Serial evolutionary networks of within-patient HIV-1 sequences reveal patterns of evolution of X4 strains

Background The HIV virus is known for its ability to exploit numerous genetic and evolutionary mechanisms to ensure its proliferation, among them, high replication, mutation and recombination rates. Sliding MinPD, a recently introduced computational method [1], was used to investigate the patterns of evolution of serially-sampled HIV-1 sequence data from eight patients with a special focus on the emergence of X4 strains. Unlike other phylogenetic methods, Sliding MinPD combines distance-based inference with a nonparametric bootstrap procedure and automated recombination detection to reconstruct the evolutionary history of longitudinal sequence data. We present serial evolutionary networks as a longitudinal representation of the mutational pathways of a viral population in a within-host environment. The longitudinal representation of the evolutionary networks was complemented with charts of clinical markers to facilitate correlation analysis between pertinent clinical information and the evolutionary relationships. Results Analysis based on the predicted networks suggests the following:: significantly stronger recombination signals (p = 0.003) for the inferred ancestors of the X4 strains, recombination events between different lineages and recombination events between putative reservoir virus and those from a later population, an early star-like topology observed for four of the patients who died of AIDS. A significantly higher number of recombinants were predicted at sampling points that corresponded to peaks in the viral load levels (p = 0.0042). Conclusion Our results indicate that serial evolutionary networks of HIV sequences enable systematic statistical analysis of the implicit relations embedded in the topology of the structure and can greatly facilitate identification of patterns of evolution that can lead to specific hypotheses and new insights. The conclusions of applying our method to empirical HIV data support the conventional wisdom of the new generation HIV treatments, that in order to keep the virus in check, viral loads need to be suppressed to almost undetectable levels.

Genetic markers, birth characteristics, and childhood leukemia risk

The cause for childhood acute lymphoblastic leukemia (ALL) remains unknown, but male gender is a risk factor, and among ethnicities, Hispanics have the highest risk. In this dissertation, we explored correlations among genetic polymorphisms, birth characteristics, and the risk of childhood ALL in a multi-ethnic sample in 161 cases and 231 controls recruited contemporaneously (2007-2012) in Houston, TX. We first examined three lymphoma risk markers, since lymphoma and ALL both stem from lymphoid cells. Of these, rs2395185 showed a risk association in non-Hispanic White males (OR=2.8, P=0.02; P interaction=0.03 for gender), but not in Hispanics. We verified previously known risk associations to validate the case-control sample. Mutations of HFE (C282Y, H63D) were genotyped to test whether iron-regulatory gene (IRG) variants known to elevate iron levels increase childhood ALL risk. Being positive for either polymorphism yielded only a modestly elevated OR in males, which increased to 2.96 (P=0.01) in the presence of a particular transferrin receptor (TFRC) genotype for rs3817672 (Pinteraction=0.04). SNP rs3817672 itself showed an ethnicity-specific association (P interaction=0.02 for ethnicity). We then examined additional IRG SNPs (rs422982, rs855791, rs733655), which showed risk associations in males (ORs=1.52 to 2.60). A polygenic model based on the number of polymorphic alleles in five IRG SNPs revealed a linear increase in risk (OR=2.00 per incremental change; P=0.002). Having three or more alleles compared with none was associated with increased risk in males (OR=4.12; P=0.004). Significant risk associations with childhood ALL was found with birth length (OR=1.18 per inch, P=0.04), high birth weight (>4,000g) (OR=1.93, P=0.01), and with gestational age (OR=1.10 per week, P=0.04). We observed a negative correlation between HFE SNP rs9366637 and gestational age (P=0.005), again, stronger in males ( P=0.001) and interacting with TFRC (P interaction=0.05). Our results showed that (i) ALL risk markers do not show universal associations across ethnicities or between genders, (ii) IRG SNPs modify ALL risk presumably by their effects on iron levels, (iii) a negative correlation between an HFE SNP and gestational age exists, which implicates an iron-related mechanism. The results suggest that currently unregulated supplemental iron intake may have implications on childhood ALL development.

