Research Article

Allelic Distribution of Puroindoline Genes Affecting the Grain Hardness in Some Iranian Bread Wheat Cultivars  

Ali Izanloo , Sanaz Norouzdokht-Nokhandan , Mohammad Mohammad , Mohammad -Ghader
Department of Agronomy and Plant Breeding, Faculty of Agriculture, University of Birjand, Shouth Khorassan, Birjand, Iran
Author    Correspondence author
Molecular Plant Breeding, 2016, Vol. 7, No. 5   doi: 10.5376/mpb.2016.07.0005
Received: 17 Nov., 2015    Accepted: 01 Jan., 2016    Published: 03 Jan., 2016
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This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Preferred citation for this article:

Ali Izanloo, Sanaz Norouzdokht-Nokhandan, Mohammad Zabet, and Mohammad-Ghader Ghaderi, 2016, Allelic Distribution of Puroindoline Genes Affecting The Grain Hardness in Some Iranian Bread Wheat Cultivars, Molecular Plant Breeding, 7(05): 1-8 (doi: 10.5376/mpb.2016.07.0005)


Grain hardness is an important characteristics influencing end-use quality of bread wheat. Wheat with the hard grain texture has higher protein content and more intensive gluten that leads to production of higher bread quality. However, soft texture wheat has lower protein content and weaker gluten, which are suitable for cake and candy production. Grain hardness is determined by the Pina and Pinb genes that are located on the short arm of chromosome 5D. In this study, 83 bread wheat cultivars were characterized for the allelic distribution of Pina and Pinb genes using allele specific markers. At the Pina locus, Pina-D1a and Pina-D1b alleles were observed in 64% and 36% of varieties, respectively. However, at the Pinb locus, 90% of varieties showed Pinb-D1a and 10% had Pinb-D1b allele. Based on the grain hardness index which was measured with the NIR, varieties whit the value less than 50 were considered as soft while above 50 were considered as hard grain texture. The results of marker-trait association showed that Pina had the significant effect (P= 0.019) on the grain hardness, as cultivars with the Pina-D1a allele were significantly softer (49.85±0.37) that those with the Pina-D1b allele (51.38±0.50). The results of regression analysis showed that for the traits including bread volume, grain hardness and water absorption as dependent variables, Pina was entered to the model. The results of this study can help wheat breeders to effectively select parents for the grain hardness in the MAS breeding programs.

