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Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
Review Article
Single-molecule optical genome mapping in
nanochannels: multidisciplinarity at the nanoscale
Jonathan Jeffet * , Sapir Margalit * , Yael Michaeli and Yuval Ebenstein
Correspondence: Jonathan Jeffet (jonath7@tauex.tau.ac.il) or Yuval Ebenstein (uv@tauex.tau.ac.il)
The human genome contains multiple layers of information that extend beyond the genetic
sequence. In fact, identical genetics do not necessarily yield identical phenotypes as evident
for the case of two different cell types in the human body. The great variation in structure
and function displayed by cells with identical genetic background is attributed to additional
genomic information content. This includes large-scale genetic aberrations, as well as diverse epigenetic patterns that are crucial for regulating specific cell functions. These genetic and epigenetic patterns operate in concert in order to maintain specific cellular functions in health and disease. Single-molecule optical genome mapping is a high-throughput
genome analysis method that is based on imaging long chromosomal fragments stretched
in nanochannel arrays. The access to long DNA molecules coupled with fluorescent tagging of various genomic information presents a unique opportunity to study genetic and
epigenetic patterns in the genome at a single-molecule level over large genomic distances.
Optical mapping entwines synergistically chemical, physical, and computational advancements, to uncover invaluable biological insights, inaccessible by sequencing technologies.
Here we describe the method’s basic principles of operation, and review the various available mechanisms to fluorescently tag genomic information. We present some of the recent
biological and clinical impact enabled by optical mapping and present recent approaches
for increasing the method’s resolution and accuracy. Finally, we discuss how multiple layers of genomic information may be mapped simultaneously on the same DNA molecule,
thus paving the way for characterizing multiple genomic observables on individual DNA
molecules.
Introduction
* These authors contributed
equally to this work.
Received: 27 January 2021
Revised: 24 February 2021
Accepted: 26 February 2021
Version of Record published:
19 March 2021
Optical DNA mapping has emerged in recent years as a valuable technique for unraveling long-range information along the genome [1–3]. The method incorporates a multi-disciplinary approach (Figure 1)
for extraction of long-range single-molecule genomic data, and provides an indispensable complementary perspective to DNA sequencing. The method is based on sequence-specific fluorescent labeling of up
to mega-base pairs (Mbp) long chromosomal DNA molecules (Figure 1A). The labeled DNA molecules
are unraveled from their entropically favored entangled state, and extended to allow orderly reading of
their fluorescent markers. In nanochannel-based optical mapping, commercialized by BioNano Genomics
[4,5], an electric field is applied on the inherently charged long DNA molecules to thread them into an
array of nanochannels (∼36 × 36 nm2 cross-section), forcing the molecules to stretch linearly due to confinement (Figure 1B.). While this extension can be achieved using various methods (thoroughly reviewed
in [3,6]), confinement in nanochannels has proven to generate the most uniform DNA linearization and
highest throughput and reproducibility [2,7], and will be the method focused on in this review.
After linearization, the confined molecules are imaged using fluorescence microscopy. The fluorescent
genetic marker pattern on each DNA molecule is localized to establish a unique barcode indicating the
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Raymond and Beverly Sackler Faculty of Exact Sciences, Center for Nanoscience and Nanotechnology, Center for Light Matter Interaction, Tel Aviv University, Tel Aviv 6997801,
Israel
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
A. Chemistry
(A)
High molecular weight
DNA extraction
Genetic barcoding
Additional labeling
(optional)
Backbone staining
Linearization in nanochannels
Multicolor imaging
Marker Localization and
molecule digitization
(C)
C. Computer science
chr1
In-silico reference
Alignment algorithms align the
molecules to an in-silico reference
Assembly algorithms align the molecules
de-novo to construct consensus genome maps
(D)
D. Biology
deletion
inversion
insertion
duplication
phasing
SV detection, phasing
Versatile whole-genome analyses
Population analysis
Figure 1. The multi-disciplinary process of optical mapping
(A) High molecular weight DNA is extracted and chemically labeled at sequence-specific sites to generate a genetic barcode.
Additional labeling of various information layers such as epigenetic marks can follow, and finally the DNA backbone is stained
with an intercalating dye. (B) Using an electrical field, DNA molecules are unraveled from their entangled state and forced into
nanochannels for linearization. Within the nanochannels, the labeled molecules are imaged in multiple colors (image obtained on
BioNano Genomics Saphyr system). The molecules and their fluorescent marks are then detected and localized, and image analysis
is performed for their digitization. (C) The digitized barcodes are then used to infer the molecules’ genomic origin, either by their
alignment to a known reference genome, or their assembly de novo. (D) The resulting genomic (and epigenetic) information obtained
is used for biological analysis based on structural variants, copy number aberrations, genome phasing and population analyses.
2
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(B)
B. Physics
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
Table 1 Long-read sequencing methods compared to optical mapping
BioNano Genomics
Saphyr
Oxford Nanopore
MinION
PromethION
PacBio SMRT sequencing,
HiFi reads
Resolution
∼1500–2500 bp [17]
Single bp
Single bp
Molecules N50*
300 kbp** [16]
10–60 kbp [19]
10–20 kbp [19]
Maximal throughput per cell
0.33–5 Tbp** (∼100–1500×
human genome) [2,16,20,21]
30–50 Gbp (10–16× human)
[19,22]
180–200 Gbp (60–66×)[19,22]
35 Gbp (11× human) [19]
Price per 1× human genome
coverage***
∼$0.37–$5.50 [16]
$155–$1550 [19]
$65–$130 [19]
$133–$266 [19]
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* ‘Molecules N50’: half of the genetic data recorded came from reads longer or equal to this value.
** Molecules under 150 kb were filtered out.
*** Costs include reagents and do not include instruments.
genomic origin of the molecule. These digitized barcodes are then either aligned to a reference map, produced according to the known genome sequence, or can be assembled to create consensus contiguous maps that span many
Mbps (Figure 1C) [2]. The computational methods of barcode mapping and consensus map generation have been
recently discussed [2,7] and are beyond the scope of this review.
Optical mapping is a vibrant field [1,2,8], and is currently the go-to method for detecting and validating large-scale
genomic rearrangements, such as structural and copy number variations (SVs, CNVs respectively) [9–13] (Figure
1D). With Mbp read lengths, optical mapping reveals such large-scale variations from the reference genome, while
conventional short-read next-generation sequencing (NGS) is blind to them. In addition, as each of the mapped DNA
molecules originates from a different cell, the single-molecule information extracted with optical mapping enables
high-throughput characterization of cellular heterogeneity which is masked by the ensemble averages that are part of
NGS analysis.
Optical mapping is commonly compared against other sequencing methods that offer long reads with
single-molecule sensitivity, such as Oxford Nanopore [14] or Pacific Biosciences’ (PacBio) single-molecule real-time
(SMRT) sequencing [15]. Unlike optical mapping, which is limited in its resolution (>500 bp for ensemble averaged
SV detection [16], and optical resolution of ∼1500–2500 bp [17]), these methods offer single base-pair resolution
with longer reads compared to NGS. Although these emerging technologies are pushing the limits of sequencing and
can already capture medium-scale SVs with high precision [18], they are still limited in the fraction of ultra-long
reads and price per genome coverage (see Table 1). Another important advantage of optical mapping is its ability to
incorporate multiple information layers simultaneously on the same single DNA molecule. These additional layers of
information include various epigenetic content, DNA damage, DNA replication sites and more, as discussed in the
last section of this review, at large not accessible to other technologies in a straightforward manner.
Since optical mapping in nanochannels fuses research from multiple disciplines, we chose to divide the following
sections according to their primary disciplines with the intention of facilitating the reader’s orientation throughout
this review. We start with a chemistry-oriented review of the main genetic labeling schemes used in optical mapping
with an emphasis on those that are compatible with the BioNano Genomics systems. Next, we highlight the physical
aspects of nanochannel-based optical mapping, discuss the various limitations they impose on genetic mapping accuracy and resolution, and describe methods which alleviate these restrictions. We then review major recent advances
in clinical diagnosis and biological applications enabled by genetic optical mapping. Finally, we survey the emerging
practices of epigenetic incorporation to optical mapping, describe the current labeling procedures and the physical
limitations, and discuss the required future improvements.
Genetic labeling schemes
The labeling schemes in optical genome mapping are roughly divided into two main subgroups: sparse labeling, where
enzymatic reactions are used to fluorescently tag specific sequences scattered along the long DNA molecules, creating
a barcode-like pattern where each marker can be localized [4,23,24]; and continuous labeling, where frequent labeling
[25], denaturation mapping [26–28] or affinity-based binding [1,27,28] generates a continuous fluorescence intensity
map along the molecule [1,27,29]. The maps generated by both methods provide a unique fluorescent signature that
discloses the molecule’s genomic origin [1,3–5,30,31].
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(A)
A.
Nicking enzyme
(B)
B.
DNMT
(C)
C.
Fluorescent
cofactor
(D)
D.
Cas9
dCas9
(E)
E.
AT/CG- specific
binding molecule
Intercalating dye
Single-strand
nick
DNA polymerase
Fluorescent
nucleotides
Sparse labeling
DNA polymerase
Competetive binding
Continuous labeling
Figure 2. Genetic labeling schemes
(A–D) sparse labeling schemes. (A) Two-step nick translation. In the first step, a nicking enzyme creates a single-strand nick in
the DNA. In the second step, DNA polymerase introduces fluorescent nucleotides to the nicked site. (B) Methyltransferase-based
one-step labeling. (C) Nick translation at target sequences with nicking Cas9, steps are similar to (A). (D) single-step fluorescent
labeling with dCas9. (E) Continuous affinity-based labeling: competitive binding of a nonsequence-specific fluorescent intercalating
dye and an AT/CG-selective molecule. This molecule blocks the dye from binding to these sites, thus keeping them dark while the
rest of the genome is labeled, resulting in a sequence-specific intensity profile of the molecules.
