scholarly journals Genetic mapping high protein content QTL from soybean ‘Nanxiadou 25’ and candidate gene analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jia Wang ◽  
Lin Mao ◽  
Zhaoqiong Zeng ◽  
Xiaobo Yu ◽  
Jianqiu Lian ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Protein Content ◽  
Candidate Genes ◽  
Seed Protein ◽  
Recombinant Inbred Lines ◽  
High Protein ◽  
Quality Trait ◽  
Seed Protein Content ◽  
High Protein Content ◽  
Major Qtl

Abstract Background Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean. Results In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL qSPC_20–1 and qSPC_20–2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of qSPC_20–1 and qSPC_20–2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait. Conclusions These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

scholarly journals Genetic Analysis of High Protein Content in ‘AC Proteus’ Related Soybean Populations Using SSR, SNP, DArT and DArTseq Markers

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Bahram Samanfar ◽  
Elroy R. Cober ◽  
Martin Charette ◽  
Le Hoa Tan ◽  
Wubishet A. Bekele ◽  
...  
Keyword(s):  
Protein Content ◽  
Qtl Analysis ◽  
Seed Protein ◽  
High Protein ◽  
Specific Marker ◽  
Seed Protein Content ◽  
Test Statistic ◽  
High Protein Content ◽  
Genomic Regions ◽  
Further Development

AbstractKey message: Several AC Proteus derived genomic regions (QTLs, SNPs) have been identified which may prove useful for further development of high yielding high protein cultivars and allele-specific marker developments. High seed protein content is a trait which is typically difficult to introgress into soybean without an accompanying reduction in seed yield. In a previous study, ‘AC Proteus’ was used as a high protein source and was found to produce populations that did not exhibit the typical association between high protein and low yield. Five high x low protein RIL populations and a high x high protein RIL population were evaluated by either quantitative trait locus (QTL) analysis or bulk segregant analyses (BSA) following phenotyping in the field. QTL analysis in one population using SSR, DArT and DArTseq markers found two QTLs for seed protein content on chromosomes 15 and 20. The BSA analyses suggested multiple genomic regions are involved with high protein content across the five populations, including the two previously mentioned QTLs. In an alternative approach to identify high protein genes, pedigree analysis identified SNPs for which the allele associated with high protein was retained in seven high protein descendants of AC Proteus on chromosomes 2, 17 and 18. Aside from the two identified QTLs (five genomic regions in total considering the two with highly elevated test statistic, but below the statistical threshold and the one with epistatic interactions) which were some distance from Meta-QTL regions and which were also supported by our BSA analysis within five populations. These high protein regions may prove useful for further development of high yielding high protein cultivars.

Effects of divergent selection for seed protein content in high-protein vs. food-grade populations of early maturity soybean

2013 ◽  
Vol 133 (1) ◽  
pp. 74-79 ◽  
Author(s):  
Takashi Sato ◽  
Melanie Van Schoote ◽  
Helmut Wagentristl ◽  
Johann Vollmann
Keyword(s):  
Protein Content ◽  
Seed Protein ◽  
Divergent Selection ◽  
High Protein ◽  
Seed Protein Content ◽  
Early Maturity ◽  
Food Grade ◽  
Selection For

scholarly journals Improving Quantitative Traits in Self-Pollinated Crops Using Simulation-Based Selection With Minimal Crossing

2021 ◽  
Vol 12 ◽  
Author(s):  
Daisuke Sekine ◽  
Mai Tsuda ◽  
Shiori Yabe ◽  
Takehiko Shimizu ◽  
Kayo Machita ◽  
...  
Keyword(s):  
Prediction Model ◽  
Protein Content ◽  
Quantitative Traits ◽  
Recurrent Selection ◽  
Seed Protein ◽  
Recombinant Inbred Lines ◽  
Initial Population ◽  
Seed Protein Content ◽  
Short Period ◽  
Simulation Based

