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PubMed2005

Genomic disorders: molecular mechanisms for rearrangements and conveyed phenotypes.

Rearrangements of our genome can be responsible for inherited as well as sporadic traits. The analyses of chromosome breakpoints in the proximal short arm of Chromosome 17 (17p) reveal nonallelic homologous recombination (NAHR) as a major mechanism for recurrent rearrangements whereas nonhomologous end-joining (NHEJ) can be responsible for many of the nonrecurrent rearrangements. Genome architectural features consisting of low-copy repeats (LCRs), or segmental duplications, can stimulate and mediate NAHR, and there are hotspots for the crossovers within the LCRs. Rearrangements introduce variation into our genome for selection to act upon and as such serve an evolutionary function analogous to base pair changes. Genomic rearrangements may cause Mendelian diseases, produce complex traits such as behaviors, or represent benign polymorphic changes. The mechanisms by which rearrangements convey phenotypes are diverse and include gene dosage, gene interruption, generation of a fusion gene, position effects, unmasking of recessive coding region mutations (single nucleotide polymorphisms, SNPs, in coding DNA) or other functional SNPs, and perhaps by effects on transvection.

Base Pairing↗
PubMed2007

African Americans with asthma: genetic insights.

It has been well established that genetic factors strongly affect susceptibility to asthma and its associated traits. It is less clear to what extent genetic variation contributes to the ethnic disparities observed for asthma morbidity and mortality. Individuals of African descent with asthma have more severe asthma, higher IgE levels, a higher degree of steroid dependency, and more severe clinical symptoms than individuals of European descent with asthma but relatively few studies have focused on this particularly vulnerable ethnic group. Similar underrepresentation exists for other minorities, including Hispanics. In this review, a summary of linkage and association studies in populations of African descent is presented, and the role of linkage disequilibrium in the dissection of a complex trait such as asthma is discussed. Consideration for the impact of population stratification in recently admixed populations (i.e., European, African) is essential in genetic association studies focusing on African ancestry groups. With the most recent update on the International HapMap Project, efficient selection of haplotype tagging single nucleotide polymorphisms (htSNPs) for African Americans has accelerated and efficiency of htSNPs chosen from one population to represent other continental groups (e.g., African) has been demonstrated. Cutting-edge approaches, such as genomewide association studies, admixture mapping, and phylogenetic analyses, offer new opportunities for dissecting the genetic basis for asthma in populations of African descent.

Black or African American↗
PubMed2006

Epistasis correlates to genomic complexity.

Whether systematic genetic interactions (epistasis) occur at the genomic scale remains a challenging topic in evolutionary biology. Epistasis should make a significant contribution to variation in complex traits and influence the evolution of genetic systems as sex, diploidy, dominance, or the contamination of genomes with deleterious mutations. We have collected data from widely different organisms and quantified epistasis in a common, per-generation scale. Simpler genomes, such as those of RNA viruses, display antagonistic epistasis (mutations have smaller effects together than expected); bacterial microorganisms do not apparently deviate from independent effects, whereas in multicellular eukaryotes, a transition toward synergistic epistasis occurs (mutations have larger effects together than expected). We propose that antagonistic epistasis might be a property of compact genomes with few nonpleiotropic biological functions, whereas in complex genomes, synergism might emerge from mutational robustness.

Animals↗
PubMed2003

Genetic linkage studies in alopecia areata.

Alopecia areata affects approximately 4.6 million individuals in the United States alone. It is typified by patchy hair loss on the scalp that can progress to cover the entire scalp (alopecia totalis) and eventually the entire body (alopecia universalis). Despite the high incidence of this condition, its genetic basis is largely unknown. It is now generally accepted, however, that it fits the paradigm of a complex trait, in which a combination of genetic and environmental factors results in the final phenotype. Genetic studies have been limited thus far to association analyses, which suggest that a permissive HLA status may potentiate the development of alopecia areata. A systematic screen for identifying the primary genetic mechanisms underlying this disorder has never before been undertaken, however. Here we discuss our approach to the identification of susceptibility genes for alopecia areata. In particular, we recently initiated a comprehensive genetic analysis by performing a genome-wide scan in a collection of alopecia families with multiple affected family members. There are currently a number of examples of complex diseases of the skin, such as psoriasis and atopic dermatitis, in which genetic studies are being undertaken that substantiate the timeliness of this approach. We anticipate that these studies will lead to the identification of the susceptibility genes and provide a foundation for understanding how they interact with each other and with other variables, such as the immune system and environmental factors.

