Development of SNP Genotyping Assays for Seed Composition Traits in Soybean.
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ABSTRACT:
SUBMITTER: Patil G
PROVIDER: S-EPMC5463095 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.
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Project description:BACKGROUND: Several techniques are available to study gene function, but many are less than ideal for soybean. Reverse genetics, a relatively new approach, can be utilized to identify novel mutations in candidate genes; this technique has not produced an allelic variant with a confirmed phenotype in soybean. Soybean raffinose synthase genes and microsomal omega-6 fatty acid desaturase genes were screened for novel alleles in mutagenized soybean populations. RESULTS: Four mutations in independent lines were identified in the raffinose synthase gene RS2; two mutations resulted in amino acid mutations and one resulted in an altered seed oligosaccharide phenotype. The resulting phenotype was an increase in seed sucrose levels as well as a decrease in both raffinose and stachyose seed oligosaccharide levels. Three mutations in independent lines were identified in the omega-6 fatty acid desaturase gene FAD2-1A; all three mutations resulted in missense amino acid mutations and one resulted in an altered seed fatty acid profile that led to an increase in oleic acid and a decrease in linoleic acid in the seed oil. CONCLUSION: The oligosaccharide phenotype controlled by the novel RS2 allele is similar to previously observed seed oligosaccharide phenotypes in RS2 mutant (PI 200508) allele-containing lines. Due to the anti-nutritional characteristics of raffinose and stachyose, this represents a positive change in seed composition. The fatty acid phenotype controlled by the novel FAD2-1A allele controls an increase in oleic acid in the seed oil, a phenotype also observed in a line previously characterized to have a null allele of the FAD2-1A gene. Molecular marker assays were developed to reliably detect the inheritance of the mutant alleles and can be used in efficient breeding for these desired seed phenotypes. Our results serve as the first demonstration of the identification of soybean mutants controlling seed phenotypes discovered through the reverse genetics technique TILLING.
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Project description:Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (r MP) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences were observed when comparing different marker densities and there appeared to be inflation in r MP due to population structure. For comparison purposes, two additional methods to predict breeding values for lines of four bi-parental populations within the GS dataset were tested. The first method predicted within each bi-parental population (WP method) and utilized a training set of full-sibs of the validation set. The second method utilized a training set of all remaining breeding lines except for full-sibs of the validation set to predict across populations (AP method). The AP method is more practical as the WP method would likely delay the breeding cycle and leverage smaller training sets. Averaging across populations for protein and oil content, r MP for the AP method (0.55, 0.30) approached r MP for the WP method (0.60, 0.52). Though comparable, r MP for yield was low for both AP and WP methods (0.12, 0.13). Based on increases in r MP as training sets increased and the effectiveness of WP vs. AP method, the AP method could potentially improve with larger training sets and increased relatedness between training and validation sets.
| S-EPMC6643879 | biostudies-literature
Project description:Soybean [Glycine max (L.) Merr.] seed is a valuable source of protein and oil worldwide. Traditionally, the natural variations were heavily used in conventional soybean breeding programs to select desired traits. However, traditional plant breeding is encumbered with low frequencies of spontaneous mutations. In mutation breeding, genetic variations from induced mutations provide abundant sources of alterations in important soybean traits; this facilitated the development of soybean germplasm with modified seed composition traits to meet the different needs of end users. In this study, a total of 2366 'Forrest'-derived M2 families were developed for both forward and reverse genetic studies. A subset of 881 M3 families was forward genetically screened to measure the contents of protein, oil, carbohydrates, and fatty acids. A total of 14 mutants were identified to have stable seed composition phenotypes observed in both M3 and M4 generations. Correlation analyses have been conducted among ten seed composition traits and compared to a collection of 103 soybean germplasms. Mainly, ethyl methanesulfonate (EMS) mutagenesis had a strong impact on the seed-composition correlation that was observed among the 103 soybean germplasms, which offers multiple benefits for the soybean farmers and industry to breed for desired multiple seed phenotypes.
