Cell & Bioscience(2019) 9:53
Tang et al. Cell Biosci
https://doi.org/10.1186/s13578-019-0314-y

Open Access

REVIEW

The single‑cell sequencing: newdevelopments and medical applications
Xiaoning Tang1,2†, Yongmei Huang1,2†, Jinli Lei1,2, Hui Luo1,2* and Xiao Zhu1,2*

Abstract
Single-cell sequencing technologies can be used to detect the genome, transcriptome and other multi-omics of
single cells. They can show the differences and evolutionary relationships of various cells. This review introduces thelatest advances in single-cell sequencing technologies and their applications in oncology, microbiology, neurology,
reproduction, immunology, digestive and urinary systems, highlighting the important role that single-cell sequencing
techniques play in these areas.
Keywords: Cancer, Clinical applications, Developments, Immunology, Single-cell sequencing technologies,
Transcriptome
BackgroundSingle-cell sequencing technologies refer to the sequencing of a single-cell genome or transcriptome, so as toobtain genomic, transcriptome or other multi-omics
information to reveal cell population differences and cellular evolutionary relationships. Traditional sequencing
methods can only get the average of many cells, unable
to analyze a small number of cells and lose cellular heterogeneity information. Compared with traditionalsequencing technology, single-cell technologies havethe advantages of detecting heterogeneity among individual cells [1], distinguishing a small number of cells,
and delineating cell maps. In 2013, it was named “Nature
Methods” as the annual technology [2]. However, early
single-cell sequencing limited its widespread use due toits high cost. But as the research progressed, many new
single-cell sequencing methods were developed that
reduced the cost threshold for single-cell sequencing.
Nowadays, single-cell sequencing technology is increasingly used in various fields. This review describes recent
advances in single-cell sequencing methods and theirapplications in tumors, microbiology, neurology, reproduction, immunity, digestion, and urinary systems, and*Correspondence: luohui@gdmu.edu.cn; bioxzhu@yahoo.com†
Xiaoning Tang and Yongmei Huang contributed equally to this work
1
The Marine Biomedical Research Institute, Guangdong Medical
University, Zhanjiang 524023, China
Full list of author information is available at the end of the article

clarifies the important role of single-cell sequencing
technologies in basic and clinical research.

Single‑cell sequencing methods and recent
developments
Development of single‑cell sequencing methods

As research continues to deepen, the capabilities of single-cell sequencing methods (Fig. 1) continue to increaseand evolve toward lower detection costs, advancing scientists research on the molecular mechanisms at thesingle-cell level. Vitak et al. [3] proposed a single-cellcombinatorial marker sequencing technique (SCI-seq)
that can simultaneously construct thousands of singlecell libraries and detect variations in somatic cell copy
number (Table 1). This technique increases the numberof cells detected and reduces the cost of library construction, and has important value in the study of somatic cellvariation. Chen et al. [4] developed a novel single-cellwhole-genome amplification method that can detect
CNV at kilobase resolution and more effectively detectmutations in more diseases (Table 1). Guo et al. [5]developed a single-cell multiple sequencing technique(scCOOL-seq) that allows simultaneous analysis of single-cell chromatin state/nuclear niche localization, copy
number variations, ploidy and DNA methylation, which
can indicate different functions and patterns of chromatinstate and DNA methylation (Table 1). Casasent et al. [6]invented a Topographic Single Cell Sequencing (TSCS)© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium,provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license,
and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/
publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Tang et al. Cell Biosci(2019) 9:53

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improve the detection abundance of single-cell technologies, but it also reduces the cost of detection by an orderof magnitude compared to single-cell sequencing techniques coated with oil droplets. The SPLit-seq technology
from Rosenberg et al., based on the principle of a lowcost combined barcode, can reduce the cost of single-celltranscriptome sequencing to 1 cent. Once again broke
the cost threshold for single cell detection [9] (Table 1).
The joint use of single‑cell sequencing technologies

