Published online 27 May 2005
Published in Crop Sci 45:1256-1263 (2005)
© 2005 Crop Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
CROP BREEDING, GENETICS & CYTOLOGY
Analyses of Acid-PAGE Gliadin Pattern of Indian Wheats (Triticum aestivum L.) Representing Different Environments and Periods
Sewa Ram*,
Nisha Jain,
Vinamrata Dawar,
R. P. Singh and
Jag Shoran
Directorate of Wheat Research, Karnal- 132001, India
* Corresponding author (sewaram01{at}yahoo.com)
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ABSTRACT
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Acid-PAGE analysis of gliadins from 159 Indian wheat (Triticum aestivum L.) cultivars developed during the last five decades was accomplished to identify gliadin band patterns as well as the extent of genetic diversity. Extensive polymorphism [genetic diversity index (H) = 0.875] in gliadin pattern was observed in the cultivars studied. A total of 147 band patterns were identified, of which 45 different mobility bands were in the region of 
gliadins, 42 in the region of 
gliadins, 30 in the region of ß, and 29 in the region of 
gliadins. Zone-wise genetic diversity index was highest in North Western Plains Zone (H = 0.904) followed by North Eastern Plains Zone (H = 0.878), Central Zone (H = 0.864), Peninsular Zone (H = 0.844), and Northern Hills Zone (H = 0.836). The gliadin pattern 1, 8, 11, and 20; ß gliadin pattern 21; gliadin pattern 15 and 20; and gliadin pattern 4, 18, and 38 were specific to cultivars of Northern Zones and gliadin 20 and ß gliadin 22 to Central and Peninsular Zones. Period-wise highest mean genetic diversity (H = 0.915) was observed in cultivars identified during 1971 through 1980 and lowest (H = 0.868) in cultivars developed after 1990. The reduction in genetic diversity during 1990 onward might be because of enhanced use of 1BL.1RS translocation. This information can be used in breeding programs to maintain genetic diversity within Indian wheat germplasm.
Abbreviations: CIMMYT, International Maize and Wheat Improvement Center • CZ, Central Zone • H, genetic diversity index • NEPZ, North Eastern Plains Zone • NHZ, Northern Hills Zone • NWPZ, North Western Plains Zone • PAGE, polyacrylamide gel electrophoresis • PZ, Peninsular Zone • SHZ, Southern Hills Zone
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INTRODUCTION
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GLIADINS AND GLUTENINS constitute around 80% of the total seed proteins in wheat, of which 40% are gliadins. The quality and quantity of gluten proteins determine quality of large number of end products. Glutenins (acid soluble) are polymeric proteins whose monomeric units are divided into high (HMW) and low (LMW) molecular weight glutenin subunits. Gliadins (alcohol soluble) are monomeric proteins and are divided into , ß, , and on the basis of their mobility in acid-PAGE. Most gliadin alleles reside at six main loci on the chromosomes of the first (gli-1) and sixth (gli-2) homoeological groups (Payne, 1987). There are also some minor loci as Gli-3, Gli-5, and Gli-6 that control few minor gliadin bands (Pogna et al., 1993; Metakovsky et al., 1997). Two new gliadin alleles Gli-D4 and Gli-D5 have also been reported on the short arm of chromosome 1D (Rodriguez and Carrillo, 1996). Several workers (Zillman and Bushuk, 1979; Metakovsky, 1991; D'Ovidio et al., 1992; Branlard et al., 1993) reported high degree of variability in gliadin patterns. Combination of different alleles of gliadins makes it possible to distinguish wheat genotypes. In addition, significant positive effects of certain gliadin alleles have been reported on gluten strength (Weegels et al., 1996; Metakovsky et al., 1997), agronomic traits, and environmental adaptation (Metakovsky and Branlard, 1998).
