346 research outputs found

    Multi-locus analysis of genomic time series data from experimental evolution.

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    Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. We first use simulated data to demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequencing coverage depth. In addition to providing quantitative estimates of selection parameters from experimental evolution data, our model can be used by practitioners to design E&R experiments with requisite power. We also explore how our likelihood-based approach can be used to infer other model parameters, including effective population size and recombination rate. Then, we apply our method to analyze genome-wide data from a real E&R experiment designed to study the adaptation of D. melanogaster to a new laboratory environment with alternating cold and hot temperatures

    E. coli Microcosms Indicate a Tight Link between Predictability of Ecosystem Dynamics and Diversity

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    The diversity-stability hypothesis proposes that ecosystem diversity is positively correlated with stability. The impact of ecosystem diversity is, however, still debated. In a microcosm experiment using diverged Escherichia coli cells, we show that the fitness of community members depends on the complexity (number of participants) of the system. Interestingly, the spread of a community member with a superior genotype is mostly stochastic in low-complexity systems, but highly deterministic in a more complex environment. We conclude that system complexity provides a buffer against stochastic effects

    Non-random genomic integration - an intrinsic property of retrogenes in Drosophila?

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    ABSTRACT: BACKGROUND: The Drosophila X-chromosome shows a significant underrepresentation of genes with male-biased gene expression (demasculinization). This trend is matched by retrogenes, which typically have a male biased gene expression pattern and show a significant movement bias from X-chromosomes to autosomes. It is currently assumed that these patterns are best explained by selection, either mediated by male meiotic sex chromosome inactivation (MSCI) or sexually antagonistic forces. We scrutinized the evolutionary dynamics of retroposition by focusing on retrogenes for which the parental copy has degenerated. RESULTS: Consistent with a functional substitution of the degenerated gene by the retrogene, patterns of sequence evolution and gene expression were similar between retroposed and parental genes. Like previous studies, our set of retrogenes showed a significant movement off the X-chromosome. In contrast to data sets where retroposition caused gene duplication, the genes in our study showed primarily female-biased or unbiased gene expression. CONCLUSIONS: Based on our results, the biased transposition pattern cannot be explained by MSCI and probably not by sexual antagonism. Rather, we propose that the movement away from the X-chromosome represents a general property of retroposition in Drosophila

    Comparison of algorithms for the analysis of Affymetrix microarray data as evaluated by co-expression of genes in known operons

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    Oligonucleotide microarrays are an informative tool to elucidate gene regulatory networks. In order for gene expression levels to be comparable across microarrays, normalization procedures have to be invoked. A large number of methods have been described to correct for systematic biases in microarray experiments. The performance of these methods has been tested only to a limited extend. Here, we evaluate two different types of microarray analyses: (i) the same gene in replicate samples and (ii) different, but co-expressed genes in the same sample. The reliability of the latter analysis needs to be determined for the analysis of regulatory networks and our report is the first attempt to evaluate for the accuracy of different microarray normalization methods in this respect. Consistent with previous results we observed a large effect of the normalization method on the outcome of the expression analyses. Our analyses indicate that different normalization methods should be performed depending on whether a study is aiming to detect differential gene expression between independent samples or whether co-expressed genes should be identified. We make recommendations about the most appropriate method to use

    Male-biased genes are overrepresented among novel Drosophila pseudoobscura sex-biased genes

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    BACKGROUND: The origin of functional innovation is among the key questions in biology. Recently, it has been shown that new genes could arise from non-coding DNA and that such novel genes are often involved in male reproduction. RESULTS: With the aim of identifying novel genes, we used the technique "generation of longer cDNA fragments from serial analysis of gene expression (SAGE) tags for gene identification (GLGI)" to extend 84 sex-biased 3'end SAGE tags that previously could not be mapped to the D. pseudoobscura transcriptome. Eleven male-biased and 33 female-biased GLGI fragments were obtained, of which 5 male-biased and 3 female-biased tags corresponded to putatively novel genes. This excess of novel genes with a male-biased gene expression pattern is consistent with previous results, which found novel genes to be primarily expressed in male reproductive tissues. 5' RACE analysis indicated that these novel transcripts are very short in length and could contain introns. Interspecies comparisons revealed that most novel transcripts show evidence for purifying selection. CONCLUSION: Overall, our data indicate that among sex-biased genes a considerable number of novel genes (approximately 2-4%) exist in D. pseudoobscura, which could not be predicted based on D. melanogaster gene models

