Toxoplasma effectors targeting host signaling and transcription

Early electron microscopy studies revealed the elaborate cellular features that define the unique adaptations of apicomplexan parasites. Among these were bulbous rhoptry (ROP) organelles and small, dense granules (GRAs), both of which are secreted during invasion of host cells. These early morphological studies were followed by the exploration of the cellular contents of these secretory organelles, revealing them to be comprised of highly divergent protein families with few conserved domains or predicted functions. In parallel, studies on host-pathogen interactions identified many host signaling pathways that were mysteriously altered by infection. It was only with the advent of forward and reverse genetic strategies that the connections between individual parasite effectors and the specific host pathways that they targeted finally became clear. The current repertoire of parasite effectors includes ROP kinases and pseudokinases that are secreted during invasion and that block host immune pathways. Similarly, many secretory GRA proteins alter host gene expression by activating host transcription factors, through modification of chromatin, or by inducing small noncoding RNAs. These effectors highlight novel mechanisms by whichhas learned to harness host signaling to favor intracellular survival and will guide future studies designed to uncover the additional complexity of this intricate host-pathogen interaction

Genetic Admixture and Population Substructure in Guanacaste Costa Rica

The population of Costa Rica (CR) represents an admixture of major continental populations. An investigation of the CR population structure would provide an important foundation for mapping genetic variants underlying common diseases and traits. We conducted an analysis of 1,301 women from the Guanacaste region of CR using 27,904 single nucleotide polymorphisms (SNPs) genotyped on a custom Illumina InfiniumII iSelect chip. The program STRUCTURE was used to compare the CR Guanacaste sample with four continental reference samples, including HapMap Europeans (CEU), East Asians (JPT+CHB), West African Yoruba (YRI), as well as Native Americans (NA) from the Illumina iControl database. Our results show that the CR Guanacaste sample comprises a three-way admixture estimated to be 43% European, 38% Native American and 15% West African. An estimated 4% residual Asian ancestry may be within the error range. Results from principal components analysis reveal a correlation between genetic and geographic distance. The magnitude of linkage disequilibrium (LD) measured by the number of tagging SNPs required to cover the same region in the genome in the CR Guanacaste sample appeared to be weaker than that observed in CEU, JPT+CHB and NA reference samples but stronger than that of the HapMap YRI sample. Based on the clustering pattern observed in both STRUCTURE and principal components analysis, two subpopulations were identified that differ by approximately 20% in LD block size averaged over all LD blocks identified by Haploview. We also show in a simulated association study conducted within the two subpopulations, that the failure to account for population stratification (PS) could lead to a noticeable inflation in the false positive rate. However, we further demonstrate that existing PS adjustment approaches can reduce the inflation to an acceptable level for gene discovery

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Population Substructure and Control Selection in Genome-Wide Association Studies

Determination of the relevance of both demanding classical epidemiologic criteria for control selection and robust handling of population stratification (PS) represents a major challenge in the design and analysis of genome-wide association studies (GWAS). Empirical data from two GWAS in European Americans of the Cancer Genetic Markers of Susceptibility (CGEMS) project were used to evaluate the impact of PS in studies with different control selection strategies. In each of the two original case-control studies nested in corresponding prospective cohorts, a minor confounding effect due to PS (inflation factor λ of 1.025 and 1.005) was observed. In contrast, when the control groups were exchanged to mimic a cost-effective but theoretically less desirable control selection strategy, the confounding effects were larger (λ of 1.090 and 1.062). A panel of 12,898 autosomal SNPs common to both the Illumina and Affymetrix commercial platforms and with low local background linkage disequilibrium (pair-wise r2<0.004) was selected to infer population substructure with principal component analysis. A novel permutation procedure was developed for the correction of PS that identified a smaller set of principal components and achieved a better control of type I error (to λ of 1.032 and 1.006, respectively) than currently used methods. The overlap between sets of SNPs in the bottom 5% of p-values based on the new test and the test without PS correction was about 80%, with the majority of discordant SNPs having both ranks close to the threshold. Thus, for the CGEMS GWAS of prostate and breast cancer conducted in European Americans, PS does not appear to be a major problem in well-designed studies. A study using suboptimal controls can have acceptable type I error when an effective strategy for the correction of PS is employed

