypic data, a committed
module––SnpReady for Rice (SR4R, http://sr4r.ic4r.org), is
developed and deployed in IC4R. SR4R features the lowest
SNP redundancy and highest genetic diversity of rice populations.
Currently, SR4R mainly integrates four reference
SNP panels, including ‘hapmapSNPs’ after data filtration
and genotype imputation, ‘tagSNPs’ selected from linkage
disequilibrium (LD)-based redundancy removal, ‘fixedSNPs’
selected from genes exhibiting selective sweep signatures,
and ‘barcodeSNPs’ selected from DNA fingerprinting
simulation. The associated SNPs in these four panels as
well as online toolkits are publicly available and download-
able.
LSD
The leaf senescence database (LSD; https://bigd.big.ac.cn/
lsd) (29,30) is dedicated to the comprehensive collection of
senescence-associated genes (SAGs) and their corresponding
mutants through manual curation. In the current version
(v3.0; see an update in (31) in this issue), LSD incorporates
5,853 SAGs and 617 mutants from 68 species. Notably,
it integrates leaf senescence-associated transcriptome
data in Arabidopsis, rice, soybean and poplar and identifies
senescence-differentially expressed small RNAs (SensmRNA)
in Arabidopsis. Moreover, LSD contains senescence
phenotypes of 90 natural accessions (ecotypes) and 42
images of ecotypes in Arabidopsis and collects mutant seed
information of SAGs in rice. Also, interaction pairs between
Sen-smRNAs and senescence-associated transcription factors
are integrated into LSD. Collectively, the updated LSD
has the great potential to continue to provide useful information
for the plant research community.
Database Commons
Database Commons (https://bigd.big.ac.cn/
databasecommons), a catalog of global biological
databases, provides open access to a comprehensive
collection of publicly available databases and their descriptive
metadata. Currently, it catalogues a total of 4615
databases, involving more than 7000 publications and
∼2000 organizations throughout the world. In the past
year, Database Commons has been updated by assigning
category tag(s) to each database, linking related databases
and providing citation information according to Europe
PMC (32). Importantly, to improve the quality of descriptive
metadata for each database, we sent invitations to
database owners (according to the publications) to call for
community curation of their own databases. As a result,
a total of 287 database owners have responded and made
valuable curations to 345 databases.
eGPS Cloud
eGPS Cloud (http://egpscloud.big.ac.cn) (33) is a multifunctional
web portal that integrates comprehensive multiomics
tools and provides online data analysis services
for studying evolutionary Genotype-Phenotype Systems
(eGPS). In the current release, eGPS Cloud is equipped
with 15 tools and 20 visualization scripts, accordingly delivering
four modularized web services, that is, genomics
data analysis, population data analysis, evolutionary & network
data analysis, and multi-omics data visualization. It
allows users to configure customized parameters for different
tools and perform various data analysis online in a
straightforward and friendly manner. Ongoing efforts are
linking eGPS Cloud with GSA in order to provide users
with seamless services for raw sequence data analysis.
BIG Search
BIG Search (https://bigd.big.ac.cn/search) is a distributed
and scalable full-text search engine built based on Elasticsearch
(a highly scalable open-source search and analytics
engine, https://www.elastic.co/). It features cross-domain
search and facilitates users to gain access to a wide range
of biological data almost in real-time. In the current version,
BIG Search includes data indexes from all NGDC’s
resources and 25 partner resources (see details at https:
//bigd.big.ac.cn/partners). Additionally, EBI data resources
have also been integrated into BIG Search powered by EBI
Search RESTful API (34). In summary, BIG Search has
been significantly updated by incorporating more data indexes
from internal and external resources and displaying
search results in a more user-friendly manner.
BIG Submission
BIG Submission (https://bigd.big.ac.cn/gsub) is a one-stop
submission portal that provides submission services for a
series of database resources in NGDC, including BioProject,
BioSample, GSA, GWH and GVM. During the past
year, BIG Submission has been upgraded by optimizing
the web interfaces and expanding the storage and computing
resources, with the purpose to meet the needs of
the rapid growth of data submissions. Importantly, it has
been equipped by Aspera, a high-speed transfer tool that
can greatly improve the data transfer efficiency and provide
users with better submission experiences.
