Epigenetics and Noncoding RNA – Principles and Clinical Impact

Genetics studies the inheritance of genetic information encoded by the base pair sequence and its variants. Sequence variants can have severe consequences as seen in genetically inherited diseases (e. g. osteogenesis Imperfecta, hypophosphatasia). On the other hand, epigenetics deals with inherited and dynamically reversible modifications of chromatin without changing the base pair sequence, resulting in a change in phenotype without a change in genotype. These modifications primarily exert their effects by influencing gene expression. Initially, the definition of epigenetics exclusively comprised inherited changes that persist across several generations without changes in the DNA sequence. This definition has been extended to include also dynamic and partially reversible changes that occur more short-term. These gene modulatory effects introduce new levels of complexity and are crucial determinants of cell fate and organismal development. With its length of approximately two meters, human DNA has to be compacted to fit into the nuclei and fulfill its functions. DNA is wrapped around histone octamers into so-called nucleosomes. DNA, histones, and other DNA-associated proteins together form what is called chromatin. DNA packaging is achieved by variable degrees of chromatin condensation depending on cell type and context. Epigenetic transcriptional regulation modifies the affinity and accessibility of cis-regulatory elements (CREs) for transcription factors and the basic transcriptional machinery and governs interaction between CREs. CREs include promoters, enhancers, silencers, and insulators and are potent modulators of gene expression impacting core cell biological processes such as proliferation and differentiation. Chromatin looping and remodeling by differential covalent modifications of DNA (e. g., methylation or hydroxylation) and histone tails (e. g., acetylation or methylation) elicit fundamental changes in CRE accessibility, thus impacting gene expression. Chromatin looping depends on a specialized machinery including cohesins. Chromatin modifications are mediated by specific enzymes like DNA methylases (DNMTs), histone-modifying enzymes, like histone methyl- and acetyltransferases (KMTs, HATs/KATs), and histone demethylases and deacetylases (KDMs, HDACs). It becomes increasingly evident that epigenetic (dys)regulation plays a decisive role in physiology and pathophysiology, impacting many age-related diseases like cancer and degenerative pathologies (e. g., osteoporosis, Alzheimer’s, or Parkinson’s) in a significant fashion. Recently, small-molecule inhibitors of chromatin-modifying enzymes (e. g., vorinostat) have been identified and successfully introduced in therapy. Significant progress in high-throughput sequencing technologies and big data analysis has broadened our understanding of noncoding (nc) RNAs and DNA sequence regions in (post-)transcriptional regulation and disease development. Among ncRNAs that play vital roles in gene expression are micro- (miRs) and long noncoding RNAs (lncRNAs; e. g., XIST or HOTAIR). By interacting with the coding genome, these RNAs modulate important genetic programs. Interfering RNAs can, for example, enhance the post-transcriptional degradation of transcripts, altering their translation, or assist in the recruitment of chromatin-modifying enzymes to regulate transcription. They can also be packaged into extracellular vesicles as cargo and thus deliver critical information to the microenvironment or even systemically to distant tissues. Therefore, ncRNAs represent a novel playground for therapeutical investigations and supplement epigenetic mechanisms of gene regulation while being subject to epigenetic regulation themselves. Last but not least, dysregulated ncRNAs can also propagate disease. Until recently, the detection of epigenetic phenomena necessitated invasive diagnostic interventions. However, with the arrival of so-called “liquid biopsies” an analysis of circulating cell-free DNA fragments (cfDNA) and RNAs as well as vesicle-packed RNAs through minimal invasively drawn blood samples can be obtained. Such “fragmentomics” and RNAomics approaches on peripheral blood will ultimately serve as diagnostic tools for personalized clinical interventions.

Efficient CRISPR-Cas9-Mediated Knock-In of Composite Tags in Zebrafish Using Long ssDNA as a Donor

Despite the unprecedented gene editing capability of CRISPR-Cas9-mediated targeted knock-in, the efficiency and precision of this technology still require further optimization, particularly for multicellular model organisms, such as the zebrafish (Danio rerio). Our study demonstrated that an ∼200 base-pair sequence encoding a composite tag can be efficiently “knocked-in” into the zebrafish genome using a combination of the CRISPR-Cas9 ribonucleoprotein complex and a long single-stranded DNA (lssDNA) as a donor template. Here, we targeted the sox3, sox11a, and pax6a genes to evaluate the knock-in efficiency of lssDNA donors with different structures in somatic cells of injected embryos and for their germline transmission. The structures and sequence characteristics of the lssDNA donor templates were found to be crucial to achieve a high rate of precise and heritable knock-ins. The following were our key findings: (1) lssDNA donor strand selection is important; however, strand preference and its dependency appear to vary among the target loci or their sequences. (2) The length of the 3′ homology arm of the lssDNA donor affects knock-in efficiency in a site-specific manner; particularly, a shorter 50-nt arm length leads to a higher knock-in efficiency than a longer 300-nt arm for the sox3 and pax6a knock-ins. (3) Some DNA sequence characteristics of the knock-in donors and the distance between the CRISPR-Cas9 cleavage site and the tag insertion site appear to adversely affect the repair process, resulting in imprecise editing. By implementing the proposed method, we successfully obtained precisely edited sox3, sox11a, and pax6a knock-in alleles that contained a composite tag composed of FLAGx3 (or PAx3), Bio tag, and HiBiT tag (or His tag) with moderate to high germline transmission rates as high as 21%. Furthermore, the knock-in allele-specific quantitative polymerase chain reaction (qPCR) for both the 5′ and 3′ junctions indicated that knock-in allele frequencies were higher at the 3′ side of the lssDNAs, suggesting that the lssDNA-templated knock-in was mediated by unidirectional single-strand template repair (SSTR) in zebrafish embryos.

