Underlying DNA Sequence Research Articles

Epigenetic Modulations for Prevention of Infectious Diseases in Shrimp Aquaculture.

Aquaculture assumes a pivotal role in meeting the escalating global food demand, and shrimp farming, in particular, holds a significant role in the global economy and food security, providing a rich source of nutrients for human consumption. Nonetheless, the industry faces formidable challenges, primarily attributed to disease outbreaks and the diminishing efficacy of conventional disease management approaches, such as antibiotic usage. Consequently, there is an urgent imperative to explore alternative strategies to ensure the sustainability of the industry. In this context, the field of epigenetics emerges as a promising avenue for combating infectious diseases in shrimp aquaculture. Epigenetic modulations entail chemical alterations in DNA and proteins, orchestrating gene expression patterns without modifying the underlying DNA sequence through DNA methylation, histone modifications, and non-coding RNA molecules. Utilizing epigenetic mechanisms presents an opportunity to enhance immune gene expression and bolster disease resistance in shrimp, thereby contributing to disease management strategies and optimizing shrimp health and productivity. Additionally, the concept of epigenetic inheritability in marine animals holds immense potential for the future of the shrimp farming industry. To this end, this comprehensive review thoroughly explores the dynamics of epigenetic modulations in shrimp aquaculture, with a particular emphasis on its pivotal role in disease management. It conveys the significance of harnessing advantageous epigenetic changes to ensure the long-term viability of shrimp farming while deliberating on the potential consequences of these interventions. Overall, this appraisal highlights the promising trajectory of epigenetic applications, propelling the field toward strengthening sustainability in shrimp aquaculture.

Elevated Plasma Copeptin Levels Identify the Presence and Severity of Nonalcoholic Fatty Liver Disease in Obesity

Abstract Background Non-alcoholic fatty liver disease is characterized by excessive fat accumulation in the liver with unclear mechanism may be due to epigenetic changes which take place at the transcriptional level without altering the underlying DNA sequence. this epigenetic alternation are involved in regulation of hepatic lipid metabolism, insulin resistance, mitochondrial damage, oxidative stress response, and the release of inflammatory cytokines, all of which have been implicated in the development and progression of NAFLD. Elevated copeptin, a vasopressin marker, is linked to metabolic disease, and obese rats with lowvasopressin concentration had a decreased risk of liver steatosis. Aim and objectives To Detect the elevation of plasma copeptin in obese patients with nonalcoholic fatty liver disease in relation to general population. Subjects and Methods This is A randomized case control cross sectional study, was carried out at internal medicine and gastroenterology department, Ain Shams University hospitals, on 100 patients above 18 years old with Hepatic Steatosis Index (HSI) and NAFLD-Liver Fat Score (LFS), over a period of 6 months. Result There was high statistically significant difference between the studied groups as regard Serum plasma copeptin. Conclusion Our study demonstrates for the first time that copeptin levels predict the presence of biopsy-proven NAFLD in obese individuals, regardless of body adiposity and the coexistence of other metabolic disorders. Studies with longitudinal design are warranted for exploring the possible involvement of AVP/V1aR system in the development and progression of NAFLD.

Prediction accuracy of regulatory elements from sequence varies by functional sequencing technique.

Various sequencing based approaches are used to identify and characterize the activities of cis-regulatory elements in a genome-wide fashion. Some of these techniques rely on indirect markers such as histone modifications (ChIP-seq with histone antibodies) or chromatin accessibility (ATAC-seq, DNase-seq, FAIRE-seq), while other techniques use direct measures such as episomal assays measuring the enhancer properties of DNA sequences (STARR-seq) and direct measurement of the binding of transcription factors (ChIP-seq with transcription factor-specific antibodies). The activities of cis-regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers. Here, machine learning models are employed to evaluate the accuracy with which cis-regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis-regulatory activity that is reflective of sequence content versus secondary processes. Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis-regulatory element prediction.

Characterization of an eye field-like state during optic vesicle organoid development.

