SGMD: the Soybean Genomics and Microarray Database

Genetic and Genomic Resources for Soybean Breeding Research

Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.

Expanding Omics Resources for Improvement of Soybean Seed Composition Traits

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.

SFGD: a comprehensive platform for mining functional information from soybean transcriptome data and its use in identifying acyl-lipid metabolism pathways

BACKGROUND

Soybean (Glycine max L.) is one of the world's most important leguminous crops producing high-quality protein and oil. Increasing the relative oil concentration in soybean seeds is many researchers' goal, but a complete analysis platform of functional annotation for the genes involved in the soybean acyl-lipid pathway is still lacking. Following the success of soybean whole-genome sequencing, functional annotation has become a major challenge for the scientific community. Whole-genome transcriptome analysis is a powerful way to predict genes with biological functions. It is essential to build a comprehensive analysis platform for integrating soybean whole-genome sequencing data, the available transcriptome data and protein information. This platform could also be used to identify acyl-lipid metabolism pathways.

DESCRIPTION

In this study, we describe our construction of the Soybean Functional Genomics Database (SFGD) using Generic Genome Browser (Gbrowse) as the core platform. We integrated microarray expression profiling with 255 samples from 14 groups' experiments and mRNA-seq data with 30 samples from four groups' experiments, including spatial and temporal transcriptome data for different soybean development stages and environmental stresses. The SFGD includes a gene co-expression regulatory network containing 23,267 genes and 1873 miRNA-target pairs, and a group of acyl-lipid pathways containing 221 enzymes and more than 1550 genes. The SFGD also provides some key analysis tools, i.e. BLAST search, expression pattern search and cis-element significance analysis, as well as gene ontology information search and single nucleotide polymorphism display.

CONCLUSION

The SFGD is a comprehensive database integrating genome and transcriptome data, and also for soybean acyl-lipid metabolism pathways. It provides useful toolboxes for biologists to improve the accuracy and robustness of soybean functional genomics analysis, further improving understanding of gene regulatory networks for effective crop improvement. The SFGD is publically accessible at http://bioinformatics.cau.edu.cn/SFGD/, with all data available for downloading.

Large-scale analysis of differential gene expression in coffee genotypes resistant and susceptible to leaf miner-toward the identification of candidate genes for marker assisted-selection

BACKGROUND

A successful development of herbivorous insects into plant tissues depends on coordination of metabolic processes. Plants have evolved complex mechanisms to recognize such attacks, and to trigger a defense response. To understand the transcriptional basis of this response, we compare gene expression profiles of two coffee genotypes, susceptible and resistant to leaf miner (Leucoptera coffella). A total of 22000 EST sequences from the Coffee Genome Database were selected for a microarray analysis. Fluorescence probes were synthesized using mRNA from the infested and non-infested coffee plants. Array hybridization, scanning and data normalization were performed using Nimble Scan® e ArrayStar® platforms. Genes with foldchange values +/-2 were considered differentially expressed. A validation of 18 differentially expressed genes was performed in infected plants using qRT-PCR approach.

RESULTS

The microarray analysis indicated that resistant plants differ in gene expression profile. We identified relevant transcriptional changes in defense strategies before insect attack. Expression changes (>2.00-fold) were found in resistant plants for 2137 genes (1266 up-regulated and 873 down-regulated). Up-regulated genes include those responsible for defense mechanisms, hypersensitive response and genes involved with cellular function and maintenance. Also, our analyses indicated that differential expression profiles between resistant and susceptible genotypes are observed in the absence of leaf-miner, indicating that defense is already build up in resistant plants, as a priming mechanism. Validation of selected genes pointed to four selected genes as suitable candidates for markers in assisted-selection of novel cultivars.

CONCLUSIONS

Our results show evidences that coffee defense responses against leaf-miner attack are balanced with other cellular functions. Also analyses suggest a major metabolic reconfiguration that highlights the complexity of this response.

