The studies on CpG islands (CGI) and Alu elements functions, evolution, and distribution in the genome started since the discovery in nineteen eighties (1981, 1986, correspondingly). Their highly skewed genome wide distribution implies the non-random retrotransposition pattern. Besides CGIs in gene promoters, CGIs clusters were observed in the homeobox gene regions and in the macrosatellites, but the whole picture of their distribution specifics was not grasped. Attempts to identify any causative features upon their (genome wide) distribution, such as the DNA context mediated preferred insertion sites of Alu repeats, have been made to ascribe their clusters location. Recent emergence of high resolution 3D map of human genome allowed segregating the genome into the large scale chromatin domains of naturally observable nuclear subcompartments, or Topologically Associated Domains (TADs), designated by spatial chromatin distribution. We utilized the chromatin map to elucidate relations between large scale chromatin state and CpG rich elements landscape. In the course of analysis it was confirmed that genes, Alu and CGI clusters maintain obvious, albeit different in strength, preference for open chromatin. For the first time it was clearly shown that the clusters density of the Alu and CGIs monotonically depend on the chromatin accessibility rate. In particular, the highest density of these elements is found in A1 euchromatin regions characterized by a high density of small length genes replicating in the early S-phase. It implies that these elements mediate (CGIs) or are a side element (Alus) of chromatin accessibility. We elucidated that both methylated and non-methylated CGIs display the affinity to chromatin accessibility. As a part of comparative genomics section, we elucidated that the dog’s genome non-canonical structure, outstanding in mammals for its high CGIs abundance compared to gene number, is explained by the presence of dense tandem CGI extended hotspots (500 kb on average) in subtelomeric and pericentromeric regions with highly skewed CG content, and not by CGIs global distribution pattern shift. The study underlines the close association of CG-rich elements distribution with the newly introduced large scale chromatin state map, proposing a refined standpoint on interrelation of aforementioned genome elements and the chromatin state. To our expertise, the TAD-associated partition model employed in the study is likely the most substantial one regarding CpG rich clusters distribution among the whole genome chromatin/isochores maps available.

Aggressiveness in humans is a hereditary behavioral trait that mobilizes all systems of the body—first of all, the nervous and endocrine systems, and then the respiratory, vascular, muscular, and others—e.g., for the defense of oneself, children, family, shelter, territory, and other possessions as well as personal interests. The level of aggressiveness of a person determines many other characteristics of quality of life and lifespan, acting as a stress factor. Aggressive behavior depends on many parameters such as age, gender, diseases and treatment, diet, and environmental conditions. Among them, genetic factors are believed to be the main parameters that are well-studied at the factual level, but in actuality, genome-wide studies of aggressive behavior appeared relatively recently. One of the biggest projects of the modern science—1000 Genomes—involves identification of single nucleotide polymorphisms (SNPs), i.e., differences of individual genomes from the reference genome. SNPs can be associated with hereditary diseases, their complications, comorbidities, and responses to stress or a drug. Clinical comparisons between cohorts of patients and healthy volunteers (as a control) allow for identifying SNPs whose allele frequencies significantly separate them from one another as markers of the above conditions. Computer-based preliminary analysis of millions of SNPs detected by the 1000 Genomes project can accelerate clinical search for SNP markers due to preliminary whole-genome search for the most meaningful candidate SNP markers and discarding of neutral and poorly substantiated SNPs. Here, we combine two computer-based search methods for SNPs (that alter gene expression) {i} Web service SNP_TATA_Comparator (DNA sequence analysis) and {ii} PubMed-based manual search for articles on aggressiveness using heuristic keywords. Near the known binding sites for TATA-binding protein (TBP) in human gene promoters, we found aggressiveness-related candidate SNP markers, including rs1143627 (associated with higher aggressiveness in patients undergoing cytokine immunotherapy), rs544850971 (higher aggressiveness in old women taking lipid-lowering medication), and rs10895068 (childhood aggressiveness-related obesity in adolescence with cardiovascular complications in adulthood). After validation of these candidate markers by clinical protocols, these SNPs may become useful for physicians (may help to improve treatment of patients) and for the general population (a lifestyle choice preventing aggressiveness-related complications).