Specification of the eye field (EF) within the neural plate marks the earliest detectable stage of eye development. Experimental evidence, primarily from non-mammalian model systems, indicates that the stable formation of this group of cells requires the activation of a set of key transcription factors (TFs). This critical event is challenging to probe in mammals and, quantitatively, little is known regarding the regulation of the transition of cells to this ocular fate. Using optic vesicle organoids to model the onset of the EF, we generate timecourse transcriptomic data allowing us to identify dynamic gene expression programs that characterise this cellular-state transition. Integrating this with chromatin accessibility data suggests a direct role of canonical EFTFs in regulating these gene expression changes, and highlights candidate cis-regulatory elements through which these TFs act. Finally, we begin to test a subset of these candidate enhancer elements, within the organoid system, by perturbing the underlying DNA sequence and measuring transcriptomic changes during EF activation.

Environment, Epigenetics, and the Pace of Human Aging

The trajectory of human aging varies widely from one individual to the next due to complex interactions between the genome and the environment that influence the aging process. Such differences in age-specific mortality and disease risk among same-aged individuals reflect variation in the pace of biological aging. Certain mechanisms involved in the progression of biological aging originate in the epigenome, where chemical modifications to the genome are able to alter gene expression without modifying the underlying DNA sequence. The epigenome serves as an interface for environmental signals, which are able to “get under the skin” to influence health and aging. A number of the molecular mechanisms involved in the aging process have been identified, although few aging phenotypes have been definitively traced to their underlying molecular causes thus far. In this review, we discuss variation in human biological aging and the epigenome's role in promoting heterogeneity in human longevity and healthspan.

Graph Theory in DNA Sequencing: Unveiling Genetic Patterns

Graph theory, a branch of mathematics that studies the properties and relationships of graphs, has emerged as a powerful tool in addressing the complexities of DNA sequencing. This paper highlights the application of graph theory in DNA sequencing and its implications in various aspects of genomics research. One fundamental concept in graph theory applied to DNA sequencing is the construction of the de Bruijn graph. This graph represents overlapping k-mers, subsequences of length k, as nodes, with edges connecting adjacent k-mers. By constructing and analyzing the de Bruijn graph, researchers can infer the underlying DNA sequence, detect errors, resolve repetitive regions, and identify structural variations in the genome. Graph algorithms such as Overlap path, Eulerian path and Hamiltonian path have been adapted to reconstruct complete DNA sequences from fragmented reads obtained through sequencing. These algorithms leverage the connectivity information present in the de Bruijn graph to traverse and assemble the reads, enabling the reconstruction of long DNA sequences accurately. the application of graph theory in DNA sequencing has revolutionized the field of genomics by providing powerful computational tools for DNA assembly, sequence analysis, and functional annotation. By leveraging graph theory concepts and algorithms, researchers can unravel the intricate information embedded within DNA sequences, leading to deeper insights into the genetic basis of life and its applications in various fields, including medicine, agriculture, and evolutionary biology. Future developments in graph-based algorithms and computational techniques hold promise for further enhancing our ability to unlock the secrets encoded within the vast realm of DNA sequences.

Novel Differentially Methylated Regions Identified by Genome-Wide DNA Methylation Analyses Contribute to Racial Disparities in Childhood Obesity.

The magnitude of the childhood obesity epidemic and its effects on public health has accelerated the pursuit of practical preventative measures. Epigenetics is one subject that holds a lot of promise, despite being relatively new. The study of potentially heritable variations in gene expression that do not require modifications to the underlying DNA sequence is known as epigenetics. Here, we used Illumina MethylationEPIC BeadChip Array to identify differentially methylated regions in DNA isolated from saliva between normal weight (NW) and overweight/obese (OW/OB) children and between European American (EA) and African American (AA) children. A total of 3133 target IDs (associated with 2313 genes) were differentially methylated (p < 0.05) between NW and OW/OB children. In OW/OB children, 792 target IDs were hypermethylated and 2341 were hypomethylated compared to NW. Similarly, in the racial groups EA and AA, a total of 1239 target IDs corresponding to 739 genes were significantly differentially methylated in which 643 target IDs were hypermethylated and 596 were hypomethylated in the AA compared to EA participants. Along with this, the study identified novel genes that could contribute to the epigenetic regulation of childhood obesity.

Genetics and epigenetics in the obesity phenotyping scenario.

