Genome Biology and Evolution,
Journal Year:
2023,
Volume and Issue:
15(2)
Published: Jan. 23, 2023
Abstract
Population
genetics
is
transitioning
into
a
data-driven
discipline
thanks
to
the
availability
of
large-scale
genomic
data
and
need
study
increasingly
complex
evolutionary
scenarios.
With
likelihood
Bayesian
approaches
becoming
either
intractable
or
computationally
unfeasible,
machine
learning,
in
particular
deep
algorithms
are
emerging
as
popular
techniques
for
population
genetic
inferences.
These
rely
on
that
learn
non-linear
relationships
between
input
model
parameters
being
estimated
through
representation
learning
from
training
sets.
Deep
currently
employed
field
comprise
discriminative
generative
models
with
fully
connected,
convolutional,
recurrent
layers.
Additionally,
wide
range
powerful
simulators
generate
under
scenarios
now
available.
The
application
empirical
sets
mostly
replicates
previous
findings
demography
reconstruction
signals
natural
selection
organisms.
To
showcase
feasibility
tackle
new
challenges,
we
designed
branched
architecture
detect
recent
balancing
temporal
haplotypic
data,
which
exhibited
good
predictive
performance
simulated
data.
Investigations
interpretability
neural
networks,
their
robustness
uncertain
creative
will
provide
further
opportunities
technological
advancements
field.
Annual Review of Genomics and Human Genetics,
Journal Year:
2023,
Volume and Issue:
24(1), P. 109 - 132
Published: April 19, 2023
DNA
sequencing
has
revolutionized
medicine
over
recent
decades.
However,
analysis
of
large
structural
variation
and
repetitive
DNA,
a
hallmark
human
genomes,
been
limited
by
short-read
technology,
with
read
lengths
100-300
bp.
Long-read
(LRS)
permits
routine
fragments
tens
to
hundreds
kilobase
pairs
in
size,
using
both
real-time
synthesis
nanopore-based
direct
electronic
sequencing.
LRS
haplotypic
phasing
genomes
enabled
the
discovery
characterization
rare
pathogenic
variants
repeat
expansions.
It
also
recently
assembly
complete,
gapless
genome
that
includes
previously
intractable
regions,
such
as
highly
centromeres
homologous
acrocentric
short
arms.
With
addition
protocols
for
targeted
enrichment,
epigenetic
modification
detection,
long-range
chromatin
profiling,
promises
launch
new
era
understanding
genetic
diversity
mutations
populations.
Forensic Science International Genetics,
Journal Year:
2023,
Volume and Issue:
65, P. 102870 - 102870
Published: April 7, 2023
Forensic
DNA
Phenotyping
(FDP)
comprises
the
prediction
of
a
person's
externally
visible
characteristics
regarding
appearance,
biogeographic
ancestry
and
age
from
crime
scene
samples,
to
provide
investigative
leads
help
find
unknown
perpetrators
that
cannot
be
identified
with
forensic
STR-profiling.
In
recent
years,
FDP
has
advanced
considerably
in
all
its
three
components,
which
we
summarize
this
review
article.
Appearance
broadened
beyond
eye,
hair
skin
color
additionally
comprise
other
traits
such
as
eyebrow
color,
freckles,
structure,
loss
men,
tall
stature.
Biogeographic
inference
progressed
continental
sub-continental
detection
resolving
co-ancestry
patterns
genetically
admixed
individuals.
Age
estimation
widened
blood
more
somatic
tissues
saliva
bones
well
new
markers
tools
for
semen.
Technological
progress
allowed
forensically
suitable
technology
largely
increased
multiplex
capacity
simultaneous
analysis
hundreds
predictors
targeted
massively
parallel
sequencing
(MPS).
Forensically
validated
MPS-based
predicting
i)
several
appearance
traits,
ii)
multi-regional
ancestry,
iii)
together
iv)
different
tissue
types,
are
already
available.
Despite
advances
will
likely
increase
impact
criminal
casework
near
future,
moving
reliable
level
detail
accuracy
police
investigators
may
desire,
requires
further
intensified
scientific
research
technical
developments
validations
necessary
funding.
Nature,
Journal Year:
2024,
Volume and Issue:
627(8004), P. 604 - 611
Published: March 6, 2024
Abstract
Human
brains
vary
across
people
and
over
time;
such
variation
is
not
yet
understood
in
cellular
terms.
Here
we
describe
a
relationship
between
people’s
cortical
neurons
astrocytes.
We
used
single-nucleus
RNA
sequencing
to
analyse
the
prefrontal
cortex
of
191
human
donors
aged
22–97
years,
including
healthy
individuals
with
schizophrenia.
Latent-factor
analysis
these
data
revealed
that,
whose
more
strongly
expressed
genes
encoding
synaptic
components,
astrocytes
distinct
functions
for
synthesizing
cholesterol,
an
astrocyte-supplied
component
membranes.
call
this
neuron
astrocyte
program
(SNAP).
In
schizophrenia
ageing—two
conditions
that
involve
declines
cognitive
flexibility
plasticity
1,2
—cells
divested
from
SNAP:
astrocytes,
glutamatergic
(excitatory)
GABAergic
(inhibitory)
all
showed
reduced
SNAP
expression
corresponding
degrees.
The
astrocytic
neuronal
components
both
involved
which
genetic
risk
factors
were
concentrated.
SNAP,
varies
quantitatively
even
among
similar
age,
may
underlie
many
aspects
normal
interindividual
differences
be
important
point
convergence
multiple
kinds
pathophysiology.
Genome Biology and Evolution,
Journal Year:
2023,
Volume and Issue:
15(2)
Published: Jan. 23, 2023
Abstract
Population
genetics
is
transitioning
into
a
data-driven
discipline
thanks
to
the
availability
of
large-scale
genomic
data
and
need
study
increasingly
complex
evolutionary
scenarios.
With
likelihood
Bayesian
approaches
becoming
either
intractable
or
computationally
unfeasible,
machine
learning,
in
particular
deep
algorithms
are
emerging
as
popular
techniques
for
population
genetic
inferences.
These
rely
on
that
learn
non-linear
relationships
between
input
model
parameters
being
estimated
through
representation
learning
from
training
sets.
Deep
currently
employed
field
comprise
discriminative
generative
models
with
fully
connected,
convolutional,
recurrent
layers.
Additionally,
wide
range
powerful
simulators
generate
under
scenarios
now
available.
The
application
empirical
sets
mostly
replicates
previous
findings
demography
reconstruction
signals
natural
selection
organisms.
To
showcase
feasibility
tackle
new
challenges,
we
designed
branched
architecture
detect
recent
balancing
temporal
haplotypic
data,
which
exhibited
good
predictive
performance
simulated
data.
Investigations
interpretability
neural
networks,
their
robustness
uncertain
creative
will
provide
further
opportunities
technological
advancements
field.