Forward-time simulation of realistic samples for genome-wide association studies

<p>Abstract</p> <p>Background</p> <p>Forward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.</p> <p>Results</p> <p>Using a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.</p> <p>Conclusions</p> <p>Our algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.</p

Genetic Ancestry, Social Classification, and Racial Inequalities in Blood Pressure in Southeastern Puerto Rico

The role of race in human genetics and biomedical research is among the most contested issues in science. Much debate centers on the relative importance of genetic versus sociocultural factors in explaining racial inequalities in health. However, few studies integrate genetic and sociocultural data to test competing explanations directly.We draw on ethnographic, epidemiologic, and genetic data collected in Southeastern Puerto Rico to isolate two distinct variables for which race is often used as a proxy: genetic ancestry versus social classification. We show that color, an aspect of social classification based on the culturally defined meaning of race in Puerto Rico, better predicts blood pressure than does a genetic-based estimate of continental ancestry. We also find that incorporating sociocultural variables reveals a new and significant association between a candidate gene polymorphism for hypertension (alpha(2C) adrenergic receptor deletion) and blood pressure.This study addresses the recognized need to measure both genetic and sociocultural factors in research on racial inequalities in health. Our preliminary results provide the most direct evidence to date that previously reported associations between genetic ancestry and health may be attributable to sociocultural factors related to race and racism, rather than to functional genetic differences between racially defined groups. Our results also imply that including sociocultural variables in future research may improve our ability to detect significant allele-phenotype associations. Thus, measuring sociocultural factors related to race may both empower future genetic association studies and help to clarify the biological consequences of social inequalities

Genetic Mapping of Social Interaction Behavior in B6/MSM Consomic Mouse Strains

Genetic studies are indispensable for understanding the mechanisms by which individuals develop differences in social behavior. We report genetic mapping of social interaction behavior using inter-subspecific consomic strains established from MSM/Ms (MSM) and C57BL/6J (B6) mice. Two animals of the same strain and sex, aged 10 weeks, were introduced into a novel open-field for 10 min. Social contact was detected by an automated system when the distance between the centers of the two animals became less than ~12 cm. In addition, detailed behavioral observations were made of the males. The wild-derived mouse strain MSM showed significantly longer social contact as compared to B6. Analysis of the consomic panel identified two chromosomes (Chr 6 and Chr 17) with quantitative trait loci (QTL) responsible for lengthened social contact in MSM mice and two chromosomes (Chr 9 and Chr X) with QTL that inhibited social contact. Detailed behavioral analysis of males identified four additional chromosomes associated with social interaction behavior. B6 mice that contained Chr 13 from MSM showed more genital grooming and following than the parental B6 strain, whereas the presence of Chr 8 and Chr 12 from MSM resulted in a reduction of those behaviors. Longer social sniffing was observed in Chr 4 consomic strain than in B6 mice. Although the frequency was low, aggressive behavior was observed in a few pairs from consomic strains for Chrs 4, 13, 15 and 17, as well as from MSM. The social interaction test has been used as a model to measure anxiety, but genetic correlation analysis suggested that social interaction involves different aspects of anxiety than are measured by open-field test

Comparison of measures of marker informativeness for ancestry and admixture mapping