Obesity is a common complex trait that elevates the risk for various diseases, including type 2 diabetes and cardiovascular disease. A combination of environmental and genetic factors influences the pathogenesis of obesity. Advances in genomic technologies have driven the identification of multiple genetic loci associated with this disease, ranging from studying severe onset cases to investigating common multifactorial polygenic forms. Additionally, findings from epigenetic analyses of modifications to the genome that do not involve changes to the underlying DNA sequence have emerged as key signatures in the development of obesity. Such modifications can mediate the effects of environmental factors, including diet and lifestyle, on gene expression and clinical presentation. This review outlines what is known about the genetic and epigenetic contributors to obesity susceptibility, along with the albeit limited therapeutic options currently available. Furthermore, we delineate the potential mechanisms of actions through which epigenetic changes can mediate environmental influences and the related opportunities they present for future interventions in the management of obesity.

Low Complexity Regions in Proteins and DNA are Poorly Correlated.

Low complexity sequences (LCRs) are well known within coding as well as non-coding sequences. A low complexity region within a protein must be encoded by the underlying DNA sequence. Here, we examine the relationship between the entropy of the protein sequence and that of the DNA sequence which encodes it. We show that they are poorly correlated whether starting with a low complexity region within the protein and comparing it to the corresponding sequence in the DNA or by finding a low complexity region within coding DNA and comparing it to the corresponding sequence in the protein. We show this is the case within the proteomes of five model organisms: Homo sapiens, Saccharomyces cerevisiae, Drosophila melanogaster, Caenorhabditis elegans, and Arabidopsis thaliana. We also report a significant bias against mononucleic codons in LCR encoding sequences. By comparison with simulated proteomes, we show that highly repetitive LCRs may be explained by neutral, slippage-based evolution, but compositionally biased LCRs with cryptic repeats are not. We demonstrate that other biological biases and forces must be acting to create and maintain these LCRs. Uncovering these forces will improve our understanding of protein LCR evolution.

Impact of Environmental and Epigenetic Changes on Mesenchymal Stem Cells during Aging

Many crucial epigenetic changes occur during early skeletal development and throughout life due to aging, disease and are heavily influenced by an individual's lifestyle. Epigenetics is the study of heritable changes in gene expression as the result of changes in the environment without any mutation in the underlying DNA sequence. The epigenetic profiles of cells are dynamic and mediated by different mechanisms, including histone modifications, non-coding RNA-associated gene silencing and DNA methylation. Given the underlining role of dysfunctional mesenchymal tissues in common age-related skeletal diseases such as osteoporosis and osteoarthritis, investigations into skeletal stem cells or mesenchymal stem cells (MSC) and their functional deregulation during aging has been of great interest and how this is mediated by an evolving epigenetic landscape. The present review describes the recent findings in epigenetic changes of MSCs that effect growth and cell fate determination in the context of aging, diet, exercise and bone-related diseases.

Pyrrole–Imidazole Polyamides – A Frontrunner in Nucleic Acid‐Based Small Molecule Drugs

AbstractThe remarkable success of messenger RNA vaccines against the ongoing coronavirus‐2019 (COVID‐19) pandemic renews attention toward nucleic acid therapeutics. While nucleic acid therapy using unmodified DNA or RNA is the primary focus in disease treatment, there is growing need to develop nucleic acid‐based small molecules owing to their potential clinical benefits as drugs in terms of cost and scalability. While small molecules targeting protein–protein interactions are known to alter the transcriptional status of a cell, they can result in a transient effect and variation of bio‐efficacy among patients. Small molecules targeting DNA and/or RNA are in demand in the precision medicine approach as they have consistent bioactivity among patients. This review details the progress of sequence‐specific DNA‐binding pyrrole–imidazole polyamides (PIPs) in modulating the transcriptional status of target gene(s) without altering the underlying DNA sequence. Here, the different versions of PIPs are listed, and also, how conjugating them with DNA alkylating agents, epigenetic modulators, and other drugs can improve their clinical utility as targeted transcription therapeutics. Owing to their specificity, functional diversity, and limited toxicity, PIP technology holds enormous promise as frontrunner in small‐molecule‐based nucleic acid drugs to precisely regulate therapeutically important genes on demand and treat intractable diseases.

