Haplotype analyses in wheat for complex traits: tracking the chromosome 3B and 7B regions associated with late maturity alpha amylase (LMA) in breeding programs

2009 ◽  
Vol 60 (5) ◽  
pp. 463 ◽  
Author(s):  
M. D. McNeil ◽  
D. Diepeveen ◽  
R. Wilson ◽  
I. Barclay ◽  
R. McLean ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Relationships ◽  
Artificial Chromosome ◽  
Wheat Breeding ◽  
Breeding Programs ◽  
Discriminating Power ◽  
Late Maturity ◽  
Australian Wheat ◽  
Wheat Lines ◽  
Chromosome 3B

The quantitative trait loci (QTLs) on chromosomes 7BL and 3BS from Halberd have been used as a major source of tolerance to late maturity α amylase (LMA) within Australian wheat breeding programs. New simple sequence repeat (SSR) markers identified from the sequencing of Bacterial Artificial Chromosome (BAC) clones from the wheat cv. Renan library, and known SSRs, were used to characterise these major QTLs. The reduction or elimination of the LMA defect in wheat cultivars is a major goal for wheat breeding programs and is confounded by the complexity in measuring the trait unambiguously. In this haplotyping study focussing on two significant chromosomal regions, markers and combinations of markers were investigated for their ability to discriminate between 39 Australian and Mexican wheat lines differing in levels of LMA. Genetic relationships among these wheat lines estimated by cluster analysis of molecular marker data were combined with phenotypic information in order to calibrate the genotypes of the wheat lines against their LMA phenotype. It was evident that some SSRs from the respective QTLs had greater discriminating power than others to identify LMA phenotypes. Discrimination was not, however, absolute and a statistical analysis of the data defined a risk factor associated with particular combinations of alleles, for use in early selection or backcrossing.

Characterization of the high α -amylase levels in grain of the wheat cultivar BD 159

1994 ◽  
Vol 45 (5) ◽  
pp. 1003 ◽  
Author(s):  
DJ Mares ◽  
K Mrva ◽  
JF Panozzo
Keyword(s):  
Amylase Activity ◽  
Wheat Cultivar ◽  
New South ◽  
Wheat Breeding ◽  
Cool Temperature ◽  
Wheat Varieties ◽  
Breeding Programs ◽  
South Wales ◽  
Late Maturity

TThe advanced wheat breeding line BD 159, from Victoria, exhibited a wide variation in falling number values at trial sites in 1990 when corresponding values for standard cultivars were uniformly high. The variable and unpredictable behaviour of BD 159 appears to be typical of a number of advanced lines and parental stocks from Australian breeding programs. The grain samples of BD 159 with low falling numbers had elevated levels of a-amylase which was distributed evenly in the proximal and distal halves of the grains. This distribution pattern, which was quite distinct from the steep gradient in a-amylase activity typical of germinated grains, and the absence of any evidence of sprouting indicated that the anomalous behaviour of BD 159 is a new and different form of the late maturity a-amylase syndrome previously described in wheat varieties such as Spica and Lerma 52. The high levels of a-amylase were reproduced at Narrabri in northern New South Wales when plants were transplanted from the field and allowed to ripen in a cool temperature glasshouse. Plants which were left to ripen in the field produced grain with a very low a-amylase activity.

GRINDING TIME—A SCREENING TEST FOR KERNEL HARDNESS IN WHEAT

1978 ◽  
Vol 58 (2) ◽  
pp. 415-420 ◽  
Author(s):  
F. G. KOSMOLAK
Keyword(s):  
Screening Test ◽  
Wheat Breeding ◽  
Small Samples ◽  
Kernel Hardness ◽  
Breeding Programs ◽  
Seed Damage ◽  
Percent Moisture ◽  
Wheat Lines ◽  
Grinding Time

A test for screening early generation wheat lines for kernel hardness is described. The test is rapid, uses small samples and is easily performed. Resulting grinding times can be used to classify wheat according to hardness, to detect possible seed damage, to give an estimate of the potential milling and baking quality of wheat and to make quality screening more efficient. Differences between hard and soft wheats are large so that protein content, kernel size and percent moisture have little effect on the use of grinding time as a quality screening test in wheat breeding programs in western Canada.

