Interaction with the absorber as the mechanism of radiation

"We must, therefore, be prepared to find that further advance into this region will require a still more extensive renunciation of features which we are accustomed to demand of the space time mode of description." — Niels Bohr

A Comprehensive Genetic Analysis of Candidate Genes Regulating Response to Trypanosoma congolense Infection in Mice

About one-third of cattle in sub-Saharan Africa are at risk of contracting “Nagana”—a disease caused by Trypanosoma parasites similar to those that cause human “Sleeping Sickness.” Laboratory mice can also be infected by trypanosomes, and different mouse breeds show varying levels of susceptibility to infection, similar to what is seen between different breeds of cattle. Survival time after infection is controlled by the underlying genetics of the mouse breed, and previous studies have localised three genomic regions that regulate this trait. These three “Quantitative Trait Loci” (QTL), which have been called Tir1, Tir2 and Tir3 (for Trypanosoma Infection Response 1–3) are well defined, but nevertheless still contain over one thousand genes, any number of which may be influencing survival. This study has aimed to identify the specific differences associated with genes that are controlling mouse survival after T. congolense infection. We have applied a series of analyses to existing datasets, and combined them with novel sequencing, and other genetic data to create short lists of genes that share polymorphisms across susceptible mouse breeds, including two promising “candidate genes”: Pram1 at Tir1 and Cd244 at Tir3. These genes can now be tested to confirm their effect on response to trypanosome infection

The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing

International audienceCurrent sampling of genomic sequence data from eukaryotes is relatively poor, biased, and inadequate to address important questions about their biology, evolution, and ecology; this Community Page describes a resource of 700 transcriptomes from marine microbial eukaryotes to help understand their role in the world's oceans

The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): illuminating the functional diversity of eukaryotic life in the oceans through transcriptome sequencing.

Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes. In practice, this means sequence databases need to be populated with enormous quantities of data for which we have some certainties about the source. Most important is the taxonomic identity of the organism from which a sequence is derived and as much functional identification of the encoded proteins as possible. In an ideal world, such information would be available as a large set of complete, well curated, and annotated genomes for all the major organisms from the environment in question. Reality substantially diverges from this ideal, but at least for bacterial molecular ecology, there is a database consisting of thousands of complete genomes from a wide range of taxa, supplemented by a phylogeny-driven approach to diversifying genomics [2]. For eukaryotes, the number of available genomes is far, far fewer, and we have relied much more heavily on random growth of sequence databases, raising the question as to whether this is fit for purpose