Association between cancer genes and germ layer specificity.

Cancer signaling pathways defining cell fates are related to differentiation. During the developmental process, three germ layers (endoderm, mesoderm, and ectoderm) are formed during embryonic development that differentiate into organs via the epigenetic regulation of specific genes. To examine the relationship, the specificities of cancer gene mutations that depend on the germ layers are studied. The major organs affected by cancer were determined based on statistics from the National Cancer Information Center of Korea, and were grouped according to their germ layer origins. Then, the gene mutation frequencies were evaluated to identify any bias based on the differentiation group using the Catalogue of Somatic Mutations in Cancer (COSMIC) database. The chi-square test showed that the p-value of 152 of 166 genes was less than 0.05, and 151 genes showed p-values of less than 0.05 even after adjusting for the false discovery rate (FDR). The germ layer-specific genes were evaluated using visualization based on basic statistics, and the results matched the top ranking genes depending on organs in the COSMIC database.The current study confirmed the germ layer specificity of major cancer genes. The germ layer specificity of mutated driver genes is possibly important in cancer treatments because each mutated gene may react differently depending on the germ layer of origin. By understanding the mechanism of gene mutation in the development and progression of cancer in the context of cell-fate pathways, a more effective therapeutic strategy for cancer can be established.

Population mutation properties of tumor evolution.

Tumor growth patterns differ depending on the individual tumor, leading to various patterns of genetic heterogeneity across tumors. Despite their importance, the population mutation properties of tumor evolution have not been well studied, especially in terms of overall genetic heterogeneity. The current study aims to examine factors in tumor evolution influencing overall genetic heterogeneity. Extensive simulations of the representative evolutionary patterns of various tumors were conducted in the current study to determine the overall genetic characteristics of tumor evolution. The variations in cell birth/death rates and angiogenesis duration were examined based on the simplest growth pattern of tumors with avascular growth, angiogenesis, and vascular growth. To examine the impact of evolutionary tree structure, three-step linear evolution and branching evolution were investigated based on various subpopulation initiation times. The population size during the initial growth phase and the duration of angiogenesis are important factors affecting overall genetic heterogeneity. Furthermore, the shape of the evolutionary tree is crucial for defining the genetic heterogeneity of the extant tumor cell population, indicating the importance of the initiation timing of subpopulations. Branching evolution results in slightly greater genetic heterogeneity in terms of allelic distribution than in terms of the number of variants. The results of the current study reveal that the pattern of tumor evolution is critical for defining tumor genetic heterogeneity. These population genetic approaches are important for understanding the properties of tumor cell populations.

Population-specific long-range linkage disequilibrium in the human genome and its influence on identifying common disease variants.

Despite the availability of large-scale sequencing data, long-range linkage disequilibrium (LRLD) has not been extensively studied. The theoretical aspects of LRLD estimates were studied to determine the best estimation method for the sequencing data of three different populations of African (AFR), European (EUR), and East-Asian (EAS) descent from the 1000 Genomes Project. Genome-wide LRLDs excluding centromeric regions revealed clear population specificity, presenting substantially more population-specific LRLDs than coincident LRLDs. Clear relationships between the functionalities of the regions in LRLDs denoted long-range interactions in the genome. The proportions of gene regions were increased in LRLD variants, and the coding sequence (CDS)-CDS LRLDs showed obvious functional similarities between genes in LRLDs. Application to theoretical case-control associations confirmed that the LRLDs in genome-wide association studies (GWASs) could contribute to false signals, although the impacts might not be severe in most cases. LRLDs with variants with functional similarity exist in the human genome indicating possible gene-gene interactions, and they differ depending on populations. Based on the current study, LRLDs should be examined in GWASs to identify true signals. More importantly, population specificity in LRLDs should be examined in relevant studies.

Evidence of Recent Intricate Adaptation in Human Populations.

Recent human adaptations have shaped population differentiation in genomic regions containing putative functional variants, mostly located in predicted regulatory elements. However, their actual functionalities and the underlying mechanism of recent adaptation remain poorly understood. In the current study, regions of genes and repeats were investigated for functionality depending on the degree of population differentiation, FST or ΔDAF (a difference in derived allele frequency). The high FST in the 5´ or 3´ untranslated regions (UTRs), in particular, confirmed that population differences arose mainly from differences in regulation. Expression quantitative trait loci (eQTL) analyses using lymphoblastoid cell lines indicated that the majority of the highly population-specific regions represented cis- and/or trans-eQTL. However, groups having the highest ΔDAFs did not necessarily have higher proportions of eQTL variants; in these groups, the patterns were complex, indicating recent intricate adaptations. The results indicated that East Asian (EAS) and European populations (EUR) experienced mutual selection pressures. The mean derived allele frequency of the high ΔDAF groups suggested that EAS and EUR underwent strong adaptation; however, the African population in Africa (AFR) experienced slight, yet broad, adaptation. The DAF distributions of variants in the gene regions showed clear selective pressure in each population, which implies the existence of more recent regulatory adaptations in cells other than lymphoblastoid cell lines. In-depth analysis of population-differentiated regions indicated that the coding gene, RNF135, represented a trans-regulation hotspot via cis-regulation by the population-specific variants in the region of selective sweep. Together, the results provide strong evidence of actual intricate adaptation of human populations via regulatory manipulation.