Because of their importance, the genetic polymorphism of gliadins has been used to evaluate genetic diversity within several germplasms in Australia (Metakovsky et al., 1990), Yugoslavia (Metakovsky et al., 1991), Italy (Metakovsky et al., 1994), France (Metakovsky and Branlard, 1998), Spain (Metakovsky et al., 2000) and Japan (Tanaka et al., 2003). Though HMW glutenin subunit composition of Indian wheats and their relationship with dough strength have been described (Sreeramulu and Singh, 1994; Sewa Ram, 2003), the diversity of gliadins in Indian wheat cultivars has not been reported so far. Indian wheat genotypes have not been classified by efficient genetic markers and there was never any selection by breeders on the basis of gliadin patterns. In the present investigation, gliadin patterns of 159 wheat cultivars identified and released in India during last 50 yr have been determined and genetic diversity evaluated. Specific gliadin patterns corresponding to different zones and years of release were also identified.
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MATERIALS AND METHODS
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One hundred fifty-nine wheat cultivars identified and released in India during the last five decades were evaluated for gliadin banding pattern. All the cultivars were procured from the genetic resource unit of the Directorate of Wheat Research, Karnal, India. Gliadins were separated by the Acid-PAGE method of Metakovsky and Novoselskaya (1991) with minor modifications. Gliadins were extracted with 70% (v/v) ethanol from single seeds. Acid (aluminium lactate, pH 3.0) polyacrylamide gel electrophoresis was done with ATTO-MAKE (ATTO CORPORATION, Tokyo, Japan) vertical apparatus. The gel was run at 150 V for 20 min and subsequently 350 V until the end of the electrophoresis. Chinese spring (CS) and Marquis (M) were used as standards for identification of gliadin patterns. Chinese Spring was found to have two biotypes, but the biotype used in the present investigation had the banding pattern reported by Metakovsky (1991). It was not possible to classify gliadin pattern of Indian wheats in accordance with the method of Metakovsky et al. (1991) because there was no variety having a and gliadins pattern similar to Chinese Spring or Marquis. A different strategy was used to identify gliadin pattern within each gliadin groups of , ß, , and by comparing banding pattern of each cultivar with all other cultivars and assigned specific number to each of the pattern. The first cultivar was given pattern number 1 and subsequently compared with band pattern of all other varieties. Cultivars with similar band pattern were grouped together. This was followed by determination of next pattern different from the previous one(s) and identification of varieties with similar band pattern by comparing with it. The strategy was followed for all the cultivars and large numbers of different patterns were identified in each group of gliadins (, ß, , and ). The exercise was repeated many a times to confirm the pattern of varieties within each group. Since Chinese Spring and Marquis were used as checks in each gel, comparison of band pattern among different varieties was easy. Homogeneity of each genotype was determined by extracting gliadins from five individual seeds from each sample. Recently, similar approach has been used in the analyses of gliadins of Japanese wheats (Tanaka et al., 2003) except that they grouped ß and gliadins together.
The genetic diversity for each gliadin pattern was calculated as per Nei (1973) as H = 1– 
pi2, where H is the genetic variation index and pi is the proportion of a particular pattern in each group of , ß, , and gliadins separately. Mean value of H was calculated for all the four groups of gliadins. Pair-wise comparisons of frequencies of gliadin patterns in different zones were performed with standard Fisher's test by calculating a z value that was tested against the desired level of significance. Dendrogram representing genetic relationships among cultivars of different zones were constructed on the basis of Ddm distances by the Neighbor-joining algorithm. The genetic distance (Ddm) was computed with the microsat software (version 1.5) developed by Erich Minch, available at http://hpgl.stanford.edu/projects/microsat/programs/; verified 4 February 2005.
