Eric Stahlberg

Compilation of mRNA Polyadenylation Signals in Arabidopsis Revealed a New Signal Element and Potential Secondary Structures

Using a novel program, SignalSleuth, and a database containing authenticated polyadenylation [poly(A)] sites, we analyzed the composition of mRNA poly(A) signals in Arabidopsis (Arabidopsis thaliana), and reevaluated previously described cis-elements within the 3′-untranslated (UTR) regions, including near upstream elements and far upstream elements. As predicted, there are absences of high-consensus signal patterns. The AAUAAA signal topped the near upstream elements patterns and was found within the predicted location to only approximately 10% of 3′-UTRs. More importantly, we identified a new set, named cleavage elements, of poly(A) signals flanking both sides of the cleavage site. These cis-elements were not previously revealed by conventional mutagenesis and are contemplated as a cluster of signals for cleavage site recognition. Moreover, a single-nucleotide profile scan on the 3′-UTR regions unveiled a distinct arrangement of alternate stretches of U and A nucleotides, which led to a prediction of the formation of secondary structures. Using an RNA secondary structure prediction program, mFold, we identified three main types of secondary structures on the sequences analyzed. Surprisingly, these observed secondary structures were all interrupted in previously constructed mutations in these regions. These results will enable us to revise the current model of plant poly(A) signals and to develop tools to predict 3′-ends for gene annotation.

Large-Scale Identification of Expressed Sequence Tags Involved in Rice and Rice Blast Fungus Interaction

To better understand the molecular basis of the defense response against the rice blast fungus (Magnaporthe grisea), a large-scale expressed sequence tag (EST) sequencing approach was used to identify genes involved in the early infection stages in rice (Oryza sativa). Six cDNA libraries were constructed using infected leaf tissues harvested from 6 conditions: resistant, partially resistant, and susceptible reactions at both 6 and 24 h after inoculation. Two additional libraries were constructed using uninoculated leaves and leaves from the lesion mimic mutant spl11. A total of 68,920 ESTs were generated from 8 libraries. Clustering and assembly analyses resulted in 13,570 unique sequences from 10,934 contigs and 2,636 singletons. Gene function classification showed that 42% of the ESTs were predicted to have putative gene function. Comparison of the pathogen-challenged libraries with the uninoculated control library revealed an increase in the percentage of genes in the functional categories of defense and signal transduction mechanisms and cell cycle control, cell division, and chromosome partitioning. In addition, hierarchical clustering analysis grouped the eight libraries based on their disease reactions. A total of 7,748 new and unique ESTs were identified from our collection compared with the KOME full-length cDNA collection. Interestingly, we found that rice ESTs are more closely related to sorghum (Sorghum bicolor) ESTs than to barley (Hordeum vulgare), wheat (Triticum aestivum), and maize (Zea mays) ESTs. The large cataloged collection of rice ESTs in this study provides a solid foundation for further characterization of the rice defense response and is a useful public genomic resource for rice functional genomics studies.

Coiled-coil protein composition of 22 proteomes – differences and common themes in subcellular infrastructure and traffic control

BackgroundLong alpha-helical coiled-coil proteins are involved in diverse organizational and regulatory processes in eukaryotic cells. They provide cables and networks in the cyto- and nucleoskeleton, molecular scaffolds that organize membrane systems and tissues, motors, levers, rotating arms, and possibly springs. Mutations in long coiled-coil proteins have been implemented in a growing number of human diseases. Using the coiled-coil prediction program MultiCoil, we have previously identified all long coiled-coil proteins from the model plant Arabidopsis thaliana and have established a searchable Arabidopsis coiled-coil protein database.ResultsHere, we have identified all proteins with long coiled-coil domains from 21 additional fully sequenced genomes. Because regions predicted to form coiled-coils interfere with sequence homology determination, we have developed a sequence comparison and clustering strategy based on masking predicted coiled-coil domains. Comparing and grouping all long coiled-coil proteins from 22 genomes, the kingdom-specificity of coiled-coil protein families was determined. At the same time, a number of proteins with unknown function could be grouped with already characterized proteins from other organisms.ConclusionMultiCoil predicts proteins with extended coiled-coil domains (more than 250 amino acids) to be largely absent from bacterial genomes, but present in archaea and eukaryotes. The structural maintenance of chromosomes proteins and their relatives are the only long coiled-coil protein family clearly conserved throughout all kingdoms, indicating their ancient nature. Motor proteins, membrane tethering and vesicle transport proteins are the dominant eukaryote-specific long coiled-coil proteins, suggesting that coiled-coil proteins have gained functions in the increasingly complex processes of subcellular infrastructure maintenance and trafficking control of the eukaryotic cell.

