Robustness of Drosophila early embryo and wing imaginal disc development

Within a developing organism, cells require information on where they are in order to differentiate into the correct cell-type. Pattern formation is the process by which cells acquire and process positional cues and thus determine their fate. This can be achieved by the production and release of a diffusible signaling molecule, called a morphogen, which forms a concentration gradient: exposure to different morphogen levels leads to the activation of specific signaling pathways. Thus, in response to the morphogen gradient, cells start to express different sets of genes, forming domains characterized by a unique combination of differentially expressed genes. As a result, a pattern of cell fates and specification emerges.Though morphogens have been known for decades, it is not yet clear how these gradients form and are interpreted in order to yield highly robust patterns of gene expression. During my PhD thesis, I investigated the properties of Bicoid (Bcd) and Decapentaplegic (Dpp), two morphogens involved in the patterning of the anterior-posterior axis of Drosophila embryo and wing primordium, respectively. In particular, I have been interested in understanding how the pattern proportions are maintained across embryos of different sizes or within a growing tissue. This property is commonly referred to as scaling and is essential for yielding functional organs or organisms. In order to tackle these questions, I analysed fluorescence images showing the pattern of gene expression domains in the early embryo and wing imaginal disc. After characterizing the extent of these domains in a quantitative and systematic manner, I introduced and applied a new scaling measure in order to assess how well proportions are maintained. I found that scaling emerged as a universal property both in early embryos (at least far away from the Bcd source) and in wing imaginal discs (across different developmental stages). Since we were also interested in understanding the mechanisms underlying scaling and how it is transmitted from the morphogen to the target genes down in the signaling cascade, I also quantified scaling in mutant flies where this property could be disrupted. While scaling is largely conserved in embryos with altered bcd dosage, my modeling suggests that Bcd trapping by the nuclei as well as pre-steady state decoding of the morphogen gradient are essential to ensure precise and scaled patterning of the Bcd signaling cascade. In the wing imaginal disc, it appears that as the disc grows, the Dpp response expands and scales with the tissue size. Interestingly, scaling is not perfect at all positions in the field. The scaling of the target gene domains is best where they have a function; Spalt, for example, scales best at the position in the anterior compartment where it helps to form one of the anterior veins of the wing. Analysis of mutants for pentagone, a transcriptional target of Dpp that encodes a secreted feedback regulator of the pathway, indicates that Pentagone plays a key role in scaling the Dpp gradient activity.

Aging preferentially affects molecular pathways implicated in development and disease of myelinating glial cells

The central and peripheral nervous systems are involved in multiple age-dependent neurological deficits that are often attributed to alterations in function of myelinating glial cells. However, the molecular events that underlie the age-related decline of glial cell function are unknown. We used Schwann cells as a model to study biological processes affected in glial cells by aging. We comprehensively profiled gene expression of the Schwann cellrich mouse sciatic nerve throughout life, from day of birth until senescence (840 days of age). We combined the aging data with the microarray transcriptional data obtained using nerves isolated from Schwann cell-specific neuropathy-inducing mutants MPZCre/+/Lpin1fE2−3/fE2−3 , MPZCre/+/ScapfE1/fE1 and Pmp22-null mice. The majority of age related transcripts were also affected in the analyzed mouse models of neuropathy (54.4%) and in development (59.5%) indicating a high level of overlapping in implicated molecular pathways. We observed that compared to peripheral nerve development, dynamically changing expression profiles in aging have opposite (anticorrelated) orientation while they copy the orientation of transcriptional changes observed in analyzed neuropathy models. Subsequent clustering and biological annotation of dynamically changing transcripts revealed that the processes most significantly deregulated in aging include inflammatory/immune response and lipid biosynthesis/metabolism. Importantly, the changes in these pathways were also observed in myelinated oligodendrocyte-rich optic nerves of aged mice, albeit with lower magnitude. This observation suggests that similar biological processes are affected in aging glial cells in central and peripheral nervous systems, however with different dynamics. Our data, which provide the first comprehensive comparison of molecular changes in glial cells in three distinct biological conditions comprising development, aging and disease, provide not only a new inside into the molecular alterations underlying neural system aging but also identify target pathways for potential therapeutic approaches to prevent or delay complications associated with age-related and inherited forms of neuropathies. *Current address: Department of Physiology, UCSF, San Francisco, CA, USA.

