Molecular analysis of glycinin genes in soybean mutants for development of gene-specific markers

Bibliometric Analysis of Functional Crops and Nutritional Quality: Identification of Gene Resources to Improve Crop Nutritional Quality through Gene Editing Technology

Food security and hidden hunger are two worldwide serious and complex challenges nowadays. As one of the newly emerged technologies, gene editing technology and its application to crop improvement offers the possibility to relieve the pressure of food security and nutrient needs. In this paper, we analyzed the research status of quality improvement based on gene editing using four major crops, including rice, soybean, maize, and wheat, through a bibliometric analysis. The research hotspots now focus on the regulatory network of related traits, quite different from the technical improvements to gene editing in the early stage, while the trends in deregulation in gene-edited crops have accelerated related research. Then, we mined quality-related genes that can be edited to develop functional crops, including 16 genes related to starch, 15 to lipids, 14 to proteins, and 15 to other functional components. These findings will provide useful reference information and gene resources for the improvement of functional crops and nutritional quality based on gene editing technology.

Reverse genetic approaches for breeding nutrient-rich and climate-resilient cereal and food legume crops

In the last decade, advancements in genomics tools and techniques have led to the discovery of many genes. Most of these genes still need to be characterized for their associated function and therefore, such genes remain underutilized for breeding the next generation of improved crop varieties. The recent developments in different reverse genetic approaches have made it possible to identify the function of genes controlling nutritional, biochemical, and metabolic traits imparting drought, heat, cold, salinity tolerance as well as diseases and insect-pests. This article focuses on reviewing the current status and prospects of using reverse genetic approaches to breed nutrient-rich and climate resilient cereal and food legume crops.

Mutagenesis of seed storage protein genes in Soybean using CRISPR/Cas9

OBJECTIVE

Soybean seeds are an important source of vegetable proteins for both food and industry worldwide. Conglycinins (7S) and glycinins (11S), which are two major families of storage proteins encoded by a small family of genes, account for about 70% of total soy seed protein. Mutant alleles of these genes are often necessary in certain breeding programs, as the relative abundance of these protein subunits affect amino acid composition and soy food properties. In this study, we set out to test the efficiency of the CRISPR/Cas9 system in editing soybean storage protein genes using Agrobacterium rhizogenes-mediated hairy root transformation system.

RESULTS

We designed and tested sgRNAs to target nine different major storage protein genes and detected DNA mutations in three storage protein genes in soybean hairy roots, at a ratio ranging from 3.8 to 43.7%. Our work provides a useful resource for future soybean breeders to engineer/develop varieties with mutations in seed storage proteins.

Genetic mapping and validation of the loci controlling 7S α' and 11S A-type storage protein subunits in soybean [Glycine max (L.) Merr.]

KEY MESSAGE

Four soybean storage protein subunit QTLs were mapped using bulked segregant analysis and an F2 population, which were validated with an F5 RIL population. The storage protein globulins β-conglycinin (7S subunit) and glycinin (11S subunits) can affect the quantity and quality of proteins found in soybean seeds and account for more than 70% of the total soybean protein. Manipulating the storage protein subunits to enhance soymeal nutrition and for desirable tofu manufacturing characteristics are two end-use quality goals in soybean breeding programs. To aid in developing soybean cultivars with desired seed composition, an F2 mapping population (n = 448) and an F5 RIL population (n = 180) were developed by crossing high protein cultivar 'Harovinton' with the breeding line SQ97-0263_3-1a, which lacks the 7S α', 11S A1, 11S A2, 11S A3 and 11S A4 subunits. The storage protein composition of each individual in the F2 and F5 populations were profiled using SDS-PAGE. Based on the presence/absence of the subunits, genomic DNA bulks were formed among the F2 plants to identify genomic regions controlling the 7S α' and 11S protein subunits. By utilizing polymorphic SNPs between the bulks characterized with Illumina SoySNP50K iSelect BeadChips at targeted genomic regions, KASP assays were designed and used to map QTLs causing the loss of the subunits. Soybean storage protein QTLs were identified on Chromosome 3 (11S A1), Chromosome 10 (7S α' and 11S A4), and Chromosome 13 (11S A3), which were also validated in the F5 RIL population. The results of this research could allow for the deployment of marker-assisted selection for desired storage protein subunits by screening breeding populations using the SNPs linked with the subunits of interest.

