On whole-genome demography of world's ethnic groups and individual genomic identity.

All current categorizations of human population, such as ethnicity, ancestry and race, are based on various selections and combinations of complex and dynamic common characteristics, that are mostly societal and cultural in nature, perceived by the members within or from outside of the categorized group. During the last decade, a massive amount of a new type of characteristics, that are exclusively genomic in nature, became available that allows us to analyze the inherited whole-genome demographics of extant human, especially in the fields such as human genetics, health sciences and medical practices (e.g., 1,2,3), where such health-related characteristics can be related to whole-genome-based categorization. Here we show the feasibility of deriving such whole-genome-based categorization. We observe that, within the available genomic data at present, (a) the study populations form about 14 genomic groups, each consisting of multiple ethnic groups; and (b), at an individual level, approximately 99.8%, on average, of the whole autosomal-genome contents are identical between any two individuals regardless of their genomic or ethnic groups.

An induced annual modulation signature in COSINE-100 data by DAMA/LIBRA's analysis method.

The DAMA/LIBRA collaboration has reported the observation of an annual modulation in the event rate that has been attributed to dark matter interactions over the last two decades. However, even though tremendous efforts to detect similar dark matter interactions were pursued, no definitive evidence has been observed to corroborate the DAMA/LIBRA signal. Many studies assuming various dark matter models have attempted to reconcile DAMA/LIBRA's modulation signals and null results from other experiments, however no clear conclusion can be drawn. Apart from the dark matter hypothesis, several studies have examined the possibility that the modulation is induced by variations in detector's environment or their specific analysis methods. In particular, a recent study presents a possible cause of the annual modulation from an analysis method adopted by the DAMA/LIBRA experiment in which the observed annual modulation could be reproduced by a slowly varying time-dependent background. Here, we study the COSINE-100 data using an analysis method similar to the one adopted by the DAMA/LIBRA experiment and observe a significant annual modulation, however the modulation phase is almost opposite to that of the DAMA/LIBRA data. Assuming the same background composition for COSINE-100 and DAMA/LIBRA, simulated experiments for the DAMA/LIBRA without dark matter signals also provide significant annual modulation with an amplitude similar to DAMA/LIBRA with opposite phase. Even though this observation does not directly explain the DAMA/LIBRA results directly, this interesting phenomenon motivates more profound studies of the time-dependent DAMA/LIBRA background data.

Effect of Salivary Exosomal miR-25-3p on Periodontitis With Insulin Resistance.

Periodontitis is caused by an oral microbial dysbiosis-mediated imbalance of the local immune microenvironment, which is promoted by insulin resistance and obesity. The prevalence and severity of periodontitis is higher in patients with type 2 diabetes than in healthy individuals, possibly because of differences in immune responses. The level of glycemic control also affects the saliva profile, which may further promote periodontal disease in diabetes patients. Therefore, we compared the salivary exosomal miRNA profiles of patients with type 2 diabetes with those of healthy individuals, and we found that exosomal miR-25-3p in saliva is significantly enriched (by approximately 2-fold, p < 0.01) in obese patients with type 2 diabetes. We also identified CD69 mRNA as a miR-25-3p target that regulates both activation of γδ T cells and the inflammatory response. Knockdown of CD69 increased (by approximately 2-fold) interleukin-17A production of γδ T cells in vitro. To evaluate the role of exosomal miRNA on progression of periodontitis, we analyzed regional immune cells in both periodontal tissues and lymph nodes from mice with periodontitis. We found that diet-induced obesity increased the population of infiltrating pro-inflammatory immune cells in the gingiva and regional lymph nodes of these mice. Treatment with miR-25-3p inhibitors prevented the local in vivo inflammatory response in mice with periodontitis and diet-induced obesity. Finally, we showed that suppression of interleukin 17-mediated local inflammation by a miR-25-3p inhibitor alleviated (by approximately 34%) ligature-induced periodontal alveolar bone loss in mice. Taken together, these data suggest that exosomal miR-25-3p in saliva contributes to development and progression of diabetes-associated periodontitis. Discovery of additional miR-25-3p targets may provide critical insights into developing drugs to treat periodontitis by regulating γδ T cell-mediated local inflammation.

