Pyrethroid genetic resistance in the dengue vector (Aedes aegypti) in Posadas, Argentina.

Pyrethroids are extensively used to control adult populations of the arboviral vector Aedes aegypti, raising concerns regarding the increasing frequency and distribution of insecticide resistance mutations (kdr: knock-down resistance) in the voltage-gated sodium channel gene (Nav). The widespread use of pyrethroids imposes a threat to the success of mosquito control and the environment. In this study, we investigated the presence of two kdr mutations (V1016I and F1534C) in the Nav gene and their distribution across four neighborhoods in Posadas, Argentina, with different Ae. aegypti abundance and contrasting socioeconomic status (SES). Alleles at each locus were interrogated using TaqMan SNP genotyping assays in DNA extracted from adult females collected in a longitudinal study. We report the presence of both pyrethroid resistance alleles (kdr 1016I = 29.08%; kdr 1534C = 70.70%) among adult females. The frequency of combined kdr genotypes reveals that approximately 70% of local adult females have enhanced resistance to pyrethroids. Both, the proportion of resistant adult females (with at least one kdr allele in each locus) and Ae. aegypti abundance showed an uneven distribution between neighborhoods with different SES (p < 0.001). In high-SES neighborhoods, we found more mosquitoes and a higher frequency of pyrethroid resistance, possibly as a consequence of different public health interventions, social habits, and insecticide use. This is the first report of kdr mutations in Ae. Aegypti in the northeast region of Argentina. Our results focus on the need for within-population (city) distribution analyses of kdr mutations and highlight the relevance of incorporating insecticide resistance monitoring within the Integrated Vector Management initiative.

Yerba mate (Ilex paraguariensis, A. St.-Hil.) de novo transcriptome assembly based on tissue specific genomic expression profiles.

BACKGROUND: The most common infusion in southern Latin-American countries is prepared with dried leaves of Ilex paraguariensis A. St.-Hil., an aboriginal ancestral beverage known for its high polyphenols concentration currently consumed in > 90% of homes in Argentina, in Paraguay and Uruguay. The economy of entire provinces heavily relies on the production, collection and manufacture of Ilex paraguariensis, the fifth plant species with highest antioxidant activity. Polyphenols are associated to relevant health benefits including strong antioxidant properties. Despite its regional relevance and potential biotechnological applications, little is known about functional genomics and genetics underlying phenotypic variation of relevant traits. By generating tissue specific transcriptomic profiles, we aimed to comprehensively annotate genes in the Ilex paraguariensis phenylpropanoid pathway and to evaluate differential expression profiles. RESULTS: In this study we generated a reliable transcriptome assembly based on a collection of 15 RNA-Seq libraries from different tissues of Ilex paraguariensis. A total of 554 million RNA-Seq reads were assembled into 193,897 transcripts, where 24,612 annotated full-length transcripts had complete ORF. We assessed the transcriptome assembly quality, completeness and accuracy using BUSCO and TransRate; consistency was also evaluated by experimentally validating 11 predicted genes by PCR and sequencing. Functional annotation against KEGG Pathway database identified 1395 unigenes involved in biosynthesis of secondary metabolites, 531 annotated transcripts corresponded to the phenylpropanoid pathway. The top 30 differentially expressed genes among tissue revealed genes involved in photosynthesis and stress response. These significant differences were then validated by qRT-PCR. CONCLUSIONS: Our study is the first to provide data from whole genome gene expression profiles in different Ilex paraguariensis tissues, experimentally validating in-silico predicted genes key to the phenylpropanoid (antioxidant) pathway. Our results provide essential genomic data of potential use in breeding programs for polyphenol content. Further studies are necessary to assess if the observed expression variation in the phenylpropanoid pathway annotated genes is related to variations in leaves' polyphenol content at the population scale. These results set the current reference for Ilex paraguariensis genomic studies and provide a substantial contribution to research and biotechnological applications of phenylpropanoid secondary metabolites.

Genome-wide scan for commons SNPs affecting bovine leukemia virus infection level in dairy cattle.