Alopecia Areata↗
PubMed2006

Genetic variants of the P-glycoprotein gene Abcb1b modulate opioid-induced hyperalgesia, tolerance and dependence.

OBJECTIVE: Opioid-induced hyperalgesia (OIH) is a state of paradoxically increased nociceptive sensitivity seen in both humans and rodents following the resolution of the acute opioid antinociceptive effects or during periods of chronic opioid administration. Using the power of genetic analysis, we hoped to discover novel mechanisms modulating this trait. BASIC METHODS: The degree of opioid-induced hyperalgesia displayed in response to a thermal stimulus applied to the hind paw was measured in 16 strains of inbred mice after 4 days of morphine administration. The degree of thermal sensitization was then used in a recently developed in silico haplotypic mapping algorithm along with a haplotypic map constructed from a database containing 209,000 single nucleotide polymorphisms. MAIN RESULTS: Analysis of the data resulted in the identification of several haplotype blocks strongly associated with the thermal opioid-induced hyperalgesia trait. The most strongly associated block was located within the Abcb1b P-glycoprotein drug transporter gene. Experiments using the P-glycoprotein inhibitor cyclosporine A and P-glycoprotein null mutant mice supported the hypothesis that a functional association exists between P-glycoprotein transporters and opioid-induced hyperalgesia. The observation of a correlation between morphine brain concentrations and the development of opioid-induced hyperalgesia was consistent with this hypothesis as well. In addition, P-glycoprotein gene deletion and pharmacological inhibition altered morphine ED50, tolerance and physical dependence. CONCLUSIONS: We conclude that the use of haplotypic mapping to identify novel mechanisms controlling complex traits is a viable approach. Variants of the Abcb1b gene may explain some portion of the interstrain differences in OIH and perhaps other consequences of chronic opioid administration.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed1994

Reproductive isolation and the period gene of Drosophila.

The identification of genes of large effect on ecologically important traits is an important aim of molecular ecology. The period gene of Drosophila is a candidate for a gene with a large influence on premating isolation between Drosophila species, as it determines species specific aspects of courtship behaviour. Strains of D. melanogaster are available which have been genetically transformed with the period gene of either D. melanogaster or D. simulans. Here we show that D. melanogaster females do not discriminate between two such strains. This suggests that period may only make a small contribution to total premating isolation between these species. We discuss the use of genetically transformed strains in assessing the influence of single genes on complex traits.

Animals↗
PubMed2014

Genetics and intelligence differences: five special findings.

Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for 'positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century-Genome-wide Complex Trait Analysis (GCTA)-which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the 'missing heritability' gap.

Genetic Predisposition to Disease↗
PubMed2026

Using deep learning models as a genetic architecture for the simulation of breeding schemes.

In several simulation studies, long-term selection led to the rapid depletion of genetic variance. These outcomes differ from real-life observations that we aim to replicate, thereby highlighting a fundamental limitation of current classical quantitative genetic simulation models. Deep learning (DL) models have demonstrated promising results in capturing complex interactions essential for maintaining genetic variance; thus, we hypothesize that DL-based genetic simulation models may preserve more genetic variance than classical models, because the biological pathways underlying complex traits exhibit interactions that classical models ignore. The primary objective of this study was to introduce alternative DL-based genetic simulation models and compare them with classical genetic simulation models in terms of their retention of additive genetic variance under truncation selection in a simulated full-sib pig breeding scheme using real haplotypes as founders. After 20 generations of directional truncation selection, the classical models (A, ADAA, and ADAAADDD) retained between 55% and 64% of their initial additive genetic variance. In contrast, while the DL_simple model lost all its additive variance, the DL medium retained 92% to 98% of its additive variance, and the DL_complex model's initial additive variance increased by 296% to 314%. This paper introduces DL-based genetic simulation models and concludes that their ability to retain additive genetic variance depends on the models' architectural complexity. When sufficiently complex, DL-based models exhibit greater retention of additive genetic variance because they intrinsically capture epistatic interactions that are converted into additive variance, as selection progresses, thus, affirming the role of non-additive genetic effects in maintaining long-term genetic variation.

