DNA Database Research Articles

Lion Localizer: A software tool for inferring the provenance of lions (Panthera leo) using mitochondrial DNA.

The illegal poaching of lions for their body parts poses a severe threat to lion populations across Africa. Poaching accounts for 35% of all human-caused lion deaths, with 51% attributed to retaliatory killings following livestock predation. In nearly half of the retaliatory killings, lion body parts are removed, suggesting that high demand for lion body parts may fuel killings attributed to human-lion conflict. Trafficked items are often confiscated in transit or destination countries far from their country of origin. DNA from lion parts may in some cases be the only available means for examining their geographic origins. In this paper, we present the Lion Localizer, a full-stack software tool that houses a comprehensive database of lion mitochondrial DNA (mtDNA) sequences sourced from previously published studies. The database covers 146 localities from across the African continent and India, providing information on the potential provenance of seized lion body parts. Lion mtDNA sequences of 350 or 1,140 bp corresponding to the cytochrome b region can be generated from lion products and queried against the Lion Localizer database. Using the query sequence, the Lion Localizer generates a listing of exact or partial matches, which are displayed on an interactive map of Africa. This allows for the rapid identification of potential regions and localities where lions have been or are presently being targeted by poachers. By examining the potential provenance of lion samples, the Lion Localizer serves as a valuable resource in the fight against lion poaching. The software is available at https://lionlocalizer.org.

Role of beta-3 adrenergic receptor polymorphism TRY64ARG in heart failure

Abstract Introduction The TRY64ARG polymorphism of the beta-3 adrenergic receptor has been associated with the onset and maintenance of hypertension, diabetes and obesity, its role in heart failure has not been studied. Objectives To examine the role of the TRY64ARG beta-3 adrenergic receptor in the improvement of left ventricular ejection fraction (LVEF) in patients with Heart Failure due to ischemic heart disease. Methods This study is a retrospective analysis based on a 5-year follow-up of patients with heart failure with decreased LVEF due to ischemic heart disease. Results We studied a sample of 338 patients with decreased LVEF collected from our Genetic database during the period of time from January 2012 to December 2016. In the scrutiny 26 patients did not have complete data for analysis, resulting in a final sample of 312 patients with a minimum follow-up of 5 years. The mean age was 58.9 years (SD 14), 72% of the population were men (n = 244), the frequency of hypertension was 168 (53.85%), diabetes 119 (38.14%), obesity (18.27%). The definition of LVEF improvement was defined as an incremental in more than 15%. There was no statistical difference in the medical treatment and revascularization methods. Patients with the TRY64ARG β3 adrenergic polymorphism present less improvement in the LVEF (42% vs 58%, p< 0.001). Conclusions The expression of the TRY64ARG polymorphism of the beta-3 adrenergic receptor in patients with HF and low LVEF is related to a lack of incremental LVEF at 5 years.

Mendelian Randomization as a Tool for Cardiovascular Research

ImportanceMendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.ObservationsMR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.Conclusions and RelevanceThis review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

69 The Bigger Picture of Phenomics: Whole-System Support for Systems Research, Models and Databases

Abstract Phenomics started with Mendel’s elegantly simple empirical studies. Soon after, Fisher discovered purines were rich in nuclei of all cells. A century later, we have the technology to compare the actual base pair sequence of DNA and RNA with the outward expressions of phenotypes. We have sire evaluation based on genomic and phenomic measure. But, being human, it is quite common to get immersed in exciting technology and tend to forget why we developed the technology in the first place. We only refer to ensuring a stable efficient food supply of plants and animals in the reports that we expect decision makers to read and give us more money. It is, however, truly wonderful that we now have the techniques to study the questions of the ages. But the future of phenomics is built on the foundations of the past. In 1974, A. E. Freeman and others convened a meeting under the mechanism of the newly formed Regional Research Project 2 on Defining the Inefficiency of Animal Production. From that workshop came the first modern multistate genetic study in dairy cattle with the objective to compare the phenotypes (milk component production, energy and nitrogen metabolism, hormones) of dairy animals that were born from bulls of High (+795 kg PTAM) and Low (167 kg PTAM) bulls. Please remember this study was designed in the mid 1970s and the first data collected in the early 1980s, decades before efficient methods of DNA and RNA composition were available. Studies conducted at Washington State University demonstrated marked genetic and environmental differences in adipose tissues of dairy animals. Enzymes involved with catabolic reactions were highly associated with High PTAM bulls while enzymes associated with anabolic reactions in adipose tissue were more closely related to increased energy intake regardless of genetic background. With mRNA chips, we were able, after almost 40 years, to directly relate variation in mRNA expression in the adipose tissue with the genetic background of the animals. This was the first such discovery in the field, and has led to more defined and expansive phenomics studies. In the year 2023, the use of genomics, phenomics, databases, large scale, cooperative studies and team science are specific recommendations, strategies and goals of the USDA, NIFA, The National Academies, and Land-Grant Universities. The AgBioData consortium is one example of international teams working together to expand the use of genetic and genomic databases, to prepare undergraduate and graduate level educational materials on FAIR databases and to encourage and support sustainable, robustly funded public and private partnerships in the use of integrated studies and large databases, including phenomics, with the sole purpose of expanding a robust, resilient, safe and plentiful food supply.

