bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2020,
Номер
unknown
Опубликована: Июнь 26, 2020
SUMMARY
Building
a
genotype-phenotype-fitness
map
of
adaptation
is
central
goal
in
evolutionary
biology.
It
notoriously
difficult
even
when
the
adaptive
mutations
are
known
because
it
hard
to
enumerate
which
phenotypes
make
these
adaptive.
We
address
this
problem
by
first
quantifying
how
fitness
hundreds
yeast
mutants
responds
subtle
environmental
shifts
and
then
modeling
number
they
must
collectively
influence
decomposing
patterns
variation.
find
that
small
predicts
near
their
original
glucose-limited
evolution
condition.
Importantly,
matter
little
at
or
condition
can
strongly
distant
environments.
This
suggests
locally
modular—affecting
environment
where
evolved—yet
globally
pleiotropic—affecting
additional
may
reduce
improve
new
Abstract
As
organisms
evolve,
the
effects
of
mutations
change
as
a
result
epistatic
interactions
with
other
accumulated
along
line
descent.
This
can
lead
to
shifts
in
adaptability
or
robustness
that
ultimately
shape
subsequent
evolution.
Here,
we
review
recent
advances
measuring,
modeling,
and
predicting
epistasis
evolutionary
trajectories,
both
microbial
cells
single
proteins.
We
focus
on
simple
patterns
global
emerge
this
data,
which
be
predicted
by
small
number
variables.
The
emergence
these
offers
promise
for
efforts
model
predict
Building
a
genotype-phenotype-fitness
map
of
adaptation
is
central
goal
in
evolutionary
biology.
It
difficult
even
when
adaptive
mutations
are
known
because
it
hard
to
enumerate
which
phenotypes
make
these
adaptive.
We
address
this
problem
by
first
quantifying
how
the
fitness
hundreds
yeast
mutants
responds
subtle
environmental
shifts.
then
model
number
collectively
influence
decomposing
patterns
variation.
find
that
small
inferred
can
predict
near
their
original
glucose-limited
evolution
condition.
Importantly,
matter
little
at
or
condition
strongly
distant
environments.
This
suggests
locally
modular
-
affecting
environment
where
they
evolved
yet
globally
pleiotropic
additional
may
reduce
improve
new
Sister
chromatid
cohesion
essential
for
mitotic
chromosome
segregation
is
thought
to
involve
the
co-entrapment
of
sister
DNAs
within
cohesin
rings.
Although
can
load
onto
chromosomes
throughout
cell
cycle,
it
only
builds
during
S
phase.
A
key
question
whether
generated
by
conversion
complexes
associated
with
un-replicated
ahead
replication
forks
into
cohesive
structures
behind
them,
or
from
nucleoplasmic
that
loaded
de
novo
nascent
forks,
a
process
would
be
dependent
on
cohesin’s
Scc2
subunit.
We
show
here
in
S.
cerevisiae,
both
mechanisms
exist
and
each
requires
different
set
replisome-associated
proteins.
Cohesion
produced
Tof1/Csm3,
Ctf4
Chl1
but
not
while
created
Scc2-dependent
loading
at
Ctf18-RFC
complex.
The
association
specific
replisome
proteins
types
establishment
opens
way
mechanistic
understanding
an
aspect
DNA
unique
eukaryotic
cells.
Journal of Animal Ecology,
Год журнала:
2023,
Номер
92(6), С. 1113 - 1123
Опубликована: Апрель 23, 2023
Abstract
Dispersal
is
a
central
life
history
trait
that
affects
the
ecological
and
evolutionary
dynamics
of
populations
communities.
The
recent
use
experimental
evolution
for
study
dispersal
promising
avenue
demonstrating
valuable
proofs
concept,
bringing
insight
into
alternative
strategies
trade‐offs,
testing
repeatability
outcomes.
Practical
constraints
restrict
studies
to
set
typically
small,
short‐lived
organisms
reared
in
artificial
laboratory
conditions.
Here,
we
argue
despite
these
restrictions,
inferences
from
can
reinforce
links
between
theoretical
predictions
empirical
observations
advance
our
understanding
eco‐evolutionary
consequences
dispersal.
We
illustrate
how
applying
an
integrative
framework
theory,
natural
systems
improve
under
more
complex
realistic
biological
scenarios,
such
as
role
biotic
interactions
syndromes.
Many
biological
features
are
conserved
and
thus
considered
to
be
resistant
evolutionary
change.
While
rapid
genetic
adaptation
following
the
removal
of
genes
has
been
observed,
we
often
lack
a
mechanistic
understanding
how
happens.
We
used
budding
yeast,
Saccharomyces
cerevisiae,
investigate
plasticity
chromosome
metabolism,
network
modules.
experimentally
evolved
cells
constitutively
experiencing
DNA
replication
stress
caused
by
absence
Ctf4,
protein
that
coordinates
enzymatic
activities
at
forks.