Sparse labeling can be further divided into several techniques. Enzymatic labeling with nicking enzymes, for example, is a well-established scheme for sparse labeling, in which single-strand breaks are introduced at specific sequence
sites by nicking enzymes [4,32,33]. The recognition sites of the enzymes span several bp and occur at distances suitable for genomic mapping. A mix of DNA polymerase and fluorescent nucleotides is then added to repair the nicked
strand, fluorescently labeling the recognition sequence, followed by introduction of DNA ligase which seals the fluorescently repaired strand (Figure 2A). Multiple nicking enzymes with different recognition sites are commercially
available, providing flexibility in tailoring the genetic markers distribution according to the genome or region of interest [4,32,33]. Although very popular in optical mapping, nick-translation on opposite strands of the DNA can lead
to double-strand breaks, compromising the achievable molecular length.
Contrary to the two-step labeling required with nicking enzymes, methyltransferases-based labeling is a direct
sequence-specific labeling method. DNA methyltransferases (DNMTs) are a family of enzymes that natively catalyze
the methylation of DNA bases in biological context. By replacing the natural methyl donor cofactor with a synthetic
analog that contains a fluorescent residue, the enzyme adds the modified moiety to the target sequence, creating a
fluorescent spot (Figure 2B) [25,34]. The use of methyltransferases that are not sensitive to the native DNA methylation of the studied sample makes this direct labeling scheme accurate and specific while keeping the length of the
molecules uncompromised. BioNano Genomics’ Direct Label and Stain (DLS) labeling assay is based on this scheme
[35]. A major drawback of both of these enzymatic labeling schemes is the limited availability of enzymes and corresponding recognition sites.
Lately, Cas9 technology was adopted as a labeling scheme for optical mapping. Cas9 enables custom-designing the
recognition site, thus allowing full control over the density and specificity of labels. McCaffrey et al. and Abid et al.
harnessed a mutant Cas9 enzyme that can cleave single strands to perform a two-step nick labeling at customizable
target sequences, such as telomere repeat sequences [36–38] (Figure 2C), while Zhang et al. presented a single-step
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Fluorescent
nucleotides
Single-strand nick
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labeling scheme that includes a mutant Cas9 with no cutting activity (dCase9) and a fluorophore embedded within the
CRISPR-dCas9 complex [39] (Figure 2D). This method can improve the mapping sensitivity to structural variations,
as it is able to target unique regions, not accessible by commercially available enzymes; however, up until now, Cas9
and dCas9 labeling were only implemented for whole-genome mapping together with nicking enzymes and not on
their own.
Alongside the above sparse labeling schemes, dense enzymatic labeling at frequent sequence motifs can create
a continuous fluorescence pattern along the DNA due to the overlap of the labels’ emission signal. These continuous patterns represent the underlying sequence and were used by Grunwald et al. to classify bacteriophage
genomes in nanochannels [25]. An elegant and cost-effective alternative to such dense labeling approach uses the
sequence-specific affinity of intercalating molecules. Continuous affinity-based labeling provides an alternate genome
mapping method, first established by denaturation mapping [26–28], followed by affinity displacement using competitive binding. In competitive binding two agents are used for labeling: a nonsequence-specific intercalating fluorescent
dye (commonly YOYO-1), and a molecule that binds selectively to either AT- or CG- rich sites (e.g., the AT-specific
antibiotic Netropsin). This molecule blocks the intercalating dye from binding to these sites, otherwise free to stain
the rest of the genome. In this manner, continuous profiles of AT or GC densities are generated, and can be compared
to a computer-generated theoretical AT or GC content map for genomic alignment (see Figure 2E) [40]. Such profiles
eliminate the need for DNA backbone staining, as the DNA molecules are already continuously marked, releasing the
extra color to be used for additional observables. This method works well for small genomes, and is used for bacterial
strain identification in clinical settings [29,41]. Nyberg et al. [42] used it to identify plasmids in a clinical isolate, and
Müller et al. combined it with CRISPR/Cas9 to identify antibiotic resistance genes [43]. Recently, competitive binding
was used by Müller et al. to map fragments of the human genome [30]. Nevertheless, the method has not yet been
applied for high-throughput mapping of large genomes.
Physical aspects of optical mapping
The physical aspects of optical genome mapping in nanochannels dictate both its advantages and its limitations.
Epi-illumination fluorescence imaging, used for visualizing the barcode patterns, provides a large field of view
(FOV) for high throughput data acquisition. On the other hand, as any optical imaging method, fluorescence imaging imposes a limitation on the achievable spatial resolution named the diffraction limit. Due to the diffraction of
light, close-by markers could be distinguished apart only if they are separated by more than approximately half of
their emitted light’s wavelength (∼250 nm that corresponds to ∼800 bp depending on the stretching factor of the
DNA molecules in the nanochannels). Optical resolution sets a limit on the maximal information density that can be
encoded onto the DNA molecules.
Another advantage of fluorescence imaging is the ability to use color for multiplexing and differentiating various
types of genomic observables on the same DNA molecules. Yet, as discussed in a recent work by Jeffet et al. [44],
introducing additional colors results in a reduction of throughput by either: (i) sequential color acquisition by emission filter switching, which increases the acquisition time linearly with each additional color; or (ii) by splitting the
camera’s field of view to image multiple colors simultaneously, therefore increasing the amount of acquisitions needed
to cover the sample area. Nevertheless, introducing a multi-color scheme is a crucial step in order to have a holistic
understanding of the interplay between various epigenetic and genetic modifications and will be discussed in the last
section of this review.
The last main physical aspect at play in this method, is the nanochannel confinement used for linearizing the
DNA molecules. Since the DNA molecules are not immobilized inside the channels, they can be electrically driven
in and out of the channels allowing numerous imaging cycles on the same array. This key feature enables ultra-high
throughput and high coverage of the entire human genome in a single experiment [2,16]. On the other hand, this
also implies that during the acquisition process the DNA molecules are free to move inside the nanochannels and
accordingly experience thermal fluctuations at room temperature. These fluctuations limit two different aspects in the
process of marker localization and molecule digitization (Figure 1B): (i) resolution, e.g., the ability to separate between
two close-by markers and detect their location individually; and (ii) mapping accuracy, the ability to determine the
correct genomic location of a marker according to its localization in the image.
As shown and calculated in some recent works [17,45–48], during the exposure time of a single frame (∼150–200
ms in the commercial system) the thermal fluctuations smear the markers’ signal, which limits the resolution of two
adjacent markers to ∼1.5–3 kbp separation. This value is larger than the optical diffraction limit discussed above
and therefore the fluctuations are the main limit on the achievable resolution. The mapping accuracy is also limited
due to the fluctuations. A single-frame-acquisition captures the DNA molecules at a nonequilibrium conformation,
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Super-resolved genetic mapping
Super-resolution techniques have revolutionized microscopy and biological research since their introduction in recent
years [65–68]. The evolution of the field, technical details and future directions are extensively discussed in several
reviews [69–71].
In the context of optical mapping, super-resolution was implemented in recent years mainly on immobilized DNA
molecules stretched on surfaces [23,72,73], where the gradual bleaching of single fluorophores was exploited [68]
to produce super-resolved maps of marker locations along single DNA molecules, with down to 10 nm resolution.
The fundamental assumption underlying these methods is that the molecules are fixed in space, which consequently
allows recognition of the different markers according to their locations at different times. The major drawback of
super-resolution imaging in the context of optical mapping, is the requirement to record many frames (typically
∼100–1000 frames [72]) of the same FOV, in order to derive the super-resolved map. Thus, the increase in resolution
is achieved at the expense of a significant reduction in throughput compared with single-frame optical mapping.
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therefore resulting in erroneous markers location registration compared with their true genomic position (Figure
3A).
Therefore, a theoretic physical account of the thermal behavior of DNA in nanochannels, is essential for assessing and improving the limits of resolution and accuracy. When DNA is confined to nanochannels with cross-section
much smaller than its statistical folding length (persistence length), it aligns with the channel and exhibits both extension and fluctuation behavior described theoretically by the classic Odijk theory [49] (leftmost panel in Figure 3A).
However, optical mapping is generally done in nanochannels that have cross-sections on the same scale as the DNA
persistence length, and therefore deviates from this ideal regime [45,47,48]. Adjustments to the Odijk theory have
been extensively studied in recent years, both theoretically [17,46,50–54] and experimentally [17,45,47,48,55–58],
and we refer the readers to two excellent reviews on the subject [6,59]. The key concepts relevant here are that deviations from the fully extended classic Odijk regime can be manifested as backfolding, hairpins, loops and bunching
of the DNA molecules inside the channels (leftmost panel in Figure 3A.). These deviations were incorporated into
recent theoretical models [51,60], albeit minor discrepancies still remain between theory and experimental data of
molecules confined to <50 × 50 nm2 cross-sections channels [17,61,62]. As a result of this research, an important
reduction of nanochannels’ widths from 45 nm to 34 nm, was introduced by BioNano Genomics in their commercial Saphyr chips for optical genome mapping. This allows better DNA extension and therefore increased genomic
resolution, and reduced alignment errors due to thermal fluctuations [17,45]. Despite remaining limitations [62], the
current framework is well-adequate to allow the extraction of valuable genetic and epigenetic information as will be
discussed in the following sections.
