Postnatal expansion of mesenteric lymph node stromal cells towards reticular and CD34+ stromal cell subsets.

Gut-draining mesenteric lymph nodes (LN) provide the framework to shape intestinal adaptive immune responses. Based on the transcriptional signatures established by our previous work, the composition and immunomodulatory function of LN stromal cells (SC) vary according to location. Here, we describe the single-cell composition and development of the SC compartment within mesenteric LNs derived from postnatal to aged mice. We identify CD34+ SC and fibroblastic reticular stromal cell (FRC) progenitors as putative progenitors, both supplying the typical rapid postnatal mesenteric LN expansion. We further establish the location-specific chromatin accessibility and DNA methylation landscape of non-endothelial SCs and identify a microbiota-independent core epigenomic signature, showing characteristic differences between SCs from mesenteric and skin-draining peripheral LNs. The epigenomic landscape of SCs points to dynamic expression of Irf3 along the differentiation trajectories of FRCs. Accordingly, a mesenchymal stem cell line acquires a Cxcl9+ FRC molecular phenotype upon lentiviral overexpression of Irf3, and the relevance of Irf3 for SC biology is further underscored by the diminished proportion of Ccl19+ and Cxcl9+ FRCs in LNs of Irf3-/- mice. Together, our data constitute a comprehensive transcriptional and epigenomic map of mesenteric LNSC development in early life and dissect location-specific, microbiota-independent properties of non-endothelial SCs.

Mammalian adipogenesis regulator (Areg) cells use retinoic acid signalling to be non- and anti-adipogenic in age-dependent manner.

Adipose stem and precursor cells (ASPCs) give rise to adipocytes and determine the composition and plasticity of adipose tissue. Recently, several studies have demonstrated that ASPCs partition into at least three distinct cell subpopulations, including the enigmatic CD142+ cells. An outstanding challenge is to functionally characterise this population, as discrepant properties, from adipogenic to non- and anti-adipogenic, have been reported for these cells. To resolve these phenotypic ambiguities, we characterised mammalian subcutaneous CD142+ ASPCs across various experimental conditions, demonstrating that CD142+ ASPCs exhibit high molecular and phenotypic robustness. Specifically, we find these cells to be firmly non- and anti-adipogenic both in vitro and in vivo, with their inhibitory signals also impacting adipogenic human cells. However, these CD142+ ASPC-specific properties exhibit surprising temporal phenotypic alterations, and emerge only in an age-dependent manner. Finally, using multi-omic and functional assays, we show that the inhibitory nature of these adipogenesis-regulatory CD142+ ASPCs (Aregs) is driven by specifically expressed secretory factors that cooperate with the retinoic acid signalling pathway to transform the adipogenic state of CD142- ASPCs into a non-adipogenic, Areg-like state.

A leukemia-protective germline variant mediates chromatin module formation via transcription factor nucleation.

Non-coding variants coordinate transcription factor (TF) binding and chromatin mark enrichment changes over regions spanning >100 kb. These molecularly coordinated regions are named "variable chromatin modules" (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. To better understand the molecular mechanisms underlying VCM formation, here, we mechanistically dissect a VCM-modulating noncoding variant that is associated with reduced chronic lymphocytic leukemia (CLL) predisposition and disease progression. This common, germline variant constitutes a 5-bp indel that controls the activity of an AXIN2 gene-linked VCM by creating a MEF2 binding site, which, upon binding, activates a super-enhancer-like regulatory element. This triggers a large change in TF binding activity and chromatin state at an enhancer cluster spanning >150 kb, coinciding with subtle, long-range chromatin compaction and robust AXIN2 up-regulation. Our results support a model in which the indel acts as an AXIN2 VCM-activating TF nucleation event, which modulates CLL pathology.

Extensive tissue-specific expression variation and novel regulators underlying circadian behavior.