BIG SSO
BIG Single Sign-On (SSO; https://bigd.big.ac.cn/sso) is a
user access control system that refers to systems where a sin-
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D30 Nucleic Acids Research, 2020, Vol. 48, Database issue
gle authentication provides access to multiple applications
by passing the authentication token seamlessly to configured
applications. In the past year, HTTPS protocols have
been deployed in all web sites for security transfer, so that
the BIG SSO system has been updated to be much safer and
more reliable. Meanwhile, services for user registration and
update have been enhanced and delivered as a micro-service.
CONCLUDING REMARKS
NGDC provides a family of database resources through big
data deposition, integration and translation, with the aim
to support worldwide research activities in both academia
and industry. In the past year, it has been significantly
updated by archiving more data submissions, performing
value-added curation, and improving web interfaces and
services. And most importantly, it has been enhanced as
the national center by joint efforts from BIG, IBP and
SINH, forming an excellent line-up of field experts from
the three institutions. Ongoing and future efforts are standardization
of data models and curation processes, unification
of web interfaces and SSO authentication across
database resources, establishment of cloud infrastructure
for big data storage and transfer, and development of a variety
of databases and tools to facilitate the translation of big
data into big discovery. NGDC is open to worldwide collaborations,
particularly seeking the possibility to collaborate
with INSDC members in dealing with big data archive. In
addition, NGDC promotes big data sharing at a worldwide
scale by setting up the Global Biodiversity and Health Big
Data Alliance (BHBD; http://bhbd-alliance.org); by July
2019, 20 organizational members from 11 countries have
joined the BHBD Alliance, with active collaborations in organizing
international meetings/symposia, training courses
and joint research projects. With more stable support from
the government and CAS, NGDC will continue to grow to
deliver a wide range of data resources and services in aid of
both domestic and international research activities.
ACKNOWLEDGEMENTS
We thank a number of users for submitting data, sending
suggestions, reporting bugs and getting involving in community
curation. The National Genomics Data Center is
indebted to its funders, including the Ministry of Science &
Technology and the Ministry of Finance of the People’s Republic
of China as well as Chinese Academy of Sciences. We
would like to express our sincere thanks to the late Professor
Bailin Hao (1934–2018), a leading bioinformatician of
his generation, who had first advocated the establishment
of national center since the 1990s.
FUNDING
Strategic Priority Research Program of the Chinese
Academy of Sciences [XDA19050302, XDB13040500,
XDB13040100]; National Key Research & Development
Program of China [2018YFD1000505, 2018YFC2000100,
2018YFC1406902, 2018YFC0910400, 2018YFC0310602,
2017YFC1201200, 2017YFC0908405, 2017YFC0908404,
2017YFC0908403, 2017YFC0907505, 2017YFC0907503,
2017YFC0907502, 2016YFE0206600, 2016YFC0906403,
2016YFC0903003, 2016YFC0901904, 2016YFC0901903,
2016YFC0901702, 2016YFC0901604, 2016YFC0901603,
2016YFB0201702]; National Natural Science Foundation
of China [91731303, 81670462, 31970565, 31871328,
31871294, 31801104, 31771465, 31771410, 31771388,
31671360, 31571358, 31525014, 1470330, 31961130380,
31711530221]; UK Royal Society-Newton Advanced
Fellowship [NAF\R1\191094]; International Partnership
Program of the Chinese Academy of Sciences
[153F11KYSB20160008, 153D31KYSB20170121]; 13th
Five-year Informatization Plan of Chinese Academy of
Sciences [XXH13505-05]; Key Program of the Chinese
Academy of Sciences [KJZD-EW-L14]; Key Research
Program of Frontier Sciences of the Chinese Academy of
Sciences [QYZDJ-SSW-SYS009]; Key Technology Talent
Program of the Chinese Academy of Sciences; The 100
Talent Program of the Chinese Academy of Sciences;
K.C. Wong Education Foundation; The Youth Innovation
Promotion Association of the Chinese Academy of Sciences
[2019104, 2018134, 2017141]; The Special Project on
Precision Medicine under the National Key R&D Program
[SQ2017YFSF090210]; The Open Biodiversity and Health
Big Data Initiative of IUBS. Funding for open access
charge: Strategic Priority Research Program of the Chinese
Academy of Sciences.