Although thermal fluctuations are an inherent limitation of the nanochannel-based mapping method [45,48,59,63],
a practical approach to minimize their effect and to increase the mapping accuracy was recently introduced by Jeffet et
al. [45]. The approach uses short exposure (40 ms) multi-frame time-lapse acquisitions instead of the longer exposure
(150–200 ms) single-frame acquisitions usually used in mapping experiments. This enables recording and analysis of
the thermal fluctuations of individual DNA molecules inside the nanochannels. As these fluctuations are correlated
at short molecular distances (see Figure 3A,B), calculating pairwise-distances between neighboring markers removes
the correlated fluctuations (middle panels in Figure 3B), and therefore provides genomic mapping that is more robust to the blinking and bleaching behavior of the markers. Averaging over these pairwise distances had shown to
improve the overall mapping accuracy by ∼2-fold (see rightmost panel in Figure 3B) compared with the straightforward marker locations averaging, and more than 6-fold compared with the 450 nm (∼1.5 kbp) mapping accuracy
of single-frame acquisition generally accepted in the field [4,17,45,47,48,64]. Consequently, this improved mapping
accuracy enabled a 5-fold increase in mapping alignment scores compared to single-frame-acquisition mapping [45].
The core idea underlying this simple analysis is that markers along the DNA molecule can be used as ‘fluctuation
reporters’, registering the local collective motion of the DNA, and thus allow fluctuation correction to the barcode
registration. The method can be further improved by increasing the label density along the DNA molecule up to the
resolution limit of two adjacent markers (∼1.5 kbp), enabling to characterize the DNA fluctuations with better spatial
resolution and to apply better fluctuations correction.
The main caveat of this approach is the need for ∼10-fold increase in acquisition time per FOV in order to record
sufficient marker positions for effective time averaging (∼40 frames are sufficient to achieve a substantial increase
in accuracy [45]). This reduces the overall throughput, but can prove useful when applied to genomes that present
assembling difficulties or when trying to compare molecules exhibiting small genomic differences.
Essays in Biochemistry (2021) EBC20200021
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Figure 3. Physical aspects of genomic optical mapping in nanochannels
(A) DNA fluctuations in nanochannels. Left, possible conformations of DNA molecules confined to nanochannels that contribute to
the measured fluctuations. Reprinted from [47], with the permission of AIP Publishing. Middle, raw kymograph (left) and the corresponding marker localizations (right) of barcode labeled genomic DNA extracted from E. coli, showing the thermal fluctuations of
confined DNA. Adapted from [48], with the permission of AIP Publishing. Right, probability distribution of observed marker separations in relation to their aligned genomic distance (calculated using 70,305 observed marker positions from single-frame images
of 4557 DNA molecules confined to 43 × 43 nm2 cross-section channels). The distribution gets wider as the genomic distance
increases and therefore mapping accuracy reduces with genomic marker separation. Reprinted from [47], with the permission of
AIP Publishing. (B) Improving mapping accuracy with pairwise distance averaging. Left, raw kymograph of the D4Z4 tandem repeat
region in chromosome 4 (see optical genome mapping impact section), confined to 45 × 45 nm2 cross-section channels (repetitive
region marked with the red dashed frame). The repetitive region was used by Jeffet et al. [45] as a ruler to quantify the accuracy and
resolution of optical mapping. Adjacent spots in the repetitive segment are distanced 3.3 kbp and each spot is composed of two
unresolved fluorophores spaced 676 bp apart. Middle, comparison between localizations maps and cumulative pairwise distances
maps of the repetitive region. The localizations map shows correlations in marker fluctuations at short genomic separations, while
the distances map shows reduced fluctuations. Right, observed locations distribution compared to the pairwise distance distribution of the ruler molecule’s markers shown to the left. The distances standard deviation is reduced by ∼2-fold compared with
locations, allowing increased mapping accuracy. (C) Enabling super-resolution with distance averaging. Left, schematic illustration
of the method. A target consisting of multiple sub-diffraction-limit spaced fluorophores is imaged as a single gaussian signal on the
camera. Pairwise distance recording between the target and an adjacent marker allows to remove the local collective fluctuations,
and thus enable sensitivity to distance shifts originating from the target’s fluorophores blinking or bleaching behavior. Middle, 3D visualization of the intensity–time profile of two fluorescent spots presented in panel (B). Each spot is composed of two fluorophores,
where a bleaching event of one of the fluorophores of the left spot is evident after 15 frames. Top right, Intensity time trace of the
spots. Bottom right, pairwise distance time-trace between the two spots. The bleaching step alters the mean distance between
the two spots allowing to resolve the sub-diffraction-limit distance between them with ∼30 nm resolution. Panels (B and C) were
adapted with permission from [45]. Copyright (2016) American Chemical Society.
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The biological impact of optical genome mapping
In the past few years, optical mapping has positioned itself as the leading technology for large-scale SVs and CNVs
detection. It is considered as a high-end alternative to cytogenetic analysis and as a complement to NGS approaches.
In this section, we will briefly review some of the recent progress in clinical and biological findings that were enabled
by optical mapping.
Current research employs optical mapping to outline the diversity found in the human genome and thus to assemble a more comprehensive map of the genome. In several recent studies, optical mapping greatly contributed
to the resolution of haplotypes, SVs and complex regions such as telomeres and sub-telomeric regions, previously
inaccessible by NGS alone [11,38,74–79].
SVs are associated with a wide variety of diseases, from rare genetic disorders to cancer [80,81]. Recent works that
studied cancer genomes identified new disease-relevant SVs, including highly complex rearrangements and repetitive regions, thus resolving loose ends in sequencing-based maps [12,13,82,83]. Poretti-Boltshauser syndrome and
Duchenne muscular dystrophy are among the genetic disorders that have recently benefited from SV detection, enabled by optical mapping [9,20,84].
Facioscapulohumeral muscular dystrophy 1 (FSHD1) is a common type of muscular dystrophy, characterized by
a CNV of the D4Z4 tandem repeat in chromosome 4. The length of each repeat unit is 3.3 kbp, and the number
of repeats can reach 150 copies in healthy individuals. However, an array of less than 10 D4Z4 copies is considered
pathogenic. Recently, Zhang et al. [85] and Dai et al. [21] demonstrated the clinical diagnosis of the syndrome by
optical mapping and showed that it is superior to the generally used blot hybridization or FISH combing. Nevertheless, disease manifestation is not determined solely by this genetic CNV, but also by the epigenetic methylation
status of the tandem repeats [86,87]. Thus, multiplexing epigenetic with genetic information enabled Sharim et al. to
simultaneously detect copy number and methylation pattern of individual DNA molecules, thereby resolving different haplotypes and distinguishing an FSHD-affected patient from a healthy individual [88]. This result stresses the
importance of a holistic view that combines genetic and epigenetic information in order to resolve a full genomic
picture. The next section will highlight the emerging incorporation of epigenetic information into optical mapping.
Optical mapping of epigenetics
The function of the genome and the resulting gene expression profile is regulated by genetic and epigenetic mechanisms. The epigenetic information is crucial for regulating specific cell functions [89]. Major epigenetic mechanisms
include covalent modifications of DNA bases [90–92] and histones [92,93], chromatin structure [89,93,94] and noncoding RNAs that can control gene expression [95]. Unlike the genetic code, which is essentially stable throughout
life, the epigenetic content is dynamically changing in response to environmental cues and has great impact on cell
activity and diseases [96].
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Unlike immobilized DNA mapping, the dynamic movement of markers due to thermal fluctuations in
nanochannel-based optical mapping, prohibits any straight-forward implementation of such super-resolution methods. Although the localization precision of markers in a single frame can be as high as ∼4 nm [47], the fluctuations
completely screen out the subtle localization shifts originating from individual marker bleaching (average standard
deviation of ∼140 nm, see rightmost panel in Figure 3B). This essentially limited the effective theoretical resolution
of nanochannel based optical mapping to ∼1 kbp [46] and experimentally to ∼1.5–3 kbp [4,17,45,47,48]. This restriction was alleviated by applying the ‘fluctuation reporters’ concept to reduce the local collective fluctuations at the
occurrence time of a bleaching event [45]. As illustrated in Figure 3C, in order to resolve sub-diffraction-limit distances in a target composed of multiple fluorophores, pairwise distance recording between the target and a close-by
marker was used. Using pairwise distances, instead of marker localizations, reduces the fluctuations to a degree where
they are smaller than the shifts caused by marker blinking or bleaching. This re-enables the use of super-resolution
techniques [68,72] to determine the inner structure of the target by the distance step-shift at a bleaching or blinking event in the target. Jeffet et al. [45] used this principle to resolve markers separated 670 bp apart with ∼30 nm
resolution (see rightmost panel in Figure 3C) [45], introducing a 15-fold resolution improvement compared to the
standard ∼450 nm (∼1.5 kbp) single-frame resolution limit [4,46,47]. However, the precision and resolution of this
technique depend on the proximity of the reference ‘fluctuation reporter’ marker. As the fluctuations correlation
between two markers drops with increasing marker spacing, the effectiveness of the correction and therefore the
super-resolution capability drops accordingly. Hence, similar to the mapping accuracy enhancement, higher label
density corresponds with better super-resolution capability, permitting that the reference marker can still be resolved
from the super-resolution target.
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The use of color to distinguish between biological entities is one of the foundations of fluorescence microscopy.
In optical mapping, it allows to visualize the genetic information, together with multiple types of epigenetic contents on the same DNA molecule (Figure 4A). Once the genomic origin of the molecule is mapped according to the
genetic barcode, the different epigenetic layers are instantaneously placed into their genomic context, and provide
locus-specific information. Various labeling schemes of epigenetic features have been developed in recent years and
will be summarized in this section together with an account of their impact on epigenetic research.
