DOI: 10.5061/dryad.wstqjq2z8
title: Data from: Rewilding shows differential gene expression in sympatric Physella acuta (Draparnaud, 1805) snail lineages

description: This dataset contains 3,302 differentially expressed genes (DEGs) from the
 freshwater snail Physella acuta, identified through transcriptomic
 analysis comparing environmental conditions (Field vs. Lab) across both
 invasive (A) and native (B) lineages. The FASTA file includes sequences
 for both upregulated (URGs) and downregulated genes (DRGs) from four
 pairwise comparisons: Field A vs. Field B, Field B vs. Lab B, Field A vs.
 Lab A, and Lab A vs. Lab B. DEGs were consistently identified using two
 independent RNA-seq analysis pipelines—STAR/Limma and
 Kallisto/DESeq2—ensuring robustness of detection. Additionally, this
 dataset includes a subset of 1,228 transcript sequences representing
 orthologs of human and mouse MitoCarta genes. The MitoCarta database
 catalogs nuclear-encoded mitochondrial proteins involved in ATP synthesis,
 metabolism, and cellular stress responses. These sequences were identified
 through transcriptome-wide similarity searches against the MitoCarta 3.0
 reference set (Rath et al. 2021) using a genome-guided transcriptome
 assembly derived from RNA-seq data of both laboratory and rewilded snails.
 An accompanying CSV file is provided, categorizing each transcript ID
 based on homology to the human database only, the mouse database only, or
 both.
description: # Rewilding shows differential gene expression in sympatric Physella acuta
 (Draparnaud, 1805) snail lineages Dataset DOI:
 [10.5061/dryad.wstqjq2z8](10.5061/dryad.wstqjq2z8) ## Description of the
 data and file structure Laboratory-bred *Physella acuta* snails from two
 genetically distinct lineages (A and B) were exposed to either controlled
 laboratory or natural field conditions for one week to investigate
 molecular mechanisms underlying differential fitness. RNA-seq was
 performed on these snails, and differential gene expression was analyzed
 using STAR/Limma and Kallisto/DESeq2. The resulting dataset includes 3,302
 differentially expressed genes and a set of 1,228 transcript sequences
 identified as orthologs of vertebrate mitochondrial genes based on
 similarity to the MitoCarta 3.0 database. Transcriptome assembly was
 genome-guided and incorporated RNA-seq data from both rewilded and
 laboratory conditions. ### Files and variables #### File:
 3302\_ALL\_Physella\_acuta\_DEGS.fasta **Description:**  This FASTA file
 contains 3,302 nucleotide sequences corresponding to differentially
 expressed genes (DEGs) identified in *Physella acuta* snails. The DEGs
 were mutually detected by two independent RNA-seq analysis
 pipelines—STAR/Limma (SL) and Kallisto/DESeq2 (KD)—from pairwise
 comparisons of invasive (A) and native (B) lineages under laboratory and
 field conditions. Each sequence entry includes a unique transcript
 identifier and the corresponding nucleotide sequence. #### File:
 MitoCarta\_Table.csv **Description:**  This CSV file contains a
 categorized table of the 1,228 *Physella acuta* transcript IDs from the
 MitoCarta_Physella_acuta_transcripts.fasta file. The table sorts
 transcripts into three groups based on their similarity to vertebrate
 mitochondrial genes: those matching only the human MitoCarta database,
 only the mouse database, or both. #### File:
 MitoCarta\_Physella\_acuta\_transcripts.fasta **Description:**  This FASTA
 file includes 1,228 transcript sequences from *Physella acuta* identified
 as orthologs of genes in the human and mouse MitoCarta 3.0 databases.
 These genes encode nuclear-encoded mitochondrial proteins involved in
 energy metabolism, ATP synthesis, and cellular stress responses. The
 sequences were derived from a genome-guided transcriptome assembly of
 RNA-seq data collected from both rewilded and laboratory snails of
 lineages A and B. ## Code/software To view or analyze the FASTA files,
 various free and open-source software programs are available. Commonly
 used tools include simple text editors such as Notepad++ (version 8.6.2)
 for Windows, TextEdit (version 1.18) for macOS, and nano (version 7.2) or
 vim (version 9.1) for Linux, which can be used for basic viewing or
 editing of sequence data. These programs allow users to inspect the
 contents of the FASTA file directly, including sequence headers and
 nucleotide sequences. The accompanying CSV file contains a table
 categorizing transcript IDs by homology to the human and/or mouse
 MitoCarta databases. For viewing and editing a CSV file on Windows, macOS,
 or Linux, several free and open-source tools are available. LibreOffice
 Calc and OnlyOffice provide full-featured spreadsheet functionality with
 support for sorting, filtering, and advanced data manipulation.
 Lightweight alternatives include Gnumeric (ideal for Linux users) and
 CSVed (a dedicated CSV editor for Windows). If a text-based approach is
 preferred, Notepad++ or VSCode (with CSV plugins) allow quick viewing and
 syntax highlighting, while VisiData offers a powerful terminal-based
 approach. No proprietary software is required to access or analyze this
 dataset. All mentioned programs are freely available, open-source, and
 widely used within the bioinformatics community.