Genetic analysis of grain protein content and dough quality traits in elite spring bread wheat (Triticum aestivum) lines through association study

Alemu, Admas; El-Baouchi, Adil; Hanafi, Samira El; Kehel, Zakaria; Eddakhir, Kenza; Tadesse, Wuletaw

doi:10.1016/j.jcs.2021.103214

Cited by 15 publications

(15 citation statements)

References 24 publications

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“…The 2 marker-trait associations (Clone ID: 871,955 and 1,049,708) obtained from GWAS on spring bread wheat were co-localized with 2 QTL (q2DL and q4BS.1) revealed in this study [28]. A study conducted GWAS using the models of MLM and FarmCPU for wheat quality traits and reported three QTL on 1B, and these three QTL co-located with q1BS.2, q1BL.5 and q1BL.6 screened in the present study [29]. A total of 15 QTL on chromosomes 1A, 1B, 4B, 4D, 5A, 6A, 6B, 7A, 7B in the present study were co-localized with the QTL for grain protein content, gluten strength and sedimentation volume revealed by previous genetic analyses [30][31][32][33].…”

Section: Gene-0412_338supporting

confidence: 67%

Uncovering the genetic basis of gluten aggregation parameters by genome-wide association analysis in wheat (Triticum aestivum L.) using GlutoPeak

Qiu

Tian

et al. 2022

BMC Plant Biol

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Background Numerous studies have shown that gluten aggregation properties directly affect the processing quality of wheat, however, the genetic basis of gluten aggregation properties were rarely reported. Results To explore the genetic basis of gluten aggregation properties in wheat, an association population consisted with 207 wheat genotypes were constructed for evaluating nine parameters of aggregation properties on GlutoPeak across three-year planting seasons. A total of 940 significant SNPs were detected for 9 GlutoPeak parameters through genome-wide association analysis (GWAS). Finally, these SNPs were integrated to 68 non-redundant QTL distributed on 20 chromosomes and 54 QTL was assigned as pleiotropic loci which accounting for multiple parameters of gluten aggregation property. Furthermore, the peak SNPs representing 54 QTL domonstrated additive effect on all the traits. There was a significant positive correlation between the number of favorable alleles and the phenotypic values of each parameter. Peak SNPs of two novel QTL, q3AL.2 and q4DL, which contributing to both PMT (peak maximum time) and A3 (area from the first minimum to torque 15 s before the maximum torque) parameters, were selected for KASP (Kompetitive Allele Specific PCR) markers development and the KASP markers can be used for effectively evaluating the quality of gluten aggregation properties in the association population. Conclusion The rapid and efficient GlutoPeak method for gluten measurement can be used for early selection of wheat breeding. This study revealed the genetic loci related to GlutoPeak parameters in association population, which would be helpful to develop wheat elite lines with improved gluten aggregation through molecular marker-assisted breeding.

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Section: Gene-0412_338supporting

confidence: 67%

Uncovering the genetic basis of gluten aggregation parameters by genome-wide association analysis in wheat (Triticum aestivum L.) using GlutoPeak

Qiu

Tian

et al. 2022

BMC Plant Biol

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“…In total, 10 GPC-linked QTLs represented by 45 SNPs were mapped on chromosomes 1A, 1B, 2B, 3A, 3D and 6A, using a set of 486 accessions from worldwide regions, especially China [ 47 ]. Alemu et al [ 17 ] reported many chromosomal regions on 2A, 3B, 3D, 5B, 6A, 6B and 7B as the source of highly significant MTAs for GPC based on GWAS analysis in 802 elite spring breeding lines. The contribution of loci on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B for protein content was confirmed in a GWAS study on UK wheat genotypes [ 48 ], whereas genomic regions on chromosome 6A were recently confirmed in a study on Russian spring cultivars [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

“…Association mapping is a complementary approach to bi-parental linkage analysis and searches for functional polymorphisms at many loci across a set of diverse germplasm providing higher mapping resolution [ 15 ]. GWAS has been used to identify the genetic factors behind the natural variation in different diverse populations including tetraploid and hexaploid wheat [ 16 , 17 , 18 , 19 ]. For instance, GWAS revealed novel genomic regions associated with high GPC in 161 wild emmer wheat lines on chromosomes 2B ( QGpc.cd1-2B.1 ) and 7B ( QGpc.cd1-7B.2 ) using 13,116 DArT-seq markers [ 16 ].…”

Section: Introductionmentioning

confidence: 99%

“…For instance, GWAS revealed novel genomic regions associated with high GPC in 161 wild emmer wheat lines on chromosomes 2B ( QGpc.cd1-2B.1 ) and 7B ( QGpc.cd1-7B.2 ) using 13,116 DArT-seq markers [ 16 ]. Using a population of around 800 spring bread wheat accessions genotyped by 5095 SNPs, significant markers associated with GPC were detected on chromosomes 2A, 3B, 3D, 5B, 6B, and 7B [ 17 ]. Nine significant GPC-associated markers had been physically mapped to chromosome 6A in 93 spring wheat cultivars using GWAS with 9351 SNPs [ 18 ].…”