Deep Learning↗
PubMed2005

The role of genetics in the development of asthma and atopy.

PURPOSE OF REVIEW: The mapping of complex traits such as asthma and atopy is one of the most important and central areas of human genetics. This article will present an overview of the current status of genetic studies of asthma and atopy using genome screens and association studies that have occurred in the literature since January 2003. RECENT FINDINGS: Many regions of the genome have been found to have linkage with the phenotypes of asthma and atopy. Over 70 variants in candidate genes have been reported to be associated with these phenotypes. The main regions these variants have been found are on chromosomes 2q, 5q, 6p, 11q, 12q, 16q and 17q. Five potential asthma susceptibility genes or complexes have been identified using a positional approach. These are ADAM33, DPP10, PHF11 and SETDB2, GPRA and SPINK5. It is evident that environmental factors will influence the expression of genes and the ultimate clinical phenotype of asthma and atopy. SUMMARY: The development of asthma and atopy involves many genes and environmental factors. An understanding of their genetic basis has great implications for their management.

Asthma↗
PubMed2026

Context-specific genetic effects inform endotypes and treatment in asthma.

BACKGROUND: Asthma has heterogeneous risk factors, subtypes, and treatments. It is often unclear how to stratify this heterogeneity in scientific studies and clinical care. Genetics could explain root causes of this clinical heterogeneity, called endotypes, but prior studies have used models that are not designed for complex diseases like asthma. OBJECTIVE: We aimed to find genetic effects that partly explain different asthma endotypes. METHODS: We used recent powerful and robust statistical models of context-specific genetic effects in complex traits. We identified genetic subtypes by clustering clinical asthma features in a case-control cohort, GALA II. We replicated the genetic endotypes in the UK Biobank with gene-context interaction tests. RESULTS: Asthma-associated single nucleotide polymorphisms, polygenic scores, and genome-wide heritability revealed subtype-specific genetic endotypes correlated with type 2 inflammation, allergy, and neuroticism. We validated the type 2 associations with molecular data including nasal RNA sequencing. In the UK Biobank, we replicated these endotypes and found they interact with several polygenic scores and drug-relevant genes. CONCLUSION: Our results show how context-specific genetic effects can unravel biomedically meaningful endotypes of complex disease and suggest novel precision treatment strategies.

Humans↗
PubMed2006

A statistical model for dissecting genomic imprinting through genetic mapping.

As a result of nonequivalent genetic contribution of maternal and paternal genomes to offsprings, genomic imprinting or called parent-of-origin effect, has been broadly identified in plants, animals and humans. Its role in shaping organism's development has been unanimously recognized. However, statistical methods for identifying imprinted quantitative trait loci (iQTL) and estimating the imprinted effect have not been well developed. In this article, we propose an efficient statistical procedure for genomewide estimating and testing the effects of significant iQTL underlying the quantitative variation of interested traits. The developed model can be applied to two different genetic cross designs, backcross and F(2) families derived from inbred lines. The proposed procedure is built within the maximum likelihood framework and implemented with the EM algorithm. Extensive simulation studies show that the proposed model is well performed in a variety of situations. To demonstrate the usefulness of the proposed approach, we apply the model to a published data in an F(2) family derived from LG/S and SM/S mouse stains. Two partially maternal imprinting iQTL are identified which regulate the growth of body weight. Our approach provides a testable framework for identifying and estimating iQTL involved in the genetic control of complex traits.

Algorithms↗
PubMed2002

Mouse models for the genetic dissection of atopy.

