Respondent-Driven Sampling in Participatory Research Contexts: Participant-Driven Recruitment

This article reports on the use of respondent-driven sampling (RDS) in participatory and community-based research. Participant-driven recruitment (PDR) retains all of the analytic capabilities of RDS while enhancing the role of respondents in framing research questions, instrument development, data interpretation, and other aspects of the research process. Merging the capabilities of RDS with participatory research methods, PDR creates new opportunities for engaging community members in research addressing social issues and in utilizing research findings within community contexts. This article outlines PDR’s synthesis of RDS and participatory research approaches, describes how PDR is implemented in community contexts, and provides two examples of the use of PDR, illustrating its process, potentials, and challenges

Improved ChIP-chip analysis by a mixture model approach

<p>Abstract</p> <p>Background</p> <p>Microarray analysis of immunoprecipitated chromatin (ChIP-chip) has evolved from a novel technique to a standard approach for the systematic study of protein-DNA interactions. In ChIP-chip, sites of protein-DNA interactions are identified by signals from the hybridization of selected DNA to tiled oligomers and are graphically represented as peaks. Most existing methods were designed for the identification of relatively sparse peaks, in the presence of replicates.</p> <p>Results</p> <p>We propose a data normalization method and a statistical method for peak identification from ChIP-chip data based on a mixture model approach. In contrast to many existing methods, including methods that also employ mixture model approaches, our method is more flexible by imposing less restrictive assumptions and allowing a relatively large proportion of peak regions. In addition, our method does not require experimental replicates and is computationally efficient. We compared the performance of our method with several representative existing methods on three datasets, including a spike-in dataset. These comparisons demonstrate that our approach is more robust and has comparable or higher power than the other methods, especially in the context of abundant peak regions.</p> <p>Conclusion</p> <p>Our data normalization and peak detection methods have improved performance to detect peak regions in ChIP-chip data.</p

Dynamics of Multiple Trafficking Behaviors of Individual Synaptic Vesicles Revealed by Quantum-Dot Based Presynaptic Probe

Although quantum dots (QDs) have provided invaluable information regarding the diffusive behaviors of postsynaptic receptors, their application in presynaptic terminals has been rather limited. In addition, the diffraction-limited nature of the presynaptic bouton has hampered detailed analyses of the behaviors of synaptic vesicles (SVs) at synapses. Here, we created a quantum-dot based presynaptic probe and characterized the dynamic behaviors of individual SVs. As previously reported, the SVs exhibited multiple exchanges between neighboring boutons. Actin disruption induced a dramatic decrease in the diffusive behaviors of SVs at synapses while microtubule disruption only reduced extrasynaptic mobility. Glycine-induced synaptic potentiation produced significant increases in synaptic and inter-boutonal trafficking of SVs, which were NMDA receptor- and actin-dependent while NMDA-induced synaptic depression decreased the mobility of the SVs at synapses. Together, our results show that sPH-AP-QD revealed previously unobserved trafficking properties of SVs around synapses, and the dynamic modulation of SV mobility could regulate presynaptic efficacy during synaptic activity

Computational analyses of eukaryotic promoters

Computational analysis of eukaryotic promoters is one of the most difficult problems in computational genomics and is essential for understanding gene expression profiles and reverse-engineering gene regulation network circuits. Here I give a basic introduction of the problem and recent update on both experimental and computational approaches. More details may be found in the extended references. This review is based on a summer lecture given at Max Planck Institute at Berlin in 2005

Forest-Stream Linkages: Effects of Terrestrial Invertebrate Input and Light on Diet and Growth of Brown Trout (Salmo trutta) in a Boreal Forest Stream

Subsidies of energy and material from the riparian zone have large impacts on recipient stream habitats. Human-induced changes, such as deforestation, may profoundly affect these pathways. However, the strength of individual factors on stream ecosystems is poorly understood since the factors involved often interact in complex ways. We isolated two of these factors, manipulating the flux of terrestrial input and the intensity of light in a 2×2 factorial design, where we followed the growth and diet of two size-classes of brown trout (Salmo trutta) and the development of periphyton, grazer macroinvertebrates, terrestrial invertebrate inputs, and drift in twelve 20 m long enclosed stream reaches in a five-month-long experiment in a boreal coniferous forest stream. We found that light intensity, which was artificially increased 2.5 times above ambient levels, had an effect on grazer density, but no detectable effect on chlorophyll a biomass. We also found a seasonal effect on the amount of drift and that the reduction of terrestrial prey input, accomplished by covering enclosures with transparent plastic, had a negative impact on the amount of terrestrial invertebrates in the drift. Further, trout growth was strongly seasonal and followed the same pattern as drift biomass, and the reduction of terrestrial prey input had a negative effect on trout growth. Diet analysis was consistent with growth differences, showing that trout in open enclosures consumed relatively more terrestrial prey in summer than trout living in covered enclosures. We also predicted ontogenetic differences in the diet and growth of old and young trout, where we expected old fish to be more affected by the terrestrial prey reduction, but we found little evidence of ontogenetic differences. Overall, our results showed that reduced terrestrial prey inputs, as would be expected from forest harvesting, shaped differences in the growth and diet of the top predator, brown trout