Section: Introductionmentioning

confidence: 99%

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Nutritional Genomic Approach for Improving Grain Protein Content in Wheat

Kartseva

Alqudah

Александров

et al. 2023

Foods

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Grain protein content (GPC) is a key aspect of grain quality, a major determinant of the flour functional properties and grain nutritional value of bread wheat. Exploiting diverse germplasms to identify genes for improving crop performance and grain nutritional quality is needed to enhance food security. Here, we evaluated GPC in a panel of 255 Triticum aestivum L. accessions from 27 countries. GPC determined in seeds from three consecutive crop seasons varied from 8.6 to 16.4% (11.3% on average). Significant natural phenotypic variation in GPC among genotypes and seasons was detected. The population was evaluated for the presence of the trait-linked single nucleotide polymorphism (SNP) markers via a genome-wide association study (GWAS). GWAS analysis conducted with calculated best linear unbiased estimates (BLUEs) of phenotypic data and 90 K SNP array using the fixed and random model circulating probability unification (FarmCPU) model identified seven significant genomic regions harboring GPC-associated markers on chromosomes 1D, 3A, 3B, 3D, 4B and 5A, of which those on 3A and 3B shared associated SNPs with at least one crop season. The verified SNP–GPC associations provide new promising genomic signals on 3A (SNPs: Excalibur_c13709_2568 and wsnp_Ku_c7811_13387117) and 3B (SNP: BS00062734_51) underlying protein improvement in wheat. Based on the linkage disequilibrium for significant SNPs, the most relevant candidate genes within a 4 Mbp-window included genes encoding a subtilisin-like serine protease; amino acid transporters; transcription factors; proteins with post-translational regulatory functions; metabolic proteins involved in the starch, cellulose and fatty acid biosynthesis; protective and structural proteins, and proteins associated with metal ions transport or homeostasis. The availability of molecular markers within or adjacent to the sequences of the detected candidate genes might assist a breeding strategy based on functional markers to improve genetic gains for GPC and nutritional quality in wheat.

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“…Each significant SNP explained between 6.1–41.7% of the phenotypic variation. Several previous studies reported multiple QTLs for GPC on chromosomes 1A, 1B, 2A, 2B, 3A, 4A, 5B, 6A, 7A, and 7B [ 17 , 37 , 38 , 39 , 40 ]. Our GWAS performed on the GPC data averaged across all six environments; however, we identified only eleven significant SNPs, nine of which were located on chromosome 6A ( Table 2 ), which agrees with several previous studies.…”

Section: Discussionmentioning

confidence: 99%

Identification of QTLs for Grain Protein Content in Russian Spring Wheat Varieties

Леонова

Kiseleva

Berezhnaya

et al. 2022

Plants

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Most modern breeding programs aim to develop wheat (T. aestivum L.) varieties with a high grain protein content (GPC) due to its greater milling and cooking quality, and improved grain price. Here, we used a genome-wide association study (GWAS) to map single nucleotide polymorphisms (SNPs) associated with GPC in 93 spring bread wheat varieties developed by eight Russian Breeding Centers. The varieties were evaluated for GPC, grain weight per spike (GWS), and thousand-kernel weight (TKW) at six environments, and genotyped with 9351 polymorphic SNPs and two SNPs associated with the NAM-A1 gene. GPC varied from 9.8 to 20.0%, depending on the genotype and environment. Nearly 52% of the genotypes had a GPC > 14.5%, which is the threshold value for entry into high-class wheat varieties. Broad-sense heritability for GPC was moderate (0.42), which is due to the significant effect of environment and genotype × environment interactions. GWAS performed on mean GPC evaluated across six environments identified eleven significant marker-trait associations, of which nine were physically mapped on chromosome 6A. Screening of wheat varieties for allelic variants of the NAM-A1 gene indicated that 60% of the varieties contained the NAM-A1c allele, followed by 33% for NAM-A1d, and 5% for NAM-A1a alleles. Varieties with the NAM-A1d allele showed significantly (p < 0.01) smaller GPC than those with NAM-A1c and NAM-A1a. However, no significant differences between NAM-A1 alleles were observed for both GWS and TKW.

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Genetic analysis of grain protein content and dough quality traits in elite spring bread wheat (Triticum aestivum) lines through association study

Cited by 15 publications

References 24 publications

Uncovering the genetic basis of gluten aggregation parameters by genome-wide association analysis in wheat (Triticum aestivum L.) using GlutoPeak

Uncovering the genetic basis of gluten aggregation parameters by genome-wide association analysis in wheat (Triticum aestivum L.) using GlutoPeak

Nutritional Genomic Approach for Improving Grain Protein Content in Wheat

Identification of QTLs for Grain Protein Content in Russian Spring Wheat Varieties

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