A primary epigenetic modification with direct impact on gene expression is DNA methylation of the base cytosine
(5-mC) in the dinucleotide sequence CpG [90]. Unmethylated CpG sites can be specifically labeled by methyltransferase enzymes, creating a complementary map to the methylome. For example, the methyltransferase M.TaqI can
directly transfer a fluorophore from a synthetic cofactor to the adenine base in the enzyme’s recognition sequence
TCGA. However, if the CpG nested in this sequence context is methylated or modified, this reaction is blocked, resulting in the exclusive labeling of unmodified cytosines in every TCGA sequence context (Figure 4B,i) [25,88,97].
In 2019, Sharim et al. used this scheme to optically map a reduced representation of the human methylome for the
first time. This ensemble-averaged reduced representation map (∼6% of human CpG sites are found within TCGA
context) captures the majority of regulatory sites in the genome [88]. Recently, this long-read methylation data was
analyzed at a single-cell level for the first time. The methylation status of promoters and their distal enhancers, simultaneously imaged on the same long DNA molecules, served to accurately deconvolve cell-type mixtures and subpopulations within a sample [98]. A recent improvement to methylation labeling, replacing the methyltransferase M.TaqI
with a modified M.SssI (which recognizes any unmethylated CpG), enabled the generation of genome-wide methylation profiles of all CpG sites [99]. DNA methylation can also be labeled directly, using methyl-binding antibodies
coupled with a fluorescent reporter [100]. However, the antibodies’ tendency to aggregate hampers DNA insertion
into the nanochannels, therefore requiring larger channel cross-sections which reduces by ∼10-fold the achievable
resolution compared to covalent base labeling [100].
Another epigenetic modification of the cytosine base, gaining increased interest in recent years due to its link to
gene regulation, development, and disease, is the oxidation product of DNA methylation, 5-hydroxymethylcytosine
(5-hmC) [91]. The fluorescent labeling of this modification involves two steps. First, the enzyme β-glucosyltransferase
(β-GT) is used to attach an azide modified glucose moiety from a synthetic cofactor (UDP-6-N3-Glu), to the hydroxyl group of 5-hmC. In the second step, a copper-free click reaction is used to connect a fluorophore-alkyne to the
azide-labeled 5-hmC (Figure 4B,ii) [101–106]. Gabrieli et al. presented a whole-genome optical 5-hmC map of human
peripheral blood cells, revealing variable regions and long-range information that were not accessible by sequencing
[106].
Another important information layer that could be explored by optical mapping is the DNA damage content. Cellular DNA damage lesions are continuously induced by exposure to various exogenous and endogenous agents, and
are a major cause for genomic instability. A labeling scheme called RADD (repair-assisted damage detection), was
developed to fluorescently label single-strand lesions in vitro by a two-step process [107–109]. First, native repair
enzymes excise the damaged bases and leave a single-strand gap at the damage locus. Next, DNA polymerase and
ligase are introduced and fill this gap with fluorescent nucleotides, allowing the visualization of the repaired damage
sites (Figure 4B,iii). As a proof of principle, sites of DNA damage induced by the chemotherapeutic agent etoposide
were recently labeled and mapped using competitive binding [30]. In the future, optical mapping can potentially be
used to reveal the effect of drugs and environmental toxicants on the genome, specifically at regions that are hard to
analyze by NGS, and locate genomic hotspots prone to damage and mutations.
Apart from chemical DNA modifications, multi-color optical mapping can be used to study basic biological processes. A recent example was seen in the mapping of origins of DNA replication [110–112]. Mapping these sites
provides basic understanding of replication mechanisms and kinetics in normal conditions. The effect of different
factors, including damaging agents, drugs, and diseases on replication, could also be studied in this manner. Lately,
Wang et al. used in vivo fluorescent nucleotide pulse-labeling of human cells to mark freshly synthesized DNA and
trace replication initiation sites with optical mapping, including sites active in very small percentages of cells (Figure
4B,iv) [110].
To summarize, any genomic feature that can be labeled with a fluorescent reporter and does not impair DNA
linearization, has the potential to be optically mapped. Detection of multiple types of observables on the same DNA
molecule remains a challenge in genomics. Optical mapping holds the potential to multiplex information on a single
DNA molecule, and thus map genomic interactions, variability and context with single-molecule sensitivity.
9
Essays in Biochemistry (2021) EBC20200021
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A.
(A)
5-Methylcytosine
(5-mC)
5-Hydroxymethylcytosine
(5-hmC)
NH2
NH2
CH3
N
O
DNA replication
O
N
DNA damage
CH2OH
N
Genetic motif
N
(I.)
(II.)
5-mC
T
C
G
A
T
C
G
A
A
G
C
T
A
G
C
T
(IV.)
(III.)
5-hmC
Damaged lesion
C
T
C
G
G
G
C
T
G
A
G
C
C
C
G
A
C
Synchronized cells
G
T
G
C
A
C
5-hmC
Fluorescent
cofactor
M.taql
Repair enzyme
β-GT
UDP-6-Glu-N3
Electroporation with
fluorescent nucleotides
N3
5-mC
T
C
G
A
T
C
G
A
A
G
C
T
A
G
C
T
C
T
C
G
G
G
C
T
G
A
G
C
C
C
G
A
C
G
T
G
C
A
C
N3
DNA polymerase
Click
reaction
Fluorescent
nucleotides
C
T
C
G
G
G
C
T
G
A
G
C
C
C
G
A
C
G
T
G
C
A
C
Recovery to
complete replication
C
T
G
G
T
G
G
A
C
C
A
C
Replication initiation site
(C)
C.
Ground truth
Sequential
multi-color
acquisition
with
ɶm²¶_²¬
Purple acquisition
Red acquisition
Green acquisition
Blue acquisition
Result
Figure 4. Genomic observables and epigenetic optical mapping in nanochannels
(A) Example observables that can be marked and viewed in optical mapping. (B) labeling schemes of the epigenetic modifications
shown in A. (i) labeling of TCGA sequences that contains an unmodified cytosine by the enzyme M.TaqI and a fluorescent cofactor;
(ii) two-step labeling of 5-hmC: the enzyme β-GT attaches a modified glucose with an azide group on it from uridine-diphospho-6-azide-glucose (UDP-6-N3-Glu) to the hydroxyl group of the 5-hmC. Then the azide group is reacted with a fluorescently-labeled alkyne via click chemistry; (iii) two-step labeling of DNA damage sites: The damaged lesion is enzymatically excised, and
replaced by fluorescent nucleotides; (iv) in vitro labeling of origins of DNA replication: fluorescent nucleotides enter synchronized
cells following electroporation. Then, fluorescence is incorporated into the newly replicated DNA and creates symmetrical replication ‘forks’. (C) An exaggerated illustration demonstrating the impact of thermal fluctuations on multi-color marker detection.
Sequential color acquisitions capture the same molecule at different off-equilibrium conformations due to fluctuations. This results
in an erroneous interpretation of marker locations along the DNA molecule compared to the ground truth.
10
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(B)
B.
Essays in Biochemistry (2021) EBC20200021
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Challenges of multi-color optical mapping and future
prospects
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Although dual-color optical mapping has been implemented [88,106,110], mapping more colors on the same
DNA molecules imposes further constraints on the method’s throughput and mapping accuracy. Meanwhile,
super-resolution in two colors was only applied to immobilized optical mapping [73], and has not yet been applied to
nanochannel-based methods. These limitations are the consequence of the color acquisition procedure employed in
the standard fluorescence microscopy setup, where each color is imaged sequentially by inserting a suitable emission
filter to the emission path. The immediate result is that each additional color acquisition requires a linear increase in
acquisition time, reducing the overall throughput.
However, an additional constraint arises from the combination of sequential color acquisition and thermal fluctuations. This creates desynchronization between the barcode maps of different colors, as each color acquisition images
the molecule at a different off-equilibrium conformation (see illustration in Figure 4C). Applying the multi-frame
distance-averaging approach discussed previously would enable resolving this issue by allowing to better approximate the equilibrium DNA conformation. However, different color markers could not be used for accurate distance
calculation, as the measurements are not synchronized. Moreover, the time delay between adjacent frames of the
same color increases with every additional color, therefore multi-color acquisitions reduce the temporal resolution of
the single-color fluctuations characterization. Furthermore, since each color should be corrected independently, the
overall acquisition time would increase by at least 10-fold multiplied by the number of information layers, resulting
in a tremendous decrease in throughput. For these reasons, and since only the genetic markers are used as anchors
to map the individual molecules to the genome, additional colors would reduce the enhancement in overall genomic
mapping accuracy compared with the results reported in [45]. Finally, since the different color acquisitions are not
synchronized, super-resolution could only be implemented independently for each color, using only markers of the
same color. This imposes the dense labeling constraint needed for super-resolution, individually to each of the colors.
Emerging possibilities of simultaneous color acquisition could alleviate these problems and allow fusing the
recorded fluctuation information from the different colors. Methods such as multi-color split view [73,113], where
the FOV is split between emission channels using dichroic mirrors; or spectral imaging [44,114–116], where spectral images are recorded using a dispersive element, can record marker locations of different colors at the same time.
Therefore, localizations of markers with different colors can be used to create an integrated multi-color fluctuation
map. This would yield a dense characterization of DNA fluctuations, greatly increasing the achievable spatial and
temporal mapping resolution with reduction of overall acquisition time compared with the single-color fluctuation
characterization. Moreover, simultaneous multi-color acquisition methods allow to resolve markers of different colors even when they are spaced by sub-diffraction limit distances. This enables registering the fluctuations with even
higher spatial resolution that would result in unprecedented mapping accuracy and super-resolution capabilities. Finally, the constraint on label density needed for applying super-resolution, would be alleviated from dense labeling of
each color independently to the total label density of all colors, allowing to apply super-resolution on all information
contents even when some motifs are sparsely dispersed on the DNA.