Global transcriptional programs in peripheral nerve endoneurium and DRG are resistant to the onset of type 1 diabetic neuropathy in Ins2 mice.

While the morphological and electrophysiological changes underlying diabetic peripheral neuropathy (DPN) are relatively well described, the involved molecular mechanisms remain poorly understood. In this study, we investigated whether phenotypic changes associated with early DPN are correlated with transcriptional alterations in the neuronal (dorsal root ganglia [DRG]) or the glial (endoneurium) compartments of the peripheral nerve. We used Ins2(Akita/+) mice to study transcriptional changes underlying the onset of DPN in type 1 diabetes mellitus (DM). Weight, blood glucose and motor nerve conduction velocity (MNCV) were measured in Ins2(Akita/+) and control mice during the first three months of life in order to determine the onset of DPN. Based on this phenotypic characterization, we performed gene expression profiling using sciatic nerve endoneurium and DRG isolated from pre-symptomatic and early symptomatic Ins2(Akita/+) mice and sex-matched littermate controls. Our phenotypic analysis of Ins2(Akita/+) mice revealed that DPN, as measured by reduced MNCV, is detectable in affected animals already one week after the onset of hyperglycemia. Surprisingly, the onset of DPN was not associated with any major persistent changes in gene expression profiles in either sciatic nerve endoneurium or DRG. Our data thus demonstrated that the transcriptional programs in both endoneurial and neuronal compartments of the peripheral nerve are relatively resistant to the onset of hyperglycemia and hypoinsulinemia suggesting that either minor transcriptional alterations or changes on the proteomic level are responsible for the functional deficits associated with the onset of DPN in type 1 DM.

Correcting for the bias due to expression specificity improves the estimation of constrained evolution of expression between mouse and human.

MOTIVATION: Comparative analyses of gene expression data from different species have become an important component of the study of molecular evolution. Thus methods are needed to estimate evolutionary distances between expression profiles, as well as a neutral reference to estimate selective pressure. Divergence between expression profiles of homologous genes is often calculated with Pearson's or Euclidean distance. Neutral divergence is usually inferred from randomized data. Despite being widely used, neither of these two steps has been well studied. Here, we analyze these methods formally and on real data, highlight their limitations and propose improvements. RESULTS: It has been demonstrated that Pearson's distance, in contrast to Euclidean distance, leads to underestimation of the expression similarity between homologous genes with a conserved uniform pattern of expression. Here, we first extend this study to genes with conserved, but specific pattern of expression. Surprisingly, we find that both Pearson's and Euclidean distances used as a measure of expression similarity between genes depend on the expression specificity of those genes. We also show that the Euclidean distance depends strongly on data normalization. Next, we show that the randomization procedure that is widely used to estimate the rate of neutral evolution is biased when broadly expressed genes are abundant in the data. To overcome this problem, we propose a novel randomization procedure that is unbiased with respect to expression profiles present in the datasets. Applying our method to the mouse and human gene expression data suggests significant gene expression conservation between these species. CONTACT: marc.robinson-rechavi@unil.ch; sven.bergmann@unil.ch SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Aging preferentially affects molecular pathways implicated in development and disease of myelinating glial cells

The central and peripheral nervous systems are involved in multiple agedependent neurological deficits that are often attributed to alterations in function of myelinating glial cells. However, the molecular events that underlie the age-related decline of glial cell function are unknown. We used Schwann cells as a model to study biological processes affected in glial cells by aging. We comprehensively profiled gene expression of the Schwann cell-rich mouse sciatic nerve throughout life, from day of birth until senescence (840 days of age). We combined the aging data with the microarray transcriptional data obtained using nerves isolated from Schwann cell-specific neuropathy-inducing mutants MPZCre/þ/Lpin1fE2-3/fE2-3, MPZCre/þ/ScapfE1/fE1 and Pmp22-null mice. A majority of age related transcripts were also affected in the analyzed mouse models of neuropathy (54.4%) and in development (59.5%) indicating a high level of overlapping in implicated molecular pathways. We observed that compared to peripheral nerve development, dynamically changing expression profiles in aging have opposite (anticorrelated) orientation while they copy the orientation of transcriptional changes observed in analyzed neuropathy models. Subsequent clustering and biological annotation of dynamically changing transcripts revealed that the processes most significantly deregulated in aging include inflammatory/ immune response and lipid biosynthesis/metabolism. Importantly, the changes in these pathways were also observed in myelinated oligodendrocyte- rich optic nerves of aged mice, albeit with lower magnitude. This observation suggests that similar biological processes are affected in aging glial cells in central and peripheral nervous systems, however with different dynamics. Our data, which provide the first comprehensive comparison of molecular changes in glial cells in three distinct biological conditions comprising development, aging and disease, provide not only a new inside into the molecular alterations underlying neural system aging but also identify target pathways for potential therapeutical approaches to prevent or delay complications associated with age-related and inherited forms of neuropathies.