Atopic disorders are complex traits with a significant contribution of heritability. Several mouse models for atopic phenotypes such as allergen-induced and intrinsic asthma, atopic dermatitis and immediate cutaneous hypersensitivity have been used to systematically dissect the genetics of these diseases. Many of the chromosomal regions identified in genome-wide screens colocalize with linkage regions of autoimmune phenotypes suggesting common regulatory genes in combination (or addition) to disease-specific genes. Moreover, many of these regions correspond to regions found in the human system, thus strengthening the likelihood of a gene contributing to the phenotype. The role of individual candidate genes has been vigorously pursued in genetically modified mice by destruction or overexpression of the candidate gene. The complex interactions of multiple contributing genes may further be elucidated in randomly mutated mouse strains. Thus mouse models can contribute largely to the elucidation of disease genes.

Animals↗
PubMed2003

Age-stratified heritability estimation in the Framingham Heart Study families.

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31-49 years, 50-60 years, and 61-79 years), reflecting the longitudinal nature of the data, for four quantitative traits. Age-adjusted heritability estimates were obtained at a single common time point for the same four quantitative traits. The importance of these groups is that they consist of the same individuals. The highest age-stratified heritability estimate (h2 = 0.88 (+/- 0.06)) was for height in the model adjusting for gender over all three age groups. SBP gave the lowest heritability estimate (h2 = 0.15 (+/- 0.11)) for the 70 age group in the model adjusting for gender, height, BMI, smoker, and drinker. BMI had slightly higher estimates (h2 = 0.64 (+/- 0.11)) in the 40 age group than previously published. The highest age-adjusted heritability estimate (h2 = 0.90 (+/- 0.06)) was for height in the model adjusting for gender. SBP gave the lowest heritability estimate (h2 = 0.38 (+/- 0.09)) for unadjusted model. These results indicate that some common, complex traits may vary little in their genetic architecture over time and suggest that a common set of genes may be contributing to observed variation for these longitudinally collected phenotypes.

Adult↗
PubMed2005

Epidemiology of neural tube defects.

The epidemiological investigation of the common open neural tube defects (NTDs), anencephaly, and spina bifida, has a long history. The most significant finding from these past studies of NTDs was the identification of the protective effect of maternal, periconceptional supplementation with folic acid. Fortuitously, the association between folic acid and NTDs became widely accepted in the early 1990s, at a time when genetic association studies of complex traits were becoming increasingly feasible. The confluence of these events has had a major impact on the direction of epidemiological, NTD research. Association studies to evaluate genes that may influence the risk of NTDs through their role in folate-related processes, or through other metabolic or developmental pathways are now commonplace. Moreover, the study of genetic as well as non-genetic, factors that may influence NTD risk through effects on the nutrient status of the mother or embryo has emerged as a major research focus. Research efforts over the past decade indicate that gene-gene, gene-environment, and higher-order interactions, as well as maternal genetic effects influence NTD risk, highlighting the complexity of the factors that underlie these conditions. The challenge for the future is to design studies that address these complexities, and are adequately powered to detect the factors or combination of factors that influence the development of NTDs.

Humans↗
PubMed2006

Candidate lung tumor susceptibility genes identified through whole-genome association analyses in inbred mice.

We performed a whole-genome association analysis of lung tumor susceptibility using dense SNP maps ( approximately 1 SNP per 20 kb) in inbred mice. We reproduced the pulmonary adenoma susceptibility 1 (Pas1) locus identified in previous linkage studies and further narrowed this quantitative trait locus (QTL) to a region of less than 0.5 Mb in which at least two genes, Kras2 (Kirsten rat sarcoma oncogene 2) and Casc1 (cancer susceptibility candidate 1; also known as Las1), are strong candidates. Casc1 knockout mouse tumor bioassays showed that Casc1-deficient mice were susceptible to chemical induction of lung tumors. We also found three more genetic loci for lung adenoma development. Analysis of one of these candidate loci identified a previously uncharacterized gene Lasc1, bearing a nonsynonymous substitution (D102E). We found that the Lasc1 Glu102 allele preferentially promotes lung tumor cell growth. Our findings demonstrate the prospects for using dense SNP maps in laboratory mice to refine previous QTL regions and identify genetic determinants of complex traits.

