DOI: 10.5061/dryad.np5hqc04p
title: Data from: <em>Cryptocercus</em> genomes expand knowledge of adaptations to xylophagy and termite sociality

description: Subsociality and wood-eating or xylophagy are understood as key drivers in
 the evolution of eusociality in Blattodea (cockroaches and termites), two
 features observed in the cockroach genus Cryptocercus, the sister group of
 all termites. We present and analyse two new high-quality genomes from
 this genus, C. punctulatus from North America and C. meridianus from
 Southeast Asia, to explore the evolutionary transitions to xylophagy and
 subsociality within Blattodea. Our analyses reveal evidence of relaxed
 selection in both Cryptocercus and termites, indicating that a reduction
 in effective population size may have occurred in their subsocial
 ancestors. These findings challenge the expected positive correlation
 between dN/dS ratios and social complexity, as Cryptocercus exhibits
 elevated dN/dS values that may exceed those of eusocial termites.
 Additionally, we identify positive selection on mitochondrial ribosomal
 proteins and components of the NADH dehydrogenase complex, suggesting
 significant evolutionary changes in energy production. Future studies
 incorporating additional genomic data from diverse blattodea species are
 essential to elucidate the molecular mechanisms driving transitions to
 xylophagy and eusociality.
description: # Cryptocercus genomes expand knowledge of adaptations to xylophagy and
 termite sociality
 [https://doi.org/10.5061/dryad.np5hqc04p](https://doi.org/10.5061/dryad.np5hqc04p) ## Description of the data and file structure Genomic DNA was extracted from single snap-frozen legs of *Cryptocercus punctulatus* individuals collected in Virginia and reared in the laboratory. The tissue was homogenised on ice using a TissueRuptor and lysed with buffer CT and Proteinase K. RNA contamination was removed by RNase A treatment. High-molecular-weight DNA was captured using Circulomics Nanodisks and eluted in elution buffer. The extraction followed the Circulomics Insect Big DNA kit protocol (v0.20a). The resulting DNA was of high quality and high molecular weight, with fragment sizes of approximately 170 kb. Quality and size distribution were confirmed using an Agilent Femto Pulse system. Genome Annotations: cryptocercus_punctulatus.scaffolded.gff - Cryptocercus punctulatus annotations based on the genome that is stored on NCBI within the project PRJNA1188519 * Annotations of IRs with BitaCora: *_IRs.fa: protein sequences of Ionotropic Receptors IR_db.: sequence database used as input for BitaCora * Enriched GO terms, results of TopGo analyses: \_BP_table.txt (from cafe results) Significant_GOterms_selection.xlsx (from selection analyses) ### Files and variables #### File: cryptocercus_punctulatus.scaffolded.gff **Description:** genome annotations for C. punctulatus The following fasta files are named xx_IR.fa contain protein sequences of aannotatedIonotropic Receptors (IRs) #### File: pame_IRs.fa **Description:** IR sequences of P. americana #### File: rspe_IRs.fa **Description:** IR sequences of R. speratus #### File: cmer_IRs.fa **Description:** IR sequences of C. meridianus #### File: znev_IRs.fa **Description:** IR sequences of Z. nevadensis #### File: csec_IRs.fa **Description:** IR sequences of C. secundus #### File: elan_IRs.fa **Description:** IR sequences of E. langierum #### File: dpun_IRs.fa **Description:** IR sequences of D. punctata #### File: cpun_IRs.fa **Description:** IR sequences of C. punctulatus #### File: focc_IRs.fa **Description:** IR sequences of F. occidentalis #### File: mnat_IRs.fa **Description:** IR sequences of M. natalensis #### File: cfor_IRs.fa **Description:** IR sequences of C. formosanus #### File: bger_IRs.fa **Description:** IR sequences of B. germanica #### File: CryptocercusRootContractions_BP_table.txt **Description:** TopGo results for contractions at the Cryptocercus root ##### Variables * GO.ID: GO term ID * Term: GO term description * Annotated: Number of annotated GO terms * Significant: Number of genes of interest * Expected: Expected number * pvalue #### File: CryptocercusRootExpansions_BP_table.txt **Description:** TopGo results for expansions at the Cryptocercus root ##### Variables * GO.ID: GO term ID * Term: GO term description * Annotated: Number of annotated GO terms * Significant: Number of genes of interest * Expected: Expected number * pvalue #### File: CryptocercusBranchesContractions_BP_table.txt **Description:** TopGo results for contractions on all Cryptocercus branches ##### Variables * GO.ID: GO term ID * Term: GO term description * Annotated: Number of annotated GO terms * Significant: Number of genes of interest * Expected: Expected number * pvalue #### File: CryptocercusBranchesExpansions_BP_table.txt **Description:** TopGo results for expansions on all Cryptocercus branches ##### Variables * GO.ID: GO term ID * Term: GO term description * Annotated: Number of annotated GO terms * Significant: Number of genes of interest * Expected: Expected number * pvalue #### File: IR_db.msa **Description:** IR database alignment file #### File: IR_db.fasta **Description:** IR database fasta file #### File: IR_db.hmm **Description:** **HMMER** output, specifically a Hidden Markov Model (HMM) database related to ionotropic receptors (IR). #### File: Significant_GOterms_selection.csv **Description:** TopGo results for selection analyses ##### Variables * GO.ID: GO term ID * Term: GO term description * Annotated: Number of annotated GO terms * Significant: Number of genes of interest * Expected: Expected number * pvalue ## Code/software Python script for calculating CpGo/e #### Access information Other publicly accessible locations of the data: * NCBI - PRJNA1188519 Data was derived from the following sources: * C. punctulatus genome is novel * C. meridianus genome here: [https://doi.org/10.1101/2025.01.20.633303](https://doi.org/10.1101/2025.01.20.633303) #### Code/Software Cpg.py: This Python script calculates the CpG observed/expected (CpG O/E) ratio for each gene sequence in a FASTA file. It reads the input file from the command line and stores each gene’s DNA sequence in a dictionary. For every sequence, it counts the number of cytosines (C), guanines (G), and CpG dinucleotides (CG). The CpG O/E value is computed as the observed number of CGs divided by the expected number based on C and G frequencies in the sequence. If no CpG sites are present, the value is set to zero. Finally, the script outputs each gene name and its CpG O/E ratio in a tab-separated format.