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ANALYSIS OF QTLS FOR EARLINESS COMPONENTS IN
BREAD WHEAT (TRITICUM AESTIVUM L.)
E. Nalini and N. Jawali
Molecular Biology Division
Bhabha Atomic Research Centre
and
S.G. Bhagwat
Nuclear Agriculture and Biotechnology Division
Bhabha Atomic Research Centre
This paper was awarded the Best Poster Presentation award at
the BARC Golden Jubilee and DAE-BRNS Life Science Symposium 2006 (LSS-2006) on
“Trends in Research and Technologies in Agriculture and Food Sciences”
held at BARC, Mumbai, during December 18-20, 2006
Abstract
Earliness, is an important trait in plant breeding. Its constituent traits flowering time and days to heading are
largely controlled by vernalization genes (Vrn), photoperiod response genes (Ppd) and developmental rate genes
(‘earliness per se’, Eps). Mapping of major genes controlling these quantitative traits, Flowering Time (FT) and
days To Heading (DTH) was carried out in an intervarietal wheat cross. We constructed a genetic linkage map
based on an F2 population (150), derived from a cross between two Indian bread wheat (Triticum aestivum L.)
varieties, Sonalika and Kalyansona. The map consisted of 236 markers and spanned a distance of 3639 cM. Field
data for FT and DTH were collected on the F2 population in Trombay environment. Totally six QTLs for flowering
time and 21 for days to heading were identified with LOD threshold of >2.0 and the phenotypic variation
ranging from 10.8 % to 67.8 %. At five of the QTLs for flowering time, the marker closest was also found to be
closest to the QTLs for days to heading. Five markers that showed association with the traits were identified
by t-test. STMS marker Xgwm325-6D showed association with both the traits. These five markers
could be useful in Marker Assisted Selection (MAS) for these traits in wheat breeding.
Introduction
Many of the economically important traits in crop
plants are quantitative in nature and are controlled by
many genes or gene complexes, that are described as
Quantitative Trait Loci (QTL). Mapping of the QTL has
been greatly facilitated due to the availability of molecular
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markers and the development of improved and powerful
statistical methods. The development of genetic maps
is a prerequisite for mapping the loci that control these
traits by QTL analysis and to identify the loci (QTLs) that
could be useful in plant breeding via marker-assisted
selection.
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The first intervarietal map of bread wheat, based on RFLP
markers, was published in 19971. An updated version of
this Chinese Spring - Courtot intervarietal genetic map
was published in 20032. More recently three intervarietal
maps based on Australian bread wheat varieties3 and
other intervarietal maps have been reported4-7. Flowering
time (FT) in wheat is a complex trait, controlled by three
groups of major genes viz. photoperiod response genes
(Ppd), vernalization response genes (Vrn) and
developmental rate genes (‘earliness per se’, Eps). Days
to Heading (DTH) is a trait correlated with FT and is also
controlled by the vernalization and photoperiod genes.
Several QTLs have been reported for FT and DTH, which
are listed in Table 1. Here, we report the identification
of QTLs for FT and DTH, using a genetic linkage map,
constructed using a cross between two Indian bread
wheat (Triticum aestivum L.) varieties, Sonalika and
Kalyansona.
Materials and Method
Plant Materials: The mapping population consisting
of 150 F2 plants was from a cross between Sonalika and
Kalyansona (bread wheat: Triticum aestivum L.). The
plants were grown in fields of BARC at Trombay,
Mumbai, India. The data on DTH (ear emergence) and
FT on these field grown plants was recorded at the
appropriate growth time.
Chemicals: The chemicals for isolation of DNA and
Agarose were from Sigma-Aldrich USA. PCR reagents
were from Bangalore Genei Pvt. Ltd. Primers were from
Genetix Ltd. The Hoechst dye was procured from
Amersham Pharmacia biotech.
Method
DNA Isolation and Quantification: DNA was isolated
from leaves following a method developed in our
Table 1 : List of QTLs detected in the present study and reported in literature
for the two quantitative traits.
* = The chromosomes in bold are the new QTLs detected in the present study
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laboratory21. DNA was quantitated by measuring
fluorescence emission using Hoechst dye on a
fluorimeter DyNA Quant 200.
PCR amplification: This was carried out in an Eppendorf
Mastercycler-Gradient cycler. AP-PCR, RAPD, ISSR, STMS,
AFLP, gene specific PCR markers viz. ITS, puroindoline
gene and Rht genes, seed proteins and morphological
markers were used for genotyping the mapping
population.
Data analysis: The polymorphic bands were scored as
presence (1) and absence (0) of band among the F2
population. The segregation of individual markers was
analyzed by chi-square test at 1% and 5% level of
significance for a goodness-of-fit to a 3:1 ratio.
Linkage map: The linkage analysis was performed using
Mapmaker ver 3.0b.22
I S S U E
“SK map”. Of the 280 markers, 236 mapped into 37
linkage groups and 44 markers remained unlinked. The
map spanned 3639 cM with 1211.2 cM for A genome,
1669.2 cM for B genome, 192.4 cM for D genome and
566.2 cM for unassigned groups. Twenty-four linkage
groups were assigned to 17 chromosomes using anchor
markers such as STMS, physically mapped AFLP markers
using nullitetrasomic lines and some gene specific loci
such as Rht etc. No linkage group was assigned to the
chromosomes 1D, 2D, 4D and 7D. The number of
markers mapped was highest in B genome (97) followed
by A genome (72) and D genome (17). The average
distance between two markers was 15.4 cM.