Natural genetic variation affects circadian rhythms across the evolutionary tree, but the underlying molecular mechanisms are poorly understood. We investigated population-level, molecular circadian clock variation by generating >700 tissue-specific transcriptomes of Drosophila melanogaster (w1118 ) and 141 Drosophila Genetic Reference Panel (DGRP) lines. This comprehensive circadian gene expression atlas contains >1700 cycling genes including previously unknown central circadian clock components and tissue-specific regulators. Furthermore, >30% of DGRP lines exhibited aberrant circadian gene expression, revealing abundant genetic variation-mediated, intertissue circadian expression desynchrony. Genetic analysis of one line with the strongest deviating circadian expression uncovered a novel cry mutation that, as shown by protein structural modeling and brain immunohistochemistry, disrupts the light-driven flavin adenine dinucleotide cofactor photoreduction, providing in vivo support for the importance of this conserved photoentrainment mechanism. Together, our study revealed pervasive tissue-specific circadian expression variation with genetic variants acting upon tissue-specific regulatory networks to generate local gene expression oscillations.

ASAP 2020 update: an open, scalable and interactive web-based portal for (single-cell) omics analyses.

Single-cell omics enables researchers to dissect biological systems at a resolution that was unthinkable just 10 years ago. However, this analytical revolution also triggered new demands in 'big data' management, forcing researchers to stay up to speed with increasingly complex analytical processes and rapidly evolving methods. To render these processes and approaches more accessible, we developed the web-based, collaborative portal ASAP (Automated Single-cell Analysis Portal). Our primary goal is thereby to democratize single-cell omics data analyses (scRNA-seq and more recently scATAC-seq). By taking advantage of a Docker system to enhance reproducibility, and novel bioinformatics approaches that were recently developed for improving scalability, ASAP meets challenging requirements set by recent cell atlasing efforts such as the Human (HCA) and Fly (FCA) Cell Atlas Projects. Specifically, ASAP can now handle datasets containing millions of cells, integrating intuitive tools that allow researchers to collaborate on the same project synchronously. ASAP tools are versioned, and researchers can create unique access IDs for storing complete analyses that can be reproduced or completed by others. Finally, ASAP does not require any installation and provides a full and modular single-cell RNA-seq analysis pipeline. ASAP is freely available at https://asap.epfl.ch.

cis-regulatory variation modulates susceptibility to enteric infection in the Drosophila genetic reference panel.

BACKGROUND: Resistance to enteric pathogens is a complex trait at the crossroads of multiple biological processes. We have previously shown in the Drosophila Genetic Reference Panel (DGRP) that resistance to infection is highly heritable, but our understanding of how the effects of genetic variants affect different molecular mechanisms to determine gut immunocompetence is still limited. RESULTS: To address this, we perform a systems genetics analysis of the gut transcriptomes from 38 DGRP lines that were orally infected with Pseudomonas entomophila. We identify a large number of condition-specific, expression quantitative trait loci (local-eQTLs) with infection-specific ones located in regions enriched for FOX transcription factor motifs. By assessing the allelic imbalance in the transcriptomes of 19 F1 hybrid lines from a large round robin design, we independently attribute a robust cis-regulatory effect to only 10% of these detected local-eQTLs. However, additional analyses indicate that many local-eQTLs may act in trans instead. Comparison of the transcriptomes of DGRP lines that were either susceptible or resistant to Pseudomonas entomophila infection reveals nutcracker as the only differentially expressed gene. Interestingly, we find that nutcracker is linked to infection-specific eQTLs that correlate with its expression level and to enteric infection susceptibility. Further regulatory analysis reveals one particular eQTL that significantly decreases the binding affinity for the repressor Broad, driving differential allele-specific nutcracker expression. CONCLUSIONS: Our collective findings point to a large number of infection-specific cis- and trans-acting eQTLs in the DGRP, including one common non-coding variant that lowers enteric infection susceptibility.

Commensal Gut Bacteria Buffer the Impact of Host Genetic Variants on Drosophila Developmental Traits under Nutritional Stress.

