Operon prediction

The module promoter_prediction() integrates Neural Network Promoter Prediction 2.0 (NNPP), to predict the upstream promoter for each of the genes in the co-directional closely packed gene clusters [37]. The output is organized into a matrix via Promoter_file_parse(). The promoter prediction matrix will be integrated with proximon table and TUBs will be defined, using Prom_IGD_Clustering().

At this moment, an operon is defined as a cluster of two or more co-directional and closely packed genes with a promoter upstream of the first gene. As the structure of operon indicates, an operon starts with a promoter and ends with a terminator, sandwiching multiple genes within. However, the presence of a promoter downstream of the last gene of the operonic cluster could also signify the end of an operon and start of a new TUB for gene (i + 1). Therefore, to redefine, an operon is a gene cluster delimited by an upstream and downstream promoter indicating the start and end of the operon, respectively.

Unlike Prom_IGD_Clustering(), where co-directionality, IGD and presence of promoter were considered to define an operon, the module Promoter_clustering() predicts the operons without considering intergenic distance at all. The pipeline compiles and exports the proximon pairs, and operons in tab-delimited files. Moreover, transitional information such as gene prediction file, upstream and downstream coordinates and fasta files are also available to the user for further analysis (Fig. ​(Fig.11).

MetaRon was implemented on whole-genome, simulated genomes, draft genome and whole-metagenomes, thus demonstrating its performance consistency at different levels of data complexity. The reason was to test the pipeline with different levels of data complexity, both in terms of diversity, information and data format such as, whole-genome or multiple scaftigs. For each of the data input, operons were identified, however, only the metagenomic data was analyzed in detail for its association with type 2 diabetes (T2D).