Genomic Analysis of Storage Protein Deficiency in Genetically Related Lines of Common Bean (Phaseolus vulgaris)

A series of genetically related lines of common bean (Phaseolus vulgaris L.) integrate a progressive deficiency in major storage proteins, the 7S globulin phaseolin and lectins. SARC1 integrates a lectin-like protein, arcelin-1 from a wild common bean accession. SMARC1N-PN1 is deficient in major lectins, including erythroagglutinating phytohemagglutinin (PHA-E) but not α-amylase inhibitor, and incorporates also a deficiency in phaseolin. SMARC1-PN1 is intermediate and shares the phaseolin deficiency. Sanilac is the parental background. To understand the genomic basis for variations in protein profiles previously determined by proteomics, the genotypes were submitted to short-fragment genome sequencing using an Illumina HiSeq 2000/2500 platform. Reads were aligned to reference sequences and subjected to de novo assembly. The results of the analyses identified polymorphisms responsible for the lack of specific storage proteins, as well as those associated with large differences in storage protein expression. SMARC1N-PN1 lacks the lectin genes pha-E and lec4-B17, and has the pseudogene pdlec1 in place of the functional pha-L gene. While the α-phaseolin gene appears absent, an approximately 20-fold decrease in β-phaseolin accumulation is associated with a single nucleotide polymorphism converting a G-box to an ACGT motif in the proximal promoter. Among residual lectins compensating for storage protein deficiency, mannose lectin FRIL and α-amylase inhibitor 1 genes are uniquely present in SMARC1N-PN1. An approximately 50-fold increase in α-amylase inhibitor like protein accumulation is associated with multiple polymorphisms introducing up to eight potential positive cis-regulatory elements in the proximal promoter specific to SMARC1N-PN1. An approximately 7-fold increase in accumulation of 11S globulin legumin is not associated with variation in proximal promoter sequence, suggesting that the identity of individual proteins involved in proteome rebalancing might also be determined at the translational level.

Identification and characterization of transcript polymorphisms in soybean lines varying in oil composition and content

BACKGROUND

Variation in seed oil composition and content among soybean varieties is largely attributed to differences in transcript sequences and/or transcript accumulation of oil production related genes in seeds. Discovery and analysis of sequence and expression variations in these genes will accelerate soybean oil quality improvement.

RESULTS

In an effort to identify these variations, we sequenced the transcriptomes of soybean seeds from nine lines varying in oil composition and/or total oil content. Our results showed that 69,338 distinct transcripts from 32,885 annotated genes were expressed in seeds. A total of 8,037 transcript expression polymorphisms and 50,485 transcript sequence polymorphisms (48,792 SNPs and 1,693 small Indels) were identified among the lines. Effects of the transcript polymorphisms on their encoded protein sequences and functions were predicted. The studies also provided independent evidence that the lack of FAD2-1A gene activity and a non-synonymous SNP in the coding sequence of FAB2C caused elevated oleic acid and stearic acid levels in soybean lines M23 and FAM94-41, respectively.

CONCLUSIONS

As a proof-of-concept, we developed an integrated RNA-seq and bioinformatics approach to identify and functionally annotate transcript polymorphisms, and demonstrated its high effectiveness for discovery of genetic and transcript variations that result in altered oil quality traits. The collection of transcript polymorphisms coupled with their predicted functional effects will be a valuable asset for further discovery of genes, gene variants, and functional markers to improve soybean oil quality.

Haplotype variation of Glu-D1 locus and the origin of Glu-D1d allele conferring superior end-use qualities in common wheat

In higher plants, seed storage proteins (SSPs) are frequently expressed from complex gene families, and allelic variation of SSP genes often affects the quality traits of crops. In common wheat, the Glu-D1 locus, encoding 1Dx and 1Dy SSPs, has multiple alleles. The Glu-D1d allele frequently confers superior end-use qualities to commercial wheat varieties. Here, we studied the haplotype structure of Glu-D1 genomic region and the origin of Glu-D1d. Using seven diagnostic DNA markers, 12 Glu-D1 haplotypes were detected among common wheat, European spelt wheat (T. spelta, a primitive hexaploid relative of common wheat), and Aegilops tauschii (the D genome donor of hexaploid wheat). By comparatively analyzing Glu-D1 haplotypes and their associated 1Dx and 1Dy genes, we deduce that the haplotype carrying Glu-D1d was likely differentiated in the ancestral hexaploid wheat around 10,000 years ago, and was subsequently transmitted to domesticated common wheat and T. spelta. A group of relatively ancient Glu-D1 haplotypes was discovered in Ae. tauschii, which may serve for the evolution of other haplotypes. Moreover, a number of new Glu-D1d variants were found in T. spelta. The main steps in Glu-D1d differentiation are proposed. The implications of our work for enhancing the utility of Glu-D1d in wheat quality improvement and studying the SSP alleles in other crop species are discussed.