Conflict of interest statement. None declared.
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APPENDIX
Corresponding author: Zhang Zhang1,2,3,10,11,*
Co-corresponding authors: Wenming Zhao1,2,3,10,*
, Jingfa
Xiao1,2,3,10,*
, Yiming Bao1,2,3,10,11,*
, Shunmin He1,4,10,*
,
Guoqing Zhang1,5,*
, Yixue Li1,5,*
, Guoping Zhao1,5,6,7,*
,
Runsheng Chen1,4,10,*
NGDC MEMBERS (Arranged by project role and then by
contribution except for Team Leader (TL), as indicated)
PGG.Han: Yang Gao5,#
, Chao Zhang5,#
, Liyun Yuan5,#
,
Guoqing Zhang1,5,*
(TL), Shuhua Xu5,14,15,16
(TL)
PGG.SNV: Chao Zhang5,#
, Yang Gao5,#
, Zhilin Ning5,#
,
Yan Lu5,#
, Shuhua Xu5,14,15,16
(TL)
CGVD: Jingyao Zeng1,2,3,#
, Na Yuan1,2,#
, Junwei Zhu1,2
,
Mengyu Pan1,2
, Hao Zhang1,2,3,10
, Qi Wang1,2,3,10
, Shuo
Shi1,2,3,10
, Meiye Jiang1,2,3,10
, Mingming Lu1,2,3,10
, Qiheng
Qian1,2,3,10
, Qianwen Gao1,2,3,10
, Yunfei Shang1,2,3,10
, Jinyue
Wang1,2,3,10
, Zhenglin Du1,2,#
(TL), Jingfa Xiao 1,2,3,10,*
(TL)
GWAS Atlas: Dongmei Tian1,2,#
, Pei Wang1,2,3,10,#
, Bixia
Tang1,2,#
, Cuiping Li1,2,#
, Xufei Teng1,2,3,10
, Xiaonan
Liu1,2,3,10
, Dong Zou1,2,3
, Shuhui Song1,2,3,#
(TL)
EWAS Data Hub: Zhuang Xiong1,2,3,10,#
, Mengwei
Li1,2,3,10,#
, Fei Yang1,2,3,10,#
, Yingke Ma1,2,3
, Jian
Sang1,2,3,10
, Zhaohua Li 1,2,3,10,11
, Rujiao Li1,2,3,#
(TL)
iSheep: Zhonghuang Wang1,2,10,#
, Qianghui Zhu9,10,#
, Junwei
Zhu1,2
, Xin Li9
, Sisi Zhang1,2
, Dongmei Tian1,2
, Hailong
Kang1,2,10
, Cuiping Li1,2
, Lili Dong1,2
, Cui Ying1,2,10
,
Guangya Duan1,2,10
, Shuhui Song1,2,3
, Menghua Li9,10
(TL), Wenming Zhao1,2,3,10,*
(TL)
eLMSG: Xiaoyang Zhi12,#
(TL), Yunchao Ling5,#
, Ruifang
Cao5,#
, Zhao Jiang12
, Haokui Zhou7
, Daqing Lv5
, Wan
Liu5
, Hans-Peter Klenk13
, Guoping Zhao1,5,6,7,*
, Guoqing
Zhang1,5,*
(TL)
PADS: Yadong Zhang1,2,3,10,#
, Zhewen Zhang1,2,3,#
, Hao
Zhang1,2,3,10
, Jingfa Xiao1,2,3,10,*
(TL)
BioProject & BioSample & GSA & BIG Submission:
Tingting Chen1,2,#
, Sisi Zhang1,2,#
, Xu Chen1,2,#
, Junwei
Zhu1,2,#
, Zhonghuang Wang1,2,3,10
, Hailong Kang1,2,3,10
,
Lili Dong1,2
, Yanqing Wang1,2,#
(TL)
GWH: Yingke Ma1,2,3,#
, Song Wu1,2,3,10
, Zhaohua
Li1,2,3,10,11
, Zheng Gong1,2,3,10
, Meili Chen1,2,3,#
(TL)
GVM: Cuiping Li1,2,#
, Dongmei Tian1,2,#
, Xufei
Teng1,2,3,10,#
, Pei Wang1,2,3,10,#
, Bixia Tang1,2,#
, Xiaonan
Liu1,2,3,10
, Dong Zou1,2,3
, Shuhui Song1,2,3,#
(TL)
NONCODE: Shuangsang Fang8
, Lili Zhang4,10
, Jincheng
Guo8
, Yiwei Niu4,10
, Yang Wu8
, Hui Li8
, Lianhe Zhao8
,
Xiyuan Li8
, Xueyi Teng4,10
, Xianhui Sun4,10
, Liang Sun8
,
Runsheng Chen1,4,10,*
, Yi Zhao8
(TL)
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D32 Nucleic Acids Research, 2020, Vol. 48, Database issue
piRBase: Jiajia Wang4,10,#
, Peng Zhang4,#
, Yanyan Li4,10
,
Yu Zheng4,10
, Runsheng Chen1,4,10,*
, Shunmin He1,4,10,*
(TL)
NPInter: Xueyi Teng4,10,#
, Xiaomin Chen4,10,#
, Hua
Xue4,10,#
, Yiheng Teng4,10
