News Update on Wheat genetics April – 2021

 [1] Single-kernel analysis of glutenin: use in wheat genetics and breeding
Glutenin was quantitatively extracted from single kernels of (i) the hexaploid Chinese Spring and all except five of the compensating nullisomic-tetrasomic stocks, (ii) nullisomic-trisomic lines of 2A-2B, 7D-7A and 7D-7B, (iii) 31 ditelocentric lines in which both of a pair of chromosomes lacked one arm, (iv) the hexaploids Prelude, Canthatch, Thatcher and Rescue, and their derived tetraploid strains, (v) the Cheyenne-Chinese Spring substitution lines, (vi) 80 hexaploid varieties from the USDA World Wheat Collection, (vii) 55 tetraploid wheats, most of which were Triticum durum, but with some wild emmer wheats were included, (viii) nine diploid wheats of T. monococcum, T. aegilopoides and T. boeticum, and (ix) Aegilops squarrosa var. strangulata. In addition, various common and durum varieties were examined. Glutenin subunit composition was determined by sodium dodecyl sulphate polyacrylamide gel electrophoresis. The long arms of chromosomes 1B, 1D and 4D contain genes coding the five largest glutenin subunits in Chinese Spring, and the results indicated that these same chromosomes contribute to the glutenin composition of other hexaploid wheats and may be essential for quality characteristics in wheat.

 [2] Domestication evolution, genetics and genomics in wheat
Domestication of plants and animals is the major factor underlying human civilization and is a gigantic evolutionary experiment of adaptation and speciation, generating incipient species. Wheat is one of the most important grain crops in the world, and consists mainly of two types: the hexaploid bread wheat (Triticum aestivum) accounting for about 95% of world wheat production, and the tetraploid durum wheat (T. durum) accounting for the other 5%. In this review, we summarize and discuss research on wheat domestication, mainly focusing on recent findings in genetics and genomics studies. T. aestivum originated from a cross between domesticated emmer wheat T. dicoccum and the goat grass Aegilops tauschii, most probably in the south and west of the Caspian Sea about 9,000 years ago. Wild emmer wheat has the same genome formula as durum wheat and has contributed two genomes to bread wheat, and is central to wheat domestication. Domestication has genetically not only transformed the brittle rachis, tenacious glume and non-free threshability, but also modified yield and yield components in wheat. Wheat domestication involves a limited number of chromosome regions, or domestication syndrome factors, though many relevant quantitative trait loci have been detected. On completion of the genome sequencing of diploid wild wheat (T. urartu or Ae. tauschii), domestication syndrome factors and other relevant genes could be isolated, and effects of wheat domestication could be determined. The achievements of domestication genetics and robust research programs in Triticeae genomics are of greatly help in conservation and exploitation of wheat germplasm and genetic improvement of wheat cultivars.

[3] Wheat genetics
The genetics of hexaploid wheat is complicated because of its polyploidy. The duplication and triplication of genes resulting from this leads to complex segregational patterns and epistatic effects, which can be difficult to analyse and resolve into the effects of component genes. It is therefore not surprising that the description and location of genes in wheat lags behind that of diploid crop species such as barley. This is despite the advantages that the aneuploid methods described in Chapter 4 have given to the analysis of wheat.

 [4] SSR- Based Genetic Diversity Assessment in Tetraploid and Hexaploid Wheat Populations

Molecular analysis for a set of hexaploid (Triticum aestvium) and tetraploid (Triticum durum) wheat cultivars was investigated by applying 11 SSR primers set. The plant materials consisted of 45 genotypes 15 of which were Triticum aestivum and 30 of T. durum obtained from four different regions Egypt, Greece, Cyprus and Italy. PCR products were separated on a 6% denaturing polyacrylamide gel electrophoresis and produced a total of 3840 DNA fragments which were used for the molecular analysis. The estimated parameters computed by POPGENE (Version 1.32) within the two population indicated that the Nei’s genetic diversity (H) was 0.2827, and the Shannon’s Information index (I) was 0.4533 with standard deviation ± 0.0699 and ± 0.0852 respectively. The analysis of population structure revealed that genetic diversity within populations (Hs=0.2761) represented 97.7% of the total genetic diversity (HT=0.2827). The proportion of the total genetic diversity that was attributed to the population differentiation was low (Gst=0.0233) within population. ANOSIM (ANalysis Of Similarities), results showed that R was equal to 0.9048 (P<0.0001) indicated that all the most similar samples of genotypes are within the same population. The wheat varieties from the four distinct regions were clustered according to SSR data into two main clusters, durum wheat varieties and bread wheat varieties, the principal coordinate analysis (PCOORDA) validated the results of the dendrogram. This study showed that the two populations still had moderate considerable level of genetic diversity and show little genetic differentiation among them. Understanding genetic variation within and between populations is essential for the establishment of an effective breeding program concerning the intraspecific and interspecific hybridization.

[5] Genetic Advance Prediction and Multivariate Analysis for Antioxidants and Agronomic Traits in Wheat

Background: The Interrelationship of traits is important for structuring crop populations and modeling selection criteria for increasing grain yield.
Aims: Assessing interrelationship of traits under drought stress and normal irrigation conditions.
Study Design: Landrace varieties from different regions of Iran were selected for evaluating the interrelationship of traits under drought stress.
Place and Duration of Study: The Research Farm of Department of Crop Production and Plant Breeding, College of Agriculture, Shiraz University, Shiraz, Iran, between 2010 and 2012 growing seasons.
Methodology: Thirty five wheat genotypes consisting of 33 landrace varieties and two cultivars were cultivated as a split plot design in three replications in 2010-11 and 2011-12 growing seasons. Drought stress and normal irrigation conditions were considered as main plots and genotypes were cultivated in subplots.
Results: Cryptic relationships among antioxidants and agronomic traits were defined by 7 and 6 factors that explained 80% and 75% of traits variation under fully irrigated and drought stress conditions respectively. Factor 2 was defined as grain yield factor and it was a contrast between antioxidants and morphological traits. In factor 2, grain yield, thousands grain weight, spikelet and grain number had the highest loadings. Stepwise regression for grain yield (Y) and other traits under drought stress indicated that thousand grain weight (X1), biological yield (X2), harvest index (X3) and grain number (X4) entered to grain yield model as Y= 44.4+ 3.03 X1+ 0.389 X2+ 12.635 X3+ 2.639 X4. Except day to heading and canopy temperature, agronomic traits had positive correlations with grain yield. Cluster analysis showed that genotypes assigned to 5 clusters under drought stress and the highest grain yield (5.3 t ha-1) and harvest index (38.1%) belonged to the fifth cluster.

Bietz, J.A., Shepherd, K.W. and Wall, J.S., 1975. Single-kernel analysis of glutenin: use in wheat genetics and breeding

[2] Peng, J.H., Sun, D. and Nevo, E., 2011. Domestication evolution, genetics and genomics in wheat. Molecular Breeding28(3), pp.281-301.

Worland, A.J., Gale, M.D. and Law, C.N., 1987. Wheat genetics. In Wheat breeding (pp. 129-171). Springer, Dordrecht.

[4] Abouzied, H.M., Eldemery, S.M. and Abdellatif, K.F., 2013. SSR-based genetic diversity assessment in tetraploid and hexaploid wheat populations. Biotechnology Journal International, pp.390-404.

[5] Ghaed-Rahimi, L. and Heidari, B., 2014. Genetic advance prediction and multivariate analysis for antioxidants and agronomic traits in wheat. Annual Research & Review in Biology, pp.2427-2449.

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