ABSTRACT
The
vertebrate
spinal
cord
comprises
multiple
functionally
distinct
neuronal
cell
types
arranged
in
characteristic
positions.
During
development,
these
different
of
neurons
differentiate
from
transcriptionally
neural
progenitors
that
are
arrayed
discrete
domains
along
the
dorsal-ventral
and
anterior-posterior
axes
embryonic
cord.
This
organization
arises
response
to
morphogen
gradients
acting
upstream
a
gene
regulatory
network,
architecture
which
determines
spatial
temporal
pattern
expression.
In
recent
years,
substantial
progress
has
been
made
deciphering
network
underlies
specification
progenitor
identities.
this
Review,
we
outline
how
identities
established
patterning
systems,
novel
experimental
approaches
study
emergence
function
diversity
The
genomics
of
human
development
Understanding
the
trajectory
a
developing
requires
an
understanding
how
genes
are
regulated
and
expressed.
Two
papers
now
present
pooled
approach
using
three
levels
combinatorial
indexing
to
examine
single-cell
gene
expression
chromatin
landscapes
from
15
organs
in
fetal
samples.
Cao
et
al.
focus
on
measurements
RNA
broadly
distributed
cell
types
provide
insights
into
organ
specificity.
Domcke
examined
accessibility
cells
these
identify
regulatory
elements
that
regulate
expression.
Together,
analyses
generate
comprehensive
atlases
early
development.
Science
,
this
issue
p.
eaba7721
eaba7612
Despite
their
crucial
role
in
health
and
disease,
our
knowledge
of
immune
cells
within
human
tissues
remains
limited.
We
surveyed
the
compartment
16
from
12
adult
donors
by
single-cell
RNA
sequencing
VDJ
generating
a
dataset
~360,000
cells.
To
systematically
resolve
cell
heterogeneity
across
tissues,
we
developed
CellTypist,
machine
learning
tool
for
rapid
precise
type
annotation.
Using
this
approach,
combined
with
detailed
curation,
determined
tissue
distribution
finely
phenotyped
types,
revealing
hitherto
unappreciated
tissue-specific
features
clonal
architecture
T
B
Our
multitissue
approach
lays
foundation
identifying
highly
resolved
types
leveraging
common
reference
dataset,
tissue-integrated
expression
analysis,
antigen
receptor
sequencing.
Abstract
Technological
advances
have
enabled
the
profiling
of
multiple
molecular
layers
at
single-cell
resolution,
assaying
cells
from
samples
or
conditions.
Consequently,
there
is
a
growing
need
for
computational
strategies
to
analyze
data
complex
experimental
designs
that
include
modalities
and
groups
samples.
We
present
Multi-Omics
Factor
Analysis
v2
(MOFA+),
statistical
framework
comprehensive
scalable
integration
multi-modal
data.
MOFA+
reconstructs
low-dimensional
representation
using
computationally
efficient
variational
inference
supports
flexible
sparsity
constraints,
allowing
jointly
model
variation
across
sample
modalities.
Identifying
terminal
nematode
cells
Single-cell
RNA
sequencing
provides
the
power
to
identify
developmental
trajectory
of
an
organism.
However,
identifying
temporal
lineage
cell
development
can
be
difficult
without
large-scale
analyses.
Packer
et
al.
sequenced
more
than
80,000
from
embryos
roundworm
Caenorhabditis
elegans
determine
expression
genes
directing
types.
Because
all
somatic
in
a
C.
individual
have
been
mapped,
authors
are
able
connect
gene
with
lineages
over
time
during
development,
noting
stark
transitions
some
cases.
Science
,
this
issue
p.
eaax1971
