Meteorological conditions at Mandya, Hassan and Davanagere were ideal for the development of severe NCLB epidemics. The % disease severity during rainy season of 2014 did not follow the normal distribution, and hence data were transformed using arcsine transformation. Significant genetic differences among the F3 progenies were revealed by the analysis of variance. Bartlett’s chi-square test was non-significant which indicated the homogeneity of error mean sum of squares across three locations. Hence data on NCLB across locations were pooled. Pooled analysis of variance of F2:3 families indicated that variance due to genotypes and genotype × environment interaction was significant indicating that expression of disease incidence significantly varied among F3 families and depended on testing environment (Table 1).
Table 1
Pooled Analysis of variance and estimates of mean, range of parents and F2:3 progenies derived from crosses CM 212 x MAI 172 and CM 202 x SKV 50 for NCLB incidence during Kharif 2014 across three locations
Source
|
DF
|
Mean sum of Squares
|
CM 212 X MAI 172
|
CM 202 X SKV 50
|
Replication
|
1
|
359.55*
|
4830.96**
|
Genotype
|
367
|
448.40**
|
421.95**
|
Location
|
2
|
14114.28**
|
18497.35**
|
Genotype*Location
|
734
|
185.22**
|
232.39**
|
Error
|
1103
|
70.32
|
71.78
|
Estimates of mean, range of parents and 366 F2:3 progenies
|
|
CM212 (Susceptible)
|
MAI172 (Resistant)
|
S v/s R (Pr < t)
|
F3 Grand mean
|
F3 Range
|
CM202 (Susceptible)
|
SKV50 (Resistant)
|
S v/s R (Pr < t)
|
F3 Grand mean
|
F3 Range
|
Hassan
|
69.5(56.4)
|
29.5 (26.5)
|
0.0144
|
58.7(50.1)
|
7–99
|
84 (66.4)
|
38.5 (38.3)
|
0.00078
|
60.16 (51.0)
|
9–99
|
Mandya
|
71.0(57.4)
|
34 (37.3)
|
0.0034
|
50.7(45.3)
|
20–81
|
70.5 (57.0)
|
26.5 (30.9)
|
0.00064
|
52.14 (46.1)
|
14–88
|
Davanagere
|
63.0 (52.5)
|
42.5(40.6)
|
0.0245
|
58.6(48.5)
|
20–90
|
78.0 (62.0)
|
22.2 (28.2)
|
0.00117
|
61.8 (52.0)
|
20–92
|
Pooled
|
67.8 (55.5)
|
35.3 (34.8)
|
0.0238
|
56.0 (48.5)
|
7–99
|
77.5 (61.8)
|
29.06 (32.5)
|
0.00053
|
58.0 (49.7)
|
9–99
|
*Significance at p = 0.05 ** Significance at p = 0.01 |
Estimation of mean, range, heritability and genetic advance
Parents differed significantly in their reaction to NCLB (Table 2). The parents MAI 172 and SKV 50 showed resistant reaction at all locations. The susceptible inbreds CM 212 and CM 202 recorded significantly higher disease incidence. The mean disease incidence of 57.92 %, 50.53 % and 57.93 % was observed at Hassan, Mandya and Davanagere, respectively and it was 55.34 % when pooled across locations. Maximum range of disease incidence (7.00 to 99.00% for Population 1 and 9.00 to 99.00 % for Population 2) was recorded at Hassan followed by Davanagere (20.00 to 90.00% and 20.00 to 92.00 % for Population1 and 2, respectively) and Mandya (20.00 to 81.00 % and 14.00 to 88.00 % for Population 1 and 2, respectively). The pooled NCLB incidence ranged from 7.00 to 99.00 % for the Population 1 and 9.00 to 99.00 for the Population 2. The frequency distribution pattern of F3 families for NCLB was negatively skewed and platykurtic at all the three locations and across locations in population 1 and 2 (Table 2, Figs. 1 and 2).
