Tensor Rules in the Stochastic Organization of Genomes and Genetic Stochastic Resonance in Algebraic Biology

The article is devoted to the new results of the author, which add his previously published ones, of studying hidden rules and symmetries in structures of long single-stranded DNA sequences in eukaryotic and prokaryotic genomes. The author uses the existence of different alphabets of n-plets in DNA: the alphabet of 4 nucleotides, the alphabet of 16 douplets, the alphabet of 64 triplets, etc. Each of such DNA alphabets of n-plets can serve for constructing a text as a chain of these n-plets. Using this possibility, the author represents any long DNA nucleotide sequence as a bunch of many so-called n-texts, each of which is written on the basis of one of these alphabets of n-plets. Each of such n-texts has its individual percents of different n-plets in its genomic DNA. But it turns out that in such multi-alphabetical or multilayer presentation of each of many genomic DNA, analyzed by the author, universal rules of probabilities and symmetry exist in interrelations of its different n-texts regarding their percents of n-plets. In this study, the tensor product of matrices and vectors is used as an effective analytical tool borrowed from the arsenal of quantum mechanics. Some additions to the topic of algebra-holographic principles in genetics are also presented. Taking into account the described genomic rules of probability, the author puts also forward a concept of the important role of stochastic resonances in genetic informatics.

Aptardi predicts polyadenylation sites in sample-specific transcriptomes using high-throughput RNA sequencing and DNA sequence

Annotation of polyadenylation sites from short-read RNA sequencing alone is a challenging computational task. Other algorithms rooted in DNA sequence predict potential polyadenylation sites; however, in vivo expression of a particular site varies based on a myriad of conditions. Here, we introduce aptardi (alternative polyadenylation transcriptome analysis from RNA-Seq data and DNA sequence information), which leverages both DNA sequence and RNA sequencing in a machine learning paradigm to predict expressed polyadenylation sites. Specifically, as input aptardi takes DNA nucleotide sequence, genome-aligned RNA-Seq data, and an initial transcriptome. The program evaluates these initial transcripts to identify expressed polyadenylation sites in the biological sample and refines transcript 3′-ends accordingly. The average precision of the aptardi model is twice that of a standard transcriptome assembler. In particular, the recall of the aptardi model (the proportion of true polyadenylation sites detected by the algorithm) is improved by over three-fold. Also, the model—trained using the Human Brain Reference RNA commercial standard—performs well when applied to RNA-sequencing samples from different tissues and different mammalian species. Finally, aptardi’s input is simple to compile and its output is easily amenable to downstream analyses such as quantitation and differential expression.

Minireview: The Epigenetic Modulation of KISS1 in Reproduction and Cancer

Epigenetics describes how both lifestyle and environment may affect human health through the modulation of genome functions and without any change to the DNA nucleotide sequence. The discovery of several epigenetic mechanisms and the possibility to deliver epigenetic marks in cells, gametes, and biological fluids has opened up new perspectives in the prevention, diagnosis, and treatment of human diseases. In this respect, the depth of knowledge of epigenetic mechanisms is fundamental to preserving health status and to developing targeted interventions. In this minireview, we summarize the epigenetic modulation of the KISS1 gene in order to provide an example of epigenetic regulation in health and disease.

Epigenetic Targets and their Inhibitors in Cancer Therapy

Epigenetics is defined as the stable and heritable alternations in gene expression without changing the DNA nucleotide sequence. The initiation and progression of cancer result from not only genetic mutation, but also aberrant epigenetic regulation, such as DNA methylation and histones acetylation. Although Genetic alternations cannot be reversed, epigenetic modification is a dynamic and reversible process. Over the past few decades, much progress has been made in the research of epigenetic medications and a variety of drugs have been developed targeting at epigenetic regulatory proteins, which are capable of restoring malignant cancer cells to the normal state. The epigenetic drugs currently approved for cancer treatment mainly target at DNA methylation and histones acetylation. In addition, there are a great many epigenetic drugs in clinical trials for cancer therapy, such as inhibitors of DNA methyltransferases, histone deacetylases, histone methyltransferases, lysine specific demethylases, and BET (bromodomain and extra-terminal domain) family proteins. We will discuss the latest developments of these inhibitors and their applications in cancer therapy.

Diagnóstico molecular na prática clínica: visão do endocrinologista

<p>Endocrinology is one of several medical specialities that have been gradually transformed by a deeper understanding of the molecular bases of disorders. Genetic testing with the purposes of defining a precise molecular diagnosis has increasingly gained space in the routine assessment of patients with endocrinopathies, and the advent of massive parallel sequencing (MPS) is boosting the incorporation of molecular information in the clinic. The main benefit of genetic testing is diagnostic precision, resulting in improved and individualized care for patients and family members, and better disease prevention. However, genetic tests are not infallible and may bear several potential risks, being thus indicated when clinical suspicion is strong and the benefit of determining a molecular diagnosis is unambiguous. In this review, these evolving concepts and current indications for molecular diagnosis in endocrinology will be explored. Molecular tools will be revised and contextualised, including those aimed at identifying changes in gene dosage (karyotpe, FISH, MLPA, aCGH, SNParray) or in the DNA nucleotide sequence (allele-specific PCR, RFLP, Sanger sequencing, MPS or NGS). Finally, matters surrounding the complex attribution of biologically relevant functional impact to identified DNA variants will be explored, together with the challenges brought by high throughput molecular analysis. These are exciting times for molecular endocrinology, and hopefully soon a translation to multiple benefits for patients will be self-evident.</p>

DNA methylation, ageing and the influence of early life nutrition

It is well established that genotype plays an important role in the ageing process. However, recent studies have suggested that epigenetic mechanisms may also influence the onset of ageing-associated diseases and longevity. Epigenetics is defined as processes that induce heritable changes in gene expression without a change in the DNA nucleotide sequence. The major epigenetic mechanisms are DNA methylation, histone modification and non-coding RNA. Such processes are involved in the regulation of tissue-specific gene expression, cell differentiation and genomic imprinting. However, epigenetic dysregulation is frequently seen with ageing. Relatively little is known about the factors that initiate such changes. However, there is emerging evidence that the early life environment, in particular nutrition, in early life can induce long-term changes in DNA methylation resulting in an altered susceptibility to a range of ageing-associated diseases. In this review, we will focus on the changes in DNA methylation that occur during ageing; their role in the ageing process and how early life nutrition can modulate DNA methylation and influence longevity. Understanding the mechanisms by which diet in early life can influence the epigenome will be crucial for the development of preventative and intervention strategies to increase well-being in later life.