List of single cell omics methods

Last updated

A list of more than 100 different single cell sequencing (omics) methods have been published. [1] The large majority of methods are paired with short-read sequencing technologies, although some of them are compatible with long read sequencing.

List

MethodReferenceSequencing ModeEarly EstimateLate Estimate
Tang method [2] Short Reads20082009
CyTOF [3] Short Reads20112012
STRT-seq / C1 [4] Short Reads20112012
SMART-seq [5] Short Reads20122013
CEL-seq [6] Short Reads20122013
Quartz-Seq [7] Short Reads20122013
PMA / SMA [8] Short Reads20122013
scBS-seq [9] Short Reads20132014
AbPair [10] Short Reads20142014
MARS-seq [11] Short Reads20142015
DR-seq [12] Short Reads20142015
G&T-Seq [13] Short Reads20142015
SCTG [14] Short Reads20142015
SIDR-seq [15] Short Reads20142015
sci-ATAC-seq [16] Short Reads20142015
Hi-SCL [17] Short Reads20152015
SUPeR-seq [18] Short Reads20152015
Drop-Chip [19] Short Reads20152015
CytoSeq [20] Short Reads20152016
inDrop [21] Short Reads20152016
sc-GEM [22] Short Reads20152016
scTrio-seq [23] Short Reads20152016
scM&T-seq [24] Short Reads20152016
PLAYR [25] Short Reads20152016
Genshaft-et-al-2016 [26] Short Reads20152016
Darmanis-et-al-2016 [27] Short Reads20152016
CRISP-seq [28] Short Reads20152016
scGESTALT [29] Short Reads20152016
CEL-Seq2 / C1 [30] Short Reads20152016
STRT-seq-2i [31] Short Reads20162017
RNAseq @10xgenomics [32] Short Reads20162017
RNAseq / Gene Expression @nanostringtech [33] Short Reads20162017
sc Targeted Gene Expression @fluidigm [34] Short Reads20162017
scTCR Wafergen [35] Short Reads20162017
CROP-seq [36] Short Reads20162017
SiC-seq [37] Short Reads20162017
mcSCRB-seq [38] Short Reads20162017
Patch-seq [39] Short Reads20162017
Geo-seq [40] Short Reads20162017
scNOMe-seq [41] Short Reads20162017
scCOOL-seq [42] Short Reads20162017
CUT&Run [43] Short Reads20162017
MATQ-seq [44] Short Reads20162017
Quartz-Seq2 [45] Short Reads20172018
Seq-Well [46] Short Reads20172018
DroNC-Seq [47] Short Reads20172018
sci-RNA-seq [48] Short Reads20172018
scATAC @10xgenomics [49] Short Reads20172018
scVDJ @10xgenomics [50] Short Reads20172018
scNMT triple omics [51] Short Reads20172018
SPLIT-seq Parse Biosciences [52] Short Reads20172018
CITE-Seq [53] Short Reads20172018
scMNase-seq [54] Short Reads20172018
Chaligne-et-al-2018 [55] Short Reads20172018
LINNAEUS [56] Short Reads20172018
TracerSeq [57] Short Reads20172018
CellTag [58] Short Reads20172018
ScarTrace [59] Short Reads20172018
scRNA-Seq Dolomite Bio [60] Short Reads20172018
Trac-looping [61] Short Reads20172018
Perturb-ATAC [62] Short Reads20182019
scMethylation [63] Short Reads20182019
scHiC [64] Short Reads20182019
Multiplex Droplet scRNAseq [65] Short Reads20182019
sci-CAR [66] Short Reads20182019
C1 CAGE single cell [67] Short Reads20182019
sc paired microRNA-mRNA [68] Short Reads20182019
scCAT-seq [69] Short Reads20182019
REAP-seq @fluidigm [70] Short Reads20182019
scCC [71] Short Reads20182019
yscRNA-SEQ [72] Short Reads20182019
TARGET-seq [73] Short Reads20182019
MULTI-seq [74] Short Reads20182019
snRNA-seq [75] Short Reads20182019
sci-RNA-seq3 [76] Short Reads20182019
BRIF-seq [77] Short Reads20182019
Drop-seq Dolomite Bio [60] Short Reads20182019
Slide-seq [78] Short Reads20182019
CUT&Tag [79] Short Reads20182019
CellTagging [80] Short Reads20182019
DART-Seq [81] Short Reads20182019
scDamID&T [82] Short Reads20182019
ACT-seq [83] Short Reads20182019
Sci-Hi-C [84] Short Reads20182019
Slide-seq [85] Short Reads20182019
Simplified-Drop-seq [86] Short Reads20182019
scChIC-seq [87] Short Reads20182019
Dip-C [88] Short Reads20182019
CoBATCH [89] Short Reads20182019
Convert-seq [90] Short Reads20182019
Droplet-based scATAC-seq [91] Short Reads20182019
ECCITE-seq [92] Short Reads20182019
dsciATAC-seq [91] Short Reads20182019
CLEVER-seq [93] Short Reads20182019
scISOr-Seq [94] Short Reads20182019
MARS-seq2.0 [95] Short Reads20182019
nano-NOMe [96] Long Reads20182019
MeSMLR-seq [97] Long Reads20182019
SMAC-seq [98] Long Reads20182019
MoonTag/SunTag [99] Short Reads20182019
SCoPE2 [100] Short Reads20182019
sci-fate [101] Short Reads20182019
μDamID [102] Short Reads20182019
Methyl-HiC [103] Short Reads20182019
RAGE-seq [104] Long Reads20182019
Paired-Seq [105] Short Reads20182019
Tn5Prime [106] Short Reads20182019
NanoPARE [107] Short Reads20182019
BART-Seq [108] Short Reads20182019
scDam&T-seq [109] Short Reads20182019
itChIP-seq [110] Short Reads20182019
SNARE-seq [111] Short Reads20182019
ASTAR-seq [112] Short Reads20182019
sci-Plex [113] Short Reads20182019
MIX-Seq [114] Short Reads20182019
microSPLiT [115] Short Reads20182019
PAIso-seq [116] Short Reads20182019
FIN-Seq [117] Short Reads20182019
LIBRA-seq [118] Short Reads20182019
scifi-RNA-seq [119] Short Reads20182019
plexDIA [120] Short Reads20212021
MPX [121] Short Reads20232023

