Epigenomic Landscapes of hESC-Derived Neural Rosettes: Modeling Neural Tube Formation and Diseases

We currently lack a comprehensive understanding of the mechanisms underlying neural tube formation and their contributions to neural tube defects (NTDs). Developing a model to study such a complex morphogenetic process, especially one that models human-specific aspects, is critical. Three-dimensional, human embryonic stem cell (hESC)-derived neural rosettes (NRs) provide a powerful resource for in vitro modeling of human neural tube formation. Epigenomic maps reveal enhancer elements unique to NRs relative to 2D systems. A master regulatory network illustrates that key NR properties are related to their epigenomic landscapes. We found that folate-associated DNA methylation changes were enriched within NR regulatory elements near genes involved in neural tube formation and metabolism. Our comprehensive regulatory maps offer insights into the mechanisms by which folate may prevent NTDs. Lastly, our distal regulatory maps provide a better understanding of the potential role of neurological-disorder-associated SNPs.</p

The emergence of the brain non-CpG methylation system in vertebrates

Mammalian brains feature exceptionally high levels of non-CpG DNA methylation alongside the canonical form of CpG methylation. Non-CpG methylation plays a critical regulatory role in cognitive function, which is mediated by the binding of MeCP2, the transcriptional regulator that when mutated causes Rett syndrome. However, it is unclear whether the non-CpG neural methylation system is restricted to mammalian species with complex cognitive abilities or has deeper evolutionary origins. To test this, we investigated brain DNA methylation across 12 distantly related animal lineages, revealing that non-CpG methylation is restricted to vertebrates. We discovered that in vertebrates, non-CpG methylation is enriched within a highly conserved set of developmental genes transcriptionally repressed in adult brains, indicating that it demarcates a deeply conserved regulatory program. We also found that the writer of non-CpG methylation, DNMT3A, and the reader, MeCP2, originated at the onset of vertebrates as a result of the ancestral vertebrate whole-genome duplication. Together, we demonstrate how this novel layer of epigenetic information assembled at the root of vertebrates and gained new regulatory roles independent of the ancestral form of the canonical CpG methylation. This suggests that the emergence of non-CpG methylation may have fostered the evolution of sophisticated cognitive abilities found in the vertebrate lineage.This work was supported by the Australian Research Council (ARC) Centre of Excellence programme in Plant Energy Biology (grant no. CE140100008). R.L. was supported by a Sylvia and Charles Viertel Senior Medical Research Fellowship, ARC Future Fellowship (no. FT120100862) and Howard Hughes Medical Institute International Research Scholarship. A.d.M. was funded by an EMBO long-term fellowship (no. ALTF 144-2014). J.L.G.-S. was supported by the Spanish government (grant no. BFU2016- 74961-P) and the institutional grant Unidad de Excelencia María de Maeztu (no. MDM-2016-0687). B.V. was supported by the Biomedical Research Council of the Agency for Science, Technology and Research of Singapore. F.G. was supported by an ARC Future Fellowship (no. FT160100267). C.W.R. was supported by an NSF grant (no. IOS-1354898). J.R.E. is an investigator of the Howard Hughes Medical Institute. Genomic data was generated at the Australian Cancer Research Foundation Centre for Advanced Cancer Genomics

Human prefrontal cortex gene regulatory dynamics from gestation to adulthood at single-cell resolution.

Human brain development is underpinned by cellular and molecular reconfigurations continuing into the third decade of life. To reveal cell dynamics orchestrating neural maturation, we profiled human prefrontal cortex gene expression and chromatin accessibility at single-cell resolution from gestation to adulthood. Integrative analyses define the dynamic trajectories of each cell type, revealing major gene expression reconfiguration at the prenatal-to-postnatal transition in all cell types followed by continuous reconfiguration into adulthood and identifying regulatory networks guiding cellular developmental programs, states, and functions. We uncover links between expression dynamics and developmental milestones, characterize the diverse timing of when cells acquire adult-like states, and identify molecular convergence from distinct developmental origins. We further reveal cellular dynamics and their regulators implicated in neurological disorders. Finally, using this reference, we benchmark cell identities and maturation states in organoid models. Together, this captures the dynamic regulatory landscape of human cortical development.This work was supported by the following grants: R.L.—National Health and Medical Research Council (NHMRC) Project Grant 1130168, NHMRC Investigator Grant 1178460, Silvia and Charles Viertel Senior Medical Research Fellowship, Howard Hughes Medical Institute International Research Scholarship, and Australian Research Council (ARC) LE170100225; S.F.—NHMRC Ideas Grant 1184421; I.V.—ARC Future Fellowship FT170100359, UNSW Scientia Fellowship, and NHMRC Project Grant RG170137; S.B.—NHMRC-ARC Dementia Research Development Fellowship 1111206; C.P.—Raine Foundation Priming Grant RPG66-21; J.M.P.—Silvia and Charles Viertel Senior Medical Research Fellowship, ARC Future Fellowship FT180100674. This work was supported by a Cancer Research Trust grant ‘‘Enabling advanced single cell cancer genomics in WA’’ and Cancer Council WA enabling grant. Genomic data were generated at the ACRF Centre for Advanced Cancer Genomics and Genomics WA. Human brain tissue was received from the UMB Brain and Tissue Bank at the University of Maryland, part of the NIH NeuroBioBank. The glioblastoma sample was procured and provided by the AGOG biobank, funded by CINSW grant SRP-08-10. L.M. was a fellow of The Lorenzo and Pamela Galli Medical Research Trust. We thank Ankur Sharma and Greg Neely for valuable feedback. The graphical abstract and elements of Figure 1A were created with BioRender.S