Fig. 1 The principle of single-cell sequencing. It is a process of
isolating a single cell for sequencing and studying cell heterogeneity,
molecular mapping, immune infiltration and epigenetic changes

that provides accurate spatial location information
for cells (Table 1). This technique accurately measuresand describes the specific characteristics of individual
tumor cells spatially and helps to study the invasion andmetastasis of tumor cells. Demaree et al. [7] describe ahigh-throughput and low-deviation single-cell sequencing (SiC-seq) method that uses droplet microfluidics toseparate, amplify, and barcode the genome of a single
cell (Table 1). This approach enables broader genomic
studies for different cell populations. The Microwell-seq
developed by Han et al. is a high-throughput and lowcost scRNA-seq platform [8] (Table 1). Not only does it

The single-cell sequencing detection cost reduction isbeneficial to the combination of other technologies andsingle-cell sequencing technologies, greatly improving the efficiency of single-cell detection. Datlinger et al.
[10] combined CRISPR screening with single-cell RNA
sequencing to invent CROP-seq (Table 1), which enables
high-throughput functional analysis of complex regulatory mechanisms and heterogeneous cell populations.
Gasperini et al. [11] combines CRISPRi and scRNA-seq
to facilitate the study of the function of regulatory elements and the interrelationship between regulatory elements and genes (Table 1). Habib et al. [12] combinedsNuc-Seq with microfluidic technology to introduce asingle-cell nuclear RNA sequencing method with low
cost, high-sensitive and high-efficiency cell classification, which is expected to be used in human cell mapping
projects (Table 1). Lake et al. [13] combined single-coresequencing (snDrop-seq) and single-cell transposon
hypersensitive site sequencing (scTHS-seq) to create a high-throughput sequencing platform for parallel

Table 1 Single-cell sequencing technologies
Single-cell sequencing

Characteristics

Functions

SCI-seq3

Single-cell combination marker

Construction of single-cell libraries and detection of cell copy number
variation

LIANTI4

Single cell whole genome amplification

Detection of cell copy number variation and disease-related mutations

scCOOL-seq5

Single cell multiplex sequencing

Detection of chromatin status/nucleosome localization, DNA methylation, copy number variation and ploidy

TSCS6

Provide accurate spatial location information

Describe the spatial characteristics of individual tumor cells

SiC-seq7

High throughput and low deviation

Extensive genomic research on different cells

Microwell-seq8

High throughput and low cost

Improve the detection abundance of single cell sequencing technology

SPLit-seq9

Combine barcode principle and low cost

Single cell transcriptome sequencing

CROP-seq10

High throughput

Analysis of complex regulatory mechanisms and functions of heterogeneous cell populations

CRISPRi + scRNA-seq11

High throughput

Analyze the function of regulatory elements and the relationshipbetween regulatory elements and cells

Single-Nucleus RNA-Seq+DroNc-Seq12

High sensitivity and high cell sorting efficiency

A variety of cells can be accurately analyzed. It may be used in the
Human Cell Atlas Project in the futureHigh throughput

It can be used to detect nuclear transcripts and epigenetic features, or
related analysis of frozen tissue in humans

Separate application

Joint application

snDrop-seq + scTHS-seq13

Tang et al. Cell Biosci(2019) 9:53

detection of nuclear transcripts and epigenetic features(Table 1). It provides a way to comprehensively analyze
gene expression and regulation in cryopreserved samplesof human tissues.
The above studies (Table 1) show that single-cellsequencing technologies were constantly updated anddeveloped, providing a technical basis for the construction of a complete cell map, greatly promoting the singlecell research process. In the future, single-cell sequencing
technologies integrated multi-omics methods may
become popular, playing an increasingly powerful role insingle-cell research of complex organs and tissues, diagnosis and treatment of clinical diseases.

Single‑cell sequencing applications
Applications in cancer

Studies have shown that genetic or genomic variation canlead to cells with different genetic and phenotypic characteristics within the tumor tissue, making the tumor
tissue highly heterogeneous [14, 15]. This high degree ofheterogeneity may be related to the mechanisms of tumorigenesis [16] and metastasis [17–19], so researchers
need to perform more accurate analysis of tumor cells.
Traditional sequencing methods can only detect cell
populations, get the average of the signals in a group ofcells, but the heterogeneity in tumor cells can be masked.
Therefore, traditional sequencing methods do not study
tumor cells well. Single-cell sequencing technologies
can perfectly compensate for the shortcomings of traditional sequencing methods. The cell map of tumor cells
and tumor microenvironment was drawn by detecting
the heterogeneity of tumor cells. Further, clarify the cellgroup within the tumor tissue and find specific markers,
as well as explain a series of problems such as tumorigenesis and metastasis. Therefore, single-cell sequencing
technologies were widely used in the research of various
tumors, and were of great significance for the development of new diagnostic and anti-tumor treatment methods (Fig. 2).
Colorectal cancer