Related Research Articles

<span class="mw-page-title-main">Functional genomics</span> Field of molecular biology

Functional genomics is a field of molecular biology that attempts to describe gene functions and interactions. Functional genomics make use of the vast data generated by genomic and transcriptomic projects. Functional genomics focuses on the dynamic aspects such as gene transcription, translation, regulation of gene expression and protein–protein interactions, as opposed to the static aspects of the genomic information such as DNA sequence or structures. A key characteristic of functional genomics studies is their genome-wide approach to these questions, generally involving high-throughput methods rather than a more traditional "candidate-gene" approach.

Cross-linking and immunoprecipitation is a method used in molecular biology that combines UV crosslinking with immunoprecipitation in order to identify RNA binding sites of proteins on a transcriptome-wide scale, thereby increasing our understanding of post-transcriptional regulatory networks. CLIP can be used either with antibodies against endogenous proteins, or with common peptide tags or affinity purification, which enables the possibility of profiling model organisms or RBPs otherwise lacking suitable antibodies.

<span class="mw-page-title-main">Chromosome conformation capture</span>

Chromosome conformation capture techniques are a set of molecular biology methods used to analyze the spatial organization of chromatin in a cell. These methods quantify the number of interactions between genomic loci that are nearby in 3-D space, but may be separated by many nucleotides in the linear genome. Such interactions may result from biological functions, such as promoter-enhancer interactions, or from random polymer looping, where undirected physical motion of chromatin causes loci to collide. Interaction frequencies may be analyzed directly, or they may be converted to distances and used to reconstruct 3-D structures.

<span class="mw-page-title-main">ABI Solid Sequencing</span>

SOLiD (Sequencing by Oligonucleotide Ligation and Detection) is a next-generation DNA sequencing technology developed by Life Technologies and has been commercially available since 2006. This next generation technology generates 108 - 109 small sequence reads at one time. It uses 2 base encoding to decode the raw data generated by the sequencing platform into sequence data.

ChIP-sequencing, also known as ChIP-seq, is a method used to analyze protein interactions with DNA. ChIP-seq combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing to identify the binding sites of DNA-associated proteins. It can be used to map global binding sites precisely for any protein of interest. Previously, ChIP-on-chip was the most common technique utilized to study these protein–DNA relations.

Epigenomics is the study of the complete set of epigenetic modifications on the genetic material of a cell, known as the epigenome. The field is analogous to genomics and proteomics, which are the study of the genome and proteome of a cell. Epigenetic modifications are reversible modifications on a cell's DNA or histones that affect gene expression without altering the DNA sequence. Epigenomic maintenance is a continuous process and plays an important role in stability of eukaryotic genomes by taking part in crucial biological mechanisms like DNA repair. Plant flavones are said to be inhibiting epigenomic marks that cause cancers. Two of the most characterized epigenetic modifications are DNA methylation and histone modification. Epigenetic modifications play an important role in gene expression and regulation, and are involved in numerous cellular processes such as in differentiation/development and tumorigenesis. The study of epigenetics on a global level has been made possible only recently through the adaptation of genomic high-throughput assays.

<span class="mw-page-title-main">RNA-Seq</span> Lab technique in cellular biology

RNA-Seq is a technique that uses next-generation sequencing to reveal the presence and quantity of RNA molecules in a biological sample, providing a snapshot of gene expression in the sample, also known as transcriptome.