Recent achievement in gene cloning and functional genomics in soybean

Soybean is a model plant for photoperiodism as well as for symbiotic nitrogen fixation. However, a rather low efficiency in soybean transformation hampers functional analysis of genes isolated from soybean. In comparison, rapid development and progress in flowering time and photoperiodic response have been achieved in Arabidopsis and rice. As the soybean genomic information has been released since 2008, gene cloning and functional genomic studies have been revived as indicated by successfully characterizing genes involved in maturity and nematode resistance. Here, we review some major achievements in the cloning of some important genes and some specific features at genetic or genomic levels revealed by the analysis of functional genomics of soybean.

Recent developments of genomic research in soybean

Soybean is an important cash crop with unique and important traits such as the high seed protein and oil contents, and the ability to perform symbiotic nitrogen fixation. A reference genome of cultivated soybeans was established in 2010, followed by whole-genome re-sequencing of wild and cultivated soybean accessions. These efforts revealed unique features of the soybean genome and helped to understand its evolution. Mapping of variations between wild and cultivated soybean genomes were performed. These genomic variations may be related to the process of domestication and human selection. Wild soybean germplasms exhibited high genomic diversity and hence may be an important source of novel genes/alleles. Accumulation of genomic data will help to refine genetic maps and expedite the identification of functional genes. In this review, we summarize the major findings from the whole-genome sequencing projects and discuss the possible impacts on soybean researches and breeding programs. Some emerging areas such as transcriptomic and epigenomic studies will be introduced. In addition, we also tabulated some useful bioinformatics tools that will help the mining of the soybean genomic data.

Soybean Knowledge Base (SoyKB): a web resource for soybean translational genomics

BACKGROUND

Soybean Knowledge Base (SoyKB) is a comprehensive all-inclusive web resource for soybean translational genomics. SoyKB is designed to handle the management and integration of soybean genomics, transcriptomics, proteomics and metabolomics data along with annotation of gene function and biological pathway. It contains information on four entities, namely genes, microRNAs, metabolites and single nucleotide polymorphisms (SNPs).

METHODS

SoyKB has many useful tools such as Affymetrix probe ID search, gene family search, multiple gene/metabolite search supporting co-expression analysis, and protein 3D structure viewer as well as download and upload capacity for experimental data and annotations. It has four tiers of registration, which control different levels of access to public and private data. It allows users of certain levels to share their expertise by adding comments to the data. It has a user-friendly web interface together with genome browser and pathway viewer, which display data in an intuitive manner to the soybean researchers, producers and consumers.

CONCLUSIONS

SoyKB addresses the increasing need of the soybean research community to have a one-stop-shop functional and translational omics web resource for information retrieval and analysis in a user-friendly way. SoyKB can be publicly accessed at http://soykb.org/.

Mapping cell fate decisions that occur during soybean defense responses

The soybean defense response to the soybean cyst nematode was used as a model to map at cellular resolution its genotype-defined cell fate decisions occurring during its resistant reactions. The defense responses occur at the site of infection, a nurse cell known as the syncytium. Two major genotype-defined defense responses exist, the G. max ([Peking])- and G. max ([PI 88788])-types. Resistance in G. max ([Peking]) is potent and rapid, accompanied by the formation of cell wall appositions (CWAs), structures known to perform important defense roles. In contrast, defense occurs by a potent but more prolonged reaction in G. max ([PI 88788]), lacking CWAs. Comparative transcriptomic analyses with confirmation by Illumina® deep sequencing were organized through a custom-developed application, Pathway Analysis and Integrated Coloring of Experiments (PAICE) that presents gene expression of these cytologically and developmentally distinct defense responses using the Kyoto Encyclopedia of Genes and Genomes (KEGG) framework. The analyses resulted in the generation of 1,643 PAICE pathways, allowing better understanding of gene activity across all chromosomes. Analyses of the rhg1 resistance locus, defined within a 67 kb region of DNA demonstrate expression of an amino acid transporter and an α soluble NSF attachment protein gene specifically in syncytia undergoing their defense responses.

