CoreCruncher: Fast and Robust Construction of Core Genomes in Large Prokaryotic Data Sets

Abstract

The core genome represents the set of genes shared by all, or nearly all, strains of a given population or species of prokaryotes. Inferring the core genome is integral to many genomic analyses, however, most methods rely on the comparison of all the pairs of genomes; a step that is becoming increasingly difficult given the massive accumulation of genomic data. Here, we present CoreCruncher; a program that robustly and rapidly constructs core genomes across hundreds or thousands of genomes. CoreCruncher does not compute all pairwise genome comparisons and uses a heuristic based on the distributions of identity scores to classify sequences as orthologs or paralogs/xenologs. Although it is much faster than current methods, our results indicate that our approach is more conservative than other tools and less sensitive to the presence of paralogs and xenologs. CoreCruncher is freely available at https://github.com/lbobay/CoreCruncher. CoreCruncher is written in Python 3.7 but can also run on Python 2.7 without modification. It requires the python library Numpy and either Usearch or Blast. Certain options require the programs muscle or mafft.

Genome size distributions in bacteria and archaea are strongly linked to evolutionary history at broad phylogenetic scales

“…We used the resulting median dN/dS of our representative genomes for further analysis. In order to examine the effect of genes’ selection on final dN/dS estimations, we randomly selected 40 genera and identified their core genes using CoreCruncher [ 84 ] using usearch [ 85 ] and the default parameters except for -score 80. We estimated the pairwise dN/dS for each core gene using the approach described previously and estimated the median dN/dS for our genus-representative genomes.…”

Phylogenetic systematics of Butyrivibrio and Pseudobutyrivibrio genomes illustrate vast taxonomic diversity, open genomes and an abundance of carbohydrate-active enzyme family isoforms

“…Core and accessory genomic fragments were identified from the Prokka annotated genomic sequences (.ffn files) using Spine v0.3.1 (http://vfsmspineagent.fsm.northwestern.edu/index_age.html) [38]. A range of other defined parameters (70–100 % similarity and present in 50–100 % of genomes) were evaluated, with 90 % [38–40], and the default value of 100 % core [41–43] definitions, using the default value of 85 % identity. Core values of 100 and 85% identity were subsequently used as the pangenomics parameters.…”

“…html) [38]. A range of other defined parameters (70-100 % similarity and present in 50-100 % of genomes) were evaluated, with 90 % [38][39][40], and the default value of 100 % core [41][42][43] definitions, using the default value of 85 % identity. Core values of 100 and 85% identity were subsequently used as the pangenomics parameters.…”

Characterization of Expression and Epigenetic Features of Core Genes in Common Wheat

“…https://plants.ensembl.org/Triticum_aestivum/Info/Index (accessed on 1 May 2022). The core genes were then identified using the core cruncher with the default parameters [29]. The detailed parameters are python corecruncher_master.py -in input_folder -out out-put_folder -length 80% -score 90%.…”