Estimation and utilisation of glutenin gene effects from the analysis of unbalanced data from wheat breeding programs

2002 ◽  
Vol 53 (4) ◽  
pp. 367 ◽  
Author(s):  
H. A. Eagles ◽  
G. J. Hollamby ◽  
N. N. Gororo ◽  
R. F. Eastwood
Keyword(s):  
Molecular Weight ◽  
Computer Software ◽  
Wheat Breeding ◽  
Dough Rheology ◽  
Unbalanced Data ◽  
Dough Strength ◽  
Data Set ◽  
Gene Effects ◽  
Breeding Programs ◽  
Multiple Alleles

Glutenins are a major determinant of dough characteristics in wheat. These proteins are determined by genes at 6 loci (Glu genes), with multiple alleles present in most breeding programs. This study was conducted to determine whether estimates of allele effects for the important dough rheological characters, maximum dough resistance (Rmax) and dough extensibility, could be determined from aggregated data from southern Australian wheat breeding programs using statistical techniques appropriate for unbalanced data. From a 2-stage analysis of 3226 samples of 1926 cultivars and breeding lines, estimates of Rmax and extensibility effects were obtained, first for the lines, and then for 31 glutenin alleles. Glutenin genes did not determine flour protein concentration, and this character was used as a covariate. Rankings of the estimates of Rmax for the alleles were similar to the relative scores for dough strength reported from previous studies, providing strong evidence that the analysis of a large, unbalanced data set from applied wheat breeding programs can provide reliable estimates. All 2-way interactions between loci were present for 18 of the alleles. Analyses including interactions showed that epistasis was important for both Rmax and extensibility, especially between the Glu-B1 locus coding for high molecular weight glutenins and the Glu-A3 and Glu-B3 loci coding for low molecular weight glutenins. Because of the complexity of these interactions, similar values of Rmax and extensibility were predicted for diverse combinations of alleles. This implied that the practical application of glutenin genes in applied wheat breeding would be greatly enhanced by computer software which can predict dough rheology characteristics from glutenin allele classifications.

Revision of the estimates of glutenin gene effects at the Glu-B1 locus from southern Australian wheat breeding programs

2004 ◽  
Vol 55 (10) ◽  
pp. 1093 ◽  
Author(s):  
H. A. Eagles ◽  
R. F. Eastwood ◽  
G. J. Hollamby ◽  
E. M. Martin ◽  
G. B. Cornish
Keyword(s):  
Development Time ◽  
Low Frequency ◽  
Wheat Breeding ◽  
Correct Identification ◽  
Gene Effects ◽  
Breeding Programs ◽  
Multiple Alleles ◽  
Intermediate Allele ◽  
Dough Extensibility ◽  
Dough Development Time

Glutenins are the major determinant of dough characteristics in wheat. These proteins are determined by genes at 6 loci, with multiple alleles present in southern Australian breeding programs. Previously, we estimated the effects of these genes on maximum dough resistance (Rmax), dough extensibility and dough development time. Subsequently, the allele previously classified as Glu-B1b was found to consist of 2 alleles, with one, now considered to be Glu-B1al, producing an overexpression of the Bx7 glutenin subunit. Therefore, there is a potential bias in our previous estimates. An extended dataset was analysed with the 2 alleles now separated. These analyses identified negligible biases in our previous estimates, probably due to a low frequency of Glu-B1al before 1999. However, Glu-B1al produced significantly higher Rmax, dough extensibility, and dough development time values than all other alleles at the Glu-B1 locus. Therefore, at intermediate allele frequencies, substantial bias in estimates of the effects of the Glu-B1 alleles can be expected without correct identification of Glu-B1al.

Flour proteins linked to quality traits in an Australian doubled haploid wheat population

2001 ◽  
Vol 52 (12) ◽  
pp. 1339 ◽  
Author(s):  
G. B. Cornish ◽  
F. Békés ◽  
H. M. Allen ◽  
D. J. Martin
Keyword(s):  
Molecular Weight ◽  
Doubled Haploid ◽  
Wheat Breeding ◽  
Dough Rheology ◽  
Quality Data ◽  
Doubled Haploid Population ◽  
Dough Strength ◽  
Protein Levels ◽  
Wheat Population ◽  
A Minor

