A systems genetics resource and analysis of sleep regulation in the mouse.

Sleep is essential for optimal brain functioning and health, but the biological substrates through which sleep delivers these beneficial effects remain largely unknown. We used a systems genetics approach in the BXD genetic reference population (GRP) of mice and assembled a comprehensive experimental knowledge base comprising a deep "sleep-wake" phenome, central and peripheral transcriptomes, and plasma metabolome data, collected under undisturbed baseline conditions and after sleep deprivation (SD). We present analytical tools to interactively interrogate the database, visualize the molecular networks altered by sleep loss, and prioritize candidate genes. We found that a one-time, short disruption of sleep already extensively reshaped the systems genetics landscape by altering 60%-78% of the transcriptomes and the metabolome, with numerous genetic loci affecting the magnitude and direction of change. Systems genetics integrative analyses drawing on all levels of organization imply α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor trafficking and fatty acid turnover as substrates of the negative effects of insufficient sleep. Our analyses demonstrate that genetic heterogeneity and the effects of insufficient sleep itself on the transcriptome and metabolome are far more widespread than previously reported.

Methylation specifies distinct estrogen-induced binding site repertoires of CBP to chromatin.

Multiple signaling pathways ultimately modulate the epigenetic information embedded in the chromatin of gene promoters by recruiting epigenetic enzymes. We found that, in estrogen-regulated gene programming, the acetyltransferase CREB-binding protein (CBP) is specifically and exclusively methylated by the coactivator-associated arginine methyltransferase (CARM1) in vivo. CARM1-dependent CBP methylation and p160 coactivators were required for estrogen-induced recruitment to chromatin targets. Notably, methylation increased the histone acetyltransferase (HAT) activity of CBP and stimulated its autoacetylation. Comparative genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) studies revealed a variety of patterns by which p160, CBP, and methyl-CBP (meCBP) are recruited (or not) by estrogen to chromatin targets. Moreover, significant target gene-specific variation in the recruitment of (1) the p160 RAC3 protein, (2) the fraction of a given meCBP species within the total CBP, and (3) the relative recruitment of different meCBP species suggests the existence of a target gene-specific "fingerprint" for coregulator recruitment. Crossing ChIP-seq and transcriptomics profiles revealed the existence of meCBP "hubs" within the network of estrogen-regulated genes. Together, our data provide evidence for an unprecedented mechanism by which CARM1-dependent CBP methylation results in gene-selective association of estrogen-recruited meCBP species with different HAT activities and specifies distinct target gene hubs, thus diversifying estrogen receptor programming.

The ABCG transporter PEC1/ABCG32 is required for the formation of the developing leaf cuticle in Arabidopsis.

The cuticle is an essential diffusion barrier on aerial surfaces of land plants whose structural component is the polyester cutin. The PERMEABLE CUTICLE1/ABCG32 (PEC1) transporter is involved in plant cuticle formation in Arabidopsis. The gpat6 pec1 and gpat4 gapt8 pec1 double and triple mutants are characterized. Their PEC1-specific contributions to aliphatic cutin composition and cuticle formation during plant development are revealed by gas chromatography/mass spectrometry and Fourier-transform infrared spectroscopy. The composition of cutin changes during rosette leaf expansion in Arabidopsis. C16:0 monomers are in higher abundance in expanding than in fully expanded leaves. The atypical cutin monomer C18:2 dicarboxylic acid is more prominent in fully expanded leaves. Findings point to differences in the regulation of several pathways of cutin precursor synthesis. PEC1 plays an essential role during expansion of the rosette leaf cuticle. The reduction of C16 monomers in the pec1 mutant during leaf expansion is unlikely to cause permeability of the leaf cuticle because the gpat6 mutant with even fewer C16:0 monomers forms a functional rosette leaf cuticle at all stages of development. PEC1/ABCG32 transport activity affects cutin composition and cuticle structure in a specific and non-redundant fashion.

Disturbed local auxin homeostasis enhances cellular anisotropy and reveals alternative wiring of auxin-ethylene crosstalk in Brachypodium distachyon seminal roots.

