Malali Gowda

Robust-LongSAGE (RL-SAGE): A Substantially Improved LongSAGE Method for Gene Discovery and Transcriptome Analysis

Serial analysis of gene expression (SAGE) is a widely used technique for large-scale transcriptome analysis in mammalian systems. Recently, a modified version called LongSAGE (S. Saha, A.B. Sparks, C. Rago, V. Akmaev, C.J. Wang, B. Vogelstein, K.W. Kinzler [2002] Nat Biotechnol 20: 508-512) was reported by increasing tag length up to 21 bp. Although the procedures for these two methods are similar, a detailed protocol for LongSAGE library construction has not been reported yet, and several technical difficulties associated with concatemer cloning and purification have not been solved. In this study, we report a substantially improved LongSAGE method called Robust-LongSAGE, which has four major improvements when compared with the previously reported protocols. First, a small amount of mRNA (50 ng) was enough for a library construction. Second, enhancement of cDNA adapter and ditag formation was achieved through an extended ligation period (overnight). Third, only 20 ditag polymerase chain reactions were needed to obtain a complete library (up to 90% reduction compared with the original protocols). Fourth, concatemers were partially digested with NlaIII before cloning into vector (pZEro-1), greatly improving cloning efficiency. The significant contribution of Robust-LongSAGE is that it solved the major technical difficulties, such as low cloning efficiency and small insert sizes associated with existing SAGE and LongSAGE protocols. Using this protocol, one can generate two to three libraries, each containing over 4.5 million tags, within a month. We recently have constructed five libraries from rice (Oryza sativa), one from maize (Zea mays), and one from the rice blast fungus (Magnaporthe grisea).

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.

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.

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.

Identification and characterization of in planta-expressed secreted effector proteins from Magnaporthe oryzae that induce cell death in rice.

Interactions between rice and Magnaporthe oryzae involve the recognition of cellular components and the exchange of complex molecular signals from both partners. How these interactions occur in rice cells is still elusive. We employed robust-long serial analysis of gene expression, massively parallel signature sequencing, and sequencing by synthesis to examine transcriptome profiles of infected rice leaves. A total of 6,413 in planta-expressed fungal genes, including 851 genes encoding predicted effector proteins, were identified. We used a protoplast transient expression system to assess 42 of the predicted effector proteins for the ability to induce plant cell death. Ectopic expression assays identified five novel effectors that induced host cell death only when they contained the signal peptide for secretion to the extracellular space. Four of them induced cell death in Nicotiana benthamiana. Although the five effectors are highly diverse in their sequences, the physiological basis of cell death induced by each was similar. This study demonstrates that our integrative genomic approach is effective for the identification of in planta-expressed cell death-inducing effectors from M. oryzae that may play an important role facilitating colonization and fungal growth during infection.

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.

Advances in rice breeding, genetics and genomics

Summary Plant breeders are responsible for impressive gains incrop productivity. More than 50% of the increasedworld food output over the past 50 years could be at-tributed to improved varieties. Recent advances inmolecular biology, such as engineering disease andinsect resistance genes, will augment work by plantbreeders and provide traits that previously did not ex-ist in the germplasm, for example, sheath blight re-sistance in rice (Lin et al. 1995). Population growthis continuing at more than 2% annually in many de-veloping rice growing countries. To feed this grow-ing population, the growth rate of rice productionneeds to be accelerated. Innovative breeding methodsand the emerging tools of molecular and genome bi-ology must supplement the conventional breedingmethods in achieving the future rice breeding goals.Biotechnological tools accelerate rice breeding andbroaden the rice gene pool. Transformation usingalien genes from bacteria, fungi, protozoan, insects,animals and plant species allow breeders to accom-347

Genome-wide characterization of methylguanosine-capped and polyadenylated small RNAs in the rice blast fungus Magnaporthe oryzae

Small RNAs are well described in higher eukaryotes such as mammals and plants; however, knowledge in simple eukaryotes such as filamentous fungi is limited. In this study, we discovered and characterized methylguanosine-capped and polyadenylated small RNAs (CPA-sRNAs) by using differential RNA selection, full-length cDNA cloning and 454 transcriptome sequencing of the rice blast fungus Magnaporthe oryzae. This fungus causes blast, a devastating disease on rice, the principle food staple for over half the world’s population. CPA-sRNAs mapped primarily to the transcription initiation and termination sites of protein-coding genes and were positively correlated with gene expression, particularly for highly expressed genes including those encoding ribosomal proteins. Numerous CPA-sRNAs also mapped to rRNAs, tRNAs, snRNAs, transposable elements and intergenic regions. Many other 454 sequence reads could not be mapped to the genome; however, inspection revealed evidence for non-template additions and chimeric sequences. CPA-sRNAs were independently confirmed using a high affinity variant of eIF-4E to capture 5′-methylguanosine-capped RNA followed by 3′-RACE sequencing. These results expand the repertoire of small RNAs in filamentous fungi.

Use of robust-long serial analysis of gene expression to identify novel fungal and plant genes involved in host-pathogen interactions.

Identification of important transcripts from fungal pathogens and host plants is indispensable for full understanding the molecular events occurring during fungal-plant interactions. Recently, we developed an improved LongSAGE method called robust-long serial analysis of gene expression (RL-SAGE) for deep transcriptome analysis of fungal and plant genomes. Using this method, we made 10 RL-SAGE libraries from two plant species (Oryza sativa and Zea maize) and one fungal pathogen (Magnaporthe grisea). Many of the transcripts identified from these libraries were novel in comparison with their corresponding EST collections. Bioinformatic tools and databases for analyzing the RL-SAGE data were developed. Our results demonstrate that RL-SAGE is an effective approach for large-scale identification of expressed genes in fungal and plant genomes.

Draft Genome Sequence of Staphylococcus aureus 118 (ST772), a Major Disease Clone from India

We report the draft genome sequence of an ST772 Staphylococcus aureus disease isolate carrying staphylococcal cassette chromosome mec (SCCmec) type V from a pyomyositis patient. Our de novo short read assembly is ∼2.8 Mb and encodes a unique Panton-Valentine leukocidin (PVL) phage with structural genes similar to those of ϕ7247PVL and novel lysogenic genes at the N termini.