Barley Genetics Newsletter 37:5-20 (2007)

Frequency distributions and composite interval mapping for QTL analysis
in 'Steptoe' x 'Morex' barley mapping population

H. S. Rao^1,\ 2†^, O. P. Basha^1^, N. K. Singh^1^, K. Sato^3^, H. S.
Dhaliwal^1^\*

Indian Institute of Technology Roorkee, UA, India

^1^Department of Biotechnology, Indian Institute of Technology Roorkee,

Roorkee 247667, Uttaranchal, INDIA

^2^Present address: 101, Maize Genetics Unit, Division of Genetics, LBS
Building,

Indian Agricultural Research Institute, New Delhi 110012, INDIA

^3^Barley Germplasm Center, Okayama University, Kurashiki 710-1146,
JAPAN

\*corresponding author Email: <hsdhafbs@iitr.ernet.in>

FAX: 91-1332-273560 Tel.: 01332-285259

^†^Additional author Email: <hsr_f12@rediffmail.com>

**ABSTRACT**

With the advancement of QTL mapping strategies, the traditional
approaches for the identification of genes and their effects responsible
for trait expression are gradually losing significance. The phenotypic
data for heading days, plant height, peduncle length, number of tillers
and stripe rust was recorded on 150 recombinant inbred line (RIL)
population developed from a barley cross of 'Steptoe' and 'Morex'.
Preliminary examinations of frequency distribution plots were fairly
useful in the prediction of number of genes governing traits expression
in barley (*[Hordeum vulgare]{.underline}* L.). The predictions were
then systematically confirmed through QTL mapping. Molecular marker data
for the population available at the public domain (GrainGenes website)
was used for the construction of linkage map and QTL analysis. Clear
colinearity was observed between the number of QTLs identified and the
number of genes predicted based upon frequency distribution study alone.
A total of 17 QTLs were detected for the five traits evaluated. Several
major QTLs were detected on chromosome 2H, which could serve as
candidate for map-based studies of phenomena such as pleiotropism,
recombination hot spots, gene-rich regions and QTL clustering.

**Keywords.** Barley, frequency distribution, quantitative trait loci,
recombinant inbred line, peduncle length, stripe rust, gene rich region.

##### 

##### INTRODUCTION

Cultivated barley (*[Hordeum vulgare]{.underline}* L.) is a diploid
(2n=14) which ranks fourth among the most important cereal crops in the
world after rice, wheat and maize. Barley belongs to the same tribe
Triticeae as that of wheat and rye and it resembles wheat in many
respects. Barley is however, more tolerant to soil salinity and drought
than wheat. Many important traits of economic and agronomic importance
in barley are quantitative in nature displaying continuous variation.
The efficiency of breeding programs depends on our knowledge of the
genetic control and genomic location of QTLs governing the trait(s) of
interest. With the advent of molecular markers (Botstein et al. 1980)
and the user-friendly statistical software it has become possible to
resolve and map the QTLs for complex traits on chromosomes.

QTL analysis in barley is significant not only for the crop itself but
also for comparative mapping with other cereal crops. The identification
of diverse taxa sharing segments of similar gene orders throughout their
genomes has been the major outcome of comparative mapping where
chromosome alignment has hastened identification of new genes for their
ultimate introgression into suitable cultivars. The genetic maps of
diploid wheat, *[Triticum monococcum]{.underline}* and barley, *[Hordeum
vulgare]{.underline}* L. are remarkably conserved except for few regions
where translocation and inversion of chromosome segments have taken
place (Dubcovsky et al. 1996). There is also a high level of genomic
conservation at specific regions with rice, maize and oat (Deynze et al.
1995, Han et al. 1998).

The results of several QTL mapping studies have indicated that there are
only few major genes, which interact with numerous minor genes and
environment to give continuous trait phenotype characteristic of
quantitative traits. Thus examination of frequency distribution plots at
single location is useful in assessing the probable number of major
genes controlling a trait. This is particularly useful when resources
are limiting and a decision has to be taken on priority basis before
starting a breeding program for which trait QTL mapping experiment
should be undertaken. The present article deals with the mapping of QTLs
for a number of traits in a barley 'Steptoe' x 'Morex' RIL mapping
population and its relationship with the predictive value of frequency
distribution for the traits.

**MATERIALS AND METHODS**

**Plant Material**

150 recombinant inbred lines (RILs) derived from a cross between two
barley (*[Hordeum vulgare]{.underline}* L.) genotypes 'Steptoe' and
'Morex', obtained from Dr. Kazuhiro Sato, Okayama University, Japan was
used as a mapping population and it was phenotyped for five traits. Each
of the RILs and the parents were sown as a single one meter row with row
to row spacing of 30cm in the experimental field at the Indian Institute
of Technology Roorkee, India in the winter season of 2005. Normal
fertilizers, irrigation and other agronomic practices were followed for
growing the population. Both 'Steptoe' and 'Morex' are hulled, six-rowed
spring barley varieties. 'Steptoe' is a late flowering and dwarf line
with reduced peduncle, few tillers per plant and moderate resistance to
stripe rust. On the other hand, 'Morex' is early flowering and tall
genotype with long peduncle, more tillers per plant and high
susceptibility to stripe rust.