Fluctuations in chromatin state at regulatory loci occur spontaneously under relaxed selection and are associated with epigenetically inherited variation in C. elegans gene expression.

Some epigenetic information can be transmitted between generations without changes in the underlying DNA sequence. Changes in epigenetic regulators, termed epimutations, can occur spontaneously and be propagated in populations in a manner reminiscent of DNA mutations. Small RNA-based epimutations occur in C. elegans and persist for around 3-5 generations on average. Here, we explored whether chromatin states also undergo spontaneous change and whether this could be a potential alternative mechanism for transgenerational inheritance of gene expression changes. We compared the chromatin and gene expression profiles at matched time points from three independent lineages of C. elegans propagated at minimal population size. Spontaneous changes in chromatin occurred in around 1% of regulatory regions each generation. Some were heritable epimutations and were significantly enriched for heritable changes in expression of nearby protein-coding genes. Most chromatin-based epimutations were short-lived but a subset had longer duration. Genes subject to long-lived epimutations were enriched for multiple components of xenobiotic response pathways. This points to a possible role for epimutations in adaptation to environmental stressors.

Abstract P3-11-10: Estrogen receptor reprogramming by HOXB13 and GATA3 in ER-positive breast cancer cells

Abstract Background: The Breast Cancer Index (BCI) is a gene expression-based signature comprising two functional biomarker panels. The Molecular Grade Index (MGI) is composed of five genes that measure tumor proliferation. BCI (H/I) is a ratio of the HOXB13 and IL17BR genes and measures estrogen signaling. Integration of MGI and BCI (H/I) provides a single prognostic score that quantifies the risk of both late (5-10 years) and overall (0-10 years) distant recurrence. BCI (H/I) has been validated to predict benefit from extended endocrine therapy across multiple adjuvant endocrine treatment backgrounds in several prospective-retrospective studies. Hormone receptor responses are dependent on genome-wide hormone receptor binding patterns. In hormone-dependent cancers, nuclear receptor binding patterns are frequently reprogrammed by other transcription factors. The homeobox transcription factor HOXB13 has previously been shown to reprogram genome-wide binding of the androgen receptor (AR) during prostate cancer tumorigenesis, where it colocalizes with FOXA1 at reprogrammed AR binding sites. Similarly, the transcription factor GATA3 was found to mediate enhancer accessibility at regulatory regions involved in estrogen receptor (ER)-mediated transcription. We have shown previously that HOXB13 overexpression reprograms and expands the ER binding pattern in breast cancer cells. In this study, we have further characterized the role of HOXB13 in reprograming the ER cistrome and evaluated potential interactions with GATA3. Methods: HOXB13 was expressed in MCF-7 and T47D cells by electroporating HOXB13 mRNA or eGFP mRNA as control. Cells were harvested after 18 hours and analyzed by western blot and chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) using antibodies against ER, HOXB13, FOXA1, GATA3 and histone H3K27ac. Chromatin accessibility was assessed by ATAC-seq. After aligning reads with Bowtie2, peak calling, data integration and motif enrichment analysis was performed using HOMER v4.10. Results: ChIP-seq analysis of T47D cells expressing HOXB13 confirmed previous results in MCF-7 cells, where binding of HOXB13 to a significant number of genomic binding sites induced changes in binding of ER, FOXA1 and GATA3 compared to control cells. Integrative analysis of ATAC-seq and ChIP-seq data revealed that HOXB13-induced reprogramming results in open chromatin that frequently exhibits increased acetylation of histone H3K27, a hallmark of transcriptional activation. While both increased chromatin accessibility and H3K27 acetylation were associated with HOX and AP-1 motif enrichment of the underlying DNA sequences, newly open chromatin was specifically co-enriched for motifs for pioneering factors such as FOXA1 and GRHL1. Conclusion: This study lends further support to a model of HOXB13-mediated reprogramming of the ER cistrome in breast cancer. Motif analysis of HOXB13-induced chromatin opening suggests interactions with other pioneer transcription factors including FOXA1 and GRHL1, while HOXB13-induced transcriptional activation is associated with motifs for activating factors such as AP-1. These results will be expanded to inducible cell lines to further characterize the effects of HOXB13 expression on ER binding and function. Citation Format: Kai Treuner, Camila De Arruda Saldanha, Sven Heinz. Estrogen receptor reprogramming by HOXB13 and GATA3 in ER-positive breast cancer cells [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-11-10.

