Species
identification
using
DNA
barcodes
has
revolutionized
biodiversity
sciences
and
society
at
large.
However,
conventional
barcoding
methods
do
not
reflect
genomic
complexity,
may
lack
sufficient
variation,
rely
on
limited
loci
that
are
universal
across
the
Tree
of
Life.
Here,
we
develop
a
novel
method
uses
exceptionally
low-coverage
genome
skim
data
to
create
“varKode”,
two-dimensional
image
representing
landscape
species.
Using
these
varKodes,
then
train
neural
networks
for
precise
taxonomic
identification.
Applying
an
expertly
annotated
dataset
including
hundreds
newly
sequenced
samples
from
plant
clade
Malpighiales,
demonstrate
>91%
precision
when
identifying
species
or
genera.
Remarkably,
high
accuracy
remains
despite
minimal
amounts
lead
failure
applying
alternative
methods.
We
further
illustrate
broad
utility
varKodes
several
focal
clades
eukaryotes
prokaryotes.
As
final
test,
classify
entire
NCBI
eukaryote
sequence-read
archive
identify
its
861
constituent
families
with
>95%
utilizing
less
than
10
Mbp
per
sample.
Enhanced
computational
efficiency
scalability,
inputs
robust
degraded
DNA,
modularity
development
make
varKoding
ideal
approach
science.
Comprehensive Reviews in Food Science and Food Safety,
Год журнала:
2021,
Номер
20(5), С. 5197 - 5225
Опубликована: Авг. 1, 2021
Abstract
Berries
represent
one
of
the
most
important
and
high‐valued
group
modern‐day
health‐beneficial
“superfoods”
whose
dietary
consumption
has
been
recognized
to
be
beneficial
for
human
health
a
long
time.
In
addition
being
delicious,
berries
are
rich
in
nutrients,
vitamins,
several
bioactive
compounds,
including
carotenoids,
flavonoids,
phenolic
acids,
hydrolysable
tannins.
However,
due
their
high
value,
berry‐based
products
often
subject
fraudulent
adulteration,
commonly
economical
gain,
but
also
unintentionally
misidentification
species.
Deliberate
adulteration
comprises
substitution
high‐value
with
lower
value
counterparts
mislabeling
product
contents.
As
is
deceptive
toward
customers
presents
risk
public
health,
food
authentication
through
different
methods
applied
as
countermeasure.
Although
many
have
developed
terms
fast,
sensitive,
reliable,
low‐cost
analysis
myriad
species,
application
on
still
limited.
The
present
review
provides
an
overview
development
analytical
chemistry
methods,
such
isotope
ratio
analysis,
liquid
gas
chromatography,
spectroscopy,
well
DNA‐based
electronic
sensors,
products.
We
provide
earlier
use
recent
advances
these
discuss
drawbacks
related
application.
Diversity,
Год журнала:
2022,
Номер
14(4), С. 262 - 262
Опубликована: Март 30, 2022
The
need
for
herbal
medicinal
plants
is
steadily
increasing.
Hence,
the
accurate
identification
of
plant
material
has
become
vital
safe
usage,
avoiding
adulteration,
and
trading.
DNA
barcoding
shown
to
be
a
valuable
molecular
tool
plants,
ensuring
safety
efficacy
materials
therapeutic
significance.
Using
morphological
characters
in
genera
with
closely
related
species,
species
delimitation
often
difficult.
Here,
we
evaluated
capability
nuclear
barcode
ITS2
plastid
barcodes
rbcL
matK
identify
20
medicinally
important
Caryophyllales.
In
our
analysis,
applied
an
integrative
approach
discrimination
using
pairwise
distance-based
unsupervised
operational
taxonomic
unit
“OTU
picking”
methods,
viz.,
ABGD
(Automated
Barcode
Gap
Analysis)
ASAP
(Assemble
Species
by
Automatic
Partitioning).
Along
OTU
picking
Supervised
Machine
Learning
methods
(SML)
were
also
implemented
recognize
divergent
taxa.
Our
results
indicated
that
was
more
successful
distinguishing
between
examined
implying
it
could
used
detect
contamination
adulteration
these
plants.
Moreover,
this
study
suggests
combination
than
one
method
assist
resolution
morphologically
similar
or
Abstract
Background
Sorbus
sensu
stricto
(
s.s.
)
is
a
genus
with
important
economical
values
because
of
its
beautiful
leaves,
and
flowers
especially
the
colorful
fruits.
It
belongs
to
tribe
Maleae
family
Rosaceae,
comprises
about
90
species
mainly
distributed
in
China.
There
on-going
dispute
infrageneric
classification
delimitation
as
are
morphologically
similar.
With
aim
shedding
light
on
circumscription
taxa
within
genus,
phylogenetic
analyses
were
performed
using
29
chloroplast
(cp)
genomes
(16
newly
sequenced)
representing
two
subgenera
eight
sections.
Results
The
16
cp
sequenced
range
between
159,646
bp
160,178
length.
All
samples
examined
22
re-annotated
lato
s.l.
contain
113
unique
genes
19
these
duplicated
inverted
repeat
(IR).
Six
hypervariable
regions
including
trnR
-
atpA
,
petN
psbM
rpl32-trnL
trnH
psbA
trnT
trnL
ndhC-trnV
screened
44–53
SSRs
14–31
dispersed
repeats
identified
potential
molecular
markers.
Phylogenetic
under
ML/BI
indicated
that
polyphyletic,
but
other
five
segregate
genera,
Aria
Chamaemespilus
Cormus
Micromeles
Torminalis
monophyletic.
Two
major
clades
four
sub-clades
resolved
full-support
s.s
.
not
consistent
existing
classification.
subgenera,
subg.
Albocarmesinae
supported
monophyletic
when
S.
tianschanica
transferred
from
hupehensis
var.
paucijuga
respectively.
current
at
sectional
level
by
analysis
genome
phylogeny.
Conclusion
Phylogenomic
useful
for
inferring
relationships
Though
structure
highly
conserved
sequences
used
most
promising
molecule
makers
population
genetics,
studies.
Species
identification
using
DNA
barcodes
has
revolutionized
biodiversity
sciences
and
society
at
large.
However,
conventional
barcoding
methods
do
not
reflect
genomic
complexity,
may
lack
sufficient
variation,
rely
on
limited
loci
that
are
universal
across
the
Tree
of
Life.
Here,
we
develop
a
novel
method
uses
exceptionally
low-coverage
genome
skim
data
to
create
“varKode”,
two-dimensional
image
representing
landscape
species.
Using
these
varKodes,
then
train
neural
networks
for
precise
taxonomic
identification.
Applying
an
expertly
annotated
dataset
including
hundreds
newly
sequenced
samples
from
plant
clade
Malpighiales,
demonstrate
>91%
precision
when
identifying
species
or
genera.
Remarkably,
high
accuracy
remains
despite
minimal
amounts
lead
failure
applying
alternative
methods.
We
further
illustrate
broad
utility
varKodes
several
focal
clades
eukaryotes
prokaryotes.
As
final
test,
classify
entire
NCBI
eukaryote
sequence-read
archive
identify
its
861
constituent
families
with
>95%
utilizing
less
than
10
Mbp
per
sample.
Enhanced
computational
efficiency
scalability,
inputs
robust
degraded
DNA,
modularity
development
make
varKoding
ideal
approach
science.