An Overview of QTL Identification and Marker-Assisted Selection for Grain Protein Content in Wheat

Kumar, Ajay; Jain, Shalu; Elias, Elias M.; Ibrahim, Mohamed; Sharma, Lakesh K.

doi:10.1007/978-981-10-6934-5_11

Cited by 39 publications

(51 citation statements)

References 107 publications

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“…Furthermore, ANOVA intuitively proved the signi cant differences in GPC, GSC, and WGC among the environments. These ndings are consistent with many previous reports in wheat at different environment [4,13,55,56]. Meanwhile, H 2 of GSC was more than that of GPC and WGC.…”

Section: Impact Of Environment On Gpc Gsc and Wgcsupporting

confidence: 93%

“…Thousand-kernel weight and spikelet compactness are important factors that determine grain yield in wheat. Moreover, several reports have demonstrated a close association between GPC and grain yield [4]. Thus, in the present study, QGpc.sicau-2BS identi ed was found associated with both GPC and thousand-kernel weight/spikelet compactness.…”

Section: Qtl Associated With the Quality Traitssupporting

confidence: 69%

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Genome-Wide association study identifies new elements on the genetic basis of quality-related traits in wheat across multiple environments

Pu¹,

Ye²,

Li³

et al. 2020

Preprint

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Backgrounds: Grain protein concentration (GPC), grain starch concentration (GSC), and wet gluten concentration (WGC) are complex traits that determine nutrient concentration, end-use quality, and yield in wheat. To identify the elite and stable loci or genomic regions conferring high GPC, GSC, and WGC, a genome-wide association study (GWAS) based on a mixed linear model (MLM) was performed using 55K single nucleotide polymorphism (SNP) array in a panel of 236 wheat accessions, including 160 commercial varieties and 76 landraces, derived from Sichuan Province, China. The panel was evaluated for GPC, GSC, and WGC at four different fields. Results: Phenotypic analysis showed variation in GPC, GSC, and WGC among the different genotypes and environments. GWAS identified 12 quantitative trait loci (QTL) (-log10(P) > 2.5) associated with these three quality traits in at least two environments and located on chromosomes 1B, 1D, 2A, 2B, 2D, 3B, 3D, 5D, and 7D; the phenotypic variation explained (PVE) by these QTL ranged from 4.2% to 10.7%. Among these, three, seven, and two QTL are associated with GPC, GSC, and WGC, respectively; five QTL (QGsc.sicau-1BL, QGsc.sicau-1DS, QGsc.sicau-2DL.1, QGsc.sicau-2DL.2, QWgc.sicau-5DL) were defined potentially novel Compared with the previously reported QTLs/genes by linkage or association mapping, 5 QTLs (QGsc.sicau-1BL, QGsc.sicau-1DS, QGsc.sicau-2DL.1, QGsc.sicau-2DL.2, QWgc.sicau-5DL) were potentially novel. Furthermore, 21 presumptive candidate genes, which are involved in the metabolism or transportation of all kinds of carbohydrates, photosynthesis, programmed cell death, the balance of abscisic acid and ethylene, within these potentially novel genomic regions were predicted. Conclusions: This study provided new genetic resources and valuable genetic information of nutritional quality to broaden the genetic background and laid the molecular foundation for marker-assisted selection in wheat quality breeding.

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Section: Impact Of Environment On Gpc Gsc and Wgcsupporting

confidence: 93%

Section: Qtl Associated With the Quality Traitssupporting

confidence: 69%

Genome-Wide association study identifies new elements on the genetic basis of quality-related traits in wheat across multiple environments

Pu¹,

Ye²,

Li³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…Functional molecular markers are preferred in marker-assisted breeding programs as they are directly associated with the trait and can give high rate of accuracy during selection in plant breeding programs. Several protein quality-related functional molecular markers have been developed in wheat (Kumar et al 2018). Similarly, recent studies conducted in maize helped in the identification of molecular markers related to pro-vitamin A content (Azmach et al 2013) and a-carotene content (Zhou et al 2012).…”

Section: Analysis Of Microbial Contaminantsmentioning

confidence: 99%

Meeting the challenge of developing food crops with improved nutritional quality and food safety: leveraging proteomics and related omics techniques

