Manoj Oak

Relationship of HMW, LMW Glutenin Subunits and γ-gliadins with Gluten Strength in Indian Durum Wheats

Twenty-four durum wheat genotypes were evaluated for two years to assess the relationship between HMWglutenin subunits, LMWB glutenin patterns, gammagliadins and gluten strength as measured by SDS-sedimentation volume. Indian durum genotypes assessed in this study represented a diverse set of Glu-1, GH-B1 and Glu-3 alleles. Considerable variability was detected for protein content and gluten strength. All the locals and released varieties derived from locals showed significantly higher protein content. Specific alleles at Glu-1, Glu-3 and Gli-B1 loci showed different effects on gluten strength. HMW glutenin subunits 2* and 14+15 showed association with high gluten strength. Genotypes having LMW-f (linked γ-43.5) showed significantly higher gluten strength than other three LMW-B patterns, i.e. LMW-b and c (linked γ-45) and LMW-e(linked γ-44). While genotypes with γ-44 and linked LMW-e patterns were found to have lowest gluten strength. The Gli-A2 locus did not show any significant association with gluten strength.

Identification of Gluten Protein Subunits and Their PCR Amplified Products Related to Sedimentation Volume in Durum Wheat

Protein content and gluten strength are the major parameters, which decide the firmness, stickiness and cooking loss of pasta. In the present study, a population of 140 F2:7 recombinant inbred lines derived from a durum wheat cross was analyzed for the association of protein and PCR based markers with gluten strength as estimated by sodium dodecyl sulfate-sedimentation (SDSS) volume. The regression analysis showed strong association of Glu-B3a, Glu-B2a and one ω-gliadin band coded by Gli-B3 locus with the SDSS volume. The association between gluten strength and Glu-B2/Gli-B3 loci is new observation. Glu-B1b was also found to be associated with gluten strength, while no association of Glu-A3 locus was observed. All these markers collectively explained 51.9% to 59.1% variation in SDSS volume at three diverse environments.

Nanocarrier-mediated foliar zinc fertilization influences expression of metal homeostasis related genes in flag leaves and enhances gluten content in durum wheat

Background Wheat is the staple food for most of the world’s population; however, it is a poor source of zinc. Foliar fertilization of zinc via zinc loaded chitosan nanocarriers (Zn-CNP) post-anthesis has proved to be a promising approach for grain zinc enhancement in durum wheat as evidenced in our earlier study. However, the molecular mechanism of uptake of zinc via Zn-CNP remains unclear. Methods/Principle findings Foliar application of Zn-CNP was performed at post anthesis stages in two durum wheat cultivars (MACS 3125 and UC1114, containing the Gpc-B1 gene), and expression levels of several metal-related genes were analyzed during early senescence. Zn-CNP application indeed caused changes in gene expression as revealed by qPCR data on representative genes involved in metal homeostasis, phloem transporters, and leaf senescence. Furthermore, zinc-regulated transporters and iron (Fe)-regulated transporter-like protein (ZIP) family [ZIP1, ZIP7, ZIP15], CA (carbonic anhydrase), and DMAS (2’-deoxymugineic acid synthase) in flag leaves exhibited significant correlation with zinc content in the seeds. The analysis of grain endosperm proteins showed enhancement of gamma gliadins while other gluten subunits decreased. Gene expression within ZIP family members varied with the type of cultivar mostly attributed to the Gpc-B1, concentration of external zinc ions as well as the type of tissue analyzed. Correlation analysis revealed the involvement of the selected genes in zinc enhancement. Conclusion At the molecular level, uptake of zinc via Zn-CNP nanocarrier was comparable to the uptake of zinc via common zinc fertilizers i.e. ZnSO4.

1BL/1RS translocation in durum wheat and its effect on end use quality traits

The gluten proteins document the genotypic identity of a wheat variety, in addition to providing valuable clues about its ancestry and technological properties. In this study, an Indian durum wheat genotype B662 was identified to carry 1BL/1RS translocation and characterized further for its effect on end use quality traits. Comparison of the end use quality traits of B662 with five other durum cultivars without 1BL/1RS, showed decreased gluten content, lower swelling index of glutenins and low MSDS-SV indicating that, B662 with 1BL/1RS is not good for pasta making. In F2:3 seeds from a durum wheat cross between the 1BL/1RS cultivar B662 and HI8498 without the translocation, the secalin Sec-1 loci segregated in theoretically expected 3:1 proportion and were inherited as a block of the rye chromosome arm. The analysis of F2:3 harvests for the two most important durum wheat quality tests showed that the presence of 1BL/1RS translocation did not alter the grain protein content values, but was associated with significant reduction of micro SDS-sedimentation volume indicating inferior quality, thus limiting the commercial exploitation of durum wheat genotypes with 1BL/1RS translocation. The cautious use of rye translocation in Indian durum wheat breeding is suggested.

Complex G × E Interactions and QTL Clusters Govern End-Use Quality Traits in Hexaploid Wheat

Evaluation of wheat end-use quality in terms of loaf volume (LV) requires enormous time and labor inputs. Hence, many studies have attempted to use grain, flour and dough properties to predict LV. Many quantitative trait loci (QTL) underlying these traits have also been identified to facilitate breeding. However, correlations between such predictive tests and LV as well as their QTLs could be influenced by the environment. In this chapter, we review recent literature on the correlations and G × E interaction (GEI) of the bread making quality traits grain protein content (GPC), sodium dodecyl sulphate sedimentation volume (SV), dough rheological traits (DRT) and LV. We briefly discuss our results from the evaluation of a hexaploid wheat recombinant inbred line population for GPC, SV, LV and nine DRT by mixograph analysis in six year-location environments in India, which revealed that correlations between DRT and LV were not stable across environments. In addition, GEI measured in terms of principal components using Additive main effects and multiplicative interaction model showed up to 47 % contribution to the total variation of the traits, which was reflected in the location-specificity of QTLs expressed in single as well as multiple environments. Even though 16 QTL clusters for four to seven traits were identified, only one of them involved LV. The strong influence of the environment on complex interrelationships between DRT and the other end-use quality traits suggested that during breeding for wheat end-use quality, marker-based selection of these traits would be more efficient if specific agro-climatic zones are targeted separately.