The Cranbrook/Halberd doubled haploid population has provided a unique opportunity to examine in detail the contributions made by a number of different high molecular weight (HMW) and low molecular weight (LMW) glutenin alleles to the dough properties in a set of homogeneous lines of wheat. A range of different instruments was employed, including Farinograph, Extensograph, Do-Corder, Resistograph, and GRL/EasyMix, to study the dough rheology of the lines from 3 sites over 2 years. Correlation studies showed that 2 basic parameters (dough strength and extensibility) were measured by these different instruments. The results presented are mainly from the Extensograph, which is a major Australian standard for determining release and marketing classification of Australian wheats. Approaches to investigate the data include bulk segregant analysis, distribution of protein alleles in the population, and multiple linear regression. As expected, the HMW glutenin alleles made a major contribution to dough strength, with a minor, but not insignificant, contribution from the LMW glutenin alleles. From a knowledge of their glutenin alleles, a glutenin strength score (GSS) was devised to allow breeders to rank the dough strength of various lines. The GSS scoring system is based on both HMW and LMW glutenin alleles, adding to a total out of 10. Extensibility, on the other hand, was predominantly influenced by protein levels in the flour and environmental conditions such as site and season. However, the LMW glutenin alleles make a significant genetic contribution to the extensibility, which can be assessed by using a glutenin extensibility score. These two glutenin quality scores currently include only the alleles present in the parents, Cranbrook and Halberd, but this could be expanded to include a wider range of alleles by analysis of the quality data from other doubled haploid populations. These quality scores would then be an extremely useful tool for assessing the potential quality of parental and early generation germplasm in wheat breeding programs, by a knowledge of the allelic composition of their HMW and LMW glutenins.

scholarly journals Inheritance of plant height, spike length and number of spikelets per spike in Durum wheat

2007 ◽  
pp. 27-33 ◽  
Author(s):  
Biljana Gorjanovic ◽  
Marija Kraljevic-Balalic
Keyword(s):  
Durum Wheat ◽  
Plant Height ◽  
Combining Ability ◽  
Wheat Breeding ◽  
Specific Combining Ability ◽  
Spike Length ◽  
First Year ◽  
Gene Effects ◽  
Breeding Programs ◽  
Additive Genes

Using the line x tester analysis we studied the combining ability and gene effects of plant height, spike length and number of spikelets per spike in durum wheat. The results of the study show that non-additive genes play more important role than additive genes in the inheritance of plant height, number of spikelets per spike in both years and in inheritance of spike length only in the first year of research. Variety Belfugito, the best general combiner for plant height and number of spikelets per spike, combined well in two best hybrids: Belfugito x Alifen and Belfugito x Yavaros 79, and these hybrids may be used in wheat breeding programs. In the majority of the cases, good specific combining ability (SCA) effects were associated with crosses of two genetically divergent parents having at least one parent as a good general combiner.

scholarly journals Rapid and Easy High-Molecular-Weight Glutenin Subunit Identification System by Lab-on-a-Chip in Wheat (Triticum aestivum L.)

Plants ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1517
Author(s):  
Dongjin Shin ◽  
Jin-Kyung Cha ◽  
So-Myeong Lee ◽  
Nkulu Rolly Kabange ◽  
Jong-Hee Lee
Keyword(s):  
Molecular Weight ◽  
High Molecular Weight ◽  
Lab On A Chip ◽  
Wheat Breeding ◽  
Glutenin Subunit ◽  
Identification System ◽  
Mobility Patterns ◽  
Breeding Programs ◽  
Molecular Weights ◽  
Chip Technology

Lab-on-a-chip technology is an emerging and convenient system to easily and quickly separate proteins of high molecular weight. The current study established a high-molecular-weight glutenin subunit (HMW-GS) identification system using Lab-on-a-chip for three, six, and three of the allelic variations at the Glu-A1, Glu-B1, and Glu-D1 loci, respectively, which are commonly used in wheat breeding programs. The molecular weight of 1Ax1 and 1Ax2* encoded by Glu-A1 locus were of 200 kDa and 192 kDa and positioned below 1Dx subunits. The HMW-GS encoded by Glu-B1 locus were electrophoresed in the following order below 1Ax1 and 1Ax2*: 1Bx13 ≥ 1Bx7 = 1Bx7OE > 1Bx17 > 1By16 > 1By8 = 1By18 > 1By9. 1Dx2 and Dx5 showed around 4-kDa difference in their molecular weights, with 1Dy10 and 1Dy12 having 11-kDa difference, and were clearly differentiated on Lab-on-a-chip. Additionally, some of the HMW-GS, including 1By8, 1By18, and 1Dy10, having different theoretical molecular weights showed similar electrophoretic mobility patterns on Lab-on-a-chip. The relative protein amount of 1Bx7OE was two-fold higher than that of 1Bx7 or 1Dx5 and, therefore, translated a significant increase in the protein amount in 1Bx7OE. Similarly, the relative protein amounts of 8 & 10 and 10 & 18 were higher than each subunit taken alone. Therefore, this study suggests the established HMW-GS identification system using Lab-on-a-chip as a reliable approach for evaluating HMW-GS for wheat breeding programs.