Whole-proteome tree of life suggests a deep burst of organism diversity.

An organism tree of life (organism ToL) is a conceptual and metaphorical tree to capture a simplified narrative of the evolutionary course and kinship among the extant organisms. Such a tree cannot be experimentally validated but may be reconstructed based on characteristics associated with the organisms. Since the whole-genome sequence of an organism is, at present, the most comprehensive descriptor of the organism, a whole-genome sequence-based ToL can be an empirically derivable surrogate for the organism ToL. However, experimentally determining the whole-genome sequences of many diverse organisms was practically impossible until recently. We have constructed three types of ToLs for diversely sampled organisms using the sequences of whole genome, of whole transcriptome, and of whole proteome. Of the three, whole-proteome sequence-based ToL (whole-proteome ToL), constructed by applying information theory-based feature frequency profile method, an "alignment-free" method, gave the most topologically stable ToL. Here, we describe the main features of a whole-proteome ToL for 4,023 species with known complete or almost complete genome sequences on grouping and kinship among the groups at deep evolutionary levels. The ToL reveals 1) all extant organisms of this study can be grouped into 2 "Supergroups," 6 "Major Groups," or 35+ "Groups"; 2) the order of emergence of the "founders" of all of the groups may be assigned on an evolutionary progression scale; 3) all of the founders of the groups have emerged in a "deep burst" at the very beginning period near the root of the ToL-an explosive birth of life's diversity.

A genome Tree of Life for the Fungi kingdom.

Fungi belong to one of the largest and most diverse kingdoms of living organisms. The evolutionary kinship within a fungal population has so far been inferred mostly from the gene-information-based trees ("gene trees"), constructed commonly based on the degree of differences of proteins or DNA sequences of a small number of highly conserved genes common among the population by a multiple sequence alignment (MSA) method. Since each gene evolves under different evolutionary pressure and time scale, it has been known that one gene tree for a population may differ from other gene trees for the same population depending on the subjective selection of the genes. Within the last decade, a large number of whole-genome sequences of fungi have become publicly available, which represent, at present, the most fundamental and complete information about each fungal organism. This presents an opportunity to infer kinship among fungi using a whole-genome information-based tree ("genome tree"). The method we used allows comparison of whole-genome information without MSA, and is a variation of a computational algorithm developed to find semantic similarities or plagiarism in two books, where we represent whole-genomic information of an organism as a book of words without spaces. The genome tree reveals several significant and notable differences from the gene trees, and these differences invoke new discussions about alternative narratives for the evolution of some of the currently accepted fungal groups.

PNA clamping-assisted fluorescence melting curve analysis for detecting EGFR and KRAS mutations in the circulating tumor DNA of patients with advanced non-small cell lung cancer.

BACKGROUND: Circulating cell-free DNA (cfDNA) is emerging as a surrogate sample type for mutation analyses. To improve the clinical utility of cfDNA, we developed a sensitive peptide nucleic acid (PNA)-based method for analyzing EGFR and KRAS mutations in the plasma cfDNA of patients with advanced non-small cell lung cancer (NSCLC). METHODS: Baseline tissue and plasma samples were collected from treatment-naïve advanced NSCLC patients participated in a randomized phase II study, which was registered with ClinicalTrials.gov at Feb. 2009 (NCT01003964). EGFR and KRAS mutations in the plasma cfDNA were analyzed retrospectively using a PNA clamping-assisted fluorescence melting curve analysis. The results were compared with those obtained from tissue analysis performed using the direct sequencing. Exploratory analyses were performed to determine survival predicted by the plasma and tissue mutation status. RESULTS: Mutation analyses in matched tissue and plasma samples were available for 194 patients for EGFR and 135 patients for KRAS. The mutation concordance rates were 82.0 % (95 % confidence interval [CI], 76.5-87.4) for EGFR and 85.9 % (95 % CI, 80.1-91.8) for KRAS. The plasma EGFR mutation test sensitivity and specificity were 66.7 % (95 % CI, 60.0-73.3) and 87.4 % (95 % CI, 82.7-92.1), respectively, and the plasma KRAS mutation test sensitivity and specificity were 50.0 % (95 % CI, 41.6-58.4) and 89.4 % (95 % CI, 84.2-94.6), respectively. The predictive value of the plasma EGFR and KRAS mutation status with respect to survival was comparable with that of the tissue mutation status. CONCLUSIONS: These data suggest that plasma EGFR and KRAS mutations can be analyzed using PNA-based real-time PCR methods and used as an alternative to tumor genotyping for NSCLC patients when tumor tissue is not available.