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RESULTS
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Spring wheat cultivars grown in different parts of the country, ranging from northern hills in the Himalayas to the peninsular part in the southern region and from Gujarat in the west to Assam in the north east, were analyzed for gliadin band pattern. Gliadins were separated into , ß, , and groups according to their mobility in acid-PAGE (Fig. 1)
. The results showed large variation in gliadin pattern encoded by six main coding loci. Five individual seeds were used from each cultivar to observe heterogeneity. Seven cultivars (namely GW322, HW2045, HI977, HUW468, RAJ3765, Lok1, and NW1014) showed heterogeneity differing in gliadin patterns and all others were homogeneous (Table 1). The patterns within each gliadin group of , ß, , and were identified by comparing banding pattern of each variety with all the other varieties and assigned specific number to each of the pattern as per the modified method of Tanaka et al. (2003). The zone-wise list of cultivars along with their pedigrees and gliadin band patterns are shown in the Table 1. The pedigree information was taken from published reports (Jain, 1994; Bisht et al., 2003). One hundred forty-seven different gliadin patterns were identified, of which 45 different mobility bands were in the region of gliadins, 43 in the region of gliadins, 30 in the region of ß, and 29 in the region of gliadins. Ideograms of all the different patterns observed are presented in Fig. 2
. The most frequent patterns were 1, 2, 7, 16, and 17 in gliadins; 1, 16, 21, and 23 in ß gliadins; 4, 5, 13, 15, 20, and 27 in gliadins, and 1, 2, 3, 4, 14, 18, 24, and 38 in the region of gliadins (Table 1). The ideogram showed larger variation in and gliadins than in and ß gliadins. This may be either due to greater staining intensity of and ß gliadins, and separation of these proteins may not be complete in a 1-D electrophoresis system. Although enough care was taken to get all the bands separated, more than one protein may be present in a band in the region.
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Fig. 1. Acid-PAGE gliadin electrophoregram of Indian wheat cultivars. The places of , ß, and gliadins along with a group of secalin bands in 1BL.1RS translocation lines are indicated. 1 = PBW65, 2 = PBW138, 3 = PBW 154, 4 = PBW175, 5 = PBW222, CS = Chinese Spring, M = Marquis, 6 = PBW226, 7 = PBW299, 8 = PBW343, 9 = PBW373, and 10 = PBW396.
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Since and ß gliadins are controlled by genes present on six homoeological groups and and gliadins on 1 homoeological groups, there may be less polymorphism in gliadins synthesized by the six homoeological groups, though it should be verified by genetic studies. Tanaka et al. (2003) also reported larger variation in gliadins than and ß gliadins in Japanese cultivars. Gliadin pattern 5 and gliadin pattern 4 (having secalin bands of 1BL.1RS translocation, Fig. 1) were present in 33% of the cultivars released after 1990. The gliadin pattern 5 was present along with 1BL.1RS translocation in most of the cultivars. The data indicate that the enormous degree of gliadin polymorphism makes gliadin patterns much more suitable than HMW glutenins to distinguish wheat genotype. Our earlier results demonstrated the presence of only 23 HMW glutenin genotypes among 148 wheat cultivars (Sewa Ram, 2003).
The genetic diversity (Nei's index) based on gliadin pattern observed in Indian wheats was higher (H = 0.870) than in other countries: Spain (H = 0.844; Metakovsky et al., 2000), France (H = 0.714; Metakovsky and Branlard, 1998), England, Italy, and the former Yugoslavia (H = 0.676, H = 0.754, and H = 0.728, respectively, Metakovsky et al., 1994). There were variations in the genetic diversity of gliadin patterns of cultivars grown in different zones in India. The genetic diversity index was highest in North Western Plains Zone (H = 0.904) followed by North Eastern Plains Zone (H = 0.878), Central Zone (H = 0.864), Peninsular Zone (H = 0.844), and North Hills Zone (H = 0.836) (Table 2). The highest genetic diversity in NWPZ may be because of the large numbers of breeding centers involved in the development of cultivars and also because of the diverse sources used in those crossing program. Moreover, there is comparatively large variation of environmental conditions in NWPZ varying from colder in Punjab to warmer in Rajasthan.