In situ genome sequencing resolves DNA sequence and structure in intact biological samples

Understanding genome organization requires integration of DNA sequence and three-dimensional spatial context; however, existing genome-wide methods lack either base pair sequence resolution or direct spatial localization. Here, we describe in situ genome sequencing (IGS), a method for simultaneously sequencing and imaging genomes within intact biological samples. We applied IGS to human fibroblasts and early mouse embryos, spatially localizing thousands of genomic loci in individual nuclei. Using these data, we characterized parent-specific changes in genome structure across embryonic stages, revealed single-cell chromatin domains in zygotes, and uncovered epigenetic memory of global chromosome positioning within individual embryos. These results demonstrate how IGS can directly connect sequence and structure across length scales from single base pairs to whole organisms.

Identification of ICS Security Risks toward the Analysis of Packet Interaction Characteristics Using State Sequence Matching Based on SF-FSM

This paper discusses two aspects of major risks related to the cyber security of an industrial control system (ICS), including the exploitation of the vulnerabilities of legitimate communication parties and the features abused by unauthorized parties. We propose a novel framework for exposing the above two types of risks. A state fusion finite state machine (SF-FSM) model is defined to describe multiple request-response packet pair sequence signatures of various applications using the same protocol. An inverted index of keywords in an industrial protocol is also proposed to accomplish fast state sequence matching. Then we put forward the concept of scenario reconstruction, using state sequence matching based on SF-FSM, to present the known vulnerabilities corresponding to applications of a specific type and version by identifying the packet interaction characteristics from the data flow in the supervisory control layer network. We also implement an anomaly detection approach to identifying illegal access using state sequence matching based on SF-FSM. An anomaly is asserted if none of the state sequence signatures in the SF-FSM is matched with a packet flow. Ultimately, an example based on industrial protocols is demonstrated by a prototype system to validate the methods of scenario reconstruction and anomaly detection.

Determining ERβ Binding Affinity to Singly Mutant ERE Using Dual Polarization Interferometry

In a classic mode of estrogen action, estrogen receptors (ERs) bind to estrogen responsive element (ERE) to activate gene transcription. A perfect ERE contains a 13-base pair sequence of a palindromic repeat separated by a three-base spacer, 5′-GGTCAnnnTGACC-3′. In addition to the consensus or wild-type ERE (wtERE), naturally occurring EREs often have one or two base pairs’ alternation. Based on the newly constructed Thermodynamic Modeling of ChIP-seq (TherMos) model, binding energy between ER[Formula: see text] and a series of 34-bp mutant EREs (mutERE) was simulated to predict the binding affinity between ERs and EREs with single base pair deviation at different sites of the 13-bp inverted sequence. Experimentally, dual polarization interferometry (DPI) method was developed to measure ER[Formula: see text]–mutEREs binding affinity. On a biotin-NeutrAvidin (NA)-biotin treated DPI chip, wtERE is immobilized. In a direct binding assay, ER[Formula: see text]–wtERE binding affinity is determined. In a competition assay, ER[Formula: see text] was preincubated with mutant EREs before being added for competitive binding to the immobilized wtERE. This competition strategy provided a successful platform to evaluate the binding affinity variation among large number of ERE with different base mutations. The experimental result correlates well with the mathematically predicted binding energy with a Spearman correlation coefficient of 0.97.

Obesity: epigenetic aspects

Epigenetics, defined as inheritable and reversible phenomena that affect gene expression without altering the underlying base pair sequence has been shown to play an important role in the etiopathogenesis of obesity. Obesity is associated with extensive gene expression changes in tissues throughout the body. Epigenetics is emerging as perhaps the most important mechanism through which the lifestyle-choices we make can directly influence the genome. Considerable epidemiological, experimental and clinical data have been amassed showing that the risk of developing disease in later life is dependent on early life conditions, mainly operating within the normative range of developmental exposures. In addition to the ‘maternal’ interactions, there has been increasing interest in the epigenetic mechanisms through which ‘paternal’ influences on offspring development can be achieved. Nutrition, among many other environmental factors, is a key player that can induce epigenetic changes not only in the directly exposed organisms but also in subsequent generations through the transgenerational inheritance of epigenetic traits. Overall, significant progress has been made in the field of epigenetics and obesity and the first potential epigenetic markers for obesity that could be detected at birth have been identified. Fortunately, epigenetic phenomena are dynamic and rather quickly reversible with intensive lifestyle changes. This is a very promising and sustainable resolution to the obesity pandemic.

Estimating Constitutive Law of a Filament From its Deformed Shapes Using Input Reconstruction

Twisting and bending dynamics of biological filaments such as DNA play a central role in their biological activity including gene expression. The elastic rod model is an efficient tool to simulate such deformations. However, the accuracy of elastic rod predictions depend strongly on the constitutive law, which follows from the atomistic structure of the DNA molecule and is known to be nonlinear and to vary along the length according to the base pair sequence of the DNA. Unfortunately, it is impractical to derive the constitutive law analytically from the atomistic structure. Identification of the nonlinear sequence-dependent constitutive law from experimental data and feasible molecular dynamics simulations remains a significant challenge. In this paper, we extend earlier work by employing techniques based on input reconstruction and state estimation filters to estimate the constitutive law using molecular dynamics data of deformations in bio-filaments.