    Gene expression analysis indicates extensive genotype-specific crosstalk between the conjugative F-plasmid and the E. coli chromosome

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    BACKGROUND: Plasmids are an important component of the bacterial genome, but the crosstalk between genes encoded on the chromosome and on the plasmid is still poorly understood. RESULTS: We performed a large-scale survey for genes on the E. coli chromosome that are affected by the presence of the conjugative F-plasmid (crosstalk). The expression pattern of about 4% (107 genes) of the genes encoded by the chromosome was affected by the presence of the F-plasmid. Comparing two different Escherichia coli strains, MG1655 and DH5α, we found a strong host genotype-specific crosstalk of the host chromosome with the F-plasmid. About 88% of the genes affected by the presence of the F-plasmid showed a significant plasmid by host genotype interaction, i.e. the presence of the F-plasmid resulted in a different gene expression in the two host genotypes. Less than 12% of the genes showed an additive effect of gene expression, i.e. host genotype independent crosstalk between plasmid and host chromosome. CONCLUSION: We propose that epistatic effects also contribute to the maintenance of F-plasmids in natural populations

    The life cycle of Drosophila orphan genes

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    Funding: Austrian Science Funds (FWF) (P22834).Orphans are genes restricted to a single phylogenetic lineage and emerge at high rates. While this predicts an accumulation of genes, the gene number has remained remarkably constant through evolution. This paradox has not yet been resolved. Because orphan genes have been mainly analyzed over long evolutionary time scales, orphan loss has remained unexplored. Here we study the patterns of orphan turnover among close relatives in the Drosophila obscura group. We show that orphans are not only emerging at a high rate, but that they are also rapidly lost. Interestingly, recently emerged orphans are more likely to be lost than older ones. Furthermore, highly expressed orphans with a strong male-bias are more likely to be retained. Since both lost and retained orphans show similar evolutionary signatures of functional conservation, we propose that orphan loss is not driven by high rates of sequence evolution, but reflects lineage-specific functional requirements.Publisher PDFPeer reviewe

    Mapping Accuracy of Short Reads from Massively Parallel Sequencing and the Implications for Quantitative Expression Profiling

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    BACKGROUND:Massively parallel sequencing offers an enormous potential for expression profiling, in particular for interspecific comparisons. Currently, different platforms for massively parallel sequencing are available, which differ in read length and sequencing costs. The 454-technology offers the highest read length. The other sequencing technologies are more cost effective, on the expense of shorter reads. Reliable expression profiling by massively parallel sequencing depends crucially on the accuracy to which the reads could be mapped to the corresponding genes. METHODOLOGY/PRINCIPAL FINDINGS:We performed an in silico analysis to evaluate whether incorrect mapping of the sequence reads results in a biased expression pattern. A comparison of six available mapping software tools indicated a considerable heterogeneity in mapping speed and accuracy. Independently of the software used to map the reads, we found that for compact genomes both short (35 bp, 50 bp) and long sequence reads (100 bp) result in an almost unbiased expression pattern. In contrast, for species with a larger genome containing more gene families and repetitive DNA, shorter reads (35-50 bp) produced a considerable bias in gene expression. In humans, about 10% of the genes had fewer than 50% of the sequence reads correctly mapped. Sequence polymorphism up to 9% had almost no effect on the mapping accuracy of 100 bp reads. For 35 bp reads up to 3% sequence divergence did not affect the mapping accuracy strongly. The effect of indels on the mapping efficiency strongly depends on the mapping software. CONCLUSIONS/SIGNIFICANCE:In complex genomes, expression profiling by massively parallel sequencing could introduce a considerable bias due to incorrectly mapped sequence reads if the read length is short. Nevertheless, this bias could be accounted for if the genomic sequence is known. Furthermore, sequence polymorphisms and indels also affect the mapping accuracy and may cause a biased gene expression measurement. The choice of the mapping software is highly critical and the reliability depends on the presence/absence of indels and the divergence between reads and the reference genome. Overall, we found SSAHA2 and CLC to produce the most reliable mapping results
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