| S-EPMC6947669 | biostudies-literature
Project description:Soybean is the world's largest source of protein for animal feed and the second largest source of vegetable oil. Improving the seed protein of soybean without negatively affecting yield and oil content is an important goal for soybean breeders. A population consisting of 132 recombinant inbred lines (RILs) was developed by crossing an elite breeding line, G00-3213 with a plant introduction, PI 594458A, with elevated protein content. In 2016 and 2017, each of the RILs was grown as a single row in Watkinsville, GA, while in 2018, the population was grown at two locations. The seed composition of RILs was analyzed with near-infrared (NIR) spectroscopy. The RIL population was genotyped using the SoySNP6k BeadChip for quantitative trait locus (QTL) mapping. Significant genotype × environment interaction was observed. QTL analyses in and across four environments identified 16, 10, 10, 16, and 5 QTLs for protein, oil, sucrose, and normalized cysteine and methionine contents, respectively. QTLs for protein content identified on chromosomes (Chrs) 3, 6, 13, and 20 were detected in multiple environments. Eight genomic regions on Chrs 3, 6, 8, 10, 13, 17, and 20 were detected that influenced two to four traits, indicating that pleiotropic or linkage effects of these loci may influence multiple seed composition traits. The results of this research provide additional genomic resources for genetic improvement of seed composition and help breeders to better understand the environmental impacts on these QTLs.Supplementary informationThe online version contains supplementary material available at 10.1007/s11032-021-01242-z.
| S-EPMC10236031 | biostudies-literature
Project description:We describe a bead-based, multiplexed, oligonucleotide ligation assay (OLA) performed on the Luminex flow cytometer. Differences between this method and those previously reported include the use of far fewer beads and the use of a universal oligonucleotide for signal detection. These innovations serve to significantly reduce the cost of the assay, while maintaining robustness and accuracy. Comparisons are made between the Luminex OLA and both pyrosequencing and direct sequencing. Experiments to assess conversion rates, call rates, and concordance across technical replicates are also presented.
| S-EPMC3987951 | biostudies-literature
Project description:Soybean was domesticated about 5,000 to 6,000 years ago in China. Although genotyping technologies such as genotyping by sequencing (GBS) and high-density array are available, it is convenient and economical to genotype cultivars or populations using medium-density SNP array in genetic study as well as in molecular breeding. In this study, 235 cultivars, collected from China, Japan, USA, Canada and some other countries, were genotyped using SoySNP8k iSelect BeadChip with 7,189 single nucleotide polymorphisms (SNPs). In total, 4,471 polymorphic SNP markers were used to analyze population structure and perform genome-wide association study (GWAS). The most likely K value was 7, indicating this population can be divided into 7 subpopulations, which is well in accordance with the geographic origins of cultivars or accession studied. The LD decay rate was estimated at 184 kb, where r2 dropped to half of its maximum value (0.205). GWAS using FarmCPU detected a stable quantitative trait nucleotide (QTN) for hilum color and seed color, which is consistent with the known loci or genes. Although no universal QTNs for flowering time and maturity were identified across all environments, a total of 30 consistent QTNs were detected for flowering time (R1) or maturity (R7 and R8) on 16 chromosomes, most of them were corresponding to known E1 to E4 genes or QTL region reported in SoyBase (soybase.org). Of 16 consistent QTNs for protein and oil contents, 11 QTNs were detected having antagonistic effects on protein and oil content, while 4 QTNs soly for oil content, and one QTN soly for protein content. The information gained in this study demonstrated that the usefulness of the medium-density SNP array in genotyping for genetic study and molecular breeding.