Conclusions
In this brief review, we have introduced nanochannel-based optical genome mapping, highlighting the method’s ability to tackle outstanding problems unaddressed by available sequencing methods. We have summarized the various
multidisciplinary aspects of the method including: (i) the chemically oriented mechanisms for genetic and epigenetic
fluorescence labeling; (ii) the physical limitations of the method arising from both the optical acquisition and the
thermodynamic properties of DNA confinement, and the ways to circumvent them; (iii) the biological impact of the
method in exploration of large-scale genomic aberrations, epigenetic content and other genomic observables such as
DNA damage and origins of replication.
Optical mapping’s ability to visualize multiple observables on the same single DNA molecule, will no doubt be
exploited in the near future to elucidate the interactions between the various information layers encoded in our
genome. We have examined the possibilities of exploring this venue and their current limitations, and pinpointed
to multi-color simultaneous-acquisition techniques that would allow to remove these limitations and provide better
mapping accuracy and resolution than ever.
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution
License 4.0 (CC BY-NC-ND).
11
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
Summary
Optical mapping in nanochannels is a single-molecule, high-throughput method that captures a high
fraction of ultra-long genomic fragments and may elucidate genomic information that is otherwise
inaccessible using sequencing.
•
Thermal fluctuations of the DNA molecules in the nanochannels pose the limit on mapping accuracy
and resolution.
•
Fluctuation mapping can improve mapping accuracy by 6-fold and allows resolution enhancement
of 15-fold by super-resolution localization.
•
Multi-color fluorescent labeling allows multiplexing several layers of genomic information coexisting
on the same DNA molecules, potentially allowing a holistic view of the genome.
•
Simultaneous color acquisition, as opposed to the current sequential color acquisition, would allow
to further improve the resolution and accuracy of the method.
Competing Interests
The authors declare that there are no competing interests associated with the manuscript.
Funding
Y.E. acknowledges support from the European Research Council Consolidator grant [grant number 817811].
Open Access
Open access for this article was enabled by the participation of Tel Aviv University in an all-inclusive Read & Publish pilot with
Portland Press and the Biochemical Society under a transformative agreement with MALMAD.
Author Contribution
J.J. and S.M. wrote the manuscript. Y.M. and Y.E. reviewed and edited the manuscript.
Acknowledgments
J.J. is grateful to the Azrieli Foundation for the award of an Azrieli Fellowship.
Abbreviations
β-GT, β-glucosyltransferase enzyme; 3D, 3-dimensional; 5-hmC, 5-hydroxymethylcytosine; 5-mC, 5-methylcytosine; bp (kbp,
Mbp, Gbp, Tbp), (kilo-, Mega-, Giga-, Tera-) base-pairs; Cas9, CRISPR-associated protein 9; CNV, copy number variation;
CpG, cytosine-phosphate-guanine (cytosine base directly followed by guanine); CRISPR, clustered regularly interspaced short
palindromic repeats; dCase9, nuclease-deficient Cas9; DLS, direct label and stain; DNA, deoxyribonucleic acid; DNMT, DNA
methyltransferase; E. coli, Escherichia coli; FOV, field of view; FSHD, facioscapulohumeral muscular dystrophy; ms, millisecond; NGS, next-generation sequencing; nm, nanometer; PacBio, Pacific Biosciences; RADD, repair-assisted damage detection; RNA, ribonucleic acid; SMRT sequencing, single-molecule real-time sequencing; SV, structural variation; UDP-6-N3-Glu,
uridine-diphospho-6-azide-glucose; YOYO-1, homodimer of oxazole yellow (green fluorescent dye used for DNA staining).
References
1
2
3
12
Müller, V. and Westerlund, F. (2017) Optical DNA mapping in nanofluidic devices: principles and applications. Lab. Chip. 17, 579–590,
https://doi.org/10.1039/C6LC01439A
Yuan, Y., Chung, C.Y.-L. and Chan, T.-F. (2020) Advances in optical mapping for genomic research. Comput Struct Biotechnol. J. 18, 2051–2062,
https://doi.org/10.1016/j.csbj.2020.07.018
Levy-Sakin, M. and Ebenstein, Y. (2013) Beyond sequencing: optical mapping of DNA in the age of nanotechnology and nanoscopy. Curr. Opin.
Biotechnol. 24, 690–698, https://doi.org/10.1016/j.copbio.2013.01.009
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons
Attribution License 4.0 (CC BY-NC-ND).
Downloaded from http://portlandpress.com/essaysbiochem/article-pdf/doi/10.1042/EBC20200021/906021/ebc-2020-0021c.pdf by guest on 28 March 2021
•
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
4
5
6
7
8
9
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons
Attribution License 4.0 (CC BY-NC-ND).
Downloaded from http://portlandpress.com/essaysbiochem/article-pdf/doi/10.1042/EBC20200021/906021/ebc-2020-0021c.pdf by guest on 28 March 2021
10
Lam, E.T., Hastie, A., Lin, C., Ehrlich, D., Das, S.K., Austin, M.D. et al. (2012) Genome mapping on nanochannel arrays for structural variation analysis
and sequence assembly. Nat. Biotechnol. 30, 771–776, https://doi.org/10.1038/nbt.2303
Bocklandt, S., Hastie, A. and Cao, H. (2019) Bionano genome mapping: high-throughput, ultra-long molecule genome analysis system for precision
genome assembly and haploid-resolved structural variation discovery. In Single Mol. and Single Cell Sequencing (Suzuki, Y., ed.), pp. 97–118,
Springer Singapore, Singapore, https://doi.org/10.1007/978-981-13-6037-4˙7
Dorfman, K.D., King, S.B., Olson, D.W., Thomas, J.D.P. and Tree, D.R. (2013) Beyond gel electrophoresis: microfluidic separations, fluorescence burst
analysis, and DNA stretching. Chem. Rev. 113, 2584–2667, https://doi.org/10.1021/cr3002142
Mendelowitz, L. and Pop, M. (2014) Computational methods for optical mapping. Gigascience 3, 33, https://doi.org/10.1186/2047-217X-3-33
Bogas, D., Nyberg, L., Pacheco, R., Azevedo, N.F., Beech, J.P., Gomila, M. et al. (2017) Applications of optical DNA mapping in microbiology.
BioTechniques 62, 255–267, https://doi.org/10.2144/000114555
Barseghyan, H., Tang, W., Wang, R.T., Almalvez, M., Segura, E., Bramble, M.S. et al. (2017) Next-generation mapping: a novel approach for detection
of pathogenic structural variants with a potential utility in clinical diagnosis. Genome Med. 9, 90, https://doi.org/10.1186/s13073-017-0479-0
Balachandran, P. and Beck, C.R. (2020) Structural variant identification and characterization. Chromosome Res. 28, 31–47,
https://doi.org/10.1007/s10577-019-09623-z
Ebert, P., Audano, P.A., Zhu, Q., Rodriguez-Martin, B., Porubsky, D., Bonder, M.J. et al. (2021) Haplotype-resolved diverse human genomes and
integrated analysis of structural variation. Science, https://doi.org/10.1126/science.abf7117
Crumbaker, M., Chan, E.K.F., Gong, T., Corcoran, N., Jaratlerdsiri, W., Lyons, R.J. et al. (2020) The Impact of Whole Genome Data on Therapeutic
Decision-Making in Metastatic Prostate Cancer: A Retrospective Analysis. Cancers 12, 1178, https://doi.org/10.3390/cancers12051178
Peng, Y., Yuan, C., Tao, X., Zhao, Y., Yao, X., Zhuge, L. et al. (2020) Integrated analysis of optical mapping and whole-genome sequencing reveals
intratumoral genetic heterogeneity in metastatic lung squamous cell carcinoma. Transl. Lung Cancer Res. 9, 670–681,
https://doi.org/10.21037/tlcr-19-401
Jain, M., Olsen, H.E., Paten, B. and Akeson, M. (2016) The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community.
Genome Biol. 17, 239, https://doi.org/10.1186/s13059-016-1103-0
Wenger, A.M., Peluso, P., Rowell, W.J., Chang, P.-C., Hall, R.J., Concepcion, G.T. et al. (2019) Accurate circular consensus long-read sequencing
improves variant detection and assembly of a human genome. Nat. Biotechnol. 37, 1155–1162, https://doi.org/10.1038/s41587-019-0217-9
Bionano Genomics Website [Internet]. [cited 2021 Jan 6]. Available from: https://bionanogenomics.com/products/bionano-data-options/
Chuang, H.-M., Reifenberger, J.G., Bhandari, A.B. and Dorfman, K.D. (2019) Extension distribution for DNA confined in a nanochannel near the Odijk
regime. J. Chem. Phys. 151, 114903, https://doi.org/10.1063/1.5121305
Amarasinghe, S.L., Su, S., Dong, X., Zappia, L., Ritchie, M.E. and Gouil, Q. (2020) Opportunities and challenges in long-read sequencing data analysis.
