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Morais, D. K.

Publications and source records attributed to Morais, D. K..

2 recordsLinked to original sources

Explorative meta-analysis of 417 extant archaeal genomes to predict their contribution to the total microbiome functionality

Unveiling the relationship between taxonomy and function in microbiomes is crucial to determine their contribution to ecosystem functioning. However, while the relationship between taxonomic and functional diversity in bacteria and fungi was reported, this is not the case for archaea. Here, we used a meta-analysis of completely annotated extant genomes of 417 taxonomically unique archaeal species to describe intergenome and intragenome redundancy of functions and to predict the extent of microbiome functionality on Earth contained within archaeal genomes using accumulation curves of all known functions from the level 3 of KEGG Orthology. We found that intergenome redundancy as functions present in multiple genomes was inversely related to intragenome redundancy as multiple copies of a gene in one genome, implying the trade of between additional copies of functionally important genes or a higher number of different genes. A logarithmic model described the relationship between functional diversity and species richness better than both the unsaturated and the saturated model, which suggests a limited total number of archaeal functions in contrast to the potential of bacteria and fungi. Using a global archaeal species richness estimate of 13,159, the logarithmic model predicts a total of 4,164.1 {+/-}2.9 KEGG level 3 functions while the non-parametric bootstrap estimate yields a lower bound of 2,994 {+/-}57 KEGG level 3 functions. Our approach not only highlights similarities in functional redundancy but also the difference in functional potential of archaea compared to other domains of life.

ecology

TAG.ME: Taxonomic Assignment of Genetic Markers for Ecology

1.BackgroundSequencing of amplified genetic markers, such as the 16S rRNA gene, have been extensively used to characterize microbial community composition. Recent studies suggested that Amplicon Sequences Variants (ASV) should replace the Operational Taxonomic Units (OTU), given the arbitrary definition of sequence identity thresholds used to define units. Alignment-free methods are an interesting alternative for the taxonomic classification of the ASVs, preventing the introduction of biases from sequence identity thresholds.\n\nResultsHere we present TAG.ME, a novel alignment-independent and amplicon-specific method for taxonomic assignment based on genetic markers. TAG.ME uses a multilevel supervised learning approach to create predictive models based on user-defined genetic marker genes. The predictive method can assign taxonomy to sequenced amplicons efficiently and effectively. We applied our method to assess gut and soil sample classification, and it outperformed alternative approaches, identifying a substantially larger proportion of species. Benchmark tests performed using the RDP database, and Mock communities reinforced the precise classification into deep taxonomic levels.\n\nConclusionTAG.ME presents a new approach to assign taxonomy to amplicon sequences accurately. Our classification model, trained with amplicon specific sequences, can address resolution issues not solved by other methods and approaches that use the whole 16S rRNA gene sequence. TAG.ME is implemented as an R package and is freely available at http://gabrielrfernandes.github.io/tagme/

bioinformatics