The progress of medicine, science, technology, education, and culture improves, year by year, quality of life and life expectancy of the populace. The modern human has a chance to further improve the quality and duration of his/her life and the lives of his/her loved ones by bringing their lifestyle in line with their sequenced individual genomes. With this in mind, one of genome-based developments at the junction of personalized medicine and bioinformatics will be considered in this work, where we used two Web services: (i) SNP_TATA_Comparator to search for alleles with a single nucleotide polymorphism (SNP) that alters the affinity of TATA-binding protein (TBP) for the TATA boxes of human gene promoters and (ii) PubMed to look for retrospective clinical reviews on changes in physiological indicators of reproductive potential in carriers of these alleles. A total of 126 SNP markers of female reproductive potential, capable of altering the affinity of TBP for gene promoters, were found using the two above-mentioned Web services. For example, 10 candidate SNP markers of thrombosis (e.g., rs563763767) can cause overproduction of coagulation inducers. In pregnant women, Hughes syndrome provokes thrombosis with a fatal outcome although this syndrome can be diagnosed and eliminated even at the earliest stages of its development. Thus, in women carrying any of the above SNPs, preventive treatment of this syndrome before a planned pregnancy can reduce the risk of death. Similarly, seven SNP markers predicted here (e.g., rs774688955) can elevate the risk of myocardial infarction. In line with Bowles’ lifespan theory, women carrying any of these SNPs may modify their lifestyle to improve their longevity if they can take under advisement that risks of myocardial infarction increase with age of the mother, total number of pregnancies, in multiple pregnancies, pregnancies under the age of 20, hypertension, preeclampsia, menstrual cycle irregularity, and in women smokers. According to Bowles’ lifespan theory—which links reproductive potential, quality of life, and life expectancy—the above information was compiled for those who would like to reduce risks of diseases corresponding to alleles in own sequenced genomes. Candidate SNP markers can focus the clinical analysis of unannotated SNPs, after which they may become useful for people who would like to bring their lifestyle in line with their sequenced individual genomes.

While year after year, conditions, quality, and duration of human lives have been improving due to the progress in science, technology, education, and medicine, only eight diseases have been increasing in prevalence and shortening human lives because of premature deaths according to the retrospective official review on the state of US health, 1990-2010. These diseases are kidney cancer, chronic kidney diseases, liver cancer, diabetes, drug addiction, poisoning cases, consequences of falls, and Alzheimer’s disease (AD) as one of the leading pathologies. There are familial AD of hereditary nature (~4% of cases) and sporadic AD of unclear etiology (remaining ~96% of cases; i.e., nonfamilial AD). Therefore, sporadic AD is no longer a purely medical problem, but rather a social challenge when someone asks oneself: “What can I do in my own adulthood to reduce the risk of sporadic AD at my old age to save the years of my lifespan from the destruction caused by it?” Here, we combine two computational approaches for regulatory SNPs: Web service SNP_TATA_Comparator for sequence analysis and a PubMed-based keyword search for articles on the biochemical markers of diseases. Our purpose was to try to find answers to the question: “What can be done in adulthood to reduce the risk of sporadic AD in old age to prevent the lifespan reduction caused by it?” As a result, we found 89 candidate SNP markers of familial and sporadic AD (e.g., rs562962093 is associated with sporadic AD in the elderly as a complication of stroke in adulthood, where natural marine diets can reduce risks of both diseases in case of minor alleles of these SNPs). In addition, rs768454929, and rs761695685 correlate with sporadic AD as a comorbidity of short stature, where maximizing stature in childhood and adolescence as an integral indicator of health can minimize (or even eliminate) the risk of sporadic AD in the elderly. After validation by clinical protocols, these candidate SNP markers may become interesting to the general population (may help to choose a lifestyle [in childhood, adolescence, and adulthood] that can reduce the risks of sporadic AD, its comorbidities, and complications in the elderly).

Variations in human genome (e.g., single nucleotide polymorphisms, SNPs) may be associated with hereditary diseases, their complications, comorbidities, and drug responses. Using Web service SNP_TATA_Comparator presented in our previous paper, here we analyzed immediate surroundings of known SNP markers of diseases and identified several candidate SNP markers that can significantly change the affinity of TATA-binding protein for human gene promoters, with circadian consequences. For example, rs572527200 may be related to asthma, where symptoms are circadian (worse at night), and rs367732974 may be associated with heart attacks that are characterized by a circadian preference (early morning). By the same method, we analyzed the 90 bp proximal promoter region of each protein-coding transcript of each human gene of the circadian clock core. This analysis yielded 53 candidate SNP markers, such as rs181985043 (susceptibility to acute Q fever in male patients), rs192518038 (higher risk of a heart attack in patients with diabetes), and rs374778785 (emphysema and lung cancer in smokers). If they are properly validated according to clinical standards, these candidate SNP markers may turn out to be useful for physicians (to select optimal treatment for each patient) and for the general population (to choose a lifestyle preventing possible circadian complications of diseases).

Belyaev’s concept of destabilizing selection during domestication was a major achievement in the XX century. Its practical value has been realized in commercial colors of the domesticated fox that never occur in the wild and has been confirmed in a wide variety of pet breeds. Many human disease models involving animals allow to test drugs before human testing. Perhaps this is why investigators doing transcriptomic profiling of domestic versus wild animals have searched for breed-specific patterns. Here we sequenced hypothalamic transcriptomes of tame and aggressive rats, identified their differentially expressed genes (DEGs), and, for the first time, applied principal component analysis to compare them with all the known DEGs of domestic versus wild animals that we could find. Two principal components, PC1 and PC2, respectively explained 67% and 33% of differential-gene-expression variance (hereinafter: log₂ value) between domestic and wild animals. PC1 corresponded to multiple orthologous DEGs supported by homologs; these DEGs kept the log₂ value sign from species to species and from tissue to tissue (i.e., a common domestication pattern). PC2 represented stand-alone homologous DEG pairs reversing the log₂ value sign from one species to another and from tissue to tissue (i.e., representing intraspecific and interspecific variation).