Genome Biol. 21, 30, https://doi.org/10.1186/s13059-020-1935-5
Logsdon, G.A., Vollger, M.R. and Eichler, E.E. (2020) Long-read human genome sequencing and its applications. Nat. Rev. Genet. 21, 597–614,
https://doi.org/10.1038/s41576-020-0236-x
Chen, M., Zhang, M., Qian, Y., Yang, Y., Sun, Y., Liu, B. et al. (2020) Identification of a likely pathogenic structural variation in the LAMA1 gene by
Bionano optical mapping. NPJ Genomic Med. 5, 31, https://doi.org/10.1038/s41525-020-0138-z
Dai, Y., Li, P., Wang, Z., Liang, F., Yang, F., Fang, L. et al. (2020) Single-molecule optical mapping enables quantitative measurement of D4Z4 repeats
in facioscapulohumeral muscular dystrophy (FSHD). J. Med. Genet. 57, 109–120, https://doi.org/10.1136/jmedgenet-2019-106078
Nanopore Products Comparison [Internet]. Oxford Nanopore Website. [cited January, 26, 2021]. Available from:
https://nanoporetech.com/products/comparison?minion1b=on&minion1c=on&gridion=on&promethion=on
Vranken, C., Deen, J., Dirix, L., Stakenborg, T., Dehaen, W., Leen, V. et al. (2014) Super-resolution optical DNA Mapping via DNA
methyltransferase-directed click chemistry. Nucleic Acids Res. 42, https://doi.org/10.1093/nar/gkt1406
Das, S.K., Austin, M.D., Akana, M.C., Deshpande, P., Cao, H. and Xiao, M. (2010) Single molecule linear analysis of DNA in nano-channel labeled with
sequence specific fluorescent probes. Nucleic Acids Res. 38, e177–e177, https://doi.org/10.1093/nar/gkq673
Grunwald, A., Dahan, M., Giesbertz, A., Nilsson, A., Nyberg, L.K., Weinhold, E. et al. (2015) Bacteriophage strain typing by rapid single molecule
analysis. Nucleic Acids Res. 43, e117, https://doi.org/10.1093/nar/gkv563
Marie, R., Pedersen, J.N., Bærlocher, L., Koprowska, K., Pødenphant, M., Sabatel, C. et al. (2018) Single-molecule DNA-mapping and whole-genome
sequencing of individual cells. Proc. Natl. Acad. Sci. U.S.A. 115, 11192–11197, https://doi.org/10.1073/pnas.1804194115
Reisner, W., Larsen, N.B., Silahtaroglu, A., Kristensen, A., Tommerup, N., Tegenfeldt, J.O. et al. (2010) Single-molecule denaturation mapping of DNA
in nanofluidic channels. Proc. Natl. Acad. Sci. 107, 13294–13299, https://doi.org/10.1073/pnas.1007081107
Freitag, C., Noble, C., Fritzsche, J., Persson, F., Reiter-Schad, M., Nilsson, A.N. et al. (2015) Visualizing the entire DNA from a chromosome in a single
frame. Biomicrofluidics 9, 044114, https://doi.org/10.1063/1.4923262
Nilsson, A.N., Emilsson, G., Nyberg, L.K., Noble, C., Stadler, L.S., Fritzsche, J. et al. (2014) Competitive binding-based optical DNA mapping for fast
identification of bacteria–multi-ligand transfer matrix theory and experimental applications on Escherichia coli. Nucleic Acids Res. 42, e118,
https://doi.org/10.1093/nar/gku556
Müller, V., Dvirnas, A., Andersson, J., Singh, V., Sriram, K.K., Johansson, P. et al. (2019) Enzyme-free optical DNA mapping of the human genome
using competitive binding. Nucleic Acids Res. 47, e89, https://doi.org/10.1093/nar/gkz489
Neely, R.K., Deen, J. and Hofkens, J. (2011) Optical mapping of DNA: single-molecule-based methods for mapping genomes. Biopolymers 95,
298–311, https://doi.org/10.1002/bip.21579
Hastie, A.R., Dong, L., Smith, A., Finklestein, J., Lam, E.T., Huo, N. et al. (2013) Rapid genome mapping in nanochannel arrays for highly complete and
accurate de novo sequence assembly of the complex Aegilops tauschii genome. PLoS ONE 8, e55864, https://doi.org/10.1371/journal.pone.0055864
13
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
14
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons
Attribution License 4.0 (CC BY-NC-ND).
Downloaded from http://portlandpress.com/essaysbiochem/article-pdf/doi/10.1042/EBC20200021/906021/ebc-2020-0021c.pdf by guest on 28 March 2021
33 Jo, K., Dhingra, D.M., Odijk, T., de Pablo, J.J., Graham, M.D., Runnheim, R. et al. (2007) A single-molecule barcoding system using nanoslits for DNA
analysis. Proc. Natl. Acad. Sci. 104, 2673–2678, https://doi.org/10.1073/pnas.0611151104
34 Goyvaerts, V., Van Snick, S., D’Huys, L., Vitale, R., Helmer Lauer, M., Wang, S. et al. (2020) Fluorescent SAM analogues for methyltransferase based
DNA labeling. Chem. Commun. 56, 3317–3320, https://doi.org/10.1039/C9CC08938A
35 Deschamps, S., Zhang, Y., Llaca, V., Ye, L., Sanyal, A., King, M. et al. (2018) A chromosome-scale assembly of the sorghum genome using nanopore
sequencing and optical mapping. Nat. Commun. 9, 4844, https://doi.org/10.1038/s41467-018-07271-1
36 McCaffrey, J., Sibert, J., Zhang, B., Zhang, Y., Hu, W., Riethman, H. et al. (2016) CRISPR-CAS9 D10A nickase target-specific fluorescent labeling of
double strand DNA for whole genome mapping and structural variation analysis. Nucleic Acids Res. 44, e11, https://doi.org/10.1093/nar/gkv878
37 Abid, H.Z., Young, E., McCaffrey, J., Raseley, K., Varapula, D., Wang, H.-Y. et al. (2020) Customized optical mapping by CRISPR-Cas9 mediated DNA
labeling with multiple sgRNAs. Nucleic Acids Res. 49, e8, https://doi.org/10.1093/nar/gkaa1088
38 Abid, H.Z., McCaffrey, J., Raseley, K., Young, E., Lassahn, K., Varapula, D. et al. (2020) Single-molecule analysis of subtelomeres and telomeres in
Alternative Lengthening of Telomeres (ALT) cells. BMC Genomics 21, 485, https://doi.org/10.1186/s12864-020-06901-7
39 Zhang, D., Chan, S., Sugerman, K., Lee, J., Lam, E.T., Bocklandt, S. et al. (2018) CRISPR-bind: a simple, custom CRISPR/dCas9-mediated labeling of
genomic DNA for mapping in nanochannel arrays. bioRxiv, https://doi.org/10.1101/371518
40 Nyberg, L.K., Persson, F., Berg, J., Bergström, J., Fransson, E., Olsson, L. et al. (2012) A single-step competitive binding assay for mapping of single
DNA molecules. Biochem. Biophys. Res. Commun. 417, 404–408, https://doi.org/10.1016/j.bbrc.2011.11.128
41 Müller, V., Nyblom, M., Johnning, A., Wrande, M., Dvirnas, A., Kk, S. et al. (2020) Cultivation-free typing of bacteria using optical DNA mapping. ACS
Infect. Dis. 6, 1076–1084, https://doi.org/10.1021/acsinfecdis.9b00464
42 Nyberg, L.K., Quaderi, S., Emilsson, G., Karami, N., Lagerstedt, E., Müller, V. et al. (2016) Rapid identification of intact bacterial resistance plasmids via
optical mapping of single DNA molecules. Sci. Rep. 6, 30410, https://doi.org/10.1038/srep30410
43 Müller, V., Rajer, F., Frykholm, K., Nyberg, L.K., Quaderi, S., Fritzsche, J. et al. (2016) Direct identification of antibiotic resistance genes on single
plasmid molecules using CRISPR/Cas9 in combination with optical DNA mapping. Sci. Rep. 6, 37938, https://doi.org/10.1038/srep37938
44 Jeffet, J., Michaeli-Hoch, Y., Torchinsky, D., Israel-Elgali, I., Shomron, N and Craggs, T.D. (2020) Multi-Modal Single-Molecule Imaging with
Continuously Controlled Spectral-resolution (CoCoS) Microscopy. bioRxiv, https://doi.org/10.1101/2020.10.13.330910
45 Jeffet, J., Kobo, A., Su, T., Grunwald, A., Green, O., Nilsson, A.N. et al. (2016) Super-resolution genome mapping in silicon nanochannels. ACS Nano
10, 9823–9830, https://doi.org/10.1021/acsnano.6b05398
46 Wang, Y., Reinhart, W.F., Tree, D.R. and Dorfman, K.D. (2012) Resolution limit for DNA barcodes in the Odijk regime. Biomicrofluidics 6, 014101,
https://doi.org/10.1063/1.3672691
47 Reinhart, W.F., Reifenberger, J.G., Gupta, D., Muralidhar, A., Sheats, J., Cao, H. et al. (2015) Distribution of distances between DNA barcode labels in
nanochannels close to the persistence length. J. Chem. Phys. 142, 064902, https://doi.org/10.1063/1.4907552
48 Sheats, J., Reifenberger, J.G., Cao, H. and Dorfman, K.D. (2015) Measurements of DNA barcode label separations in nanochannels from time-series
data. Biomicrofluidics 9, 064119, https://doi.org/10.1063/1.4938732
49 Odijk, T. (1983) The statistics and dynamics of confined or entangled stiff polymers. Macromolecules 16, 1340–1344,
https://doi.org/10.1021/ma00242a015
50 Su, T., Das, S.K., Xiao, M. and Purohit, P.K. (2011) Transition between two regimes describing internal fluctuation of DNA in a nanochannel. Kreplak L,
editor. PLoS ONE 6, e16890, https://doi.org/10.1371/journal.pone.0016890
51 Ödman, D., Werner, E., Dorfman, K.D., Doering, C.R. and Mehlig, B. (2018) Distribution of label spacings for genome mapping in nanochannels.