Genomic selection and marker-assisted recurrent selection have been applied to improve quantitative traits in many cross-pollinated crops. However, such selection is not feasible in self-pollinated crops owing to laborious crossing procedures. In this study, we developed a simulation-based selection strategy that makes use of a trait prediction model based on genomic information to predict the phenotype of the progeny for all possible crossing combinations. These predictions are then used to select the best cross combinations for the selection of the given trait. In our simulated experiment, using a biparental initial population with a heritability set to 0.3, 0.6, or 1.0 and the number of quantitative trait loci set to 30 or 100, the genetic gain of the proposed strategy was higher or equal to that of conventional recurrent selection method in the early selection cycles, although the number of cross combinations of the proposed strategy was considerably reduced in each cycle. Moreover, this strategy was demonstrated to increase or decrease seed protein content in soybean recombinant inbred lines using SNP markers. Information on 29 genomic regions associated with seed protein content was used to construct the prediction model and conduct simulation. After two selection cycles, the selected progeny had significantly higher or lower seed protein contents than those from the initial population. These results suggest that our strategy is effective in obtaining superior progeny over a short period with minimal crossing and has the potential to efficiently improve the target quantitative traits in self-pollinated crops.

scholarly journals SNP marker association for incrementing soybean seed protein content

2020 ◽  
Vol 6 ◽  
pp. 1-11
Author(s):  
Arthur Bernardeli ◽  
Aluízio Borem ◽  
Rodrigo Lorenzoni ◽  
Rafael Aguiar ◽  
Jessica Nayara Basilio Silva ◽  
...  
Keyword(s):  
Protein Content ◽  
Seed Protein ◽  
Recombinant Inbred Lines ◽  
Soybean Seed ◽  
Snp Markers ◽  
Snp Marker ◽  
Seed Protein Content ◽  
Single Marker Analysis ◽  
Soybean Breeding ◽  
Single Marker

Soybean seed protein content (SPC) has been decreasing throughout last decades and DNA marker association has shown its usefulness to improve this trait even in soybean breeding programs that focus primarily on soybean yield and seed oil content (SOC). Aiming to elucidate the association of two SNP markers (ss715630650 and ss715636852) to the SPC, a soybean population of 264 F5-derived recombinant inbred lines (RILs) from a bi-parental cross was tested in four environments. Through the single-marker analysis, the additive effect () and the portion of SPC variation due to the SNPs () for single and multi-environment data were assessed, and transgressive RILs for SPC were observed. The estimates revealed the association of both markers to SPC in most of environments. The marker ss715636852 was more frequently associated to SPC, including multi-environment data, and contributed up to  = 1.30% for overall SPC, whereas ss715630650 had significant association just in two locations, with contributions of  = 0.76% and  = 0.74% to overall SPC in Vic1 and Cap1, respectively. The RIL 84-13 was classified as an elite genotype due to its favorable alleles and high SPC means, which reached 53.78% in Cap1, and 46.33% in MET analysis. Thus, these results confirm the usefulness of the SNP marker ss715636852 in a soybean breeding program for SPC.

scholarly journals Genome-Wide Scans for Delineation of Candidate Genes Regulating Seed-Protein Content in Chickpea

2016 ◽  
Vol 7 ◽  
Author(s):  
Hari D. Upadhyaya ◽  
Deepak Bajaj ◽  
Laxmi Narnoliya ◽  
Shouvik Das ◽  
Vinod Kumar ◽  
...  
Keyword(s):  
Protein Content ◽  
Candidate Genes ◽  
Seed Protein ◽  
Seed Protein Content ◽  
Genome Wide

scholarly journals Meta-analysis of QTL reveals the genetic control of yield-related traits and seed protein content in pea

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Anthony Klein ◽  
Hervé Houtin ◽  
Céline Rond-Coissieux ◽  
Myriam Naudet-Huart ◽  
Michael Touratier ◽  
...  
Keyword(s):  
Protein Content ◽  
Candidate Genes ◽  
Seed Weight ◽  
Seed Protein ◽  
Meta Analysis ◽  
Snp Array ◽  
Grain Legume ◽  
Potential Candidate ◽  
Seed Protein Content ◽  
Breeding Target

