Pelvic spine reduction affects diet but not gill raker morphology in two polymorphic brook stickleback (Culaea inconstans) populations
Data files
Nov 01, 2023 version files 1.41 GB
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Mee_etal_CCDB_Culaea_guts_metabarcoding.zip
1.41 GB
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Mee_etal_gill_rakers.csv
38.86 KB
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Metadata_culaea_gut.csv
9.02 KB
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README.md
4.58 KB
Abstract
Pelvic spine polymorphism occurs in several species in the stickleback family (Gasterosteidae). Given parallel selection driving similar phenotypic polymorphisms in multiple stickleback species, we sought to determine the extent of parallelism in the ecological consequences of pelvic spine reduction. Based on a metabarcoding analysis of brook stickleback gut contents in two polymorphic populations, we found a shift towards a planktonic diet was associated with pelvic spine reduction. These results contrast with those found in threespine stickleback where pelvic spine reduction is associated with a shift towards a benthic diet. Hence, we found non-parallel consequences of spine polymorphism across species. Furthermore, a change in gill raker morphology has been consistently implicated in the change in diet in pelvic-reduced threespine stickleback. But we found no evidence of any difference in gill raker morphology associated with pelvic spine polymorphism in brook stickleback.
The data consist of two files - one is a zip archive of sequence data from metabarcoding of brook stickleback gut contents, and one is a csv file of measurements and counts of brook stickleback gill rakers. In addition, there is a separate “metadata” csv file associated with the metabarcoding dataset, which includes the phenotype, sex, size, and population information for each individual in the metabarcoding dataset (this sample information is included as columns in the csv file for the gill raker dataset).
Description of the data and file structure
Mee_etal_CCDB_Culaea_guts_metabarcoding.zip - This zip archive contains fastq files with the sequence information from 95 brook stickleback guts.
Metadata_culaea_gut.csv - this csv file has all the sample information (e.g. sex, pelvic phenotype, length, population) for all 95 brook stickleback in the metabarcoding dataset. Columns in this file:
Sample_ID.IonCode: the unique sample ID associated with each individual in the sequence data file
Sample_ID: the unique sample ID assigned to each individual at the tim of capture
Lake: the lake of origin for each individual
Trap_location: description of the access point for setting traps in each lake. “North” and “South” for Shunda Lake refer to direction relative to the boat launch.
Habitat: whether the sample was collected in a trap set adjacent to shore (“Littoral”) or in a trap floated >50m from shore (“Pelagic”)
Year: the year the individual was sampled
FL_mm: the fish length in centimetres (FL stands for “fork length”, but this is actually the “total length” because stickleback don’t have a forked caudal fin)
Sex: sex, as assigned at time of capture
Pelvic_code: the pelvic phenotype coded as 1 = spined, 2 = vestigial, 3 = unspined
Pelvic_pheno: the pelvic phenotype coded as “spined”, “int” (= vestigial), or “unspined”
Pelvic_pheno2: the pelvic phenotype coded as “spined” (corresponding to Pelvic_code = 1) or “reduced” (corresponding to Pelvic_code = 2 or 3)
Mee_etal_gill_rakers.csv - this csv file has all the sample information and gill raker measurements for all the brook stickleback analysed in this study. Missing data is stored as blank cells. Columns in this file:
Sample_ID: the unique sample ID for each individual
Sex: sex, as assigned at time of capture
Lake: the lake of origin for each individual
Year: the year the individual was sampled
Habitat: whether the sample was collected in a trap set adjacent to shore (“Littoral”) or in a trap floated >50m from shore (“Pelagic”)
FL_cm: the fish length in centimetres (FL stands for “fork length”, but this is actually the “total length” because stickleback don’t have a forked caudal fin)
Pelvicpheno: the pelvic phenotype coded as 1 = spined, 2 = vestigial, 3 = unspined
Reduced: the pelvic phenotype coded as “no” = not reduced (corresponding to Pelvicpheno = 1) or “yes” = reduced (corresponding to Pelvicpheno = 2 or 3)
L_rakers: the number of gill rakers on the left arch
