Infection and Inflammation in Schizophrenia and Bipolar Disorder: A Genome Wide Study for Interactions with Genetic Variation

Inflammation and maternal or fetal infections have been suggested as risk factors for schizophrenia (SZ) and bipolar disorder (BP). It is likely that such environmental effects are contingent on genetic background. Here, in a genome-wide approach, we test the hypothesis that such exposures increase the risk for SZ and BP and that the increase is dependent on genetic variants. We use genome-wide genotype data, plasma IgG antibody measurements against Toxoplasma gondii, Herpes simplex virus type 1, Cytomegalovirus, Human Herpes Virus 6 and the food antigen gliadin as well as measurements of C-reactive protein (CRP), a peripheral marker of inflammation. The subjects are SZ cases, BP cases, parents of cases and screened controls. We look for higher levels of our immunity/infection variables and interactions between them and common genetic variation genome-wide. We find many of the antibody measurements higher in both disorders. While individual tests do not withstand correction for multiple comparisons, the number of nominally significant tests and the comparisons showing the expected direction are in significant excess (permutation p=0.019 and 0.004 respectively). We also find CRP levels highly elevated in SZ, BP and the mothers of BP cases, in agreement with existing literature, but possibly confounded by our inability to correct for smoking or body mass index. In our genome-wide interaction analysis no signal reached genome-wide significance, yet many plausible candidate genes emerged. In a hypothesis driven test, we found multiple interactions among SZ-associated SNPs in the HLA region on chromosome 6 and replicated an interaction between CMV infection and genotypes near the CTNNA3 gene reported by a recent GWAS. Our results support that inflammatory processes and infection may modify the risk for psychosis and suggest that the genotype at SZ-associated HLA loci modifies the effect of these variables on the risk to develop SZ.     

山羊基因组与遗传变异图谱研究进展

高通量测序技术和生物信息学的发展极大的促进了山羊分子生物学研究。山羊参考基因组的不断完善以及基因组重测序技术的应用,在全基因组水平上发现了大量的遗传变异信息(SNP、Indel和CNV),丰富了山羊分子群体遗传学研究利用的分子标记。综述了山羊参考基因组组装和全基因组变异图谱的构建及其在山羊上的研究进展,以期为进一步利用分子遗传标记进行山羊的各种性状的遗传基础研究和遗传资源保护利用提供科学依据和参考。     

The Expression and Regulation of Chemerin in the Epidermis

Chemerin is a protein ligand for the G protein-coupled receptor CMKLR1 and also binds to two atypical heptahelical receptors, CCRL2 and GPR1. Chemerin is a leukocyte attractant, adipokine, and antimicrobial protein. Although chemerin was initially identified as a highly expressed gene in healthy skin keratinocytes that was downregulated during psoriasis, the regulation of chemerin and its receptors in the skin by specific cytokines and microbial factors remains unexplored. Here we show that chemerin, CMKLR1, CCRL2 and GPR1 are expressed in human and mouse epidermis, suggesting that this tissue may be both a source and target for chemerin mediated effects. In human skin cultures, chemerin is significantly downregulated by IL-17 and IL-22, key cytokines implicated in psoriasis, whereas it is upregulated by acute phase cytokines oncostatin M and IL-1β. Moreover, we show that human keratinocytes in vitro and mouse skin in vivo respond to specific microbial signals to regulate expression levels of chemerin and its receptors. Furthermore, in a cutaneous infection model, chemerin is required for maximal bactericidal effects in vivo. Together, our findings reveal previously uncharacterized regulators of chemerin expression in skin and identify a physiologic role for chemerin in skin barrier defense against microbial pathogens.     