MAS; Grain hardness; Quality; Bread wheat

Physical characteristics of wheat grain, including grain weight, dimensions, shape, uniformity, density and texture, can affect the storage, transportation, milling and marketing of bread wheat. Grain hardness is an important quality characteristic of bread wheat that determines the end use properties and market classification of the grain. Wheat is classified into soft, medium soft, hard, medium hard and extra hard on the basis of grain hardness (reviewed in Pasha et al., 2012).
In soft wheat, the starch granules are loosely bound to the surrounding protein matrix, the soft grains are easy to mill and produce fine-textured flour with a high proportion of undamaged starch granules. In contrast, in the hard wheat there is a tight linkage between the starch granules and protein matrix, hard grains resist mechanical crushing and are more difficult to mill and more energy is needed during milling. Hence, flour with coarser texture is produced with higher proportion of damaged starch granules. Hard wheat is more suitable for yeast-leavened bread because of the higher water absorption of damaged starch, while soft wheat, which has low water absorption due to less protein and starch damage, is ideal for cookies, cakes and pastries(Lillemo et al., 2006; Morris and Rose, 1996).
Grain hardness is controlled by one major genetic factor, the hardness locus (Ha) on the short arm of chromosome 5D. The locus contains two genes Puroindoline a (Pina) and Puroindoline b (Pinb) within a region of about 82.0 bp (Chantret et al., 2005; Morris, 2002). The Pina and Pinb genes code for puroindoline a and puroindoline b proteins, respectively. These genes confer soft endosperm when they are both in their wild-type allelic states (Pina-D1a/Pinb-D1a). Hard wheat is the result of mutations in either Pina or Pinb (Morris, 2002). Both genes have various different alleles in hexaploid wheat. Highly conserved mutations in these two genes have been identified and named Pina-D1b and Pinb-D1b, the former being a null allele and the latter representing a glycine to serine mutation at position 46 in the puroindoline protein (Giroux and Morris, 1997; 1998). Several more alleles of Pina-D1 and Pinb-D1 have now been identified. Until recently, 17 Pina and 25 Pinb alleles have been reported in hexaploid wheat and related species (Chen et al., 2012; Morris and Bhave, 2008). Recent studies showed that all hardness mutations do not have equal effect of grain texture (Giroux et al., 2000; Martin et al., 2001). Data of allelic contribution of Pina and Pinb indicated that those hard wheats with null allele at Pina loci which lack puroindoline a protein (Pina-D1b /Pinb-D1a) were somewhat harder than those hard wheats that possess a normal soft puroindoline a but have an altered, mutant form of puroindoline b (Pina-D1a /Pinb-D1b) (Morris and Massa, 2003).
Knowledge on the allelic variability of Pina and Pinb genes in representative sets of bread wheat germplasm is of importance for their classification and it can help better explain the nature and different classes of grain hardness. It can also assist wheat breeders to precisely apply this information in a marker-assisted selection program. Therefore, the objective of this study was to characterize some Iranian wheat cultivars for the allelic distribution of puroindoline genes and to study their association with grain quality characteristics.
1 Results and Discussion
1.1 Grain quality related traits
The descriptive statistics for grain quality traits, measured with the NIR, showed that the average of grain protein content was 12.81% with the range of 11.5-14.0 in the studied wheat cultivars. The mean of hardness index of the grains was 50.41 with the variation range of 44.0-58.0. Zeleny number was obtained with an average of 35.09 and variation range of 32.0-40.0. Bread volume had the average of 498.4 with the variation range from 450 to 570 values. (Table 1). The phenotypic coefficient of variations for traits showed the existence of variations between the studied wheat cultivars, except for water absorption with 1.3%.Bivariate correlation analysis showed that grain hardness had a positive correlation with protein content (r = 0.59, p < 0.0001) and Zeleny number (r = 0.57, p < 0.0001) that is consistent with the reports of Grosse et al. (2004). According to these reports, significantly positive correlation was observed between grain protein content and grain hardness (Table 2). A significantly positive correlation was also observed between Zeleny number and protein content (r = 0.87, p < 0.0001), which was accordance with the results of Shevery and Tatham (2000), where grain protein content had a positive correlation with Zeleny number. It can be concluded that the harder grains had more water absorption. The correlation analysis of the studied traits showed that the water absorption had significantly positive correlation with protein content (r = 0.42, p < 0.0001), Zeleny number (r = 0.38, p < 0.001) and grain hardness (r = 0.23, p < 0.05).



Table 1 Mean, standard deviation, range and phenotypic coefficient of variations of grain quality related traits measured in the studied wheat cultivars.



Table 2 Bivariate correlation analysis for some quality related traits in wheat cultivars. Protein content (PROT), Zeleny Number (ZELL), Bread Volume (BV), Hardness Index (HI), Water Absorption (WA)


Hard texture wheat had higher protein and more intensive gluten and thus higher bread quality compared to soft texture wheat (Bushuk, 1998; Tipples et al., 1994). High protein content and hard grains would produce courser flour with more damaged starch, consequently lead to higher water absorption.

1.2 Pina and Pinb alleles
A set of co-dominant STS primers (Huang and Brûlé-Babel, 2011) for identification of the puroindoline a alleles, amplified two specific bands of 447 and 625 bp (Figure 1) for Pina-D1a and Pina-D1b alleles, respectively. In this study, Pina-D1a allele was observed in 64% of the cultivars (54), while Pina-D1b allele was observed in 36% of the studied cultivars (30).



Figure 1 The STS primers of Pina-F1c، Pina-R1b، Pina-R2a amplified fragments of 447 bp and 625 bp from for Pina-D1a and Pina-D1b alleles at the puroindoline a locus, respectively. The lanes from 1 to 11 representing cultivars of Darya, Arg, Rooshan, Dez, Zarrin, Tajan. Pishtaz, Chamran, Kohdasht, Kavir and Maroon, respectively.


However, primers used for identification of alleles in the Pinb locus amplified a band of 250 bp for Pinb-D1a and Pinb-D1b alleles (Figure 2). Pinb-D1a allele was observed in 90% of the cultivars (76), while only 10% of the cultivars (8) represented the Pinb-D1b allele. None of the alternative mutations in puroindoline b (Pinb-D1c-d) was detected in the studied wheat cultivars.