Placental contribution to the origins of sexual dimorphism in health and diseases: sex chromosomes and epigenetics

Sex differences occur in most non-communicable diseases, including metabolic diseases, hypertension, cardiovascular disease, psychiatric and neurological disorders and cancer. In many cases, the susceptibility to these diseases begins early in development. The observed differences between the sexes may result from genetic and hormonal differences and from differences in responses to and interactions with environmental factors, including infection, diet, drugs and stress. The placenta plays a key role in fetal growth and development and, as such, affects the fetal programming underlying subsequent adult health and accounts, in part for the developmental origin of health and disease (DOHaD). There is accumulating evidence to demonstrate the sex-specific relationships between diverse environmental influences on placental functions and the risk of disease later in life. As one of the few tissues easily collectable in humans, this organ may therefore be seen as an ideal system for studying how male and female placenta sense nutritional and other stresses, such as endocrine disruptors. Sex-specific regulatory pathways controlling sexually dimorphic characteristics in the various organs and the consequences of lifelong differences in sex hormone expression largely account for such responses. However, sex-specific changes in epigenetic marks are generated early after fertilization, thus before adrenal and gonad differentiation in the absence of sex hormones and in response to environmental conditions. Given the abundance of X-linked genes involved in placentogenesis, and the early unequal gene expression by the sex chromosomes between males and females, the role of X- and Y-chromosome-linked genes, and especially those involved in the peculiar placenta-specific epigenetics processes, giving rise to the unusual placenta epigenetic landscapes deserve particular attention. However, even with recent developments in this field, we still know little about the mechanisms underlying the early sex-specific epigenetic marks resulting in sex-biased gene expression of pathways and networks. As a critical messenger between the maternal environment and the fetus, the placenta may play a key role not only in buffering environmental effects transmitted by the mother but also in expressing and modulating effects due to preconceptional exposure of both the mother and the father to stressful conditions.

Dissecting the Functional Impacts of Non-Coding Genetic Variation

A large proportion of the variation in traits between individuals can be attributed to variation in the nucleotide sequence of the genome. The most commonly studied traits in human genetics are related to disease and disease susceptibility. Although scientists have identified genetic causes for over 4,000 monogenic diseases, the underlying mechanisms of many highly prevalent multifactorial inheritance disorders such as diabetes, obesity, and cardiovascular disease remain largely unknown. Identifying genetic mechanisms for complex traits has been challenging because most of the variants are located outside of protein-coding regions, and determining the effects of such non-coding variants remains difficult. In this dissertation, I evaluate the hypothesis that such non-coding variants contribute to human traits and diseases by altering the regulation of genes rather than the sequence of those genes. I will specifically focus on studies to determine the functional impacts of genetic variation associated with two related complex traits: gestational hyperglycemia and fetal adiposity. At the genomic locus associated with maternal hyperglycemia, we found that genetic variation in regulatory elements altered the expression of the HKDC1 gene. Furthermore, we demonstrated that HKDC1 phosphorylates glucose in vitro and in vivo, thus demonstrating that HKDC1 is a fifth human hexokinase gene. At the fetal-adiposity associated locus, we identified variants that likely alter VEPH1 expression in preadipocytes during differentiation. To make such studies of regulatory variation high-throughput and routine, we developed POP-STARR, a novel high throughput reporter assay that can empirically measure the effects of regulatory variants directly from patient DNA. By combining targeted genome capture technologies with STARR-seq, we assayed thousands of haplotypes from 760 individuals in a single experiment. We subsequently used POP-STARR to identify three key features of regulatory variants: that regulatory variants typically have weak effects on gene expression; that the effects of regulatory variants are often coordinated with respect to disease-risk, suggesting a general mechanism by which the weak effects can together have phenotypic impact; and that nucleotide transversions have larger impacts on enhancer activity than transitions. Together, the findings presented here demonstrate successful strategies for determining the regulatory mechanisms underlying genetic associations with human traits and diseases, and value of doing so for driving novel biological discovery.

Ribosomal frameshifting and transcriptional slippage: from genetic steganography and cryptography to adventitious use

Genetic decoding is not ‘frozen’ as was earlier thought, but dynamic. One facet of this is frameshifting that often results in synthesis of a C-terminal region encoded by a new frame. Ribosomal frameshifting is utilized for the synthesis of additional products, for regulatory purposes and for translational ‘correction’ of problem or ‘savior’ indels. Utilization for synthesis of additional products occurs prominently in the decoding of mobile chromosomal element and viral genomes. One class of regulatory frameshifting of stable chromosomal genes governs cellular polyamine levels from yeasts to humans. In many cases of productively utilized frameshifting, the proportion of ribosomes that frameshift at a shift-prone site is enhanced by specific nascent peptide or mRNA context features. Such mRNA signals, which can be 5′ or 3′ of the shift site or both, can act by pairing with ribosomal RNA or as stem loops or pseudoknots even with one component being 4 kb 3′ from the shift site. Transcriptional realignment at slippage-prone sequences also generates productively utilized products encoded trans-frame with respect to the genomic sequence. This too can be enhanced by nucleic acid structure. Together with dynamic codon redefinition, frameshifting is one of the forms of recoding that enriches gene expression.