Microarray Detection Call Methodology as a Means to Identify and Compare Transcripts Expressed within Syncytial Cells from Soybean (Glycine max) Roots Undergoing Resistant and Susceptible Reactions to the Soybean Cyst Nematode (Heterodera glycines)

Background. A comparative microarray investigation was done using detection call methodology (DCM) and differential expression analyses. The goal was to identify genes found in specific cell populations that were eliminated by differential expression analysis due to the nature of differential expression methods. Laser capture microdissection (LCM) was used to isolate nearly homogeneous populations of plant root cells. Results. The analyses identified the presence of 13,291 transcripts between the 4 different sample types. The transcripts filtered down into a total of 6,267 that were detected as being present in one or more sample types. A comparative analysis of DCM and differential expression methods showed a group of genes that were not differentially expressed, but were expressed at detectable amounts within specific cell types. Conclusion. The DCM has identified patterns of gene expression not shown by differential expression analyses. DCM has identified genes that are possibly cell-type specific and/or involved in important aspects of plant nematode interactions during the resistance response, revealing the uniqueness of a particular cell population at a particular point during its differentiation process.

Syncytium gene expression in Glycine max([PI 88788]) roots undergoing a resistant reaction to the parasitic nematode Heterodera glycines

The plant parasitic nematode, Heterodera glycines is the major pathogen of Glycine max (soybean). H. glycines accomplish parasitism by creating a nurse cell known as the syncytium from which it feeds. The syncytium undergoes two developmental phases. The first is a parasitism phase where feeding sites are selected, initiating the development of the syncytium. During this earlier phase (1-4 days post infection), syncytia undergoing resistant and susceptible reactions appear the same. The second phase is when the resistance response becomes evident (between 4 and 6dpi) and is completed by 9dpi. Analysis of the resistant reaction of G. max genotype PI 88788 (G. max([PI 88788])) to H. glycines population NL1-RHg/HG-type 7 (H. glycines([NL1-RHg/HG-type 7])) is accomplished by laser microdissection of syncytia at 3, 6 and 9dpi. Comparative analyses are made to pericycle and their neighboring cells isolated from mock-inoculated roots. These analyses reveal induced levels of the jasmonic acid biosynthesis and 13-lipoxygenase pathways. Direct comparative analyses were also made of syncytia at 6 days post infection to those at 3dpi (base line). The comparative analyses were done to identify localized gene expression that characterizes the resistance phase of the resistant reaction. The most highly induced pathways include components of jasmonic acid biosynthesis, 13-lipoxygenase pathway, S-adenosyl methionine pathway, phenylpropanoid biosynthesis, suberin biosynthesis, adenosylmethionine biosynthesis, ethylene biosynthesis from methionine, flavonoid biosynthesis and the methionine salvage pathway. In comparative analyses of 9dpi to 6dpi (base line), these pathways, along with coumarin biosynthesis, cellulose biosynthesis and homogalacturonan degradation are induced. The experiments presented here strongly implicate the jasmonic acid defense pathway as a factor involved in the localized resistant reaction of G. max([PI 88788]) to H. glycines([NL1-RHg/HG-type 7]).

A gene expression analysis of syncytia laser microdissected from the roots of the Glycine max (soybean) genotype PI 548402 (Peking) undergoing a resistant reaction after infection by Heterodera glycines (soybean cyst nematode)

