Spatial
transcriptomics
(ST)
represents
a
revolutionary
approach
in
molecular
biology,
providing
unprecedented
insights
into
the
spatial
organization
of
gene
expression
within
tissues.
This
review
aims
to
elucidate
advancements
ST
technologies,
their
computational
tools,
and
pivotal
applications
neuroscience.
It
is
begun
with
historical
overview,
tracing
evolution
from
early
image-based
techniques
contemporary
sequence-based
methods.
Subsequently,
methods
essential
for
data
analysis,
including
preprocessing,
cell
type
annotation,
clustering,
detection
spatially
variable
genes,
cell-cell
interaction
3D
multi-slices
integration
are
discussed.
The
central
focus
this
application
neuroscience,
where
it
has
significantly
contributed
understanding
brain's
complexity.
Through
ST,
researchers
advance
brain
atlas
projects,
gain
development,
explore
neuroimmune
dysfunctions,
particularly
tumors.
Additionally,
enhances
neuronal
vulnerability
neurodegenerative
diseases
like
Alzheimer's
neuropsychiatric
disorders
such
as
schizophrenia.
In
conclusion,
while
already
profoundly
impacted
challenges
remain
issues
enhancing
sequencing
technologies
developing
robust
tools.
underscores
transformative
potential
paving
way
new
therapeutic
research.
Journal of genetics and genomics/Journal of Genetics and Genomics,
Год журнала:
2023,
Номер
50(9), С. 625 - 640
Опубликована: Март 27, 2023
The
ability
to
explore
life
kingdoms
is
largely
driven
by
innovations
and
breakthroughs
in
technology,
from
the
invention
of
microscope
350
years
ago
recent
emergence
single-cell
sequencing,
which
scientific
community
has
been
able
visualize
at
an
unprecedented
resolution.
Most
recently,
Spatially
Resolved
Transcriptomics
(SRT)
technologies
have
filled
gap
probing
spatial
or
even
three-dimensional
organization
molecular
foundation
behind
mysteries
life,
including
origin
different
cellular
populations
developed
totipotent
cells
human
diseases.
In
this
review,
we
introduce
progress
challenges
on
SRT
perspectives
bioinformatic
tools,
as
well
representative
applications.
With
currently
fast-moving
promising
results
early
adopted
research
projects,
can
foresee
bright
future
such
new
tools
understanding
most
profound
analytical
level.
Nature Biotechnology,
Год журнала:
2024,
Номер
unknown
Опубликована: Апрель 2, 2024
A
key
challenge
of
analyzing
data
from
high-resolution
spatial
profiling
technologies
is
to
suitably
represent
the
features
cellular
neighborhoods
or
niches.
Here
we
introduce
covariance
environment
(COVET),
a
representation
that
leverages
gene-gene
covariate
structure
across
cells
in
niche
capture
multivariate
nature
interactions
within
it.
We
define
principled
optimal
transport-based
distance
metric
between
COVET
niches
scales
millions
cells.
Using
encode
context,
developed
environmental
variational
inference
(ENVI),
conditional
autoencoder
jointly
embeds
and
single-cell
RNA
sequencing
into
latent
space.
ENVI
includes
two
decoders:
one
impute
gene
expression
modality
second
project
information
onto
data.
can
confer
context
genomics
single
dissociated
outperforms
alternatives
for
imputing
on
diverse
datasets.
Heliyon,
Год журнала:
2023,
Номер
9(5), С. e15306 - e15306
Опубликована: Апрель 18, 2023
Spatially
resolved
techniques
for
exploring
the
molecular
landscape
of
tissue
samples,
such
as
spatial
transcriptomics,
often
result
in
millions
data
points
and
images
too
large
to
view
on
a
regular
desktop
computer,
limiting
possibilities
visual
interactive
exploration.
TissUUmaps
is
free,
open-source
browser-based
tool
GPU-accelerated
visualization
exploration
10
Analytical Chemistry,
Год журнала:
2023,
Номер
95(42), С. 15450 - 15460
Опубликована: Окт. 10, 2023
In
this
Perspective,
we
discuss
the
current
status
and
advances
in
spatial
transcriptomics
technologies,
which
allow
high-resolution
mapping
of
gene
expression
intact
cell
tissue
samples.
Spatial
enables
creation
maps
patterns
within
their
native
context,
adding
an
extra
layer
information
to
bulk
sequencing
data.
has
expanded
significantly
recent
years
is
making
a
notable
impact
on
range
fields,
including
architecture,
developmental
biology,
cancer,
neurodegenerative
infectious
diseases.
