Composition and regulation of maternal and zygotic transcriptomes reflects species-specific reproductive mode

Background Early embryos contain mRNA transcripts expressed from two distinct origins; those expressed from the mother's genome and deposited in the oocyte (maternal) and those expressed from the embryo's genome after fertilization (zygotic). The transition from maternal to zygotic control occurs at different times in different animals according to the extent and form of maternal contributions, which likely reflect evolutionary and ecological forces. Maternally deposited transcripts rely on post-transcriptional regulatory mechanisms for precise spatial and temporal expression in the embryo, whereas zygotic transcripts can use both transcriptional and post-transcriptional regulatory mechanisms. The differences in maternal contributions between animals may be associated with gene regulatory changes detectable by the size and complexity of the associated regulatory regions. Results We have used genomic data to identify and compare maternal and/or zygotic expressed genes from six different animals and find evidence for selection acting to shape gene regulatory architecture in thousands of genes. We find that mammalian maternal genes are enriched for complex regulatory regions, suggesting an increase in expression specificity, while egg-laying animals are enriched for maternal genes that lack transcriptional specificity. Conclusions We propose that this lack of specificity for maternal expression in egg-laying animals indicates that a large fraction of maternal genes are expressed non-functionally, providing only supplemental nutritional content to the developing embryo. These results provide clear predictive criteria for analysis of additional genomes.Molecular and Cellular Biolog

ImmPort, toward repurposing of open access immunological assay data for translational and clinical research

Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components–Private Data, Shared Data, Data Analysis, and Resources—for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the ImmPort Shared Data portal , which allows research data to be repurposed to accelerate the translation of new insights into discoveries

Pairing of Competitive and Topologically Distinct Regulatory Modules Enhances Patterned Gene Expression

Biological networks are inherently modular, yet little is known about how modules are assembled to enable coordinated and complex functions. We used RNAi and time series, whole-genome microarray analyses to systematically perturb and characterize components of a Caenorhabditis elegans lineage-specific transcriptional regulatory network. These data are supported by selected reporter gene analyses and comprehensive yeast one-hybrid and promoter sequence analyses. Based on these results, we define and characterize two modules composed of muscle- and epidermal-specifying transcription factors that function together within a single cell lineage to robustly specify multiple cell types. The expression of these two modules, although positively regulated by a common factor, is reliably segregated among daughter cells. Our analyses indicate that these modules repress each other, and we propose that this cross-inhibition coupled with their relative time of induction function to enhance the initial asymmetry in their expression patterns, thus leading to the observed invariant gene expression patterns and cell lineage. The coupling of asynchronous and topologically distinct modules may be a general principle of module assembly that functions to potentiate genetic switches.Molecular and Cellular Biolog

Variation in the Human Immune System Is Largely Driven by Non-Heritable Influences

There is considerable heterogeneity in immunological parameters between individuals, but its sources are largely unknown. To assess the relative contribution of heritable versus non-heritable factors, we have performed a systems-level analysis of 210 healthy twins between 8–82 years of age. We measured 204 different parameters, including cell population frequencies, cytokine responses, and serum proteins, and found that 77% of these are dominated (> 50% of variance) and 58% almost completely determined (> 80% of variance) by non-heritable influences. In addition, some of these parameters become more variable with age, suggesting the cumulative influence of environmental exposure. Similarly, the serological responses to seasonal influenza vaccination are also determined largely by non-heritable factors, likely due to repeated exposure to different strains. Lastly, in MZ twins discordant for cytomegalovirus infection, over half of all parameters are affected. These results highlight the largely reactive and adaptive nature of the immune system in healthy individuals

Cytomegalovirus infection enhances the immune response to influenza

Cytomegalovirus (CMV) is a beta-herpes virus present in a latent form in most people worldwide. In immunosuppressed individuals, CMV can reactivate and cause serious clinical complications, but the effect of the latent state on healthy people remains elusive. We undertook a systems approach to understand the differences between seropositive and negative subjects and measured hundreds of immune system components from blood samples including cytokines and chemokines, immune cell phenotyping, gene expression, ex vivo cell responses to cytokine stimuli and the antibody response to seasonal influenza vaccination. As expected, we found decreased responses to vaccination and an overall down-regulation of immune components in aged individuals regardless of CMV serostatus. In contrast, CMV-infected young adults exhibited an overall up-regulation of immune components including enhanced antibody responses to influenza vaccination, increased CD8+ T cell sensitivity, and elevated levels of circulating IFN-γ compared to uninfected individuals. Experiments with young mice infected with murine CMV also showed significant protection from an influenza virus challenge compared with uninfected animals, although this effect declined with time. These data show that CMV and its murine equivalent can have a beneficial effect on the immune response of young, healthy individuals, which may explain the continued coexistence of CMV and mammals throughout their evolution

Network motifs in the transcriptional regulation network of Escherichia coli

Network motifs in the transcriptional regulation network of Escherichia col

Reconstructing the Genomic Content of Microbiome Taxa through Shotgun Metagenomic Deconvolution

<div><p>Metagenomics has transformed our understanding of the microbial world, allowing researchers to bypass the need to isolate and culture individual taxa and to directly characterize both the taxonomic and gene compositions of environmental samples. However, associating the genes found in a metagenomic sample with the specific taxa of origin remains a critical challenge. Existing binning methods, based on nucleotide composition or alignment to reference genomes allow only a coarse-grained classification and rely heavily on the availability of sequenced genomes from closely related taxa. Here, we introduce a novel computational framework, integrating variation in gene abundances across multiple samples with taxonomic abundance data to deconvolve metagenomic samples into taxa-specific gene profiles and to reconstruct the genomic content of community members. This assembly-free method is not bounded by various factors limiting previously described methods of metagenomic binning or metagenomic assembly and represents a fundamentally different approach to metagenomic-based genome reconstruction. An implementation of this framework is available at <a href="http://elbo.gs.washington.edu/software.html" target="_blank">http://elbo.gs.washington.edu/software.html</a>. We first describe the mathematical foundations of our framework and discuss considerations for implementing its various components. We demonstrate the ability of this framework to accurately deconvolve a set of metagenomic samples and to recover the gene content of individual taxa using synthetic metagenomic samples. We specifically characterize determinants of prediction accuracy and examine the impact of annotation errors on the reconstructed genomes. We finally apply metagenomic deconvolution to samples from the Human Microbiome Project, successfully reconstructing genus-level genomic content of various microbial genera, based solely on variation in gene count. These reconstructed genera are shown to correctly capture genus-specific properties. With the accumulation of metagenomic data, this deconvolution framework provides an essential tool for characterizing microbial taxa never before seen, laying the foundation for addressing fundamental questions concerning the taxa comprising diverse microbial communities.</p></div