BACKGROUND: Bovine leukemia virus (BLV) infection is omnipresent in dairy herds causing direct economic losses due to trade restrictions and lymphosarcoma-related deaths. Milk production drops and increase in the culling rate are also relevant and usually neglected. The BLV provirus persists throughout a lifetime and an inter-individual variation is observed in the level of infection (LI) in vivo. High LI is strongly correlated with disease progression and BLV transmission among herd mates. In a context of high prevalence, classical control strategies are economically prohibitive. Alternatively, host genomics studies aiming to dissect loci associated with LI are potentially useful tools for genetic selection programs tending to abrogate the viral spreading. The LI was measured through the proviral load (PVL) set-point and white blood cells (WBC) counts. The goals of this work were to gain insight into the contribution of SNPs (bovine 50KSNP panel) on LI variability and to identify genomics regions underlying this trait. RESULTS: We quantified anti-p24 response and total leukocytes count in peripheral blood from 1800 cows and used these to select 800 individuals with extreme phenotypes in WBCs and PVL. Two case-control genomic association studies using linear mixed models (LMMs) considering population stratification were performed. The proportion of the variance captured by all QC-passed SNPs represented 0.63 (SE ± 0.14) of the phenotypic variance for PVL and 0.56 (SE ± 0.15) for WBCs. Overall, significant associations (Bonferroni's corrected -log10p > 5.94) were shared for both phenotypes by 24 SNPs within the Bovine MHC. Founder haplotypes were used to measure the linkage disequilibrium (LD) extent (r2 = 0.22 ± 0.27 at inter-SNP distance of 25-50 kb). The SNPs and LD blocks indicated genes potentially associated with LI in infected cows: i.e. relevant immune response related genes (DQA1, DRB3, BOLA-A, LTA, LTB, TNF, IER3, GRP111, CRISP1), several genes involved in cell cytoskeletal reorganization (CD2AP, PKHD1, FLOT1, TUBB5) and modelling of the extracellular matrix (TRAM2, TNXB). Host transcription factors (TFs) were also highlighted (TFAP2D; ABT1, GCM1, PRRC2A). CONCLUSIONS: Data obtained represent a step forward to understand the biology of BLV-bovine interaction, and provide genetic information potentially applicable to selective breeding programs.

A Bayesian deconvolution strategy for immunoprecipitation-based DNA methylome analysis.

DNA methylation is an indispensible epigenetic modification required for regulating the expression of mammalian genomes. Immunoprecipitation-based methods for DNA methylome analysis are rapidly shifting the bottleneck in this field from data generation to data analysis, necessitating the development of better analytical tools. In particular, an inability to estimate absolute methylation levels remains a major analytical difficulty associated with immunoprecipitation-based DNA methylation profiling. To address this issue, we developed a cross-platform algorithm-Bayesian tool for methylation analysis (Batman)-for analyzing methylated DNA immunoprecipitation (MeDIP) profiles generated using oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq). We developed the latter approach to provide a high-resolution whole-genome DNA methylation profile (DNA methylome) of a mammalian genome. Strong correlation of our data, obtained using mature human spermatozoa, with those obtained using bisulfite sequencing suggest that combining MeDIP-seq or MeDIP-chip with Batman provides a robust, quantitative and cost-effective functional genomic strategy for elucidating the function of DNA methylation.

An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs).

We report a novel resource (methylation profiles of DNA, or mPod) for human genome-wide tissue-specific DNA methylation profiles. mPod consists of three fully integrated parts, genome-wide DNA methylation reference profiles of 13 normal somatic tissues, placenta, sperm, and an immortalized cell line, a visualization tool that has been integrated with the Ensembl genome browser and a new algorithm for the analysis of immunoprecipitation-based DNA methylation profiles. We demonstrate the utility of our resource by identifying the first comprehensive genome-wide set of tissue-specific differentially methylated regions (tDMRs) that may play a role in cellular identity and the regulation of tissue-specific genome function. We also discuss the implications of our findings with respect to the regulatory potential of regions with varied CpG density, gene expression, transcription factor motifs, gene ontology, and correlation with other epigenetic marks such as histone modifications.

A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC.

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and are essential in self versus non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune diseases. Yet identification of causal variants is problematic owing to linkage disequilibrium that extends across multiple HLA and non-HLA genes in the MHC. We therefore set out to characterize the linkage disequilibrium patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common SNPs and deletion-insertion polymorphisms across four population samples. The analysis provides informative tag SNPs that capture much of the common variation in the MHC region and that could be used in disease association studies, and it provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

Immunogenomics: molecular hide and seek.

Similar to other classical science disciplines, immunology has been embracing novel technologies and approaches giving rise to specialised sub-disciplines such as immunogenetics and, more recently, immunogenomics, which, in many ways, is the genome-wide application of immunogenetic approaches. Here, recent progress in the understanding of the immune sub-genome will be reviewed, and the ways in which immunogenomic datasets consisting of genetic and epigenetic variation, linkage disequilibrium and recombination can be harnessed for disease association and evolutionary studies will be discussed. The discussion will focus on data available for the major histocompatibility complex and the leukocyte receptor complex, the two most polymorphic regions of the human immune sub-genome.

Genetic analysis of completely sequenced disease-associated MHC haplotypes identifies shuffling of segments in recent human history.