Rare high-impact disease variants: properties and identifications.

Although many genome-wide association studies have been performed, the identification of disease polymorphisms remains important. It is now suspected that many rare disease variants induce the association signal of common variants in linkage disequilibrium (LD). Based on recent development of genetic models, the current study provides explanations of the existence of rare variants with high impacts and common variants with low impacts. Disease variants are neither necessary nor sufficient due to gene-gene or gene-environment interactions. A new method was developed based on theoretical aspects to identify both rare and common disease variants by their genotypes. Common disease variants were identified with relatively small odds ratios and relatively small sample sizes, except for specific situations in which the disease variants were in strong LD with a variant with a higher frequency. Rare disease variants with small impacts were difficult to identify without increasing sample sizes; however, the method was reasonably accurate for rare disease variants with high impacts. For rare variants, dominant variants generally showed better Type II error rates than recessive variants; however, the trend was reversed for common variants. Type II error rates increased in gene regions containing more than two disease variants because the more common variant, rather than both disease variants, was usually identified. The proposed method would be useful for identifying common disease variants with small impacts and rare disease variants with large impacts when disease variants have the same effects on disease presentation.

Ancestral alleles in the human genome based on population sequencing data.

Ancestral allele information is useful for genetics studies. Previously, the identification of ancestral alleles was primarily based on sequence alignments between species. Alternative ways to identify ancestral alleles were proposed in this study based on population sequencing data. The methods described here utilized the diversity between haplotypes harboring ancestral and newly emerged alleles. Simulations showed that these methods were reliable for identifying ancestral alleles when the variants had not aged too greatly. Application to the human genome sequencing data suggested the role of indels in maintaining the GC content in the human genome. The deletion-to-insertion ratios and GC proportions were correlated depending on the sizes of insertions and deletions in the direction of increasing GC content. There were GC-biased fixations in single base-pair insertions and AT-biased fixations in single base-pair deletions in the results based on the proposed methods. In the current study, GC-biased gene conversions in nucleotide substitutions were very slight or insignificant. In the variants of several quantitative trait loci (QTLs), slight GC-biased gene conversion was observed in nucleotide substitutions. For the QTL indels, insertions were observed more often than deletions, and deletion-biased fixation was observed, providing new insights into the evolution of functional genes.

A novel approach for identifying causal models of complex diseases from family data.

Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.

Effective population size of korean populations.

Recently, new methods have been developed for estimating the current and recent changes in effective population sizes. Based on the methods, the effective population sizes of Korean populations were estimated using data from the Korean Association Resource (KARE) project. The overall changes in the population sizes of the total populations were similar to CHB (Han Chinese in Beijing, China) and JPT (Japanese in Tokyo, Japan) of the HapMap project. There were no differences in past changes in population sizes with a comparison between an urban area and a rural area. Age-dependent current and recent effective population sizes represent the modern history of Korean populations, including the effects of World War II, the Korean War, and urbanization. The oldest age group showed that the population growth of Koreans had already been substantial at least since the end of the 19th century.

Linkage disequilibrium decay and past population history in the human genome.

The fluctuation of population size has not been well studied in the previous studies of theoretical linkage disequilibrium (LD) expectation. In this study, an improved theoretical prediction of LD decay was derived to account for the effects of changes in effective population sizes. The equation was used to estimate effective population size (N(e)) assuming a constant N(e) and LD at equilibrium, and these N(e) estimates implied the past changes of N(e) for a certain number of generations until equilibrium, which differed based on recombination rate. As the influence of recent population history on the N(e) estimates is larger than old population history, recent changes in population size can be inferred more accurately than old changes. The theoretical predictions based on this improved expression showed accurate agreement with the simulated values. When applied to human genome data, the detailed recent history of human populations was obtained. The inferred past population history of each population showed good correspondence with historical studies. Specifically, four populations (three African ancestries and one Mexican ancestry) showed population growth that was significantly less than that of other populations, and two populations originated from China showed prominent exponential growth. During the examination of overall LD decay in the human genome, a selection pressure on chromosome 14, the gephyrin gene, was observed in all populations.

Effective population size of current human population.