**Phenotypic Data**

The data on five quantitative traits were recorded as the average of
five competitive plants per RIL. The number of days to heading was
recorded as the number of days from sowing till half of the tillers in a
RIL had flowered. Plant height (cm) was recorded as the length of plant
from the base at the soil surface to the tip of spike of the tallest
tiller excluding awns. Peduncle length was measured as the length of
peduncle from the base of flag leaf to the base of basal spikelet of a
spike. The number of effective tillers bearing spikes was taken as the
number of tillers per plant. The data on natural incidence of stripe
rust at the adult plant stage under field conditions was recorded as
percent severity of the leaf area covered by stripes of uredia and the
type of pustules, where the symbol S for susceptible was used for large
pustules without any necrotic area; MS, MR for moderately
susceptible/resistance for small pustules with or without necrotic areas
around them and R for hypersensitive immune reaction without any
pustule.

**Data Analysis**

The basic statistical analysis was performed for all the traits
recorded. Mean, range and standard deviations were estimated.
Correlation coefficient among various traits was calculated to infer
probable inter-relationships between the traits studied. Frequency
distribution plots for traits were presented as about ten phenotypic
classes in the RIL population.

**Genotypic data and Linkage mapping**

Genotypic data for 343 molecular markers available at the public domain
(GrainGenes website: http://www.gene.pbi.nrc.ca) for 150 RILs of
'Steptoe' x 'Morex' mapping population was utilized for the construction
of linkage map. Standard χ^2^ test was used to test the segregation
pattern of each marker. Linkage map was constructed by using the
software package MAPMAKER/EXP version 3.0 (Lincoln et al. 1992). A LOD
score of 3.0 and a maximum recombination frequency of 0.40 were used to
declare linkage between two markers.

**QTL mapping**

QTL analysis was performed using the method of Composite Interval
Mapping (CIM) (Zeng 1994) as in QTL Cartographer version 2.5 (Wang et
al. 2005). Composite interval mapping combines the approaches of
interval mapping (IM) and Single Marker Analysis in a multiple
regression framework. Initially it builds cofactors by selecting most
significant markers through Single Marker Analysis methodology. Once the
model containing cofactors is built, the entire genome is rescanned
using interval mapping. We used model 6 with window size 10 cM where
forward and backward regression method was utilized. Walk speed was set
at 2 cM to scan the entire genome. We performed 1000 permutations at
0.05 significance level to balance type 1 and type 2 errors and declare
appropriate threshold levels for QTL (Churchill and Doerge 1994). The
best estimate of QTL location was assumed to correspond to the position
having the peak significance level and the confidence interval was drawn
according to 1-LOD support interval (Lander and Botstein 1989).

#### **RESULTS**

#### 

#### **Frequency distribution for various traits**

The frequency distributions for the five traits evaluated are given in
Figure 1. Only plant height showed normal distribution while all other
traits displayed various levels of skewedness. The days to heading trait
was roughly partitioned into two phenotypic classes, one with early
heading habit while the other showing late heading trait. Peduncle
length also showed two phenotypic classes but the distribution tended to
be strongly influenced by embedded peduncle genotype rather than emerged
peduncle. Tiller numbers showed broad range with transgressive
segregation towards both ends. The histogram for stripe rust showed
continuous disease distribution pattern and the phenotypic classes were
clearly partitioned into five clusters.

**Phenotypic data Analysis**

Except for the heading days all traits showed transgressive segregation
and their phenotypic values exceeded beyond both of the mean parental
values (Table 1). The correlation coefficients between most of the trait
combinations were found to be significant ( Table 2). As expected
peduncle length had extraordinarily high correlation with heading days
and plant height. Peduncle length and heading habit were negatively
correlated, i.e. the emerged peduncle inbred lines had more probability
of early heading habit whereas the embedded peduncle lines had late
heading. The significant positive correlation between plant height and
peduncle extrusion could explain the fact that in taller plants,
peduncle grew faster to emerge out of the boot leaf before anthesis.

#### **TABLE 1.** Trait means in parent and trait means, standard deviations (SD) and range in RILs of

####  *Steptoe* x *Morex* population

  ----------------- ----------- ------------ --------------- -------------
                    Parents                  RIL population  

  Trait             *Steptoe*   *Morex*      Range           Mean ± SD

  Heading days      126.0       100.0        101.0 -- 126.0  112.05 ± 7.35

  Plant height (cm) 66.4        100.1        61.0 -- 126.6   95.57 ± 13.27

  Peduncle length   5.7         24.2         0 -- 28.6       10.21 ± 6.61
  (cm)                                                       

  Tiller number     2.6         3.1          1.2 -- 6.4      3.49 ± 1.08

  Stripe rust (%)   12.5        75           0 -- 100        43.11 ± 22.83
  ----------------- ----------- ------------ --------------- -------------

**TABLE 2.** Correlation coefficient (r) among various traits in RIL
population

  --------------- -------------- -------------- ------------ -------------
                  Plant height   Peduncle       Tiller       Stripe rust
                                 length         number       

  Heading days    -0.5491\*      -0.7392\*      -0.4987\*    -0.2056

  Plant height                   0.6360\*       0.5112\*     0.1595

  Panicle                                       0.3880\*     0.1334
  exertion                                                   

  Tiller number                                              0.2111
  --------------- -------------- -------------- ------------ -------------

\* P \< 0.0001

**Linkage map**

Out of the 434 polymorphic molecular markers data available at
GrainGenes website, we selected 343 by rejecting markers with more than
40% missing genotypes and those showing segregation distortion at 0.05
significance level (χ^2^ =3.841). Except for the two regions in
chromosomes 5 (1H) and 6 (6H), the whole genome was adequately covered
with markers and the centromeres were placed on consensus positions
based on marker orders along the chromosomes. The order of markers and
centromere positions did not vary much from their established map
positions. The combined length of the linkage map was 824.1 cM with
average spacing of 2.40 cM between adjacent markers.