Maize Feature Store: A centralized resource to manage andanalyze curated maize multi-omics features formachine learning applications.

The big-data analysis of complex data associated with maize genomes accelerates genetic research and improves agronomic traits. As a result, efforts have increased to integrate diverse datasets and extract meaning from these measurements. Machine learning models are a powerful tool for gaining knowledge from large and complex datasets. However, these models must be trained on high-quality features to succeed. Currently, there are no solutions to host maize multi-omics datasets with end-to-end solutions for evaluating and linking features to target gene annotations. Our work presents the Maize Feature Store (MFS), a versatile application that combines features built on complex data to facilitate exploration, modeling and analysis. Feature stores allow researchers to rapidly deploy machine learning applications by managing and providing access to frequently used features. We populated the MFS for the maize reference genome with over 14 000 gene-based features based on published genomic, transcriptomic, epigenomic, variomic and proteomics datasets. Using the MFS, we created an accurate pan-genome classification model with an AUC-ROC score of 0.87. The MFS is publicly available through the maize genetics and genomics database. Database URL https://mfs.maizegdb.org/.

COLOCdb: a comprehensive resource for multi-model colocalization of complex traits.

Large-scale genome-wide association studies (GWAS) have provided profound insights into complex traits and diseases. Yet, deciphering the fine-scale molecular mechanisms of how genetic variants manifest to cause the phenotypes remains a daunting task. Here, we present COLOCdb (https://ngdc.cncb.ac.cn/colocdb), a comprehensive genetic colocalization database by integrating more than 3000 GWAS summary statistics and 13 types of xQTL to date. By employing two representative approaches for the colocalization analysis, COLOCdb deposits results from three key components: (i) GWAS-xQTL, pair-wise colocalization between GWAS loci and different types of xQTL, (ii) GWAS-GWAS, pair-wise colocalization between the trait-associated genetic loci from GWASs and (iii) xQTL-xQTL, pair-wise colocalization between the genetic loci associated with molecular phenotypes in xQTLs. These results together represent the most comprehensive colocalization analysis, which also greatly expands the list of shared variants with genetic pleiotropy. We expect that COLOCdb can serve as a unique and useful resource in advancing the discovery of new biological mechanisms and benefit future functional studies.

Genetic Databases and Gene Editing Tools for Enhancing Crop Resistance against Abiotic Stress.

Abiotic stresses extensively reduce agricultural crop production globally. Traditional breeding technology has been the fundamental approach used to cope with abiotic stresses. The development of gene editing technology for modifying genes responsible for the stresses and the related genetic networks has established the foundation for sustainable agriculture against environmental stress. Integrated approaches based on functional genomics and transcriptomics are now expanding the opportunities to elucidate the molecular mechanisms underlying abiotic stress responses. This review summarizes some of the features and weblinks of plant genome databases related to abiotic stress genes utilized for improving crops. The gene-editing tool based on clustered, regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) has revolutionized stress tolerance research due to its simplicity, versatility, adaptability, flexibility, and broader applications. However, off-target and low cleavage efficiency hinder the successful application of CRISPR/Cas systems. Computational tools have been developed for designing highly competent gRNA with better cleavage efficiency. This powerful genome editing tool offers tremendous crop improvement opportunities, overcoming conventional breeding techniques' shortcomings. Furthermore, we also discuss the mechanistic insights of the CRISPR/Cas9-based genome editing technology. This review focused on the current advances in understanding plant species' abiotic stress response mechanism and applying the CRISPR/Cas system genome editing technology to develop crop resilience against drought, salinity, temperature, heavy metals, and herbicides.

