Metagenomic signatures
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB39726 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5418864_1.fastq.gz | Fastqsanger.gz | |||
| ERR5418864_2.fastq.gz | Fastqsanger.gz | |||
| ERR5418865_1.fastq.gz | Fastqsanger.gz | |||
| ERR5418865_2.fastq.gz | Fastqsanger.gz | |||
| ERR5418866_1.fastq.gz | Fastqsanger.gz |
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Project description:Metagenomic signatures of early life brain damage
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Project description:The switch between biological states during key life-history transitions requires major reprogramming at the behavioural level that is under the control of the brain. In this study we focused on major life-history transitions in bumblebee queens (Bombus terrestris) that involve switching from virgin to mated and reproductively mature. To reveal the molecular processes underpinning the behavioural changes that accompany these transitions, we characterised the neurogenomic state of queens that succeeded or failed in making these transitions. Analyses of shared transcription patterns suggested that failures are associated with larger molecular signatures than successes. This was observed at the level of total numbers of differentially expressed genes (DEGs) and proportions of these genes that were up-regulated, and applies to both mating and reproductive maturation. ‘Failed Reproductive’ queens were the most distinct phenotype, associated with the highest number of DEGs (1,578) and two networks of co-expressed genes. Mating status influenced gene expression the least, followed by the transition between the two successful phenotypes (mating to reproductive maturation) and reproductive maturation. However, this pattern was not mirrored in terms of functional specialisations, for Gene Ontology (GO) terms, KEGG pathways and co-expression networks associated with DEGs. Out of the 21 highly connected (hub) genes associated with co-expression networks, 9 are involved in neural processes and 4 are regulators of gene expression. This study shows that different life-history transitions trigger distinct molecular profiles, within a single caste of a eusocial insect. Failure to surmount key life-history transitions has the largest effect on a queen’s neurogenomic state, and it triggers a massive overall up-regulation of gene expression. Hence, failure is an important outcome that must be taken into account when analysing the molecular regulation of important life-history transitions.
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Project description:Restif2006 - Whooping cough
This model is described in the article:
Integrating life history and
cross-immunity into the evolutionary dynamics of pathogens.
Restif O, Grenfell BT.
Proc. Biol. Sci. 2006 Feb; 273(1585):
409-416
Abstract:
Models for the diversity and evolution of pathogens have
branched into two main directions: the adaptive dynamics of
quantitative life-history traits (notably virulence) and the
maintenance and invasion of multiple, antigenically diverse
strains that interact with the host's immune memory. In a first
attempt to reconcile these two approaches, we developed a
simple modelling framework where two strains of pathogens,
defined by a pair of life-history traits (infectious period and
infectivity), interfere through a given level of
cross-immunity. We used whooping cough as a potential example,
but the framework proposed here could be applied to other acute
infectious diseases. Specifically, we analysed the effects of
these parameters on the invasion dynamics of one strain into a
population, where the second strain is endemic. Whereas the
deterministic version of the model converges towards stable
coexistence of the two strains in most cases, stochastic
simulations showed that transient epidemic dynamics can cause
the extinction of either strain. Thus ecological dynamics,
modulated by the immune parameters, eventually determine the
adaptive value of different pathogen genotypes. We advocate an
integrative view of pathogen dynamics at the crossroads of
immunology, epidemiology and evolution, as a way towards
efficient control of infectious diseases.
This
version of the model can be used for both the stochastic and the
deterministic simulations described in the article. For
deterministic interpretations with infinite population sizes, set
the population size
N = 1. The model reproduces the deterministic time
courses. Stochastic interpretation with Copasi UI gave results
similar to the article, but was not extensively tested. The
initial conditions for competition simulations can be derived by
equilibrating the system for one pathogen and then adding a
starting concentration for the other.
Originally
created by libAntimony v1.3 (using libSBML 4.1.0-b1)
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000249.
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To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
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Project description:DNA structural variation (SV) comprises a major portion of genetic diversity, but its biological impact is unclear. We propose that the genetic history and extraordinary phenotypic variation of dogs make them an ideal mammal in which to study the effects of SV on biology and disease. The hundreds of existing dog breeds were created by selection of extreme morphological and behavioral traits. And along with those traits, each breed carries increased risk for different diseases. We used array CGH to create the first map of DNA copy number variation (CNV) or SV in dogs. The extent of this variation, and some of the gene classes affected, are similar to those of mice and humans. Most canine CNVs affect genes, including disease and candidate disease genes, and are thus likely to be functional. We identified many CNVs that may be breed or breed class specific. Cluster analysis of CNV regions showed that dog breeds tend to group according to breed classes. Our combined findings suggest many CNVs are (1) in linkage disequilibrium with flanking sequence, and (2) associated with breed specific traits. We discuss how a catalog of structural variation in dogs will accelerate the identification of the genetic basis of canine traits and diseases, beginning with the use of whole genome association and candidate CNV/gene approaches. Chen WK, Swartz JD, Rush LJ, Alvarez, CE. Mapping DNA structural variation in dogs. Genome Res. 2009. 19: 500 509 PMID: 19015322 Array comparitive genomic hybridization analysis of structural variation in 9 dogs, and 1 lymphoma cell line.
2010-05-22 | E-GEOD-18317 | biostudies-arrayexpress
Project description:Sexually dimorphic traits are by definition exaggerated in one sex, which may arise from a history of sex-specific selection â in males, females, or both. If this exaggeration comes at a cost, exaggeration is expected to be greater in higher condition individuals (condition-dependent). Although studies using small numbers of morphological traits are generally supportive, this prediction has not been examined at a larger scale. We test this prediction across the trancriptome by determining the condition-dependence of sex-biased (dimorphic) gene expression. We find that high-condition populations are more sexually dimorphic in transcription than low-condition populations. High condition populations have more male-biased genes and more female-biased genes, and a greater degree of sexually dimorphic expression in these genes. Also, condition-dependence in male-biased genes was greater than in a set of unbiased genes. Interestingly, male-biased genes expressed in the testes were not more condition-dependent than those in the soma. By contrast, increased female-biased expression under high condition may be have occurred because of the greater contribution of the ovary-specific transcripts to the entire mRNA pool. We did not find any genomic signatures distinguishing the condition-dependent sex-biased genes. The degree of condition-dependent sexual dimorphism (CDSD) did not differ between the autosomes and the X-chromosome. There was only weak evidence that rates of evolution correlated with CDSD. We suggest that the sensitivity of both female-biased genes and male-biased genes to condition may be akin to the overall heightened sensitivity to condition that life-history and sexually selected traits tend to exhibit. Our results demonstrate that through condition-dependence, early life experience has dramatic effects on sexual dimorphism in the adult transcriptome. There were 8 biologically distinct samples. Each was replicated 6 times for a total of 48 biological samples on 24 arrays. There was no reference or control sample as a loop design was used. Each of the 48 samples are represented separately.
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