Construction of QTL map
The genetic linkage map obtained above was utilized to
construct QTL map for the two quantitative traits.
Composite Interval Mapping is an extension of Simple
QTL map: The genetic map thus
constructed was used to derive QTL map
by Composite Interval Mapping (CIM)
and Multitrait Composite Interval
Mapping (MCIM) for quantitative traits
using QTL Cartographer ver. 2.523.
T-test: Marker association with the trait
of the markers closest to the QTL
identified by CIM was analyzed by
t-test. Software such as Origin ver. 6.1
(Originlab corporation, USA) was used
for performing t-test.
Results and Discussion
Construction of linkage map
Fig. 1 : Different types of PCR-based marker techniques
used for genotyping the mapping population
Segregation of 280 markers (11 AP-PCR,
26 RAPD, 8 ISSR, 14 STMS, 210 AFLP,
5 proteins, 2 morphological and 4 gene specific markers
(Fig.1) among the mapping population was used, to
construct a genetic linkage map hereafter referred to as
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Interval Mapping; it considers both the markers flanking
the QTL and background markers, which may or may
not be linked to the QTL. CIM is said to give
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more power and precision in the detection of QTLs than
SIM. One of the most important advantages of CIM is
that the markers can be used as boundary conditions to
narrow down the most likely QTL position. The resolution
of QTL locations can be greatly increased.
A total of eight QTLs were identified for FT of which one
each was located on chromosomes 3A, 5A, 5B, 6B, 6D,
7B and two on the unassigned linkage group 11. The
phenotypic variation in these QTLs ranged from
13.3 % to 42.0 % and the LOD ranged between
2.0 and 3.2. A total of 21 QTLs for DTH were
identified that were located on chromosomes 2A,
2B, 3A, 3D, 5A, 5B, 6A, 6B, 6D, 7A, 7B and on
unassigned linkage groups 8, 11 and 12. The QTLs
for DTH were with LOD values ranging between
from 2.1 and 6.8 and the phenotypic variation
ranging between 10.8% and 67.8 % (Table 2).
Table 2 : Composite interval map for the quantitative traits DTH and FT
*,** Means for marker allele classes, which differed significantly at P< 0.05 and 0.01 respectively
a
Intervals in cM were obtained by marking positions ± 1 LOD from the peak
b
Values in parentheses are the distances (cM) of the marker from the peak
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Fig. 2 : A representative QTL cartographer plot involving chromosome 6B obtained using
Composite Interval Mapping (CIM) for the trait DTH. The LOD value is given on the Y-axis and
the name of the markers and distance between them in cM on the X-axis. The arrow point at
the QTL at the position 0.0 cM and the marker associated is SS13RA having a LOD score of 6.8.
As an example a representative QTL cartographer plot
involving chromosome 6B obtained using Composite
Interval Mapping (CIM) for the trait DTH is shown in
Fig. 2. The markers closest to the QTLs for FT on
chromosome 3A, 5B, 6B, 6D and 7B were also closest
to the QTLs for DTH viz. 1) E1_M31 on chromosome
3A1, 2) E17_M7B on chromosome 5B, 3) E17_M7A
on chromosome 7B, 4) SS13RA on chromosome 6B and
5) Xgwm325-6D on chromosome 6D.
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Association of a marker with a QTL was analyzed by
two-population t-test. The F2 population was divided
into two groups, based on the alleles of a marker closest
to a QTL. The trait means of the two groups were
subjected to t-test for significance. Significant differences
between the means were obtained for five markers (Table
2). These five markers that are associated with the trait
could be useful in Marker Assisted Selection (MAS) for
these traits in wheat breeding.
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About the Authors
Ms. Nalini Eswaran, a DAEMumbai University collaborative
fellow, is a first rank holder in
M.Sc. degree in Life Sciences
(Specialization in Biomacromolecules,) from Mumbai
University in the year 2001. She
was awarded the DAE-Mumbai
University collaborative fellowship for doing Ph.D.,
in 2001. She is carrying out her research project
entitled “Genetic Linkage Map of Bread Wheat With
an Emphasis on Genes Controlling Plant
Morphology” in the Molecular Biology Division
under the guidance of Dr. Narendra Jawali. The
paper titled “Analysis of QTLs for Earliness
components in bread wheat (Triticum aestivum)”
was awarded best poster presentation, at the BARC
Golden Jubilee and DAE-BRNS Life Science
Symposium 2006 (LS S-2006) on “Trends in
Research and Technologies in Agriculture and Food
Sciences” at BARC, Trombay, Mumbai 18-20 Dec
2006.
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Dr S.G. Bhagwat did his
M.Sc. in Botany from Poona
University, Pune in the year
1975. He joined the 19th Batch
of Training School in the Biology
and Radiobiology discipline. He
did his PhD. on “Grain protein
variation in wheat”. Currently,
he is working in the Nuclear Agriculture and
Biotechnology Division of the Bioscience group,
BARC. His research interests are genetics and genetic
improvement of wheat.
Dr Narendra Jawali obtained
M.Sc., Degree in Biochemistry
from
Central
College,
Bangalore
University
Bangalore in 1975. He joined
the 19 th Batch of Training
School in the Biology and
Radiobiology discipline. He
obtained his Ph.D. in 1988
from Mumbai University. He is working in the
Molecular Biology Division of the Bioscience group,
BARC. His research interests are plant and microbial
molecular genetics.
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