Deep and comparative analysis of the mycelium and appressorium transcriptomes of Magnaporthe grisea using MPSS, RL-SAGE, and oligoarray methods

BackgroundRice blast, caused by the fungal pathogen Magnaporthe grisea, is a devastating disease causing tremendous yield loss in rice production. The public availability of the complete genome sequence of M. grisea provides ample opportunities to understand the molecular mechanism of its pathogenesis on rice plants at the transcriptome level. To identify all the expressed genes encoded in the fungal genome, we have analyzed the mycelium and appressorium transcriptomes using massively parallel signature sequencing (MPSS), robust-long serial analysis of gene expression (RL-SAGE) and oligoarray methods.ResultsThe MPSS analyses identified 12,531 and 12,927 distinct significant tags from mycelia and appressoria, respectively, while the RL-SAGE analysis identified 16,580 distinct significant tags from the mycelial library. When matching these 12,531 mycelial and 12,927 appressorial significant tags to the annotated CDS, 500 bp upstream and 500 bp downstream of CDS, 6,735 unique genes in mycelia and 7,686 unique genes in appressoria were identified. A total of 7,135 mycelium-specific and 7,531 appressorium-specific significant MPSS tags were identified, which correspond to 2,088 and 1,784 annotated genes, respectively, when matching to the same set of reference sequences. Nearly 85% of the significant MPSS tags from mycelia and appressoria and 65% of the significant tags from the RL-SAGE mycelium library matched to the M. grisea genome. MPSS and RL-SAGE methods supported the expression of more than 9,000 genes, representing over 80% of the predicted genes in M. grisea. About 40% of the MPSS tags and 55% of the RL-SAGE tags represent novel transcripts since they had no matches in the existing M. grisea EST collections. Over 19% of the annotated genes were found to produce both sense and antisense tags in the protein-coding region. The oligoarray analysis identified the expression of 3,793 mycelium-specific and 4,652 appressorium-specific genes. A total of 2,430 mycelial genes and 1,886 appressorial genes were identified by both MPSS and oligoarray.ConclusionThe comprehensive and deep transcriptome analysis by MPSS and RL-SAGE methods identified many novel sense and antisense transcripts in the M. grisea genome at two important growth stages. The differentially expressed transcripts that were identified, especially those specifically expressed in appressoria, represent a genomic resource useful for gaining a better understanding of the molecular basis of M. grisea pathogenicity. Further analysis of the novel antisense transcripts will provide new insights into the regulation and function of these genes in fungal growth, development and pathogenesis in the host plants.

Genome-Wide Identification of Arabidopsis Coiled-Coil Proteins and Establishment of the ARABI-COIL Database

Increasing evidence demonstrates the importance of long coiled-coil proteins for the spatial organization of cellular processes. Although several protein classes with long coiled-coil domains have been studied in animals and yeast, our knowledge about plant long coiled-coil proteins is very limited. The repeat nature of the coiled-coil sequence motif often prevents the simple identification of homologs of animal coiled-coil proteins by generic sequence similarity searches. As a consequence, counterparts of many animal proteins with long coiled-coil domains, like lamins, golgins, or microtubule organization center components, have not been identified yet in plants. Here, all Arabidopsis proteins predicted to contain long stretches of coiled-coil domains were identified by applying the algorithm MultiCoil to a genome-wide screen. A searchable protein database, ARABI-COIL (http://www.coiled-coil.org/arabidopsis), was established that integrates information on number, size, and position of predicted coiled-coil domains with subcellular localization signals, transmembrane domains, and available functional annotations. ARABI-COIL serves as a tool to sort and browse Arabidopsis long coiled-coil proteins to facilitate the identification and selection of candidate proteins of potential interest for specific research areas. Using the database, candidate proteins were identified for Arabidopsis membrane-bound, nuclear, and organellar long coiled-coil proteins.

RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection

Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (≥2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (≥10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.

Magnaporthe grisea Infection Triggers RNA Variation and Antisense Transcript Expression in Rice

Rice blast disease, caused by the fungal pathogen Magnaporthe grisea, is an excellent model system to study plant-fungal interactions and host defense responses. In this study, comprehensive analysis of the rice (Oryza sativa) transcriptome after M. grisea infection was conducted using robust-long serial analysis of gene expression. A total of 83,382 distinct 21-bp robust-long serial analysis of gene expression tags were identified from 627,262 individual tags isolated from the resistant (R), susceptible (S), and control (C) libraries. Sequence analysis revealed that the tags in the R and S libraries had a significant reduced matching rate to the rice genomic and expressed sequences in comparison to the C library. The high level of one-nucleotide mismatches of the R and S library tags was due to nucleotide conversions. The A-to-G and U-to-C nucleotide conversions were the most predominant types, which were induced in the M. grisea-infected plants. Reverse transcription-polymerase chain reaction analysis showed that expression of the adenine deaminase and cytidine deaminase genes was highly induced after inoculation. In addition, many antisense transcripts were induced in infected plants and expression of four antisense transcripts was confirmed by strand-specific reverse transcription-polymerase chain reaction. These results demonstrate that there is a series of dynamic and complex transcript modifications and changes in the rice transcriptome at the M. grisea early infection stages.

Hardware/Software Integration for FPGA-based All-Pairs Shortest-Paths

Field-programmable gate arrays (FPGAs) are being employed in high performance computing systems owing to their potential to accelerate a wide variety of long-running routines. Parallel FPGA-based designs often yield a very high speedup. Applications using these designs on reconfigurable supercomputers involve software on the system managing computation on the FPGA. To extract maximum performance from an FPGA design at the application level, it becomes necessary to minimize associated data movement costs on the system. We address this hardware/software integration challenge in the context of the all-pairs shortest-paths (APSP) problem in a directed graph. We employ a parallel FPGA-based design using a blocked algorithm to solve large instances of APSP. With appropriate design choices and optimizations, experimental results on the Cray XD1 show that the FPGA-based implementation sustains an application-level speedup of 15 over an optimized CPU-based implementation

A component-based implementation of multiple sequence alignment

This paper addresses the efficient execution of a Multiple Sequence Alignment (MSA) method, in particular the progressive alignment-based CLUSTAL W algorithm, on a cluster of workstations. We describe a scalable component-based implementation of CLUSTAL W program targeting distributed memory machines and multiple query workloads. We look at the effect of data caching on the performance of the data server. We present a distributed, persistent cache approach for caching intermediate results for reuse in subsequent or concurrent queries. Our initial results show that the cache-enabled CLUSTAL W program scales well on a cluster of workstations.

Improving performance of multiple sequence alignment analysis in multi-client environments

This paper is concerned with the efficient execution of multiple sequence alignment methods in a multiple client environment. Multiple sequence alignment (MSA) is a computationally expensive method, which is commonly used in computational and molecular biology. Large databases of protein and gene sequences are available to the scientific community. Oftentimes, these databases are accessed by multiple users to execute MSA queries. The data server has to handle multiple concurrent queries in such situations. We look at the effect of data caching on the performance of the data server. We describe an approach for caching intermediate results for reuse in subsequent or concurrent queries. We focus on progressive alignment-based strategies, in particular the CLUSTAL W algorithm. Our results for 350 sets of sequences show an average speedup of up to 2.5 is obtained by caching intermediate results. Our results also show that the cache-enabled CLUSTAL W program scales well on a SMP machine.