Estimation of Low Quantity Genes: A Hierarchical Model for Analyzing Censored Quantitative Real-Time PCR Data

<div><p>Analysis of gene quantities measured by quantitative real-time PCR (qPCR) can be complicated by observations that are below the limit of quantification (LOQ) of the assay. A hierarchical model estimated using MCMC methods was developed to analyze qPCR data of genes with observations that fall below the LOQ (censored observations). Simulated datasets with moderate to very high levels of censoring were used to assess the performance of the model; model results were compared to approaches that replace censored observations with a value on the log scale approximating zero or with values ranging from one to the LOQ of ten gene copies. The model was also compared to a Tobit regression model. Finally, all approaches for handling censored observations were evaluated with DNA extracted from samples that were spiked with known quantities of the antibiotic resistance gene <i>tetL</i>. For the simulated datasets, the model outperformed substitution of all values from 1–10 under all censoring scenarios in terms of bias, mean square error, and coverage of 95% confidence intervals for regression parameters. The model performed as well or better than substitution of a value approximating zero under two censoring scenarios (approximately 57% and 79% censored values). The model also performed as well or better than Tobit regression in two of three censoring scenarios (approximately 79% and 93% censored values). Under the levels of censoring present in the three scenarios of this study, substitution of any values greater than 0 produced the least accurate results. When applied to data produced from spiked samples, the model produced the lowest mean square error of the three approaches. This model provides a good alternative for analyzing large amounts of left-censored qPCR data when the goal is estimation of population parameters. The flexibility of this approach can accommodate complex study designs such as longitudinal studies.</p></div

Domestic Dogs in Rural Communities around Protected Areas: Conservation Problem or Conflict Solution?

<div><p>Although domestic dogs play many important roles in rural households, they can also be an important threat to the conservation of wild vertebrates due to predation, competition and transmission of infectious diseases. An increasing number of studies have addressed the impact of dogs on wildlife but have tended to ignore the motivations and attitudes of the humans who keep these dogs and how the function of dogs might influence dog-wildlife interactions. To determine whether the function of domestic dogs in rural communities influences their interactions with wildlife, we conducted surveys in rural areas surrounding protected lands in the Valdivian Temperate Forests of Chile. Sixty percent of farm animal owners reported the use of dogs as one of the primary means of protecting livestock from predators. The probability of dog–wild carnivore interactions was significantly associated with the raising of poultry. In contrast, dog–wild prey interactions were not associated with livestock presence but had a significant association with poor quality diet as observed in previous studies. Dog owners reported that they actively encouraged the dogs to chase off predators, accounting for 25–75% of the dog–wild carnivore interactions observed, depending on the predator species. Humans controlled the dog population by killing pups and unwanted individuals resulting in few additions to the dog population through breeding; the importation of predominantly male dogs from urban areas resulted in a sex ratios highly dominated by males. These results indicate that dog interactions with wildlife are related to the role of the dog in the household and are directly influenced by their owners. To avoid conflict with local communities in conservation areas, it is important to develop strategies for managing dogs that balance conservation needs with the roles that dogs play in these rural households.</p></div

Best models to estimate the probability of owned dog interactions with carnivores and prey species.

<p>Summary of model selection to estimate the probability of owned dog interactions with carnivores and prey species. Models are ranked by AICc values. Columns include the number of variables (K), Akaike’s Information Criterion (AICc), distance from the lowest AICc (Δ AICc), and Akaike’s model weight (ωi). Models showed include only those with a ΔAICc ≤2. See table1 in Supplementary material for all competing models.</p

Farm animal ownership.

<p>Farm animal ownership in rural households around three protected areas in southern Chile.</p

Dog-wildlife interactions reported by dog owners.

<p>Number of households with dogs (n = 123) indicating dog-wildlife interactions observed during the previous year.</p

Demography and management of rural dogs.

<p>^a 36% of the pups that died were killed by the dog owner;</p><p>^b 92.6% males and 7.4% females;</p><p>^c 7.5% killed by the dog owner.</p><p>Demography and management of domestic dogs in rural areas around three protected areas in Southern Chile.</p

Model-averaged odds ratios of rural dogs interacting with carnivore and prey species.

<p>Model-averaged parameter estimates shown as odds ratios and 95% confidence intervals for explaining rural dog interactions with carnivore and prey species. Odds Ratios <1 indicate a negative association with occurrence while Odds Ratios >1 indicate a positive association with occurrence.</p

Measures of farm animal protection in rural areas in southern Chile.

<p>Measures of farm animal protection against carnivore predators reported by rural interviewees around three protected areas in southern Chile.</p

Comparison (mean of the group) of the tissue (jejunum, ileum, cecum, and colon) microbiomes of pigs at 7 or 9 weeks of age that were not challenged (control) or were challenged with <i>S</i>. <i>enterica</i> serovar Typhimurium strain 798 (Salmonella).

<p>The colors represent the same genus in all four panels. A figure legend can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0139106#pone.0139106.s005" target="_blank">S1 Table</a>.</p

Principal coordinate analysis graphs comparing the total compositions of the microbiomes in four pig tissues (jejunum, ileum, cecum, and colon) at various times.

<p>The symbol shape associated with each data point represents the time of sample collection (5 (upside down triangle), 7 (triangles), 9 (circles), and 11 (squares) weeks of age). The symbol color reflects the treatment: maroon = non-challenged controls, red = challenged with <i>S</i>. <i>enterica</i> serovar Typhimurium strain 798, green = <i>Lawsonia intracellularis</i> strain PHE/MN1-00, blue = both challenge pathogens.</p