**Genomic distribution of QTLs**

QTLs detected by CIM analysis as implemented in QTL Cartographer version
2.5 are presented in Table 3. The parent contributing respective alleles
for increasing trait value for heading days (HD), plant height (PH),
peduncle length (PL), number of tillers (TN) and the allele conferring
resistance to stripe rust (SR) were indicated in the table. In the
present study, five QTLs were identified for heading days exceeding the
threshold LOD score. 'Morex' parent contributed early heading alleles
for all the QTLs identified. Most of the phenotypic variance was
explained by the QTLs on 2H and 1H while those on 7H and 3H had only a
minor effect. Identification of several plant height QTLs spread
throughout genome (7H, 2H, 2H, 3H, 6H, 6H and 5H) supported the results
of frequency distribution. The two QTLs on 2H and 3H together explained
about 40% of the phenotypic variance. The alleles responsible for
increase or decrease in height had come from both of the parents and
thus supporting transgressive segregation observed for some of the RILs.
Two major QTLs, one each on chromosomes 2H and 3H were identified for
peduncle length while a third putative QTL detected on 1H had only a
minor effect. Only one QTL was identified for tillering ability on
chromosome 2H. For stripe rust, although four resistance QTLs spread
across chromosomes 2H, 3H, 4H and 5H were identified, none of them
explained significant phenotypic variance.

### TABLE 3. Chromosome mapping of various QTLs with nearest linked molecular marker for different traits

+--------+-----+-------------------+-------+-----+------+-----+-----+
| Trait  | C   | Marker interval   | Pos   | LOD | Addi | R   | All |
|        | hro |                   | ition |     | tive | ^2^ | ele |
|        | mos |                   | (cM)  |     |      | x   |     |
|        | ome |                   |       |     |      | 100 |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
| *He    | 1   | ABC156d - ABG022A | 41.61 | 4   | 1.   | 6   | *S* |
| ading* | (   |                   |       | .35 | 8964 | .60 |     |
|        | 7H) |                   |       |     |      |     |     |
| *date* |     |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 2   | ABG005 - Pox      | 33.41 | 18  | 4.   | 31  | *S* |
|        | (   |                   |       | .78 | 1443 | .42 |     |
|        | 2H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 2   | Adh8 -- CDO537    | 47.00 | 6   | 2.47 | 8   | *S* |
|        | (   |                   |       | .39 |      | .00 |     |
|        | 2H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 3   | ABG471 - ABG399   | 38.11 | 3   | 1.   | 4   | *S* |
|        | (   |                   |       | .22 | 6616 | .96 |     |
|        | 3H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 5   | ABC307A-cMWG706A  | 31.31 | 11  | 3.   | 19  | *S* |
|        | (   |                   |       | .69 | 2381 | .35 |     |
|        | 1H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
| *      | 1   | Pgk2B - PSR129    | 67.91 | 2   | 2.   | 4   | *S* |
| Plant* | (   |                   |       | .49 | 8861 | .72 |     |
|        | 7H) |                   |       |     |      |     |     |
| *h     |     |                   |       |     |      |     |     |
| eight* |     |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 2   | ABG005 - Pox      | 33.41 | 8   | -5.  | 18  | *M* |
|        | (   |                   |       | .83 | 7128 | .43 |     |
|        | 2H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 2   | Adh8 - CDO537     | 43.31 | 8   | -6.  | 20  | *M* |
|        | (   |                   |       | .41 | 1379 | .57 |     |
|        | 2H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 3   | ABC156c - AtpbB   | 46.81 | 12  | -5.  | 18  | *M* |
|        | (   |                   |       | .37 | 7998 | .77 |     |
|        | 3H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 6   | CDO497 - ABR335   | 40.91 | 3   | 3.   | 6   | *S* |
|        | (   |                   |       | .07 | 2705 | .00 |     |
|        | 6H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 6   | BCD340E - ksuD17  | 45.91 | 3   | 3.   | 7   | *S* |
|        | (   |                   |       | .74 | 5796 | .24 |     |
|        | 6H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 7   | ABG708 - Dor5     | 30.31 | 4   | -4.  | 9   | *M* |
|        | (   |                   |       | .93 | 2142 | .72 |     |
|        | 5H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
| *Ped   | 2   | ABG358 - ABG459   | 28.71 | 19  | -3.  | 36  | *M* |
| uncle* | (   |                   |       | .30 | 9943 | .24 |     |
|        | 2H) |                   |       |     |      |     |     |
| *l     |     |                   |       |     |      |     |     |
| ength* |     |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 3   | ABG471 - ABG399   | 38.11 | 4   | -2.  | 15  | *M* |
|        | (   |                   |       | .63 | 6111 | .38 |     |
|        | 3H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 5   | ABC307A           | 92.31 | 2   | -1.  | 6   | *M* |
|        | (   |                   |       | .61 | 7200 | .76 |     |
|        | 1H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
| *      | 2   | MWG858 - ABG358   | 28.61 | 4   | -0.  | 11  | *M* |
| Tiller | (   |                   |       | .89 | 3615 | .02 |     |
| \#*    | 2H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
| *      | 2   | MWG858 - ABG358   | 26.61 | 2   | -4.  | 6   | *S* |
| Stripe | (   |                   |       | .95 | 9528 | .22 |     |
| rust   | 2H) |                   |       |     |      |     |     |
| resis  |     |                   |       |     |      |     |     |
| tance* |     |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 3   | ABG377 - MWG555b  | 61.31 | 5   | 7.   | 11  | *M* |
|        | (   |                   |       | .10 | 0202 | .30 |     |
|        | 3H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 4   | ABC321 - ABR315   | 30.21 | 3   | -5.  | 6   | *S* |
|        | (   |                   |       | .24 | 1908 | .88 |     |
|        | 4H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+
|        | 7   | ABG391            | 1     | 2   | -4.  | 5   | *S* |
|        | (   |                   | 24.81 | .64 | 6547 | .56 |     |
|        | 5H) |                   |       |     |      |     |     |
+--------+-----+-------------------+-------+-----+------+-----+-----+

