Serial Analysis of Gene Expression: Applications in Malaria Parasite, Yeast, Plant, and Animal Studies

Methodology optimizing SAGE library tag-to-gene mapping: application to Leishmania

BACKGROUND

Leishmaniasis are widespread parasitic-diseases with an urgent need for more active and less toxic drugs and for effective vaccines. Understanding the biology of the parasite especially in the context of host parasite interaction is a crucial step towards such improvements in therapy and control. Several experimental approaches including SAGE (Serial analysis of gene expression) have been developed in order to investigate the parasite transcriptome organisation and plasticity. Usual SAGE tag-to-gene mapping techniques are inadequate because almost all tags are normally located in the 3'-UTR outside the CDS, whereas most information available for Leishmania transcripts is restricted to the CDS predictions. The aim of this work is to optimize a SAGE libraries tag-to-gene mapping technique and to show how this development improves the understanding of Leishmania transcriptome.

FINDINGS

The in silico method implemented herein was based on mapping the tags to Leishmania genome using BLAST then mapping the tags to their gene using a data-driven probability distribution. This optimized tag-to-gene mappings improved the knowledge of Leishmania genome structure and transcription. It allowed analyzing the expression of a maximal number of Leishmania genes, the delimitation of the 3' UTR of 478 genes and the identification of biological processes that are differentially modulated during the promastigote to amastigote differentiation.

CONCLUSION

The developed method optimizes the assignment of SAGE tags in trypanosomatidae genomes as well as in any genome having polycistronic transcription and small intergenic regions.

In-depth global analysis of transcript abundance levels in porcine alveolar macrophages following infection with porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome virus (PRRSV) is a major pathogen of swine worldwide and causes considerable economic loss. Identifying specific cell signaling or activation pathways that associate with variation in PRRSV replication and macrophage function may lead to identification of novel gene targets for the control of PRRSV infection. Serial Analysis of Gene Expression (SAGE) was used to create and survey the transcriptome of in vitro mock-infected and PRRSV strain VR-2332-infected porcine alveolar macrophages (PAM) at 0, 6, 12, 16, and 24 hours after infection. The transcriptome data indicated changes in transcript abundance occurring in PRRSV-infected PAMs over time after infection with more than 590 unique tags with significantly altered transcript abundance levels identified (P < .01). Strikingly, innate immune genes (whose transcript abundances are typically altered in response to other pathogens or insults including IL-8, CCL4, and IL-1β) showed no or very little change at any time point following infection.

From genome to proteome: great progress in the domesticated silkworm (Bombyx mori L.)

As the only truly domesticated insect, the silkworm not only has great economic value, but it also has value as a model for genetics and molecular biology research. Genomics and proteomics have recently shown vast potential to be essential tools in domesticated silkworm research, especially after the completion of the Bombyx mori genome sequence. This paper reviews the progress of the domesticated silkworm genome, particularly focusing on its genetic map, physical map and functional genome. This review also presents proteomics, the proteomic technique and its application in silkworm research.

Simultaneous gene expression profiling in human macrophages infected with Leishmania major parasites using SAGE

Background

Leishmania (L) are intracellular protozoan parasites that are able to survive and replicate within the harsh and potentially hostile phagolysosomal environment of mammalian mononuclear phagocytes. A complex interplay then takes place between the macrophage (MΦ) striving to eliminate the pathogen and the parasite struggling for its own survival.

To investigate this host-parasite conflict at the transcriptional level, in the context of monocyte-derived human MΦs (MDM) infection by L. major metacyclic promastigotes, the quantitative technique of serial analysis of gene expression (SAGE) was used.

Results

After extracting mRNA from resting human MΦs, Leishmania-infected human MΦs and L. major parasites, three SAGE libraries were constructed and sequenced generating up to 28,173; 57,514 and 33,906 tags respectively (corresponding to 12,946; 23,442 and 9,530 unique tags). Using computational data analysis and direct comparison to 357,888 publicly available experimental human tags, the parasite and the host cell transcriptomes were then simultaneously characterized from the mixed cellular extract, confidently discriminating host from parasite transcripts. This procedure led us to reliably assign 3,814 tags to MΦs' and 3,666 tags to L. major parasites transcripts. We focused on these, showing significant changes in their expression that are likely to be relevant to the pathogenesis of parasite infection: (i) human MΦs genes, belonging to key immune response proteins (e.g., IFNγ pathway, S100 and chemokine families) and (ii) a group of Leishmania genes showing a preferential expression at the parasite's intra-cellular developing stage.

Conclusion

Dual SAGE transcriptome analysis provided a useful, powerful and accurate approach to discriminating genes of human or parasitic origin in Leishmania-infected human MΦs. The findings presented in this work suggest that the Leishmania parasite modulates key transcripts in human MΦs that may be beneficial for its establishment and survival. Furthermore, these results provide an overview of gene expression at two developmental stages of the parasite, namely metacyclic promastigotes and intracellular amastigotes and indicate a broad difference between their transcriptomic profiles. Finally, our reported set of expressed genes will be useful in future rounds of data mining and gene annotation.

The maize root transcriptome by serial analysis of gene expression

Serial Analysis of Gene Expression was used to define number and relative abundance of transcripts in the root tip of well-watered maize seedlings (Zea mays cv FR697). In total, 161,320 tags represented a minimum of 14,850 genes, based on at least two tags detected per transcript. The root transcriptome has been sampled to an estimated copy number of approximately five transcripts per cell. An extrapolation from the data and testing of single-tag identifiers by reverse transcription-PCR indicated that the maize root transcriptome should amount to at least 22,000 expressed genes. Frequency ranged from low copy number (2-5, 68.8%) to highly abundant transcripts (100-->1,200; 1%). Quantitative reverse transcription-PCR for selected transcripts indicated high correlation with tag frequency. Computational analysis compared this set with known maize transcripts and other root transcriptome models. Among the 14,850 tags, 7,010 (47%) were found for which no maize cDNA or gene model existed. Comparing the maize root transcriptome with that in other plants indicated that highly expressed transcripts differed substantially; less than 5% of the most abundant transcripts were shared between maize and Arabidopsis (Arabidopsis thaliana). Transcript categories highlight functions of the maize root tip. Significant variation in abundance characterizes transcripts derived from isoforms of individual enzymes in biochemical pathways.