Table 2 Test for normality, skewness, kurtosis and estimates of genetic components for NCLB disease incidence in F2:3 populations derived from the crosses CM 212 x MAI 172 and CM 202 x SKV 50
Character
|
CM 212 x MAI 172
|
CM 202 x SKV 50
|
Hassan
|
Mandya
|
Davanagere
|
Across locations
|
Hassan
|
Mandya
|
Davanagere
|
Across locations
|
Skewness
|
-1.008
|
-0.428
|
-0.367
|
-0.213
|
-0.876
|
-0.355
|
-0.212
|
-0.278
|
Kurtosis
|
1.859
|
-0.294
|
0.499
|
0.223
|
1.636
|
1.240
|
-0.192
|
0.621
|
KS Test
|
0.111
|
0.077
|
0.118
|
0.048
|
0.117
|
0.077
|
0.113
|
0.041
|
Pr > D
|
<0.010
|
<0.010
|
<0.010
|
0.037
|
<0.010
|
<0.010
|
<0.010
|
0.146
|
Mean (%)
|
57.92
|
50.34
|
57.93
|
55.34
|
60.06
|
52.56
|
62.07
|
58.23
|
Range (%)
|
7-99
|
20-81
|
20-90
|
7-99
|
9-99
|
14 - 88
|
20 - 92
|
9-99
|
Genotypic Coefficient of Variation (GCV in %)
|
27.91
|
18.73
|
29.28
|
35.14
|
27.52
|
16.99
|
29.17
|
32.14
|
Phenotypic Coefficient of Variation (PCV in %)
|
31.41
|
27.57
|
29.66
|
42.89
|
30.83
|
27.32
|
29.61
|
41.45
|
Heritability (%)
|
78.92
|
46.14
|
97.49
|
67.12
|
79.67
|
38.70
|
97.06
|
60.11
|
Genetic Advance as per cent Mean (GAM in %)
|
51.07
|
22.77
|
59.57
|
56.66
|
50.60
|
21.78
|
59.20
|
51.33
|
KS test: Kolmogorov Smirnov goodness of fit
The estimates of phenotypic and genotypic coefficient of variation were high in both populations. High heritability and genetic advance which is a measure of genetic gain under selection were observed at all the locations and over locations (Table 2).
Construction of linkage map
Parental polymorphism survey using SNPs
The resistant (MAI 172 and SKV 50) and susceptible inbreds (CM 212 and CM 202) were genotyped using 768 SNP markers. The polymorphism percentage between the two parents was 38.67 % in Population 1 and 37.76 % in Population 2. The polymorphic SNPs were used for genotyping the two F2:3 populations (Population 1: CM 212 x MAI 172 and Population 2: CM 202 x SKV 50). Among these markers, only 297 SNP markers were polymorphic in population 1 and 290 SNP markers in population 2.
Genetic linkage mapping
Out of 768 SNP markers, 297 SNP markers in population 1 and 290 SNP markers in population 2 were segregating in a Mendelian fashion and linkage map was constructed using these markers employing ICIM software V3.1. Linkage groups were formed at threshold logarithm of odd (LOD) 2.5 and maximum recombination fraction of 0.30. A total of 297 SNP markers polymorphic for Population 1 were mapped on 10 linkage groups (LGs) spanning a total length of 3623.88 cM (Table 3). The linkage groups LG7 and LG9 consisted of least number of markers (16) and LG5 had maximum number of markers (45). The length of linkage group LG10 was minimum (210.12 cM) and it was maximum in LG5 (531.03 cM) with an average interval distance of 12.20 cM indicating comparatively high-density linkage map. The linkage map for the population 2 consisted of 290 polymorphic SNP markers which spanned 4261.92 cM. Minimum number of markers were mapped in the linkage group LG9 (15 markers) and it was maximum in LG1 (51 markers). The length of linkage groups ranged from 205.1cM (LG9) to 749.04 cM (LG1) with an average inter marker distance of 14.69 cM. The arrangement of markers was comparable with the consensus map constructed for maize. Linkage maps constructed on F2:3 mapping populations were used for identification and mapping of QTLs conferring resistance to NCLB disease.