R_rakers: the number of gill rakers on the right arch
Rakers_mean: the mean number of gill rakers (averaged across left and right arches)
Rakers_max: the maximum number of gill rakers (on either the left or right arch)
L_raker_length_1: length of the second gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the left ceratobranchial
L_raker_length_2: length of the third gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the left ceratobranchial
L_raker_length_3: length of the fourth gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the left ceratobranchial
L_raker_max: the length of the longest gill raker (in micrometers) on the left arch
R_raker_length_1: length of the second gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the right ceratobranchial
R_raker_length_2: length of the third gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the right ceratobranchial
R_raker_length_3: length of the fourth gill raker (in micrometers) from the epibranchial-ceratobranchial joint on the right ceratobranchial
R_raker_max: the length of the longest gill raker (in micrometers) on the right arch
Raker_length_max: the length of the longest gill raker (in micrometers)
use: coded “yes” or “no” to indicate whether to use the sample in analyses or not
notes: justification for “use” decision
Brook stickleback were collected in Alberta, Canada, from Muir Lake (UTF-8 encoded WGS84 latitude and longitude: 53.627659, -113.957524) and Shunda Lake (52.453899, -116.146192).
For gut content metabarcoding: Fish guts collected from 95 fish in 2019 were shipped to the Canadian Centre for DNA Barcoding at the University of Guelph for membrane-based DNA extraction and amplicon sequencing. This metabarcoding approached used five PCR primer sets designed to amplify a barcode region of the cytochrome c oxidase subunit I (COI) gene in arthropods, mollusks, annelids, amphipods, and microalgae (details of COI amplification can be found at http://ccdb.ca/site/wp-content/uploads/2016/09/CCDB_Amplification.pdf). A second round of PCR amplification added Ion Torrent sequencing adapters and a unique multiplex identifier (MID) sequence to the 5’ end of amplicons for each sample. Amplified COI fragments were then pooled and single-end sequenced on an Ion Torrent PGM sequencing platform (Thermo Fisher, Waltham, MA, USA). The resulting sequence data was automatically de-multiplexed by the PGM Torrent Browser (Thermo Fisher, Waltham, MA, USA).
For gill rakers: Fish that had been bleached and stained with alizarin red for morphological analyses were used to investigate variation in gill raker morphology associated with different pelvic phenotypes. We removed the first branchial arches from both sides of each fish with forceps and scissors, cleared away all the gill filaments, and photographed the gill rakers in a plastic weighing boat using a Nikon SMZ-75T Greenough-type stereo microscope with a mounted Imaging Source camera and NIS-Elements D Software (©2021 Nikon Corporation). We counted the number of gill rakers on the left and right gill arches, and we measured the length of the second through fourth gill raker from the epibranchial-ceratobranchial joint on the ceratobranchial, which were consistently the three longest gill rakers on each arch.
For gut content metabarcoding: We removed primer and adapter sequences from the de-multiplexed reads, and discarded reads that consisted of only primer or adapter sequence using CUTADAPT v2.3. We used DADA2 in R v4.2.2 to trim and filter reads, estimate error rates for the filtered and trimmed amplicon dataset, combine identical reads into unique sequences, and infer biologically meaningful (as opposed to spurious) amplified sequence variants (ASVs). We exported the list of ASVs across all samples to a fasta file and used the JAMP pipeline in BOLDigger to identify the best-fitting taxonomic identification for each ASV. We used the PHYLOSEQ package to create a data object in R that allowed us to associate the abundance of each taxon identified in each fish’s gut with other sample data (i.e. lake, sex, size, and pelvic phenotype). We used the DESeq2 package in R to conduct Wald tests of the Log2 fold-differences in the abundances of each eukaryote family in the diets of brook stickleback.
For gill rakers: We set contrasts among factors using the contr.sum function, and we used the CAR package in R to generate an ANOVA table with type III sums of squares.