EggLib: processing, analysis and simulation tools for population genetics and genomics

<p>Abstract</p> <p>Background</p> <p>With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios.</p> <p>Results</p> <p>In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the <monospace>egglib </monospace>script which provides direct access to pre-programmed Python applications.</p> <p>Conclusions</p> <p>EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website <url>http://egglib.sourceforge.net/</url> where a full documentation and a manual can also be found and downloaded.</p

Adaptive evolution of the symbiotic gene NORK is not correlated with shifts of rhizobial specificity in the genus Medicago

<p>Abstract</p> <p>Background</p> <p>The <it>NODULATION RECEPTOR KINASE </it>(<it>NORK</it>) gene encodes a Leucine-Rich Repeat (LRR)-containing receptor-like protein and controls the infection by symbiotic rhizobia and endomycorrhizal fungi in Legumes. The occurrence of numerous amino acid changes driven by directional selection has been reported in this gene, using a limited number of messenger RNA sequences, but the functional reason of these changes remains obscure. The <it>Medicago </it>genus, where changes in rhizobial associations have been previously examined, is a good model to test whether the evolution of <it>NORK </it>is influenced by rhizobial interactions.</p> <p>Results</p> <p>We sequenced a region of 3610 nucleotides (encoding a 392 amino acid-long region of the NORK protein) in 32 <it>Medicago </it>species. We confirm that positive selection in <it>NORK </it>has occurred within the <it>Medicago </it>genus and find that the amino acid positions targeted by selection occur in sites outside of solvent-exposed regions in LRRs, and other sites in the N-terminal region of the protein. We tested if branches of the <it>Medicago </it>phylogeny where changes of rhizobial symbionts occurred displayed accelerated rates of amino acid substitutions. Only one branch out of five tested, leading to <it>M. noeana</it>, displays such a pattern. Among other branches, the most likely for having undergone positive selection is not associated with documented shift of rhizobial specificity.</p> <p>Conclusion</p> <p>Adaptive changes in the sequence of the NORK receptor have involved the LRRs, but targeted different sites than in most previous studies of LRR proteins evolution. The fact that positive selection in <it>NORK </it>tends not to be associated to changes in rhizobial specificity indicates that this gene was probably not involved in evolving rhizobial preferences. Other explanations (<it>e.g</it>. coevolutionary arms race) must be tested to explain the adaptive evolution of <it>NORK</it>.</p

Purifying Selection and Molecular Adaptation in the Genome of Verminephrobacter, the Heritable Symbiotic Bacteria of Earthworms

While genomic erosion is common among intracellular symbionts, patterns of genome evolution in heritable extracellular endosymbionts remain elusive. We study vertically transmitted extracellular endosymbionts (Verminephrobacter, Betaproteobacteria) that form a beneficial, species-specific, and evolutionarily old (60–130 Myr) association with earthworms. We assembled a draft genome of Verminephrobacter aporrectodeae and compared it with the genomes of Verminephrobacter eiseniae and two nonsymbiotic close relatives (Acidovorax). Similar to V. eiseniae, the V. aporrectodeae genome was not markedly reduced in size and showed no A–T bias. We characterized the strength of purifying selection (ω = dN/dS) and codon usage bias in 876 orthologous genes. Symbiont genomes exhibited strong purifying selection (ω = 0.09 ± 0.07), although transition to symbiosis entailed relaxation of purifying selection as evidenced by 50% higher ω values and less codon usage bias in symbiont compared with reference genomes. Relaxation was not evenly distributed among functional gene categories but was overrepresented in genes involved in signal transduction and cell envelope biogenesis. The same gene categories also harbored instances of positive selection in the Verminephrobacter clade. In total, positive selection was detected in 89 genes, including also genes involved in DNA metabolism, tRNA modification, and TonB-dependent iron uptake, potentially highlighting functions important in symbiosis. Our results suggest that the transition to symbiosis was accompanied by molecular adaptation, while purifying selection was only moderately relaxed, despite the evolutionary age and stability of the host association. We hypothesize that biparental transmission of symbionts and rare genetic mixing during transmission can prevent genome erosion in heritable symbionts

Amount of Information Needed for Model Choice in Approximate Bayesian Computation

Approximate Bayesian Computation (ABC) has become a popular technique in evolutionary genetics for elucidating population structure and history due to its flexibility. The statistical inference framework has benefited from significant progress in recent years. In population genetics, however, its outcome depends heavily on the amount of information in the dataset, whether that be the level of genetic variation or the number of samples and loci. Here we look at the power to reject a simple constant population size coalescent model in favor of a bottleneck model in datasets of varying quality. Not only is this power dependent on the number of samples and loci, but it also depends strongly on the level of nucleotide diversity in the observed dataset. Whilst overall model choice in an ABC setting is fairly powerful and quite conservative with regard to false positives, detecting weaker bottlenecks is problematic in smaller or less genetically diverse datasets and limits the inferences possible in non-model organism where the amount of information regarding the two models is often limited. Our results show it is important to consider these limitations when performing an ABC analysis and that studies should perform simulations based on the size and nature of the dataset in order to fully assess the power of the study

