Microcystis, the dominant species among cyanobacterial blooms, normally forms colonies under natural conditions but exists as single cells or paired cells in axenic laboratory cultures after long-term cultivation. Here, a bloom-forming Microcystis aeruginosa strain CHAOHU 1326 was studied because it presents a colonial morphology and grows on the water surface during axenic laboratory culturing. We first examined the morphological features of strain CHAOHU 1326 and three other unicellular M. aeruginosa strains FACHB-925, FACHB-940, and FACHB-975 cultured under the same conditions by scanning and transmission electron microscopy. Then, we compared the extracellular polysaccharide (EPS)-producing ability of colonial strain CHAOHU 1326 to that of the three unicellular M. aeruginosa strains, and found that strain CHAOHU 1326 produced a higher amount of EPS than the other strains during growth. Moreover, based on genome sequencing, multiple gene clusters implicated in EPS biosynthesis and a cluster of 12 genes predicted to be involved in gas vesicle synthesis in strain CHAOHU 1326 were detected. These predicted genes were all functional and expressed in M. aeruginosa CHAOHU 1326 as determined by reverse transcription PCR. These findings provide a physiological and genetic basis to better understand colony formation and buoyancy control during M. aeruginosa blooming.

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Horizontal transfer of catabolic plasmids is used in genetic bioaugmentation for environmental pollutant remediation. In this study, we examined the effectiveness of genetic bioaugmentation with dioxin-catabolic plasmids harbored by Rhodococcus sp. strain p52 in laboratory-scale sequencing batch reactors (SBRs). During 100 days of operation, bioaugmentation decreased the dibenzofuran content (120 mg L) in the synthetic wastewater by 32.6%-100% of that in the nonbioaugmented SBR. Additionally, dibenzofuran was removed to undetectable levels in the bioaugmented SBR, in contrast, 46.8 ± 4.1% of that in the influent remained in the nonbioaugmented SBR after 96 days. Moreover, transconjugants harboring pDF01 and pDF02 were isolated from the bioaugmented SBR after 2 days, and their abilities to degrade dibenzofuran were confirmed. After 80 days, the copy numbers of strain p52 decreased by 3 orders of magnitude and accounted for 0.05 ± 0.01% of the total bacteria, while transconjugants were present at around 10 copies mL sludge and accounted for 8.2 ± 0.3% of the total bacteria. Evaluation of the bacterial community profile of sludge by high-throughput 16S rRNA gene sequencing revealed that genetic bioaugmentation led to a bacterial community with an even distribution of genera in the SBR. This study demonstrates the promise of genetic bioaugmentation with catabolic plasmids for dioxins remediation.

In 2001, Sen and Churchill reported a general Bayesian framework for quantitative trait loci (QTL) mapping in inbred line crosses. The framework is a powerful one, as many QTL mapping methods can be represented as special cases and many important considerations are accommodated. These considerations include accounting for covariates, nonstandard crosses, missing genotypes, genotyping errors, multiple interacting QTL, and nonnormal as well as multivariate phenotypes. The dimension of a multivariate phenotype easily handled within the framework is bounded by the number of subjects, as a full-rank covariance matrix describing correlations across the phenotypes is required. We address this limitation and extend the Sen-Churchill framework to accommodate expression quantitative trait loci (eQTL) mapping studies, where high-dimensional gene-expression phenotypes are obtained via microarrays. Doing so allows for the precise comparison of existing eQTL mapping approaches and facilitates the development of an eQTL interval-mapping approach that shares information across transcripts and improves localization of eQTL. Evaluations are based on simulation studies and a study of diabetes in mice.T HE quantitative trait loci (QTL) mapping framework developed by Sen and Churchill (2001), referred to hereinafter as the Sen-Churchill framework, unifies many methods for QTL mapping in inbred line crosses. The seminal work of Lander and Botstein (1989) and subsequent methods including Haley-Knott regression (1992), composite interval mapping, and multiple QTL mapping ( Jansen 1993;Zeng 1993Zeng , 1994Jansen and Stam 1994), are all represented, at least approximately, as special cases of the framework. The framework also accounts for covariates, nonstandard cross designs, missing genotype data, genotyping errors, multiple interacting QTL, and nonnormal as well as multivariate phenotypes. As a result, it provides a powerful approach to localize the genetic basis of quantitative traits.There has been much interest recently in identifying the genetic basis of thousands of gene-expression traits measured via microarrays (Brem et al. 2002;Schadt et al. 2003;Yvert et al. 2003;Cox 2004). The multi-trait version of the Sen-Churchill framework is based on the multivariate normal distribution. This approach becomes problematic when the number of traits is larger than the number of subjects, as the estimated covariance matrix will have less than full rank. To address this, we here extend the Sen-Churchill framework to accommodate expression phenotypes. We first highlight aspects of the Sen-Churchill framework important to our development, and then detail the extension. We show that the extended framework generalizes the currently available expression QTL (eQTL) mapping methods and facilitates the development of an approach that allows for both interval mapping of eQTL and information sharing across transcripts. Evaluations are based on simulation studies and a study of diabetes in mice. Generalizations of the framework are also discuss...