**DISCUSSIONS**

#### **Frequency distribution of various traits**

####  RILs are inbred lines derived from a cross of two diverse parents in which the individual genes are resolved into homozygous progenies. If we construct a histogram on such a population, the number and size of phenotypic classes obtained is directly related to the number of genes influencing the trait. For example, if a single gene controls the trait, there will be two phenotypic classes of equal sizes and if two genes control the trait there will be three phenotypic classes in 1:2:1 size proportion. If we assume the genes are additive and explaining equal variance, their should be n + 1 number of phenotypic classes observed for n number of genes in the population for as many number of additive gene combinations. On the other hand if epistatic interactions were significant and the individual genes were contributing unequally towards the overall phenotype, the distribution of phenotypic classes becomes skewed. From the preliminary observation of histograms (Figure 1) the approximate number of genes responsible for each trait could be predicted. For example, there should be one gene explaining most of the phenotypic variance for heading days as we observed two broad phenotypic classes in the histogram. There should also be one more gene with lesser but significant effect, which is responsible for minor third phenotypic class in between the two major classes. Height is the perfect example of quantitative inheritance where we expect large number of alleles acting additively to give normal distribution. The presence of two phenotypic classes is the indicative of single gene inheritance for peduncle length, but their unequal proportion could be explained by presence of one more parallel allele contributing towards short peduncle length phenotype. Tillering trait showed normal distribution and large transgressive segregation beyond both parental types. Thus, in barley we do not expect tiller number to be governed by single gene. Although we observed only one QTL exceeding the threshold LOD score, there is an indication of two more putative QTLs on chromosomes 7H and 1H (Figure 3). Also, some of the QTLs on chromosomes 3H and 6H identified by Franckowiak and Lundqvist, 2002, Buck-Sorlin, 2002 and Babb and Muehlbauer, 2003, remained undetected in the present study. The most probable explanation could be that 'Steptoe' and 'M' are not diverse enough with respect to tillering ability and it actually limited the QTL mapping approach to detect all genes of the trait. Frequency distribution of stripe rust has shown overall normal disease distribution pattern clustered in three major segregative and two minor transgressive groups. Both parents were susceptible to stripe rust but the rust progressed slowly in 'Steptoe' with very low terminal severity, usually called slow rusting. The five classes for rust severity could be explained by the presence of four genes, each of which was contributing additively towards resistance to stripe rust. When the resistance alleles for all four genes were present in a single genotype (4R), maximum resistance is expected which was observed with zero percent rust severity in the first transgressive group. Similarly, genotypes with 3R+1S, 2R+2S, 1R+3S and 4S allele combinations explained second, third, fourth and fifth groups, respectively in the frequency distribution plot. 

