The development and use of a molecular model for soybean maturity groups.

BACKGROUND: Achieving appropriate maturity in a target environment is essential to maximizing crop yield potential. In soybean [Glycine max (L.) Merr.], the time to maturity is largely dependent on developmental response to dark periods. Once the critical photoperiod is reached, flowering is initiated and reproductive development proceeds. Therefore, soybean adaptation has been attributed to genetic changes and natural or artificial selection to optimize plant development in specific, narrow latitudinal ranges. In North America, these regions have been classified into twelve maturity groups (MG), with lower MG being shorter season than higher MG. Growing soybean lines not adapted to a particular environment typically results in poor growth and significant yield reductions. The objective of this study was to develop a molecular model for soybean maturity based on the alleles underlying the major maturity loci: E1, E2, and E3. RESULTS: We determined the allelic variation and diversity of the E maturity genes in a large collection of soybean landraces, North American ancestors, Chinese cultivars, North American cultivars or expired Plant Variety Protection lines, and private-company lines. The E gene status of accessions in the USDA Soybean Germplasm Collection with SoySNP50K Beadchip data was also predicted. We determined the E allelic combinations needed to adapt soybean to different MGs in the United States (US) and discovered a strong signal of selection for E genotypes released in North America, particularly the US and Canada. CONCLUSIONS: The E gene maturity model proposed will enable plant breeders to more effectively transfer traits into different MGs and increase the overall efficiency of soybean breeding in the US and Canada. The powerful yet simple selection strategy for increasing soybean breeding efficiency can be used alone or to directly enhance genomic prediction/selection schemes. The results also revealed previously unrecognized aspects of artificial selection in soybean imposed by soybean breeders based on geography that highlights the need for plant breeding that is optimized for specific environments.

Cytogenetic and Sequence Analyses of Mitochondrial DNA Insertions in Nuclear Chromosomes of Maize.

The transfer of mitochondrial DNA (mtDNA) into nuclear genomes is a regularly occurring process that has been observed in many species. Few studies, however, have focused on the variation of nuclear-mtDNA sequences (NUMTs) within a species. This study examined mtDNA insertions within chromosomes of a diverse set of Zea mays ssp. mays (maize) inbred lines by the use of fluorescence in situ hybridization. A relatively large NUMT on the long arm of chromosome 9 (9L) was identified at approximately the same position in four inbred lines (B73, M825, HP301, and Oh7B). Further examination of the similarly positioned 9L NUMT in two lines, B73 and M825, indicated that the large size of these sites is due to the presence of a majority of the mitochondrial genome; however, only portions of this NUMT (~252 kb total) were found in the publically available B73 nuclear sequence for chromosome 9. Fiber-fluorescence in situ hybridization analysis estimated the size of the B73 9L NUMT to be ~1.8 Mb and revealed that the NUMT is methylated. Two regions of mtDNA (2.4 kb and 3.3 kb) within the 9L NUMT are not present in the B73 mitochondrial NB genome; however, these 2.4-kb and 3.3-kb segments are present in other Zea mitochondrial genomes, including that of Zea mays ssp. parviglumis, a progenitor of domesticated maize.

Major soybean maturity gene haplotypes revealed by SNPViz analysis of 72 sequenced soybean genomes.

In this Genomics Era, vast amounts of next-generation sequencing data have become publicly available for multiple genomes across hundreds of species. Analyses of these large-scale datasets can become cumbersome, especially when comparing nucleotide polymorphisms across many samples within a dataset and among different datasets or organisms. To facilitate the exploration of allelic variation and diversity, we have developed and deployed an in-house computer software to categorize and visualize these haplotypes. The SNPViz software enables users to analyze region-specific haplotypes from single nucleotide polymorphism (SNP) datasets for different sequenced genomes. The examination of allelic variation and diversity of important soybean [Glycine max (L.) Merr.] flowering time and maturity genes may provide additional insight into flowering time regulation and enhance researchers' ability to target soybean breeding for particular environments. For this study, we utilized two available soybean genomic datasets for a total of 72 soybean genotypes encompassing cultivars, landraces, and the wild species Glycine soja. The major soybean maturity genes E1, E2, E3, and E4 along with the Dt1 gene for plant growth architecture were analyzed in an effort to determine the number of major haplotypes for each gene, to evaluate the consistency of the haplotypes with characterized variant alleles, and to identify evidence of artificial selection. The results indicated classification of a small number of predominant haplogroups for each gene and important insights into possible allelic diversity for each gene within the context of known causative mutations. The software has both a stand-alone and web-based version and can be used to analyze other genes, examine additional soybean datasets, and view similar genome sequence and SNP datasets from other species.