NGS-based clonality testing is a sensitive and complementary method for MRD monitoring in acute lymphoblastic leukaemia

Aim: Measurable residual disease (MRD) has been recognised as an important prognostic marker in acute lymphoblastic leukaemia (ALL) alongside genetic profiling. Next generation sequencing (NGS) based clonality testing facilitates identification of the full range of clonal populations with underlying DNA sequences, thereby offering improved sensitivity and specificity for MRD monitoring. Here, we interrogate the clinical utility of NGS-based MRD assay for disease monitoring in ALL.

Computational Protocol for DNA Methylation Profiling in Plants Using Restriction Enzyme-Based Genome Reduction.

Epigenetics can be described as heritable phenotype changes that do not involve alterations in the underlying DNA sequence. Having widespread implications in fundamental biological phenomena, there is an increased interest in characterizing epigenetic modifications and studying their functional implications. DNA methylation, particularly 5-methylcytosine (5mC), stands out as the most studied epigenetic mark and several methodologies have been created to investigate it. With the development of next-generation sequencing technologies, several approaches to DNA methylation profiling were conceived, with differences in resolution and genomic scope. Besides the gold standard whole-genome bisulfite sequencing, which is costly for population-scale studies, genomic reduced representation methods emerged as viable alternatives to investigate methylation loci. Whole-genome bisulfite sequencing provides single-base methylation resolution but is costly for population-scale studies. Genomic reduction methods emerged as viable alternatives to investigate a fraction of methylated loci. One of such approaches uses double digestion with the restriction enzymes PstI and one of the isoschizomers, MspI and HpaII, with differential sensitivity to 5mC at the restriction site. Statistical comparison of sequencing reads counts obtained from the two libraries for each sample (PstI-MspI and PstI-HpaII) is used to infer the methylation status of thousands of cytosines. Here, we describe a general overview of the technique and a computational protocol to process the generated data to provide a medium-scale inventory of methylated sites in plant genomes. The software is available at https://github.com/wendelljpereira/DArTseqMet .

Decoding Cancer Formation: The Impact of Epigenetic Factors

This study delves into the critical role of epigenetic factors in the formation and progression of cancer, offering a comprehensive analysis of the molecular mechanisms that drive tumorigenesis. Epigenetic modifications, including DNA methylation, histone modification, and non-coding RNA regulation, have emerged as key players in the regulation of gene expression without altering the underlying DNA sequence. These modifications can lead to the activation of oncogenes or the silencing of tumor suppressor genes, thereby contributing to the initiation and progression of cancer. The research highlights how disruptions in normal epigenetic processes can result in abnormal cell growth, metastasis, and resistance to apoptosis, which are hallmarks of cancer. By analyzing recent advancements in epigenetic research, the study underscores the importance of understanding these mechanisms to identify potential biomarkers for early cancer detection and to develop targeted therapies that can reverse epigenetic alterations. Through a detailed examination of various cancer types, the study demonstrates the widespread impact of epigenetic changes across different forms of the disease. It also explores the potential of epigenetic therapies, such as inhibitors of DNA methyltransferases and histone deacetylases, in reprogramming cancer cells to a more normal state. This study contributes to the growing body of knowledge on the molecular underpinnings of cancer and offers insights into the development of novel therapeutic strategies that target epigenetic factors, paving the way for more effective and personalized cancer treatments.

EpiCas-DL: Predicting sgRNA activity for CRISPR-mediated epigenome editing by deep learning

CRISPR-mediated epigenome editing enables gene expression regulation without changing the underlying DNA sequence, and thus has vast potential for basic research and gene therapy. Effective selection of a single guide RNA (sgRNA) with high on-target efficiency and specificity would facilitate the application of epigenome editing tools. Here we performed an extensive analysis of CRISPR-mediated epigenome editing tools on thousands of experimentally examined on-target sites and established EpiCas-DL, a deep learning framework to optimize sgRNA design for gene silencing or activation. EpiCas-DL achieves high accuracy in sgRNA activity prediction for targeted gene silencing or activation and outperforms other available in silico methods. In addition, EpiCas-DL also identifies both epigenetic and sequence features that affect sgRNA efficacy in gene silencing and activation, facilitating the application of epigenome editing for research and therapy. EpiCas-DL is available at http://www.sunlab.fun:3838/EpiCas-DL.

