Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1044425 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR26936300.fastq.gz | Fastqsanger.gz | |||
| SRR26936301.fastq.gz | Fastqsanger.gz | |||
| SRR26936302.fastq.gz | Fastqsanger.gz | |||
| SRR26936303.fastq.gz | Fastqsanger.gz | |||
| SRR26936304.fastq.gz | Fastqsanger.gz |
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Project description:Bread aroma is the principal characteristic perceived by the consumer yet it is mostlydisregarded in the product chain. The main aim of this study was to evaluate the potential toinclude bread aroma as a new target criterion into the wheat product chain. The objectivesof our study were to (i) quantify the influence of genetic versus environmental factors onthe bread aroma and quality characteristics, (ii) evaluate whether bread baked from modernwheat varieties differ in terms of aroma from those baked from old varieties and (iii) comparegenomic and metabolomic approaches for their efficiency to predict bread aroma and qualitycharacteristics in a wheat breeding program. Agronomic characters as well as bread aroma andquality traits were assessed for 18 old and 22 modern winter wheat varieties evaluated at up tothree locations in Germany. Metabolite profiles of all 120 flour samples were collected using a7200 GC-QTOF. Considerable differences in the adjusted entry means for all examined breadaroma and quality characters were observed. For aroma, which was rated on a scale from 1 to9, the adjusted entry means varied for the 40 wheat varieties between 3 and 8. In contrast,the aroma of bread prepared from old and modern wheat varieties did not differ significantly(P<0.05). Bread aroma was not significantly (P<0.05) correlated with grain yield, whichsuggested that it is possible to select for the former character in wheat breeding programswithout reducing the gain of selection for the latter. Finally, we have shown that bread aromacan be better predicted using a combination of metabolite and SNP genotyping profiles insteadof the SNP genotyping profile only. In conclusion, we have illustrated possibilities to increasethe quality of wheat for consumers in the product chain.
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Project description:Bread wheat is the most widely cultivated crop worldwide, used in the production of food products and a feed source for animals. Selection tools that can be applied early in the breeding cycle are needed to accelerate genetic gain for increased wheat production while maintaining or improving grain quality if demand from human population growth is to be fulfilled. Proteomics screening assays of wheat flour can assist breeders to select the best performing breeding lines and to filter out the worst performing ones. In this study, we optimised a robust LCMS1 shotgun quantitative proteomics method to screen thousands of wheat genotypes. Using 6 cultivars and 4 replicates, we tested 3 resuspension ratios, 2 extraction buffers, 3 sets of proteases, and multiple LC settings. Protein identifications by LCMS2 was used to select the best parameters. A total 8738 wheat proteins were identified. The best method was validated on an independent set of 96 cultivars and peptides quantities were normalized using sample weights, an internal standard, and Quality Controls. Data mining tools found particularly useful to explore the flour proteome are presented. DOI 10.3390/ijms23020713
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Project description:Bread wheat (Triticum aestivum L.) is one of the most valuable cereal crops for the human consumption. Its grain storage proteins greatly impact bread quality, though may cause food intolerances or allergies in susceptible individuals. Consequently, the investigation of a proteome polymorphism among wheat varieties is important to spot the genotypes, which would be promising donors for the breeding of hypoallergenic cereals. Herein, we discovered diversity of grain proteins in three Ukrainian wheat cultivars: ‘Sotnytsia’, ‘Panna’ (both modern selection) and ‘Ukrainka’ (old landrace). Firstly, proteins were isolated with a SDS-containing buffer that allowed extraction of various groups of storage proteins (glutenins, gliadins, globulins and albumins). Secondly, the proteome was profiled by the two-dimensional gel electrophoresis, revealing 810 clearly-separated gel spots. Software-assisted analysis of gel images, showed 66 differentially abundant proteins. Using multi-enzymatic digestion, followed by the tandem mass spectrometry, we identified 49 differentially accumulated proteins. Parallel ultrahigh-performance liquid chromatography profiling and direct mass spectrometry quantification complemented the results. With this approach we quantified 127 proteins, 12 being differentially abundant. Principal component analysis confirmed genotype as a major source of variation in both cases. Non-gluten fraction was the most diverse among investigated bread wheat cultivars. Information from public databases of clinically relevant plant proteins highlighted variable groups of wheat allergens/toxins. Data suggested that one of the modern cultivars contained less health affecting proteins in grain. Finally, we proposed set of genetic landmarks for the development of DNA marker system, which will enable fast and efficient assessment of medical safety of multiple wheat genotypes to facilitate breeding programs.
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Project description:Root traits are significant targets for breeding stress-resilient and high-yielding wheat genotypes under climatic fluctuations. However, root transcriptome analysis is usually obscured due to challenges in root research. We performed transcriptome analysis of thirty bread wheat cultivars using RNA-seq to investigate the diversity and expression of root system architecture (RSA) related transcripts. We examined the expression patterns of these transcripts in both root and leaf tissues and found that various transcripts are root-specific which could be manipulated for desirable root traits.The presented RNA-seq datasets provide valueable source for identification of genes involved in various biological processes under varying climatic conditions.
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