#### **QTL Analysis**

**Heading Days:** Days to Flower or heading days is considered to be an
important trait for planning of a breeding program. Early-heading
genotypes are preferred when the objective is to grow a cultivar late or
early in the growing season. Heading time in barley and wheat is
governed by three major genetic systems: vernalization requirement
(response to low temperature at the initial stages of plant
development), photoperiod sensitivity (day length) and narrow-sense
earliness (response to sum of temperature over a long period).
Vernalization is the requirement of low temperature period to plants for
transition from a vegetative to a reproductive phase. Among the
*[vrn]{.underline}* loci, *[Vrn1]{.underline}* on the group 5
chromosomes of Triticeae (A, B, D and H genomes) are the most
extensively characterized in terms of its effects and inheritance (Law
et al. 1976, Galiba et al. 1993, Kato et al. 1999). The vernalization
responsive phenotype is often found in conjunction with photoperiod
sensitivity, a delay in flowering when plants are grown under short-day
conditions (Karsai et al. 2001). Low vernalization requirement of barley
was probably met with partially but longer photoperiod could be
available only in the last week of March and hence delayed flowering in
RILs with *[Ppd]{.underline}*. The *[Ppd]{.underline}* -- H1
photosensitivity locus was first described by Laurie et al. (1994) on
the short arm of chromosome 2H. In barley, *[eps]{.underline}* 2S,
located near the centromere region of the 2H chromosome has been
reported to be a QTL for the environment independent narrow-sense
earliness (Laurie et al. 1995). The RILs in the present investigation
were sown without vernalization treatment. The QTL analysis carried out
without partitioning of heading trait into three categories identified
two significant QTL on 2H which probably represent *[Ppd]{.underline}*
and *[eps]{.underline}* loci. Thus major effect on heading days under
field conditions was due to the photoperiod and environment independent
narrow sense earliness genes. Major role of 2H in determining heading
days in barley is also inferred from the investigations carried out by
Marquez-Cedillo et al. (2001), Kicherer et al. (2000), Karsai et al.
(2005) and Qi et al. (1998) who detected heading days QTL on chromosomes
2H; 2H; 2H, 4H, 5H; and 2H, 7H, respectively.

**Plant Height:** Before the green revolution, one of the major causes
of yield loss was lodging of tall cultivars during rain and strong
winds. Plant height and culm stiffness are reported to be the two most
important traits determining lodging resistance in cereal plants (Keller
et al. 1999). Murthy and Rao (1980) and Stanca et al. (1979) have worked
out significant correlation between lodging resistance and dwarfness in
barley. Recently Chloupek et al. (2006) demonstrated the significance of
different sets of semi-dwarf genes in the determination of different
root system size that was further implicated with biotic and abiotic
stresses. With the development of semi-dwarf varieties, yield loss was
largely overcome and the plant utilized its resources in increasing
harvest index rather than its biomass. If the objective of the breeding
program is to enhance the grain production as in most instances, the
breeder prefers dwarf variety but if the objective is to utilize the
plant for dual purpose for fodder as well, then the breeder obviously
goes with taller varieties. Several studies in the recent past had
identified QTL for plant height in barley distributed throughout genome
but the major QTLs identified in the present study on chromosome 2H and
3H were found to occur more often than others. For example, Thomas et
al. (1995) detected plant height QTLs on 1H, 3H and 7H; Marquez-Cedillo
et al. (2001) on 2H, 3H, 4H and 5H; Kicherer et al. (2000) identified on
2H and 3H; Qi et al. (1998) on 2H, 3H and 7H; Teulat et al. (2001) on
2H, 3H, 4H, 5H, 6H and 7H; Zhu et al. (1999) on 1H, 3H, 4H and 6H; and
Chloupek et al. (2006) on 3H, 4H, 5H and 7H.

**Peduncle length:** Peduncle length is an important character in barley
as the inability of spikes to emerge out of boot leaf not only
eliminates outcrossing but also adversely affects the use of its
photosynthetic contribution to seed-setting and seed development. From
the preliminary observation on correlation coefficient, we can predict
that heading date and plant height jointly influences the ability of
peduncle to emerge out since early heading and tall plants had emerged
peduncle. We can infer that photoperiod (2H) had major effect on
peduncle length while narrow sense earliness (2H and 1H) had relatively
minor effect on peduncle length. Chromosome 3H also had significant
influence on the trait which might be coming from major plant height QTL
on the same chromosome. Hence, we can conclude that peduncle length is a
composite trait whose component traits include heading days and plant
height.

**Number of Tillers:** Tiller number is regarded as an important yield
component in wheat, barley and rice as the number of effective tillers
is equal to the number of spikes. The plants with lesser tiller number
generally have long spikes with increased grain weight and overall
sturdy plant architecture (Vasu at al. 2006). But the advantage of high
tiller numbered plant is that the overall harvest index from single
plant is much higher and it saves the unit area of land required to grow
plants for similar yields. In the present study, the tillering ability
of plants behaved as a single gene inherited trait and only one QTL on
chromosome 2H could be detected. Although earlier studies have also
indicated single gene inheritance pattern for the trait, chromosomal
locations of QTLs were not consistent with the present study.
Franckowiak and Lundqvist, 2002, Buck-Sorlin 2002 and Babb and
Muehlbauer 2003 have identified major QTL *lnt1* on chromosome 3HL and a
second QTL *cul2* on 6HL.