Maternal and paternal growth regulatory factor expression in hybrid sunfish.

Unidirectional hybridization between bluegill (Lepomis macrochirus) and pumpkinseed (L. gibbosus) sunfish enables researchers to explore the relative expression of paternal and maternal alleles in hybrids. Past studies have found that the metabolic dysfunction in bluegill-pumpkinseed hybrids may be due to incompatibilities between nuclear and mitochondrial genomes. However, the consequences of hybridization on body size and muscle growth have not been examined. This topic is particularly interesting because hybrids grow larger than parentals despite the fact that they are often sired by smaller, precociously mature bluegills. In order to improve our understanding of growth dynamics in hybrid sunfish, I conducted real-time quantitative PCR using species-specific primers on the white muscle tissue of bluegills, pumpkinseeds, and hybrids collected from Lake Opinicon, ON. Five growth factors that have been linked to muscle growth and body size demonstrated similar expression for maternal and paternal alleles. While about half of the hybrids showed the same pattern with myogenin, about half showed very low levels of mRNA for the paternal (bluegill) gene. While this did not explain the heterosis seen in hybrids, it may explain the small body phenotype of the cuckholding bluegill males. I explored the upstream genetic structure of bluegill myogenin and established that four alleles exist within the population. Furthermore, I uncovered a relationship in hybrids between the proximal promoter/ 5’ UTR of myogenin and its transcript level. I found that the hybrids demonstrating low paternal myogenin expression unfailingly possessed A3 or A4 alleles, but future studies will be needed to reveal the molecular links between the genotype and the growth phenotype. A similar genotype-phenotype association was not obvious in parentals, even those that were homozygous for these alleles. Whether this relationship can provide insight into the genetic determinants of bluegill alternative mating strategies has yet to be determined.

HNF1B variants associate with promoter methylation and regulate gene networks activated in prostate and ovarian cancer

Two independent regions within HNF1B are consistently identified in prostate and ovarian cancer genome-wide association studies (GWAS); their functional roles are unclear. We link prostate cancer (PC) risk SNPs rs11649743 and rs3760511 with elevated HNF1B gene expression and allele-specific epigenetic silencing, and outline a mechanism by which common risk variants could effect functional changes that increase disease risk: functional assays suggest that HNF1B is a pro-differentiation factor that suppresses epithelial-to-mesenchymal transition (EMT) in unmethylated, healthy tissues. This tumor-suppressor activity is lost when HNF1B is silenced by promoter methylation in the progression to PC. Epigenetic inactivation of HNF1B in ovarian cancer also associates with known risk SNPs, with a similar impact on EMT. This represents one of the first comprehensive studies into the pleiotropic role of a GWAS-associated transcription factor across distinct cancer types, and is the first to describe a conserved role for a multi-cancer genetic risk factor.

Regulatory T cells control strain specific resistance to Experimental Autoimmune Prostatitis

Susceptibility to autoimmune diseases results from the encounter of a complex and long evolved genetic context with a no less complex and changing environment. Major actors in maintaining health are regulatory T cells (Treg) that primarily dampen a large subset of autoreactive lymphocytes escaping thymic negative selection. Here, we directly asked whether Treg participate in defining susceptibility and resistance to Experimental Autoimmune Prostatitis (EAP). We analyzed three common laboratory strains of mice presenting with different susceptibility to autoimmune prostatitis upon immunization with prostate proteins. The NOD, the C57BL/6 and the BALB/c mice that can be classified along a disease score ranging from severe, mild and to undetectable, respectively. Upon mild and transient depletion of Treg at the induction phase of EAP, each model showed an increment along this score, most remarkably with the BALB/c mice switching from a resistant to a susceptible phenotype. We further show that disease associates with the upregulation of CXCR3 expression on effector T cells, a process requiring IFNγ. Together with recent advances on environmental factors affecting Treg, these findings provide a likely cellular and molecular explanation to the recent rise in autoimmune diseases incidence.