The major histocompatibility complex (MHC) is recognised as one of the most important genetic regions in relation to common human disease. Advancement in identification of MHC genes that confer susceptibility to disease requires greater knowledge of sequence variation across the complex. Highly duplicated and polymorphic regions of the human genome such as the MHC are, however, somewhat refractory to some whole-genome analysis methods. To address this issue, we are employing a bacterial artificial chromosome (BAC) cloning strategy to sequence entire MHC haplotypes from consanguineous cell lines as part of the MHC Haplotype Project. Here we present 4.25 Mb of the human haplotype QBL (HLA-A26-B18-Cw5-DR3-DQ2) and compare it with the MHC reference haplotype and with a second haplotype, COX (HLA-A1-B8-Cw7-DR3-DQ2), that shares the same HLA-DRB1, -DQA1, and -DQB1 alleles. We have defined the complete gene, splice variant, and sequence variation contents of all three haplotypes, comprising over 259 annotated loci and over 20,000 single nucleotide polymorphisms (SNPs). Certain coding sequences vary significantly between different haplotypes, making them candidates for functional and disease-association studies. Analysis of the two DR3 haplotypes allowed delineation of the shared sequence between two HLA class II-related haplotypes differing in disease associations and the identification of at least one of the sites that mediated the original recombination event. The levels of variation across the MHC were similar to those seen for other HLA-disparate haplotypes, except for a 158-kb segment that contained the HLA-DRB1, -DQA1, and -DQB1 genes and showed very limited polymorphism compatible with identity-by-descent and relatively recent common ancestry (<3,400 generations). These results indicate that the differential disease associations of these two DR3 haplotypes are due to sequence variation outside this central 158-kb segment, and that shuffling of ancestral blocks via recombination is a potential mechanism whereby certain DR-DQ allelic combinations, which presumably have favoured immunological functions, can spread across haplotypes and populations.

A comparison of tagging methods and their tagging space.

Single-nucleotide polymorphism (SNP) tagging is widely used as a way of saving genotyping costs in association studies. A number of different tagging methods have been developed to reduce the number of markers to be genotyped while maintaining power for detecting effects on non-assayed SNPs. How the different methods perform in different settings, the degree to which they overlap and share common tags and how they differ are important questions. We investigated these questions by comparing three widely used tagging methods/algorithms--one haplotype r2-based method, one pair-wise r2-based method and one method which was based on haplotype diversity but focused on major haplotypes. Tagging efficiency was defined as the number of genotyped markers divided by the number of tagging SNPs. Tagging effectiveness was defined as the proportion of un-genotyped or 'hidden' SNPs being detected (having a pair-wise or haplotype r2 with a set of tagging SNPs over a threshold, e.g. haplotype r2> or =0.80). The ENCODE regions genotyped on the HapMap CEPH individuals were examined in this study. Tagging effectiveness was generally poor for rare SNPs than for common SNPs, for all three tagging methods. Inclusion of rare SNPs into initial HapMap scheme could enhance the performance of tags on rare hidden SNPs at the expense of increased genotyping cost. At a moderate tagging efficiency, more than 90% of hidden SNPs detected by tagging SNPs selected by one method were also detected by tagging SNPs selected by another method, and this figure could be increased to 100% if tagging efficiency was allowed to drop. These results indicate that the tagging space is highly concordant between different tagging methods, despite the fact that they often involve different sets of tagging SNPs.

A high-resolution linkage-disequilibrium map of the human major histocompatibility complex and first generation of tag single-nucleotide polymorphisms.

Autoimmune, inflammatory, and infectious diseases present a major burden to human health and are frequently associated with loci in the human major histocompatibility complex (MHC). Here, we report a high-resolution (1.9 kb) linkage-disequilibrium (LD) map of a 4.46-Mb fragment containing the MHC in U.S. pedigrees with northern and western European ancestry collected by the Centre d'Etude du Polymorphisme Humain (CEPH) and the first generation of haplotype tag single-nucleotide polymorphisms (tagSNPs) that provide up to a fivefold increase in genotyping efficiency for all future MHC-linked disease-association studies. The data confirm previously identified recombination hotspots in the class II region and allow the prediction of numerous novel hotspots in the class I and class III regions. The region of longest LD maps outside the classic MHC to the extended class I region spanning the MHC-linked olfactory-receptor gene cluster. The extended haplotype homozygosity analysis for recent positive selection shows that all 14 outlying haplotype variants map to a single extended haplotype, which most commonly bears HLA-DRB1*1501. The SNP data, haplotype blocks, and tagSNPs analysis reported here have been entered into a multidimensional Web-based database (GLOVAR), where they can be accessed and viewed in the context of relevant genome annotation. This LD map allowed us to give coordinates for the extremely variable LD structure underlying the MHC.