Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms

Table 1 Network methods and their adaptation to biological questions

Network term	Term description	Biological meaning in this work
Node	Single unit of a graph	A V4 sequence
Edge	Connection between two nodes	Sequence similarity between two V4 sequences
Assortativity	Measure of the preferential connection between a set of nodes of interest	Evaluation of similarity of a set of sequences from the same habitat or location (for example, if sequences from one habitat are more similar to one another than they are similar to sequences from other habitats, their assortativity will be high. Environments with distinctive similar V4 will have such a high assortativity). See Figure 2C.
Closeness	Measure of the centrality/peripherality of a node in a network	Measure of sequence divergence relative to the rest of the dataset (for example, divergent sequences (with respect to the rest of the dataset) have a low closeness and tend to be more peripheral as they share less similarity to other sequences). See Figure 2D.
Shortest path	Shortest distance between a pair of nodes	Measure to quantify the divergence between a pair of sequences (for example, a long shortest path between an environmental sequence and a sequence from a cultured ciliate indicates a high divergence between these sequences, since these sequences are not direct neighbors in the graph). See Figure 2D.

Listed are the most important network terms introduced into microbial ecology in the framework of this study. The table indicates how these methods can be applied to HTS data to address fundamental questions on the diversity and distribution of microbial organisms. HTS, high-throughput sequencing.

ISSN: 1741-7007