Paired-end tags (PET) are the short sequences at the 5’ and 3' ends of a DNA fragment which are unique enough that they (theoretically) exist together only once in a genome, therefore making the sequence of the DNA in between them available upon search or upon further sequencing. Paired-end tags (PET) exist in PET libraries with the intervening DNA absent, that is, a PET "represents" a larger fragment of genomic or cDNA by consisting of a short 5' linker sequence, a short 5' sequence tag, a short 3' sequence tag, and a short 3' linker sequence. It was shown conceptually that 13 base pairs are sufficient to map tags uniquely. However, longer sequences are more practical for mapping reads uniquely. The endonucleases used to produce PETs give longer tags but sequences of 50–100 base pairs would be optimal for both mapping and cost efficiency. After extracting the PETs from many DNA fragments, they are linked (concatenated) together for efficient sequencing. On average, 20–30 tags could be sequenced with the Sanger method, which has a longer read length. Since the tag sequences are short, individual PETs are well suited for next-generation sequencing that has short read lengths and higher throughput. The main advantages of PET sequencing are its reduced cost by sequencing only short fragments, detection of structural variants in the genome, and increased specificity when aligning back to the genome compared to single tags, which involves only one end of the DNA fragment.

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ATAC-seq is a technique used in molecular biology to assess genome-wide chromatin accessibility. In 2013, the technique was first described as an alternative advanced method for MNase-seq, FAIRE-Seq and DNase-Seq. ATAC-seq is a faster analysis of the epigenome than DNase-seq or MNase-seq.

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Single-cell transcriptomics examines the gene expression level of individual cells in a given population by simultaneously measuring the RNA concentration of hundreds to thousands of genes. Single-cell transcriptomics makes it possible to unravel heterogeneous cell populations, reconstruct cellular developmental pathways, and model transcriptional dynamics — all previously masked in bulk RNA sequencing.

Transcriptomics technologies are the techniques used to study an organism's transcriptome, the sum of all of its RNA transcripts. The information content of an organism is recorded in the DNA of its genome and expressed through transcription. Here, mRNA serves as a transient intermediary molecule in the information network, whilst non-coding RNAs perform additional diverse functions. A transcriptome captures a snapshot in time of the total transcripts present in a cell. Transcriptomics technologies provide a broad account of which cellular processes are active and which are dormant. A major challenge in molecular biology is to understand how a single genome gives rise to a variety of cells. Another is how gene expression is regulated.

<span class="mw-page-title-main">Single cell epigenomics</span> Study of epigenomics in individual cells by single cell sequencing

Single cell epigenomics is the study of epigenomics in individual cells by single cell sequencing. Since 2013, methods have been created including whole-genome single-cell bisulfite sequencing to measure DNA methylation, whole-genome ChIP-sequencing to measure histone modifications, whole-genome ATAC-seq to measure chromatin accessibility and chromosome conformation capture.

<span class="mw-page-title-main">Spatial transcriptomics</span> Range of methods designed for assigning cell types

Spatial transcriptomics is a method for assigning cell types to their locations in the histological sections and can also be used to determine subcellular localization of mRNA molecules. First described in 2016 by Ståhl et al., it has since undergone a variety of improvements and modifications.

CITE-Seq is a method for performing RNA sequencing along with gaining quantitative and qualitative information on surface proteins with available antibodies on a single cell level. So far, the method has been demonstrated to work with only a few proteins per cell. As such, it provides an additional layer of information for the same cell by combining both proteomics and transcriptomics data. For phenotyping, this method has been shown to be as accurate as flow cytometry by the groups that developed it. It is currently one of the main methods, along with REAP-Seq, to evaluate both gene expression and protein levels simultaneously in different species.

<span class="mw-page-title-main">MNase-seq</span> Method used to analyse protein interactions with DNA

MNase-seq, short for micrococcal nuclease digestion with deep sequencing, is a molecular biological technique that was first pioneered in 2006 to measure nucleosome occupancy in the C. elegans genome, and was subsequently applied to the human genome in 2008. Though, the term ‘MNase-seq’ had not been coined until a year later, in 2009. Briefly, this technique relies on the use of the non-specific endo-exonuclease micrococcal nuclease, an enzyme derived from the bacteria Staphylococcus aureus, to bind and cleave protein-unbound regions of DNA on chromatin. DNA bound to histones or other chromatin-bound proteins may remain undigested. The uncut DNA is then purified from the proteins and sequenced through one or more of the various Next-Generation sequencing methods.

<span class="mw-page-title-main">RNA timestamp</span> Technology that enables the age of any given RNA transcript to be inferred by exploiting RNA editing

An RNA timestamp is a technology that enables the age of any given RNA transcript to be inferred by exploiting RNA editing. In this technique, the RNA of interest is tagged to an adenosine rich reporter motif that consists of multiple MS2 binding sites. These MS2 binding sites recruit a complex composed of ADAR2 and MCP. The binding of the ADAR2 enzyme to the RNA timestamp initiates the gradual conversion of adenosine to inosine molecules. Over time, these edits accumulate and are then read through RNA-seq. This technology allows us to glean cell-type specific temporal information associated with RNA-seq data, that until now, has not been accessible.

Single-cell genome and epigenome by transposases sequencing (scGET-seq) is a DNA sequencing method for profiling open and closed chromatin. In contrast to single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq), which only targets active euchromatin, scGET-seq is also capable of probing inactive heterochromatin.

References

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