Mapping determined several traits. The physiological components of

QTL for water regime in spring bread wheat 2014

for the first time the authors assessed and map the chromosomes QTLs for the
manifestation of morpho-physiological and agronomic indices of plant water
status and related quantitative traits such as plants height, weight and dry
matter content in spring bread wheat (Triticum aestivum L). Following the study
of ten agronomic traits, 13 QTLs were mapped on linkage group 1A, 2B, 2D, 4A,
5A, 5B, 5D, 6A and 6D. Some of the identified QTLs concurrently determined
several traits. The physiological components of water status were shown to
correlate with quantitative traits I wheat plants such as plant height, weight
and dry matter content, and the correlation coefficients were determined for
all traits under study. Water retention capacity after  3 H correlated with water retention capacity
after 24 H(rxy=0.47). The correlations were also established between water
retention capacity after 3H and plant height at booting stage (rxy=0.29). and
between water retention capacity after 3H and plant dry weight (rxy=0.33). Statistical
calculations supported generally observed negative correlation (up to -1)
between leaf water and dry matter contents, as well as between the roots
indices of variance in the mapping population of the wheat lines. The results
obtained in the present study with promote future effects in the fine map. The
genes residing with in the identified QTLs, to eventually clone these genes in
order to established the physiological mechanism for maintaining water homeostasis
in higher plants cell to accomplish the practical implementations of marker-
assisted assessment of water status in wheat plants study on the basis of
morpho-physiological and economical

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Water is essential for
vital activities of plants and prokaryotes, because in the cell it is the basic
medium containing metabolic processes and major components, initial,
intermediate or final of numerous physiological and biochemical reactions
1,2. The special role of the water in the life of higher plants is the
necessity to continually replenish moisture losses due to water evaporation
when plants are affected by various ecological and geographical stress factors.
Physiological adaptation to such environmental factors include superior
capacity of water retention by cells and tissue due to high cytoplasm viscosity
and elasticity, higher proportion of tightly bound water in the total moisture
content and the maintenance of water homeostasis in living organisms 1,3.

Most physiological
characteristics important for practical breeding are quantitative and mostly
depend on allelic patterns of several genetic loci. The currently accumulated
evidence holds that the gene ensembles effecting the means and genetic variance
of a quantitative trait are usually determined by the limiting environment
facts 4. The change in the limiting factors entail a shift of the spectrum of
genetic loci that establish trait evidence 5,6. Nevertheless, in addition to
the above concept, there exist certain k genes7 that under all conditions
contribute to the formation of the particular quantitative traits, even
although the effect of this contribution depends on the environment. Such
genetic loci dubbed quantitative traits loci (QTLs) are the major interest for
the current molecular approach to the breeding for polygenic traits including
Marker Assisted Selection (MAS) 7. QTL analysis in different plants species
as already revealed properties facets of realization of genetic programs under
water stress. Corn yield is known to decline when water stress takes place
during flowering stage. One of the main object of corn growers is to enhance
and crop production under limited water supply and most drought conditions.
However, one should keep in mind that the physiological traits of drought
resistance is usually polygenic and partially correlates with other
characteristics. To resolve this complex problem, the methodology of QTL
identification was worked out in the mid1990s with the ultimate goal of developing
the MAS strategies for specific characters as in corn and wheat. This approach
act as basis of further research of physiological and genetic constituent of
plant water status.

Most of the studies on
the drought effects in plants are usually carried out by using the vegetative
organs like leaves. The loss of water activates two types of response. These
response are

Rapid arrest of
cell growth in young growing organs.

Decline in
photosynthesis and sucrose metabolism in the leaves.

Abscisic acid ABA produces
in the root apices and circulating in the xylem is an important trigger of such
responses to stress condition. When face with numerous co-dependent
interaction, it is very difficult to attribute the observed response of growing
plants to several putatively key factors. Clarification of this tissue is
mostly important in the case of crop plants, because the identification of key
genes would be open the possibility to work for sustained plant adaptation and
increase the plant resistance during the plant stress factors. The use of QTL
methodology seems the most assessable approach because it allows various
characters. Moreover, co-localization of QTLS provides new information about
trait linkage at different levels of integration from enzyme activities to gas
exchange or for leaves growth.

The first attempt to identify
QTLs that determine the quantitative ABA level as related to the severity of
the water stress applied DNA markers and segregating F2 population of wheat and
corn (8). Despite the low marker density (32) in corn. The author managed to
demonstrate the principle possibility of using this method. A more thorough
analysis was carried out using 81 F2 corn populations and 84 markers. In
addition to water stress, ABA effects were related to the other plant indices,
such as stomatal conductance, water potential, turgor potential, number of
roots and root tension, chlorophyll florescence, and several other

Recently QTLs for ABA
response were mapped in wheat seedlings. The author employed the F2 mapping
population developed by cross var. Chinese Spring to CS line with 5A chromosome
substituted with that from var. Hope (Hope 5A). This experiment was identified
QTL on chromosomes 5A, which determine the degree of drought tolerance and seed
dormancy in wheat. The physiological characteristics defined by QTL were minor
and limited to physiological indices of drought resistance and similar indices
of seed dormancy. These authors suggested that observed changes in wheat
response to ABA, at least in part are determined by identified QTL on
chromosomes 5A and that QTL in question controls both the dehydration mechanism
and seedling resistance to moisture deficit.