Observations gained from model organisms are essential, yet it remains unclear to which degree they are applicable to distant relatives. For example, in the dicotyledon Arabidopsis thaliana (Arabidopsis), auxin biosynthesis via indole-3-pyruvic acid (IPA) is essential for root development and requires redundant TRYPTOPHAN AMINOTRANSFERASE OF ARABIDOPSIS 1 (TAA1) and TAA1-RELATED (TAR) genes. A promoter T-DNA insertion in the monocotyledon Brachypodium distachyon (Brachypodium) TAR2-LIKE gene (BdTAR2L) severely down-regulates expression, suggesting reduced tryptophan aminotransferase activity in this mutant, which thus represents a hypomorphic Bdtar2l allele (Bdtar2l(hypo) ). Counterintuitive however, Bdtar2l(hypo) mutants display dramatically elongated seminal roots because of enhanced cell elongation. This phenotype is also observed in another, stronger Bdtar2l allele and can be mimicked by treating wild type with L-kynerunine, a specific TAA1/TAR inhibitor. Surprisingly, L-kynerunine-treated as well as Bdtar2l roots display elevated rather than reduced auxin levels. This does not appear to result from compensation by alternative auxin biosynthesis pathways. Rather, expression of YUCCA genes, which are rate-limiting for conversion of IPA to auxin, is increased in Bdtar2l mutants. Consistent with suppression of Bdtar2l(hypo) root phenotypes upon application of the ethylene precursor 1-aminocyclopropane-1-carboxylic-acid (ACC), BdYUCCA genes are down-regulated upon ACC treatment. Moreover, they are up-regulated in a downstream ethylene-signaling component homolog mutant, Bd ethylene insensitive 2-like 1, which also displays a Bdtar2l root phenotype. In summary, Bdtar2l phenotypes contrast with gradually reduced root growth and auxin levels described for Arabidopsis taa1/tar mutants. This could be explained if in Brachypodium, ethylene inhibits the rate-limiting step of auxin biosynthesis in an IPA-dependent manner to confer auxin levels that are sub-optimal for root cell elongation, as suggested by our observations. Thus, our results reveal a delicate homeostasis of local auxin and ethylene activity to control cell elongation in Brachypodium roots and suggest alternative wiring of auxin-ethylene crosstalk as compared to Arabidopsis.

POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq profiles by non-linear normalization.

Chromatin immunoprecipitation coupled with massive parallel sequencing (ChIP-seq) is increasingly used to map protein-chromatin interactions at global scale. The comparison of ChIP-seq profiles for RNA polymerase II (PolII) established in different biological contexts, such as specific developmental stages or specific time-points during cell differentiation, provides not only information about the presence/accumulation of PolII at transcription start sites (TSSs) but also about functional features of transcription, including PolII stalling, pausing and transcript elongation. However, annotation and normalization tools for comparative studies of multiple samples are currently missing. Here, we describe the R-package POLYPHEMUS, which integrates TSS annotation with PolII enrichment over TSSs and coding regions, and normalizes signal intensity profiles. Thereby POLYPHEMUS facilitates to extract information about global PolII action to reveal changes in the functional state of genes. We validated POLYPHEMUS using a kinetic study on retinoic acid-induced differentiation and a publicly available data set from a comparative PolII ChIP-seq profiling in Caenorhabditis elegans. We demonstrate that POLYPHEMUS corrects the data sets by normalizing for technical variation between samples and reveal the potential of the algorithm in comparing multiple data sets to infer features of transcription regulation from dynamic PolII binding profiles.

A qualitative continuous model of cellular auxin and brassinosteroid signaling and their crosstalk.

MOTIVATION: Hormone pathway interactions are crucial in shaping plant development, such as synergism between the auxin and brassinosteroid pathways in cell elongation. Both hormone pathways have been characterized in detail, revealing several feedback loops. The complexity of this network, combined with a shortage of kinetic data, renders its quantitative analysis virtually impossible at present. RESULTS: As a first step towards overcoming these obstacles, we analyzed the network using a Boolean logic approach to build models of auxin and brassinosteroid signaling, and their interaction. To compare these discrete dynamic models across conditions, we transformed them into qualitative continuous systems, which predict network component states more accurately and can accommodate kinetic data as they become available. To this end, we developed an extension for the SQUAD software, allowing semi-quantitative analysis of network states. Contrasting the developmental output depending on cell type-specific modulators enabled us to identify a most parsimonious model, which explains initially paradoxical mutant phenotypes and revealed a novel physiological feature. AVAILABILITY: The package SQUADD is freely available via the Bioconductor repository at http://www.bioconductor.org/help/bioc-views/release/bioc/html/SQUADD.html.

Dissecting the retinoid-induced differentiation of F9 embryonal stem cells by integrative genomics.