**Stripe Rust:** Stripe rust is a major disease in Triticeae and its
causal organism in barley is a biotrophic fungus, *[Puccinia
striiformis]{.underline}* f. sp. *[hordei]{.underline}*. The
characteristic feature of the disease is the appearance of pale stripes
on leaves followed by emergence of orange brown uredosori that contain
fungal spores. Yield loss of upto 30 % may occur, as photosynthetic and
metabolic capabilities of the plant are severely impaired. Rust
resistance in Triticeae is mainly of two types viz., vertical and
horizontal. Vertical resistance is race-specific conditioned by
gene-for-gene interaction between host and pathogen (Flor 1946).
Horizontal resistance, on the other hand is race-non-specific governed
by multiple genes with small effects. The results of the present
analysis show that the resistance QTLs identified were acting in a race
non-specific manner where they prevent pathogen(s) to form a basic
compatibility reaction. The 'Steptoe' is a slow stripe rusting genotype.
The rust infection is of susceptible type but the disease progresses
very slowly without causing an appreciable loss. Some of the QTLs for
resistance mapped in the present study were colinear with the previously
mapped QTL using different barley populations on chromosomes 4H, 5H
(Chen et al. 1994); 2H, 3H, 1H, 6H (Toojinda et al. 2000); 1H, 2H, 4H,
6H, 7H (Berloo et al. 2001); 2H, 4H (Kicherer et al. 2000); and on 3H,
4H, 7H (Toojinda et al. 1998) using local rust pathotypes further
confirming their race-non-specific resistance. The QTLs with their low
individual phenotypic variances when pyramided in a single genotype
could confer high overall resistance. The approach for pyramiding of
resistance QTLs was well demonstrated for 1H, 4H and 7H conferring
resistance to stripe rust at seedling stage in barley by Castro et al.,
(2003).

**QTL clusters**

Although the large genome size (4.9 × 10**^9^** bp) of barley makes the
genetic manipulations difficult, some of the recent advances in
comparative genomics have suggested the presence of recombination hot
spots and gene-rich regions in Triticeae where targeted approaches could
be utilized for genome analysis (Gill et al. 1996). Identification of
multiple QTLs on chromosomes 2H and 3H were also indicative of gene-rich
regions in barley. 2H is especially important because it contained QTLs
for all of the traits analyzed in the present study. Aissani and
Bernardi (1991) suggested the distribution of less conserved genes in
euchromatic regions while the distribution of conserved genes in the
heterochromatin region. This could be of evolutionary significance as
the genes in euchromatin region exposed to manipulations were providing
diversity for the plants to adjust to different environmental conditions
while the genes of heterochromatin region might be regulatory in
function, which must be conserved for their essential role in the very
existence of the organism.

Although the QTL analysis is of tremendous use in the identification of
genomic regions pertaining to the traits of economic importance, it
fails to identify the complete set of genes of a biochemical pathway
leading to the expression of trait. Many of the conserved genes for
which there are no allelic variants cannot be detected by this approach.
Such genes have been conserved through evolutionary forces and any
attempt to change them could have deleterious effect on the survival
ability of the organism.

**CONCLUSION**

It has been shown here that QTL mapping is an accurate approach for the
identification of genes underlying a trait but it is also cost intensive
to carry out such exercise for all traits. On the other hand,
construction of frequency distribution plots in routinely developed
mapping populations could be used as diagnostic assessment for the
prediction of number and effects of genes before planning QTL mapping
experiment. Although such an approach is very crude, it would be useful
in making appropriate allocation of resources.

In the present study, it has been found that proximal region of
chromosome 2H is of special interest as it contains QTLs for all of the
traits studied explaining large phenotypic variances and thus the region
could serve as candidates for further investigation. Significant
correlation among various traits was because of QTL linked in coupling
phase and in some of the instances pleiotropism cannot be ruled out. The
other genomic regions of interest include chromosome 3(3H) and
chromosome 5(1H), which harbors QTL for heading, peduncle length and
plant height. Further study needs to be carried out to fine map and
ultimately dissect out the individual genes in the region. Map-based
cloning is gradually becoming a feasible approach for dissection of the
QTL genes in Triticeae (Li et al. 2003). The individual QTL effects
could be studied efficiently by generating near isogenic lines (NILs) in
an [organized]{.underline} backcross program, which specifically
nullifies the background noise. In the recent past bioinformatics tools
have gained significant importance to aid *[in silico]{.underline}*
comparative genomic studies in species with large unmanipulable genomes
like barley and wheat with the help of well studied genomes such as
*[Arabidopsis thaliana]{.underline}*, rice and maize.

**ACKNOWLEDGEMENT**

The authors extend thanks to Dr. Firoz Hossain, Indian Agricultural
Research Institute, New Delhi for his valuable suggestions and
discussion while preparing the manuscript.

![](media/image1.png){width="6.2625in" height="7.75in"}

**Figure 1.** Frequency distribution plots for heading days (HD), plant
height (PH), peduncle length (PL), tiller number (TN), and stripe rust
(SR) in RILs of *Steptoe* x *M* population.

![](media/image2.png){width="6.479861111111111in"
height="7.604861111111111in"}

**Figure 2.** Genetic map of SM barley RIL population with 343 molecular
markers indicating QTLs for heading days (HD), plant height (PH),
peduncle length (PL), number of tillers (TN) and stripe rust (SR).
Vertical bar and the symbols represent confidence interval and peak LOD
scores respectively for various QTLs

![](media/image3.png){width="6.5in" height="7.117361111111111in"}

**Figure 2. (continued)** Genetic map of SM barley RIL population with
343 molecular markers indicating QTLs for heading days (HD), plant
height (PH), peduncle length (PL), number of tillers (TN) and stripe
rust (SR). Vertical bar and the symbols represent confidence interval
and peak LOD scores respectively for various QTLs.