Similar results were
obtained in another study using the two mapping populations constructed from
the F8:9 recombinant inbred lines; the experiments were performed under
laboratory conditions when wheat plants were exposed to osmotic stress and
conventional water regime. Eighty eight QTLs mapped in this experiment
explained 3.33-77.01% of the phenotypic variance for physiological drought resistance,
and many agronomical important traits were assessed in parallel. The authors
found that of 88 identified QTLs, not all of these 22 QTL for drought resistance
demonstrating the importance of field experiments.
          The Malaysian scientists
identified and mapped several QTLs for drought tolerance in wheat .By
comprehensive testing of 120 F2 genotypes in the mapping population under
drought condition, these authors found that the relative water content under
drought resistance exhibited extended difference indicating a minor gene effect
on this trait. A single marker analysis revealed the major QTLs associated with
the trait of drought resistance. The results obtained in this study included
the development of molecular SSR markers. To on 5D and one 5A chromosomes.
These markers associated with the trait of drought resistance explaining 3,22
and 21% of the total variation respectively.

Plant height is a
crucial index one assessing the trait for wheat yield. Its full manifestation
Chinese researcher study the genotype and environmental interactions during the
water stress conditions by using the mapping population develop from the double
haploid lines. They found that none of the identified QTLs was active during
all phases of plants ontogenesis and that additive effects of analyses QTLs
were more important than the QTLs environment interactions. Some of the
identified QTLs, that signified the genotypes under study manifested high
adaptations to low moisture conditions. As a result, the authors concluded that
the plant height is complex trait depend as a whole on the journal
physiological status of the cell and the water regime in particular.

    The architecture and state of the root
system are other features essential for maintaining an optimum water regime of
plants. In wheat, these characters are important when the crops are grown under
deep soil moisture conditions where the traits help the plants to limited water
access. Mapping QTLs for the seminal root angle and the number of embryonic roots
was performed by using the mapping population derived of doubled wheat haploids
breed by a cross between two varieties. The varieties are SeriM82 and Hartog
six QTLs with moderate effect were found to determine the seminal root angle,
together with other six QTLs also of moderate effect, which stood for the
number of embryonic roots. It found that QTLs for seminal root angle were
located on chromosomes 2A, 3D, 5D, 6A, whereas 6B, QTLs for the number of
embryonic roots are found on the chromosomes number 1B, 3A, 3B, 4A, and 6A
while the authors failed to establish the interaction between genetic
components of plants cell and physiological index of wheat water regimes.

     It is obvious that the delineating the
genomic regions responsible for the water status is important both in
fundamental and applied aspects. First such study provides valuable information
about the transcription response of higher plant genome when affected by water
stress. Second it provides new information on the physiological manifestation
of genes in water stress environments. Third in feature the identification of
such regions would probably help to identify the individual genes and their
promoters that directly respond to water stress 
to belong to Cis-elements with an important role in the molecular and
physiological mechanism for the implementation of water homeostasis and final
is the mapping QTLs that stands for physiological manifestation of economic
traits including those determining plant water status and critical for improving
crops agronomic properties by MAS, would promote the breeding process and in
this way provide new highly productive varieties and lines, including drought
resistance genotypes. However, despite numerous studies which identified the
genetic determinants responsible for physiological drought resistance and water
regime of plant including the reports listed, the genetic determinants of water
retention capacity of cells and tissues, and agronomic constituents of plant
water status have not been as yet researched by QTLs analysis in such most
valuable crop as wheat.

    We identified chromosomal loci (QTLs)
involved in the control of physiological manifestations of plant moisture
content, water retention and water deficit in spring wheat tissues and
established correlations between the physiological components of plant water
status and several quantitative morphological traits of plant growth and

Materials and method:

Plant material: the
mapping population ITMI was developed by pollinating plants offspring bread
wheat cv. Opata 85 with pollen of synthetic hexaploid W7984; the latter is an
amphidiploid resulted by the crossing Aegilops tauschii Coss., accession
CIGM86.940(genome DD) with tetraploid wheat T. turgidum var. durum cv. Altar 84
(genome AABB) ( the female parent). Interspecies cross was accomplished by
doctor A. Mujeeb-Kazi (CIMMYT, Mexico) 5,17. Ten seeds from each of randomly chooses
lines were selected by doctor P. Leroy (INRA, Clermont-Ferrand) from total of
150 recombinant inbred lines develop in the Cornell University United States by
single seed descent breeding up to F8 or F9. Four of these 114 lines were
discarded because of low seed difference. The rest 110 lines were used in the
present study carried out on the experimental plots the Vavilov Institute of
Plant Industry.