Biomicrofluidics 12, 034115, https://doi.org/10.1063/1.5038417
52 Jain, A., Sheats, J., Reifenberger, J.G., Cao, H. and Dorfman, K.D. (2016) Modeling the relaxation of internal DNA segments during genome mapping in
nanochannels. Biomicrofluidics 10, 054117, https://doi.org/10.1063/1.4964927
53 Dorfman, K.D. (2017) The statistical segment length of DNA: opportunities for biomechanical modeling in polymer physics and next-generation
genomics. J. Biomech. Eng. 140, 020801, https://doi.org/10.1115/1.4037790
54 Odijk, T. (2008) Scaling theory of DNA confined in nanochannels and nanoslits. Phys. Rev. E. 77, 1–4, https://doi.org/10.1103/PhysRevE.77.060901
55 Nyberg, L., Persson, F., Akerman, B. and Westerlund, F. (2013) Heterogeneous staining: a tool for studies of how fluorescent dyes affect the physical
properties of DNA. Nucleic Acids Res. 41, e184–e184, https://doi.org/10.1093/nar/gkt755
56 Reisner, W., Morton, K.J., Riehn, R., Wang, Y.M., Yu, Z., Rosen, M. et al. (2005) Statics and dynamics of single DNA molecules confined in
nanochannels. Phys. Rev. Lett. 94, 196101, https://doi.org/10.1103/PhysRevLett.94.196101
57 Gupta, D., Miller, J.J., Muralidhar, A., Mahshid, S., Reisner, W. and Dorfman, K.D. (2015) Experimental evidence of weak excluded volume effects for
nanochannel confined DNA. ACS Macro Lett. 4, 759–763, https://doi.org/10.1021/acsmacrolett.5b00340
58 Persson, F., Utko, P., Reisner, W., Larsen, N.B. and Kristensen, A. (2009) Confinement spectroscopy: probing single DNA molecules with tapered
nanochannels. Nano Lett. 9, 1382–1385, https://doi.org/10.1021/nl803030e
59 Dai, L., Renner, C.B. and Doyle, P.S. (2016) The polymer physics of single DNA confined in nanochannels. Adv. Colloid Interface Sci. 232, 80–100,
https://doi.org/10.1016/j.cis.2015.12.002
60 Chen, J.Z.Y. (2018) Self-avoiding wormlike chain confined in a cylindrical tube: scaling behavior. Phys. Rev. Lett. 121, 037801,
https://doi.org/10.1103/PhysRevLett.121.037801
61 Bhandari, A.B. and Dorfman, K.D. (2019) Simulations corroborate telegraph model predictions for the extension distributions of nanochannel confined
DNA. Biomicrofluidics 13, 044110, https://doi.org/10.1063/1.5109566
62 Bhandari, A.B. and Dorfman, K.D. (2020) Limitations of the equivalent neutral polymer assumption for theories describing nanochannel-confined DNA.
Phys. Rev. E. 101, 012501, https://doi.org/10.1103/PhysRevE.101.012501
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons
Attribution License 4.0 (CC BY-NC-ND).
Downloaded from http://portlandpress.com/essaysbiochem/article-pdf/doi/10.1042/EBC20200021/906021/ebc-2020-0021c.pdf by guest on 28 March 2021
63 Karpusenko, A., Carpenter, J.H., Zhou, C., Lim, S.F., Pan, J. and Riehn, R. (2012) Fluctuation modes of nanoconfined DNA. J. Appl. Phys. 111,
24701–247018, https://doi.org/10.1063/1.3675207
64 Cao, H., Hastie, A.R., Cao, D., Lam, E.T., Sun, Y., Huang, H. et al. (2014) Rapid detection of structural variation in a human genome using
nanochannel-based genome mapping technology. Gigascience 3, 34, https://doi.org/10.1186/2047-217X-3-34
65 Rust, M.J., Bates, M. and Zhuang, X. (2006) Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3,
793–796, https://doi.org/10.1038/nmeth929
66 Hell, S.W. and Wichmann, J. (1994) Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence
microscopy. Opt. Lett. 19, 780–782, https://doi.org/10.1364/OL.19.000780
67 Betzig, E., Patterson, G.H., Sougrat, R., Lindwasser, O.W., Olenych, S., Bonifacino, J.S. et al. (2006) Imaging intracellular fluorescent proteins at
nanometer resolution. Science 313, 1642–1645, https://doi.org/10.1126/science.1127344
68 Gordon, M.P., Ha, T. and Selvin, P.R. (2004) Single-molecule high-resolution imaging with photobleaching. Proc. Natl. Acad. Sci. U.S.A. 101,
6462–6465, https://doi.org/10.1073/pnas.0401638101
69 Moerner, W.E.W.E. (2015) Single-molecule spectroscopy, imaging, and photocontrol: foundations for super-resolution microscopy (Nobel Lecture).
Angew. Chem. Int. Ed. Engl. 54, 8067–8093, https://doi.org/10.1002/anie.201501949
70 Schermelleh, L., Ferrand, A., Huser, T., Eggeling, C., Sauer, M., Biehlmaier, O. et al. (2019) Super-resolution microscopy demystified. Nat. Cell Biol. 21,
72–84, https://doi.org/10.1038/s41556-018-0251-8
71 Möckl, L. and Moerner, W.E. (2020) Super-resolution microscopy with single molecules in biology and beyond-essentials, current trends, and future
challenges. J. Am. Chem. Soc. 142, 17828–17844, https://doi.org/10.1021/jacs.0c08178
72 Neely, R.K., Dedecker, P., Hotta, J.-I., Urbanavičiūtė, G., Klimašauskas, S. and Hofkens, J. (2010) DNA fluorocode: a single molecule, optical map of
DNA with nanometre resolution. Chem. Sci. 1, 453–460, https://doi.org/10.1039/c0sc00277a
73 Baday, M., Cravens, A., Hastie, A., Kim, H., Kudeki, D.E., Kwok, P.-Y. et al. (2012) Multicolor super-resolution DNA imaging for genetic analysis. Nano
Lett. 12, 3861–3866, https://doi.org/10.1021/nl302069q
74 Chaisson, M.J.P., Sanders, A.D., Zhao, X., Malhotra, A., Porubsky, D., Rausch, T. et al. (2019) Multi-platform discovery of haplotype-resolved structural
variation in human genomes. Nat. Commun. 10, 1784, https://doi.org/10.1038/s41467-018-08148-z
75 Soifer, L., Fong, N.L., Yi, N., Ireland, A.T., Lam, I., Sooknah, M. et al. (2020) Fully Phased Sequence of a Diploid Human Genome Determined de Novo
from the DNA of a Single Individual. G3: Genes|Genomes|Genetics 10, 2911–2925, https://doi.org/10.1534/g3.119.400995
76 Young, E., Abid, H.Z., Kwok, P.Y., Riethman, H. and Xiao, M. (2020) Comprehensive analysis of human subtelomeres by whole genome mapping. PLos
Genet. 16, 1–21, https://doi.org/10.1371/journal.pgen.1008347
77 Wong, K.H.Y., Ma, W., Wei, C.-Y., Yeh, E.-C., Lin, W.-J., Wang, E.H.F. et al. (2020) Towards a reference genome that captures global genetic diversity.
Nat. Commun. 11, 5482, https://doi.org/10.1038/s41467-020-19311-w
78 Levy-Sakin, M., Pastor, S., Mostovoy, Y., Li, L., Leung, A.K.Y., McCaffrey, J. et al. (2019) Genome maps across 26 human populations reveal
population-specific patterns of structural variation. Nat. Commun. 10, 1025, https://doi.org/10.1038/s41467-019-08992-7
79 Young, E., Pastor, S., Rajagopalan, R., McCaffrey, J., Sibert, J., Mak, A.C.Y. et al. (2017) High-throughput single-molecule mapping links subtelomeric
variants and long-range haplotypes with specific telomeres. Nucleic Acids Res. 45, e73, https://doi.org/10.1093/nar/gkx017
80 Li, Y., Roberts, N.D., Wala, J.A., Shapira, O., Schumacher, S.E., Kumar, K. et al. (2020) Patterns of somatic structural variation in human cancer
genomes. Nature 578, 112–121, https://doi.org/10.1038/s41586-019-1913-9
81 Stankiewicz, P. and Lupski, J.R. (2010) Structural variation in the human genome and its role in disease. Annu. Rev. Med. 61, 437–455,
https://doi.org/10.1146/annurev-med-100708-204735
82 Chan, E.K.F., Cameron, D.L., Petersen, D.C., Lyons, R.J., Baldi, B.F., Papenfuss, A.T. et al. (2018) Optical mapping reveals a higher level of genomic
architecture of chained fusions in cancer. Genome Res. 28, 726–738, https://doi.org/10.1101/gr.227975.117
83 Hadi, K., Yao, X., Behr, J.M., Deshpande, A., Xanthopoulakis, C., Tian, H. et al. (2020) Distinct classes of complex structural variation uncovered across
thousands of cancer genome graphs. Cell 183, 197.e32–210.e32, https://doi.org/10.1016/j.cell.2020.08.006
84 Shieh, J.T., Penon-Portmann, M., Wong, K.H.Y., Levy-Sakin, M., Verghese, M., Slavotinek, A. et al. (2020) Application of full genome analysis to
diagnose rare monogenic disorders. medRxiv, https://doi.org/10.1101/2020.10.22.20216531
85 Zhang, Q., Xu, X., Ding, L., Li, H., Xu, C., Gong, Y. et al. (2019) Clinical application of single-molecule optical mapping to a multigeneration FSHD1
pedigree. Mol. Genetics & Genomic Med. 7, e565, https://doi.org/10.1002/mgg3.565
86 Gaillard, M.-C., Roche, S., Dion, C., Tasmadjian, A., Bouget, G., Salort-Campana, E. et al. (2014) Differential DNA methylation of the D4Z4 repeat in
patients with FSHD and asymptomatic carriers. Neurology 83, 733–742, https://doi.org/10.1212/WNL.0000000000000708
87 Huichalaf, C., Micheloni, S., Ferri, G., Caccia, R. and Gabellini, D. (2014) DNA methylation analysis of the macrosatellite repeat associated with FSHD
muscular dystrophy at single nucleotide level. PLoS ONE 9, e115278, https://doi.org/10.1371/journal.pone.0115278
88 Sharim, H., Grunwald, A., Gabrieli, T., Michaeli, Y., Margalit, S., Torchinsky, D. et al. (2019) Long-read single-molecule maps of the functional
methylome. Genome Res. 29, 646–656, https://doi.org/10.1101/gr.240739.118
89 Allis, C.D. and Jenuwein, T. (2016) The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 17, 487–500,
https://doi.org/10.1038/nrg.2016.59
90 Dor, Y. and Cedar, H. (2018) Principles of DNA methylation and their implications for biology and medicine. Lancet 392, 777–786,
https://doi.org/10.1016/S0140-6736(18)31268-6
91 Shi, D.-Q., Ali, I., Tang, J. and Yang, W.-C. (2017) New insights into 5hmC DNA modification: generation, distribution and function. Front Genet 8, 100,
https://doi.org/10.3389/fgene.2017.00100
92 Heck, C., Michaeli, Y., Bald, I. and Ebenstein, Y. (2019) Analytical epigenetics: single-molecule optical detection of DNA and histone modifications.