, Peng Zhang4
, Quan Kang4
,
Yajing Hao4
, Yi Zhao8
, Runsheng Chen1,4,10,*
, Shunmin
He1,4,10,*
(TL)
LncBook & LncRNAWiki: Jiabao Cao1,2,3,10,#
, Lin
Liu1,2,3,10,#
, Zhao Li1,2,3,10,#
, Qianpeng Li1,2,3,10
, Dong
Zou1,2,3
, Qiang Du1,2,3,10
, Amir A. Abbasi25
, Huma
Shireen25
, Nashaiman Pervaiz25
, Fatima Batool25
, Rabail
Z. Raza25
, Lina Ma1,2,3,#
(TL)
EDK & PED: Guangyi Niu1,2,3,10,#
, Yuansheng
Zhang1,2,3,10,#
, Dong Zou1,2,3,#
, Tongtong Zhu1,2,3,10,11
,
Jian Sang1,2,3,10
, Mengwei Li1,2,3,10
, Lili Hao1,2,3,#
(TL)
MethBank: Dong Zou1,2,3,#
, Guoliang Wang24,#
, Mengwei
Li1,2,3,10,#
, Rujiao Li1,2,3,#
(TL)
EWAS Atlas: Mengwei Li1,2,3,10,#
, Rujiao Li1,2,3
, Yiming
Bao1,2,3,10,11,*
(TL)
IC4R: Jun Yan17,#
, Jian Sang1,2,3,10,#
, Dong Zou1,2,3,#
,
Chen Li22
, Zhennan Wang10,23
, Yuansheng Zhang1,2,3,10
,
Tongtong Zhu1,2,3,10,11
, Shuhui Song1,2,3
(TL), Xiangfeng
Wang17
(TL), Lili Hao1,2,3
(TL)
LSD: Zhonghai Li18,#
(TL), Yang Zhang1,2,3,10,#
, Dong
Zou1,2,3
, Yi Zhao19
, Houling Wang18
, Yi Zhang18
, Xinli
Xia18,20
, Hongwei Guo18,21
, Zhang Zhang1,2,3,10,11,*
Database Commons: Dong Zou1,2,3,#
, Lina Ma1,2,3,#
(TL)
eGPS Cloud: Lili Dong1,2,#
, Bixia Tang1,2,#
, Junwen
Zhu1,2,#
, Qing Zhou1,2,10
, Zhonghuang Wang1,2,10
, Hongen
Kang1,2,10
, Xu Chen1,2
, Li Lan1,2
, Yiming Bao1,2,3,10,11,*
(TL), Wenming Zhao1,2,3,10,*
(TL)
BIG Search: Dong Zou1,2,3,#
(TL)
BIG SSO: Junwei Zhu1,2,#
(TL), Bixia Tang1,2,#
BHBD: Yiming Bao1,2,3,10,11,*
, Li Lan1,2
, Xin Zhang1,2
,
Yingke Ma1,2,3
, Yongbiao Xue26
(Project Leader)
Hardware & System Administration: Yubin Sun1,2
, Shuang
Zhai1,2
, Lei Yu1,2
, Mingyuan Sun1,2
, Huanxin Chen1,2
(TL)
Writing Group: Zhang Zhang1,2,3,10,11,*
, Wenming
Zhao1,2,3,10,*
, Jingfa Xiao1,2,3,10,*
, Yiming Bao1,2,3,10,11,*
, Lili
Hao1,2,3
NGDC PARTNERS (Listed in alphabetical order by
database names)
AnimalTFDB: Hui Hu27
, An-Yuan Guo27
dbPAF & WERAM: Shaofeng Lin27
, Yu Xue27
dbPPT: Chenwei Wang27
, Yu Xue27
dbPSP: Wanshan Ning27
, Yu Xue27
CellMarker: Xinxin Zhang28
, Yun Xiao28
, Xia Li28
CGDB: Yiran Tu27
, Yu Xue27
circAtlas: Wanying Wu29
, Peifeng Ji29
, Fangqing Zhao29
DEG & DoriC: Hao Luo30,31,32
, Feng Gao30,31,32
iEKPD: Yaping Guo27
, Yu Xue27
GenTree: Hao Yuan33,34
, Yong E. Zhang10,33,34
hTFtarget: Qiong Zhang27
, An-yuan Guo27
iUUCD: Jiaqi Zhou27
, Yu Xue27
LncRNADisease: Zhou Huang35
, Qinghua Cui35,36
lncRNASNP: Ya-Ru Miao27
, An-Yuan Guo27
MiCroKiTS: Chen Ruan27
, Yu Xue27
PceRBase: Chunhui Yuan37
, Ming Chen37
PlantTFDB: Jin-Pu Jin38
, Feng Tian38
, Ge Gao38
PLMD: Ying Shi27
, Yu Xue27
PTMD: Lan Yao27
, Yu Xue27
, Qinghua Cui35,36
RhesusBase: Xiangshang Li39
, Chuan-Yun Li39
SEGreg: Qing Tang27
, An-Yuan Guo27
THANATOS: Di Peng27
, Yu Xue27
1
National Genomics Data Center, Beijing 100101, China
2
BIG Data Center, Beijing Institute of Genomics, Chinese
Academy of Sciences, Beijing 100101, China
3
