Neuron,
Journal Year:
2023,
Volume and Issue:
111(23), P. 3745 - 3764.e7
Published: Sept. 29, 2023
Leptomeninges,
consisting
of
the
pia
mater
and
arachnoid,
form
a
connective
tissue
investment
barrier
enclosure
brain.
The
exact
nature
leptomeningeal
cells
has
long
been
debated.
In
this
study,
we
identify
five
molecularly
distinct
fibroblast-like
transcriptomes
in
cerebral
leptomeninges;
link
them
to
anatomically
cell
types
pia,
inner
outer
arachnoid
barrier,
dural
border
layer;
contrast
sixth
transcriptome
present
choroid
plexus
median
eminence.
Newly
identified
transcriptional
markers
enabled
molecular
characterization
responsible
for
adherence
layers
one
another
barrier.
These
also
proved
useful
identifying
features
development,
injury,
repair
that
were
preserved
or
changed
after
traumatic
brain
injury.
Together,
findings
highlight
value
fibroblast
subsets
their
cellular
locations
toward
advancing
understanding
physiology
pathology.
Cell,
Journal Year:
2022,
Volume and Issue:
185(10), P. 1777 - 1792.e21
Published: May 1, 2022
Spatially
resolved
transcriptomic
technologies
are
promising
tools
to
study
complex
biological
processes
such
as
mammalian
embryogenesis.
However,
the
imbalance
between
resolution,
gene
capture,
and
field
of
view
current
methodologies
precludes
their
systematic
application
analyze
relatively
large
three-dimensional
mid-
late-gestation
embryos.
Here,
we
combined
DNA
nanoball
(DNB)-patterned
arrays
in
situ
RNA
capture
create
spatial
enhanced
resolution
omics-sequencing
(Stereo-seq).
We
applied
Stereo-seq
generate
mouse
organogenesis
spatiotemporal
atlas
(MOSTA),
which
maps
with
single-cell
high
sensitivity
kinetics
directionality
transcriptional
variation
during
organogenesis.
used
this
information
gain
insight
into
molecular
basis
cell
heterogeneity
fate
specification
developing
tissues
dorsal
midbrain.
Our
panoramic
will
facilitate
in-depth
investigation
longstanding
questions
concerning
normal
abnormal
development.
Genome biology,
Journal Year:
2022,
Volume and Issue:
23(1)
Published: Jan. 18, 2022
Heterogeneity
in
single-cell
RNA-seq
(scRNA-seq)
data
is
driven
by
multiple
sources,
including
biological
variation
cellular
state
as
well
technical
introduced
during
experimental
processing.
Deconvolving
these
effects
a
key
challenge
for
preprocessing
workflows.
Recent
work
has
demonstrated
the
importance
and
utility
of
count
models
scRNA-seq
analysis,
but
there
lack
consensus
on
which
statistical
distributions
parameter
settings
are
appropriate.
Nature,
Journal Year:
2022,
Volume and Issue:
610(7930), P. 143 - 153
Published: Aug. 25, 2022
Abstract
Embryonic
stem
(ES)
cells
can
undergo
many
aspects
of
mammalian
embryogenesis
in
vitro
1–5
,
but
their
developmental
potential
is
substantially
extended
by
interactions
with
extraembryonic
cells,
including
trophoblast
(TS)
endoderm
(XEN)
and
inducible
XEN
(iXEN)
6–11
.
Here
we
assembled
cell-derived
embryos
from
mouse
ES
TS
iXEN
showed
that
they
recapitulate
the
development
whole
natural
embryo
utero
up
to
day
8.5
post-fertilization.
Our
model
displays
headfolds
defined
forebrain
midbrain
regions
develops
a
beating
heart-like
structure,
trunk
comprising
neural
tube
somites,
tail
bud
containing
neuromesodermal
progenitors,
gut
tube,
primordial
germ
cells.
This
complete
within
an
yolk
sac
initiates
blood
island
development.
Notably,
demonstrate
neurulating
Pax6
-knockout
aggregated
wild-type
recapitulates
ventral
domain
expansion
occurs
natural,
ubiquitous
embryos.
Thus,
these
embryoids
are
powerful
for
dissecting
roles
diverse
cell
lineages
genes
results
self-organization
ability
two
types
reconstitute
through
beyond
gastrulation
neurulation
early
organogenesis.
PLoS Computational Biology,
Journal Year:
2023,
Volume and Issue:
19(8), P. e1011288 - e1011288
Published: Aug. 17, 2023
Dimensionality
reduction
is
standard
practice
for
filtering
noise
and
identifying
relevant
features
in
large-scale
data
analyses.
In
biology,
single-cell
genomics
studies
typically
begin
with
to
2
or
3
dimensions
produce
"all-in-one"
visuals
of
the
that
are
amenable
human
eye,
these
subsequently
used
qualitative
quantitative
exploratory
analysis.
However,
there
little
theoretical
support
this
practice,
we
show
extreme
dimension
reduction,
from
hundreds
thousands
2,
inevitably
induces
significant
distortion
high-dimensional
datasets.
We
therefore
examine
practical
implications
low-dimensional
embedding
find
extensive
distortions
inconsistent
practices
make
such
embeddings
counter-productive
exploratory,
biological
lieu
this,
discuss
alternative
approaches
conducting
targeted
feature
exploration
enable
hypothesis-driven
discovery.
