Shared probe design and existing microarray reanalysis using PICKY

<p>Abstract</p> <p>Background</p> <p>Large genomes contain families of highly similar genes that cannot be individually identified by microarray probes. This limitation is due to thermodynamic restrictions and cannot be resolved by any computational method. Since gene annotations are updated more frequently than microarrays, another common issue facing microarray users is that existing microarrays must be routinely reanalyzed to determine probes that are still useful with respect to the updated annotations.</p> <p>Results</p> <p><smcaps>PICKY</smcaps> 2.0 can design shared probes for sets of genes that cannot be individually identified using unique probes. <smcaps>PICKY</smcaps> 2.0 uses novel algorithms to track sharable regions among genes and to strictly distinguish them from other highly similar but nontarget regions during thermodynamic comparisons. Therefore, <smcaps>PICKY</smcaps> does not sacrifice the quality of shared probes when choosing them. The latest <smcaps>PICKY</smcaps> 2.1 includes the new capability to reanalyze existing microarray probes against updated gene sets to determine probes that are still valid to use. In addition, more precise nonlinear salt effect estimates and other improvements are added, making <smcaps>PICKY</smcaps> 2.1 more versatile to microarray users.</p> <p>Conclusions</p> <p>Shared probes allow expressed gene family members to be detected; this capability is generally more desirable than not knowing anything about these genes. Shared probes also enable the design of cross-genome microarrays, which facilitate multiple species identification in environmental samples. The new nonlinear salt effect calculation significantly increases the precision of probes at a lower buffer salt concentration, and the probe reanalysis function improves existing microarray result interpretations.</p

Moult cycle specific differential gene expression profiling of the crab Portunus pelagicus

Background: Crustacean moulting is a complex process involving many regulatory pathways. A holistic approach to examine differential gene expression profiles of transcripts relevant to the moulting process, across all moult cycle stages, was used in this study. Custom cDNA microarrays were constructed for Portunus pelagicus. The printed arrays contained 5000 transcripts derived from both the whole organism, and from individual organs such as the brain, eyestalk, mandibular organ and Y-organ from all moult cycle stages.Results: A total of 556 clones were sequenced from the cDNA libraries used to construct the arrays. These cDNAs represented 175 singletons and 62 contigs, resulting in 237 unique putative genes. The gene sequences were classified into the following biological functions: cuticular proteins associated with arthropod exoskeletons, farnesoic acid O-methyltransferase (FaMeT), proteins belonging to the hemocyanin gene family, lectins, proteins relevant to lipid metabolism, mitochondrial proteins, muscle related proteins, phenoloxidase activators and ribosomal proteins. Moult cycle-related differential expression patterns were observed for many transcripts. Of particular interest were those relating to the formation and hardening of the exoskeleton, and genes associated with cell respiration and energy metabolism.Conclusions: The expression data presented here provide a chronological depiction of the molecular events associated with the biological changes that occur during the crustacean moult cycle. Tracing the temporal expression patterns of a large variety of transcripts involved in the moult cycle of P. pelagicus can provide a greater understanding of gene function, interaction, and regulation of both known and new genes with respect to the moulting process

Trees and Insects Have Microbiomes: Consequences for Forest Health and Management

Purpose of Review Forest research has shown for a long time that microorganisms influence tree-insect interactions, but the complexity of microbial communities, as well as the holobiont nature of both trees and insect herbivores, has only recently been taken fully into account by forest entomologists and ecologists. In this article, we review recent findings on the effects of tree-insect-microbiome interactions on the health of tree individuals and discuss whether and how knowledge about tree and insect microbiomes could be integrated into forest health management strategies. We then examine the effects tree-insect-microbiome interactions on forest biodiversity and regeneration, highlighting gaps in our knowledge at the ecosystem scale. Recent Findings Multiple studies show that herbivore damage in forest ecosystems is clearly influenced by tripartite interactions between trees, insects and their microbiomes. Recent research on the plant microbiome indicates that microbiomes of planted trees could be managed at several stages of production, from seed orchards to mature forests, to improve the resistance of forest plantations to insect pests. Therefore, the tree microbiome could potentially be fully integrated into forest health management strategies. To achieve this aim, future studies will have to combine, as has long been done in forest research, holistic goals with reductionist approaches. Efforts should be made to improve our understanding of how microbial fluxes between trees and insects determine the health of forest ecosystems, and to decipher the underlying mechanisms, through the development of experimental systems in which microbial communities can be manipulated. Knowledge about tree-insect-microbiome interactions should then be integrated into spatial models of forest dynamics to move from small-scale mechanisms to forest ecosystem-scale predictions.CEnter of the study of Biodiversity in AmazoniaCOntinental To coastal Ecosystems: evolution, adaptability and governanceBiosurveillance Next-Gen des changements dans la structure et le fonctionnement des écosystèmesHOlistic Management of Emerging forest pests and Diseases,Role of endosymbiotic bacteria in the long-term evolution of a diverse and globally-distributed aphid genus: a Phylogenomic Analysi