The syncytium is a nurse cell formed within the roots of Glycine max by the plant parasitic nematode Heterodera glycines. Its development and maintenance are essential for nematode survival. The syncytium appears to undergo two developmental phases during its maturation into a functional nurse cell. The first phase is a parasitism phase where the nematode establishes the molecular circuitry that during the second phase ensures a compatible interaction with the plant cell. The cytological features of syncytia undergoing susceptible or resistant reactions appear the same during the parasitism phase. Depending on the outcome of any defense response, the second phase is a period of syncytium maintenance (susceptible reaction) or failure (resistant reaction). In the analyses presented here, the localized gene expression occurring at the syncytium during the resistant reaction was studied. This was accomplished by isolating syncytial cells from Glycine max genotype Peking (PI 548402) by laser capture microdissection. Microarray analyses using the Affymetrix soybean GeneChip directly compared Peking syncytia undergoing a resistant reaction to those undergoing a susceptible reaction during the parasitism phase of the resistant reaction. Those analyses revealed lipoxygenase-9 and lipoxygenase-4 as the most highly induced genes in the resistant reaction. The analysis also identified induced levels of components of the phenylpropanoid pathway. These genes included phenylalanine ammonia lyase, chalcone isomerase, isoflavone reductase, cinnamoyl-CoA reductase and caffeic acid O-methyltransferase. The presence of induced levels of these genes implies the importance of jasmonic acid and phenylpropanoid signaling pathways locally at the site of the syncytium during the resistance phase of the resistant reaction. The analysis also identified highly induced levels of four S-adenosylmethionine synthetase genes, the EARLY-RESPONSIVE TO DEHYDRATION 2 gene and the 14-3-3 gene known as GENERAL REGULATORY FACTOR 2. Subsequent analyses studied microdissected syncytial cells at 3, 6 and 9 days post infection (dpi) during the course of the resistant reaction, resulting in the identification of signature gene expression profiles at each time point in a single G. max genotype, Peking.

A correlation between host-mediated expression of parasite genes as tandem inverted repeats and abrogation of development of female Heterodera glycines cyst formation during infection of Glycine max

Host-mediated (hm) expression of parasite genes as tandem inverted repeats was investigated as a means to abrogate the formation of mature Heterodera glycines (soybean cyst nematode) female cysts during its infection of Glycine max (soybean). A Gateway-compatible hm plant transformation system was developed specifically for these experiments in G. max. Three steps then were taken to identify H. glycines candidate genes. First, a pool of 150 highly conserved H. glycines homologs of genes having lethal mutant phenotypes or phenocopies from the free living nematode Caenorhabditis elegans were identified. Second, annotation of those 150 genes on the Affymetrix soybean GeneChip allowed for the identification of a subset of 131 genes whose expression could be monitored during the parasitic phase of the H. glycines life cycle. Third, a microarray analyses identified a core set of 32 genes with induced expression (>2.0-fold, log base 2) during the parasitic stages of infection. H. glycines homologs of small ribosomal protein 3a and 4 (Hg-rps-3a [accession number CB379877] and Hg-rps-4 [accession number CB278739]), synaptobrevin (Hg-snb-1 [accession number BF014436]) and a spliceosomal SR protein (Hg-spk-1 [accession number BI451523.1]) were tested for functionality in hm expression studies. Effects on H. glycines development were observed 8 days after infection. Experiments demonstrated that 81-93% fewer females developed on transgenic roots containing the genes engineered as tandem inverted repeats. The effect resembles RNA interference. The methodology has been used here as an alternative approach to engineer resistance to H. glycines.

Population-specific gene expression in the plant pathogenic nematode Heterodera glycines exists prior to infection and during the onset of a resistant or susceptible reaction in the roots of the Glycine max genotype Peking

BACKGROUND

A single Glycine max (soybean) genotype (Peking) reacts differently to two different populations of Heterodera glycines (soybean cyst nematode) within the first twelve hours of infection during resistant (R) and susceptible (S) reactions. This suggested that H. glycines has population-specific gene expression signatures. A microarray analysis of 7539 probe sets representing 7431 transcripts on the Affymetrix soybean GeneChip were used to identify population-specific gene expression signatures in pre-infective second stage larva (pi-L2) prior to their infection of Peking. Other analyses focused on the infective L2 at 12 hours post infection (i-L2(12h)), and the infective sedentary stages at 3 days post infection (i-L2(3d)) and 8 days post infection (i-L2/L3(8d)).