A genetic risk score combining 32 SNPs is associated with body mass index and improves obesity prediction in people with major depressive disorder.

BACKGROUND: Obesity is strongly associated with major depressive disorder (MDD) and various other diseases. Genome-wide association studies have identified multiple risk loci robustly associated with body mass index (BMI). In this study, we aimed to investigate whether a genetic risk score (GRS) combining multiple BMI risk loci might have utility in prediction of obesity in patients with MDD. METHODS: Linear and logistic regression models were conducted to predict BMI and obesity, respectively, in three independent large case-control studies of major depression (Radiant, GSK-Munich, PsyCoLaus). The analyses were first performed in the whole sample and then separately in depressed cases and controls. An unweighted GRS was calculated by summation of the number of risk alleles. A weighted GRS was calculated as the sum of risk alleles at each locus multiplied by their effect sizes. Receiver operating characteristic (ROC) analysis was used to compare the discriminatory ability of predictors of obesity. RESULTS: In the discovery phase, a total of 2,521 participants (1,895 depressed patients and 626 controls) were included from the Radiant study. Both unweighted and weighted GRS were highly associated with BMI (P <0.001) but explained only a modest amount of variance. Adding 'traditional' risk factors to GRS significantly improved the predictive ability with the area under the curve (AUC) in the ROC analysis, increasing from 0.58 to 0.66 (95% CI, 0.62-0.68; χ(2) = 27.68; P <0.0001). Although there was no formal evidence of interaction between depression status and GRS, there was further improvement in AUC in the ROC analysis when depression status was added to the model (AUC = 0.71; 95% CI, 0.68-0.73; χ(2) = 28.64; P <0.0001). We further found that the GRS accounted for more variance of BMI in depressed patients than in healthy controls. Again, GRS discriminated obesity better in depressed patients compared to healthy controls. We later replicated these analyses in two independent samples (GSK-Munich and PsyCoLaus) and found similar results. CONCLUSIONS: A GRS proved to be a highly significant predictor of obesity in people with MDD but accounted for only modest amount of variance. Nevertheless, as more risk loci are identified, combining a GRS approach with information on non-genetic risk factors could become a useful strategy in identifying MDD patients at higher risk of developing obesity.

Pom1 gradient buffering through intermolecular auto-phosphorylation.

Concentration gradients provide spatial information for tissue patterning and cell organization, and their robustness under natural fluctuations is an evolutionary advantage. In rod-shaped Schizosaccharomyces pombe cells, the DYRK-family kinase Pom1 gradients control cell division timing and placement. Upon dephosphorylation by a Tea4-phosphatase complex, Pom1 associates with the plasma membrane at cell poles, where it diffuses and detaches upon auto-phosphorylation. Here, we demonstrate that Pom1 auto-phosphorylates intermolecularly, both in vitro and in vivo, which confers robustness to the gradient. Quantitative imaging reveals this robustness through two system's properties: The Pom1 gradient amplitude is inversely correlated with its decay length and is buffered against fluctuations in Tea4 levels. A theoretical model of Pom1 gradient formation through intermolecular auto-phosphorylation predicts both properties qualitatively and quantitatively. This provides a telling example where gradient robustness through super-linear decay, a principle hypothesized a decade ago, is achieved through autocatalysis. Concentration-dependent autocatalysis may be a widely used simple feedback to buffer biological activities.