Zhang et al. [20] mapped the T cell immunoreceptor ofcolorectal cancer by single-cell sequencing technology,
and revealed the subgroup classification, tissue distribution characteristics, tumor heterogeneity and drug target
gene expression of colorectal cancer T cells. A potential
state transition relationship between T cell populations
and subpopulations distributed across tissues was identified. In the same year, Bian et al. [21] used this techniqueto analyze the characteristics and relationship of genomic
copy number variation, DNA methylation abnormality
and gene expression change during the occurrence andmetastasis of human colorectal cancer from single cell

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Fig. 2 The clinical applications of single-cell sequencing indifferent fields, like cancer, immune system, reproductive system,
microorganisms, etc. These will help to clarify some of the problems
and provide a basis for finding better treatments

resolution and multi-group level. The above studies areof great significance for revealing the new mechanismof human colon cancer and improving the diagnosis andtreatment of colorectal cancer.
Breast cancer
The origin and transformation of breast cancer

Breast cancer is a highly heterogeneous disease caused
by genetically altered mammary epithelial cells. Nguyen
et al. [22–24] mapped the single cell pattern of humanmammary epithelial cells by single-cell sequencing technology and analyzed the diversity and status of cell types
in breast cells. The findings help to understand the earlyorigins of breast cancer and provide the basis for improving the early detection of cancer and preventing cancer
progression. Casasent et al. [6] reported the polyclonal
origin of breast cancer and the mechanism of transformation between ductal carcinoma in situ and invasive
carcinoma by topographic single-cell sequencing. Direct
genomic lineages between in situ tumor subpopulations
and invasive tumor subpopulations are revealed in thisstudy. Furthermore, the time and reason for the occurrence of subcloning and the mechanisms of the formationof invasive carcinoma due to the intra-ductal cloning into
adjacent tissues were further demonstrated. The resultsof this study provide a theoretical basis for preventing
early breast cancer from turning into invasive cancer.
Breast cancer microenvironment

The single-cell technologies explored the immune
microenvironment of breast cancer and finds immunizing changes. Azizi et al. [25] mapped a single-cell mapof various immune cells in the microenvironment ofbreast tumor. Through this map, the gene expression

Tang et al. Cell Biosci(2019) 9:53

characteristics of human breast tumors and paired normal tissues, lymph node tissues and peripheral blood
were analyzed. It was found that the heterogeneity of
intratumoral lymphocytes and myeloid cells can induce
combined gene expression through environmental
stimulation. Based on T cell receptor (TCR) and T cell
matched single-cell RNA sequencing data, the T cell
continuous activation profile was inconsistent with thepolarization model of macrophage in cancer. This study
examined the microenvironment of breast cancer andhelped to differentiate its immune cells and to identify
the differences in gene expression of tumor-infiltrating
immune cells and the causes of differences.

Page 4 of 9tumor growth [27]. It is of great significance for the treatment of such diseases.
Head and neck cell carcinoma

Puram et al. [29] analyzed the ecosystem of head andneck squamous cell carcinoma (HNSCC) by single-cellsequencing technology, delineating the first cell map ofhead and neck tumors and revealing the types of headand neck tumors and their metastasis-related procedures. This study provides a new understanding of thecauses and metastasis of tumor metastasis, and helps tofind new targets for blocking tumor metastasis.
Hematological tumors

Breast cancer and estrogen

The researchers observed a close relationship between
estrogen and breast cancer. Estrogen activates estrogen receptor alpha (ERα) to drive the progression ofbreast cancer. Zhu et al. [26] studied the estrogen signaling pathway and the mechanism of ERα-regulatedtranscription by single-cell transcriptome sequencing,and found the dynamic transcriptional heterogeneity of ERα-positive breast cancer cells after estrogenstimulation. This study reveals the metabolic pathways
involved in estrogen-mediated monocarbon, purine
and polyamine synthesis in breast cancer, and the discovery that PPAT and AZIN1 were direct ERa targets
for the cell survival and growth of breast cancer. It supplements the pathogenesis of breast cancer and provides a theoretical basis for the study of tumor-targeteddrugs.
Brain tumor