RESULTS

Differential expression and false discovery rate (FDR) analyses comparing populations of pi-L2 (i.e., incompatible population, NL1-RHg to compatible population, TN8) identified 71 genes that were induced in NL1-RHg as compared to TN8. These genes included putative gland protein G23G12, putative esophageal gland protein Hgg-20 and arginine kinase. The comparative analysis of pi-L2 identified 44 genes that were suppressed in NL1-RHg as compared to TN8. These genes included a different Hgg-20 gene, an EXPB1 protein and a cuticular collagen. By 12 h, there were 7 induced genes and 0 suppressed genes in NL1-RHg. By 3d, there were 9 induced and 10 suppressed genes in NL1-RHg. Substantial changes in gene expression became evident subsequently. At 8d there were 13 induced genes in NL1-RHg. This included putative gland protein G20E03, ubiquitin extension protein, putative gland protein G30C02 and beta-1,4 endoglucanase. However, 1668 genes were found to be suppressed in NL1-RHg. These genes included steroid alpha reductase, serine proteinase and a collagen protein.

CONCLUSION

These analyses identify a genetic expression signature for these two populations both prior to and subsequently as they undergo an R or S reaction. The identification of genes like steroid alpha reductase and serine proteinase that are involved in feeding and nutritional uptake as being highly suppressed during the R response at 8d may indicate genes that the plant is targeting. The analyses also identified numerous putative parasitism genes that are differentially expressed. The 1668 genes that are suppressed in NL1-RHg, and hence induced in TN8 may represent genes that are important during the parasitic stages of H. glycines development. The potential for different arrays of putative parasitism genes to be expressed in different nematode populations may indicate how H. glycines evolve mechanisms to overcome resistance.

SoyXpress: a database for exploring the soybean transcriptome

BACKGROUND

Experiments using whole transcriptome microarrays produce massive amounts of data. To gain a comprehensive understanding of this gene expression data it needs to be integrated with other available information such as gene function and metabolic pathways. Bioinformatics tools are essential to handle, organize and interpret the results. To date, no database provides whole transcriptome analysis capabilities integrated with terms describing biological functions for soybean (Glycine max (L) Merr.). To this end we have developed SoyXpress, a relational database with a suite of web interfaces to allow users to easily retrieve data and results of the microarray experiment with cross-referenced annotations of expressed sequence tags (EST) and hyperlinks to external public databases. This environment makes it possible to explore differences in gene expression, if any, between for instance transgenic and non-transgenic soybean cultivars and to interpret the results based on gene functional annotations to determine any changes that could potentially alter biological processes.

RESULTS

SoyXpress is a database designed for exploring the soybean transcriptome. Currently SoyXpress houses 380,095 soybean Expressed Sequence Tags (EST), linked with metabolic pathways, Gene Ontology terms, SwissProt identifiers and Affymetrix gene expression data. Array data is presently available from an experiment profiling global gene expression of three conventional and two genetically engineered soybean cultivars. The microarray data is linked with the sequence data, for maximum knowledge extraction. SoyXpress is implemented in MySQL and uses a Perl CGI interface.

CONCLUSION

SoyXpress is designed for the purpose of exploring potential transcriptome differences in different plant genotypes, including genetically modified crops. Soybean EST sequences, microarray and pathway data as well as searchable and browsable gene ontology are integrated and presented. SoyXpress is publicly accessible at http://soyxpress.agrenv.mcgill.ca.