Parallel
populations
adapted
stress,
over
1000
generations,
acquiring
multiple,
concerted
mutations.
These
mutations
altered
two
metabolism
modules,
sister
chromatid
cohesion,
inactivated
third,
damage
checkpoint.
The
selected
define
functionally
reproducible
trajectory.
suggest
implications
for
genome
evolution
in
natural
cancer.All
plants,
animals
fungi
share
common
ancestor,
though
they
have
become
very
distinct
billions
years,
all
essential
machinery
needed
grow
divide.
At
heart
this
is
complex
interaction
proteins
involved
replication,
process
duplicating
material
every
time
cell
divides.
needs
done
with
great
care,
error
rates
as
small
one
mistake
billion.
Otherwise,
can
accumulate
genome,
causing
problems
long-term
survival.
Despite
overall
principles
remaining
same,
underlying
mechanisms
vary
across
different
organisms.
Given
precision
complexity
replicating
DNA,
it
was
not
clear
had
differences.
Fumasoni
Murray
set
out
answer
forcing
strain
yeast
evolve
removing
gene
an
important,
but
essential,
component
replication.
were
still
able
reproduce,
hampered
mutation.
studied
after
reproduced
thousand
giving
enough
acquire
new
would
allow
compensate
initial
defects.
In
eight
separate
samples,
made
many
same
changes
order
overcome
original
segregation
third
feature
normally
protect
against
accumulation
damaged
DNA.
findings
show
pathways
controlled,
laboratory
environment
quickly
processes
damaged.
behavior
mutated
mimicked
cancer
cells,
which
struggling
adapt
their
machinery.
Studying
follows
perturbations
could
help
researchers
better
deal
challenges
treatment
development
antibiotic
resistance
bacteria,
well
leading
deeper
both
biology.
Proceedings of the National Academy of Sciences,
Год журнала:
2020,
Номер
117(31), С. 18582 - 18590
Опубликована: Июль 17, 2020
Significance
Cellular
modules,
such
as
the
translation
machinery
(TM),
are
key
units
of
adaptive
evolution
because
fitness
depends
on
their
performance.
In
rapidly
evolving
populations,
natural
selection
may
not
be
able
to
improve
all
modules
simultaneously
mutations
in
different
compete
against
each
other.
We
hypothesize
that
adaptation
some
would
stall,
despite
availability
beneficial
mutations.
empirically
demonstrate
evolutionary
stalling
TM
module
experimental
populations
Escherichia
coli
.
Natural
initially
improved
TM,
but
its
focus
shifted
away
other
cellular
before
TM’s
performance
was
fully
restored.
This
work
shows
rapid
shifts
can
slow
down
improvement
individual
components
nature.
As
an
adapting
population
traverses
the
fitness
landscape,
its
local
neighborhood
(i.e.,
collection
of
effects
single-step
mutations)
can
change
shape
because
interactions
with
mutations
acquired
during
evolution.
These
changes
to
distribution
affect
both
rate
adaptation
and
accumulation
deleterious
mutations.
However,
while
numerous
models
landscapes
have
been
proposed
in
literature,
empirical
data
on
how
this
evolution
remains
limited.
In
study,
we
directly
measure
landscape
laboratory
adaptation.
Using
a
barcode-based
mutagenesis
system,
91
specific
gene
disruption
genetic
backgrounds
spanning
8000-10,000
generations
two
constant
environments.
We
find
that
mean
decreases
one
environment,
indicating
reduction
mutational
robustness,
but
does
not
other.
show
these
distribution-level
patterns
result
from
differences
relative
frequency
certain
epistasis
at
level
individual
mutations,
including
fitness-correlated
idiosyncratic
epistasis.
Nature Cell Biology,
Год журнала:
2023,
Номер
25(4), С. 616 - 625
Опубликована: Апрель 1, 2023
Abstract
Metabolism
is
intertwined
with
various
cellular
processes,
including
controlling
cell
fate,
influencing
tumorigenesis,
participating
in
stress
responses
and
more.
a
complex,
interdependent
network,
local
perturbations
can
have
indirect
effects
that
are
pervasive
across
the
metabolic
network.
Current
analytical
technical
limitations
long
created
bottleneck
data
interpretation.
To
address
these
shortcomings,
we
developed
Metaboverse,
user-friendly
tool
to
facilitate
exploration
hypothesis
generation.
Here
introduce
algorithms
leverage
network
extract
complex
reaction
patterns
from
data.
minimize
impact
of
missing
measurements
within
methods
enable
pattern
recognition
multiple
reactions.
Using
identify
previously
undescribed
metabolite
signature
correlated
survival
outcomes
early
stage
lung
adenocarcinoma
patients.
yeast
model,
suggesting
an
adaptive
role
citrate
homeostasis
during
mitochondrial
dysfunction
facilitated
by
transporter,
Ctp1.
We
demonstrate
Metaboverse
augments
user’s
ability
meaningful
multi-omics
datasets
develop
actionable
hypotheses.