Table 3
QTLs detected for NCLB at individual location and combined across locations using 366 F2:3 families (Threshold LOD Score = 2.50)
Location
|
Chromosome/ Bin
|
Flanking markers
|
Position (cM)
|
Maximum LOD Score
|
R2 (%)
|
Genetic effect
|
Gene action
|
Donor allele
|
Left
|
Right
|
Additive
|
Dominance
|
CM 212 x MAI 172
|
Hassan
|
3.14
|
pza01791-2
|
pza00309-1
|
276
|
6.68
|
29.94
|
0.91
|
-0.65
|
PD
|
MAI172
|
6.11
|
PZA00382-17
|
PHM4503-25
|
201
|
2.58
|
8.44
|
1.47
|
-1.44
|
D
|
MAI172
|
7.03
|
PHM2691-31
|
PZA00132-17
|
47
|
3.53
|
30.14
|
0.78
|
-1.32
|
OD
|
MAI172
|
8.04
|
PZA02955.3
|
PHM9695-8
|
63
|
2.71
|
8.84
|
0.10
|
0.70
|
OD
|
MAI172
|
9.01
|
PZA01866.1
|
PZA00213-19
|
3
|
3.08
|
3.92
|
0.25
|
-0.11
|
PD
|
MAI172
|
10.09
|
PZA00130.9
|
PZA00007.1
|
169
|
4.46
|
16.09
|
0.06
|
1.78
|
OD
|
MAI172
|
Mandya
|
3.04
|
PZA02090-1
|
PZA01765.1
|
73
|
2.68
|
5.34
|
0.23
|
-0.11
|
PD
|
MAI172
|
4.10
|
PHM9635-30
|
PZA01187-1
|
193
|
2.67
|
3.24
|
-0.13
|
0.27
|
OD
|
CM212
|
8.04
|
PZA02955.3
|
PHM9695-8
|
65
|
2.58
|
5.88
|
0.21
|
-0.13
|
PD
|
MAI172
|
Davanagere
|
4.09
|
PZA00125.2
|
PHM3112-5
|
163
|
3.06
|
3.66
|
0.11
|
-0.62
|
OD
|
MAI172
|
6.03
|
PHM8327-18
|
PZA00540.3
|
48
|
2.52
|
6.32
|
-0.36
|
-0.01
|
A
|
CM212
|
6.11
|
PZA01468.1
|
pza03577-1
|
214
|
3.79
|
4.53
|
0.13
|
0.59
|
OD
|
MAI172
|
Across locations
|
1.01
|
PHM2130-29
|
PZA00447.6
|
10
|
2.64
|
3.63
|
0.04
|
0.54
|
OD
|
MAI172
|
6.03
|
PHM8327-18
|
PZA00540.3
|
48
|
4.86
|
11.08
|
-0.40
|
0.11
|
PD
|
CM212
|
6.01
|
PZA01527.1
|
PZA03090-31
|
11
|
2.98
|
3.69
|
0.51
|
-0.15
|
PD
|
MAI172
|
CM 202 x SKV 50
|
Hassan
|
5.12
|
PZA00472-2
|
PZA02862.10
|
240
|
4.30
|
14.45
|
0.23
|
-0.80
|
OD
|
SKV-50
|
8.05
|
PHM4968-10
|
PHM7898-10
|
86
|
2.55
|
27.37
|
0.13
|
1.86
|
OD
|
SKV-50
|
10.07
|
PHM11946-17
|
PHM4905-6
|
131
|
3.23
|
15.88
|
0.11
|
1.94
|
OD
|
SKV-50
|
Mandya
|
9.10
|
PHM14104-23
|
PHM2749-10
|
199
|
2.62
|
4.73
|
-0.20
|
0.01
|
A
|
CM202
|
Davanagere
|
4.07
|
PHM9635-30
|
PHM15427-11
|
138
|
3.84
|
4.08
|
0.10
|
-0.80
|
OD
|
SKV-50
|
5.25
|
PHM1506-23
|
PHM3512-186
|
492
|
4.53
|
5.61
|
-0.31
|
0.23
|
PD
|
CM202
|
10.03
|
PHM11226-13
|
PHM1576-25
|
51
|
3.25
|
3.52
|
0.23
|
0.17
|
PD
|
SKV-50
|
Across locations
|
3.12
|
PZA00827.1
|
PZA00817-2
|
232
|
2.86
|
6.55
|
-0.24
|
0.19
|
D
|
CM202
|
8.15
|
PHM765-24
|
PHM3337-23
|
286
|
5.15
|
10.85
|
0.07
|
0.73
|
OD
|
SKV-50
|
Nearest markers: Position of QTL peak as indicated by left and right flanking marker; |
Position: Position of QTL peak as indicated by cumulative distance from the end of the short arm; |
Max LOD: Likelihood of odds (LOD) scores = Likelihood ratios (LR)/4.6052. Critical thresholds of QTL were defined at LOD 2.5; |
R2: Percentage of the phenotypic variance explained by genotype at Max LOD peak; Genetic effect: additive and dominance effect at QTL peak, Gene action was established by |d|/|a|: A (additive): 0 to 0.20, PD (partial dominance): 0.21 to 0.80, D (dominance): 0.81 to 1.20, and OD (over dominance) > 1.20; |
Donor NCLBR allele detected by +/- of additive with reference to MAI 172. Positive values showed resistance alleles came from MAI172, negative values showed resistance alleles came from CM212. |
QTL analysis
The QTLs were detected using the disease incidence data from three locations during rainy season of 2014 and pooled across locations.
