Jonas Warringer

Publications (42) View all

• Source

  Available from: Jeffrey Peter Townsend

  Article: Abundant gene-by-environment interactions in gene expression reaction norms to copper within Saccharomyces cerevisiae.

  Andrea Hodgins-Davis, Aleksandra B Adomas, Jonas Warringer, Jeffrey P Townsend
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  ABSTRACT: Genetic variation for plastic phenotypes potentially contributes phenotypic variation to populations that can be selected during adaptation to novel ecological contexts. However, the basis and extent of plastic variation that manifests in diverse environments remains elusive. Here we characterize copper reaction norms for mRNA abundance among five S. cerevisiae strains to a) describe population variation across the full range of ecologically relevant copper concentrations, from starvation to toxicity, and b) to test the hypothesis that plastic networks exhibit increased population variation for gene expression. We find that although the vast majority of the variation is small in magnitude (considerably less than two-fold), not just some, but most genes demonstrate variable expression across environments, across genetic backgrounds, or both. Plastically expressed genes included both genes regulated directly by copper-binding transcription factors Mac1 and Ace1 and genes indirectly responding to the downstream metabolic consequences of the copper gradient, particularly genes involved in copper, iron, and sulfur homeostasis. Copper-regulated gene networks exhibited more similar behavior within the population in environments where those networks have a large impact on fitness. Nevertheless, expression variation in genes like Cup1, important to surviving copper stress, was linked with variation in mitotic fitness and in the breadth of differential expression across the genome. By revealing a broader and deeper range of population variation, our results provide further evidence for the interconnectedness of genome-wide mRNA levels, their dependence on environmental context and genetic background, and the abundance of variation in gene expression that can contribute to future evolution.
  Genome Biology and Evolution 09/2012; · 4.62 Impact Factor
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  Available from: Jonas Warringer

  Article: Exploration of multivariate analysis in microbial coding sequence modeling.

  Tahir Mehmood, Jon Bohlin, Anja Bråthen Kristoffersen, Solve Sæbø, Jonas Warringer, Lars Snipen
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  ABSTRACT: Gene finding is a complicated procedure that encapsulates algorithms for coding sequence modeling, identification of promoter regions, issues concerning overlapping genes and more. In the present study we focus on coding sequence modeling algorithms; that is, algorithms for identification and prediction of the actual coding sequences from genomic DNA. In this respect, we promote a novel multivariate method known as Canonical Powered Partial Least Squares (CPPLS) as an alternative to the commonly used Interpolated Markov model (IMM). Comparisons between the methods were performed on DNA, codon and protein sequences with highly conserved genes taken from several species with different genomic properties. The multivariate CPPLS approach classified coding sequence substantially better than the commonly used IMM on the same set of sequences. We also found that the use of CPPLS with codon representation gave significantly better classification results than both IMM with protein (p < 0.001) and with DNA (p < 0.001). Further, although the mean performance was similar, the variation of CPPLS performance on codon representation was significantly smaller than for IMM (p < 0.001). The performance of coding sequence modeling can be substantially improved by using an algorithm based on the multivariate CPPLS method applied to codon or DNA frequencies.
  BMC Bioinformatics 05/2012; 13:97. · 2.75 Impact Factor
• Article: The Ashbya gossypii EF-1α promoter of the ubiquitously used MX cassettes is toxic to Saccharomyces cerevisiae.

  Roja Babazadeh, Soode Moghadas Jafari, Martin Zackrisson, Anders Blomberg, Stefan Hohmann, Jonas Warringer, Marcus Krantz
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  ABSTRACT: Protein overexpression based on introduction of multiple gene copies is well established. To improve purification or quantification, proteins are typically fused to peptide tags. In Saccharomyces cerevisiae, this has been hampered by multicopy toxicity of the TAP and GFP cassettes used in the global strain collections. Here, we show that this effect is due to the EF-1α promoter in the HIS3MX marker cassette rather than the tags per se. This promoter is frequently used in heterologous marker cassettes, including HIS3MX, KanMX, NatMX, PatMX and HphMX. Toxicity could be eliminated by promoter replacement or exclusion of the marker cassette. To our knowledge, this is the first report of toxicity caused by introduction of a heterologous promoter alone.
  FEBS letters 12/2011; 585(24):3907-13. · 3.54 Impact Factor
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  Available from: Jonas Warringer

  Article: A Partial Least Squares based algorithm for parsimonious variable selection.

  Tahir Mehmood, Harald Martens, Solve Sæbø, Jonas Warringer, Lars Snipen
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  ABSTRACT: In genomics, a commonly encountered problem is to extract a subset of variables out of a large set of explanatory variables associated with one or several quantitative or qualitative response variables. An example is to identify associations between codon-usage and phylogeny based definitions of taxonomic groups at different taxonomic levels. Maximum understandability with the smallest number of selected variables, consistency of the selected variables, as well as variation of model performance on test data, are issues to be addressed for such problems. We present an algorithm balancing the parsimony and the predictive performance of a model. The algorithm is based on variable selection using reduced-rank Partial Least Squares with a regularized elimination. Allowing a marginal decrease in model performance results in a substantial decrease in the number of selected variables. This significantly improves the understandability of the model. Within the approach we have tested and compared three different criteria commonly used in the Partial Least Square modeling paradigm for variable selection; loading weights, regression coefficients and variable importance on projections. The algorithm is applied to a problem of identifying codon variations discriminating different bacterial taxa, which is of particular interest in classifying metagenomics samples. The results are compared with a classical forward selection algorithm, the much used Lasso algorithm as well as Soft-threshold Partial Least Squares variable selection. A regularized elimination algorithm based on Partial Least Squares produces results that increase understandability and consistency and reduces the classification error on test data compared to standard approaches.
  Algorithms for Molecular Biology 12/2011; 6(1):27. · 1.35 Impact Factor
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  Available from: Jonas Warringer

  Article: Mining for genotype-phenotype relations in Saccharomyces using partial least squares.

  Tahir Mehmood, Harald Martens, Solve Saebø, Jonas Warringer, Lars Snipen
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  ABSTRACT: Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS) for mapping genotype-phenotype relations. Applying this methodology to an extensive data set for the model yeast Saccharomyces cerevisiae, we found that the relationship between genotype-phenotype involves surprisingly few genes in the sense that an overwhelmingly large fraction of the phenotypic variation can be explained by variation in less than 1% of the full gene reference set containing 5791 genes. These phenotype influencing genes were evolving 20% faster than non-influential genes and were unevenly distributed over cellular functions, with strong enrichments in functions such as cellular respiration and transposition. These genes were also enriched with known paralogs, stop codon variations and copy number variations, suggesting that such molecular adjustments have had a disproportionate influence on Saccharomyces yeasts recent adaptation to environmental changes in its ecological niche. BLAST and PLS based multivariate approach derived results that adhere to the known yeast phylogeny and gene ontology and thus verify that the methodology extracts a set of fast evolving genes that capture the phylogeny of the yeast strains. The approach is worth pursuing, and future investigations should be made to improve the computations of genotype signals as well as variable selection procedure within the PLS framework.
  BMC Bioinformatics 08/2011; 12:318. · 2.75 Impact Factor