scholarly journals Increased Predictive Accuracy of Multi-Environment Genomic Prediction Model for Yield and Related Traits in Spring Wheat (Triticum aestivum L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Vipin Tomar ◽  
Daljit Singh ◽  
Guriqbal Singh Dhillon ◽  
Yong Suk Chung ◽  
Jesse Poland ◽  
...  
Keyword(s):  
Complex Traits ◽  
Predictive Accuracy ◽  
Model Performance ◽  
Environmental Variation ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Environmental Variance ◽  
Breeding Programs ◽  
Breeding Lines ◽  
The Impact

Genomic selection (GS) has the potential to improve the selection gain for complex traits in crop breeding programs from resource-poor countries. The GS model performance in multi-environment (ME) trials was assessed for 141 advanced breeding lines under four field environments via cross-predictions. We compared prediction accuracy (PA) of two GS models with or without accounting for the environmental variation on four quantitative traits of significant importance, i.e., grain yield (GRYLD), thousand-grain weight, days to heading, and days to maturity, under North and Central Indian conditions. For each trait, we generated PA using the following two different ME cross-validation (CV) schemes representing actual breeding scenarios: (1) predicting untested lines in tested environments through the ME model (ME_CV1) and (2) predicting tested lines in untested environments through the ME model (ME_CV2). The ME predictions were compared with the baseline single-environment (SE) GS model (SE_CV1) representing a breeding scenario, where relationships and interactions are not leveraged across environments. Our results suggested that the ME models provide a clear advantage over SE models in terms of robust trait predictions. Both ME models provided 2–3 times higher prediction accuracies for all four traits across the four tested environments, highlighting the importance of accounting environmental variance in GS models. While the improvement in PA from SE to ME models was significant, the CV1 and CV2 schemes did not show any clear differences within ME, indicating the ME model was able to predict the untested environments and lines equally well. Overall, our results provide an important insight into the impact of environmental variation on GS in smaller breeding programs where these programs can potentially increase the rate of genetic gain by leveraging the ME wheat breeding trials.

scholarly journals Late-maturity α-amylase (LMA): exploring the underlying mechanisms and end-use quality effects in wheat

Planta ◽  
2021 ◽  
Vol 255 (1) ◽  
Author(s):  
Ashley E. Cannon ◽  
Elliott J. Marston ◽  
Alecia M. Kiszonas ◽  
Amber L. Hauvermale ◽  
Deven R. See
Keyword(s):  
Wheat Breeding ◽  
Protein Accumulation ◽  
Comprehensive Overview ◽  
Breeding Programs ◽  
Future Directions ◽  
Open Questions ◽  
Late Maturity ◽  
End Use ◽  
Molecular Aspects ◽  
Underlying Mechanisms

Abstract Main conclusion A comprehensive understanding of LMA from the underlying molecular aspects to the end-use quality effects will greatly benefit the global wheat industry and those whose livelihoods depend upon it. Abstract Late-maturity α-amylase (LMA) leads to the expression and protein accumulation of high pI α-amylases during late grain development. This α-amylase is maintained through harvest and leads to an unacceptable low falling number (FN), the wheat industry’s standard measure for predicting end-use quality. Unfortunately, low FN leads to significant financial losses for growers. As a result, wheat researchers are working to understand and eliminate LMA from wheat breeding programs, with research aims that include unraveling the genetic, biochemical, and physiological mechanisms that lead to LMA expression. In addition, cereal chemists and quality scientists are working to determine if and how LMA-affected grain impacts end-use quality. This review is a comprehensive overview of studies focused on LMA and includes open questions and future directions.

The storage protein activator gene Spa-B1 and grain quality traits in southern Australian wheat breeding programs

2012 ◽  
Vol 63 (4) ◽  
pp. 311 ◽  
Author(s):  
H. A. Eagles ◽  
Karen Cane ◽  
Marie Appelbee ◽  
Haydn Kuchel ◽  
R. F. Eastwood ◽  
...  
Keyword(s):  
Storage Protein ◽  
Grain Quality ◽  
Mixed Model ◽  
Important Determinant ◽  
Market Value ◽  
Wheat Breeding ◽  
Quality Traits ◽  
Breeding Programs ◽  
Protein Activator ◽  
Australian Wheat

Grain quality is an important determinant of market value of wheat in southern Australia and in many other parts of the world. Identification of the genes that influence grain quality traits and estimation of effects of alleles of these genes can improve the effectiveness of wheat breeding. An efficient method for estimating the effects of alleles of recently discovered genes is to use mixed-model analyses in large plant breeding datasets that have already been characterised for previously known genes. We used this method to estimate the effects of two alleles of Spa-B1, a storage protein activator gene that is linked to Glu-B1, on grain quality traits. Alleles of the two genes tracked together as haplotypes for generations, but recombination events were identified. These recombination events were used to enhance confidence in identification of the alleles. The effects of the alleles of Spa-B1 were small and statistically not significant for all of the grain quality traits in our population.