GEMINI: Integrative Exploration of Genetic Variation and Genome Annotations

Modern DNA sequencing technologies enable geneticists to rapidly identify genetic variation among many human genomes. However, isolating the minority of variants underlying disease remains an important, yet formidable challenge for medical genetics. We have developed GEMINI (GEnome MINIng), a flexible software package for exploring all forms of human genetic variation. Unlike existing tools, GEMINI integrates genetic variation with a diverse and adaptable set of genome annotations (e.g., dbSNP, ENCODE, UCSC, ClinVar, KEGG) into a unified database to facilitate interpretation and data exploration. Whereas other methods provide an inflexible set of variant filters or prioritization methods, GEMINI allows researchers to compose complex queries based on sample genotypes, inheritance patterns, and both pre-installed and custom genome annotations. GEMINI also provides methods for ad hoc queries and data exploration, a simple programming interface for custom analyses that leverage the underlying database, and both command line and graphical tools for common analyses. We demonstrate GEMINI''s utility for exploring variation in personal genomes and family based genetic studies, and illustrate its ability to scale to studies involving thousands of human samples. GEMINI is designed for reproducibility and flexibility and our goal is to provide researchers with a standard framework for medical genomics.This is a PLOS Computational Biology Software Article.     

脂肪因子Chemerin与妊娠相关疾病的关系展望

<正>1 Introduction Recurrent pregnant loss,gestational diabetes,premature delivery,intrauterine growth restriction,preeclampsia and other pregnancy-related complications have severe impact on the fetus development and the health and life quality of the mother.These diseases are also causes of unstability and huge economic burden for the family as well as the     

A Genome Wide Meta-Analysis Study for Identification of Common Variation Associated with Breast Cancer Prognosis

Objective

Genome wide association studies (GWAs) of breast cancer mortality have identified few potential associations. The concordance between these studies is unclear. In this study, we used a meta-analysis of two prognostic GWAs and a replication cohort to identify the strongest associations and to evaluate the loci suggested in previous studies. We attempt to identify those SNPs which could impact overall survival irrespective of the age of onset.

Methods

To facilitate the meta-analysis and to refine the association signals, SNPs were imputed using data from the 1000 genomes project. Cox-proportional hazard models were used to estimate hazard ratios (HR) in 536 patients from the POSH cohort (Prospective study of Outcomes in Sporadic versus Hereditary breast cancer) and 805 patients from the HEBCS cohort (Helsinki Breast Cancer Study). These hazard ratios were combined using a Mantel-Haenszel fixed effects meta-analysis and a p-value threshold of 5×10⁻⁸ was used to determine significance. Replication was performed in 1523 additional patients from the POSH study.

Results

Although no SNPs achieved genome wide significance, three SNPs have significant association in the replication cohort and combined p-values less than 5.6×10⁻⁶. These SNPs are; rs421379 which is 556 kb upstream of ARRDC3 (HR = 1.49, 95% confidence interval (CI) = 1.27–1.75, P = 1.1×10⁻⁶), rs12358475 which is between ECHDC3 and PROSER2 (HR = 0.75, CI = 0.67–0.85, P = 1.8×10⁻⁶), and rs1728400 which is between LINC00917 and FOXF1.

Conclusions

In a genome wide meta-analysis of two independent cohorts from UK and Finland, we identified potential associations at three distinct loci. Phenotypic heterogeneity and relatively small sample sizes may explain the lack of genome wide significant findings. However, the replication at three SNPs in the validation cohort shows promise for future studies in larger cohorts. We did not find strong evidence for concordance between the few associations highlighted by previous GWAs of breast cancer survival and this study.     