Environmental DNA metabarcoding of water samples as a tool for monitoring Iberian freshwater fish composition.

Environmental DNA (eDNA) metabarcoding has been increasingly used to monitor the community assemblages of a wide variety of organisms. Here, we test the efficacy of eDNA metabarcoding to assess the composition of Iberian freshwater fishes, one of the most endangered groups of vertebrates in Spain. For this purpose, we sampled 12 sampling sites throughout one of Spain's largest basins, the Duero, which is home to approximately 70% of the genera and 30% of the primary freshwater fish in Spain. We sampled these sampling sites in the summer by using electrofishing, a traditional sampling method, and eDNA metabarcoding of river water samples using the mitochondrial 12S rRNA gene (12S) as a marker. We also resampled four of these sampling sites in autumn by eDNA. We compared the results obtained through eDNA metabarcoding with those of electrofishing surveys (ones conducted for the present study and past ones) and assessed the suitability of 12S as an eDNA metabarcoding marker for this group of freshwater fishes. We found that the 12S fragment, analysed for 25 Iberian species, showed sufficient taxonomic resolution to be useful for eDNA approaches, and even showed population-level differences in the studied populations across the tissue samples for Achondrostoma arcasii. In most cases, a greater number of species was detected through eDNA metabarcoding than through electrofishing. Based on our results, eDNA metabarcoding is a powerful tool to study the freshwater fish composition in the Iberian Peninsula and to unmask cryptic diversity. However, we highlight the need to generate a local genetic database for 12S gene for such studies and to interpret the results with caution when studying only mitochondrial DNA. Finally, our survey shows that the high detection sensitivity of eDNA metabarcoding and the non-invasiveness of this method allows it to act as a detection system for species of low abundance, such as early invasive species or species in population decline, two key aspects of conservation management of Spanish freshwater fishes.

Generation of random sequences using DNA cryptography for OTP encryption

DNA cryptography is considered as a promising new field for improving cybersecurity and privacy using parallelism and storage capacity of DNA molecules. In this work, novel technique is proposed for generating random and unpredictable keys for symmetric One Time Pad cryptosystems. To achieve this, publicly available DNA sequences stored in genetic databases are used as a source of inherently random, diverse, and variable-length sequences. The proposed approach is based on two steps. The first step uses a DNA self-assembly structure, mathematical operations and DNA techniques. In the second step, an entropy source and chaotic function are incorporated as a random number generator and pseudorandom number generator, respectively, to further enhance the randomness and unpredictability of the generated OTP keys. Additionally, a secure key exchange approach is also proposed including minimization and optimization in both secure and public channels used for key exchange.

GenBank 2024 Update.

GenBank® (https://www.ncbi.nlm.nih.gov/genbank/) is a comprehensive, public database that contains 25 trillion base pairs from over 3.7 billion nucleotide sequences for 557 000 formally described species. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. Recent updates include policies for including spatio-temporal metadata, clarified documentation for GenBank data processing, enhanced foreign contamination screening tools, new processes in the Submission Portal, migration of Entrez Genome and Assembly displays into NCBI Datasets, and the impending retirement of tbl2asn, replaced by table2asn.

Analysis of polymorphism and development of a molecular-genetic system for genotyp-ing by the telomerase reverse transcriptase (TERT) gene

This article explores the genetic variability of the gene that encodes telomerase reverse transcriptase (TERT), which plays a key role in maintaining telomere length and, as a result, genome stability in various eukaryotic species. The study employs a comprehensive approach that combines phylogenetic and bioinformatic analysis with molecular-genetic research methods. The research involved the screening of genetic databases to investigate TERT gene orthologues across organisms belonging to different systematic groups. The TERT gene, which is prevalent in a wide range of eukaryotic biological species, exhibits polymorphisms that have the potential to influence TERT enzyme function and, consequently, animal phenotypes. The primary focus of this study centers on the pig TERT gene, selected as a model organism due to its genetic similarity to humans and its importance as a productive agricultural species. The article explores the exon-intron structure of the TERT gene, analyzing the size of the corresponding transcript and protein product. Furthermore, it provides data on polymorphisms in the pig TERT gene, including missense and synonymous variants. The chromosomal localization of these polymorphisms is characterized and correlated with the domain structure of the TERT enzyme. For the evaluation of the impact of polymorphisms on the structural and functional properties of the TERT enzyme, a molecular-genetic system based on the PCR-RFLP method has been developed. This PCR-RFLP system serves as a basis for subsequent experimental analyses of missense and synonymous variants in population and association studies, allowing for an assessment of the prevalence of these polymorphisms and their significance for animal phenotypes. Given the significance of further laboratory investigation of the pig TERT gene, the developed PCR-RFLP system becomes necessary for the assessment of the functional implications of the polymorphisms within this gene and the potential identification of causative ones among them. The synergy of bioinformatics and molecular-genetic methods in this study lays the groundwork for future impactful research in this field. The presented study holds promise for marker-associated selection, as it opens the way for the use of the TERT gene as a marker in the genetic improvement of agricultural animal species.

