Comparing the influence of assembly processes governing bacterial community succession based on DNA and RNA data

Xiu Jia*, Francisco Dini-Andreote, Joana Falcão Salles

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

4 Citations (Scopus)
62 Downloads (Pure)


Quantifying which assembly processes structure microbiomes can assist prediction, manipulation, and engineering of community outcomes. However, the relative importance of these processes might depend on whether DNA or RNA are used, as they differ in stability. We hypothesized that. RNA-inferred community responses to (a)biotic fluctuations are faster than those inferred by DNA; the relative influence of variable selection is stronger in RNA-inferred communities (environmental factors are spatiotemporally heterogeneous), whereas homogeneous selection largely influences DNA-inferred communities (environmental filters are constant). To test these hypotheses, we characterized soil bacterial communities by sequencing both 16S rRNA amplicons from the extracted DNA and RNA transcripts across distinct stages of soil primary succession and quantified the relative influence of each assembly process using ecological null model analysis. Our results revealed that variations in α-diversity and temporal turnover were higher in RNA- than in DNA-inferred communities across successional stages, albeit there was a similar community composition; in line with our hypotheses, the assembly of RNA-inferred community was more closely associated with environmental variability (variable selection) than using the standard DNA-based approach, which was largely influenced by homogeneous selection. This study illustrates the need for benchmarking approaches to properly elucidate how community assembly processes structure microbial communities.

Original languageEnglish
Article number798
Number of pages14
Issue number6
Publication statusPublished - Jun-2020


  • Ecological modeling
  • Dispersal
  • Selection
  • Drift
  • Community turnover
  • 16S rRNA gene

Cite this