<p>Abstract</p> <p>Background</p> <p>Admixture mapping is a powerful gene mapping approach for an admixed population formed from ancestral populations with different allele frequencies. The power of this method relies on the ability of ancestry informative markers (AIMs) to infer ancestry along the chromosomes of admixed individuals. In this study, more than one million SNPs from HapMap databases and simulated data have been interrogated in admixed populations using various measures of ancestry informativeness: Fisher Information Content (FIC), Shannon Information Content (SIC), F statistics (F_ST), Informativeness for Assignment Measure (I_n), and the Absolute Allele Frequency Differences (delta, δ). The objectives are to compare these measures of informativeness to select SNP markers for ancestry inference, and to determine the accuracy of AIM panels selected by each measure in estimating the contributions of the ancestors to the admixed population.</p> <p>Results</p> <p>F_STand I_nhad the highest Spearman correlation and the best agreement as measured by Kappa statistics based on deciles. Although the different measures of marker informativeness performed comparably well, analyses based on the top 1 to 10% ranked informative markers of simulated data showed that I_nwas better in estimating ancestry for an admixed population.</p> <p>Conclusions</p> <p>Although millions of SNPs have been identified, only a small subset needs to be genotyped in order to accurately predict ancestry with a minimal error rate in a cost-effective manner. In this article, we compared various methods for selecting ancestry informative SNPs using simulations as well as SNP genotype data from samples of admixed populations and showed that the I_nmeasure estimates ancestry proportion (in an admixed population) with lower bias and mean square error.</p

ISL1 Directly Regulates FGF10 Transcription during Human Cardiac Outflow Formation

The LIM homeodomain gene Islet-1 (ISL1) encodes a transcription factor that has been associated with the multipotency of human cardiac progenitors, and in mice enables the correct deployment of second heart field (SHF) cells to become the myocardium of atria, right ventricle and outflow tract. Other markers have been identified that characterize subdomains of the SHF, such as the fibroblast growth factor Fgf10 in its anterior region. While functional evidence of its essential contribution has been demonstrated in many vertebrate species, SHF expression of Isl1 has been shown in only some models. We examined the relationship between human ISL1 and FGF10 within the embryonic time window during which the linear heart tube remodels into four chambers. ISL1 transcription demarcated an anatomical region supporting the conserved existence of a SHF in humans, and transcription factors of the GATA family were co-expressed therein. In conjunction, we identified a novel enhancer containing a highly conserved ISL1 consensus binding site within the FGF10 first intron. ChIP and EMSA demonstrated its direct occupation by ISL1. Transcription mediated by ISL1 from this FGF10 intronic element was enhanced by the presence of GATA4 and TBX20 cardiac transcription factors. Finally, transgenic mice confirmed that endogenous factors bound the human FGF10 intronic enhancer to drive reporter expression in the developing cardiac outflow tract. These findings highlight the interest of examining developmental regulatory networks directly in human tissues, when possible, to assess candidate non-coding regions that may be responsible for congenital malformations

Dissecting the Within-Africa Ancestry of Populations of African Descent in the Americas

The ancestry of African-descended Americans is known to be drawn from three distinct populations: African, European, and Native American. While many studies consider this continental admixture, few account for the genetically distinct sources of ancestry within Africa--the continent with the highest genetic variation. Here, we dissect the within-Africa genetic ancestry of various populations of the Americas self-identified as having primarily African ancestry using uniparentally inherited mitochondrial DNA.We first confirmed that our results obtained using uniparentally-derived group admixture estimates are correlated with the average autosomal-derived individual admixture estimates (hence are relevant to genomic ancestry) by assessing continental admixture using both types of markers (mtDNA and Y-chromosome vs. ancestry informative markers). We then focused on the within-Africa maternal ancestry, mining our comprehensive database of published mtDNA variation (∼5800 individuals from 143 African populations) that helped us thoroughly dissect the African mtDNA pool. Using this well-defined African mtDNA variation, we quantified the relative contributions of maternal genetic ancestry from multiple W/WC/SW/SE (West to South East) African populations to the different pools of today's African-descended Americans of North and South America and the Caribbean.Our analysis revealed that both continental admixture and within-Africa admixture may be critical to achieving an adequate understanding of the ancestry of African-descended Americans. While continental ancestry reflects gender-specific admixture processes influenced by different socio-historical practices in the Americas, the within-Africa maternal ancestry reflects the diverse colonial histories of the slave trade. We have confirmed that there is a genetic thread connecting Africa and the Americas, where each colonial system supplied their colonies in the Americas with slaves from African colonies they controlled or that were available for them at the time. This historical connection is reflected in different relative contributions from populations of W/WC/SW/SE Africa to geographically distinct Africa-derived populations of the Americas, adding to the complexity of genomic ancestry in groups ostensibly united by the same demographic label