Peptide nucleic acid array for detection of point mutations in hepatitis B virus associated with antiviral resistance.

The detection of antiviral-resistant hepatitis B virus (HBV) mutations is important for monitoring the response to treatment and for effective treatment decisions. We have developed an array using peptide nucleic acid (PNA) probes to detect point mutations in HBV associated with antiviral resistance. PNA probes were designed to detect mutations associated with resistance to lamivudine, adefovir, and entecavir. The PNA array assay was sensitive enough to detect 10(2) copies/ml. The PNA array assay was able to detect mutants present in more than 5% of the virus population when the total HBV DNA concentration was greater than 10(4) copies/ml. We analyzed a total of 68 clinical samples by this assay and validated its usefulness by comparing results to those of the sequencing method. The PNA array correctly identified viral mutants and has high concordance (98.3%) with direct sequencing in detecting antiviral-resistant mutations. Our results showed that the PNA array is a rapid, sensitive, and easily applicable assay for the detection of antiviral-resistant mutation in HBV. Thus, the PNA array is a useful and powerful diagnostic tool for the detection of point mutations or polymorphisms.

Highly sensitive PNA array platform technology for single nucleotide mismatch discrimination.

Reliable discrimination of single nucleotide mismatch was demonstrated using arrays with peptide nucleic acid (PNA) probes. Newly developed PNA probes immobilization method and hybridization conditions for PNA arrays gave excellent specificity and sensitivity. And we compared the specificity, sensitivity, and stability obtained with the PNA and DNA arrays in discriminating single nucleotide mismatches. PNA arrays had superior perfect match-to-mismatch signal ratios and sensitivities. The relative signal intensities of mismatch PNA probes ranged from 1.6% to 12.1% of the perfect match PNA probes. These results demonstrated that the PNA arrays were 2.0 to 37.3 times more specific and about 10 times more sensitive than DNA arrays. A PNA array showed the same specificity and sensitivity after 12-month storage at room temperature.

Peptide nucleic acid-based array for detecting and genotyping human papillomaviruses.

We describe a novel array for accurate and reliable genotyping of human papillomavirus (HPV) using peptide nucleic acid (PNA) probes. In order to exploit the superior hybridization properties of PNA with target HPV DNAs, we developed a novel PNA array (PANArray HPV). PANArray HPV enables the detection and genotyping of HPVs using 32 type-specific PNA capture probes for medically important HPVs. All tested HPV types showed highly unique hybridization patterns with type-specific PNA probes. PNA array results showed stable specificities and sensitivities after up to 13 months of storage at room temperature. Also, we demonstrated the superior specificity, sensitivity, and stability of PNA arrays for HPV genotyping. We compared the genotyping results of the PNA array to sequencing with MY09/11 PCR products derived from 72 clinical samples. The results showed excellent agreement between the PNA array and sequencing, except for samples reflecting multiple infections. The results from the PNA array were compared with those of type-specific PCR when discrepant results occurred owing to multiple infections. The results for the PNA array matched those of type-specific PCR in all cases. Newly developed PNA arrays show excellent specificity and sensitivity and long shelf life. Our results suggest that the PNA array represents a reliable alternative to conventional DNA arrays for HPV genotyping, as well as for diagnostics.