Association mapping (AM) is a powerful tool for fine mapping complex trait variation down to nucleotide sequences by exploiting historical recombination events. A major problem in AM is controlling false positives that can arise from population structure and family relatedness. False positives are often controlled by incorporating covariates for structure and kinship in mixed linear models (MLM). These MLM-based methods are single locus models and can introduce false negatives due to over fitting of the model. In this study, eight different statistical models, ranging from single-locus to multilocus, were compared for AM for three traits differing in heritability in two crop species: soybean (Glycine max L.) and maize (Zea mays L.). Soybean and maize were chosen, in part, due to their highly differentiated rate of linkage disequilibrium (LD) decay, which can influence false positive and false negative rates. The fixed and random model circulating probability unification (FarmCPU) performed better than other models based on an analysis of Q-Q plots and on the identification of the known number of quantitative trait loci (QTLs) in a simulated data set. These results indicate that the FarmCPU controls both false positives and false negatives. Six qualitative traits in soybean with known published genomic positions were also used to compare these models, and results indicated that the FarmCPU consistently identified a single highly significant SNP closest to these known published genes. Multiple comparison adjustments (Bonferroni, false discovery rate, and positive false discovery rate) were compared for these models using a simulated trait having 60% heritability and 20 QTLs. Multiple comparison adjustments were overly conservative for MLM, CMLM, ECMLM, and MLMM and did not find any significant markers; in contrast, ANOVA, GLM, and SUPER models found an excessive number of markers, far more than 20 QTLs. The FarmCPU model, using less conservative methods (false discovery rate, and positive false discovery rate) identified 10 QTLs, which was closer to the simulated number of QTLs than the number found by other models.
Background CRISPR/Cas9 gene editing is now revolutionizing the ability to effectively modify plant genomes in the absence of efficient homologous recombination mechanisms that exist in other organisms. However, soybean is allotetraploid and is commonly viewed as difficult and inefficient to transform. In this study, we demonstrate the utility of CRISPR/Cas9 gene editing in soybean at relatively high efficiency. This was shown by specifically targeting the Fatty Acid Desaturase 2 (GmFAD2) that converts the monounsaturated oleic acid (C18:1) to the polyunsaturated linoleic acid (C18:2), therefore, regulating the content of monounsaturated fats in soybean seeds. Results We designed two gRNAs to guide Cas9 to simultaneously cleave two sites, spaced 1Kb apart, within the second exons of GmFAD2–1A and GmFAD2–1B. In order to test whether the Cas9 and gRNAs would perform properly in transgenic soybean plants, we first tested the CRISPR construct we developed by transient hairy root transformation using Agrobacterium rhizogenesis strain K599. Once confirmed, we performed stable soybean transformation and characterized ten, randomly selected T0 events. Genotyping of CRISPR/Cas9 T0 transgenic lines detected a variety of mutations including large and small DNA deletions, insertions and inversions in the GmFAD2 genes. We detected CRISPR- edited DNA in all the tested T0 plants and 77.8% of the events transmitted the GmFAD2 mutant alleles to T1 progenies. More importantly, null mutants for both GmFAD2 genes were obtained in 40% of the T0 plants we genotyped. The fatty acid profile analysis of T1 seeds derived from CRISPR-edited plants homozygous for both GmFAD2 gene s showed dramatic increases in oleic acid content to over 80%, whereas linoleic acid decreased to 1.3–1.7%. In addition, transgene-free high oleic soybean homozygous genotypes were created as early as the T1 generation. Conclusions Overall, our data showed that dual gRNA CRISPR/Cas9 system offers a rapid and highly efficient method to simultaneously edit homeologous soybean genes, which can greatly facilitate breeding and gene discovery in this important crop plant. Electronic supplementary material The online version of this article (10.1186/s12870-019-1906-8) contains supplementary material, which is available to authorized users.
Plant seeds accumulate phosphorus in the form of myo-inositol-1,2,3,4,5,6-hexa-kisphosphate, commonly referred to as phytic acid. Phytic acid is found complexed with cationic mineral species in the form of phytate, which is not well digested or absorbed by monogastric species such as humans, poultry, and swine. As a result, soybean [Glycine max (L.) Merr.] has an effective defi ciency of phosphorus and other minerals, despite high levels of minerals and phosphorus in the seed. Excreted phytate can also contribute to phosphorus contamination of groundwater and eutrophication of freshwater lakes and streams. In maize (Zea mays L. ssp. mays), a recessive mutation in a conserved region within the low phytic acid 1 (lpa1) gene is responsible for the low phytic acid phenotype. We have identifi ed recessive mutations in two soybean homologs of the maize lpa1 gene in soybean line CX1834, a mutagenized line with a low phytic acid phenotype. In three populations analyzed, we identifi ed complete association between homozygosity for mutant alleles of the two lpa1 homologs and the low phytic acid phenotype in soybean. Molecular marker assays were designed that can be used to directly select for the mutant alleles that control the phenotype.
BackgroundAlthough modern soybean cultivars feature yellow seed coats, with the only color variation found at the hila, the ancestral condition is black seed coats. Both seed coat and hila coloration are due to the presence of phenylpropanoid pathway derivatives, principally anthocyanins. The genetics of soybean seed coat and hilum coloration were first investigated during the resurgence of genetics during the 1920s, following the rediscovery of Mendel's work. Despite the inclusion of this phenotypic marker into the extensive genetic maps developed for soybean over the last twenty years, the genetic basis behind the phenomenon of brown seed coats (the R locus) has remained undetermined until now.ResultsIn order to identify the gene responsible for the r gene effect (brown hilum or seed coat color), we utilized bulk segregant analysis and identified recombinant lines derived from a population segregating for two phenotypically distinct alleles of the R locus. Fine mapping was accelerated through use of a novel, bioinformatically determined set of Simple Sequence Repeat (SSR) markers which allowed us to delimit the genomic region containing the r gene to less than 200 kbp, despite the use of a mapping population of only 100 F6 lines. Candidate gene analysis identified a loss of function mutation affecting a seed coat-specific expressed R2R3 MYB transcription factor gene (Glyma09g36990) as a strong candidate for the brown hilum phenotype. We observed a near perfect correlation between the mRNA expression levels of the functional R gene candidate and an UDP-glucose:flavonoid 3-O-glucosyltransferase (UF3GT) gene, which is responsible for the final step in anthocyanin biosynthesis. In contrast, when a null allele of Glyma09g36990 is expressed no upregulation of the UF3GT gene was found.ConclusionsWe discovered an allelic series of four loss of function mutations affecting our R locus gene candidate. The presence of any one of these mutations was perfectly correlated with the brown seed coat/hilum phenotype in a broadly distributed survey of soybean cultivars, barring the presence of the epistatic dominant I allele or gray pubescence, both of which can mask the effect of the r allele, resulting in yellow or buff hila. These findings strongly suggest that loss of function for one particular seed coat-expressed R2R3 MYB gene is responsible for the brown seed coat/hilum phenotype in soybean.
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