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

<p>Abstract</p> <p>Background</p> <p>High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.</p> <p>Results</p> <p>In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:</p> <p>1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).</p> <p>Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.</p> <p>2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.</p> <p>Conclusions</p> <p>Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.</p> <p>SNiPlay is available at: <url>http://sniplay.cirad.fr/</url>.</p

Chloroquine Clinical Failures in P. falciparum Malaria Are Associated with Mutant Pfmdr-1, Not Pfcrt in Madagascar

Molecular studies have demonstrated that mutations in the Plasmodium falciparum chloroquine resistance transporter gene (Pfcrt) play a major role in chloroquine resistance, while mutations in P. falciparum multidrug resistance gene (Pfmdr-1) act as modulator. In Madagascar, the high rate of chloroquine treatment failure (44%) appears disconnected from the overall level of in vitro CQ susceptibility (prevalence of CQ-resistant parasites <5%) or Pfcrt mutant isolates (<1%), strongly contrasting with sub-Saharan African countries. Previous studies showed a high frequency of Pfmdr-1 mutant parasites (>60% of isolates), but did not explore their association with P. falciparum chloroquine resistance. To document the association of Pfmdr-1 alleles with chloroquine resistance in Madagascar, 249 P. falciparum samples collected from patients enrolled in a chloroquine in vivo efficacy study were genotyped in Pfcrt/Pfmdr-1 genes as well as the estimation of the Pfmdr-1 copy number. Except 2 isolates, all samples displayed a wild-type Pfcrt allele without Pfmdr-1 amplification. Chloroquine treatment failures were significantly associated with Pfmdr-1 86Y mutant codon (OR = 4.6). The cumulative incidence of recurrence of patients carrying the Pfmdr-1 86Y mutation at day 0 (21 days) was shorter than patients carrying Pfmdr-1 86N wild type codon (28 days). In an independent set of 90 selected isolates, in vitro susceptibility to chloroquine was not associated with Pfmdr-1 polymorphisms. Analysis of two microsatellites flanking Pfmdr-1 allele showed that mutations occurred on multiple genetic backgrounds. In Madagascar, Pfmdr-1 polymorphism is associated with late chloroquine clinical failures and unrelated with in vitro susceptibility or Pfcrt genotype. These results highlight the limits of the current in vitro tests routinely used to monitor CQ drug resistance in this unique context. Gaining insight about the mechanisms that regulate polymorphism in Pfmdr1 remains important, particularly regarding the evolution and spread of Pfmdr-1 alleles in P. falciparum populations under changing drug pressure which may have important consequences in terms of antimalarial use management

A systematic review and meta-analysis of evidence for correlation between molecular markers of parasite resistance and treatment outcome in falciparum malaria

<p>Abstract</p> <p>Background</p> <p>An assessment of the correlation between anti-malarial treatment outcome and molecular markers would improve the early detection and monitoring of drug resistance by <it>Plasmodium falciparum</it>. The purpose of this systematic review was to determine the risk of treatment failure associated with specific polymorphisms in the parasite genome or gene copy number.</p> <p>Methods</p> <p>Clinical studies of non-severe malaria reporting on target genetic markers (SNPs for <it>pfmdr1</it>, <it>pfcrt</it>, <it>dhfr</it>, <it>dhps</it>, gene copy number for <it>pfmdr1</it>) providing complete information on inclusion criteria, outcome, follow up and genotyping, were included. Three investigators independently extracted data from articles. Results were stratified by gene, codon, drug and duration of follow-up. For each study and aggregate data the random effect odds ratio (OR) with 95%CIs was estimated and presented as Forest plots. An OR with a lower 95^thconfidence interval > 1 was considered consistent with a failure being associated to a given gene mutation.</p> <p>Results</p> <p>92 studies were eligible among the selection from computerized search, with information on <it>pfcrt </it>(25/159 studies), <it>pfmdr1 </it>(29/236 studies), <it>dhfr </it>(18/373 studies), <it>dhps </it>(20/195 studies). The risk of therapeutic failure after chloroquine was increased by the presence of <it>pfcrt </it>K76T (Day 28, OR = 7.2 [95%CI: 4.5–11.5]), <it>pfmdr1 </it>N86Y was associated with both chloroquine (Day 28, OR = 1.8 [95%CI: 1.3–2.4]) and amodiaquine failures (OR = 5.4 [95%CI: 2.6–11.3, p < 0.001]). For sulphadoxine-pyrimethamine the <it>dhfr </it>single (S108N) (Day 28, OR = 3.5 [95%CI: 1.9–6.3]) and triple mutants (S108N, N51I, C59R) (Day 28, OR = 3.1 [95%CI: 2.0–4.9]) and <it>dhfr</it>-<it>dhps </it>quintuple mutants (Day 28, OR = 5.2 [95%CI: 3.2–8.8]) also increased the risk of treatment failure. Increased <it>pfmdr1 </it>copy number was correlated with treatment failure following mefloquine (OR = 8.6 [95%CI: 3.3–22.9]).</p> <p>Conclusion</p> <p>When applying the selection procedure for comparative analysis, few studies fulfilled all inclusion criteria compared to the large number of papers identified, but heterogeneity was limited. Genetic molecular markers were related to an increased risk of therapeutic failure. Guidelines are discussed and a checklist for further studies is proposed.</p