Mapping the genetic architecture of complex traits in experimental populations

SUMMARY: Understanding how interactions among set of genes affect diverse phenotypes is having a greater impact on biomedical research, agriculture and evolutionary biology. Mapping and characterizing the isolated effects of single quantitative trait locus (QTL) is a first step, but we also need to assemble networks of QTLs and define non-additive interactions (epistasis) together with a host of potential environmental modulators. In this article, we present a full-QTL model with which to explore the genetic architecture of complex trait in multiple environments. Our model includes the effects of multiple QTLs, epistasis, QTL-by-environment interactions and epistasis-by-environment interactions. A new mapping strategy, including marker interval selection, detection of marker interval interactions and genome scans, is used to evaluate putative locations of multiple QTLs and their interactions. All the mapping procedures are performed in the framework of mixed linear model that are flexible to model environmental factors regardless of fix or random effects being assumed. An F-statistic based on Henderson method III is used for hypothesis tests. This method is less computationally greedy than corresponding likelihood ratio test. In each of the mapping procedures, permutation testing is exploited to control for genome-wide false positive rate, and model selection is used to reduce ghost peaks in F-statistic profile. Parameters of the full-QTL model are estimated using a Bayesian method via Gibbs sampling. Monte Carlo simulations help define the reliability and efficiency of the method. Two real-world phenotypes (BXD mouse olfactory bulb weight data and rice yield data) are used as exemplars to demonstrate our methods. AVAILABILITY: A software package is freely available at http://ibi.zju.edu.cn/software/qtlnetwork     

Mapping interspecific genetic architecture in a host-parasite interaction system

Under a hypothesis that the host-parasite interaction system is governed by genome-for-genome interaction, we propose a genetic model that integrates genetic information from both the host and parasite genomes. The model can be used for mapping quantitative trait loci (QTL) conferring the interaction between host and parasite and detecting interactions among these QTL. A one-dimensional genome-scan strategy is used to map QTL in both the host and parasite genomes simultaneously conditioned on selected pairs of markers controlling the background genetic variation; a two-dimensional genome-scan procedure is conducted to search for epistasis within the host and parasite genomes and interspecific QTL-by-QTL interactions between the host and parasite genomes. A permutation test is adopted to calculate the empirical threshold to control the experimentwise false-positive rate of detected QTL and QTL interactions. Monte Carlo simulations were conducted to examine the reliability and the efficiency of the proposed models and methods. Simulation results illustrated that our methods could provide reasonable estimates of the parameters and adequate powers for detecting QTL and QTL-by-QTL interactions.     

Mapping human genetic ancestry

The human genome is a mosaic with respect to its evolutionary history. Based on a phylogenetic analysis of 23,210 DNA sequence alignments from human, chimpanzee, gorilla, orangutan, and rhesus, we present a map of human genetic ancestry. For about 23% of our genome, we share no immediate genetic ancestry with our closest living relative, the chimpanzee. This encompasses genes and exons to the same extent as intergenic regions. We conclude that about 1/3 of our genes started to evolve as human-specific lineages before the differentiation of human, chimps, and gorillas took place. This explains recurrent findings of very old human-specific morphological traits in the fossils record, which predate the recent emergence of the human species about 5-6 MYA. Furthermore, the sorting of such ancestral phenotypic polymorphisms in subsequent speciation events provides a parsimonious explanation why evolutionary derived characteristics are shared among species that are not each other's closest relatives.     

Mapping the gene expression universe

Methods to globally survey gene expression provide valuable insights into gene function during development. In particular, comprehensive in situ hybridization studies have demonstrated that gene expression patterns are extraordinarily diverse and new imaging techniques have been introduced to capture these patterns with higher resolution at the tissue, cellular, and subcellular levels. The analysis of massive image databases can be greatly facilitated by computer vision techniques once annotated image sets reach the crucial mass sufficient to train the computer in pattern recognition. Ultimately, genome-wide atlases of gene expression during development will record gene activity in living animals with at least cellular resolution and in the context of morphogenetic events. These emerging datasets will lead to great advances in the field of comparative genomics and revolutionize our ability to decipher and model developmental processes for a variety of organisms.     

Defining the genetic architecture of human developmental language impairment

Language is a uniquely human trait, which poses limitations on animal models for discovering biological substrates and pathways. Despite this challenge, rapidly developing biotechnology in the field of genomics has made human genetics studies a viable alternative route for defining the molecular neuroscience of human language. This is accomplished by studying families that transmit both normal and disordered language across generations. The language disorder reviewed here is specific language impairment (SLI), a developmental deficiency in language acquisition despite adequate opportunity, normal intelligence, and without any apparent neurological etiology. Here, we describe disease gene discovery paradigms as applied to SLI families and review the progress this field has made. After review the evidence that genetic factors influence SLI, we discuss methods and findings from scans of the human chromosomes, including the main replicated regions on chromosomes 13, 16 and 19 and two identified genes, ATP2C2 and CMIP that appear to account for the language variation on chromosome 16. Additional work has been done on candidate genes, i.e., genes chosen a priori and not through a genome scanning studies, including several studies of CNTNAP2 and some recent work implicating BDNF as a gene x gene interaction partner of genetic variation on chromosome 13 that influences language. These recent developments may allow for better use of post-mortem human brain samples functional studies and animal models for circumscribed language subcomponents. In the future, the identification of genetic variation associated with language phenotypes will provide the molecular pathways to understanding human language.     