It is generally believed that brain astrocytomas and oligodendrogliomas originate from different types of cells.
However, Venteicher et al. [27] found that IDH mutant
gliomas share a common origin through single-cellsequencing technology. The difference between themis mainly the difference in genetics and the composition of the tumor microenvironment. Two of the different subtypes of tumors have universally similar stem cell
programs, which can be distinguished from similar neuroglial mass spectrometry systems. Tirosh et al. [28] identified cancer stem cells and their differentiated progeny
through a single cell map in human oligodendroglioma.
The findings support the cancer stem cell hypothesis andconfirm that cancer stem cells were the main source ofgrowth for oligodendroglioma. These studies suggestthat these cells may become new therapeutic targets.
Researcher Suvà suggested that immunotherapy can beused to attack specific cell types, thereby terminating

Single-cell sequencing technologies help to find classification markers and analyze the causes of disease occurrence in hematological tumors with high heterogeneity,
providing a theoretical basis for clinical diagnosis andtreatment of diseases.
Ledergor et al. [30] found at the single-cell level that
there were common expressions and differences in certain genes among different myeloma plasma cell samples. New markers can be sought by these common
expressions. Differences in gene expression patterns
and chromosome structure among the samples may
be responsible for the high heterogeneity of myeloma
plasma cells. This study summarizes the positive role ofthe single-cell approach in the diagnosis, treatment, andprognosis of myeloma. Peripheral blood is used to distinguish tumor cells and diagnose diseases. It can not only
facilitate the collection of samples but also reduce thepain of patients during the collection of samples.
In the study of acute leukemia, Ley et al. [16] foundgenes associated with AML, and measured 9 mutations in each tumor sample cell. The results suggest thatthese heterogeneities caused by genetic mutations may
be related to pathogenesis. Hou et al. [31] performed awhole exome single-cell sequencing on cells from patientswith JAK2-negative myeloproliferative tumors, and theresults indicated that this tumor represents a monoclonal evolution. They further identified candidate mutations associated with essential thrombocythemia (ET)and speculated that these mutations may be involved intumor progression. De Bie et al. [32] demonstrated thesequence of mutations in T cell acute lymphoblastic leukemia (T-ALL) by targeted single-cell sequencing, and
T-ALL development can begin in pluripotent progenitor
cells.
Liver cancer and lung cancer

Chinese researchers at the single-cell level mapped theimmunological map of the liver cancer microenvironment

Tang et al. Cell Biosci(2019) 9:53

and the T cell immune map of lung cancer [33, 34]. The
subgroup classification, tissue distribution characteristics, tumor heterogeneity and drug target gene expression of immune cells in liver cancer and lung cancer wererevealed. The above studies are helpful to understandthe immune microenvironment of liver cancer and lungcancer, to find effective biomarkers, new tumor immunotherapy, and drug targets. It is of great significance for the
diagnosis and treatment of liver cancer and lung cancer.
Despite a large number of microorganisms in theworld, researchers have only studied a small fraction of
the microbial species. Due to the extremely small sample
size of most microorganisms and the difficulty of culture,
it is very difficult to study the microbial genome structure. However, the emergence of single-cell sequencing
has led to important breakthroughs in the microbiology
field. Single-cell sequencing technology provides cellspecific genetic information that is lacking in traditional
genome-wide studies of bacteria. It also discovers genes
associated with bacterial life activities and classifies
microorganisms by genomic models [35]. Lan et al. [36]performed high-throughput single-cell genome sequencing (SiC-seq) on bacterial and fungal synthetic communities to analyze the distribution of antibiotic resistancegenes, virulence factors and phage sequences in environmental microbial communities. This study enabled themicrobial single-cell sequencing of prokaryotes. In the
future, this technology may isolate low titer pathogenic
bacterial samples and sequence them at the single-celllevel to examine their virulence genotype sources [7].
According to the above studies, single-cell sequencing
technologies play important roles in the classification,
evolution and drug resistance of microorganisms. It isgood for mining meaningful environmental microbes andfinding ways to resist antimicrobial resistance.