Figure 2 Agarose gel electrophoresis of PCR products for the allele specific primers of A) Pinb-D1aF and Pinb-D1aR for identification of Pinb-D1a allele, and B) ( Pinb-D1aF and Pinb-D1bR for identification of Pinb-D1b allele. M is 100 bp DNA size marker, numbers from left to right (1-19) were cultivars of Soomali3, Sistan, Shahpasand, Shahi, Shole, Shariyar, Shiraz, Shiroodi, Tabasi, Toos, Quds, Ghafghaz, Gaskogen, Cross Alborz, Cross Falat hamoon, Karaj2, Karaj 3, Karkhe, Kpphdasht, respectively.


In general, 56% of the cultivars had the wild type alleles (Pina-D1a and Pinb-D1a) at both loci (Table 3). 34.5% of the cultivars showed the mutation allele at puroindoline a locus (Pina-D1b), but the wild type allele at the puroindoline b locus. The cultivars with Pina-D1a and Pinb-D1b were about 8.3% (7), while only one cultivar was found to have mutation alleles at both loci (Pina-D1b/Pinb-D1b).



Table 3 Mean squares of quality traits resulted from the analysis of variance for different Pin alleles in the studied wheat cultivars. Protein content (PROT), Zeleny Number (ZELL), Bread Volume (BV), Hardness Index (HI), Water Absorption (WA)

Note: *, represent significant differences at 5% significant level

NS, represent non-significant differences 


1.3 Marker-trait association
The results of unbalanced analysis of variance for the quality traits as variate and the Pin alleles as factors (Table 4) showed that only Pina had a significant effect on grain hardness (p = 0.019), water absorption (p = 0.015) and bread volume (p = 0.012). Pinb and the interaction between Pina and Pinb had not significant effects on grain quality traits. Mean comparison between different alleles at the Pina and Pinb genes as well as allelic combinations at both loci showed that cultivars with the Pina-null allele (Pina-D1b) had significantly higher grain hardness (51.34 ± 0.48) relative to those with the wild-type (Pina-D1a) allele (49.88±0.36). At this locus, cultivars with Pina-D1b allele had also significantly higher water absorption (64.95±0.14) and relatively smaller bread volume relative to Pina-D1a allele (Table 5). Although, F-statistic for allelic combinations showed no significant differences, p-value for HI, WA and BV were 0.09, 0.08 and 0.07, respectively. Cultivars having wild-type alleles at both loci (Pina-D1a/Pinb-D1a) had relatively smaller grain hardness (49.76 ± 0.4), while cultivars bearing either mutant alleles at each locus or both loci showed relatively higher harness index (Table 5).



Table 4 The classification of wheat germplasm based on allelic combination and grain texture



Table 5 Means, standard error of means and F-statistics for different traits at different alleles and allelic combinations of Pin genes. Protein content (PROT), Zeleny Number (ZELL), Bread Volume (BV), Hardness Index (HI), Water Absorption (WA)


