Shape-IT: new rapid and accurate algorithm for haplotype inference

<p>Abstract</p> <p>Background</p> <p>We have developed a new computational algorithm, Shape-IT, to infer haplotypes under the genetic model of coalescence with recombination developed by Stephens et al in Phase v2.1. It runs much faster than Phase v2.1 while exhibiting the same accuracy. The major algorithmic improvements rely on the use of binary trees to represent the sets of candidate haplotypes for each individual. These binary tree representations: (1) speed up the computations of posterior probabilities of the haplotypes by avoiding the redundant operations made in Phase v2.1, and (2) overcome the exponential aspect of the haplotypes inference problem by the smart exploration of the most plausible pathways (ie. haplotypes) in the binary trees.</p> <p>Results</p> <p>Our results show that Shape-IT is several orders of magnitude faster than Phase v2.1 while being as accurate. For instance, Shape-IT runs 50 times faster than Phase v2.1 to compute the haplotypes of 200 subjects on 6,000 segments of 50 SNPs extracted from a standard Illumina 300 K chip (13 days instead of 630 days). We also compared Shape-IT with other widely used software, Gerbil, PL-EM, Fastphase, 2SNP, and Ishape in various tests: Shape-IT and Phase v2.1 were the most accurate in all cases, followed by Ishape and Fastphase. As a matter of speed, Shape-IT was faster than Ishape and Fastphase for datasets smaller than 100 SNPs, but Fastphase became faster -but still less accurate- to infer haplotypes on larger SNP datasets.</p> <p>Conclusion</p> <p>Shape-IT deserves to be extensively used for regular haplotype inference but also in the context of the new high-throughput genotyping chips since it permits to fit the genetic model of Phase v2.1 on large datasets. This new algorithm based on tree representations could be used in other HMM-based haplotype inference software and may apply more largely to other fields using HMM.</p

Computation of haplotypes on SNPs subsets: advantage of the "global method"

BACKGROUND: Genetic association studies aim at finding correlations between a disease state and genetic variations such as SNPs or combinations of SNPs, termed haplotypes. Some haplotypes have a particular biological meaning such as the ones derived from SNPs located in the promoters, or the ones derived from non synonymous SNPs. All these haplotypes are "subhaplotypes" because they refer only to a part of the SNPs found in the gene. Until now, subhaplotypes were directly computed from the very SNPs chosen to constitute them, without taking into account the rest of the information corresponding to the other SNPs located in the gene. In the present work, we describe an alternative approach, called the "global method", which takes into account all the SNPs known in the region and compare the efficacy of the two "direct" and "global" methods. RESULTS: We used empirical haplotypes data sets from the GH1 promoter and the APOE gene, and 10 simulated datasets, and randomly introduced in them missing information (from 0% up to 20%) to compare the 2 methods. For each method, we used the PHASE haplotyping software since it was described to be the best. We showed that the use of the "global method" for subhaplotyping leads always to a better error rate than the classical direct haplotyping. The advantage provided by this alternative method increases with the percentage of missing genotyping data (diminution of the average error rate from 25% to less than 10%). We applied the global method software on the GRIV cohort for AIDS genetic associations and some associations previously identified through direct subhaplotyping were found to be erroneous. CONCLUSION: The global method for subhaplotyping can reduce, sometimes dramatically, the error rate on patient resolutions and haplotypes frequencies. One should thus use this method in order to minimise the risk of a false interpretation in genetic studies involving subhaplotypes. In practice the global method is always more efficient than the direct method, but a combination method taking into account the level of missing information in each subject appears to be even more interesting when the level of missing information becomes larger (>10%)

ISHAPE: new rapid and accurate software for haplotyping

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

Evidence After Imputation for a Role of MICA Variants in Nonprogression and Elite Control of HIV Type 1 Infection

Past genome-wide association studies (GWAS) involving individuals with AIDS have mainly identified associations in the HLA region. Using the latest software, we imputed 7 million single-nucleotide polymorphisms (SNPs)/indels of the 1000 Genomes Project from the GWAS-determined genotypes of individuals in the Genomics of Resistance to Immunodeficiency Virus AIDS nonprogression cohort and compared them with those of control cohorts. The strongest signals were in MICA, the gene encoding major histocompatibility class I polypeptide-related sequence A (P = 3.31 × 10−12), with a particular exonic deletion (P = 1.59 × 10−8) in full linkage disequilibrium with the reference HCP5 rs2395029 SNP. Haplotype analysis also revealed an additive effect between HLA-C, HLA-B, and MICA variants. These data suggest a role for MICA in progression and elite control of human immunodeficiency virus type 1 infectio

Gene expression profiling reveals a conserved microglia signature in larval zebrafish

International audienceMicroglia are the resident macrophages of the brain. Over the past decade, our understanding of the function of these cells has significantly improved. Microglia do not only play important roles in the healthy brain but are involved in almost every brain pathology. Gene expression profiling allowed to distinguish microglia from other macro-phages and revealed that the full microglia signature can only be observed in vivo. Thus, animal models are irreplaceable to understand the function of these cells. One of the popular models to study microglia is the zebrafish larva. Due to their optical transparency and genetic accessibility, zebrafish larvae have been employed to understand a variety of microglia functions in the living brain. Here, we performed RNA sequencing of larval zebrafish microglia at different developmental time points: 3, 5, and 7 days post fertilization (dpf). Our analysis reveals that larval zebrafish microglia rapidly acquire the core microglia signature and many typical microglia genes are expressed from 3 dpf onwards. The majority of changes in gene expression happened between 3 and 5 dpf, suggesting that differentiation mainly takes place during these days. Furthermore, we compared the larval microglia transcriptome to published data sets of adult zebrafish microglia, mouse microglia, and human microglia. Larval microglia shared a significant number of expressed genes with their adult counterparts in zebrafish as well as with mouse and human microglia. In conclusion, our results show that larval zebrafish microglia mature rapidly and express the core microglia gene signature that seems to be conserved across species. K E Y W O R D S brain, evolution, microglia, RNA sequencing, transcriptome, zebrafis