Applications in the nervous system
Nerve cell typing

In the nervous system, there is a difference among individual neurons because there are some unique copy
number variations in nerve cells [37]. The heterogeneity among these neurons makes it difficult to study how
brain circuits are formed and to resolve neuronal reconnections. However, single-cell sequencing technology canstudy many different periods of nerve cells, and draw adetailed single-cell map to understand and identify different types of neurons and their connecting moleculesin the brain [38]. Luo et al. [39] differentiated subtypesof mouse and human frontal cortical neuronal cellsby high-throughput single-cell methylation sequencing. They identified a new set of neurons in the humanfrontal cortex and redefine the neuron type based on the
methylation group of neurons. Lake et al. [40] used a new

Page 5 of 9

single-cell nuclear sequencing method to map the second
generation single cell of an adult brain. A variety of different neurons, glial cell subtypes, and cell subtypes thatare more susceptible to common risk factors for different
brain diseases are found. It is expected to understand thepathogenesis of neurological diseases.
Applications of brain nerve development and regeneration
process

Single-cell sequencing technologies can study the typesof brain cells and the relationships among cells during
development (Fig. 2). Fan et al. [41] identified multiple
subpopulations of cells in each region in multiple regionsof human metaphase embryos by single-cell sequencing
techniques, and analyzed gene expression and neuronalmaturation in these regions. Zhong et al. [42] mappeda single-cell transcriptome map of human prefrontal
embryonic development through single-cell sequencing.
From this map, the diversity of cell types in the prefrontal
lobe of the human embryonic brain and the developmental relationship among different cell types were analyzed,
and the molecular regulation mechanism of neuron production and loop formation was further revealed. It is
important to study the function of key cell types and to
map intact human brain cells. Carter et al. [43] identified a major subset of cerebellar cells and a subpopulation that is beneficial to cerebellar development in amouse cerebellar development map drawn by single-cellsequencing. These studies will facilitate future researchon cerebellar development, neurobiology and diseases.

Applications in the field of reproductive
and embryonic medicine
The single-cell sequencing technologies can sequenceand quantify the whole genome of germ cells and embryonic cells at the single-cell level (Fig. 2). This will help tounderstand the occurrence of germ cells and the screening, diagnosis, and treatment of reproductive and genetic
diseases.
Germ cell

Chen et al. [44] revealed the dynamic process and molecular characteristics of gene expression during spermatogenesis in mice and the specific patterns of alternative
splicing through single-cell sequencing technology, as
well as the discovery of key regulators for specific stagesof male germ cell development. In the same year, the teamperformed single-cell RNA sequencing (scRNA-seq)
analysis of human normal testicular cells and abnormal
testicular cells. Based on the results, a hierarchical modelof spermatogonial subtypes, spermatocyte subtypes andsperm cell subtypes was established, and specific markers for human germ cells were further discovered. In

Tang et al. Cell Biosci(2019) 9:53

addition, changes of expression patterns in testicularsomatic cells in an NOA patient were identified, which
may be the pathogenesis of NOA [45]. The above studies
provide valuable data sources for the development andmaturation of mammalian sperm and the development ofgametes. It also contributes to the understanding of maleinfertility and the treatment of such diseases.
Reproductive support

Single cell sequencing technology can detect the advantages of a small number of cells, which can be applied toprenatal diagnosis and assisted reproduction. Detectionof female egg cell polar cells or embryonic cells by single-cell sequencing to select healthy embryo transfer can
reduce the birth rate of newborns with congenital genetic
diseases and help prevent genetic diseases [46, 47].
Embryonic cell

In terms of animals, single-cell transcriptome sequencing technology is used to map the cell development ofzebrafish and African cockroach embryos, providing
important clues for understanding developmental biology [48–50]. Li et al. [51] mapped the genome-wide mapof human embryos prior to implantation by single-cell
multi-sequence sequencing. This study has implications
for the analysis of complex and highly coordinated epigenetic processes in the pre-implantation developmentof human embryos. Vento-Tormo et al. [52] performeda transcriptome analysis of placental cells in early pregnancy by single-cell sequencing technology and mapped
placental cell maps. Through the cell map, three subpopulations of perivascular and stromal cells located in different decidual layers and dNK (decidual natural killer)
were found. It has also identified regulatory responses
that may minimize the immune response of harmful
mothers, as well as revealing interactions that contributeto the success of placenta and reproduction. The findings are important for understanding early pregnancy
processes and improving the diagnosis and treatment ofpregnancy-related diseases.

