Unraveling the genetic basis of full flowering date in olive tree through QTL mapping approach: Towards climate-adaptive breeding
Abstract
Background
Future
climate
models
project
severe
impacts
on
flowering
phenology
of
perennial
fruit
trees
in
the
Mediterranean
region
under
increasing
global
warming,
including
olive
tree,
a
key
species
extensively
cultivated
region.
Thus,
understanding
genetic
factors
regulating
is
crucial
for
providing
knowledge
to
select
suitable
cultivars
and
designing
future
breeding
programs.
Here,
we
aimed
investigate
control
full
date
(FFD)
through
Quantitative
Trait
Loci
(QTL)
mapping
approach.
Two
high-density
parental
maps,
with
more
than
10k
SNPs,
were
constructed
based
an
“Olivière”
x
“Arbequina”
F1
hybrid
progeny.
Phenological
observations
same
progeny
conducted
across
five
environments
(site
×
season),
data
served
compute
Best
Linear
Unbiased
Predictors
(BLUPs)
FFD.
Both
FFD-based
BLUPs
single-environment
used
detect
QTLs,
which
further
explored
in-silico
candidate
genes
investigation.
Results
Analysis
FFD
distribution
highlighted
high
heritability
transgressive
segregation.
A
total
18
significant
QTLs
identified
analysis,
six
selected
as
most
relevant.
co-detected
linkage
groups
(LGs)
both
maps
some
environments:
LG09
(qFDO9b/
qFDA9 )
LG07
(qFDO7/
qFDA7 ).
Additionally,
four
LG3
(qFDA3 ),
LG22
(qFDA22 )
LG13
(qFDA13)
map,
(qFDO13)
map
revealed
well
analyses.
qFDA13
qFDA22
characterized
by
higher
explained
variance
(14.6%
11.6%,
respectively)
additive
values
(-1.09
+
1.15,
respectively).
Candidate
investigation
within
probably
involved
transcription
regulation,
WRKY71 ,
RLT3 ,
ABSCISIC
ACID-INSENSITIVE-5-LIKE ,
addition
transport
protein:
FT–INTERACTING
protein1 .
Genes
shown
interact
main
regulators
such
FLOWERING
LOCUS
T
(FT)
C
(FLC).
Conclusion
Our
study
highlight
tree.
The
genomic
regions
covered
detected
represent
valuable
resources
investigations
genome-wide
association
functional
genomics
studies.
These
findings
will
provide
information
applying
selection
develop
new
varieties
adapted
projections.
Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown
Published: April 24, 2025
Language: Английский