There were many patterns specific to each zone and some were common among all the zones. The gliadin pattern 7, 16, and 17 and ß gliadin pattern 1, 2, and 3 were present in all the zones. The gliadin pattern 1, 8, 11, and 20; the ß gliadin pattern 21; the gliadin pattern 15 and 20, and the gliadin pattern 4, 18, and 38 were specific to cultivars of Northern Zones and gliadin pattern 20 and ß gliadin pattern 22 were specific to the Central and Peninsular Zones. Fisher's test analysis (z-test) indicated that gliadin 11 and gliadin 4 and 18 patterns were significantly higher in Northern Zones and gliadin 22 pattern was significantly higher in CZ and PZ (Table 3). Difference between groups of cultivars might be caused by breeder's preference as well as hidden natural selection specific for each location.
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DISCUSSION
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Gliadins have been used by several workers around the world for genetic diversity studies in wheat, and large numbers of patterns have been reported. The data in this investigation showed higher genetic variability in Indian wheats as compared with earlier reports from different parts in the world. The divergence may be because of different types of parents used and selection pressure exerted because of diverse climatic conditions prevailing in different zones. For example, cold conditions in northern region during winter and comparatively warm and dry condition in Central and Peninsular zones with the progressive reduction of maturity period from 180 d in NHZ to 100 d in PZ. Disease spectrum also varies from one zone to another. Multinational collaborations (specially CIMMYT) also contributed in expanding the genetic base of Indian wheats by providing materials with diverse genetic sources suited for different environments. Analyses of genetic distances among groups of cultivars released in different zones in India showed that cultivars representing CZ and NEPZ were closer to each other than to cultivars from other zones (Fig. 3)
. Cultivars from NHZ exhibited the largest genetic distance from cultivars grown in other zones. Similar relationships were observed when Nei's genetic distance matrix was used except that cultivars from PZ showed a closer relationship to cultivars from NWPZ. Different gliadins might have some advantage over other gliadins in adaptation to the conditions prevailing in these zones or these are closely linked with genes having adaptive value to the specific environment, though that needs to be confirmed by genetic analysis. The gliadin pattern 4 (1BL.1RS translocation having secalin bands as shown in Fig. 1) was present predominantly in the cultivars released for cultivation in NHZ, NWPZ, and NEPZ. In addition, gliadin patterns 1, 2, 18, and 38 were predominantly present in cultivars developed for rain-fed conditions. Thus, data exhibit the association of genotypes to environmental factors as has also been reported by Nevo et al. (1988)(1995). However, recently Dreisigacker et al. (2004) reported no significant differences among wheat lines from CIMMYT (based on SSR and pedigree analyses) targeted to different megaenvironments representing different parts in the world.
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Fig. 3. Dendrogram based on Dad distances among cultivars grown in different zones in India (NWPZ = North Western Plains Zone, NEPZ = North Eastern Plains Zone, CZ = Central zone, PZ = Peninsular Zone, and NHZ = Northern Hill Zone).
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Analysis of gliadin pattern of cultivars developed in different years showed that many new gliadin patterns appeared and some lost while few were retained. For example, gliadin patterns 1, 2, 18, and 38 were present in cultivars representing all the periods. Thus, new sources were utilized in the breeding program during the subsequent years of release. It implies that old cultivars should be preserved because these may contain unique genes and gene combinations that are absent from recent cultivars. There was little reduction in genetic diversity in cultivars released after 1990. Period-wise highest mean genetic diversity (H = 0.915) was observed in cultivars released from 1971 through 1980 and lowest (H = 0.868) in cultivars released after 1990 (Table 2). The higher genetic diversity identified in cultivars released from 1971 through 1980 might be due to the fact that many active wheat breeding centers were initiated in India representing different areas, and large numbers of diverse crosses were made. All India Co-ordinated Wheat Improvement Program was started in 1965 for multilocational testing of entries otherwise it was region specific program. Some reduction in genetic diversity in cultivars released after 1990 may be due to the enhanced use of 1BL.1RS translocation during that period. This is exhibited by the occurrence of 1BL.1RS translocation more frequently (50%) in cultivars released after 1990.