Applications in the field of immunology
As an important system for the body to perform immune
response and immune function, the immune system has
an important role in resisting the invasion of external
pathogens. Many immune cells with unique functions in
the immune system are a research hotspot.
Application of natural killer (NK) cells, DC cells
and lymphocytes

Single-cell sequencing technologies can detect individual
immune cells, thereby distinguishing different groups ofPage 6 of 9

immune cells, as well as discovering new immune cell
populations and their relationships (Fig. 2). This helps
to understand the complex immune system and propose new targets for disease treatment. Crinier et al. [53]identified subpopulations of the spleen and blood NK
cells in mice and humans by single-cell RNA sequencing,revealing two distinct features that distinguish blood andspleen NK cells. And through the comparison of transcriptomics, the similarity between two major subgroups
NK1 and NK2 in organs and species is highlighted. This
study provides an in-depth understanding of the biologyof NK cells and contributes to the translation of animalstudies into human-related research. Villani et al. [54]identified multiple subtypes of DC cells and monocytes
in human blood by single-cell RNA-seq and revealed a
new subset of DC cells that have the properties of plasmacytoid DCs but are effective in activating T cells.
In response to this finding, one of the researchers suggested “stimulating such cells or potentially enhancing
the body’s immune system to fight cancer.” Such cells may
become a new anti-cancer means to remove tumor cells
through their own immune system, avoiding the damage of normal chemotherapy drugs to normal cells. The
study redefines the relationship among DC cells, helps
analyze the developmental processes and functions of
the immune system, and completes immune surveillance
under normal and disease states. Xin et al. [55] usedsingle-cell RNA sequencing to study immune cells andcytokines during persistent infection. It was found thatthe heterogeneity of IL-10 expressing CD4 T cells andthe production of IL-10 by a subset of helper cells during
different infections play an important role in promoting
humoral immunity.
Causes of immune cell heterogeneity

Single-cell sequencing can study immune cells with highheterogeneity caused by pathogens, accurately detect thegenetic material of individual immune cells, and help tounderstand the complex immune mechanism of the body[56]. Interestingly, in addition to pathogens, aging canalso lead to increased cellular heterogeneity. MartinezJimenez et al. [57] performed single-cell RNA sequencing
on CD4+ T cells in different states of young and old mice,and found that aging affects cell transcriptional kinetics,
resulting in increased heterogeneity of gene expression
among immune cells. Further, the immune cells are unable to make an asynchronous reaction, and the immune
performance is weakened. This study helps explain theweakening of the immune system with increasing age. It
is suggested that the increase in intercellular transcriptional variation may represent the aging characteristics,
laying the foundation for exploring the aging mechanism

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of cells. Recently, single-cell sequencing has found new
discoveries in the immune cells of the central nervous
system during the inflammatory phase. Jordão et al. [58]found that in the development of neuroinflammatory
pathology, the specific differentiation of myeloid cell subpopulations is obvious because the self-renewal, random
proliferation and clonal expansion of CNS macrophage
subpopulations. Moreover, the antigen presentation of
CNS macrophages has no significant relationship withthe pathological role of neuroinflammation. Studies haveshown that dendritic cells and monocyte-derived cells
are the main participants in antigen presentation duringexperimental autoimmune encephalomyelitis (EAE). This
study maps the dynamic map of myeloid cell subpopulations in the central nervous system, reveals complex
changes in the characteristic molecules of myeloid cellsubsets during neuroinflammation, and provides a theoretical basis for improving the treatment of EAE.
According to the above research, the heterogeneity of
immune cells will affect the immune status of the body.
An increase in the heterogeneity of immune cells may
cause immune cells to have specific functions that help
fight against pathogen invasion. It may also cause thebody’s immunity to decline, which is a feature of tissue
aging. Therefore, the study of immune cell heterogeneity can help people understand the complex and delicate
immune mechanisms of the body, and perhaps adjust
some immune mechanisms to treat certain diseases.