Recommendations of the DNA Commission of the International Society for Forensic Genetics (ISFG) on short tandem repeat sequence nomenclature

The DNA Commission of the International Society for Forensic Genetics (ISFG) has developed a set of nomenclature recommendations for short tandem repeat (STR) sequences. These recommendations follow the 2016 considerations of the DNA Commission of the ISFG, incorporating the knowledge gained through research and population studies in the intervening years. While maintaining a focus on backward compatibility with the CE data that currently populate national DNA databases, this report also looks to the future with the establishment of recommended minimum sequence reporting ranges to facilitate interlaboratory comparisons, automated solutions for sequence-based allele designations, a suite of resources to support bioinformatic development, guidance for characterizing new STR loci, and considerations for incorporating STR sequences and other new markers into investigative databases.

Population-based prevalence and mutational landscape of von Willebrand disease using large-scale genetic databases

Von Willebrand disease (VWD) is a common bleeding disorder caused by mutations in the von Willebrand factor gene (VWF). The true global prevalence of VWD has not been accurately established. We estimated the worldwide and within-population prevalence of inherited VWD by analyzing exome and genome data of 141,456 individuals gathered by the genome Aggregation Database (gnomAD). We also extended our data deepening by mining the main databases containing VWF variants i.e., the Leiden Open Variation Database (LOVD) and the Human Gene Mutation Database (HGMD) with the goal to explore the global mutational spectrum of VWD. A total of 4,313 VWF variants were identified in the gnomAD population, of which 505 were predicted to be pathogenic or already reported to be associated with VWD. Among the 282,912 alleles analyzed, 31,785 were affected by the aforementioned variants. The global prevalence of dominant VWD in 1000 individuals was established to be 74 for type 1, 3 for 2A, 3 for 2B and 6 for 2M. The global prevalences for recessive VWD forms (type 2N and type 3) were 0.31 and 0.7 in 1000 individuals, respectively. This comprehensive analysis provided a global mutational landscape of VWF by means of 927 already reported variants in the HGMD and LOVD datasets and 287 novel pathogenic variants identified in the gnomAD. Our results reveal that there is a considerably higher than expected prevalence of putative disease alleles and variants associated with VWD and suggest that a large number of VWD patients are undiagnosed.

Isolation, Characterization, and Identification of Gut Bacteria from Piscine Ectoparasite, Argulus Bengalensis (Ramakrishna 1951) and their Relationship with Haematophagy

Gut microbiome plays a pivotal role in health and nutrition of most organisms. Argulus bengalensis is a haematophagus ectoparasite of fresh water carp and its infection causes extensive damage to fish farms. The present study aims at isolation, characterization and identification of the gut bacteria from Argulus bengalensis and to decipher its potential contribution in haematophagy of the parasite. The gut bacteria were isolated, cultured and identified based on analysis of its morphological, physiological and biochemical features as well as 16s rDNA analyses against the NCBI genetic database. Antibiotic sensitivity was tested. Haemolytic activity and ability of the isolates to produce anticoagulant substance were also tested to justify the hypothesis. Two isolates were identified to be similar type strains of Acenatobacter baumanii and Aeromonas hydrophila respectively which have accession number MW811800 and MW806655 respectively. Both bacteria were found sensitive to most antibiotics. Both Acenatobacter baumanii and Aeromonas hydrophila showed their haemolytic activities and able to secrete anticoagulant substances establishing their mutualistic association which increase the fitness of the parasitic host facilitating haematophagy. The outcome of the study thus may provide a scientific direction to develop novel methods to control of Argulosis.