Maize Brittle stalk2 encodes a COBRA-like protein expressed in early organ development but required for tissue flexibility at maturity.

The maize (Zea mays) brittle stalk2 (bk2) is a recessive mutant, the aerial parts of which are easily broken. The bk2 phenotype is developmentally regulated and appears 4 weeks after planting, at about the fifth-leaf stage. Before this time, mutants are indistinguishable from wild-type siblings. Afterward, all organs of the bk2 mutants turn brittle, even the preexisting ones, and they remain brittle throughout the life of the plant. Leaf tension assays and bend tests of the internodes show that the brittle phenotype does not result from loss of tensile strength but from loss in flexibility that causes the tissues to snap instead of bend. The Bk2 gene was cloned by a combination of transposon tagging and a candidate gene approach and found to encode a COBRA-like protein similar to rice (Oryza sativa) BC1 and Arabidopsis (Arabidopsis thaliana) COBRA-LIKE4. The outer periphery of the stalk has fewer vascular bundles, and the sclerids underlying the epidermis possess thinner secondary walls. Relative cellulose content is not strictly correlated with the brittle phenotype. Cellulose content in mature zones of bk2 mature stems is lowered by 40% but is about the same as wild type in developing stems. Although relative cellulose content is lowered in leaves after the onset of the brittle phenotype, total wall mass as a proportion of dry mass is either unchanged or slightly increased, indicating a compensatory increase in noncellulosic carbohydrate mass. Fourier transform infrared spectra indicated an increase in phenolic ester content in the walls of bk2 leaves and stems. Total content of lignin is unaffected in bk2 juvenile leaves before or after appearance of the brittle phenotype, but bk2 mature and developing stems are markedly enriched in lignin compared to wild-type stems. Despite increased lignin in bk2 stems, loss of staining with phloroglucinol and ultraviolet autofluorescence is observed in vascular bundles and sclerid layers. Consistent with the infrared analyses, levels of saponifiable hydroxycinnamates are elevated in bk2 leaves and stems. As Bk2 is highly expressed during early development, well before the onset of the brittle phenotype, we propose that Bk2 functions in a patterning of lignin-cellulosic interactions that maintain organ flexibility rather than having a direct role in cellulose biosynthesis.

Neural network analyses of infrared spectra for classifying cell wall architectures.

About 10% of plant genomes are devoted to cell wall biogenesis. Our goal is to establish methodologies that identify and classify cell wall phenotypes of mutants on a genome-wide scale. Toward this goal, we have used a model system, the elongating maize (Zea mays) coleoptile system, in which cell wall changes are well characterized, to develop a paradigm for classification of a comprehensive range of cell wall architectures altered during development, by environmental perturbation, or by mutation. Dynamic changes in cell walls of etiolated maize coleoptiles, sampled at one-half-d intervals of growth, were analyzed by chemical and enzymatic assays and Fourier transform infrared spectroscopy. The primary walls of grasses are composed of cellulose microfibrils, glucuronoarabinoxylans, and mixed-linkage (1 --> 3),(1 --> 4)-beta-D-glucans, together with smaller amounts of glucomannans, xyloglucans, pectins, and a network of polyphenolic substances. During coleoptile development, changes in cell wall composition included a transient appearance of the (1 --> 3),(1 --> 4)-beta-D-glucans, a gradual loss of arabinose from glucuronoarabinoxylans, and an increase in the relative proportion of cellulose. Infrared spectra reflected these dynamic changes in composition. Although infrared spectra of walls from embryonic, elongating, and senescent coleoptiles were broadly discriminated from each other by exploratory principal components analysis, neural network algorithms (both genetic and Kohonen) could correctly classify infrared spectra from cell walls harvested from individuals differing at one-half-d interval of growth. We tested the predictive capabilities of the model with a maize inbred line, Wisconsin 22, and found it to be accurate in classifying cell walls representing developmental stage. The ability of artificial neural networks to classify infrared spectra from cell walls provides a means to identify many possible classes of cell wall phenotypes. This classification can be broadened to phenotypes resulting from mutations in genes encoding proteins for which a function is yet to be described.