IGF-1 modulates gene expression of proteins involved in inflammation,cytoskeleton, and liver architecture

Even though the liver synthesizes most of circulating IGF-1, it lacks its receptor under physiological conditions. However, according to previous studies, a damaged liver expresses the receptor. For this reason, herein, we examine hepatic histology and expression of genes encoding proteins of the cytoskeleton, extracellular matrix, and cell-cell molecules and inflammation-related proteins. A partial IGF-1 deficiency murine model was used to investigate IGF-1’s effects on liver by comparing wild-type controls, heterozygous igf1^+/?, and heterozygous mice treated with IGF-1 for 10 days. Histology, microarray for mRNA gene expression, RT-qPCR, and lipid peroxidation were assessed. Microarray analyses revealed significant underexpression of igf1 in heterozygous mice compared to control mice, restoring normal liver expression after treatment, which then normalized its circulating levels. IGF-1 receptor mRNA was overexpressed in Hz mice liver, while treated mice displayed a similar expression to that of the controls. Heterozygous mice showed overexpression of several genes encoding proteins related to inflammatory and acute-phase proteins and underexpression or overexpression of genes which coded for extracellular matrix, cytoskeleton, and cell junction components. Histology revealed an altered hepatic architecture. In addition, liver oxidative damage was found increased in the heterozygous group. The mere IGF-1 partial deficiency is associated with relevant alterations of the hepatic architecture and expression of genes involved in cytoskeleton, hepatocyte polarity, cell junctions, and extracellular matrix proteins. Moreover, it induces hepatic expression of the IGF-1 receptor and elevated acute-phase and inflammation mediators, which all resulted in liver oxidative damage.     

Robust regulatory architecture of pan-neuronal gene expression

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A powerful method to integrate genotype and gene expression data for dissecting the genetic architecture of a disease

To decipher the genetic architecture of human disease, various types of omics data are generated. Two common omics data are genotypes and gene expression. Often genotype data for a large number of individuals and gene expression data for a few individuals are generated due to biological and technical reasons, leading to unequal sample sizes for different omics data. Unavailability of standard statistical procedure for integrating such datasets motivates us to propose a two-step multi-locus association method using latent variables. Our method is powerful than single/separate omics data analysis and it unravels comprehensively deep-seated signals through a single statistical model. Extensive simulation confirms that it is robust to various genetic models as its power increases with sample size and number of associated loci. It provides p-values very fast. Application to real dataset on psoriasis identifies 17 novel SNPs, functionally related to psoriasis-associated genes, at much smaller sample size than standard GWAS.     

Sex-specific genetic architecture of human fatness in Chinese: the SAPPHIRe Study

To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex–genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia–Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype–sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.     

Genome-wide gene expression profiling of microgravity effect on human liver cells

Human exposure to microgravity is considered the major environmental factor of space flight that affects cells and tissues causing adverse effects to human health. Ground-based gravity-simulation experiments at the cellular and molecular levels have gained some insight into the underlying molecular and cellular alterations induced by microgravity. However, systematic study and detailed molecular mechanisms of the adverse effect of microgravity on living cells are still lacking. The main objective of this study was to apply DNA microarray technology in time-course experiments for genome-wide search of genes whose expression are altered by microgravity, as part of the effort in the identification of major space genes. In this study, we analyzed global gene expression profiles for a human liver cell line exposed to a ground-based modeled microgravity system for 1, 3, and 4 days using the rotary cell culture system (RCCS) and the Agilent 22k human oligo DNA microarrays. We have found that 139 genes' mRNA levels were significantly (P < or = 0.01) altered by the microgravity exposures. Some of these identified genes were further verified by Northern analysis.     

The genetic architecture of selection at the human dopamine receptor D4 (DRD4) gene locus

Associations of the seven-repeat (7R) allele of the human dopamine receptor D4 (DRD4) gene with both the personality trait of novelty seeking and attention deficit/hyperactivity disorder have been reported. Recently, on the basis of the unusual DNA sequence organization of the DRD4 7R 48-bp tandem repeat (VNTR), we proposed that the 7R allele originated as a rare mutational event that increased to high frequency by positive selection. We now have resequenced the entire DRD4 locus from 103 individuals homozygous for 2R, 4R, or 7R variants of the VNTR, a method developed to directly estimate haplotype diversity. DNA from individuals of African, European, Asian, North and South American, and Pacific Island ancestry were used. 4R/4R homozygotes exhibit little linkage disequilibrium (LD) over the region examined, with more polymorphisms observed in DNA samples from African individuals. In contrast, the evidence for strong LD surrounding the 7R allele is dramatic, with all 7R/7R individuals (including those from Africa) exhibiting the same alleles at most polymorphic sites. By intra-allelic comparison at 18 high-heterozygosity sites spanning the locus, we estimate that the 7R allele arose prior to the upper Paleolithic era (approximately 40000-50000 years ago). Further, the pattern of recombination at these polymorphic sites is the pattern expected for selection acting at the 7R VNTR itself, rather than at an adjacent site. We propose a model for selection at the DRD4 locus consistent with these observed LD patterns and with the known biochemical and physiological differences between receptor variants.