NGSPanPipe: A Pipeline for Pan-genome Identification in Microbial Strains from Experimental Reads

Pangenomics in Microbial and Crop Research: Progress, Applications, and Perspectives

Advances in sequencing technologies and bioinformatics tools have fueled a renewed interest in whole genome sequencing efforts in many organisms. The growing availability of multiple genome sequences has advanced our understanding of the within-species diversity, in the form of a pangenome. Pangenomics has opened new avenues for future research such as allowing dissection of complex molecular mechanisms and increased confidence in genome mapping. To comprehensively capture the genetic diversity for improving plant performance, the pangenome concept is further extended from species to genus level by the inclusion of wild species, constituting a super-pangenome. Characterization of pangenome has implications for both basic and applied research. The concept of pangenome has transformed the way biological questions are addressed. From understanding evolution and adaptation to elucidating host–pathogen interactions, finding novel genes or breeding targets to aid crop improvement to design effective vaccines for human prophylaxis, the increasing availability of the pangenome has revolutionized several aspects of biological research. The future availability of high-resolution pangenomes based on reference-level near-complete genome assemblies would greatly improve our ability to address complex biological problems.

Distinctive features gleaned from the comparative genomes analysis of clinical and non-clinical isolates of Klebsiella pneumoniae

It is of interest to describe the distinctive features gleaned from the comparative genome analysis of clinical and non-clinical isolates of Klebsiella pneumoniae. The core genome of K. pneumoinae consisted of 3568 genes. Comparative genome analysis shows that mdtABCD, toxin-antitoxin systems are unique to clinical isolates and catB, benA, and transporter genes for citrate utilization are exclusive to non-clinical isolates. We further noted aromatic compound degrading genes in non-clinical isolates unlike in the later isolates. We grouped 88 core genes into 3 groups linked to infections, drug-resistance or xenobiotic metabolism using codon usage variation analysis. It is inferred using the neutrality plot analysis of GC12 with GC3 that codon usage variation is dominant over mutation pressure. Thus, we document data to distinguish clinical and non-clinical isolates of K. pneumoniae using comparative genomes analysis for understanding of genome diversity during speciation.