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1.  RNA-Seq Atlas of Glycine max: A guide to the soybean transcriptome 
BMC Plant Biology  2010;10:160.
Background
Next generation sequencing is transforming our understanding of transcriptomes. It can determine the expression level of transcripts with a dynamic range of over six orders of magnitude from multiple tissues, developmental stages or conditions. Patterns of gene expression provide insight into functions of genes with unknown annotation.
Results
The RNA Seq-Atlas presented here provides a record of high-resolution gene expression in a set of fourteen diverse tissues. Hierarchical clustering of transcriptional profiles for these tissues suggests three clades with similar profiles: aerial, underground and seed tissues. We also investigate the relationship between gene structure and gene expression and find a correlation between gene length and expression. Additionally, we find dramatic tissue-specific gene expression of both the most highly-expressed genes and the genes specific to legumes in seed development and nodule tissues. Analysis of the gene expression profiles of over 2,000 genes with preferential gene expression in seed suggests there are more than 177 genes with functional roles that are involved in the economically important seed filling process. Finally, the Seq-atlas also provides a means of evaluating existing gene model annotations for the Glycine max genome.
Conclusions
This RNA-Seq atlas extends the analyses of previous gene expression atlases performed using Affymetrix GeneChip technology and provides an example of new methods to accommodate the increase in transcriptome data obtained from next generation sequencing. Data contained within this RNA-Seq atlas of Glycine max can be explored at http://www.soybase.org/soyseq.
doi:10.1186/1471-2229-10-160
PMCID: PMC3017786  PMID: 20687943
2.  A nematode demographics assay in transgenic roots reveals no significant impacts of the Rhg1 locus LRR-Kinase on soybean cyst nematode resistance 
BMC Plant Biology  2010;10:104.
Background
Soybean cyst nematode (Heterodera glycines, SCN) is the most economically damaging pathogen of soybean (Glycine max) in the U.S. The Rhg1 locus is repeatedly observed as the quantitative trait locus with the greatest impact on SCN resistance. The Glyma18g02680.1 gene at the Rhg1 locus that encodes an apparent leucine-rich repeat transmembrane receptor-kinase (LRR-kinase) has been proposed to be the SCN resistance gene, but its function has not been confirmed. Generation of fertile transgenic soybean lines is difficult but methods have been published that test SCN resistance in transgenic roots generated with Agrobacterium rhizogenes.
Results
We report use of artificial microRNA (amiRNA) for gene silencing in soybean, refinements to transgenic root SCN resistance assays, and functional tests of the Rhg1 locus LRR-kinase gene. A nematode demographics assay monitored infecting nematode populations for their progress through developmental stages two weeks after inoculation, as a metric for SCN resistance. Significant differences were observed between resistant and susceptible control genotypes. Introduction of the Rhg1 locus LRR-kinase gene (genomic promoter/coding region/terminator; Peking/PI 437654-derived SCN-resistant source), into rhg1- SCN-susceptible plant lines carrying the resistant-source Rhg4+ locus, provided no significant increases in SCN resistance. Use of amiRNA to reduce expression of the LRR-kinase gene from the Rhg1 locus of Fayette (PI 88788 source of Rhg1) also did not detectably alter resistance to SCN. However, silencing of the LRR-kinase gene did have impacts on root development.
Conclusion
The nematode demographics assay can expedite testing of transgenic roots for SCN resistance. amiRNAs and the pSM103 vector that drives interchangeable amiRNA constructs through a soybean polyubiqutin promoter (Gmubi), with an intron-GFP marker for detection of transgenic roots, may have widespread use in legume biology. Studies in which expression of the Rhg1 locus LRR-kinase gene from different resistance sources was either reduced or complemented did not reveal significant impacts on SCN resistance.
doi:10.1186/1471-2229-10-104
PMCID: PMC3095272  PMID: 20529370
3.  Complementary genetic and genomic approaches help characterize the linkage group I seed protein QTL in soybean 
BMC Plant Biology  2010;10:41.
Background
The nutritional and economic value of many crops is effectively a function of seed protein and oil content. Insight into the genetic and molecular control mechanisms involved in the deposition of these constituents in the developing seed is needed to guide crop improvement. A quantitative trait locus (QTL) on Linkage Group I (LG I) of soybean (Glycine max (L.) Merrill) has a striking effect on seed protein content.
Results
A soybean near-isogenic line (NIL) pair contrasting in seed protein and differing in an introgressed genomic segment containing the LG I protein QTL was used as a resource to demarcate the QTL region and to study variation in transcript abundance in developing seed. The LG I QTL region was delineated to less than 8.4 Mbp of genomic sequence on chromosome 20. Using Affymetrix® Soy GeneChip and high-throughput Illumina® whole transcriptome sequencing platforms, 13 genes displaying significant seed transcript accumulation differences between NILs were identified that mapped to the 8.4 Mbp LG I protein QTL region.
Conclusions
This study identifies gene candidates at the LG I protein QTL for potential involvement in the regulation of protein content in the soybean seed. The results demonstrate the power of complementary approaches to characterize contrasting NILs and provide genome-wide transcriptome insight towards understanding seed biology and the soybean genome.
doi:10.1186/1471-2229-10-41
PMCID: PMC2848761  PMID: 20199683

Results 1-3 (3)