Over the past two decades, wheat breeders in India used the short arm of rye chromosome 1R as source of genes for disease and pest resistance and improved agronomic performance. However, reduced gluten strength and loaf volume and increased dough stickiness have been found associated with 1BL.1RS translocation (Dhaliwal et al., 1988; Lee et al., 1995). The negative effects on dough properties may be due to presence of secalins coded by 1RS of rye (Dhaliwal et al., 1988) or loss of wheat prolamins codified by genes of the 1BS arm (Payne et al., 1987). However, the negative effect of 1BL.1RS on dough properties can be minimized by incorporating specific combinations of prolamin genes (Martin and Carrillo, 1999). Zone-wise analysis of the data indicated the prevalence of 1BL.1RS translocation in cultivars representing Northern Hills, North Western, and North Eastern plains where intense cold conditions prevail during winter period, as compared with CZ where warm and dry conditions exist. Earlier studies also showed the presence of genes showing resistance to cold conditions in 1BL.1RS translocation lines. Metakovsky and Branlard (1998) reported similar results in a study of French cultivars where 1BL.1RS translocation lines were prevalent in Northern part of the country. In contrast, cultivars with allele Gli-D2m were, on an average, earlier, cold sensitive, and grown in South of France. It is plausible to suggest that chromosomal segments marked by these alleles may be involved in multilocus combinations affecting the degree of plant adaptation to local environment (Allard, 1996).
The presence of large number of different mobility bands in the gene pool surveyed indicated that extensive genetic introgressions contributed to the genetic base. During the last four decades, the introduction of large numbers of diversified germplasm from CIMMYT including Mexican semidwarf genes during the 1960s and 1BL.1RS translocation during the 1990s in the breeding program led to the generation of high yielding varieties adapted to the Indian conditions. Different combinations of gliadin patterns were prevalent in different zones suggesting the adaptive properties of individual alleles or the chromosome segments in which these alleles reside (Nevo et al., 1995; Metakovsky and Branlard, 1998). The alternative hypothesis may be that the more common pattern in specific geographic regions might reflect descent from common, often-used parents, and might not indicate fixation by natural selection. The data thus exhibited that gliadins can be used in the identification of varieties as well as powerful tool for the evaluation of wheat genetic resources. Moreover, association of gliadin pattern with specific traits such as disease resistance, quality, or adaptation to abiotic stress can be identified. Therefore, protein electrophoresis of gliadins and other highly polymorphic storage proteins along with DNA-based markers inside the coding sequences of storage proteins (Devos et al., 1995; Pagnotta et al., 1995) as well as microsatellite and AFLP markers representing entire genome (Manifesto et al., 2001) can be used for precise germplasm identification and their utilization. This information can be valuable source in addressing breeding issues for exploiting genetic variability in developing successful combinations of gliadins.
In conclusion, the present investigation demonstrates the extensive polymorphism in gliadin pattern of Indian wheats (H = 0.870). All cultivars except a few could be distinguished by the Acid-PAGE analysis of gliadins. Zone-wise genetic diversity index was highest in North Western Plains Zone (H = 0.904) and lowest in Northern Hills Zone (H = 0.836). Some of the patterns were present predominantly in specific zones showing some advantage over other gliadins in adaptation to the conditions prevailing in these zones or these are closely linked with genes having adaptive value to the specific environment. Period-wise highest mean genetic diversity (H = 0.915) was observed in cultivars released from 1971 through 1980 and lowest (H = 0.868) in cultivars developed after 1990. This information can be used in breeding programs to maintain genetic diversity within Indian wheat germplasm.
Received for publication May 31, 2004.
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ABSTRACT
INTRODUCTION