The high molecular weight glutenin subunit composition in old and modern bread wheats cultivated in Iran

2006 ◽  
Vol 57 (10) ◽  
pp. 1109 ◽  
Author(s):  
Ali-Akbar Shahnejat-Bushehri ◽  
Masoud Gomarian ◽  
Bahman Yazdi-Samadi
Keyword(s):  
Molecular Weight ◽  
High Molecular Weight ◽  
Polyacrylamide Gel Electrophoresis ◽  
Sodium Dodecylsulfate ◽  
Quality Parameters ◽  
Wheat Breeding ◽  
Quality Score ◽  
Glutenin Subunit ◽  
Breeding Programs ◽  
Sds Page

All current and old wheat cultivars grown in Iran were characterised by sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE). The high-molecular-weight glutenin subunit (HMW-GS) banding patterns for each cultivar were assigned a Glu-1 quality score, a theoretical quality score based on Payne’s Glu-1 quality assignments. At the Glu-A1 loci, HMW-GS subunit compositions N, 7 + 8, 2 + 12 and 2*, 7 + 8, 2 + 12 were found to be predominant being expressed in 24 and 15 cultivars, respectively, out of 95. Eighteen different alleles were identified for the 3 loci studied: Glu-A1 (3), Glu-B1 (9), and Glu-D1 (6). The glutenin quality scores of Iranian wheat ranged from 4 to 10, with an average of 7.4. It was found that some cultivars were heterogeneous in HMW-GS composition. In cv. Cooleh, only one glutenin subunit at the Glu-B1 locus was present. HMW-GS 2*** + 12′ was found in 6 cultivars and biotypes. The results obtained here describing the allelic composition of bread wheat commonly grown in Iran may be useful in wheat breeding programs selecting for good quality parameters.

scholarly journals Comparison study in statistical estimation of gene effects based on a real data set

2021 ◽  
Vol 1978 (1) ◽  
pp. 012047
Author(s):  
Xiaona Sheng ◽  
Yuqiu Ma ◽  
Jiabin Zhou ◽  
Jingjing Zhou
Keyword(s):  
Statistical Estimation ◽  
Real Data ◽  
Comparison Study ◽  
Data Set ◽  
Gene Effects

scholarly journals Recent advances in CRISPR/Cas9 and applications for wheat functional genomics and breeding

aBIOTECH ◽  
2021 ◽  
Author(s):  
Jun Li ◽  
Yan Li ◽  
Ligeng Ma
Keyword(s):  
Functional Genomics ◽  
Genome Editing ◽  
Functional Annotation ◽  
Genome Engineering ◽  
Agronomic Traits ◽  
Wheat Breeding ◽  
Breeding Programs ◽  
Base Editing ◽  
The World ◽  
World Food Security

AbstractCommon wheat (Triticum aestivum L.) is one of the three major food crops in the world; thus, wheat breeding programs are important for world food security. Characterizing the genes that control important agronomic traits and finding new ways to alter them are necessary to improve wheat breeding. Functional genomics and breeding in polyploid wheat has been greatly accelerated by the advent of several powerful tools, especially CRISPR/Cas9 genome editing technology, which allows multiplex genome engineering. Here, we describe the development of CRISPR/Cas9, which has revolutionized the field of genome editing. In addition, we emphasize technological breakthroughs (e.g., base editing and prime editing) based on CRISPR/Cas9. We also summarize recent applications and advances in the functional annotation and breeding of wheat, and we introduce the production of CRISPR-edited DNA-free wheat. Combined with other achievements, CRISPR and CRISPR-based genome editing will speed progress in wheat biology and promote sustainable agriculture.

scholarly journals Current cancer driver variant predictors learn to recognize driver genes instead of functional variants

BMC Biology ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Daniele Raimondi ◽  
Antoine Passemiers ◽  
Piero Fariselli ◽  
Yves Moreau
Keyword(s):  
Data Sets ◽  
Precision Oncology ◽  
Complex Task ◽  
Excellent Performance ◽  
Driver Genes ◽  
Significant Drop ◽  
Data Set ◽  
Gene Effects ◽  
Cancer Driver ◽  
Functional Variants

Abstract Background Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenesis and precision oncology. Various bioinformatics methods have attempted to solve this complex task. Results In this study, we investigate the assumptions on which these methods are based, showing that the different definitions of driver and passenger variants influence the difficulty of the prediction task. More importantly, we prove that the data sets have a construction bias which prevents the machine learning (ML) methods to actually learn variant-level functional effects, despite their excellent performance. This effect results from the fact that in these data sets, the driver variants map to a few driver genes, while the passenger variants spread across thousands of genes, and thus just learning to recognize driver genes provides almost perfect predictions. Conclusions To mitigate this issue, we propose a novel data set that minimizes this bias by ensuring that all genes covered by the data contain both driver and passenger variants. As a result, we show that the tested predictors experience a significant drop in performance, which should not be considered as poorer modeling, but rather as correcting unwarranted optimism. Finally, we propose a weighting procedure to completely eliminate the gene effects on such predictions, thus precisely evaluating the ability of predictors to model the functional effects of single variants, and we show that indeed this task is still open.