![](media/image4.png){width="6.502083333333333in"
height="7.879861111111111in"}

**Figure 3.** QTL likelihood maps for various traits obtained from
composite interval mapping (CIM) analysis indicating LOD score along the
ordinate while genetic map (all chromosomes together) along the
abscissa. The respective threshold LOD estimated by 1000 permutations at
0.05 significance, are represented as horizontal line.

**REFERENCES**

Aissani, B., and G. Bernardi, 1991: CpG islands: features and
distribution in the genomes of vertebrates. Gene **106,** 173-183

Babb, S., G. J. Muehlbauer, 2003: Genetic and morphological
characterization of the barley uniculm2 (*cul2*) mutant. Theor. Appl.
Genet. **106**, 846--857

Botstein, D., R. L. White, M. Skolnick, and R. W. Davis, 1980:
Construction of genetic linkage map in man using restriction fragment
length polymorphisms. Am. J. Hum. Genet. **32,** 314-331

Buck-Sorlin, G. H. 2002: The search for QTL in barley (*Hordeum vulgare*
L.) using a new mapping population. Cell Mol. Biol. Lett. **7**,
523--535

Castro, A. J., X. Chen, P. M. Hayes, and M. Johnston, 2003: Pyramiding
Quantitative Trait Locus (QTL) Alleles Determining Resistance to Barley
Stripe Rust: Effects on Resistance at the Seedling Stage. Crop Sci.
**43,** 651--659

Chen, F. Q., D. Prehn, P. M. Hayes, D. Mulroney, A. Corey and H. E.
Vivar, 1994: Mapping genes for resistance to barley stripe rust
(*[Puccinia striiformis]{.underline}* f. sp. *[hordei]{.underline}*).
Theor. Appl. Genet. **88,** 215--219

Chloupek, O., B. P. Forster, and W. T. B. Thomas, 2006: The effect of
semi-dwarf genes on root system size in field-grown barley. Theor. Appl.
Genet. **112**, 779--786

Churchill, G. A., and R. W. Doerge, 1994: Empirical threshold values for
quantitative trait mapping. Genetics **138,** 963-971

Deynze, A. E. V., J. C. Nelson, E. S. Yglesias, S. E. Harrington, D. P.
Braga, S. R. McCouch, and M. E. Sorrells, 1995: Comparative mapping in
grasses. Wheat relationships. Mol. Genet. Genomics **248,** 744-754

Dubcovsky, J., Ming-Cheng Luo, Gan-Yuan Zhong, R. Bransteitter, A.
Desai, A. Kilian, A. Kleinhofs, and J. Dvorak, 1996: Genetic map of
diploid wheat, *[Triticum monocuccum]{.underline}* L. and its comparison
with maps of *[Hordeum vulgare]{.underline}* L. Genetics **143,**
983-999

Flor, H.H., 1946: Genetics of pathogenicity in *[Melampsora
lini]{.underline}*. J. Agric. Res. **73,** 335--357

Franckowiak, J. D., and U. Lundqvist, 2002: Current List of New and
Revised Barley Genetic Stock Descriptions. Barley Genet. Newsl. **32**,
47

Galiba, G., S. A. Quarrie, J. Sutka, A. Morgounov, and J. W. Snape,
1995: RFLP mapping of vernalization (*[Vrn1]{.underline}*) and frost
resistance (*[Fr1]{.underline}*) genes on chromosome 5A of wheat. Theor.
Appl. Genet. **90,** 1174-1179

Gill, K. S., B. S. Gill, T. R. Endo, E. V. Boyko, 1996: Identification
and high-density mapping of gene-rich regions in chromosome group 5 of
wheat. Genetics **143,** 1001-1012

Han, F., A. Kleinhofs, S. E. Ullrich, A. Kilian, M. Yano, and T. Sasaki,
1998: Synteny with rice: Analysis of barley malting quality QTL and rpg4
chromosome regions. Genome **41,** 373--380

Karsai, I., K. Meszaros, L. Lang, P. M. Hayes, and Z. Bedo, 2001:
Multivariate analysis of traits determining adaptation in cultivated
barley. Plant Breed. **120,** 217-222

Karsai, I., P. Szucs, K. Meszaros, T. Filichkina, P. M. Hayes, J. S.
Skinner, L. Lang, and Z. Bedo, 2005: The Vrn-H2 locus is a major
determinant of flowering time in a facultative x winter growth habit
barley (*Hordeum vulgare* L.) mapping population. Theor. Appl. Genet.
**110,** 1458-1466

Kato, K,, H. Miura, and S. Sawada, 1999: QTL mapping of genes
controlling ear emergence time and plant height on chromosome 5A of
wheat. Theor. Appl. Genet. **98,** 472-477

Keller, M., Ch. Karutz, J. E. Schmid, P. Stamp, M. Winzeler, B. Keller,
and M. M. Messmer, 1999: Quantitative trait loci for lodging resistance
in a segregating wheat x spelt population. Theor. Appl. Genet. **98,**
1171-1182

Kicherer, S., G. Backes, U. Walther, and A. Jahoor, 2000: Localising
QTLs for leaf rust resistance and agronomic traits in barley (*Hordeum
vulgare* L.). Theor. Appl. Genet. **100,** 881-888