Curr. Opin. Biotechnol. 55, 151–158, https://doi.org/10.1016/j.copbio.2018.09.006
15
Essays in Biochemistry (2021) EBC20200021
https://doi.org/10.1042/EBC20200021
16
© 2021 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons
Attribution License 4.0 (CC BY-NC-ND).
Downloaded from http://portlandpress.com/essaysbiochem/article-pdf/doi/10.1042/EBC20200021/906021/ebc-2020-0021c.pdf by guest on 28 March 2021
93 Chen, Z., Li, S., Subramaniam, S., Shyy, J.Y.-J. and Chien, S. (2017) Epigenetic regulation: a new frontier for biomedical engineers. Annu. Rev.
Biomed. Eng. 19, 195–219, https://doi.org/10.1146/annurev-bioeng-071516-044720
94 Klein, D.C. and Hainer, S.J. (2020) Genomic methods in profiling DNA accessibility and factor localization. Chromosome Res. 28, 69–85,
https://doi.org/10.1007/s10577-019-09619-9
95 Holoch, D. and Moazed, D. (2015) RNA-mediated epigenetic regulation of gene expression. Nat. Rev. Genet. 16, 71–84,
https://doi.org/10.1038/nrg3863
96 Cavalli, G. and Heard, E. (2019) Advances in epigenetics link genetics to the environment and disease. Nature 571, 489–499,
https://doi.org/10.1038/s41586-019-1411-0
97 Gilboa, T., Torfstein, C., Juhasz, M., Grunwald, A., Ebenstein, Y., Weinhold, E. et al. (2016) Single-molecule DNA methylation quantification using
electro-optical sensing in solid-state nanopores. ACS Nano 10, 8861–8870, https://doi.org/10.1021/acsnano.6b04748
98 Margalit, S., Abramson, Y., Sharim, H., Manber, Z., Bhattacharya, S., Chen, Y.-W. et al. (2021) Long reads capture simultaneous enhancer-promoter
methylation status for cell-type deconvolution. bioRxiv, https://doi.org/10.1101/2021.01.28.428654
99 Gabrieli, T., Michaeli, Y., Avraham, S., Torchinsky, D., Juhasz, M., Coruh, C. et al. (2021) Chemoenzymatic labeling of DNA methylation patterns for
single-molecule epigenetic mapping.. bioRxiv, https://doi.org/10.1101/2021.02.24.432628
100 Lim, S.F., Karpusenko, A., Sakon, J.J., Hook, J.A., Lamar, T.A. and Riehn, R. (2011) DNA methylation profiling in nanochannels. Biomicrofluidics 5,
34106–341068, https://doi.org/10.1063/1.3613671
101 Michaeli, Y., Shahal, T., Torchinsky, D., Grunwald, A., Hoch, R. and Ebenstein, Y. (2013) Optical detection of epigenetic marks: sensitive quantification
and direct imaging of individual hydroxymethylcytosine bases. Chem. Commun. 49, 8599–8601, https://doi.org/10.1039/c3cc42543f
102 Shahal, T., Gilat, N., Michaeli, Y., Redy-Keisar, O., Shabat, D. and Ebenstein, Y. (2014) Spectroscopic quantification of 5-hydroxymethylcytosine in
genomic DNA. Anal. Chem. 86, 8231–8237, https://doi.org/10.1021/ac501609d
103 Gilat, N., Tabachnik, T., Shwartz, A., Shahal, T., Torchinsky, D., Michaeli, Y. et al. (2017) Single-molecule quantification of 5-hydroxymethylcytosine for
diagnosis of blood and colon cancers. Clin. Epigenetics 9, 70, https://doi.org/10.1186/s13148-017-0368-9
104 Nifker, G., Levy-Sakin, M., Berkov-Zrihen, Y., Shahal, T., Gabrieli, T., Fridman, M. et al. (2015) One-Pot Chemoenzymatic Cascade for Labeling of the
Epigenetic Marker 5-Hydroxymethylcytosine. ChemBioChem 16, 1857–1860, https://doi.org/10.1002/cbic.201500329
105 Margalit, S., Avraham, S., Shahal, T., Michaeli, Y., Gilat, N., Magod, P. et al. (2020) 5-Hydroxymethylcytosine as a clinical biomarker:
Fluorescence-based assay for high-throughput epigenetic quantification in human tissues. Int. J. Cancer 146, 115–122,
https://doi.org/10.1002/ijc.32519
106 Gabrieli, T., Sharim, H., Nifker, G., Jeffet, J., Shahal, T., Arielly, R. et al. (2018) Epigenetic Optical Mapping of 5-Hydroxymethylcytosine in Nanochannel
Arrays. ACS Nano 12, 7148–7158, https://doi.org/10.1021/acsnano.8b03023
107 Zirkin, S., Fishman, S., Sharim, H., Michaeli, Y., Don, J. and Ebenstein, Y. (2014) Lighting up individual DNA damage sites by in vitro repair synthesis.
J. Am. Chem. Soc. 136, 7771–7776, https://doi.org/10.1021/ja503677n
108 Gilat, N., Torchinsky, D., Margalit, S., Michaeli, Y., Avraham, S., Sharim, H. et al. (2020) Rapid Quantification of Oxidation and UV Induced DNA Damage
by Repair Assisted Damage Detection-(Rapid RADD). Anal. Chem. 92, 9887–9894, https://doi.org/10.1021/acs.analchem.0c01393
109 Torchinsky, D., Michaeli, Y., Gassman, N.R. and Ebenstein, Y. (2019) Simultaneous detection of multiple DNA damage types by multi-colour fluorescent
labelling. Chem. Commun. 55, 11414–11417, https://doi.org/10.1039/C9CC05198H
110 Wang, W., Klein, K., Proesmans, K., Yang, H., Marchal, C., Zhu, X. et al. (2020) Genome-wide mapping of human DNA replication by optical replication
mapping supports a stochastic model of eukaryotic replication. bioRxiv, https://doi.org/10.1101/2020.08.24.263459
111 Lacroix, J., Pélofy, S., Blatché, C., Pillaire, M.-J., Huet, S., Chapuis, C. et al. (2016) Analysis of DNA Replication by Optical Mapping in Nanochannels.
Small 12, 5963–5970, https://doi.org/10.1002/smll.201503795
112 De Carli, F., Menezes, N., Berrabah, W., Barbe, V., Genovesio, A. and Hyrien, O. (2018) High-throughput optical mapping of replicating DNA . Small
Methods 2, 1800146, https://doi.org/10.1002/smtd.201800146
113 Ratzke, C., Hellenkamp, B. and Hugel, T. (2014) Four-colour FRET reveals directionality in the Hsp90 multicomponent machinery. Nat. Commun. 5,
4192, https://doi.org/10.1038/ncomms5192
114 Zhang, Y., Song, K.-H., Dong, B., Davis, J.L., Shao, G., Sun, C. et al. (2019) Multicolor super-resolution imaging using spectroscopic single-molecule
localization microscopy with optimal spectral dispersion. Appl. Opt. 58, 2248, https://doi.org/10.1364/AO.58.002248
115 Moon, S., Yan, R., Kenny, S.J., Shyu, Y., Xiang, L., Li, W. et al. (2017) Spectrally Resolved, Functional Super-Resolution Microscopy Reveals Nanoscale
Compositional Heterogeneity in Live-Cell Membranes. J. Am. Chem. Soc. 139, 10944–10947, https://doi.org/10.1021/jacs.7b03846
116 Mlodzianoski, M.J., Curthoys, N.M., Gunewardene, M.S., Carter, S. and Hess, S.T. (2016) Super-resolution imaging of molecular emission spectra and
single molecule spectral fluctuations. PLoS ONE 11, 1–12, https://doi.org/10.1371/journal.pone.0147506