Eukaryotic genomes encode several buffering mechanisms that robustly maintain invariant phenotypic outcome despite fluctuating environmental conditions. Here we show that the Drosophila gut-associated commensals, represented by a single facultative symbiont, Lactobacillus plantarum (LpWJL), constitutes a so far unexpected buffer that masks the contribution of the host's cryptic genetic variation (CGV) to developmental traits while the host is under nutritional stress. During chronic under-nutrition, LpWJL consistently reduces variation in different host phenotypic traits and ensures robust organ patterning during development; LpWJL also decreases genotype-dependent expression variation, particularly for development-associated genes. We further provide evidence that LpWJL buffers via reactive oxygen species (ROS) signaling whose inhibition impairs microbiota-mediated phenotypic robustness. We thus identified a hitherto unappreciated contribution of the gut facultative symbionts to host fitness that, beyond supporting growth rates and maturation timing, confers developmental robustness and phenotypic homogeneity in times of nutritional stress.

Mitochondrial haplotypes affect metabolic phenotypes in the Drosophila Genetic Reference Panel.

The nature and extent of mitochondrial DNA variation in a population and how it affects traits is poorly understood. Here we resequence the mitochondrial genomes of 169 Drosophila Genetic Reference Panel lines, identifying 231 variants that stratify along 12 mitochondrial haplotypes. We identify 1,845 cases of mitonuclear allelic imbalances, thus implying that mitochondrial haplotypes are reflected in the nuclear genome. However, no major fitness effects are associated with mitonuclear imbalance, suggesting that such imbalances reflect population structure at the mitochondrial level rather than genomic incompatibilities. Although mitochondrial haplotypes have no direct impact on mitochondrial respiration, some haplotypes are associated with stress- and metabolism-related phenotypes, including food intake in males. Finally, through reciprocal swapping of mitochondrial genomes, we demonstrate that a mitochondrial haplotype associated with high food intake can rescue a low food intake phenotype. Together, our findings provide new insight into population structure at the mitochondrial level and point to the importance of incorporating mitochondrial haplotypes in genotype-phenotype relationship studies.

Bayesian association scan reveals loci associated with human lifespan and linked biomarkers.

The enormous variation in human lifespan is in part due to a myriad of sequence variants, only a few of which have been revealed to date. Since many life-shortening events are related to diseases, we developed a Mendelian randomization-based method combining 58 disease-related GWA studies to derive longevity priors for all HapMap SNPs. A Bayesian association scan, informed by these priors, for parental age of death in the UK Biobank study (n=116,279) revealed 16 independent SNPs with significant Bayes factor at a 5% false discovery rate (FDR). Eleven of them replicate (5% FDR) in five independent longevity studies combined; all but three are depleted of the life-shortening alleles in older Biobank participants. Further analysis revealed that brain expression levels of nearby genes (RBM6, SULT1A1 and CHRNA5) might be causally implicated in longevity. Gene expression and caloric restriction experiments in model organisms confirm the conserved role for RBM6 and SULT1A1 in modulating lifespan.

TEMPLE: analysing population genetic variation at transcription factor binding sites.

Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA-protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java-based cross-platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line.

Quantifying signaling pathway activation to monitor the quality of induced pluripotent stem cells.

Many attempts have been made to evaluate the safety and potency of human induced pluripotent stem cells (iPSCs) for clinical applications using transcriptome data, but results so far have been ambiguous or even contradictory. Here, we characterized stem cells at the pathway level, rather than at the gene level as has been the focus of previous work. We meta-analyzed publically-available gene expression data sets and evaluated signaling and metabolic pathway activation profiles for 20 human embryonic stem cell (ESC) lines, 12 human iPSC lines, five embryonic body lines, and six fibroblast cell lines. We demonstrated the close resemblance of iPSCs with ESCs at the pathway level, and provided examples of how pathway activity can be applied to identify iPSC line abnormalities or to predict in vitro differentiation potential. Our results indicate that pathway activation profiling is a promising strategy for evaluating the safety and potency of iPSC lines in translational medicine applications.

Positive Selection at the Polyhomeotic Locus Led to Decreased Thermosensitivity of Gene Expression in Temperate Drosophila melanogaster.

