Molecular Characterization of Potential Microcystin-Producing Cyanobacteria in Lake Ontario Embayments and Nearshore Waters▿

The distribution and genotypic variation of potential microcystin (MC) producers along the southern and eastern shores of Lake Ontario in 2001 and 2003 were examined using a suite of PCR primers. Cyanobacterial, Microcystis sp., and Microcystis-specific toxin primer sets identified shoreline distribution of cyanobacterial DNA (in 97% of the stations) and MC synthetase genes (in 50% of the stations). Sequence analysis of a partial mcyA amplicon targeting Microcystis, Anabaena, and Planktothrix species indicated that the Microcystis sp. genotype was the dominant MC genotype present and revealed a novel Microcystis-like sequence containing a 6-bp insert. Analysis of the same samples with genus-specific mcyE primers confirmed that the Microcystis sp. genotype was the dominant potential MC producer. Genotype compositions within embayments were relatively homogenous compared to those for shoreline and tributary samples. MC concentrations along the shoreline exhibited both temporal and spatial differences as evidenced by the protein phosphatase inhibition assay, at times exceeding the World Health Organization guideline value for drinking water of 1.0 μg MC-LReq liter−1. MC genotypes are widespread along the New York State shoreline of Lake Ontario, appear to originate nearshore, and can be carried through the lake via wind and surface water current patterns

A Guide to the Chloroplast Transcriptome Analysis Using RNA-Seq

Since its first use in plants in 2007, high-throughput RNA sequencing (RNA-Seq) has generated a vast amount of data for both model and nonmodel species. Organellar transcriptomes, however, are virtually always overlooked at the data analysis step. We therefore developed ChloroSeq, a bioinformatic pipeline aimed at facilitating the systematic analysis of chloroplast RNA metabolism, and we provide here a step-by--step user's manual. Following the alignment of quality-controlled data to the genome of interest, ChloroSeq measures genome expression level along with splicing and RNA editing efficiencies. When used in combination with the Tuxedo suite (TopHat and Cufflinks), ChloroSeq allows the simultaneous analysis of organellar and nuclear transcriptomes, opening the way to a better understanding of nucleus-organelle cross talk. We also describe the use of R commands to produce publication-quality figures based on ChloroSeq outputs. The effectiveness of the pipeline is illustrated through analysis of an RNA-Seq dataset covering the transition from growth to maturation to senescence of Arabidopsis thaliana leaves