Microsatellites as markers for Australian wheat improvement

2001 ◽  
Vol 52 (12) ◽  
pp. 1121 ◽  
Author(s):  
N. Harker ◽  
L. R. Rampling ◽  
M. R. Shariflou ◽  
M. J. Hayden ◽  
T. A. Holton ◽  
...  
Keyword(s):  
Molecular Marker ◽  
Genetic Markers ◽  
Wheat Breeding ◽  
Genetic Maps ◽  
Wheat Varieties ◽  
Breeding Programs ◽  
Wheat Improvement ◽  
Australian Wheat ◽  
Mapping Populations

Microsatellite markers have been shown to be highly polymorphic and simple to use in hexaploid wheat. This study aimed to establish microsatellites as informative markers for Australian wheat improvement. By screening microsatellites developed as part of the Wheat Microsatellite Consortium and other available microsatellite sources, 257 informative microsatellites for Australian wheat varieties were identified and reported in the Australian National Wheat Molecular Marker Program microsatellite database (http://www.scu.edu.au/research/cpcg/). Of these, 151 microsatellites identifying 172 loci were scored on at least 1 of 4 double haploid mapping populations and were then integrated, where possible, into existing genetic maps. Polymorphism information content values were calculated for most microsatellites to establish a reference for their value for future investigations. The mapping of available microsatellites enhances the quality of the genetic maps and may provide useful genetic markers for traits of interest to the Australian wheat breeding programs.

Genetic and environmental variation for grain quality traits routinely evaluated in southern Australian wheat breeding programs

2002 ◽  
Vol 53 (9) ◽  
pp. 1047 ◽  
Author(s):  
H. A. Eagles ◽  
G. J. Hollamby ◽  
R. F. Eastwood
Keyword(s):  
Water Absorption ◽  
Development Time ◽  
Grain Quality ◽  
Wheat Breeding ◽  
Breeding Programs ◽  
Environmental Correlations ◽  
Flour Protein ◽  
Australian Wheat ◽  
Dough Development Time ◽  
Milling Yield

Milling yield, maximum dough resistance (Rmax), dough extensibility, flour protein concentration (flour protein), particle size index (PSI), water absorption, and dough development time are important determinants of grain quality and are routinely evaluated in Australian wheat breeding programs. Information on allelic variation at the 6 loci determining glutenin proteins is also regularly obtained and used to predict Rmax and extensibility. For each character, except dough development time, 4029 observations on 2377 lines and 94 environments were analysed to estimate genotypic and environmental variances, heritabilities, genotypic and environmental correlations, and the effects of glutenin genes. A subset was analysed for dough development time. Milling yield, Rmax, extensibility, PSI, water absorption, and dough development time had intra-class correlation coefficients, or broad-sense heritabilities, between 0.66 and 0.76, and extensibility had a value of 0.52, with flour protein at 0.36. Genotypic and environmental correlations between extensibility and flour protein were high at +0.78 and +0.85, respectively. Rmax had a genotypic correlation with dough development time of +0.67, which was substantially due to pleiotropic effects of glutenin genes. Rmax, extensibility, PSI, and dough development time were influenced by glutenin genes. For Rmax about 50% of the genotypic variance could be explained by glutenin genes. For extensibility about 50% could be explained by flour protein, with 50% of the remainder by the inclusion of glutenin genes. For dough development time about 15% could be explained by flour protein, with a further 30% by glutenin genes. For PSI, about 40% of the genotypic variation could be accounted for by glutenin genes after the removal of the effects of flour protein and milling yield. We concluded that dough development time could be added to Rmax and extensibility as a trait that can be usefully predicted by the glutenin genes, but more work is required for PSI.

scholarly journals Combination Capacity and Association Among Traits of Grain Yield in Wheat (Triticum aestivum L.): A Review