Whole Genome Analysis of Gene Expression Reveals Coordinated Activation of Signaling and Metabolic Pathways during Pollen-Pistil Interactions in Arabidopsis

Plant reproduction depends on the concerted activation of many genes to ensure correct communication between pollen and pistil. Here, we queried the whole transcriptome of Arabidopsis (Arabidopsis thaliana) in order to identify genes with specific reproductive functions. We used the Affymetrix ATH1 whole genome array to profile wild-type unpollinated pistils and unfertilized ovules. By comparing the expression profile of pistils at 0.5, 3.5, and 8.0 h after pollination and applying a number of statistical and bioinformatics criteria, we found 1,373 genes differentially regulated during pollen-pistil interactions. Robust clustering analysis grouped these genes in 16 time-course clusters representing distinct patterns of regulation. Coregulation within each cluster suggests the presence of distinct genetic pathways, which might be under the control of specific transcriptional regulators. A total of 78% of the regulated genes were expressed initially in unpollinated pistil and/or ovules, 15% were initially detected in the pollen data sets as enriched or preferentially expressed, and 7% were induced upon pollination. Among those, we found a particular enrichment for unknown transcripts predicted to encode secreted proteins or representing signaling and cell wall-related proteins, which may function by remodeling the extracellular matrix or as extracellular signaling molecules. A strict regulatory control in various metabolic pathways suggests that fine-tuning of the biochemical and physiological cellular environment is crucial for reproductive success. Our study provides a unique and detailed temporal and spatial gene expression profile of in vivo pollen-pistil interactions, providing a framework to better understand the basis of the molecular mechanisms operating during the reproductive process in higher plants.

DATA DRIVEN APPROACHES TO IDENTIFY DETERMINANTS OF HEART DISEASES AND CANCER RESISTANCE

Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

Guiding Monte Carlo tree searches with neural networks in the game of go

A dissertation submitted in fulfillment of the requirements to the degree of Master in Computer Science and Computer Engineering

Identification and characterisation of telomere regulatory and signalling pathways after induction of telomere dysfunction

Telomeres are DNA-protein complexes which cap the ends of eukaryotic linear chromosomes. In normal somatic cells telomeres shorten and become dysfunctional during ageing due to the DNA end replication problem. This leads to activation of signalling pathways that lead to cellular senescence and apoptosis. However, cancer cells typically bypass this barrier to immortalisation in order to proliferate indefinitely. Therefore enhancing our understanding of telomere dysfunction and pathways involved in regulation of the process is essential. However, the pathways involved are highly complex and involve interaction between a wide range of biological processes. Therefore understanding how telomerase dysfunction is regulated is a challenging task and requires a systems biology approach. In this study I have developed a novel methodology for visualisation and analysis of gene lists focusing on the network level rather than individual or small lists of genes. Application of this methodology to an expression data set and a gene methylation data set allowed me to enhance my understanding of the biology underlying a senescence inducing drug and the process of immortalisation respectively. I then used the methodology to compare the effect of genetic background on induction of telomere uncapping. Telomere uncapping was induced in HCT116 WT, p21-/- and p53-/- cells using a viral vector expressing a mutant variant of hTR, the telomerase RNA template. p21-/- cells showed enhanced sensitivity to telomere uncapping. Analysis of a candidate pathway, Mismatch Repair, revealed a role for the process in response to telomere uncapping and that induction of the pathway was p21 dependent. The methodology was then applied to analysis of the telomerase inhibitor GRN163L and synergistic effects of hypoglycaemia with this drug. HCT116 cells were resistant to GRN163L treatment. However, under hypoglycaemic conditions the dose required for ablation of telomerase activity was reduced significantly and telomere shortening was enhanced. Overall this new methodology has allowed our group and collaborators to identify new biology and improve our understanding of processes regulating telomere dysfunction.

The RGBarrier assay: the parallel study of gene regulatory element performance at defined chromosomal locations