In population 1, six QTL positions were identified for NCLB resistance at Hassan location (Table 3, Fig. 3). The QTLs on chromosome 7, 3, 10, 8 and 6 were major which explained 30.14, 22.94, 16.09, 8.84 and 8.44 % phenotypic variance whereas, QTL on chromosome 9 was minor with 3.92 % phenotypic variance. The favorable alleles for these QTLs were contributed by the resistant parent MAI 172. Three QTLs were detected on chromosome 3, 4 and 8 at Mandya which explained 5.34, 3.24, and 5.88 % phenotypic variation. Out of three QTLs found at Davanagere, the QTL located on chromosome 4 explained 3.66 % phenotypic variation and the other two QTLs were located on chromosome 6 which explained 6.32 and 4.53 % phenotypic variation, respectively. In combined QTL analysis three QTLs were identified with the QTL located on chromosome 1 explained 3.63 % phenotypic variation. The remaining QTL were located on chromosome 6 explaining 11.08 and 3.69 % phenotypic variation.
In population 2, three QTL positions were identified at Hassan (Table 3, Fig. 4) and the QTL located on chromosome 8 was the major with phenotypic variation of 27.37 % followed by the second major QTL located on chromosome 5 with 14.45 % phenotypic variation. The third major QTL located on chromosome 10 explained 15.58 % phenotypic variation. Only one QTL position was identified at Mandya on chromosome 9 which explained 4.73 % phenotypic variation. The favorable allele for this QTL was contributed by susceptible parent CM 202 which showed additive gene action. The First QTL located on chromosome 4 explained 4.08 % phenotypic variation with LOD of 3.84 at Davanagere. The second and third QTL located on chromosome 5 and 10 exhibited 5.61 and 3.52 % phenotypic variation. In combined QTL analysis, two QTL positions were identified for NCLB resistance with the QTL located on chromosome 3 explained 6.55 % phenotypic variation. The second QTL located on chromosome 8 explained 10.85 % phenotypic variation.
Genomic selection
Best linear unbiased predictors (BLUPs)
The genotypic data of 297 polymorphic SNPs of the Population 1 and 290 polymorphic markers of Population 2 were used to estimate the marker effects of each SNP using the RR-BLUP procedure. The marker effects estimated for Population 1 ranged from − 0.0866 to 0.0857 and from − 0.0101 to 0.0105 for Population 2 (Supplementary Table S1). The estimated effects were included in the model to predict the genomic estimated breeding values (GEBVs) of each individual (Supplementary Table S2).
Prediction accuracy and cross validation
The entire 366 F2:3 progenies from population 1 were cross validated 100 times in two different ratios of validation set and training set. The first case was with two-fold cross validation, where in each time validation set and training sets were randomly selected equally as 1:1. In this case the prediction accuracy of the GEBVs was 24% (Table 4). The second case was with five-fold cross validation, where the population was divided into five equal parts, where four sets were used as training set against one validation set. In this case the prediction accuracy of the GEBVs was 26%. The same kind of cross validation was done for Population 2 where GEBV prediction accuracies were 29% and 32% for the validation ratios of 1:1 and 1:5, respectively (Table 4, Figs. 5 and 6). The prediction accuracy measured in terms of correlation between the BLUEs and GEBVs was found positive (Table 5). The Population 1 had a correlation of 0.79 and for the Population 2 it was 0.83. However, when predictions were made using top 10 per centselections correlation between GEBVs and their BLUEs was reduced to 0.35 in Population 1 and 0.50 in Population 2.