Retinoic acid (RA) triggers physiological processes by activating heterodimeric transcription factors (TFs) comprising retinoic acid receptor (RARα, ß, γ) and retinoid X receptor (RXRα, ß, γ). How a single signal induces highly complex temporally controlled networks that ultimately orchestrate physiological processes is unclear. Using an RA-inducible differentiation model, we defined the temporal changes in the genome-wide binding patterns of RARγ and RXRα and correlated them with transcription regulation. Unexpectedly, both receptors displayed a highly dynamic binding, with different RXRα heterodimers targeting identical loci. Comparison of RARγ and RXRα co-binding at RA-regulated genes identified putative RXRα-RARγ target genes that were validated with subtype-selective agonists. Gene-regulatory decisions during differentiation were inferred from TF-target gene information and temporal gene expression. This analysis revealed six distinct co-expression paths of which RXRα-RARγ is associated with transcription activation, while Sox2 and Egr1 were predicted to regulate repression. Finally, RXRα-RARγ regulatory networks were reconstructed through integration of functional co-citations. Our analysis provides a dynamic view of RA signalling during cell differentiation, reveals RAR heterodimer dynamics and promiscuity, and predicts decisions that diversify the RA signal into distinct gene-regulatory programs.

Unsupervised Analysis of Flow Cytometry Data in a Clinical Setting Captures Cell Diversity and Allows Population Discovery.

Data obtained with cytometry are increasingly complex and their interrogation impacts the type and quality of knowledge gained. Conventional supervised analyses are limited to pre-defined cell populations and do not exploit the full potential of data. Here, in the context of a clinical trial of cancer patients treated with radiotherapy, we performed longitudinal flow cytometry analyses to identify multiple distinct cell populations in circulating whole blood. We cross-compared the results from state-of-the-art recommended supervised analyses with results from MegaClust, a high-performance data-driven clustering algorithm allowing fast and robust identification of cell-type populations. Ten distinct cell populations were accurately identified by supervised analyses, including main T, B, dendritic cell (DC), natural killer (NK) and monocytes subsets. While all ten subsets were also identified with MegaClust, additional cell populations were revealed (e.g. CD4+HLA-DR+ and NKT-like subsets), and DC profiling was enriched by the assignment of additional subset-specific markers. Comparison between transcriptomic profiles of purified DC populations and publicly available datasets confirmed the accuracy of the unsupervised clustering algorithm and demonstrated its potential to identify rare and scarcely described cell subsets. Our observations show that data-driven analyses of cytometry data significantly enrich the amount and quality of knowledge gained, representing an important step in refining the characterization of immune responses.

Neutrophils and Snail Orchestrate the Establishment of a Pro-tumor Microenvironment in Lung Cancer.

Understanding the immune compartment of tumors facilitates the development of revolutionary new therapies. We used a Kras(G12D)-driven mouse model of lung cancer to establish an immune signature and identified a contribution of Gr1+ neutrophils to disease progression. Depletion experiments showed that Gr1+ cells (1) favor tumor growth, (2) reduce T cell homing and prevent successful anti-PD1 immunotherapy, and (3) alter angiogenesis, leading to hypoxia and sustained Snail expression in lung cancer cells. In turn, Snail accelerated disease progression and increased intratumoral Cxcl2 secretion and neutrophil infiltration. Cxcl2 was produced mainly by neutrophils themselves in response to a factor secreted by Snail-expressing tumor cells. We therefore propose a vicious cycle encompassing neutrophils and Snail to maintain a deleterious tumor microenvironment.

Automated quantitative histology reveals vascular morphodynamics during Arabidopsis hypocotyl secondary growth.

Among various advantages, their small size makes model organisms preferred subjects of investigation. Yet, even in model systems detailed analysis of numerous developmental processes at cellular level is severely hampered by their scale. For instance, secondary growth of Arabidopsis hypocotyls creates a radial pattern of highly specialized tissues that comprises several thousand cells starting from a few dozen. This dynamic process is difficult to follow because of its scale and because it can only be investigated invasively, precluding comprehensive understanding of the cell proliferation, differentiation, and patterning events involved. To overcome such limitation, we established an automated quantitative histology approach. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with automated cell type recognition through machine learning, we could establish a cellular resolution atlas that reveals vascular morphodynamics during secondary growth, for example equidistant phloem pole formation. DOI: http://dx.doi.org/10.7554/eLife.01567.001.