History Shaped the Geographic Distribution of Genomic Admixture on the Island of Puerto Rico

Contemporary genetic variation among Latin Americans human groups reflects population migrations shaped by complex historical, social and economic factors. Consequently, admixture patterns may vary by geographic regions ranging from countries to neighborhoods. We examined the geographic variation of admixture across the island of Puerto Rico and the degree to which it could be explained by historic and social events. We analyzed a census-based sample of 642 Puerto Rican individuals that were genotyped for 93 ancestry informative markers (AIMs) to estimate African, European and Native American ancestry. Socioeconomic status (SES) data and geographic location were obtained for each individual. There was significant geographic variation of ancestry across the island. In particular, African ancestry demonstrated a decreasing East to West gradient that was partially explained by historical factors linked to the colonial sugar plantation system. SES also demonstrated a parallel decreasing cline from East to West. However, at a local level, SES and African ancestry were negatively correlated. European ancestry was strongly negatively correlated with African ancestry and therefore showed patterns complementary to African ancestry. By contrast, Native American ancestry showed little variation across the island and across individuals and appears to have played little social role historically. The observed geographic distributions of SES and genetic variation relate to historical social events and mating patterns, and have substantial implications for the design of studies in the recently admixed Puerto Rican population. More generally, our results demonstrate the importance of incorporating social and geographic data with genetics when studying contemporary admixed populations

Bacterial community dynamics in full-scale activated sludge bioreactors: operational and ecological factors driving community assembly and performance.

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a "structure-function" paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors' communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation

Non-Metric Multi-Dimensional Scaling (NMDS) ordination diagram of temporal variations in bacterial community structure.

<p>The ordination is based on a Bray-Curtis similarity matrix of the square-root transformed abundance data obtained from the T-RFLP profiles from both CAS bioreactors: HC (•) and LC (▪). The open arrows point to the first sampling time and the black arrows point to the last sampling time for each bioreactor. Each scatter point in the plot represents the bacterial community in a particular bioreactor at a particular point in time. The separation between the points is relative to their similarity in terms of community composition and they are connected chronologically to show their relative changes throughout the sampling period. The stress value for the tridimensional NMDS ordination is shown. Two non-parametric analyses were calculated to test the significance of the differences observed in the NMDS ordination plot: One-way Analysis of Similarities (ANOSIM): <b><i>R</i></b><b> = 0.5451 </b><b>(</b><b><i>P</i></b><b><0.0001)</b>; One-way Non-Parametric Multivariate Analysis of Variances (NPMANOVA): <b><i>F</i></b><b> = 4.014 (</b><b><i>P</i></b><b><0.0001)</b>.</p

Rényi diversity profiles of the bacterial communities from the CAS bioreactors.

<p>The profiles were derived from the T-RFLP raw abundance matrices: HC (•) and LC (▪). The x- and y-axes show the alpha value of the Rényi’s formula and their associated Rényi diversity profile values (H<i>α</i>), respectively. Rényi profile values at the scales of 1, 2 and infinite are proportional to Shannon diversity index, Simpson diversity index and Berger–Parker diversity index, respectively (see Kindt and Coe <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0042524#pone.0042524-Legendre1" target="_blank">[47]</a> for further information).</p

Canonical Correspondence Analysis (CCA) of the relationship between operational parameters and bacterial community structure.

<p>The ordination was based on square-root transformed data of the measured operational parameters (arrows): BOD-influent (A), Flow (B), F/M (C), HRT (D), NO₃^–N (E), pH (F), PO₄³⁻ (G), SRT (H), Temperature (I), TSS-influent (J); and the T-RFLP abundance profiles from both CAS bioreactors: HC (•), LC (▪). Numbers next to symbols indicate the relative sampling time. An unrestricted Monte-Carlo permutation test was performed (1000 permutations) to determine the statistical significance of the relationship between the environmental variables and the canonical axes.</p

Temporal variations of TSS (A) and BOD (B) removal efficiencies.

<p>Percentage values represent the difference between measured influent and effluent concentrations of TSS and BOD for both WWTP: HC (•), LC (▪).</p

Correlation analyses of the relationship between plants’ influent and effluent BOD concentrations.

<p>LC (A) and HC (B). The Pearson’s correlation coefficient (r), the linear regression coefficient of determination (R²) and the probability value (<i>P</i>) of the analysis are shown.</p

Comparison of the richness of bacterial populations (OTUs) detected in each CAS bioreactor per restriction enzyme.^a

a<p>CAS: Conventional Activated Sludge; OTU: Operational Taxonomic Unit.</p>b<p>WWTP: Wastewater Treatment Plant.</p>c<p>TRFs: Terminal Restriction Fragments; Values in parentheses represent the total number of distinctive TRFs detected per restriction enzyme in both bacterial communities combined during the 12 samplings times.</p