Vertebrate genomes are organised into a variety of nuclear environments and chromatin states that have profound effects on the regulation of gene transcription. This variation presents a major challenge to the expression of transgenes for experimental research, genetic therapies and the production of biopharmaceuticals. The majority of transgenes succumb to transcriptional silencing by their chromosomal environment when they are randomly integrated into the genome, a phenomenon known as chromosomal position effect (CPE). It is not always feasible to target transgene integration to transcriptionally permissive “safe harbour” loci that favour transgene expression, so there remains an unmet need to identify gene regulatory elements that can be added to transgenes which protect them against CPE. Dominant regulatory elements (DREs) with chromatin barrier (or boundary) activity have been shown to protect transgenes from CPE. The HS4 element from the chicken beta-globin locus and the A2UCOE element from a human housekeeping gene locus have been shown to function as DRE barriers in a wide variety of cell types and species. Despite rapid advances in the profiling of transcription factor binding, chromatin states and chromosomal looping interactions, progress towards functionally validating the many candidate barrier elements in vertebrates has been very slow. This is largely due to the lack of a tractable and efficient assay for chromatin barrier activity. In this study, I have developed the RGBarrier assay system to test the chromatin barrier activity of candidate DREs at pre-defined isogenic loci in human cells. The RGBarrier assay consists in a Flp-based RMCE reaction for the integration of an expression construct, carrying candidate DREs, in a pre-characterised chromosomal location. The RGBarrier system involves the tracking of red, green and blue fluorescent proteins by flow cytometry to monitor on-target versus off-target integration and transgene expression. The analysis of the reporter (GFP) expression for several weeks gives a measure of the protective ability of each candidate elements from chromosomal silencing. This assay can be scaled up to test tens of new putative barrier elements in the same chromosomal context in parallel. The defined chromosomal contexts of the RGBarrier assays will allow for detailed mechanistic studies of chromosomal silencing and DRE barrier element action. Understanding these mechanisms will be of paramount importance for the design of specific solutions for overcoming chromosomal silencing in specific transgenic applications.

Drinking water disinfection by-products, genetic polymorphisms, and birth outcomes in a european mother-child cohort study

International audience

Legal Framework for Cross-Regional Networks: The Case of Services and Migration

Paper prepared by Marion Panizzon and Charlotte Sieber-Gasser for the International Conference on the Political Economy of Liberalising Trade in Services, Hebrew University of Jerusalem, 14-15 June 2010 Recent literature has shed light on the economic potential of cross-border networks. These networks, consisting of expatriates and their acquaintances from abroad and at home, provide the basis for the creation of cross-border value added chains and therewith the means for turning brain drain into brain circulation. Both aspects are potentially valuable for economic growth in the developing world. Unilateral co-development policies operating through co-funding of expatriate business ventures, but also bilateral agreements liberalising circular migration for a limited set of per-sons testify to the increasing awareness of governments about the potential, which expatriate networks hold for economic growth in developing countries. Whereas such punctual efforts are valuable, viewed from a long term perspective, these top-down, government mandated Diaspora stimulation programs, will not replace, this paper argues, the market-driven liberalisation of infrastructure and other services in developing countries. Nor will they carry, in the case of circular labour migration, the political momentum to liberalise labour market admission for those non-nationals, who will eventually emerge as the future transnational entrepreneurs. It will take a combination of mode 4 and infrastructure services openings-cum regulation for countries at both sides of the spectrum to provide the basis and precondition for transnational business and entrepreneurial networks to emerge and translate into cross-border, value added production chains. Two key issues are of particular relevance in this context: (i) the services sector, especially in infrastructure, tends to suffer from inefficiencies, particularly in developing countries, and (ii) labour migration, a highly complex issue, still faces disproportionately rigid barriers despite well-documented global welfare gains. Both are hindrances for emerging markets to fully take advantage of the potential of these cross-border networks. Adapting the legal framework for enhancing the regulatory and institutional frameworks for services trade, especially in infrastructure services sectors (ISS) and labour migration could provide the incentives necessary for brain circulation and strengthen cross-border value added chains by lowering transaction costs. This paper analyses the shortfalls of the global legal framework – the shallow status quo of GATS commitments in ISS and mode 4 particular – in relation to stimulating brain circulation and the creation of cross-border value added chains in emerging markets. It highlights the necessity of adapting the legal framework, both on the global and the regional level, to stimulate broader and wider market access in the four key ISS sectors (telecommunications, transport, professional and financial services) in developing countries, as domestic supply capacity, global competitiveness and economic diversification in ISS sectors are necessary for mobilising expatriate re-turns, both physical and virtual. The paper argues that industrialised, labour receiving countries need to offer mode 4 market access to wider categories of persons, especially to students, graduate trainees and young professionals from abroad. Further-more, free trade in semi-finished products and mode 4 market access are crucial for the creation of cross-border value added chains across the developing world. Finally, the paper discusses on the basis of a case study on Jordan why the key features of trade agreements, which promote circular migration and the creation of cross-border value added chains, consist of trade liberalisation in services and liberal migration policies.