In order to estimate the effective population size (Ne) of the current human population, two new approaches, which were derived from previous methods, were used in this study. One is based on the deviation from linkage equilibrium (LE) between completely unlinked loci in different chromosomes and another is based on the deviation from the Hardy-Weinberg Equilibrium (HWE). When random mating in a population is assumed, genetic drifts in population naturally induce linkage disequilibrium (LD) between chromosomes and the deviation from HWE. The latter provides information on the Ne of the current population, and the former provides the same when the Ne is constant. If Ne fluctuates, recent Ne changes are reflected in the estimates based on LE, and the comparison between two estimates can provide information regarding recent changes of Ne. Using HapMap Phase III data, the estimates were varied from 622 to 10 437, depending on populations and estimates. The Ne appeared to fluctuate as it provided different estimates for each of the two methods. These Ne estimates were found to agree approximately with the overall increment observed in recent human populations.

Relative mutation rates of each nucleotide for another estimated from allele frequency spectra at human gene loci.

This study aims to comprehensively examine the mutation rates of one base for another in human gene loci. In contrast to most previous efforts based on divergence data from untranscribed regions, the present study employs the basic theory of the reversible recurrent mutation model using large-scale, high-quality re-sequencing data from public databases of gene loci. Population mutation parameters (4Nnu and 4Nmu) are obtained for each pair of base substitutions. The estimated parameters show good strand reversal symmetry, supporting the existence of mutation-drift equilibrium. Analysis of specific gene regions including mRNA, coding sequence (CDS), 5'-untranslated region (5'-UTRs), 3'-UTR and intron shows that there are clear differences in the mutation rates of each base for another depending on the location of the base in question. Results from analyses that take the adjacent bases into account exhibit excellent strand reversal symmetry, confirming that the identity of an adjacent base influences mutation rates. The CpG to TpG (or CpG to CpA) substitution is found at a rate approximately seven-fold higher than the reverse transition in intron regions due to cytosine deamination, but the effect is strongly reduced in mRNA regions and almost entirely lost in 5'-UTRs. However, from the overall increased transitions in sites other than CpGs and the proportion of CpGs in the total sequence, CpG methylation is not the main factor responsible for the increased rate of transitions as compared with transversions. In this report, after adjusting average mutation rates to the sequence compositions, no substitution bias is found between A+T and C+G, indicating base composition equilibrium in human gene loci. Population differences are also identified between groups of people of African and European descent, presumably due to past population histories. By applying the basic theory of population genetics to re-sequenced data, this study contributes new, detailed information regarding mutations in human gene regions.

Genotype and neuropsychological response inhibition as resilience promoters for attention-deficit/hyperactivity disorder, oppositional defiant disorder, and conduct disorder under conditions of psychosocial adversity.

Whereas child personality, IQ, and family factors have been identified as enabling a resilient response to psychosocial adversity, more direct biological resilience factors have been less well delineated. This is particularly so for child attention-deficit/hyperactivity disorder (ADHD), which has received less attention from a resilience perspective than have associated externalizing disorders. Children from two independent samples were classified as resilient if they avoided developing ADHD, oppositional defiant disorder (ODD), or conduct disorder (CD) in the face of family adversity. Two protective factors were examined for their potential relevance to prefrontal brain development: neuropsychological response inhibition, as assessed by the Stop task, and a composite catecholamine genotype risk score. Resilient children were characterized in both samples by more effective response inhibition, although the effect in the second sample was very small. Genotype was measured in Sample 1, and a composite high risk genotype index was developed by summing presence of risk across markers on three genes expressed in prefrontal cortex: dopamine transporter, dopamine D4 receptor, and noradrenergic alpha-2 receptor. Genotype was a reliable resilience indicator against development of ADHD and CD, but not ODD, in the face of psychosocial adversity. Results illustrate potential neurobiological protective factors related to development of prefrontal cortex that may enable children to avoid developing ADHD and CD in the presence of psychosocial adversity.

The adrenergic receptor alpha-2A gene (ADRA2A) and neuropsychological executive functions as putative endophenotypes for childhood ADHD.

There is resurgent interest in the psychiatric literature in endophenotypes, variables thought to more strongly reflect the effects of candidate genes than do manifest disorders. In a sample of 176 children with attention deficit hyperactivity disorder (ADHD) and 52 of their siblings, we examined the validity of several putative endophenotypes for ADHD that represent commonly used clinical measures of multiple cognitive/neuropsychological domains of executive functions (EFs). We review their distributional normality, their relations to ADHD symptoms in probands and unaffected siblings relative to nonADHD controls, and their correlation in siblings. We also tested theEF measures' associations with the ADRA2A gene and whether they mediated or moderated the associations between ADHD and ADRA2A. Several EF measures showed association with ADRA2A, as well as moderation, but not mediation, of its association with ADHD. Implications of the results for evaluating the validity and utility of putative endophenotype measures and for finding candidate gene effects on ADHD are discussed.