To understand gene expression networks leading to functional properties and compositional traits of the soybean seed, we have undertaken a detailed examination of soybean seed development from a few days post-fertilization to the mature seed using Illumina high-throughput transcriptome sequencing (RNA-Seq). RNA was sequenced from seven different stages of seed development, yielding between 12 million and 78 million sequenced transcripts. These have been aligned to the 79,000 gene models predicted from the soybean genome recently sequenced by the Department of Energy Joint Genome Institute. Over one hundred gene models were identified with high expression exclusively in young seed stages, starting at just four days after fertilization. These were annotated as being related to many basic components and processes such as histones and proline-rich proteins. Genes encoding storage proteins such as glycinin and beta-conglycinin had their highest expression levels at the stages of largest fresh weight, confirming previous knowledge that these storage products are being rapidly accumulated before the seed begins the desiccation process. Other gene models showed high expression in the dry, mature seeds, perhaps indicating the preparation of pathways needed later, in the early stages of imbibition. Many highly-expressed gene models at the dry seed stage are, as expected, annotated as hydrophilic proteins associated with low water conditions, such as late embryogenesis abundant (LEA) proteins and dehydrins, which help preserve the cellular structures and nutrients within the seed during desiccation. More significantly, the power of RNA-Seq to detect genes expressed at low levels revealed hundreds of transcription factors with notable expression in at least one stage of seed development. Results from a second biological replicate demonstrate high reproducibility of these data revealing a comprehensive view of the transciptome of seed development in the cultivar Williams, the reference cultivar for the first soybean genome sequence.

We report on the design and demonstration of an optical imaging system capable of exciting surfacebound fluorophores within the resonant evanescent electric field of a photonic crystal surface and gathering fluorescence emission that is directed toward the imaging objective by the photonic crystal. The system also has the ability to quantify shifts in the local resonance angle induced by the adsorption of biomolecules on the photonic crystal surface for label-free biomolecular imaging. With these two capabilities combined within a single detection system, we demonstrate label-free images selfregistered to enhanced fluorescence images with 328× more sensitive fluorescence detection relative to a glass surface. This technique is applied to a DNA microarray where label-free quantification of immobilized capture DNA enables improved quality control and subsequent enhanced fluorescence detection of dye-tagged hybridized DNA yields 3× more genes to be detected versus commercially available microarray substrates.

BackgroundTo understand gene expression networks leading to functional properties of the soybean seed, we have undertaken a detailed examination of soybean seed development during the stages of major accumulation of oils, proteins, and starches, as well as the desiccating and mature stages, using microarrays consisting of up to 27,000 soybean cDNAs. A subset of these genes on a highly-repetitive 70-mer oligonucleotide microarray was also used to support the results.ResultsIt was discovered that genes related to cell growth and maintenance processes, as well as energy processes like photosynthesis, decreased in expression levels as the cotyledons approached the mature, dry stage. Genes involved with some storage proteins had their highest expression levels at the stage of highest fresh weight. However, genes encoding many transcription factors and DNA binding proteins showed higher expression levels in the desiccating and dry seeds than in most of the green stages.ConclusionsData on 27,000 cDNAs have been obtained over five stages of soybean development, including the stages of major accumulation of agronomically-important products, using two different types of microarrays. Of particular interest are the genes found to peak in expression at the desiccating and dry seed stages, such as those annotated as transcription factors, which may indicate the preparation of pathways that will be needed later in the early stages of imbibition and germination.

Technical variability during DNA capture probe printing remains an important obstacle to obtaining high quality data from microarray experiments. While methods that use fluorescent labels for visualizing printed arrays prior to hybridization have been presented, the ability to measure spot density using label-free techniques would provide valuable information on spot quality without altering standard microarray protocols. In this study, we present the use of a photonic crystal biosensor surface and a high resolution label-free imaging detection instrument to generate prehybridization images of spotted oligonucleotide microarrays. Spot intensity, size, level of saturation, and local background intensity were measured from these images. This information was used for the automated identification of missed spots (due to mechanical failure or sample depletion) as well as the assignment of a score that reflected the quality of each printed feature. Missed spots were identified with >95% sensitivity. Furthermore, filtering based on spot quality scores increased pairwise correlation of posthybridization spot intensity between replicate arrays, demonstrating that label-free spot quality scores captured the variability in the microarray data. This imaging modality can be applied for the quality control of printed cDNA, oligonucleotide, and protein microarrays.

The soybean () seed coat has distinctive, genetically programmed patterns of pigmentation, and the recessive mutation can epistatically overcome the dominant and alleles, which inhibit seed color by producing small interfering RNAs (siRNAs) targeting () mRNAs. Small RNA sequencing of dissected regions of immature seed coats demonstrated that siRNA levels cause the patterns produced by the and alleles of the locus, which restrict pigment to the hilum or saddle region of the seed coat, respectively. To identify the locus, we compared RNA-seq data from dissected regions of two Clark isolines having similar saddle phenotypes mediated by siRNAs but different genotypes (homozygous versus homozygous). By examining differentially expressed genes, mapping information, and genome resequencing, we identified a 129-bp deletion in Glyma.11G190900 encoding Argonaute5 (AGO5), a member of the Argonaute family. Amplicon sequencing of several independent saddle pattern mutants from different genetic backgrounds revealed independent lesions affecting , thus establishing Glyma.11G190900 as the locus. Nonfunctional AGO5 from alleles leads to altered distributions of siRNAs, thus explaining how the mutation reverses the phenotype of the seed coat regions from yellow to pigmented, even in the presence of the normally dominant or alleles.