Characterizing North Carolina black bear (Ursus americanus) populations using UrsaPlex v2.0

American black bears (Ursus americanus) have been successfully restored in North Carolina (NC) due to management and research efforts by the North Carolina Wildlife Resources Commission and various partners. Investigations by law enforcement in NC involving black bears typically center on a) illegal take, b) purchase, possession, and sale of bear parts, or c) human-bear interactions. Effective prosecution of illegal parties requires methods that permit individual identification of black bears. Typically, individualization is achieved using robust DNA profiling and comparison to accepted genetic databases. Currently, a genetic database of highly variable loci genotyped from black bears across their range in NC does not exist. To address this, we focused on genotyping NC black bears using an updated version of UrsaPlex (UrsaPlex v2.0), a short tandem repeat (STR) panel of 11 loci and three sex-linked markers, previously developed to permit individualization for California black bears. Biological samples were obtained from NC black bears following IACUC approved protocols. Total genomic DNA was isolated from each sample and genotyped using UrsaPlex v2.0. The number of alleles in the final genotyped population (n = 173) ranged from five (UamD118 and UamB8) to 33 (UamA9). The observed heterozygosity (Ho) ranged from 0.471 (UamB1) to 0.872 (UamA9), while the expected heterozygosity (He) ranged from 0.469 (UamB1) to 0.919 (UamA9). The probability of identity (PID) was calculated as 6.9 × 10-13. These results demonstrate the potential utility of UrsaPlex v2.0 for permitting individual identification of NC black bears for use in forensic casework and for population management.

Genetic Polymorphism Analysis of 24 Y-STRs in a Han Chinese Population in Luzhou, Southwest China.

Han is the largest of China's 56 ethnic groups and the most populous ethnic group in the world. The Luzhou region is located in southwest China, at the junction of three provinces. The unique historical factors contribute to the genetic polymorphism information. Short tandem repeats (STRs) are highly polymorphic, but the polymorphism of the Y chromosomal STRs (Y-STRs) loci in the Luzhou region is still unclear. It is of great significance to provide Y-STRs genetic data for the Han population from the Luzhou areas of southwest China. A total of 910 unrelated male individuals of the Han population from the Luzhou area were recruited, and 24 Y-STRs were analyzed. The population structure and phylogenetic relationships were compared with those of another 11 related Han populations. A total of 893 different haplotypes were achieved from 910 samples, of which 877 (98.21%) haplotypes were unique. Haplotype diversity and discrimination were 0.999956 and 0.981319, respectively. The lowest genetic diversity of DYS437 is 0.4321, and the highest genetic diversity of DYS385a/b is 0.9642. Pair-to-pair genetic distance and relative probability values indicate that Luzhou Han people are close to Sichuan Han people, Guangdong Han people, and Hunan Han people, which is consistent with geographical distribution, historical influence, and economic development. The 24 Y-STR markers of the southwest Luzhou Han population were highly polymorphic, which provided us with genetic polymorphism information and enriched the population genetic database. Therefore, it is of great value to our forensic applications and population genetics research.

DNA Identification of Parasitic Copepods <i>Salmincola</i> (Copepoda, Siphonostomatoida, Lernaeopodidae): Variability and Rate of Evolution of the Mitochondrial Cytochrome c Oxidase Subunit I Gene

The barcode fragment of the COI gene was sequenced in 91 specimens of five species of parasitic Salmincola copepods, sampled from salmonids mainly from the Russian Far East: S. californiensis (mykiss and masu salmon) and S. edwardsii (various species of chars, sockeye salmon from Lake Kronotskoe), S. carpionis (various species of chars), S. markewitschi (whitespotted char), S. stellata (Sakhalin taimen). A total of 41 haplotypes were found with a maximum level of differences of 0.183 nucleotide substitutions per position. The distance between species varied from 0.139 ± 0.014 in the S. markewitschi–S. carpionis pair to 0.179 ± 0.015 in the S. stellata–S. californiensis pair. The intraspecific nucleotide diversity of the COI gene fragment is much lower: for S. californiensis and S. edwardsii, inhabiting the gill cavity and fins of the host – 0.013 ± 0.003 and 0.015 ± 0.003, and for S. stellata, S. markewitschi, and S. carpionis, localized in the buccal cavity of the hosts – 0.002 ± 0.001, 0.004 ± 0.001, and 0.005 ± 0.001, respectively. A comparison of samples of three Salmincola copepod species from different regions of the Russian Far East revealed a significant (Fst = 0.28–0.42, P \( \ll \) 0.001) genetic subdivision. Three subclades of edwardsii-like copepods – S. edwardsii from the Russian Far East, S. edwardsii from the American brook char of eastern North America, and S. siscowet from the lake char of Michigan (COI sequences of copepods from the last two groups are taken from genetic databases) – differed from each other by an average of 9.3–10.9% nucleotide positions, which means the need for a taxonomic revision of S. edwardsii. According to the molecular dating carried out, the divergence of Salmincola lineages started in the Miocene and ended in the early Pliocene. The phylogenetic substitution rate was 0.0228 (95% interval: 0.0132–0.033) nucleotide substitutions/position/million years/lineage. The rate of nucleotide substitutions at the population level is 3.7 times higher – 0.0849 (0.0212–0.170). The high level of variability of the COI gene fragment makes this marker a useful tool both for developing the taxonomy and phylogeny of Salmincola and Lernaeopodidae copepods at the species and genus levels, and for analyzing the differentiation of their populations.

