Genome-wide in situ exon capture for selective resequencing

Increasingly powerful sequencing technologies are ushering in an era of personal genome sequences and raising the possibility of using such information to guide medical decisions. Genome resequencing also promises to accelerate the identification of disease-associated mutations. Roughly 98% of the human genome is composed of repeats and intergenic or non-protein-coding sequences. Thus, it is crucial to focus resequencing on high-value genomic regions. Protein-coding exons represent one such type of high-value target. We have developed a method of using flexible, high-density microarrays to capture any desired fraction of the human genome, in this case corresponding to more than 200,000 protein-coding exons. Depending on the precise protocol, up to 55-85% of the captured fragments are associated with targeted regions and up to 98% of intended exons can be recovered. This methodology provides an adaptable route toward rapid and efficient resequencing of any sizeable, non-repeat portion of the human genome.     

‘Who’s in the Network?’ When Stakeholders Influence Data Analysis

Environmental applications of social network analysis (SNA) are just beginning to emerge, and so far have focussed on understanding the characteristics of social networks that increase the likelihood of collective action and successful natural resource management. We move beyond this discussion to demonstrate how knowledge gained from analysing the social networks of stakeholders can be harnessed for selecting stakeholders, and further, how these analyses can be influenced by the expressed wishes and concerns of stakeholders. Although we began our SNA using concepts derived from the resource-management literature, stakeholder involvement in the interpretation of the results led to the use of SNA techniques that had not previously been applied in the context of resource management. We thus re-analysed our data and modified our selection of research participants. Re-analysis led to the selection of research participants who (1) had unique positions in the network, thus occupying non-redundant communication roles in the network, (2) came from different stakeholder categories and (3) were relatively well-connected to others and tended to broker across different segments of the network. By combining insights from researchers and stakeholders in this way, it was possible to use SNA in an innovative and sensitive way to better meet the needs of the stakeholders and the research project.

Pathogen-induced human TH17 cells produce IFN-γ or IL-10 and are regulated by IL-1β

IL-17-producing CD4+ T helper cells (TH17) have been extensively investigated in mouse models of autoimmunity. However, the requirements for differentiation and the properties of pathogen-induced human TH17 cells remain poorly defined. Using an approach that combines the in vitro priming of naive T cells with the ex vivo analysis of memory T cells, we describe here two types of human TH17 cells with distinct effector function and differentiation requirements. Candida albicans-specific TH17 cells produced IL-17 and IFN-γ, but no IL-10, whereas Staphylococcus aureus-specific TH17 cells produced IL-17 and could produce IL-10 upon restimulation. IL-6, IL-23 and IL-1β contributed to TH17 differentiation induced by both pathogens, but IL-1β was essential in C. albicans-induced TH17 differentiation to counteract the inhibitory activity of IL-12 and to prime IL-17/IFN-γ double-producing cells. In addition, IL-1β inhibited IL-10 production in differentiating and in memory TH17 cells, whereas blockade of IL-1β in vivo led to increased IL-10 production by memory TH17 cells. We also show that, after restimulation, TH17 cells transiently downregulated IL-17 production through a mechanism that involved IL-2-induced activation of STAT5 and decreased expression of ROR-γt. Taken together these findings demonstrate that by eliciting different cytokines C. albicans and S. aureus prime TH17 cells that produce either IFN-γ or IL-10, and identify IL-1β and IL-2 as pro- and anti-inflammatory regulators of TH17 cells both at priming and in the effector phase.     

The Drosophila melanogaster Genetic Reference Panel

A major challenge of biology is understanding the relationship between molecular genetic variation and variation in quantitative traits, including fitness. This relationship determines our ability to predict phenotypes from genotypes and to understand how evolutionary forces shape variation within and between species. Previous efforts to dissect the genotype-phenotype map were based on incomplete genotypic information. Here, we describe the Drosophila melanogaster Genetic Reference Panel (DGRP), a community resource for analysis of population genomics and quantitative traits. The DGRP consists of fully sequenced inbred lines derived from a natural population. Population genomic analyses reveal reduced polymorphism in centromeric autosomal regions and the X chromosome, evidence for positive and negative selection, and rapid evolution of the X chromosome. Many variants in novel genes, most at low frequency, are associated with quantitative traits and explain a large fraction of the phenotypic variance. The DGRP facilitates genotype-phenotype mapping using the power of Drosophila genetics.     

Analysis of Plasmodium falciparum diversity in natural infections by deep sequencing

Malaria elimination strategies require surveillance of the parasite population for genetic changes that demand a public health response, such as new forms of drug resistance. Here we describe methods for the large-scale analysis of genetic variation in Plasmodium falciparum by deep sequencing of parasite DNA obtained from the blood of patients with malaria, either directly or after short-term culture. Analysis of 86,158 exonic single nucleotide polymorphisms that passed genotyping quality control in 227 samples from Africa, Asia and Oceania provides genome-wide estimates of allele frequency distribution, population structure and linkage disequilibrium. By comparing the genetic diversity of individual infections with that of the local parasite population, we derive a metric of within-host diversity that is related to the level of inbreeding in the population. An open-access web application has been established for the exploration of regional differences in allele frequency and of highly differentiated loci in the P.?falciparum genome.