The
genesis
of
broad
neuronal
classes
from
multipotential
neural
progenitor
cells
has
been
extensively
studied,
but
less
is
known
about
the
diversification
a
single
class
into
multiple
types.
We
used
single-cell
RNA-seq
to
study
how
newly
born
(postmitotic)
mouse
retinal
ganglion
cell
(RGC)
precursors
diversify
~45
discrete
Computational
analysis
provides
evidence
that
RGC
transcriptomic
type
identity
not
specified
at
mitotic
exit,
acquired
by
gradual,
asynchronous
restriction
postmitotic
precursors.
Some
types
are
identifiable
until
week
after
they
generated.
Immature
RGCs
may
be
project
ipsilaterally
or
contralaterally
rest
brain
before
their
emerges.
Optimal
transport
inference
identifies
groups
with
largely
nonoverlapping
fates,
distinguished
selectively
expressed
transcription
factors
could
act
as
fate
determinants.
Our
framework
for
investigating
molecular
within
class.
Nature Communications,
Год журнала:
2018,
Номер
9(1)
Опубликована: Июль 11, 2018
Retinal
ganglion
cells
(RGCs)
convey
the
major
output
of
information
collected
from
eye
to
brain.
Thirty
subtypes
RGCs
have
been
identified
date.
Here,
we
analyze
6225
(average
5000
genes
per
cell)
right
and
left
eyes
by
single-cell
RNA-seq
classify
them
into
40
using
clustering
algorithms.
We
identify
additional
markers,
as
well
transcription
factors
predicted
cooperate
in
specifying
RGC
subtypes.
Zic1,
a
marker
eye-enriched
subtype,
is
validated
immunostaining
situ.
Runx1
Fst,
markers
other
subtypes,
are
purified
fluorescent
situ
hybridization
(FISH)
immunostaining.
show
extent
gene
expression
variability
needed
for
subtype
segregation,
hierarchy
diversification
cell-type
population
Finally,
present
website
comparing
Cell Reports,
Год журнала:
2017,
Номер
18(8), С. 2058 - 2072
Опубликована: Фев. 1, 2017
Highlights•Anatomical
characterization
of
Cre
expression
in
the
retina
88
driver
lines•Morphological
and
histochemical
classification
Cre+
RGC
types
26
lines•High
resolution
whole
brain
imaging
labeled
retinal
axons
reveals
central
targets•Correspondences
described
between
line
projection
patternsSummaryUnderstanding
how
>30
ganglion
cells
(RGCs)
mouse
each
contribute
to
visual
processing
will
require
more
tools
that
label
manipulate
specific
RGCs.
We
screened
analyzed
recombinase
using
transgenic
lines.
In
many
lines,
was
expressed
multiple
cell
classes,
but
several
exhibited
selective
expression.
comprehensively
mapped
projections
from
RGCs
lines
viral
tracers,
high-throughput
imaging,
a
data
pipeline.
identified
over
50
retinorecipient
regions
present
quantitative
retina-to-brain
connectivity
map,
enabling
comparisons
target-specificity
across
Projections
two
major
targets
were
notably
correlated:
projecting
outer
shell
or
core
lateral
geniculate
projected
superficial
deep
layers
within
superior
colliculus,
respectively.
Retinal
images
are
available
online
at
http://connectivity.brain-map.org.Graphical
abstract
PLoS ONE,
Год журнала:
2017,
Номер
12(7), С. e0180091 - e0180091
Опубликована: Июль 28, 2017
The
retina
communicates
with
the
brain
using
≥30
parallel
channels,
each
carried
by
axons
of
distinct
types
retinal
ganglion
cells.
In
every
mammalian
one
finds
so-called
"alpha"
cells
(αRGCs),
identified
their
large
cell
bodies,
stout
axons,
wide
and
mono-stratified
dendritic
fields,
high
levels
neurofilament
protein.
mouse,
three
αRGC
have
been
described
based
on
responses
to
light
steps:
On-sustained,
Off-sustained,
Off-transient.
Here
we
employed
a
transgenic
mouse
line
that
labels
αRGCs
in
live
retina,
allowing
systematic
targeted
recordings.
We
characterize
known
identify
fourth,
On-transient
responses.
All
four
share
basic
aspects
visual
signaling,
including
receptive
field
center,
weak
antagonistic
surround,
absence
any
direction
selectivity.
They
also
distinctive
waveform
action
potential,
faster
than
other
RGC
types.
Morphologically,
they
differ
level
stratification
within
IPL,
which
accounts
for
response
properties.
Molecularly,
type
has
signature.
A
comparison
across
mammals
suggests
common
theme,
large-bodied
split
signal
into
channels
arranged
symmetrically
respect
polarity
kinetics.
Scientific Reports,
Год журнала:
2020,
Номер
10(1)
Опубликована: Июнь 17, 2020
Abstract
Most
irreversible
blindness
results
from
retinal
disease.
To
advance
our
understanding
of
the
etiology
blinding
diseases,
we
used
single-cell
RNA-sequencing
(scRNA-seq)
to
analyze
transcriptomes
~85,000
cells
fovea
and
peripheral
retina
seven
adult
human
donors.
Utilizing
computational
methods,
identified
58
cell
types
within
6
classes:
photoreceptor,
horizontal,
bipolar,
amacrine,
ganglion
non-neuronal
cells.
Nearly
all
are
shared
between
two
regions,
but
there
notable
differences
in
gene
expression
proportions
foveal
cohorts
types.
We
then
atlas
map
636
genes
implicated
as
causes
or
risk
factors
for
diseases.
Many
expressed
striking
class-,
type-,
region-specific
patterns.
Finally,
compared
signatures
cynomolgus
macaque
monkey,
Macaca
fascicularis
.
show
that
over
90%
correspond
transcriptomically
those
previously
macaque,
disease-related
is
largely
conserved
species.
These
validate
use
modeling
disease,
provide
a
foundation
investigating
molecular
mechanisms
underlying
visual
processing.
Cell Reports,
Год журнала:
2022,
Номер
40(2), С. 111040 - 111040
Опубликована: Июль 1, 2022
Classification
and
characterization
of
neuronal
types
are
critical
for
understanding
their
function
dysfunction.
Neuronal
classification
schemes
typically
rely
on
measurements
electrophysiological,
morphological,
molecular
features,
but
aligning
such
datasets
has
been
challenging.
Here,
we
present
a
unified
mouse
retinal
ganglion
cells
(RGCs),
the
sole
output
neurons.
We
use
visually
evoked
responses
to
classify
1,859
RGCs
into
42
types.
also
obtain
morphological
or
transcriptomic
data
from
subsets
these
align
functional
publicly
available
datasets.
create
an
online
database
that
allows
users
browse
download
light
using
machine
learning
algorithm.
This
work
provides
resource
studies
RGCs,
upstream
circuits
in
retina,
projections
brain,
establishes
framework
future
efforts
open
distribution.