Lander, E. S., and D. Botstein, 1989: Mapping Mendelian factors
underlying Quantitative traits using RFLP linkage maps. Genetics
**121,** 185-199

Laurie, D. A., N. Pratchett, J. H. Bezant, and J. W. Snape, 1994:
Genetic analysis of a photoperiod response gene on the short arm of
chromosome 2 (2H) of *[Hordeum vulgare]{.underline}* (barley). Heredity
**72,** 619-627

Laurie, D. A., N. Pratchett, J. H. Bezant, and J. W. Snape, 1995: RFLP
mapping of five major genes and eight quantitative trait loci
controlling flowering time in winter x spring barley (*[Hordeum
vulgare]{.underline}* L.) cross. Genome **38,** 575-585

Law, C. N., A. J. Worland, B. Giorgi, 1976: The genetic control of
ear-emergence time by chromosomes 5A and 5D of wheat. Heredity **36,**
49-58

Li, H., S. A. Brooks, W. Li, J. P. Fellers, H. N. Trick, and B. S. Gill,
2003: Map-based cloning of leaf rust resistance gene
*[Lr21]{.underline}* from the large and polyploid genome of bread wheat.
Genetics **164,** 655-664

Lincoln, S. E., M. Daly, and E. S. Lander, 1992: Constructing genetic
maps with MAPMAKER/EXP 3.0. Whitehead Institute technical report, 3^rd^
edn. Cambridge

Marquez-Cedillo, L. A., P. M. Hayes, A. Kleinhofs, W. G. Legge, B. G.
Rossnagel, K. Sato, S. E. Ullrich, and D. M. Wesenberg, The North
American Barley Genome Mapping Project, 2001: QTL analysis of agronomic
traits in barley based on the doubled haploid progeny of two elite North
American varieties representing different germplasm groups. Theor. Appl.
Genet. **103,** 625-637

Murthy, B. N., and M. V. Rao, 1980: Evolving suitable index for lodging
resistance in barley. Indian J. Genet. Plant. Breed. **40,** 253-261

Qi, X., R. E. Niks, P. Stam, and P. Lindhout, 1998: Identification of
QTLs for partial resistance to leaf rust ( *Puccinia hordei*) in barley.
Theor. Appl. Genet. **96,** 1205*--*1215

Stanca, A. M., G. Jenkins, and P. R. Hanson, 1979: Varietal responses in
spring barley to natural and artificial lodging and to a growth
regulator. J. Agric. Sci. Camb. **93,** 449-456

Teulat, B., O. Merah, I. Souyris, and D. This, 2001: QTLs for agronomic
traits from a Mediterranean barley progeny grown in several
environments. Theor. Appl. Genet. **103,** 774--787

Thomas, W. T. B., W. Powell, R. Waugh, K. J. Chalmers, U. M. Barua, P.
Jack, V. Lea, B. P. Forster, J. S. Swanston, R. P. Ellis, P. R. Hanson,
and R. C. M. Lance, 1995: Detection of quantitative trait loci for
agronomic, yield, grain and disease characters in spring barley
(*Hordeum vulgare* L.). Theor. Appl. Genet. **91,** 1037-1047

Toojinda, T., E. Baird, A. Booth, L. Broers, P. Hayes, W. Powell, W.
Thomas, H. Vivar, and G. Young, 1998: Introgression of quantitative
trait loci (QTLs) determining stripe rust resistance in barley: an
example of marker-assisted line development. Theor. Appl. Genet. **96,**
123*--*131

Toojinda, T., L. H. Broers, X. M. Chen, P. M. Hayes, A. Kleinhofs, J.
Korte, D. Kudrna, H. Leung, R. F. Line, W. Powell, L. Ramsay, H. E.
Vivar, and R. Waugh, 2000: Mapping quantitative and qualitative disease
resistance genes in a doubled haploid population of barley (*[Hordeum
vulgare]{.underline}*). Theor. Appl. Genet. **101,** 580--589

van Berloo, R., H. Aalbers, A. Werkman, and R. E. Niks, 2001: Resistance
QTL confirmed through development of QTL-NILs for barley leaf rust
resistance. Mol. Breed. **8,** 187-195

Vasu K., S. Sood, H. S. Dhaliwal, P. Chhuneja, B. S. Gill, 2006:
Identification and mapping of a tiller inhibition gene *(tin3)* in
wheat. Theor. Appl. Genet. (*Published online*)

Wang, S., C. J. Basten, Z. B. Zeng, 2005: Windows QTL Cartographer 2.5.
Department of Statistics, North Carolina State University, Raleigh
<http://www.statgen.ncsu.edu/qtl/crt/WQTL.htm>

Zang, Z. B., 1994: Precision mapping of quantitative trait loci.
Genetics **136,** 1457-1468

Zhu, H., L. Gilchrist, P. Hayes, A. Kleinhofs, D. Kudrna, Z. Liu, L.
Prom, B. Steffenson, T. Toojinda, and H. Vivar, 1999: Does function
follow form? Principal QTLs for Fusarium head blight (FHB) resistance
are coincident with QTLs for inflorescence traits and plant height in a
doubled-haploid population of barley. Theor. Appl. Genet. **99,**
1221--123