Epigenetic regulation in neural crest development : role of DNA methyltransferases 3A and 3B

The neural crest is a group of migratory, multipotent stem cells that play a crucial role in many aspects of embryonic development. This uniquely vertebrate cell population forms within the dorsal neural tube but then emigrates out and migrates long distances to different regions of the body. These cells contribute to formation of many structures such as the peripheral nervous system, craniofacial skeleton, and pigmentation of the skin. Why some neural tube cells undergo a change from neural to neural crest cell fate is unknown as is the timing of both onset and cessation of their emigration from the neural tube. In recent years, growing evidence supports an important role for epigenetic regulation as a new mechanism for controlling aspects of neural crest development. In this thesis, I dissect the roles of the de novo DNA methyltransferases (DNMTs) 3A and 3B in neural crest specification, migration and differentiation. First, I show that DNMT3A limits the spatial boundary between neural crest versus neural tube progenitors within the neuroepithelium. DNMT3A promotes neural crest specification by directly mediating repression of neural genes, like Sox2 and Sox3. Its knockdown causes ectopic Sox2 and Sox3 expression at the expense of neural crest territory. Thus, DNMT3A functions as a molecular switch, repressing neural to favor neural crest cell fate. Second, I find that DNMT3B restricts the temporal window during which the neural crest cells emigrate from the dorsal neural tube. Knockdown of DNMT3B causes an excess of neural crest emigration, by extending the time that the neural tube is competent to generate emigrating neural crest cells. In older embryos, this resulted in premature neuronal differentiation. Thus, DNMT3B regulates the duration of neural crest production by the neural tube and the timing of their differentiation. My results in avian embryos suggest that de novo DNA methylation, exerted by both DNMT3A and DNMT3B, plays a dual role in neural crest development, with each individual paralogue apparently functioning during a distinct temporal window. The results suggest that de novo DNA methylation is a critical epigenetic mark used for cell fate restriction of progenitor cells during neural crest cell fate specification. Our discovery provides important insights into the mechanisms that determine whether a cell becomes part of the central nervous system or peripheral cell lineages.

Metastability and dynamics of stem cells: from direct observations to inference at the single cell level

Organismal development, homeostasis, and pathology are rooted in inherently probabilistic events. From gene expression to cellular differentiation, rates and likelihoods shape the form and function of biology. Processes ranging from growth to cancer homeostasis to reprogramming of stem cells all require transitions between distinct phenotypic states, and these occur at defined rates. Therefore, measuring the fidelity and dynamics with which such transitions occur is central to understanding natural biological phenomena and is critical for therapeutic interventions.

While these processes may produce robust population-level behaviors, decisions are made by individual cells. In certain circumstances, these minuscule computing units effectively roll dice to determine their fate. And while the 'omics' era has provided vast amounts of data on what these populations are doing en masse, the behaviors of the underlying units of these processes get washed out in averages.

Therefore, in order to understand the behavior of a sample of cells, it is critical to reveal how its underlying components, or mixture of cells in distinct states, each contribute to the overall phenotype. As such, we must first define what states exist in the population, determine what controls the stability of these states, and measure in high dimensionality the dynamics with which these cells transition between states.

To address a specific example of this general problem, we investigate the heterogeneity and dynamics of mouse embryonic stem cells (mESCs). While a number of reports have identified particular genes in ES cells that switch between 'high' and 'low' metastable expression states in culture, it remains unclear how levels of many of these regulators combine to form states in transcriptional space. Using a method called single molecule mRNA fluorescent in situ hybridization (smFISH), we quantitatively measure and fit distributions of core pluripotency regulators in single cells, identifying a wide range of variabilities between genes, but each explained by a simple model of bursty transcription. From this data, we also observed that strongly bimodal genes appear to be co-expressed, effectively limiting the occupancy of transcriptional space to two primary states across genes studied here. However, these states also appear punctuated by the conditional expression of the most highly variable genes, potentially defining smaller substates of pluripotency.

Having defined the transcriptional states, we next asked what might control their stability or persistence. Surprisingly, we found that DNA methylation, a mark normally associated with irreversible developmental progression, was itself differentially regulated between these two primary states. Furthermore, both acute or chronic inhibition of DNA methyltransferase activity led to reduced heterogeneity among the population, suggesting that metastability can be modulated by this strong epigenetic mark.

Finally, because understanding the dynamics of state transitions is fundamental to a variety of biological problems, we sought to develop a high-throughput method for the identification of cellular trajectories without the need for cell-line engineering. We achieved this by combining cell-lineage information gathered from time-lapse microscopy with endpoint smFISH for measurements of final expression states. Applying a simple mathematical framework to these lineage-tree associated expression states enables the inference of dynamic transitions. We apply our novel approach in order to infer temporal sequences of events, quantitative switching rates, and network topology among a set of ESC states.