Epigenetics and its essence in understanding human growth, development and disease

Epigenetics is a scientific discipline encompassing the genetic and non-genetic related perspectives of heritable phenotypic modifications of whose aetiologies include behavioural, anthropogenic, environmental, metabolic and spatiotemporal variables. Behavioral epigenetics examines how epigenetics shapes animal and human behaviour to explicate how nurture moulds nature; nature prefers to biological heredity and nurture prefers to occurrrences in the environment and hereditary during the lifespan of all individuals. Behavioural epigenetics features how experiences and the environment produce individual disparities in behaviour, cognition, personality, and mental health influence gene expression. Epigenetic gene regulation relates to modification of DNA sequence and histones as well as DNA methylation. These epigenetic alterations effect the growth of neurons in the developing brain and functional modification of neurons in the developed brain, with resultant significant alterations in neuron morphology. Epigenetic changes occur in the developing fetus and throughout the lifespan of an individual, with alterations in individual traits and transgenerational inheritance. Epigenetics is associated with heritable changes in gene actions and these are not due to DNA sequence alterations. Epigenetics may be termed sustained, long-run changes in the transcription veracity of a heritable or non-heritable cell. DNA methylation and histone alteration are mechanisms which modify gene expression without changing the underlying DNA sequence. Gene expression is driven by repressor protein actions which bind to DNA silencer regions.DNA methylation turns a gene ''off'' culminating in genetic information impairment to be read from DNA, but extricating the methyl tag can turn ''on'' the gene. Histone alteration defines the packaging of DNA into the chromosomes; and.these changes influence gene expression. This review provides the latitude to examine the extant information in the universal characterizations of epigenetic formulations, such as ageing, susceptibility to pollutant and irritant exposure.

Characterization of the Clinical and Molecular Perspectives of Epigenetics

This review provides the latitude to examine the extant information in the univeral characterizations of epigenetic formulations. Epigenetics encompasses the interaction of behaviours and environment culminating in changes which influence gene activity. In contrast to genetic modifications, epigenetic modifications are reversible; and do not alter the DNA sequence but are capable of interferring in the way the DNA sequence is read. Epigenetic alterations involve genetic changes which effect gene functionality without modifying the underlying DNA sequence. DNA methylation depicts the covalent superimposed methyl group to cytosine in CpG dinucleotides. DNA methylation presents as a veritable epigenetic modification; and it governs gene expression by changing chromosome structure, DNA conformation and stability as well as the function trajectory between DNA and protein. DNA methylation regulates gene expression via the conscription of proteins associated with gene expression or by the inhibition of the binding of transcription factor(s) to DNA. Whereas genetic alterations do modify protein formation, it is clear that epigenetic alterations impact on gene expression to put genes ''on'' and ''off'', as appropriate. The resultant impact of environmental and anthropogenic idiosyncracies, such as diet and physical activity are liable to induce epigenetic modifications in behaviours and gene-environment interactions. Genes are not always in functional mode. DNA methylation constitutes a select epigenetic process applied by cells for the control of gene expression. within the genome. Alterations in gene activity and epigenetic errors can result in varying genetic, metabolic and degenerative disorders which may disparately or in comorbid presentaions influence inter alia health, gene activity or expression, protein production and functionality. This entry exemplifies the reading and understanding of epigenetics in relation to inter alia beneficial developmental theories within the human race.

SPERM DNA METHYLATION PREDICTS HUMAN AGING IN FERTILE AND INFERTILE MEN

Epigenetics refers to heritable changes in gene expression that do not involve changes in the underlying DNA sequence. One of the most studied mechanisms of epigenetic change is DNA methylation. It is postulated that adverse outcomes related to advanced paternal age and assisted reproductive technologies (ART) are due to epigenetic changes. Prior studies have described accurate age estimation based on human somatic cell DNA methylation. We sought to evaluate the DNA methylation patterns of somatic cells and sperm from fertile men and men with idiopathic infertility.