Extensive Evolutionary Changes in Regulatory Element Activity during Human Origins Are Associated with Altered Gene Expression and Positive Selection

Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS) sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species

The Cost of Male Aggression and Polygyny in California Sea Lions (Zalophus californianus)

In polygynous mating systems, males often increase their fecundity via aggressive defense of mates and/or resources necessary for successful mating. Here we show that both male and female reproductive behavior during the breeding season (June–August) affect female fecundity, a vital rate that is an important determinant of population growth rate and viability. By using 4 years of data on behavior and demography of California sea lions (Zalophus californianus), we found that male behavior and spatial dynamics—aggression and territory size—are significantly related to female fecundity. Higher rates of male aggression and larger territory sizes were associated with lower estimates of female fecundity within the same year. Female aggression was significantly and positively related to fecundity both within the same year as the behavior was measured and in the following year. These results indicate that while male aggression and defense of territories may increase male fecundity, such interactions may cause a reduction in the overall population growth rate by lowering female fecundity. Females may attempt to offset male-related reductions in female fecundity by increasing their own aggression—perhaps to defend pups from incidental injury or mortality. Thus in polygynous mating systems, male aggression may increase male fitness at the cost of female fitness and overall population viability

Modulators of Cytoskeletal Reorganization in CA1 Hippocampal Neurons Show Increased Expression in Patients at Mid-Stage Alzheimer's Disease

During the progression of Alzheimer's disease (AD), hippocampal neurons undergo cytoskeletal reorganization, resulting in degenerative as well as regenerative changes. As neurofibrillary tangles form and dystrophic neurites appear, sprouting neuronal processes with growth cones emerge. Actin and tubulin are indispensable for normal neurite development and regenerative responses to injury and neurodegenerative stimuli. We have previously shown that actin capping protein beta2 subunit, Capzb2, binds tubulin and, in the presence of tau, affects microtubule polymerization necessary for neurite outgrowth and normal growth cone morphology. Accordingly, Capzb2 silencing in hippocampal neurons resulted in short, dystrophic neurites, seen in neurodegenerative diseases including AD. Here we demonstrate the statistically significant increase in the Capzb2 expression in the postmortem hippocampi in persons at mid-stage, Braak and Braak stage (BB) III-IV, non-familial AD in comparison to controls. The dynamics of Capzb2 expression in progressive AD stages cannot be attributed to reactive astrocytosis. Moreover, the increased expression of Capzb2 mRNA in CA1 pyramidal neurons in AD BB III-IV is accompanied by an increased mRNA expression of brain derived neurotrophic factor (BDNF) receptor tyrosine kinase B (TrkB), mediator of synaptic plasticity in hippocampal neurons. Thus, the up-regulation of Capzb2 and TrkB may reflect cytoskeletal reorganization and/or regenerative response occurring in hippocampal CA1 neurons at a specific stage of AD progression

Quantitative Models of the Mechanisms That Control Genome-Wide Patterns of Transcription Factor Binding during Early Drosophila Development

Transcription factors that drive complex patterns of gene expression during animal development bind to thousands of genomic regions, with quantitative differences in binding across bound regions mediating their activity. While we now have tools to characterize the DNA affinities of these proteins and to precisely measure their genome-wide distribution in vivo, our understanding of the forces that determine where, when, and to what extent they bind remains primitive. Here we use a thermodynamic model of transcription factor binding to evaluate the contribution of different biophysical forces to the binding of five regulators of early embryonic anterior-posterior patterning in Drosophila melanogaster. Predictions based on DNA sequence and in vitro protein-DNA affinities alone achieve a correlation of ∼0.4 with experimental measurements of in vivo binding. Incorporating cooperativity and competition among the five factors, and accounting for spatial patterning by modeling binding in every nucleus independently, had little effect on prediction accuracy. A major source of error was the prediction of binding events that do not occur in vivo, which we hypothesized reflected reduced accessibility of chromatin. To test this, we incorporated experimental measurements of genome-wide DNA accessibility into our model, effectively restricting predicted binding to regions of open chromatin. This dramatically improved our predictions to a correlation of 0.6–0.9 for various factors across known target genes. Finally, we used our model to quantify the roles of DNA sequence, accessibility, and binding competition and cooperativity. Our results show that, in regions of open chromatin, binding can be predicted almost exclusively by the sequence specificity of individual factors, with a minimal role for protein interactions. We suggest that a combination of experimentally determined chromatin accessibility data and simple computational models of transcription factor binding may be used to predict the binding landscape of any animal transcription factor with significant precision