Parameter estimation for robust HMM analysis of ChIP-chip data

Tiling arrays are an important tool for the study of transcriptional activity, protein-DNA interactions and chromatin structure on a genome-wide scale at high resolution. Although hidden Markov models have been used successfully to analyse tiling array data, parameter estimation for these models is typically ad hoc. Especially in the context of ChIP-chip experiments, no standard procedures exist to obtain parameter estimates from the data. Common methods for the calculation of maximum likelihood estimates such as the Baum-Welch algorithm or Viterbi training are rarely applied in the context of tiling array analysis. Results: Here we develop a hidden Markov model for the analysis of chromatin structure ChIP-chip tiling array data, using t emission distributions to increase robustness towards outliers. Maximum likelihood estimates are used for all model parameters. Two different approaches to parameter estimation are investigated and combined into an efficient procedure. Conclusion: We illustrate an efficient parameter estimation procedure that can be used for HMM based methods in general and leads to a clear increase in performance when compared to the use of ad hoc estimates. The resulting hidden Markov model outperforms established methods like TileMap in the context of histone modification studies.13 page(s

Development of Flax (<em>Linum usitatissimum L.)</em> Mutant Populations for Forward and Reverse Genetics

International audienceMutagenesis has long been used to increase genetic diversity in different crop species including cultivated flax. In particular, ethyl methane sulfonate (EMS) has been used to create large mutant populations that can be screened using TILLING to identify mutations in specific genes via a reverse genetics approach. Additionally, forward genetics can be used to identify mutants showing interesting phenotypes. Such approaches have been used to identify flax mutants showing modifications in fiber cell wall structure and seed metabolism. The creation and characterization of flax mutant populations is a powerful strategy for gene discovery and for introducing genetic variability in this species that has a narrow genetic base

The role of iron in phytoplankton photosynthesis, and the potential for iron-limitation of primary productivity in the sea

Iron supply has been suggested to influence phytoplankton biomass, growth rate and species composition, as well as primary productivity in both high and low NO3− surface waters. Recent investigations in the equatorial Pacific suggest that no single factor regulates primary productivity. Rather, an interplay of bottom-up (i.e., ecophysiological) and top-down (i.e., ecological) factors appear to control species composition and growth rates. One goal of biological oceanography is to isolate the effects of single factors from this multiplicity of interactions, and to identify the factors with a disproportionate impact. Unfortunately, our tools, with several notable exceptions, have been largely inadequate to the task. In particular, the standard technique of nutrient addition bioassays cannot be undertaken without introducing artifacts. These so-called ‘bottle effects’ include reducing turbulence, isolating the enclosed sample from nutrient resupply and grazing, trapping the isolated sample at a fixed position within the water column and thus removing it from vertical movement through a light gradient, and exposing the sample to potentially stimulatory or inhibitory substances on the enclosure walls. The problem faced by all users of enrichment experiments is to separate the effects of controlled nutrient additions from uncontrolled changes in other environmental and ecological factors. To overcome these limitations, oceanographers have sought physiological or molecular indices to diagnose nutrient limitation in natural samples. These indices are often based on reductions in the abundance of photosynthetic and other catalysts, or on changes in the efficiency of these catalysts. Reductions in photosynthetic efficiency often accompany nutrient limitation either because of accumulation of damage, or impairment of the ability to synthesize fully functional macromolecular assemblages. Many catalysts involved in electron transfer and reductive biosyntheses contain iron, and the abundances of most of these catalysts decline under iron-limited conditions. Reductions of ferredoxin or cytochrome f content, nitrate assimilation rates, and dinitrogen fixation rates are amongst the diagnostics that have been used to infer iron limitation in some marine systems. An alternative approach to diagnosing iron-limitation uses molecules whose abundance increases in response to iron-limitation. These include cell surface iron-transport proteins, and the electron transfer protein flavodoxin which replaces the Fe-S protein ferredoxin in many Fe-deficient algae and cyanobacteria