Genome Sequencing Highlights the Dynamic Early History of Dogs

To identify genetic changes underlying dog domestication and reconstruct their early evolutionary history, we generated high-quality genome sequences from three gray wolves, one from each of the three putative centers of dog domestication, two basal dog lineages (Basenji and Dingo) and a golden jackal as an outgroup. Analysis of these sequences supports a demographic model in which dogs and wolves diverged through a dynamic process involving population bottlenecks in both lineages and post-divergence gene flow. In dogs, the domestication bottleneck involved at least a 16-fold reduction in population size, a much more severe bottleneck than estimated previously. A sharp bottleneck in wolves occurred soon after their divergence from dogs, implying that the pool of diversity from which dogs arose was substantially larger than represented by modern wolf populations. We narrow the plausible range for the date of initial dog domestication to an interval spanning 11–16 thousand years ago, predating the rise of agriculture. In light of this finding, we expand upon previous work regarding the increase in copy number of the amylase gene (AMY2B) in dogs, which is believed to have aided digestion of starch in agricultural refuse. We find standing variation for amylase copy number variation in wolves and little or no copy number increase in the Dingo and Husky lineages. In conjunction with the estimated timing of dog origins, these results provide additional support to archaeological finds, suggesting the earliest dogs arose alongside hunter-gathers rather than agriculturists. Regarding the geographic origin of dogs, we find that, surprisingly, none of the extant wolf lineages from putative domestication centers is more closely related to dogs, and, instead, the sampled wolves form a sister monophyletic clade. This result, in combination with dog-wolf admixture during the process of domestication, suggests that a re-evaluation of past hypotheses regarding dog origins is necessary.     

Copy Number Variation in the Horse Genome

We constructed a 400K WG tiling oligoarray for the horse and applied it for the discovery of copy number variations (CNVs) in 38 normal horses of 16 diverse breeds, and the Przewalski horse. Probes on the array represented 18,763 autosomal and X-linked genes, and intergenic, sub-telomeric and chrY sequences. We identified 258 CNV regions (CNVRs) across all autosomes, chrX and chrUn, but not in chrY. CNVs comprised 1.3% of the horse genome with chr12 being most enriched. American Miniature horses had the highest and American Quarter Horses the lowest number of CNVs in relation to Thoroughbred reference. The Przewalski horse was similar to native ponies and draft breeds. The majority of CNVRs involved genes, while 20% were located in intergenic regions. Similar to previous studies in horses and other mammals, molecular functions of CNV-associated genes were predominantly in sensory perception, immunity and reproduction. The findings were integrated with previous studies to generate a composite genome-wide dataset of 1476 CNVRs. Of these, 301 CNVRs were shared between studies, while 1174 were novel and require further validation. Integrated data revealed that to date, 41 out of over 400 breeds of the domestic horse have been analyzed for CNVs, of which 11 new breeds were added in this study. Finally, the composite CNV dataset was applied in a pilot study for the discovery of CNVs in 6 horses with XY disorders of sexual development. A homozygous deletion involving AKR1C gene cluster in chr29 in two affected horses was considered possibly causative because of the known role of AKR1C genes in testicular androgen synthesis and sexual development. While the findings improve and integrate the knowledge of CNVs in horses, they also show that for effective discovery of variants of biomedical importance, more breeds and individuals need to be analyzed using comparable methodological approaches.     

Detection of Marker-Free Precision Genome Editing and Genetic Variation through the Capture of Genomic Signatures

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A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation

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The Impact of Phenotypic and Genetic Heterogeneity on Results of Genome Wide Association Studies of Complex Diseases

Phenotypic misclassification (between cases) has been shown to reduce the power to detect association in genetic studies. However, it is conceivable that complex traits are heterogeneous with respect to individual genetic susceptibility and disease pathophysiology, and that the effect of heterogeneity has a larger magnitude than the effect of phenotyping errors. Although an intuitively clear concept, the effect of heterogeneity on genetic studies of common diseases has received little attention. Here we investigate the impact of phenotypic and genetic heterogeneity on the statistical power of genome wide association studies (GWAS). We first performed a study of simulated genotypic and phenotypic data. Next, we analyzed the Wellcome Trust Case-Control Consortium (WTCCC) data for diabetes mellitus (DM) type 1 (T1D) and type 2 (T2D), using varying proportions of each type of diabetes in order to examine the impact of heterogeneity on the strength and statistical significance of association previously found in the WTCCC data. In both simulated and real data, heterogeneity (presence of “non-cases”) reduced the statistical power to detect genetic association and greatly decreased the estimates of risk attributed to genetic variation. This finding was also supported by the analysis of loci validated in subsequent large-scale meta-analyses. For example, heterogeneity of 50% increases the required sample size by approximately three times. These results suggest that accurate phenotype delineation may be more important for detecting true genetic associations than increase in sample size.     