CAS Key Laboratory of Genome Sciences and Information,
Beijing Institute of Genomics, Chinese Academy of
Sciences, Beijing 100101, China
4
Key Laboratory of RNA Biology, Center for Big Data Research
in Health, Institute of Biophysics, Chinese Academy
of Sciences, Beijing 100101, China
5
Bio-Med Big Data Center, Key Laboratory of Computational
Biology, CAS-MPG Partner Institute for Computational
Biology, Shanghai Institute of Nutrition and Health,
Chinese Academy of Sciences, Shanghai 200231, China
6
CAS Key Laboratory of Synthetic Biology, Institute of
Plant Physiology and Ecology, Shanghai Institutes for Biological
Sciences, Chinese Academy of Sciences, Shanghai
200231, China
7
Center for Quantitative Synthetic Biology, Institute of
Synthetic Biology, Shenzhen Institutes of Advanced Technology,
Chinese Academy of Sciences, Shenzhen, China
8
Key Laboratory of Intelligent Information Processing, Advanced
Computer Research Center, Institute of Computing
Technology, Chinese Academy of Sciences, Beijing 100190,
China
9
CAS Key Laboratory of Animal Ecology and Conservation
Biology, Institute of Zoology, Chinese Academy of Sciences,
Beijing 100101, China
10
University of Chinese Academy of Sciences, Beijing
100049, China
11
School of Future Technology, University of Chinese
Academy of Sciences, Beijing 100049, China
12
Yunnan Institute of Microbiology, School of Life Sciences,
Yunnan University, Kunming, Yunnan 650091,
China
13
School of Natural and Environmental Sciences, Ridley
Building 2, Newcastle University, Newcastle upon Tyne,
UK
14
School of Life Science and Technology, ShanghaiTech
University, Shanghai 201210, China
15
Center for Excellence in Animal Evolution and Genetics,
Chinese Academy of Sciences, Kunming 650223, China
16
Collaborative Innovation Center of Genetics and Development,
Shanghai 200438, China
17
Department of Crop Genomics and Bioinformatics, College
of Agronomy and Biotechnology, China Agricultural
University, Beijing 100094, China
18
Beijing Advanced Innovation Center for Tree Breeding
by Molecular Design, Beijing Forestry University, Beijing
100083, China
19
College of Life Sciences, Peking University, Beijing
100871, China
20
College of Biological Sciences and Biotechnology, National
Engineering Laboratory for Tree Breeding, Beijing
Forestry University, Beijing 100083, China
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Nucleic Acids Research, 2020, Vol. 48, Database issue D33
21
Institute of Plant and Food Science, Department of Biology,
Southern University of Science and Technology
(SUSTech), Shenzhen, Guangdong 518055, China
22
Rice Research Institute, Guangdong Academy of Agricultural
Sciences, Guangzhou 510640, China
23
Institute of Zoology, Chinese Academy of Sciences, Beijing
100101, China
24
College of Plant Protection, Hunan Agricultural University,
Hunan 410128, China
25
National Center for Bioinformatics, Programme of Comparative