2018 ◽  
Vol 10 (5) ◽  
pp. 179
Author(s):  
Alexsander Rigatti ◽  
Alan J. de Pelegrin ◽  
Carine Meier ◽  
Andrei Lunkes ◽  
Luís A. Klein ◽  
...  
Keyword(s):  
Grain Yield ◽  
Combining Ability ◽  
Genetic Relationships ◽  
Triticum Aestivum L ◽  
Wheat Breeding ◽  
Direct Selection ◽  
Breeding Programs ◽  
Environment Effect ◽  
Superior Genotypes ◽  
Selection Of

Grain yield is a complex quantitative trait, because its expression is associated to the large number of genes with small effect. In addition, there is interaction among different yield components and environment effect, making difficult the direct selection of genotypes. The most viable alternative for wheat breeding programs, an autogamous plant, is use artificial crosses in order to obtain superior genotypes. Hybridization after use of successive self-fertilizations results in segregating populations, which reveal the genetic variability, especially when the parents are genetically different. Therefore, it is important to know genetic relationships between crosses, which will serve as reference for decision making in the choice of combinations. Therefore, general combining ability (GCA) and specific combining ability (SCA) are used, which facilitate choice of the best parents to compose crossover block. In addition to these parameters, path analysis can be used to determine importance of primary and secondary traits and to guide indirect selection of promising genotypes by means of interest traits.

The effect of 3BS locus of Sumai 3 on Fusarium head blight resistance in Australian wheats

2007 ◽  
Vol 47 (5) ◽  
pp. 603 ◽  
Author(s):  
G. Q. Xie ◽  
M. C. Zhang ◽  
S. Chakraborty ◽  
C. J. Liu
Keyword(s):  
Molecular Markers ◽  
Fusarium Head Blight ◽  
Fusarium Head Blight Resistance ◽  
Wheat Breeding ◽  
Head Blight ◽  
Breeding Programs ◽  
Backcross Populations ◽  
Australian Wheat ◽  
Fhb Resistance ◽  
Sumai 3

The 3BS allele of Sumai 3 has been the main source of Fusarium head blight (FHB) resistance worldwide. Using molecular markers and FHB resistance screenings, we have analysed the effects of this allele in two backcross and two 4-way F2 populations derived from elite Australian cultivars. Compared to individuals without the Sumai 3 allele, individuals with the allele showed an average 32.0% reduction in FHB severity as measured by number of diseased spikelets. This value was slightly reduced to 29.2% when the total number of spikelets was taken into account by expressing severity as the proportion of diseased spikelets. When compared to the parental cultivars, progeny with the 3BS allele of Sumai 3 offered, on average, 43.3% reduction in FHB severity. Significant differences were not detected between progeny that were homozygous or heterozygous for the 3BS locus, indicating a dominant inheritance of this locus. These results confirm that the 3BS allele controls a large component of the FHB resistance in Sumai 3, which can be readily incorporated and detected in backcross populations using molecular markers. The materials derived from this study could offer significant benefits to the Australian wheat breeding programs.

Starch pasting properties and genetic relationships of wheat cultivars important to Victorian wheat breeding

1995 ◽  
Vol 46 (5) ◽  
pp. 861 ◽  
Author(s):  
KM McCormick ◽  
JF Panozzo ◽  
HA Eagles
Keyword(s):  
Genetic Relationships ◽  
Pasting Properties ◽  
Wheat Breeding ◽  
Wheat Cultivars ◽  
Breeding Programs ◽  
Starch Quality ◽  
Parental Material ◽  
The Common ◽  
Paste Viscosity ◽  
Starch Paste

Starch quality, particularly high paste viscosity, is important in producing marketable wheat for several end uses. Peak starch paste viscosity was measured for 65 wheat cultivars significant to Victorian wheat breeding. Coefficients of kinship were calculated between these cultivars to assess their genetic relationships. In terms of paste viscosity, 15 of the 20 highest ranking cultivars were related. Currawa, a cultivar released in 1912, was the common ancestor and proposed source of high paste viscosity in this family of cultivars, which included the currently grown cultivar, Rosella. Most cultivars in the lower rank were closely related to WW15, which is a semi-dwarf parent from CIMMYT that was used extensively in Australian breeding programs in the past two decades. This survey provides information for choosing parental material for starch quality improvement and offers an explanation for the decrease in peak viscosity of modern Australian cultivars.

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