Abstract Pea is one of the most important grain legume crops in temperate regions worldwide. Improving pea yield is a critical breeding target. Nine inter-connected pea recombinant inbred line populations were evaluated in nine environments at INRAE Dijon, France and genotyped using the GenoPea 13.2 K SNP array. Each population has been evaluated in two to four environments. A multi-population Quantitative Trait Loci (QTL) analysis for seed weight per plant (SW), seed number per plant (SN), thousand seed weight (TSW) and seed protein content (SPC) was done. QTL were then projected on the multi-population consensus map and a meta-analysis of QTL was performed. This analysis identified 17 QTL for SW, 16 QTL for SN, 35 QTL for TSW and 21 QTL for SPC, shedding light on trait relationships. These QTL were resolved into 27 metaQTL. Some of them showed small confidence intervals of less than 2 cM encompassing less than one hundred underlying candidate genes. The precision of metaQTL and the potential candidate genes reported in this study enable their use for marker-assisted selection and provide a foundation towards map-based identification of causal polymorphisms.

scholarly journals Direct and indirect effects of morphophysiological traits on kernel protein content of confectionary sunflower

Genetika ◽  
2017 ◽  
Vol 49 (3) ◽  
pp. 1015-1021
Author(s):  
Nada Hladni ◽  
Milan Jockovic ◽  
Sinisa Jocic ◽  
Vladimir Miklic ◽  
Dragana Miladinovic ◽  
...  
Keyword(s):  
Protein Content ◽  
Seed Weight ◽  
Seed Protein ◽  
High Protein ◽  
Protein Yield ◽  
Path Coefficient ◽  
Seed Protein Content ◽  
Path Coefficient Analysis ◽  
Negative Effect ◽  
Kernel Protein

The most important criterion for introducing new confectionary sunflower hybrids into production is high protein yield. In the breeding process it is important to identify traits which could be used as selection criteria for increased kernel protein content. Increase of kernel protein content results in increased protein yield. This research was conducted during three vegetation seasons on 22 NS high-protein two-line confectionary sunflower hybrids produced within the breeding program at IFVCNS, Novi Sad, Serbia. Strong and very strong correlations were found among the largest number of examined traits. Based on the analysis of simple correlation coefficients, strong negative correlation was determined between kernel protein content and kernel ratio (-0.516*). A weak negative interdependence was determined between head diameter, seed protein content, and kernel protein content. Positive but weak correlation was determined between kernel protein content and thickness of seed, length of seed, width of seed, and 1000 seed weight. Path coefficient analysis for kernel protein content at phenotypic level showed that the thickness of seed had a strong positive direct effect on kernel protein content (DE=382*). Kernel ratio and width of seed had a very strong direct negative effect on kernel protein content (DE=-0.990**; DE=0.600**). A weak direct positive effect of head diameter, seed protein content and length of seed was established, whereas 1000 seed weight had a weak direct negative effect on kernel protein content. Path coefficient analysis indicates showed that the thickness of seed has high great influence on kernel protein content, and an important selection criterion for breeding for high protein yield.

scholarly journals Proteins and Bioactive Peptides in High Protein Content Foods

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1186
Author(s):  
Fidel Toldrá ◽  
Leticia Mora
Keyword(s):  
Enzymatic Hydrolysis ◽  
Protein Content ◽  
Human Body ◽  
Bioactive Peptides ◽  
High Protein ◽  
Microbial Fermentation ◽  
Gastrointestinal Digestion ◽  
High Protein Content ◽  
By Products

Foods and their industry by-products constitute very good sources of bioactive peptides, which can be naturally generated during processing but are also extensively produced through enzymatic hydrolysis, microbial fermentation, and even during gastrointestinal digestion in the human body [...]

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