and Evolutionary Genomics, Faculty of Biological
Sciences, Quaid-i-Azam University, Islamabad 45320, Pak-
istan
26
Beijing Institute of Genomics, Chinese Academy of Sciences,
Beijing 100101, China
27
Department of Bioinformatics and Systems Biology, Key
Laboratory of Molecular Biophysics of the Ministry of
Education, Hubei Bioinformatics and Molecular Imaging
Key Laboratory, College of Life Science and Technology,
Huazhong University of Science and Technology, Wuhan,
Hubei 430074, China
28
College of Bioinformatics Science and Technology,
Harbin Medical University, Harbin, Heilongjiang 150081,
China
29
Beijing Institutes of Life Science, Chinese Academy of Sciences,
Beijing 100101, China
30
Department of Physics, School of Science, Tianjin University,
Tianjin 300072, China
31
Frontier Science Center of Synthetic Biology, Key Laboratory
of Systems Bioengineering, Tianjin University, Tianjin
300072, China
32
SynBio Research Platform, Collaborative Innovation
Center of Chemical Science and Engineering (Tianjin),
Tianjin 300072, China
33
Key Laboratory of Zoological Systematics and Evolution
and State Key Laboratory of Integrated Management
of Pest Insects and Rodents, Institute of Zoology, Chinese
Academy of Sciences, Beijing 100101, China
34
CAS Center for Excellence in Animal Evolution and Genetics,
Chinese Academy of Sciences, Kunming, Yunnan
650223, China
35
Department of Biomedical Informatics, School of Basic
Medical Sciences, MOE Key Lab of Cardiovascular Sciences,
Center for Noncoding RNA Medicine, Peking University,
Beijing 100190, China
36
Center of Bioinformatics, Key Laboratory for NeuroInformation
of Ministry of Education, School of Life Science
and Technology, University of Electronic Science and
Technology of China, Chengdu, Sichuan 610054, China
37
Department of Bioinformatics, State Key Laboratory
of Plant Physiology and Biochemistry, Institute of Plant
Science, College of Life Sciences, Zhejiang University,
Hangzhou, Zhejiang 310058, China
38
Biomedical Pioneering Innovation Center (BIOPIC), Beijing
Advanced Innovation Center for Genomics (ICG),
Center for Bioinformatics (CBI), and State Key Laboratory
of Protein and Plant Gene Research at School of Life Sciences,
Peking University, Beijing 100871, China
39
Institute of Molecular Medicine, Peking University, Beijing
100871, China
*To whom correspondence should be addressed: Zhang
Zhang (zhangzhang@big.ac.cn).
Correspondence may also be addressed to Wenming
Zhao (zhaowm@big.ac.cn), Jingfa Xiao (xiaojingfa@big.ac.cn),
Yiming Bao (baoym@big.ac.cn),
Shunmin He (heshunmin@ibp.ac.cn), Guoqing Zhang
(gqzhang@picb.ac.cn), Yixue Li (yxli@sibs.ac.cn), Guoping
Zhao (gpzhao@sibs.ac.cn) and Runsheng Chen
(crs@sun5.ibp.ac.cn).
#
The authors wish it to be known that, in their opinion,
these authors should be regarded as Joint First Authors.
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