Taken together, we identify distinct expression states in ES cells, gain fundamental insight into how a strong epigenetic modifier enforces the stability of these states, and develop and apply a new method for the identification of cellular trajectories using scalable in situ readouts of cellular state.

Integrative genomic, epigenetic and metabolomic characterization of beef from grass-fed Angus steers

Beef constitutes a main component of the American diet and still represent the principal source of protein in many parts of the world. Currently, the meat market is experiencing an important transformation; consumers are increasingly switching from consuming traditional beef to grass-fed beef. People recognized products obtained from grass-fed animals as more natural and healthy. However, the true variations between these two production systems regarding various aspects remain unclear. This dissertation provides information from closely genetically related animals, in order to decrease confounding factors, to explain several confused divergences between grain-fed and grass-fed beef. First, we examined the growth curve, important economic traits and quality carcass characteristics over four consecutive years in grain-fed and grass-fed animals, generating valuable information for management decisions and economic evaluation for grass-fed cattle operations. Second, we performed the first integrated transcriptomic and metabolomic analysis in grass-fed beef, detecting alterations in glucose metabolism, divergences in free fatty acids and carnitine conjugated lipid levels, and altered β-oxidation. Results suggest that grass finished beef could possibly benefit consumer health from having lower total fat content and better lipid profile than grain-fed beef. Regarding animal welfare, grass-fed animals may experience less stress than grain-fed individuals as well. Finally, we contrasted the genome-wide DNA methylation of grass-fed beef against grain-fed beef using the methyl-CpG binding domain sequencing (MBD-Seq) method, identifying 60 differentially methylated regions (DMRs). Most of DMRs were located inside or upstream of genes and displayed increased levels of methylation in grass-fed individuals, implying a global DNA methylation increment in this group. Interestingly, chromosome 14, which has been associated with large effects on ADG, marbling, back fat, ribeye area and hot carcass weight in beef cattle, allocated the largest number of DMRs (12/60). The pathway analysis identified skeletal and muscular system as the preeminent physiological system and function, and recognized carbohydrates metabolism, lipid metabolism and tissue morphology among the highest ranked networks. Therefore, although we recognize some limitations and assume that additional examination is still required, this project provides the first integrative genomic, epigenetic and metabolomics characterization of beef produced under grass-fed regimen.

Differential expression in “rogue” paramutation in peas (Pisum sativum L.)

Dissertação de Mestrado, Engenharia Biológica, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2014

Past, present and future of epigenetics applied to livestock breeding

This article reviews the concept of Lamarckian inheritance and the use of the term epigenetics in the field of animal genetics. Epigenetics was first coined by Conrad Hal Waddington (1905–1975), who derived the term from the Aristotelian word epigenesis. There exists some controversy around the word epigenetics and its broad definition. It includes any modification of the expression of genes due to factors other than mutation in the DNA sequence. This involves DNA methylation, post-translational modification of histones, but also linked to regulation of gene expression by non-coding RNAs, genome instabilities or any other force that could modify a phenotype. There is little evidence of the existence of transgenerational epigenetic inheritance in mammals, which may commonly be confounded with environmental forces acting simultaneously on an individual, her developing fetus and the germ cell lines of the latter, although it could have an important role in the cellular energetic status of cells. Finally, we review some of the scarce literature on the use of epigenetics in animal breeding programs.

Epigenetic markers to predict conversion from gestational diabetes to type 2 diabetes

CONTEXT: Lifestyle factors mediate epigenetic changes that can cause chronic diseases. Although animal and laboratory studies link epigenetic changes to diabetes, epigenetic information in women with gestational diabetes (GDM) and type 2 diabetes is lacking. OBJECTIVE: To measure epigenetic markers across pregnancy and early postpartum and identify markers that could be used as predictors for conversion from GDM to type 2 diabetes. DESIGN: Global histone H3 dimethylation was measured at three time points: 30 weeks gestation, 8-10 weeks postpartum and 20 weeks postpartum, in white blood cells from four groups of women with and without diabetes. SETTING AND PARTICIPANTS: A total of 39 participants (six to nine in each group) were recruited including: non-diabetic women; women with GDM who developed postpartum type 2 diabetes; women with GDM without postpartum type 2 diabetes; and women with type 2 diabetes. MAIN OUTCOME MEASURE: Percentages of dimethylation of H3 histones relative to total H3 histone methylation were compared between diabetic/non-diabetic groups using appropriate comparative statistics. RESULTS: H3K27 dimethylation was 50-60% lower at 8-10 and 20 weeks postpartum in women with GDM who developed type 2 diabetes, compared with non-diabetic women. H3K4 dimethylation was 75% lower at 8-10 weeks postpartum in women with GDM who subsequently developed type 2 diabetes compared with women who had GDM who did not. CONCLUSIONS: The percentage of dimethylation of histones H3K27 and H3K4 varied with diabetic state and has the potential as a predictive tool to identify women who will convert from GDM to type 2 diabetes.