Project description:This dataset addresses two phenomena affected by reference strain bias in model organism research, specifically in the nematode C. elegans. I) C. elegans is the leading system for research into RNA interference (RNAi); this research has been conducted exclusively in the reference strain. However, sensitivity to RNAi is remarkably diverse across wild-type strains. Here, we used RNA sequencing to evaluate the transcriptional response of the reference strain and four other strains to RNAi by transcriptionally profiling these strains in three conditions: exogenous RNAi targeting germline-expressed genes 1) par-1 and 2) pos-1, and 3) the control condition. II) Gene expression quantification in non-reference strains relies on successful alignment of DNA reads to the reference genome, but high sequence divergence can lead to mapping failure. Here, we used this RNA-seq dataset to characterize the extent to which poor DNA genome assembly limits expression quantification inferences.
Project description:Malaria morbidity and mortality caused by both Plasmodium falciparum and Plasmodium vivax extend well beyond the African continent, and, although P. vivax causes 80-300 million severe cases each year, vivax transmission remains poorly understood. Plasmodium parasites are transmitted by Anopheles mosquitoes, and the critical site of interaction between parasite and host is at the mosquito's luminal midgut brush border. While the genome of the "model" African P. falciparum vector, Anopheles gambiae, has been sequenced, evolutionary divergence limits its utility as a reference across anophelines, especially non-sequenced P. vivax vectors such as Anopheles albimanus. Clearly, enabling technologies and platforms that bridge this substantial scientific gap are required in order to provide public health scientists key transcriptomic and proteomic information that could spur the development of novel interventions to combat this disease. To our knowledge, no approaches have been published which address this issue. To bolster our understanding of P. vivax-An. albimanus midgut interactions, we developed an integrated bioinformatic-hybrid RNA-Seq-LC-MS/MS approach involving An. albimanus transcriptome (15,764 contigs) and luminal midgut subproteome (9,445 proteins) assembly, which, when used with our custom Diptera protein database (685,078 sequences), facilitated a comparative proteomic analysis of the midgut brush borders of two important malaria vectors, An. gambiae and An. albimanus. Summary from: http://www.mcponline.org/content/early/2012/10/17/mcp.M112.019596.long The An. albimanus transcriptome dataset is available at http://funcgen.vectorbase.org/RNAseq/Anopheles_albimanus/INSP/v2
Project description:Using an integrated systems approach, the expressed proteome of B. diazoefficiens strain 110scp4 was measured under i) normal, oxic growth, and ii) microoxic growth condtions. This included, as a first step, the sequencing and de novo assembly of the genome of this widely used rhizobial model strain, which turned out to harbor several deletions and insertions compared to the B. diazoefficiens USDA 110 NCBI reference genome. With this optimal basis in hand, a shotgun proteomics approach relying on a slightly adapated FASP protocol was carried out, allowing to identify 2900 (oxia) and 2826 (microoxia) proteins, respectively, thereby largely expanding the proteome known to be expressed under microoxic conditions.