Gene expression profiling reveals a conserved microglia signature in larval zebrafish

Microglia are the resident macrophages of the brain. Over the past decade, our understanding of the function of these cells has significantly improved. Microglia do not only play important roles in the healthy brain but are involved in almost every brain pathology. Gene expression profiling allowed to distinguish microglia from other macrophages and revealed that the full microglia signature can only be observed in vivo. Thus, animal models are irreplaceable to understand the function of these cells. One of the popular models to study microglia is the zebrafish larva. Due to their optical transparency and genetic accessibility, zebrafish larvae have been employed to understand a variety of microglia functions in the living brain. Here, we performed RNA sequencing of larval zebrafish microglia at different developmental time points: 3, 5, and 7 days post fertilization (dpf). Our analysis reveals that larval zebrafish microglia rapidly acquire the core microglia signature and many typical microglia genes are expressed from 3 dpf onwards. The majority of changes in gene expression happened between 3 and 5 dpf, suggesting that differentiation mainly takes place during these days. Furthermore, we compared the larval microglia transcriptome to published data sets of adult zebrafish microglia, mouse microglia, and human microglia. Larval microglia shared a significant number of expressed genes with their adul

Association Study of Common Genetic Variants and HIV- 1 Acquisition in 6,300 Infected Cases and 7,200 Controls

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6×10−11). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception ofCCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size

Genome-Wide Association Study Identifies Single Nucleotide Polymorphism in DYRK1A Associated with Replication of HIV-1 in Monocyte-Derived Macrophages

Background: HIV-1 infected macrophages play an important role in rendering resting T cells permissive for infection, in spreading HIV-1 to T cells, and in the pathogenesis of AIDS dementia. During highly active anti-retroviral treatment (HAART), macrophages keep producing virus because tissue penetration of antiretrovirals is suboptimal and the efficacy of some is reduced. Thus, to cure HIV-1 infection with antiretrovirals we will also need to efficiently inhibit viral replication in macrophages. The majority of the current drugs block the action of viral enzymes, whereas there is an abundance of yet unidentified host factors that could be targeted. We here present results from a genome-wide association study identifying novel genetic polymorphisms that affect in vitro HIV-1 replication in macrophages. Methodology/Principal Findings: Monocyte-derived macrophages from 393 blood donors were infected with HIV-1 and viral replication was determined using Gag p24 antigen levels. Genomic DNA from individuals with macrophages that had relatively low (n = 96) or high (n = 96) p24 production was used for SNP genotyping with the Illumina 610 Quad beadchip. A total of 494,656 SNPs that passed quality control were tested for association with HIV-1 replication in macrophages, using linear regression. We found a strong association between in vitro HIV-1 replication in monocyte-derived macrophages and SNP rs12483205 in DYRK1A (p = 2.16×10-5). While the association was not genome-wide significant (p<1×10-7), we could replicate this association using monocyte-derived macrophages from an independent group of 31 individuals (p = 0.0034). Combined analysis of the initial and replication cohort increased the strength of the association (p = 4.84×10-6). In addition, we found this SNP to be associated with HIV-1 disease progression in vivo in two independent cohort studies (p = 0.035 and p = 0.0048). Conclusions/Significance: These findings suggest that the kinase DYRK1A is involved in the replication of HIV-1, in vitro in macrophages as well as in vivo. © 2011 Bol et al

Bioinformatics analyses in the context of AIDS genomic

Les technologies actuelles permettent d’explorer le génome entier pour y découvrir des variants génétiques associés aux maladies. Cela implique des outils bioinformatiques adaptés à l’interface de l’informatique, des statistiques et de la biologie. Ma thèse a porté sur l’exploitation bioinformatique des données génomiques issues de la cohorte GRIV du SIDA et du projet international IHAC (International HIV Acquisition Consortium). Posant les prémices de l'imputation, j’ai d’abord développé le logiciel SUBHAP. Notre équipe a montré que la région HLA était essentielle dans la non progression et le contrôle de la charge virale et cela m’a conduit à étudier le phénotype non-progresseur non « elite ». J’ai ainsi révélé un variant du gène CXCR6 qui, en dehors du HLA, est le seul résultat identifié par approche génome-entier et répliqué. L’imputation des données du projet IHAC (10000 patients infectés et 15000 contrôles) a été réalisée et des premières associations sont en cours d’exploration.Nowadays with the newest technologies, the entire genome can be explored to uncover genetic variants which may be linked to diseases. This requires bioinformatics tools which are adequate for studies which are at the border between computing, statistics and biology. My thesis work focused on the bioinformatical analysis of genomic data from the GRIV AIDS cohort and from the IHAC (International HIV Acquisition Consortium) project. I first laid the foundation for imputation work by developing the SUBHAP software. Our team showed that the HLA region was essential in non-progression and viral charge control. This led me to study the non progressor non elite phenotype. Thus, I uncovered a variant of the CXCR6 gene which is, apart from HLA, the only result identified with a GWAS approach so far and which has been reproduced. The imputation of data from the IHAC project (10000 infected patients and 15000 control subjects) was also performed and the first associations are now being studied