An integrative analysis of the human placental transcriptome

Pregnancy outcome is inextricably linked to placental development, which is strictly regulated both temporally and spatially by mechanisms that are only partially understood. Although the placenta is absolutely indispensable for fetal development in utero, it remains the least understood human tissue. Although the placenta is a shared organ between the mother and fetus, it is of embryonic origin, and therefore its development is largely regulated by the fetal genome. This overall goal of this research was to investigate three key aspects of human placental gene regulation: (1) The effect of genomic imprinting on gene regulation, (2) the differences in placental gene expression between the sexes, and (3) the co-expression relationships that exist between genes on a transcriptome scale. Firstly, this research identified a window of epigenetic imprinting plasticity for the long non-coding RNA H19, which is heavily implicated in placental development and function. These results suggested that variation in H19 imprinting may contribute to early programming of placental phenotype and highlighted the need for quantitative and robust methodologies to further elucidate the role of imprinted genes in normal and pathological placental development. Secondly, by conducting a transcriptome-scale meta-analysis of sex-biased gene expression, this research revealed that 140 genes are differentially expressed between male and female placentae. A majority of these genes are autosomal, many of which are involved in high-level regulatory processes such as gene transcription, cell growth and proliferation and hormonal function. Of particular interest, all genes in the LHB-CGB cluster were expressed more highly in female placentas, which includes genes involved in placental development, the maintenance of pregnancy and maternal immune tolerance of the conceptus. These results demonstrated that sex-biased gene expression in the normal human placenta occurs across the genome and includes genes that are central to growth, development and the maintenance of pregnancy. Thirdly, by undertaking a comprehensive analysis of human placental gene co-expression using RNA sequencing and the integration of five human and one mouse transcriptome dataset, this research identified clusters of correlated genes, whose patterns of co-expression are highly preserved across human gestation and between human and mouse, subsequently revealing highly conserved molecular networks involved in placental development. Furthermore, by reducing the complexity of the placental transcriptome by summarizing co-expressed genes, this work identified a group of co-expressed genes implicated in preeclampsia and also outlines a novel method for identifying for non-invasive biomarkers of placental development. In summary, each aspect of this PhD research has provided new insights into how gene expression is regulated in the human placenta and has revealed previously unappreciated aspects of the placental transcriptional landscape.Thesis (Ph.D.) (Research by Publication) -- University of Adelaide, School of Paediatrics and Reproductive Health, 2015

Large scale gene expression meta-analysis reveals tissue-specific, sex-biased gene expression in humans

The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased gene expression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased gene expression in multiple human tissues. We analysed 22 publicly available human gene expression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of gene expression between males and females. We found the greatest sex differences in gene expression in the brain, specifically in the anterior cingulate cortex, (1818 genes), followed by the heart (375 genes), kidney (224 genes), colon (218 genes) and thyroid (163 genes). More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased gene expression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases

Integrative transcriptome metaanalysis reveals widespread sex-biased gene expression at the human fetal-maternal interface

As males and females share highly similar genomes, the regulation of many sexually dimorphic traits is constrained to occur through sex-biased gene regulation. There is strong evidence that human males and females differ in terms of growth and development in utero and that these divergent growth strategies appear to place males at increased risk when in sub-optimal conditions. Since the placenta is the interface of maternal-fetal exchange throughout pregnancy, these developmental differences are most likely orchestrated by differential placental function. To date, progress in this field has been hampered by a lack of genome-wide information on sex differences in placental gene expression. Therefore, our motivation in this study was to characterize sex-biased gene expression in the human placenta. We obtained gene expression data for > 300 non-pathological placenta samples from11 microarray datasets and applied mapping-based array probe re-annotation and inverse-variance meta-analysis methods which showed that > 140 genes (false discovery rate (FDR) 60%) are autosomal, many of which are involved in high-level regulatory processes such as gene transcription, cell growth and proliferation and hormonal function. Of particular interest, we detected higher female expression from all seven genes in the LHB-CGB cluster, which includes genes involved in placental development, the maintenance of pregnancy and maternal immune tolerance of the conceptus. These results demonstrate that sex-biased gene expression in the normal human placenta occurs across the genome and includes genes that are central to growth, development and the maintenance of pregnancy

Allelic expression ratios for <i>H19, IGF2</i> and <i>IGF2R</i> in the human placenta.

<p>The 50∶50 ratio represents equal expression from both alleles and 0∶100 ratio represents expression exclusively from one allele. Each point on the graph represents the allelic expression ratio measured in an individual placental sample. <i>H19</i> and <i>IGF2</i> samples are from first trimester and term placentae, <i>IGF2R</i> samples are all from first trimester placentae.</p

Ratio of expression from each allele in human first trimester and term placentae measured by pyrosequencing.

<p>Each point on the graph represents the allelic expression ratio observed in an individual placental sample. (<b>A</b>) <i>H19</i> allelic expression ratio for each gestational age class. (<b>B</b>) Expression from the <i>H19</i> repressed allele is significantly higher (*<i>P</i><0.001) in first trimester placental samples. (<b>C-D</b>) <i>IGF2</i> allelic expression ratios are similar for each gestational age class (<b>C</b>) with no significant difference (<b>D</b>) between first trimester and term. First trimester samples are 6–12 weeks of gestation term samples are 37–42 weeks of gestation.</p