MetaSVs: A pipeline combining long and short reads for analysis and visualization of structural variants in metagenomes

Abstract

Structural variants (SVs, including large-scale insertions, deletions, inversions, and translocations) significantly impact the functions of genes in the microbial genome, and SVs in the microbiome are associated with diverse biological processes and human diseases. With the advancements in sequencing and bioinformatics technologies, increasingly, sequencing data and analysis tools are already being extensively utilized for microbiome SV analyses, leading to a higher demand for more dedicated SV analysis workflows. Moreover, due to the unique detection biases of various sequencing technologies, including short-read sequencing (such as Illumina platforms) and long-read sequencing (e.g., Oxford Nanopore and PacBio), SV discovery based on multiple platforms is necessary to comprehensively identify the wide variety of SVs. Here, we establish an integrated pipeline MetaSVs combining Nanopore long reads and Illumina short reads to analyze SVs in the microbial genomes from gut microbiome and further identify differential SVs that can be reflective of metabolic differences. Our pipeline provides researchers easy access to SVs and relevant metabolites in the microbial genomes without the requirement of specific technical expertise, which is particularly useful to researchers interested in metagenomic SVs but lacking sophisticated bioinformatic knowledge.

Keywords: hybrid sequencing; metagenome; microbiome; nanopore; structural variants.

Figure 1

Flowchart of microbial structural variants (SVs) analysis based on short and long reads. The software used is marked in red texts. KEGG, Kyoto Encyclopedia of Genes and Genomes.

Figure 2

Introduction to the main program for detecting metagenomic SVs. (A) The only input argument (the “config.ini” file) of the main program. The red fonts indicate the parameters that need to be modified for different projects and the green fonts indicate the annotation information marked by # at the beginning of the line. (B) The main program (call_SVs_procedure.py). (C) The shell scripts generated by the main program, the running process, and the results of the scripts. An example is given for step 12 (KEGG enrichment analysis), marked with red boxes. KEGG, Kyoto Encyclopedia of Genes and Genomes; SV, structural variant.

Figure 3

Structural variations (SVs) in the example human gut microbiome. (A) Number of SVs (including insertions, deletions, duplications, and translocations) in Anaerobutyricum hallii of the T1 and T2 groups. ***Wilcoxon test, p < 0.05. (B) Distribution of SVs on genes in reference MAG of A. hallii. The gray circle denotes the reference MAG, with the T1 group inside the circle and the T2 group outside. The result of functional enrichment of SV‐affected genes, including the number of genes (C) and the corresponding ko ID (D) mapped to each functional pathway based on KEGG; metabolism‐related pathways account for six of them; p values were from Fisher's test. KEGG, Kyoto Encyclopedia of Genes and Genomes; MAG, metagenome‐assembled genome.