The
latest
advancements
have
resulted
development
highly
multiplexed
methods,
transcriptomic-wide
analysis,
single-cell
resolution
utilizing
diverse
technological
approaches.
provide
detailed
analysis
molecular
foundations
behind
main
methods
based
microdissection,
situ
sequencing,
single-molecule
FISH,
capturing,
selection
regions
interest,
or
nuclei
dissociation.
We
contextualize
detection
capturing
efficiency,
strengths,
limitations,
compatibility,
applications
these
techniques
as
well
data
analysis.
addition,
Perspective
discusses
future
directions
potential
transcriptomics,
highlighting
importance
continued
promote
widespread
adoption
research
community.
Journal of Hematology & Oncology,
Год журнала:
2024,
Номер
17(1)
Опубликована: Авг. 24, 2024
The
emergence
of
spatial
multi-omics
has
helped
address
the
limitations
single-cell
sequencing,
which
often
leads
to
loss
context
among
cell
populations.
Integrated
analysis
genome,
transcriptome,
proteome,
metabolome,
and
epigenome
enhanced
our
understanding
biology
molecular
basis
human
diseases.
Moreover,
this
approach
offers
profound
insights
into
interactions
between
intracellular
intercellular
mechanisms
involved
in
development,
physiology,
pathogenesis
In
comprehensive
review,
we
examine
current
advancements
technologies,
focusing
on
their
evolution
refinement
over
past
decade,
including
improvements
throughput
resolution,
modality
integration,
accuracy.
We
also
discuss
pivotal
contributions
revealing
heterogeneity,
constructing
detailed
atlases,
deciphering
crosstalk
tumor
immunology,
advancing
translational
research
cancer
therapy
through
precise
mapping.
Nucleic Acids Research,
Год журнала:
2024,
Номер
53(D1), С. D30 - D44
Опубликована: Ноя. 11, 2024
The
National
Genomics
Data
Center
(NGDC),
which
is
a
part
of
the
China
for
Bioinformation
(CNCB),
offers
comprehensive
suite
database
resources
to
support
global
scientific
community.
Amidst
unprecedented
accumulation
multi-omics
data,
CNCB-NGDC
committed
continually
evolving
and
updating
its
core
through
big
data
archiving,
integrative
analysis
value-added
curation.
Over
past
year,
has
expanded
collaborations
with
international
databases
established
new
subcenters
focusing
on
biodiversity,
traditional
Chinese
medicine
tumor
genetics.
Substantial
efforts
have
been
made
toward
encompassing
broad
spectrum
developing
innovative
enhancing
existing
resources.
Notably,
developed
single-cell
omics
(scTWAS
Atlas),
genome
variation
(VDGE),
health
disease
(CVD
Atlas,
CPMKG,
Immunosenescence
Inventory,
HemAtlas,
Cyclicpepedia,
IDeAS),
biodiversity
biosynthesis
(RefMetaPlant,
MASH-Ocean)
research
tools
(CCLHunter).
All
services
are
publicly
accessible
at
https://ngdc.cncb.ac.cn.
Spatial
transcriptomics
(ST)
is
advancing
our
understanding
of
complex
tissues
and
organisms.
However,
building
a
robust
clustering
algorithm
to
define
spatially
coherent
regions
in
single
tissue
slice
aligning
or
integrating
multiple
slices
originating
from
diverse
sources
for
essential
downstream
analyses
remains
challenging.
Numerous
clustering,
alignment,
integration
methods
have
been
specifically
designed
ST
data
by
leveraging
its
spatial
information.
The
absence
comprehensive
benchmark
studies
complicates
the
selection
future
method
development.
Toxicologic Pathology,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
Recent
advances
in
bioanalytical
and
imaging
technologies
have
revolutionized
our
ability
to
assess
complex
biological
pathological
changes
within
tissue
samples.
Spatial
omics,
a
rapidly
evolving
technology,
enables
the
simultaneous
detection
of
multiple
biomolecules
sections,
allowing
for
high-dimensional
molecular
profiling
microanatomical
contexts.
This
offers
powerful
opportunity
precise,
multidimensional
exploration
disease
pathophysiology.
The
Pathology
2.0
working
group
European
Society
Toxicologic
(ESTP)
includes
subgroup
dedicated
spatial
omics
technologies.
Their
primary
goal
is
raise
awareness
about
these
emerging
their
potential
applications
discovery
toxicologic
pathology.
review
provides
an
overview
commonly
used,
commercially
available
platforms
transcriptomic,
proteomic,
multiomic
analysis,
discussing
technical
aspects
illustrative
examples
applications.
To
harness
power
translational
drug
human
safety
risk
assessment,
we
emphasize
important
role
pathologists
at
every
stage
workflow—from
hypothesis
generation
sample
preparation,
data
interpretation.
offer
novel
opportunities
target
discovery,
lead
selection,
preclinical
clinical
development
compound
development.