Table 4
Prediction accuracies of QTL mapping and Genomic selection for F2:3 families derived from crosses CM 212 x MAI 172 and CM 202 x SKV 50
Location
|
CM 212 x MAI 172
|
CM 202 x SKV 50
|
Total Variance (%) explained by additive QTLs
|
GS Accuracy (%)
|
Total Variance (%) explained by additive QTLs
|
GS Accuracy (%)
|
PVE
|
GVE
|
Heritability
|
Two-fold cross validation
|
Five-fold cross validation
|
PVE
|
GVE
|
Heritability
|
Two-fold cross validation
|
Five-fold cross validation
|
Davanagere
|
6.56
|
10.25
|
0.97
|
-
|
-
|
18.95
|
37.16
|
0.98
|
-
|
-
|
Hassan
|
4.65
|
7.27
|
0.82
|
-
|
-
|
2.82
|
5.52
|
0.82
|
-
|
-
|
Mandya
|
3.23
|
5.05
|
0.45
|
-
|
-
|
2.87
|
5.63
|
0.47
|
-
|
-
|
Across location
|
6.34
|
9.90
|
0.64
|
24.0
|
26.0
|
4.66
|
9.13
|
0.51
|
29.0
|
32.0
|
PVE: Phenotypic Variance Explained; GVE: Genotypic Variance Explained |
Table 5 Correlation between BLUEs and GEBVs estimated for NCLB incidence for all the individuals from Population 1 (CM 212 x MAI 172) and Population 2 (CM 202 x SKV 50) (A- All the individuals and B- 10 % individuals selected based on GEBVs)
A.
|
Population 1
|
Population 2
|
BLUEs
|
GEBVs
|
BLUEs
|
GEBVs
|
BLUEs
|
1
|
-
|
1
|
-
|
GEBVs
|
0.79
|
1
|
0.83
|
1
|
B.
|
Population 1
|
Population 2
|
BLUEs
|
GEBV
|
BLUEs
|
GEBVs
|
BLUEs
|
1
|
-
|
1
|
-
|
GEBVs
|
0.35
|
1
|
0.50
|
1
|
Analysis of variance of combining ability of inbreds developed from NCLB resistant F 3 progenies
The analysis of variance for combining ability with respect to 12 quantitative traits indicated that the crosses exhibited high level of significance for all the traits (Table 6). The variance due to crosses was further divided into variance due to lines, testers and line × testers. The variance due to lines was significant for ear height, kernel rows per cob and kernel per rows whereas, variance due to testers was significant for days to 50 per cent anthesis, days to 75 per cent dry husk, plant height, ear height, kernel rows per cob, test weight and plot yield. The line × tester interaction variance was highly significant for all the traits. The GCA/SCA variance ratio was less than unity.
Table 6
Analysis of variance for combining ability in maize
Source of variation
|
DF
|
Days to 50% Anthesis
|
Days to 50% silking
|
Days to 75% husk
|
Plant height (cm)
|
Ear height (cm)
|
Cob length (cm)
|
Replication
|
1
|
0.83
|
6.62
|
2.76
|
12.22
|
6.89
|
1.40
|
Crosses
|
135
|
21.04 **
|
21.83 ***
|
28.11**
|
948.83**
|
489.28 **
|
7.59**
|
Line Effect
|
33
|
27.55
|
28.97
|
32.94
|
820.78
|
607.21 *
|
8.30
|
Tester Effect
|
3
|
7.31
|
7.51
|
181.68***
|
8949.92***
|
2906.91 ***
|
6.88
|
Line × Tester Effect
|
99
|
19.29 **
|
19.89 **
|
21.84**
|
749.06**
|
376.71 **
|
7.37 **
|
Error
|
173
|
3.47
|
3.59
|
0.81
|
22.43
|
9.97
|
1.03
|
Total
|
347
|
11.66
|
12.16
|
14.05
|
466.23
|
242.10
|
4.02
|
Source of variation
|
DF
|
Ear circumference (cm)
|
Kernel rows per cob
|
Kernels per row
|
Test weight (g)
|
Shelling %
|
Plot yield (Kg)
|
Replication
|
1.00
|
0.61
|
0.004
|
7.01
|
0.22
|
1.31
|
0.004
|
Crosses
|
135
|
2.20 **
|
4.44**
|
64.58 **
|
25.33**
|
35.94 **
|
0.50 **
|
Line Effect
|
33
|
2.35
|
7.29 **
|
107.64**
|
24.92
|
44.02
|
0.52
|
Tester Effect
|
3.00
|
5.19
|
11.01 *
|
10.95
|
164.59**
|
15.01
|
2.43 **
|
Line × Tester Effect
|
99
|
2.06 **
|
3.30 **
|