Drosophila melanogaster as a cosmopolitan species has successfully adapted to a wide range of different environments. Variation in temperature is one important environmental factor that influences the distribution of species in nature. In particular for insects, which are mostly ectotherms, ambient temperature plays a major role in their ability to colonize new habitats. Chromatin-based gene regulation is known to be sensitive to temperature. Ambient temperature leads to changes in the activation of genes regulated in this manner. One such regulatory system is the Polycomb group (PcG) whose target genes are more expressed at lower temperatures than at higher ones. Therefore, a greater range in ambient temperature in temperate environments may lead to greater variability (plasticity) in the expression of these genes. This might have detrimental effects, such that positive selection acts to lower the degree of the expression plasticity. We provide evidence for this process in a genomic region that harbors two PcG-regulated genes, polyhomeotic proximal (ph-p) and CG3835. We found a signature of positive selection in this gene region in European populations of D. melanogaster and investigated the region by means of reporter gene assays. The target of selection is located in the intergenic fragment between the two genes. It overlaps with the promoters of both genes and an experimentally validated Polycomb response element (PRE). This fragment harbors five sequence variants that are highly differentiated between European and African populations. The African alleles confer a temperature-induced plasticity in gene expression, which is typical for PcG-mediated gene regulation, whereas thermosensitivity is reduced for the European alleles.

On multilabel classification methods of incompletely labeled biomedical text data.

Multilabel classification is often hindered by incompletely labeled training datasets; for some items of such dataset (or even for all of them) some labels may be omitted. In this case, we cannot know if any item is labeled fully and correctly. When we train a classifier directly on incompletely labeled dataset, it performs ineffectively. To overcome the problem, we added an extra step, training set modification, before training a classifier. In this paper, we try two algorithms for training set modification: weighted k-nearest neighbor (WkNN) and soft supervised learning (SoftSL). Both of these approaches are based on similarity measurements between data vectors. We performed the experiments on AgingPortfolio (text dataset) and then rechecked on the Yeast (nontext genetic data). We tried SVM and RF classifiers for the original datasets and then for the modified ones. For each dataset, our experiments demonstrated that both classification algorithms performed considerably better when preceded by the training set modification step.

Biomedical progress rates as new parameters for models of economic growth in developed countries.

While the doubling of life expectancy in developed countries during the 20th century can be attributed mostly to decreases in child mortality, the trillions of dollars spent on biomedical research by governments, foundations and corporations over the past sixty years are also yielding longevity dividends in both working and retired population. Biomedical progress will likely increase the healthy productive lifespan and the number of years of government support in the old age. In this paper we introduce several new parameters that can be applied to established models of economic growth: the biomedical progress rate, the rate of clinical adoption and the rate of change in retirement age. The biomedical progress rate is comprised of the rejuvenation rate (extending the productive lifespan) and the non-rejuvenating rate (extending the lifespan beyond the age at which the net contribution to the economy becomes negative). While staying within the neoclassical economics framework and extending the overlapping generations (OLG) growth model and assumptions from the life cycle theory of saving behavior, we provide an example of the relations between these new parameters in the context of demographics, labor, households and the firm.

Potential therapeutic approaches for modulating expression and accumulation of defective lamin A in laminopathies and age-related diseases.

Scientific understanding of the genetic components of aging has increased in recent years, with several genes being identified as playing roles in the aging process and, potentially, longevity. In particular, genes encoding components of the nuclear lamina in eukaryotes have been increasingly well characterized, owing in part to their clinical significance in age-related diseases. This review focuses on one such gene, which encodes lamin A, a key component of the nuclear lamina. Genetic variation in this gene can give rise to lethal, early-onset diseases known as laminopathies. Here, we analyze the literature and conduct computational analyses of lamin A signaling and intracellular interactions in order to examine potential mechanisms for altering or slowing down aberrant Lamin A expression and/or for restoring the ratio of normal to aberrant lamin A. The ultimate goal of such studies is to ameliorate or combat laminopathies and related diseases of aging, and we provide a discussion of current approaches in this review.