Diversity of eukaryotic and prokaryotic microbiota revealed by metabarcoding in Neotropical floodplain lakes.

The diversity of eukaryotic and prokaryotic communities has been assessed by morphological and genetic approaches, which are used to characterize the microbiota in different environments. Here, planktonic prokaryotic and eukaryotic communities of the Araguaia River, located in the Central region of Brazil, were analyzed based on metabarcoding analysis of rRNA genes to evaluate the diversity of these groups in tropical floodplain lakes. Also, we tested their spatial concordance throughout the Araguaia river. Water samples were collected from 8 floodplain lakes in Araguaia River. The 16S and 18S rRNA genes were amplified and sequenced using Illumina MiSeq. For eukaryotes, 34,242 merged reads were obtained and 225 distinct OTUs were delineated, of which 106 OTUs were taxonomically classified. For prokaryotes, 26,426 sequences were obtained and 351 OTUs were detected. Of them, 231 were classified in at least one taxonomic category. The most representative eukaryotes belonged to Ciliophora, Chlorophyta and Charophyta. The prokaryotic phylum with the most OTUs classified were Proteobacteria, Actinobacteria and Bacteroidetes. The lakes did not show spatial concordance when comparing the similarity between their microbiota. The knowledge of freshwater biodiversity using DNA sequencing for important rivers, such as Araguaia River, can improve microbiota inventories of tropical biodiversity hotspots.

Mantel test in population genetics.

The comparison of genetic divergence or genetic distances, estimated by pairwise FST and related statistics, with geographical distances by Mantel test is one of the most popular approaches to evaluate spatial processes driving population structure. There have been, however, recent criticisms and discussions on the statistical performance of the Mantel test. Simultaneously, alternative frameworks for data analyses are being proposed. Here, we review the Mantel test and its variations, including Mantel correlograms and partial correlations and regressions. For illustrative purposes, we studied spatial genetic divergence among 25 populations of Dipteryx alata ("Baru"), a tree species endemic to the Cerrado, the Brazilian savannas, based on 8 microsatellite loci. We also applied alternative methods to analyze spatial patterns in this dataset, especially a multivariate generalization of Spatial Eigenfunction Analysis based on redundancy analysis. The different approaches resulted in similar estimates of the magnitude of spatial structure in the genetic data. Furthermore, the results were expected based on previous knowledge of the ecological and evolutionary processes underlying genetic variation in this species. Our review shows that a careful application and interpretation of Mantel tests, especially Mantel correlograms, can overcome some potential statistical problems and provide a simple and useful tool for multivariate analysis of spatial patterns of genetic divergence.