2 Conclusion and Discussion
In this study, 84 wheat cultivars were characterized for the major alleles of Pina and Pinb genes. The most frequent allele was Pinb-D1a and the second most frequent allele was Pina-D1a. This result suggests that most of the wheat cultivars were soft grain, with allelic combination of Pina-D1a/Pinb-D1a at both loci. The Pina-D1b (Null mutation) allele was the most frequent grain hardness allele which observed in 36% of the cultivars. The hardness allele of Pinb-D1b was observed only in 10% of the studied wheat cultivars. Lillemo et al. (2006) also found the Pina-D1b as the most frequent hardness allele which presented in 283 of the 328 lines with hard endosperm. A study of historically important CIMMYT bread wheat lines showed that Pina-D1b has been the dominating hardness allele since the inception of the wheat breeding program in Mexico (Lillemo et al., 2006). Mohammadi et al. (2013) reported Pina-D1a/Pinb-D1a allelic combinations as the most frequent genotypes.
The most second frequent genotype was Pina-D1b/Pinb-D1a genotypes. However, Cane et al. (2004) reported that the Pinb-D1b allele was the major determinant of hardness in southern Australian wheat germplasm, so that,  this allele was found in 84% of the cultivars and breeding lines (Cane et al., 2004). The Pinb-D1b allele has been the most frequent hardness allele in hard wheat cultivars in North American and northern European germplasm (Lillemo and Morris, 2000; Morris et al., 2001). Whereas the Pinb-D1b allele prevails among the spring and winter wheats of North America, Europe, China and Australia (Cane et al., 2004; Lillemo and Morris, 2000; Morris et al., 2001; Xia et al., 2005), Pinb-D1c and Pinb-D1d were mostly found in Western Europe (Lillemo and Morris, 2000). Likewise, the Pina-D1b has been found to be the primary cause of hardness in Iranian and Indian wheat (Mohammadi et al., 2013; Ram et al., 2002).
Based on unbalanced analysis of variance to identify marker-trait association, Pina had a significant effect on grain hardness, water absorption and bread volume. In this study, cultivars with the Pina-D1a allele were significantly harder with more water absorption and less bread volume. Several studies have indicated that cultivars with Pina-null alleles (Pina-D1b) are usually harder than those of Pinb-D1b in bread wheat, so that Pina-D1b allele gives slightly harder endosperm than Pinb-D1b, and is associated with lower milling yield and higher water absorption compared to Pinb-D1b (Cane et al., 2004; Chen et al., 2013; Chen et al., 2006; Giroux et al., 2000; Lillemo et al., 2006; Martin et al., 2001). Morris and Massa (2003) have also reported that Among the hard red spring wheat cultivars that possess the Pina-D1b (a-null) hardness allele were harder than the hard red winter wheat cultivars that possess the Pinb-D1b allele based on NIR, PSI, and break flour yield. Malekzadeh et al. (2008) have reported that among Iranian wheats, those possessing Pina-D1b allele represented a higher hardness value than those with Pinb-D1b allele. However, Pina-D1b may be less preferable from a milling standpoint as well as processing quality. Genotypes with Pina-D1b alleles may have a relatively inferior processing quality for steamed bread, pan bread, and Chinese noodles than the Pinb-D1b genotype (Chen et al., 2007; Chen et al., 2012).
The results of this study showed that the wild type alleles (Pinb-D1a and Pina-D1a) had the highest allelic frequency, while mutant alleles (Pina-D1b and Pinb-D1b) representing hardness characteristic were less frequent in the tested wheat cultivars. Among hardness alleles, Pina-D1b was observed in 36% of cultivars, while only 10% of the wheat cultivars possessed Pinb-D1b. According to marker-trait association analysis, hard wheat cultivars having Pina-D1b (null-mutant allele) were harder in grain texture, with more water absorption and lesser bread volume. The use of STS diagnostic markers is a simple and reliable method to characterize wheat germplasms for Pina and Pinb allelic variability and distribution. The result of this study provides useful information for this set of wheat cultivars, which can be used in the future MAS wheat quality improvement programs.
3 Materials and Methods
3.1 Plant materials and DNA extraction
A total of 84 wheat cultivars were planted at the experimental field of Faculty of Agriculture, University of Birjand, Iran, in the 2013-14 cropping season according to local management practices. At the stage of tillering, leaf samples of each individual were collected and snap-frozen in liquid nitrogen then stored at -20°C. After harvest, about 50 g of bulked clean seeds from each individual were used to measure grain quality traits including grain hardness, protein content, Water absorption, bread volume, Zeleny Number using the near-infrared reflectance (NIR) spectroscopy (Inframatic No. 8100) on ground grain (Method 39-70A in AACCI, 2002).
Extraction of DNA was performed according to the method of Pallotta et al. (2003) with minor modifications. The quality and quantity of the extracted DNA was assessed using NanoDrop 2000 spectrophotometer (Thermo Scientific).
3.2 PCR amplification of Pina and Pinb
The Pina alleles were amplified using a set of co-dominant STS primers (Table 6) described by (Huang and Brûlé-Babel, 2011) yielding products of ~447 bp and ~625 bp for Pina-D1a and Pina-D1b alleles, respectively. The Pinb-D1a and Pinb-D1b alleles were identified using allele specific primers that amplify a fragment of about 250 bp (Giroux and Morris, 1997; 1998).



Table 6 The primer characteristics with the expected size product and the PCR thermo cycling conditions


PCR amplifications were performed in an Eppendorf gradient thermocycler. PCR reactions were carried out in 20 μL volume containing 2 μL of 10X PCR buffer, 1.5 mM MgCl2, 0.4 mM of each dNTP, 1 U of Taq DNA polymerase and ~100 ng of genomic DNA. Thermal cycling conditions for the primer pairs are presented in Table 6. PCR products were separated on 1.5% agarose gel.
3.3 Statistical analysis
The statistical analysis was performed to estimate the effects of the puroindoline genes on grain quality traits and to identify effective alleles on quality traits. In order to compare the effects of different alleles on the quality related traits, the unbalanced analysis of variance was carried out by GenStat release 12.1 (Payne et al., 2009). Grain quality related traits were considered as varieties and Pin alleles and allelic combinations were considered as factors.
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