OC 60.2 Population-Based Prevalence and Mutational Landscape of Von Willebrand Disease using Large-Scale Genetic Databases

OC 60.2 Population-Based Prevalence and Mutational Landscape of Von Willebrand Disease using Large-Scale Genetic Databases

"Big Data" Analyses Underlie Clinical Discoveries at the Aortic Institute.

This issue of the Yale Journal of Biology and Medicine (YJBM) focuses on Big Data and precision analytics in medical research. At the Aortic Institute at Yale New Haven Hospital, the vast majority of our investigations have emanated from our large, prospective clinical database of patients with thoracic aortic aneurysm (TAA), supplemented by ultra-large genetic sequencing files. Among the fundamental clinical and scientific discoveries enabled by application of advanced statistical and artificial intelligence techniques on these clinical and genetic databases are the following: From analysis of Traditional "Big Data" (Large data sets). 1. Ascending aortic aneurysms should be resected at 5 cm to prevent dissection and rupture. 2. Indexing aortic size to height improves aortic risk prognostication. 3. Aortic root dilatation is more malignant than mid-ascending aortic dilatation. 4. Ascending aortic aneurysm patients with bicuspid aortic valves do not carry the poorer prognosis previously postulated. 5. The descending and thoracoabdominal aorta are capable of rupture without dissection. 6. Female patients with TAA do more poorly than male patients. 7. Ascending aortic length is even better than aortic diameter at predicting dissection. 8. A "silver lining" of TAA disease is the profound, lifelong protection from atherosclerosis. From Modern "Big Data" Machine Learning/Artificial Intelligence analysis: 1. Machine learning models for TAA: outperforming traditional anatomic criteria. 2. Genetic testing for TAA and dissection and discovery of novel causative genes. 3. Phenotypic genetic characterization by Artificial Intelligence. 4. Panel of RNAs "detects" TAA. Such findings, based on (a) long-standing application of advanced conventional statistical analysis to large clinical data sets, and (b) recent application of advanced machine learning/artificial intelligence to large genetic data sets at the Yale Aortic Institute have advanced the diagnosis and medical and surgical treatment of TAA.

DisVar: an R library for identifying variants associated with diseases using large-scale personal genetic information.

Genetic variants may potentially play a contributing factor in the development of diseases. Several genetic disease databases are used in medical research and diagnosis but the web applications used to search these databases for disease-associated variants have limitations. The application may not be able to search for large-scale genetic variants, the results of searches may be difficult to interpret and variants mapped from the latest reference genome (GRCH38/hg38) may not be supported. In this study, we developed a novel R library called "DisVar" to identify disease-associated genetic variants in large-scale individual genomic data. This R library is compatible with variants from the latest reference genome version. DisVar uses five databases of disease-associated variants. Over 100 million variants can be simultaneously searched for specific associated diseases. The package was evaluated using 24 Variant Call Format (VCF) files (215,054 to 11,346,899 sites) from the 1000 Genomes Project. Disease-associated variants were detected in 298,227 hits across all the VCF files, taking a total of 63.58 m to complete. The package was also tested on ClinVar's VCF file (2,120,558 variants), where 20,657 hits associated with diseases were identified with an estimated elapsed time of 45.98 s. DisVar can overcome the limitations of existing tools and is a fast and effective diagnostic and preventive tool that identifies disease-associated variations from large-scale genetic variants against the latest reference genome.