Assessing plant water
retention, moisture deficit, and dry matter content was made in triplicate
using the strand method 1,3.Plant samples were dried in a thermostat oven at
105oc to constant weight. The total amount of water (x) as a
percentage of fresh weight was determined with a formula: x=100(b-c)/(b-a), a
is the weight of an empty weighing bottle, b is the weight of the weighing
bottle with fresh plant material, and c is the weight of the weighing bottle
with the dry plant material. Water deficit in the leaves was calculated as
percentage of total water content at the saturation state using the formula:
WD=100Wa /W where Wa is the amount of water absorbed at
complete leaf saturation calculated as a difference between the leaf weight
after the complete saturation of leaves and before saturation. W is the total
water content in the leaves at the state of saturation determined as the
difference between the leaf weight after complete saturation of leaves and
their dry weight. Water retention capacity was determined by using the formula:
WRC = 100B/A, where WRC is the water loss by leaves through the experiment expressed
as a percentage of its initial contents in leaves, A is the water content at
the beginning of the experiment, and B is the water loss during wilting period.
When leaf water regime was assessed after wilting, the leaves exposed to
wilting for 3 or 24 hours after sampling were also used for parallel evaluation
of the same water regime indices: water content, water deficit and water
retention capacity.

Determine of height and
weight of growing plants was performed by using the standard method which
explains previously.

Statistical processing:

   The data were processed using the
MAPMAKER/QTL computer program. This program performs calculations using the
Haldane function and therefore we used the mapping data from the database Grain
Genes to convert distances on the map using the MAPMAKER/EXP 3.0 program. The
data from phenotypic analysis were integrated into the existing basic map
developed for the ITMI population. When mapping QTLs, we used only those
markers that were consistent with the

Kosambi mapping functions.
Mapping of QTLs and comparison of the resulting genetic map with the existing
chromosome chart were accomplished using the computer program QGENE.

   To estimate the accuracy of the relationship
established between the identified loci and polymorphisms of particular traits,
we used the threshold value of the logarithm of odds. For each trait, we
conducted separate QTL analysis, and only loci with were taken into account.

   To determine the nature of the relationship
between the observed characters and conditions of water regime, we calculated
correlation coefficients rxy. The ratio between rxy   and the corresponding t-test value
served as a criterion for important assessment. To integrate the average value
of indices estimated under various conditions of water regime, the analysis of
variance was employed, in particular, we determined the mean square deviations
and variance ratio F, and significance of data was concluded. The value p
_ 3 and 12, with 3> LOD >_2. In one case QTL was
established with LOD score >4. The loci with LOD scores above 3 were
regarded as major, and those with LOD scores between 2 and 3, as strong. Trait
names and their code are listed in table 1. QTL positions and molecular markers
corresponding to the maximum LOD score for each specific QTLs are also listed
in table. In table 1; in addition this table presents particular QTL. LOD score
and percentage of phenotypic variance (R2) determined by the
identified QTL are given separately each character and each identified QTL.

As a whole, we found 13 QTLs for ten traits; these QTLs were mapped on
the linkage groups 1A, 1B, 2B, 2D, 4A, 5A,5B, 5D, 6A and 6D.Some of the
identified QTLs stand for the manifestation of the several phenotype. To
illustrate, the measurements of water retention capacity in lines of the ITMI
mapping population after 3 and 24 hour revealed QTLs; two of them were major
and one strong. The trait for water deficit was determined by a strong QTLs on
chromosome. 6A transferred from the female parent.

QTLs for water content in the roots were
assembled on chromosomes 5B and 6D. It is notable that the same chromosomes
comprise QTLs for traits of root dry matter content. The traits of the root
weight are determined and calculate by a single QTL on the same chromosome 5B
in a slightly different region on this linkage group. Plant height at the stage
of booting was determined by four QTLs located on chromosomes B, 5A, and 5D.
Three of these four QTLs were major ones, and one was strong. Plant eight was
determined by QTLs were strong and explained almost identical percentages of
phenotypic variance of this trait.

To relate the physiological components of plant water status with
quantitative morphological and biochemical characteristics that determine
growth and development of wheat plants, we calculated the correlation
coefficients for all traits under study. In general, in the ITMI lines, as seen
from the data presented in Table 2, root hydration after 24 h was weakly
correlated with plant dry weight. The values of indices for water retention,
dry matter content and root weight varied in different lines of the mapping
population at the average levels of correlation.

As a whole, the correlations between the traits were most vivid. Most
obvious was the average positive correlation between water retention capacity at
24 h. One should also note weak correlation between water retention capacity
after 3 h and plant height at the booting stage and between water retention
capacity after 3 h and plant dry weight.

Concerning the trait water retention after 24 h, we find average
negative correlation with the average hydration and weak negative correlation
with water deficit; it means that the values of WRC-24 index are associated
with declining W and WD indices or vice versa. Another noticeable fact is
correlation established between WRC-24 and dry matter content and between
WRC-24 plant dry weight and root dry weight.