Jain

Rustagi²,

Kumar

et al. 2019

Biotechnol Lett

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Eliminating malnutrition remains an imminent priority in our efforts to achieve food security and providing adequate calories, proteins, and micronutrients to the growing world population. Malnutrition may be attributed to socioeconomic factors (poverty and limited accessibility to nutritional food), dietary preferences, inherent nutrient profiles of traditional food crops, and to a combination of all such factors. Modern advancements in ''omics'' technology have made it possible to reliably predict, diagnose, and suggest ways to remedy the low protein content and bioavailability of key micronutrients in food crops. In this review, we briefly describe how proteomics techniques can potentially be used for improving the nutrient profile of major crops, through high throughput multiplexed assays. Food safety is another important issue where proteomics and related platforms can offer solution for absolute quantitation of food allergens and mycotoxins present in the plant-based food. The purpose of the present review is to discuss the proteomic-based strategies in food crops to meet the challenges of overcoming malnutrition throughout the world.

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“…Grain protein content (GPC) plays an important role in end-use quality and thus determines the economic value of the crop. Improvement in GPC is a major objective in wheat breeding programs around the world [ 1 ]. Grain proteins are generally classified into four groups, albumins, globulins, prolamins, and glutelins [ 1 ].…”

Section: Introductionmentioning

confidence: 99%

“…Improvement in GPC is a major objective in wheat breeding programs around the world [ 1 ]. Grain proteins are generally classified into four groups, albumins, globulins, prolamins, and glutelins [ 1 ]. Among the three major food crops (rice, wheat, and maize), wheat ( Triticum aestivum L.) is unique in accumulating gluten proteins in its grains.…”

Section: Introductionmentioning

confidence: 99%

Effects of HMW-GSs on quality related traits in wheat (Triticum aestivum L.) under different water regimes

et al. 2020

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Alleles at the Glu-1 loci play important roles in the functional properties of wheat flour. The effects of various high-molecular-weight glutenin subunit (HMW-GS) compositions on quality traits and bread-making properties were evaluated using 235 doubled haploid lines (DHs). The experiment was conducted in a split plot design with two water regimes as the main plot treatment, and DH lines as the subplot treatments. Results showed that the presence of subunit pair 5+10 at the Glu-D1 locus, either alone or in combination with others, appears to provide an improvement in quality and bread-making properties. At the Glu-A1 locus, subunit 1 produced a higher Zeleny sedimentation value (Zel) and stretch area (SA) than subunit 2* when subunits 14+15 and 5+10 were expressed at the Glu-B1 and Glu-D1 loci, and 2* had a positive effect on the maximum dough resistance (Rmax) when subunits 14+15 and 5'+12 were expressed at the Glu-B1 and Glu-D1 loci, respectively. Given subunit 1 at the Glu-A1 locus and 5'+12 at the Glu-D1 locus, the effects of Glu-B1 subunits 14+15 on the tractility (Tra), dough stability time (ST), and dough development time (DT) under the well-watered regime were significantly higher than those of Glu-B1 subunits 13+16. However, 13+16 had a positive effect on SA under the rain-fed regime when subunits 2* and 5 +10 were expressed at the Glu-A1 and Glu-D1 loci, respectively. Multiple comparisons analysis revealed that the Zel and Rmax of the six subunits and eight HMW-GS compositions were stable under different water regimes. Overall, subunit compositions 1, 13+16 and 5+10 and 1, 14+15 and 5+10 had higher values for quality traits and bread-baking properties under the two water regimes. These results could play a positive guiding role in selecting and popularizing varieties suitable for production and cultivation in local areas.

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An Overview of QTL Identification and Marker-Assisted Selection for Grain Protein Content in Wheat

Cited by 39 publications

References 107 publications

Genome-Wide association study identifies new elements on the genetic basis of quality-related traits in wheat across multiple environments

Genome-Wide association study identifies new elements on the genetic basis of quality-related traits in wheat across multiple environments

Meeting the challenge of developing food crops with improved nutritional quality and food safety: leveraging proteomics and related omics techniques

Effects of HMW-GSs on quality related traits in wheat (Triticum aestivum L.) under different water regimes

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