Protease inhibitor expression in soybean roots exhibiting susceptible and resistant interactions with soybean cyst nematode

Protease inhibitors play a role in regulating proteases during cellular development and in plant defense. We cloned and sequenced cDNA encoding six protease inhibitors expressed in soybean roots infected with soybean cyst nematode (SCN) and determined their expression patterns. Four of these protease inhibitors are novel and have not been reported previously. Using RT-PCR, we measured the relative transcript levels of each protease inhibitor in roots of the soybean cv. Peking inoculated with either SCN TN8 to examine the expression of protease inhibitors during the susceptible interaction or with SCN NL1-RHg representing the resistant interaction. Within 12 to 24 hours, mRNA transcripts encoding five of the six protease inhibitors were more highly elevated in soybean roots exhibiting the susceptible interaction than the resistant interaction. Transcripts encoding two protease inhibitors possessing Kunitz trypsin inhibitor domains were induced 37- and 27-fold in the susceptible interaction within 1 dpi, but were induced only 5- to 7-fold in roots displaying the resistant interaction. Our results indicate that soybean roots recognize differences between these two SCN populations before the nematodes initiate a feeding site, and accordingly the roots express transcripts encoding soybean protease inhibitors differentially. These transcripts were generally less abundant in roots exhibiting the resistant interaction.

A time-course comparative microarray analysis of an incompatible and compatible response by Glycine max (soybean) to Heterodera glycines (soybean cyst nematode) infection

The development of an infection in soybean [Glycine max L. cultivar (cv.) Peking] roots by incompatible (I) and compatible (C) populations of soybean cyst nematode (SCN) (Heterodera glycines) was assayed using an AffymetriX soybean GeneChip. This time-course microarray analysis, using 37,744 probe sets, measured transcript abundance during I and C. These analyses reveal that infection by individual I and C H. glycines populations influence the transcription of G. max genes differently. A substantial difference in gene expression is present between I and C at 12 h post infection. Thus, G. max can differentiate between I and C nematode populations even before they have begun to select their feeding sites. The microarray analysis identified genes induced earlier in infection during I than C. MA also identified amplitude differences in transcript abundance between I and C reactions. Some of the probe sets measuring increased transcript levels during I represented no apical meristem (NAM) and WRKY transcription factors as well as NBS-LRR kinases. Later during I, heat shock protein (HSPs) probe sets (i.e. HSP90, HSP70, ClpB/HSP101) measured increased transcript abundance. These results demonstrate that G. max roots respond very differently to the different H. glycines races even before their feeding site selection has occurred. The ability of G. max to engage an I reaction, thus, appears to be dependent on the ability of root cells to recognize the different races of H. glycines because these experiments were conducted in the identical G. max genetic background.

Laser capture microdissection (LCM) and comparative microarray expression analysis of syncytial cells isolated from incompatible and compatible soybean (Glycine max) roots infected by the soybean cyst nematode (Heterodera glycines)

Syncytial cells in soybean (Glycine max cultivar [cv.] Peking) roots infected by incompatible and compatible populations of soybean cyst nematode (SCN [Heterodera glycines]) were collected using laser capture microdissection (LCM). Gene transcript abundance was assayed using Affymetrix soybean GeneChips, each containing 37,744 probe sets. Our analyses identified differentially expressed genes in syncytial cells that are not differentially expressed in the whole root analyses. Therefore, our results show that the mass of transcriptional activity occurring in the whole root is obscuring identification of transcriptional events occurring within syncytial cells. In syncytial cells from incompatible roots at three dpi, genes encoding lipoxygenase (LOX), heat shock protein (HSP) 70, superoxidase dismutase (SOD) were elevated almost tenfold or more, while genes encoding several transcription factors and DNA binding proteins were also elevated, albeit at lower levels. In syncytial cells formed during the compatible interaction at three dpi, genes encoding prohibitin, the epsilon chain of ATP synthase, allene oxide cyclase and annexin were more abundant. By 8 days, several genes of unknown function and genes encoding a germin-like protein, peroxidase, LOX, GAPDH, 3-deoxy-D-arabino-heptolosonate 7-phosphate synthase, ATP synthase and a thioesterase were abundantly expressed. These observations suggest that gene expression is different in syncytial cells as compared to whole roots infected with nematodes. Our observations also show that gene expression is different between syncytial cells that were isolated from incompatible and compatible roots and that gene expression is changing over the course of syncytial cell development as it matures into a functional feeding site.