scholarly journals Evolution of Physiologic Races and Virulence of Puccinia striiformis on Wheat in Syria and Lebanon

Plant Disease ◽  
2002 ◽  
Vol 86 (5) ◽  
pp. 499-504 ◽  
Author(s):  
A. H. Yahyaoui ◽  
M. S. Hakim ◽  
M. El Naimi ◽  
N. Rbeiz
Keyword(s):  
Resistance Genes ◽  
Puccinia Striiformis ◽  
Yellow Rust ◽  
Wheat Breeding ◽  
Natural Conditions ◽  
Breeding Programs ◽  
Land Race ◽  
Physiologic Races ◽  
Resistant Genotypes

Virulence-avirulence phenotypes of Puccinia striiformis isolates collected in Lebanon and Syria were determined on seedlings of the wheat-yellow rust differential genotypes. We found 25 and 11 physiologic races over 6 years (1994 to 1999) in Syria and Lebanon, respectively. The composition of physiologic races found in Syria and Lebanon differed greatly between 1994 and 1999. Races identified in 1999, such as 230E150 and 230E134, have wider spectra of virulence on resistant genotypes than races collected in 1994. In Lebanon, three races were found in 1994 compared with six races in 1999. Yellow rust differential genotypes were used in a trap nursery to monitor yellow rust populations under natural conditions. Races identified from cultivars in the trap nursery in Syria and Lebanon, and from land race cultivars in Iraq, were recovered among the races identified from farm fields. Yellow rust samples were collected from Yemen, and none of the races identified from Yemen samples were identical to those in Syria and Lebanon. Virulence frequencies in the yellow rust population on the differential genotypes tested in the trap nurseries were above 70% for some resistance genes. Yellow rust populations in Syria and Lebanon have diverse virulence phenotypes. P. striiformis populations appear to be changing over, and this would be an important consideration for wheat breeding programs in the region.

scholarly journals Plant communities of the Soutpansberg Arid Northern Bushveld

Koedoe ◽  
2009 ◽  
Vol 51 (1) ◽  
Author(s):  
Theo H.C. Mostert ◽  
George J. Bredenkamp ◽  
Rachel E. Mostert
Keyword(s):  
Plant Communities ◽  
Computer Software ◽  
Detrended Correspondence Analysis ◽  
Adansonia Digitata ◽  
Data Set ◽  
Themeda Triandra ◽  
Sociological Approach ◽  
Event Driven ◽  
Vegetation Maps ◽  
Single Data

The Soutpansberg Arid Northern Bushveld is one of eight major vegetation types (MVT) described for the Soutpansberg-Blouberg region. The plant communities of this MVT are described in detail. Main ecological drivers of the vegetation structure and species composition of these communities are discussed and some conservation recommendations are made. Phytosociological data from a subset of 72 Braun-Blanquet sample plots collected in the Soutpansberg Arid Northern Bushveld were classified using Two-way Indicator Species Analysis (TWINSPAN) and ordinated using a Detrended Correspondence Analysis (DECORANA). The resulting classification was further refined with table-sorting procedures based on the Braun-Blanquet floristic-sociological approach to vegetation classification using the computer software MEGATAB and JUICE. Eight plant communities were identified and described as Commiphora tenuipetiolata-Adansonia digitata short open woodland, Ledebouria ovatifolia-Commiphora mollis short bushland, Phyllanthus reticulatus-Acacia nigrescens short bushland, Tinnea rhodesiana-Combretum apiculatum short bushland, Dichrostachys cinerea subsp. africana-Spirostachys africana low thickets, Themeda triandra-Pterocarpus rotundifolius short closed grassland on steep basaltic slopes, Cyperus albostriatus-Syzygium cordatum sandveld wetlands, and Sesamothamnus lugardii-Catophractes alexandri tall sparse shrubland. These plant communities are event-driven ecosystems, predominantly infl uenced by frequent droughts, exposure to desiccation and unpredictable rainfall events. The complex topography of the Soutpansberg further contributes to the aridity of these ecosystems. The classifi cation and ordination analyses show similar groupings in the vegetation of the Soutpansberg Arid Mountain Bushveld. This confi rms the usefulness of complimentary analysis, using both classifi cation and ordination methods on a single data set in order to examine patterns and to search for group structure.Conservation implications: The results from this study will alter existing regional vegetation maps profoundly. The described plant communities of these arid event-driven ecosystems should be used as benchmark examples of the region’s primary vegetation. Conservation and management planning should be based on these vegetation units.

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