Biological networks and epistasis in genome-wide association studies

Over the last few years, technological improvements have made possible the genotyping of hundreds of thousands of SNPs, enabling whole-genome association studies. The first genome-wide association studies have recently been completed to detect causal variant for complex traits. Although increasing evidence suggests that interaction between loci, such as epistasis between two loci, should be considered, most of these studies proceed by considering each SNP independently. One reason for this choice is that looking at all pairs of SNPs increases dramatically the number of tests (approximatively 50 billions of tests for a 300,000 SNPs data set) that faces with computational limitation and strong multiple testing correction.
We proposed to reduce the number of tests by focusing on pairs of SNPs that belong to genes known to interact in some metabolic network. Although some interactions might be missed, these pairs of genes are good candidates for epistasis. Furthermore the use of protein interaction databases (such as the STRING database) may reduce the number of tests by a factor of 5,000.
Results using this approach will be presented on simulated data sets and on public data sets.
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GeMprospector—online design of cross-species genetic marker candidates in legumes and grasses

The web program GeMprospector (URL: ) allows users to automatically design large sets of cross-species genetic marker candidates targeting either legumes or grasses. The user uploads a collection of ESTs from one or more legume or grass species, and they are compared with a database of clusters of homologous EST and genomic sequences from other legumes or grasses, respectively. Multiple sequence alignments between submitted ESTs and their homologues in the appropriate database form the basis of automated PCR primer design in conserved exons such that each primer set amplifies an intron. The only user input is a collection of ESTs, not necessarily from more than one species, and GeMprospector can boost the potential of such an EST collection by combining it with a large database to produce cross-species genetic marker candidates for legumes or grasses

CoaSim: A flexible environment for simulating genetic data under coalescent models

BACKGROUND: Coalescent simulations are playing a large role in interpreting large scale intra-specific sequence or polymorphism surveys and for planning and evaluating association studies. Coalescent simulations of data sets under different models can be compared to the actual data to test the importance of different evolutionary factors and thus get insight into these. RESULTS: We have created the CoaSim application as a flexible environment for Monte Carlo simulation of various types of genetic data under equilibrium and non-equilibrium coalescent processes for a variety of applications. Interaction with the tool is through the Guile version of the Scheme scripting language. Scheme scripts for many standard and advanced applications are provided and these can easily be modified by the user for a much wider range of applications. A graphical user interface with less functionality and flexibility is also included. It is primarily intended as an exploratory and educational tool CONCLUSION: CoaSim is a powerful tool because of its flexibility and ease of use. This is illustrated through very varied uses of the application, e.g. evaluation of association mapping methods, parametric bootstrapping, and design and choice of markers for specific question

An analysis of synteny of Arachis with Lotus and Medicago sheds new light on the structure, stability and evolution of legume genomes

<p>Abstract</p> <p>Background</p> <p>Most agriculturally important legumes fall within two sub-clades of the Papilionoid legumes: the Phaseoloids and Galegoids, which diverged about 50 Mya. The Phaseoloids are mostly tropical and include crops such as common bean and soybean. The Galegoids are mostly temperate and include clover, fava bean and the model legumes <it>Lotus </it>and <it>Medicago </it>(both with substantially sequenced genomes). In contrast, peanut (<it>Arachis hypogaea</it>) falls in the Dalbergioid clade which is more basal in its divergence within the Papilionoids. The aim of this work was to integrate the genetic map of <it>Arachis </it>with <it>Lotus </it>and <it>Medicago </it>and improve our understanding of the <it>Arachis </it>genome and legume genomes in general. To do this we placed on the <it>Arachis </it>map, comparative anchor markers defined using a previously described bioinformatics pipeline. Also we investigated the possible role of transposons in the patterns of synteny that were observed.</p> <p>Results</p> <p>The <it>Arachis </it>genetic map was substantially aligned with <it>Lotus </it>and <it>Medicago </it>with most synteny blocks presenting a single main affinity to each genome. This indicates that the last common whole genome duplication within the Papilionoid legumes predated the divergence of <it>Arachis </it>from the Galegoids and Phaseoloids sufficiently that the common ancestral genome was substantially diploidized. The <it>Arachis </it>and model legume genomes comparison made here, together with a previously published comparison of <it>Lotus </it>and <it>Medicago </it>allowed all possible <it>Arachis-Lotus-Medicago </it>species by species comparisons to be made and genome syntenies observed. Distinct conserved synteny blocks and non-conserved regions were present in all genome comparisons, implying that certain legume genomic regions are consistently more stable during evolution than others. We found that in <it>Medicago </it>and possibly also in <it>Lotus</it>, retrotransposons tend to be more frequent in the variable regions. Furthermore, while these variable regions generally have lower densities of single copy genes than the more conserved regions, some harbor high densities of the fast evolving disease resistance genes.</p> <p>Conclusion</p> <p>We suggest that gene space in Papilionoids may be divided into two broadly defined components: more conserved regions which tend to have low retrotransposon densities and are relatively stable during evolution; and variable regions that tend to have high retrotransposon densities, and whose frequent restructuring may fuel the evolution of some gene families.</p

Ribosome-Targeting Antibiotics Impair T Cell Effector Function and Ameliorate Autoimmunity by Blocking Mitochondrial Protein Synthesis

While antibiotics are intended to specifically target bacteria, most are known to affect host cell physiology. In addition, some antibiotic classes are reported as immunosuppressive for reasons that remain unclear. Here, we show that Linezolid, a ribosomal-targeting antibiotic (RAbo), effectively blocked the course of a T cell mediated autoimmune disease. Linezolid and other RAbos were strong inhibitors of T helper-17 cell effector function in vitro, showing that this effect was independent of their antibiotic activity. Perturbing mitochondria! translation in differentiating T cells, either with RAbos or through the inhibition of mitochondria! elongation factor G1 (mEF-G1) progressively compromised the integrity of the electron transport chain. Ultimately, this led to deficient oxidative phosphorylation, diminishing nicotinamide adenine dinucleotide concentrations and impairing cytokine production in differentiating T cells. In accordance, mice lacking mEF-G1 in T cells were protected from experimental autoimmune encephalomyelitis, demonstrating that this pathway is crucial in maintaining T cell function and pathogenicity

Using Biological Networks to Search for Interacting SNPs

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Comparative transcriptomic analyses of thymocytes using 10x Genomics and Parse scRNA-seq technologies

Abstract Background Single-cell RNA sequencing experiments commonly use 10x Genomics (10x) kits due to their high-throughput capacity and standardized protocols. Recently, Parse Biosciences (Parse) introduced an alternative technology that uses multiple in-situ barcoding rounds within standard 96-well plates. Parse enables the analysis of more cells from multiple samples in a single run without the need for additional reagents or specialized microfluidics equipment. To evaluate the performance of both platforms, we conducted a benchmark study using biological and technical replicates of mouse thymus as a complex immune tissue. Results We found that Parse detected nearly twice the number of genes compared to 10x, with each platform detecting a distinct set of genes. The comparison of multiplexed samples generated from 10x and Parse techniques showed 10x data to have lower technical variability and more precise annotation of biological states in the thymus compared to Parse. Conclusion Our results provide a comprehensive comparison of the suitability of both single-cell platforms for immunological studies