| S-EPMC5954420 | biostudies-literature
Project description:BackgroundPCR allelic discrimination technologies have broad applications in the detection of single nucleotide polymorphisms (SNPs) in genetics and genomics. The use of fluorescence-tagged probes is the leading method for targeted SNP detection, but assay costs and error rates could be improved to increase genotyping efficiency. A new assay, rhAmp, based on RNase H2-dependent PCR (rhPCR) combined with a universal reporter system attempts to reduce error rates from primer/primer and primer/probe dimers while lowering costs compared to existing technologies. Before rhAmp can be widely adopted, more experimentation is required to validate its effectiveness versus established methods.ResultsThe aim of this study was to compare the accuracy, sensitivity and costs of TaqMan, KASP, and rhAmp SNP genotyping methods in sugar beet (Beta vulgaris L.). For each approach, assays were designed to genotype 33 SNPs in a set of 96 sugar beet individuals obtained from 12 parental lines. The assay sensitivity was tested using a series of dilutions from 100 to 0.1 ng per PCR reaction. PCR was carried out on the QuantStudio 12K Flex Real-Time PCR System (Thermo Fisher Scientific, USA). The call-rate, defined as the percentage of genotype calls relative to the possible number of calls, was 97.0, 97.6, and 98.1% for TaqMan, KASP, and rhAmp, respectively. For rhAmp SNP, 24 of the 33 SNPs demonstrated 100% concordance with other two technologies. The genotype concordance with either technologies for the other 9 targets was above 99% (99.34-99.89%).ConclusionThe sensitivity test demonstrated that TaqMan and rhAmp were able to successfully determine SNP genotypes using as little as 0.2 ng DNA per reaction, while the KASP was unable to ascertain SNP states below 0.9 ng of DNA per reaction. Comparative cost per reaction was also analyzed with rhAmp SNP offering the lowest cost per reaction. In conclusion, rhAmp produced more calls than either TaqMan or KASP, higher signal to NTC data while offering the lowest cost per reaction.
| S-EPMC5872507 | biostudies-literature
Project description:BACKGROUND: Innate immune system is the first line of research when studying immune response to diverse infections and autoimmune/inflammatory diseases. This immune response has been reported to be genetically diverse, due to polymorphisms coded by different genes. For this reason, our purpose was to develop a multiplex assay that allows the genotyping of candidate single nucleotide polymorphisms (SNPs) in innate immune genes. FINDINGS: We developed three multiplex PCR panels coupled with the minisequencing (SNaPshot) technique (multiplex PCR, multiplex primer extension, and capillary electrophoresis). The panels were tested in a sample set composed of 100 anonymous DNAs from healthy blood donors living in São Miguel Island (Azores, Portugal). Sixteen relevant SNPs among nine genes of the innate immune system--IL1?, IL1?, IL6, IL10, IL12RB1, TLR2, TLR4, TLR9 and CD14--were genotyped and validated by direct sequencing, with the exception of one that was undetected by minisequencing. We suggest that these panels can be used in future studies for detection of risk gene variants in several populations and/or diseases. CONCLUSIONS: In summary, we propose a multiplex assay that is able to identify the most frequent candidate SNPs in innate immune genes, using a medium scale genotyping platform. The assays can be used to evaluate the risk gene variants in populations of various geographic origins.
| S-EPMC3626843 | biostudies-literature
Project description:BACKGROUND: The molecular, biochemical, and genetic mechanisms that regulate the complex metabolic network of soybean seed development determine the ultimate balance of protein, lipid, and carbohydrate stored in the mature seed. Many of the genes and metabolites that participate in seed metabolism are unknown or poorly defined; even more remains to be understood about the regulation of their metabolic networks. A global omics analysis can provide insights into the regulation of seed metabolism, even without a priori assumptions about the structure of these networks. RESULTS: With the future goal of predictive biology in mind, we have combined metabolomics, transcriptomics, and metabolic flux technologies to reveal the global developmental and metabolic networks that determine the structure and composition of the mature soybean seed. We have coupled this global approach with interactive bioinformatics and statistical analyses to gain insights into the biochemical programs that determine soybean seed composition. For this purpose, we used Plant/Eukaryotic and Microbial Metabolomics Systems Resource (PMR, http://www.metnetdb.org/pmr, a platform that incorporates metabolomics data to develop hypotheses concerning the organization and regulation of metabolic networks, and MetNet systems biology tools http://www.metnetdb.org for plant omics data, a framework to enable interactive visualization of metabolic and regulatory networks. CONCLUSIONS: This combination of high-throughput experimental data and bioinformatics analyses has revealed sets of specific genes, genetic perturbations and mechanisms, and metabolic changes that are associated with the developmental variation in soybean seed composition. Researchers can explore these metabolomics and transcriptomics data interactively at PMR.
| S-EPMC4331812 | biostudies-literature