A decline in transcript abundance for Heterodera glycines homologs of Caenorhabditis elegans uncoordinated genes accompanies its sedentary parasitic phase

Background

Heterodera glycines (soybean cyst nematode [SCN]), the major pathogen of Glycine max (soybean), undergoes muscle degradation (sarcopenia) as it becomes sedentary inside the root. Many genes encoding muscular and neuromuscular components belong to the uncoordinated (unc) family of genes originally identified in Caenorhabditis elegans. Previously, we reported a substantial decrease in transcript abundance for Hg-unc-87, the H. glycines homolog of unc-87 (calponin) during the adult sedentary phase of SCN. These observations implied that changes in the expression of specific muscle genes occurred during sarcopenia.

Results

We developed a bioinformatics database that compares expressed sequence tag (est) and genomic data of C. elegans and H. glycines (CeHg database). We identify H. glycines homologs of C. elegans unc genes whose protein products are involved in muscle composition and regulation. RT-PCR reveals the transcript abundance of H. glycines unc homologs at mobile and sedentary stages of its lifecycle. A prominent reduction in transcript abundance occurs in samples from sedentary nematodes for homologs of actin, unc-60B (cofilin), unc-89, unc-15 (paromyosin), unc-27 (troponin I), unc-54 (myosin), and the potassium channel unc-110 (twk-18). Less reduction is observed for the focal adhesion complex gene Hg-unc-97.

Conclusion

The CeHg bioinformatics database is shown to be useful in identifying homologs of genes whose protein products perform roles in specific aspects of H. glycines muscle biology. Our bioinformatics comparison of C. elegans and H. glycines genomic data and our Hg-unc-87 expression experiments demonstrate that the transcript abundance of specific H. glycines homologs of muscle gene decreases as the nematode becomes sedentary inside the root during its parasitic feeding stages.

Identification of Heterodera glycines (soybean cyst nematode [SCN]) cDNA sequences with high identity to those of Caenorhabditis elegans having lethal mutant or RNAi phenotypes

The soybean cyst nematode (SCN; Heterodera glycines) is a devastating obligate parasite of Glycine max (soybean) causing one billion dollars in losses to the US economy per year and over ten billion dollars in losses worldwide. While much is understood about the pathology of H. glycines, its genome sequence is not well characterized or fully sequenced. We sought to create bioinformatic tools to mine the H. glycines nucleotide database. One way is to use a comparative genomics approach by anchoring our analysis with an organism, like the free-living nematode Caenorhabditis elegans. Unlike H. glycines, the C. elegans genome is fully sequenced and is well characterized with a number of lethal genes identified through experimental methods. We compared an EST database of H. glycines with the C. elegans genome. Our goal was identifying genes that may be essential for H. glycines survival and would serve as an automated pipeline for RNAi studies to both study and control H. glycines. Our analysis yielded a total of nearly 8334 conserved genes between H. glycines and C. elegans. Of these, 1508 have lethal phenotypes/phenocopies in C. elegans. RNAi of a conserved ribosomal gene from H. glycines (Hg-rps-23) yielded dead and dying worms as shown by positive Sytox fluorescence. Endogenous Hg-rps-23 exhibited typical RNA silencing as shown by RT-PCR. However, an unrelated gene Hg-unc-87 did not exhibit RNA silencing in the Hg-rps-23 dsRNA-treated worms, demonstrating the specificity of the silencing.

