American Journal of Psychiatry,
Год журнала:
2021,
Номер
178(1), С. 30 - 38
Опубликована: Янв. 1, 2021
Recent
progress
in
the
identification
of
genes
and
genomic
regions
contributing
to
autism
spectrum
disorder
(ASD)
has
had
a
broad
impact
on
our
understanding
nature
genetic
risk
for
range
psychiatric
disorders,
ASD
biology,
defining
key
challenges
now
facing
field
efforts
translate
gene
discovery
into
an
actionable
pathology.
While
these
advances
have
not
yet
transformative
clinical
practice,
there
is
nonetheless
cause
real
optimism:
reliable
lists
are
large
growing
rapidly;
identified
encoded
proteins
already
begun
point
relatively
small
number
areas
where
parallel
neuroscience
functional
genomics
yielding
profound
insights;
strong
evidence
pointing
mid-fetal
prefrontal
cortical
development
as
one
nexus
vulnerability
some
largest-effect
genes;
multiple
plausible
paths
forward
toward
rational
therapeutics
that,
while
admittedly
challenging,
constitute
fundamental
departures
from
what
was
possible
prior
era
successful
discovery.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2022,
Номер
unknown
Опубликована: Март 21, 2022
Abstract
The
depletion
of
disruptive
variation
caused
by
purifying
natural
selection
(constraint)
has
been
widely
used
to
investigate
protein-coding
genes
underlying
human
disorders,
but
attempts
assess
constraint
for
non-protein-coding
regions
have
proven
more
difficult.
Here
we
aggregate,
process,
and
release
a
dataset
76,156
genomes
from
the
Genome
Aggregation
Database
(gnomAD),
largest
public
open-access
genome
reference
dataset,
use
this
build
mutational
map
whole
genome.
We
present
refined
model
that
incorporates
local
sequence
context
regional
genomic
features
detect
depletions
across
As
expected,
proteincoding
sequences
overall
are
under
stronger
than
non-coding
regions.
Within
genome,
constrained
enriched
known
regulatory
elements
variants
implicated
in
complex
diseases
traits,
facilitating
triangulation
biological
annotation,
disease
association,
DNA
analysis.
More
tend
regulate
genes,
while
captures
additional
functional
information
underrecognized
gene
metrics.
demonstrate
genome-wide
provides
an
effective
approach
characterizing
improving
identification
interpretation
genetic
variation.
Nature Genetics,
Год журнала:
2022,
Номер
54(9), С. 1305 - 1319
Опубликована: Авг. 18, 2022
Abstract
To
capture
the
full
spectrum
of
genetic
risk
for
autism,
we
performed
a
two-stage
analysis
rare
de
novo
and
inherited
coding
variants
in
42,607
autism
cases,
including
35,130
new
cases
recruited
online
by
SPARK.
We
identified
60
genes
with
exome-wide
significance
(
P
<
2.5
×
10
−6
),
five
NAV3
,
ITSN1
MARK2
SCAF1
HNRNPUL2
).
The
association
is
primarily
driven
loss-of-function
(LoF)
variants,
an
estimated
relative
4,
consistent
moderate
effect.
Autistic
individuals
LoF
four
moderate-risk
;
n
=
95)
have
less
cognitive
impairment
than
129
autistic
highly
penetrant
CHD8,
SCN2A,
ADNP,
FOXP1
SHANK3
)
(59%
vs
88%,
1.9
Power
calculations
suggest
that
much
larger
numbers
are
needed
to
identify
additional
genes.
PLoS Computational Biology,
Год журнала:
2020,
Номер
16(7), С. e1008050 - e1008050
Опубликована: Июль 20, 2020
Machine
learning
algorithms
trained
to
predict
the
regulatory
activity
of
nucleic
acid
sequences
have
revealed
principles
gene
regulation
and
guided
genetic
variation
analysis.
While
human
genome
has
been
extensively
annotated
studied,
model
organisms
less
explored.
Model
organism
genomes
offer
both
additional
training
unique
annotations
describing
tissue
cell
states
unavailable
in
humans.
Here,
we
develop
a
strategy
train
deep
convolutional
neural
networks
simultaneously
on
multiple
apply
it
learn
sequence
predictors
for
large
compendia
mouse
data.
Training
improves
expression
prediction
accuracy
held
out
variant
sequences.
We
further
demonstrate
novel
powerful
approach
models
analyze
variants
associated
with
molecular
phenotypes
disease.
Together
these
techniques
unleash
thousands
non-human
epigenetic
transcriptional
profiles
toward
more
effective
investigation
how
affects