Population Genetic Consequences of the Allee Effect and the Role of Offspring-Number Variation

A strong demographic Allee effect in which the expected population growth rate is negative below a certain critical population size can cause high extinction probabilities in small introduced populations. But many species are repeatedly introduced to the same location and eventually one population may overcome the Allee effect by chance. With the help of stochastic models, we investigate how much genetic diversity such successful populations harbor on average and how this depends on offspring-number variation, an important source of stochastic variability in population size. We find that with increasing variability, the Allee effect increasingly promotes genetic diversity in successful populations. Successful Allee-effect populations with highly variable population dynamics escape rapidly from the region of small population sizes and do not linger around the critical population size. Therefore, they are exposed to relatively little genetic drift. It is also conceivable, however, that an Allee effect itself leads to an increase in offspring-number variation. In this case, successful populations with an Allee effect can exhibit less genetic diversity despite growing faster at small population sizes. Unlike in many classical population genetics models, the role of offspring-number variation for the population genetic consequences of the Allee effect cannot be accounted for by an effective-population-size correction. Thus, our results highlight the importance of detailed biological knowledge, in this case on the probability distribution of family sizes, when predicting the evolutionary potential of newly founded populations or when using genetic data to reconstruct their demographic history.     

Elusive Copy Number Variation in the Mouse Genome

Background

Array comparative genomic hybridization (aCGH) to detect copy number variants (CNVs) in mammalian genomes has led to a growing awareness of the potential importance of this category of sequence variation as a cause of phenotypic variation. Yet there are large discrepancies between studies, so that the extent of the genome affected by CNVs is unknown. We combined molecular and aCGH analyses of CNVs in inbred mouse strains to investigate this question.

Principal Findings

Using a 2.1 million probe array we identified 1,477 deletions and 499 gains in 7 inbred mouse strains. Molecular characterization indicated that approximately one third of the CNVs detected by the array were false positives and we estimate the false negative rate to be more than 50%. We show that low concordance between studies is largely due to the molecular nature of CNVs, many of which consist of a series of smaller deletions and gains interspersed by regions where the DNA copy number is normal.

Conclusions

Our results indicate that CNVs detected by arrays may be the coincidental co-localization of smaller CNVs, whose presence is more likely to perturb an aCGH hybridization profile than the effect of an isolated, small, copy number alteration. Our findings help explain the hitherto unexplored discrepancies between array-based studies of copy number variation in the mouse genome.     

Evaluating Quantitative Variation in the Genome of ZEA MAYS

Genomic diversity within the species Zea mays has been examined by measuring the variation in the repetitive component of the nuclear genome among North American inbred lines and varieties. This was done by preparing a set of clones of repetitive maize sequences that differ in function, molecular arrangement and multiplicity and then using these as probes for quantitative hybridization to DNA from various maize genotypes. The comparison showed that the majority of repeated sequences are markedly variable in copy number among the ten maize strains tested.The clone sample contained the rDNA and 5S genes, the major repeat of the chromosome knobs, sequences functioning as origins of DNA replication in yeast (ARS sequences) and randomly cloned sequences of unknown function and chromosomal location. The sequences ranged in reiteration frequency from 200 to greater than 10(5) copies and included both tandemly arrayed and dispersed repeats. The copy numbers were measured by hybridizing labeled cloned sequences to aliquots of high molecular weight genomic DNA that were applied to nitrocellulose filters through a slotted template (slot blotting). The hybridization signal on an autoradiogram occurred in a narrow band that could be scored reliably with a densitometer. This provided a rapid method of determining the abundance of particular repeated sequences in individual plants and plant populations. Using this technique, we found that the copy number of repeated sequences of all types generally varied among the strains by two- to threefold, although at least one sequence showed no detectable variation. In contrast to the variability found between strains, individuals within an inbred line or variety were found to be indistinguishable in terms of specific sequence multiplicity. Each genotype has a different pattern of copy numbers for the set of repeated sequence clones, and this pattern is characteristic of all individuals of a particular genotype. The data also show that the copy number of each sequence varies independently. No strains had uniformly high or low copy numbers for the entire set of probes.