DNA microarray technology in toxicogenomics of aquatic models: methods and applications

Toxicogenomics represents the merging of toxicology with genomics and bioinformatics to investigate biological functions of genome in response to environmental contaminants. Aquatic species have traditionally been used as models in toxicology to characterize the actions of environmental stresses. Recent completion of the DNA sequencing for several fish species has spurred the development of DNA microarrays allowing investigators access to toxicogenomic approaches. However, since microarray technology is thus far limited to only a few aquatic species and derivation of biological meaning from microarray data is highly dependent on statistical arguments, the full potential of microarray in aquatic species research has yet to be realized. Herein we review some of the issues related to construction, probe design, statistical and bioinformatical data analyses, and current applications of DNA microarrays. As a model a recently developed medaka (Oryzias latipes) oligonucleotide microarray was described to highlight some of the issues related to array technology and its application in aquatic species exposed to hypoxia. Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology. Microarray applications in aquatic toxicogenomics will range from the discovery of diagnostic biomarkers, to establishment of stress-specific signatures and molecular pathways hallmarking the adaptation to new environmental conditions.

Timecourse microarray analyses reveal global changes in gene expression of susceptible Glycine max (soybean) roots during infection by Heterodera glycines (soybean cyst nematode)

Changes in gene expression within roots of Glycine max (soybean), cv. Kent, susceptible to infection by Heterodera glycines (the soybean cyst nematode [SCN]), at 6, 12, and 24 h, and 2, 4, 6, and 8 days post-inoculation were monitored using microarrays containing more than 6,000 cDNA inserts. Replicate, independent biological samples were examined at each time point. Gene expression was analyzed statistically using T-tests, ANOVA, clustering algorithms, and online analytical processing (OLAP). These analyses allow the user to query the data in several ways without importing the data into third-party software. RT-PCR confirmed that WRKY6 transcription factor, trehalose phosphate synthase, EIF4a, Skp1, and CLB1 were differentially induced across most time-points. Other genes induced across most timepoints included lipoxygenase, calmodulin, phospholipase C, metallothionein-like protein, and chalcone reductase. RT-PCR demonstrated enhanced expression during the first 12 h of infection for Kunitz trypsin inhibitor and sucrose synthase. The stress-related gene, SAM-22, phospholipase D and 12-oxophytodienoate reductase were also induced at the early time-points. At 6 and 8 dpi there was an abundance of transcripts expressed that encoded genes involved in transcription and protein synthesis. Some of those genes included ribosomal proteins, and initiation and elongation factors. Several genes involved in carbon metabolism and transport were also more abundant. Those genes included glyceraldehyde 3-phosphate dehydrogenase, fructose-bisphosphate aldolase and sucrose synthase. These results identified specific changes in gene transcript levels triggered by infection of susceptible soybean roots by SCN.

Tomato Expression Database (TED): a suite of data presentation and analysis tools

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at .

Online analytical processing (OLAP): a fast and effective data mining tool for gene expression databases

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB.

FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression

BACKGROUND

While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.

RESULTS

We describe a bioinformatics pipeline known as FunnyBase that has been used to store, annotate, and analyze 40,363 expressed sequence tags (ESTs) from the heart and liver of the fish, Fundulus heteroclitus. Primary annotations based on sequence similarity are linked to networks of systematic annotation in Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) and can be queried and computationally utilized in downstream analyses. Steps are taken to ensure that the annotation is self-consistent and that the structure of GO is used to identify higher level functions that may not be annotated directly. An integrated framework for cDNA library production, sequencing, quality control, expression data generation, and systems-level analysis is presented and utilized. In a case study, a set of genes, that had statistically significant regression between gene expression levels and environmental temperature along the Atlantic Coast, shows a statistically significant (P < 0.001) enrichment in genes associated with amine metabolism.

CONCLUSION

The methods described have application for functional genomics studies, particularly among non-model organisms. The web interface for FunnyBase can be accessed at http://genomics.rsmas.miami.edu/funnybase/super_craw4/. Data and source code are available by request at jpaschall@bioinfobase.umkc.edu.