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 ß-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.

Identification of suitable grapevine reference genes for qRT-PCR derived from heterologous species.

Identification and validation of suitable reference genes that exhibit robust transcriptional stability across many sample types is an absolute requirement of all qRT-PCR experiments. Often, however, only small numbers of reference genes, validated across limited sample types, are available for non-model species. This points to a clear need to assess and validate a wider range of potential reference genes than is currently available. We therefore looked to test and validate a large number of potential reference genes across a wide range of tissue types and treatments to determine the applicability of these reference genes for use in grapevine and other non-model plant species. Potential reference genes were selected based on stability of gene transcription in the model plant species Arabidopsis or due to their common use in the grapevine community. The selected reference genes were analyzed across two datasets consisting of a range of either 'Sauvignon blanc' or 'Pinot noir' tissues. A total of 11 potential reference genes were screened across the two datasets. Gene stability was analyzed by GeNorm, a widely used Excel application, or an ANOVA-based method developed in red clover. Both analysis methods showed that all 11 potential reference genes are stably expressed in the datasets tested, but the rankings of gene stability differed based on the datasets and analysis method used. Furthermore, the transcript stability of these genes, initially identified in Arabidopsis and now validated in grapevine, suggests applicability across a wide range of non-model plant species in addition to their utility in grapevine.