The meaning and measure of concordance factors in phylogenomics
Molecular Biology and Evolution,
Год журнала:
2024,
Номер
41(11)
Опубликована: Окт. 17, 2024
Abstract
As
phylogenomic
datasets
have
grown
in
size,
researchers
developed
new
ways
to
measure
biological
variation
and
assess
statistical
support
for
specific
branches.
Larger
more
sites
loci
therefore
less
sampling
variance.
While
we
can
accurately
the
mean
signal
these
datasets,
lower
variance
is
often
reflected
uniformly
high
measures
of
branch
support—such
as
bootstrap
posterior
probability—limiting
their
utility.
also
revealed
substantial
topologies
found
across
individual
loci,
such
that
single
species
tree
inferred
by
most
phylogenetic
methods
represents
a
limited
summary
data
many
purposes.
In
contrast
support,
degree
underlying
topological
among
should
be
approximately
constant
regardless
size
dataset.
“Concordance
factors”
(CFs)
similar
statistics
become
increasingly
important
tools
phylogenetics.
this
review,
explain
why
CFs
thought
descriptors
rather
than
argue
they
provide
information
about
predictive
power
not
contained
support.
We
review
growing
suite
measuring
concordance,
compare
them
common
framework
reveals
interrelationships,
demonstrate
how
calculate
using
an
example
from
birds.
discuss
might
change
future
move
beyond
estimating
“tree
life”
toward
myriad
evolutionary
histories
genomic
variation.
Язык: Английский
Multivariate Trait Evolution: Models for the Evolution of the Quantitative Genetic G-Matrix on Phylogenies.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 29, 2024
Abstract
Genetic
covariance
matrices
(G-matrices)
are
a
key
focus
for
research
and
predictions
from
quantitative
genetic
evolutionary
models
of
multiple
traits.
There
is
consensus
among
geneticists
that
the
G-matrix
can
evolve
through
“deep”
time.
Yet,
evolution
conspicuously
lacking.
In
contrast,
field
macroevolution
has
several
stochastic
univariate
traits
evolving
on
phylogenies.
However,
despite
much
into
multivariate
phylogenetic
comparative
methods,
analytical
how
trait
might
phylogenies
have
not
been
considered.
Here
we
show
three
phylogenies,
based
Lie
group
theory,
Riemannian
geometry
differential
(diffusion)
equations,
be
combined
to
unify
genetics
macroevolutionary
theory
in
coherent
mathematical
framework.
The
provide
basis
understanding
G-matrices
fit
data
via
simulation
using
Approximate
Bayesian
Computation.
Such
used
generate
test
hypotheses
about
variances
covariances,
together
with
themselves,
these
vary
across
phylogeny.
This
unification
an
important
advance
study
phenotypes,
allowing
construction
synthetic
species
over
Lay
Summary
We
unite
Quantitative
Genetics,
major
microevolution,
macroevolution.
To
do
this,
allow
component
matrix
additive
covariances
(the
G-matrix)
along
trees.
because
assumed
constant
genetics,
but
it
recognised
evolves
timescales
(in
“deep
time”).
Uniting
Genetics
allows
more
complete
description
Darwin’s
evolution,
further
testing
hypotheses.
Язык: Английский
Convergent expansions of keystone gene families drive metabolic innovation in a major eukaryotic clade
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 23, 2024
Many
remarkable
innovations
have
repeatedly
occurred
across
vast
evolutionary
distances.
When
convergent
traits
emerge
on
the
tree
of
life,
they
are
sometimes
driven
by
same
underlying
gene
families,
while
other
times
many
different
families
involved.
Conversely,
a
family
may
be
recruited
for
single
trait
or
traits.
To
understand
general
rules
governing
convergence
at
both
genomic
and
phenotypic
levels,
we
systematically
tested
associations
between
56
binary
metabolic
count
in
14,710
from
993
species
Saccharomycotina
yeasts.
Using
recently
developed
phylogenetic
approach
that
reduces
spurious
correlations,
discovered
expansion
contraction
was
significantly
linked
to
gain
loss
45/56
(80%)
While
601/746
(81%)
significant
were
associated
with
only
one
trait,
also
identified
several
'keystone'
up
13/56
(23%)
all
These
results
indicate
yeasts
governed
narrow
set
major
genetic
elements
mechanisms.
Язык: Английский
Error rates in Q_ST--F_ST comparisons depend on genetic architecture and estimation procedures
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 2, 2024
Abstract
Genetic
and
phenotypic
variation
among
populations
is
one
of
the
fundamental
subjects
evolutionary
genetics.
One
question
that
arises
often
in
data
on
natural
whether
differentiation
a
particular
trait
might
be
caused
part
by
selection.
For
past
several
decades,
researchers
have
used
Q
ST
–
F
approaches
to
compare
amount
or
more
traits
(measured
statistic
)
with
genome-wide
genetic
variants
).
Theory
says
under
neutrality,
should
approximately
equal
expectation,
so
values
much
larger
than
are
consistent
local
adaptation
driving
subpopulations’
apart,
smaller
stabilizing
selection
similar
optima.
At
same
time,
investigators
differed
their
definitions
(such
as
“ratio
averages”
vs.
“average
ratios”
versions
variance
components
.
Here,
we
show
these
details
matter.
Different
different
interpretations
terms
coalescence
comparing
incompatible
statistics
can
lead
elevated
type
I
error
rates,
some
choices
leading
rates
near
when
nominal
rate
5%.
We
conduct
simulations
varying
architectures
forms
population
structure
how
they
affect
distribution
When
many
loci
influence
trait,
our
support
procedures
grounded
coalescent-based
framework
for
neutral
phenotytpic
differentiation.
Язык: Английский