Adenoma↗
PubMed2006

A protocol for high-throughput phenotyping, suitable for quantitative trait analysis in mice.

Whole-genome genetic association studies in outbred mouse populations represent a novel approach to identifying the molecular basis of naturally occurring genetic variants, the major source of quantitative variation between inbred strains of mice. Measuring multiple phenotypes in parallel on each mouse would make the approach cost effective, but protocols for phenotyping on a large enough scale have not been developed. In this article we describe the development and deployment of a protocol to collect measures on three models of human disease (anxiety, type II diabetes, and asthma) as well as measures of mouse blood biochemistry, immunology, and hematology. We report that the protocol delivers highly significant differences among the eight inbred strains (A/J, AKR/J, BALBc/J, CBA/J, C3H/HeJ, C57BL/6 J, DBA/2 J, and LP/J), the progenitors of a genetically heterogeneous stock (HS) of mice. We report the successful collection of multiple phenotypes from 2000 outbred HS animals. The phenotypes measured in the protocol form the basis of a large-scale investigation into the genetic basis of complex traits in mice designed to examine interactions between genes and between genes and environment, as well as the main effects of genetic variants on phenotypes.

Animals↗
PubMed2006

Genome wide gene expression studies in mood disorders.

Microarrays offer the possibility of screening in parallel virtually all genes expressed in a given tissue or to study the molecular signature associated with available treatments. As such, this technology has been increasingly used to investigate multifactorial and polygenic complex traits such as psychiatric disorders, in particular, schizophrenia and mood disorders. This review focuses on microarray studies investigating mood disorders. Study designs, methodologic approaches and limitations, subsequent follow-up strategies, and confirmation of results are discussed. Despite the apparent disparate and not always concordant results, it appears evident that this technology is a powerful and inevitable approach for the study of mood disorders, especially when phenotype-specific confounders are properly accounted for. Thus, alterations of mitochondrial, oligodendrocyte, and myelin related genes in bipolar disorder, of signaling and olidendroglial related genes in depression, and of GABA-glutamate related genes in depression and suicide have been observed and have confirmed new avenues for the study and the treatment of these complex disorders.

Gene Expression Profiling↗
PubMed2004

Sex- and lineage-specific inheritance of depression-like behavior in the rat.

The Wistar-Kyoto (WKY) rat exhibits physiological and behavioral similarities to endophenotypes of human depression. In the forced swim test (FST), a well-characterized antidepressant-reversible test for behavioral despair in rodents, WKYs express characteristics of behavioral despair; increased immobility, and decreased climbing. To map genetic loci linked to behavior in the FST, we conducted a quantitative trait loci (QTL) analysis of the segregating F2 generation of a WKY x Fisher 344 (F344) reciprocal intercross. Using linear-model-based genome scans to include covariate (sex or lineage)-by-QTL interaction effects, four significant QTL influencing climbing behavior were identified. In addition, we identified three, seven, and two suggestive QTL for climbing, immobility, and swimming, respectively. One of these loci was pleiotropic, affecting both immobility and climbing. As found in human linkage studies, several of these QTL showed sex- and/or lineage-dependent effects. A simultaneous search strategy identified three epistatic locus pairs for climbing. Multiple regression analysis was employed to characterize the joint contributions of these QTL and to clarify the sex- and lineage-dependent effects. As expected for complex traits, FST behavior is influenced by multiple QTL of small effect, each contributing 5%-10%, accounting for a total 10%-30% of the phenotypic variance. A number of loci mapped in this study share overlapping candidate regions with previously identified emotionality QTL in mice as well as with susceptibility loci recognized by linkage or genome scan analyses for major depression or bipolar disorder in humans. The presence of these loci across species suggests that these QTL may represent universal genetic factors contributing to mood disorders.

Animals↗