51.84 **
|
21.24**
|
33.88 **
|
0.44 **
|
Error
|
173
|
0.52
|
0.56
|
6.46
|
0.09
|
3.86
|
0.005
|
Total
|
347
|
1.29
|
2.31
|
30.87
|
12.72
|
18.83
|
0.24
|
* Significant at P = 0.05, ** Significant at P = 0.01 |
Identification of inbreds showing high general combining ability effects, crosses with high specific combining ability and heterosis
Out of 34 lines 17 showed significant gca effects for grain yield (Supplementary Table S3) and 21 lines (61%) were assigned high (H) overall gca status (Supplementary Table S4). The line MAI-E2-70 was the best overall general combiner followed by MAI-E9-183 and MAI-E9-39. The testers NAI137 and V351 were the best overall general combiners. High (H) overall sca status was exhibited by 65 out of 136 hybrids. The cross MAI-E2-155 x MAI105 (L x L) was the best cross followed by MAI-E2-179 x V351 (L x H) and MAI-E2-72 x MAI105 (H x L) (Supplementary Table S5). Among 136 single crosses, 50 had high (H) overall heterotic status of which MAI-E9-46 × MAI105 manifested best overall heterotic status followed by MAI-E9-178 x MAI105 and MAI-E9-46 x NAI137 (Supplementary Table S6).
The best single cross hybrids based on mean, sca effects and standard heterosis for grain yield were MAI-E2-72 x MAI105, MAI-E9-46 x NAI137, MAI-E2-70 x NAI137, MAI-E2-81 x V351, MAI-E9-220 x V351, MAI-E9-211 x NAI137, and CIL1218 x V351 compared to the best commercial check DKC9144 (Table 7).
Table 7
Best single cross hybrids based on mean, SCA effects and standard heterosis for grain yield
Hybrid
|
Mean
|
SCA effect
|
Standard Heterosis
|
Type of cross
|
CIL1218 x V351
|
3.165**
|
1.131 ***
|
22.75 **
|
L x H
|
MAI-E2-72 x MAI105
|
3.014 **
|
1.156 ***
|
16.89 **
|
H x L
|
MAI-E9-211 x NAI137
|
2.941 **
|
0.842 ***
|
14.08 **
|
H x H
|
MAI-E2-70 x NAI137
|
2.931 **
|
0.587 ***
|
13.67 **
|
H x H
|
MAI-E2-81 x V351
|
2.843 **
|
0.552 ***
|
10.26 **
|
H x H
|
MAI-E9-46 x NAI137
|
2.632 **
|
0.371 ***
|
2.06
|
H x H
|
MAI-E9-220 x V351
|
2.610**
|
0.450 ***
|
1.22
|
H x H
|
* Significant at p = 0.05, ** Significant at p = 0.01 and *** Significant at p = 0.001 |
Molecular diversity analysis in the resistant inbreds developed
The diversity was assessed in the 45 inbreds and most of the inbred lines could be discriminated with SSR markers. Out of 64 SSR markers tested 35 were found to be polymorphic for the genotypes studied (Supplementary Table S7). The PIC (polymorphism information content) value ranged from 0.11 (bnlg1327) to 0.85 (umc1951) with mean value of 0.45. Allelic frequency was in the range of 0.52 to 0.93. Markers umc1139, mmc0111 and umc2269 (0.93) showed high allelic frequency, followed by umc1080 (0.90) and least was seen in case of bnlg1449 (0.52). Gene diversity was in the range of 0.24 (bnlg1942) to 0.50 (umc1139, bnlg1063, umc1085 and bnlg1887) with mean value 0.46.
Clustering of inbreds based on SSR marker data
The UPGMA based dendrogram was obtained from the data deduced from the DNA profiles of the samples analysed (Fig. 7). Forty-five maize inbreds were clustered by Jaccard’s similarity coefficients which ranged from 0.17 to 0.81 per cent and at similarity coefficient of 0.41, four main groups were observed. The Cluster CI consisted of 21 inbred lines, followed by cluster CII (16), cluster CIII (6) and CIV was with least number of inbred lines (2).