Conclusion and perspectives
After completing the Human Genome Project, scientists
have proposed a human cell atlas program designed tocomplete the mapping of 37 trillion cells in the humanbody. Single-cell sequencing technologies can accurately
study individual cells and will be an important driving
force for this project. The cell maps depicted by singlecell sequencing technology help people distinguishamong cell types and understand cell-to-cell relationships. One can further understand physiological processes and pathological mechanisms at the single-celllevel to find new diagnostic markers or new therapeutictargets. This will provide a practical basis for improving
the diagnosis and treatment of the diseases.
This review introduced single-cell sequencing methods
and their applications in tumors, microorganism, nervous system, reproductive medicine and immunology,
highlighting the great advantages of single-cell sequencing technologies in the study of highly heterogeneous
single-cell. However, single-cell sequencing technologies
still have problems such as cumbersome operation andhigh detection cost, which limits the promotion of technology. It is hoped that the single-cell sequencing technologies will be more simplified, more powerful, and thedetection cost will be further reduced, so that the technologies can be applied to basic research and play animportant role in clinical diagnosis and treatment.

Application in the digestive system and urinary
systemHaber et al. [59] found many new intestinal epithelial cell
subtypes by single-cell transcriptome sequencing andmapped the expression of intestinal epithelial cells. From
this map, the mechanism of intestinal cells maintaining
homeostasis and responding to pathogenic microorganisms is explained. Gao et al. [60] used high-precision
single-cell transcriptome sequencing to analyze the four
digestive organs of human embryonic stage and multiple cells of the adult large intestine, revealing the related
mechanisms of gene regulation in the development offour human digestive organs (Fig. 2). Wang et al. [61]demonstrated the heterogeneity of precursor cells forming the initial nephron in the human embryonic stage
and the corresponding transcriptional regulatory eventsand signaling pathways in the process of differentiationof precursor cells into tubular epithelial cells by singlecell transcriptome sequencing (Fig. 2). This study also
demonstrated the expression characteristics of candidate
pathogenic genes for congenital nephropathy and contributed to the treatment of congenital nephropathy.

Abbreviations
SCI-seq: single-cell combinatorial marker sequencing technique; scCOOLseq: single-cell chromatin overall omic-scale landscape sequencing; TSCS:
topographic Single Cell Sequencing; scRNA-seq: single-cell RNA-seq; CRISPR:
clustered regularly interspaced short palindromic repeats; CROP-seq: cRISPR
droplet sequencing; sNuc-Seq: single-Nucleus RNA Sequencing; snDrop-seq:
single-core sequencing; scTHS-seq: single-cell transposon hypersensitive site
sequencing; TCR​: T cell receptor; ERα: estrogen receptor alpha; PPAT: phosphoribosyl pyrophosphate amidotransferase; AZIN1: antizyme inhibitor 1; IDH:
isocitrate dehydrogenase; HNSCC: head and neck squamous cell carcinoma;
AML: acute myeloid leukemia; ET: essential thrombocythemia; T-ALL: T cell
acute lymphoblastic leukemia; NOA: non obstructive azoospermic; dNK cells:
decidual natural killer cells; NK cells: natural killer cell; DC cells: dendritic cells;
IL-10: interleukin-10; CD4: cluster of differentiation 4; CNS: central nervous
system; EAE: experimental autoimmune encephalomyelitis.
Acknowledgements
The authors would like to thank Dr. Dongpei Li in Medical College of Georgia,
Augusta University, GA USA for proofreading and constructive criticism of themanuscript.
Authors’ contributions
All authors read and approved the final manuscript.
Funding
This work was supported partly by National Natural Science Foundation ofChina (81541153); Guangdong Provincial Science and Technology Programs(2016A050503046, 2015A050502048 and 2016B030309002); The PublicService Platform of South China Sea for R&D Marine Biomedicine Resources(GDMUK201808).

Tang et al. Cell Biosci(2019) 9:53

Availability of data and materials
Not applicable.
Ethics approval and consent to participate
Not applicable.
Consent for publication
All authors consent for publication.
Competing interests
The authors declare that they have no competing interests.
Author details
1
The Marine Biomedical Research Institute, Guangdong Medical University,
Zhanjiang 524023, China. 2 Guangdong Provincial Zhanjiang Bay Key Laboratory, Zhanjiang 524023, China.
Received: 23 April 2019 Accepted: 18 June 2019

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