Northern Cardinal microbiome pilot study 2020-2021
Data files
Nov 24, 2024 version files 4.35 GB
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mapping_file_allyears.txt
204.10 KB
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NOCA_2020_16S.zip
2.14 GB
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NOCA_sequences_Feb2022.zip
2.18 GB
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phyloseq.biom
27.93 MB
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README.md
8.82 KB
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tree.nwk
6.44 MB
Abstract
Animal populations can exhibit dramatic variation in individual fitness, and microbiota are emerging as a potentially understudied factor influencing host health. Bacterial diversity and community structure of the gut microbiome are associated with many aspects of fitness in animals, but relatively little is known about the generality of these relationships in wild populations and non-mammalian taxa. We studied the Northern Cardinal (Cardinalis cardinalis), a member of a taxon that is ecologically important but underrepresented in microbiome research: songbirds. To test for relationships between the microbiota and host fitness, we sampled the cloacal microbiomes of wild cardinals and measured body condition index, assessed the coloration of sexual ornaments (beak and plumage), and collected blood to estimate the glucocorticoid response to stress. Both alpha and beta bacterial diversity were related to individual variation in body condition and several sexual ornaments, but not glucocorticoid concentrations. Our results from a free-living songbird population add to a growing body of research linking avian host fitness to internal bacterial community characteristics. This study sets the stage for manipulative experiments to determine how challenges to fitness and microbiomes may upset these relationships.
The following is a dataset (DOI: https://doi.org/10.5061/dryad.41ns1rnnq) for a paper published in 2024 in the journal Oikos. This dataset includes:
- Raw microbiome files. Files included are:
- “NOCA 2020 16S.zip” - expandable .zip file containing fastq.gz files, each of which is a compressed file containing forward and reverse reads of a DNA sequence that was extracted, amplified, and sequenced. Data in this .zip file are from microbiome samples collected from February 2020 through January 2021. Sequences match sample IDs in “mapping file allyears.txt”.
- “NOCA sequences Feb2022.zip” - expandable .zip file containing fastq.gz files, each of which is a compressed file containing forward and reverse reads of a DNA sequence that was extracted, amplified, and sequenced. Data in this .zip file are from microbiome samples collected from February 2021 through October 2021. Sequences match sample IDs in “mapping file allyears.txt”.
- Files output from a QIIME2 pipeline that filtered and processed the above raw sequence files (see methods and references within our published paper in Oikos for details), which were imported into R Studio. In R Studio, all 3 files were merged to create a merged phyloseq object, which became the main data frame from which all downstream analysis and hypothesis testing were performed. Files included are:
- “tree.nwk” - a midpoint-rooted phylogenetic tree file created using FASTTREE2 in QIIME2.
- “phyloseq.biom” - a file containing species abundances per microbiome sample (Sample IDs match Sample IDs in “mapping file allyears.txt”)
- “mapping file allyears.txt” - a text file (which can and should be opened in Excel or a similar spreadsheet program for viewing or editing) that includes all “metadata” (i.e. non-microbiome information and variables) for each microbiome sample. See a brief explanation of each column below in “Description of the data and file structure.”
- “Oikos R1 script.R” - An R script (long series of code that can be opened in R Studio or viewed a text file) used to further process and analyze the above three QIIME2 output files in R. Script is annotated so each line or section of code has a brief explanation for why the code was chosen, often with information explaining the function and/or package (an open source series of functions and pre-loaded datasets) was used. Refer to the paper published in Oikos for context.
Description of metadata columns in “mapping file allyears.txt”
Below is a list of each column in the metadata file “mapping file allyears.txt”. “N/A” refers to missing values for the column for that sample, unless otherwise specified.
- Sampleid - the unique sample ID for each microbiome sample
- extraction_id - the unique id used during DNA extractions
- bird_name - the bird name assigned to the bird from which the microbiome sample was collected
- timepoint - refers to the sample timepoint (1 or 2) from an experiment in which each bird was captured, sampled, released for treatment, and then recaptured. “N/A” refers to samples that were not involved in this experiment.
- project - designates a sample as part of the study published in Oikos (“descriptive2020-2021”) or a separate empirical study (“2022stress”)
- microbiome - refers to the body region that was sampled
- case_or_control - designates a sample as a sample from a bird or a DNA extraction blank (negative control sample)
- batch - refers to which of 3 sequencing batches the sample was processed
- Sample_or_Control - designates a sample as a sample from a bird or a DNA extraction blank (negative control sample)
- DNAquant - DNA yield after DNA extraction
- treatment - designates which treatment the sampled bird received
- treatment_days - number of days between samples
- year - year sample was collected
- date - date sample was collected
- season - season sample was collected. breeding season designated as February - September, non-breeding season designated as October - January
- overall_timepoint - some birds were captured more than once through the project, this designates how many times the bird had been sampled by the time of this sample overall
- sex - sex of the bird sampled
- site - study site where the bird was captured and sampled
- time_trap - time of day of the sampled bird hit the mist net
- time_bled - time of day of the first blood sample taken from the sampled bird
- age - age of the sampled bird. NSTL = nestling, HY = hatch-year, AHY = after-hatch-year, ASY = after-second-year, ATY = after-third-year
- mass - mass (grams) of the sampled bird
- wing - unflattened wing chord length (mm) of the sampled bird
- tarsus - tarsus bone length (mm) of the sampled bird
- tail - tail length (mm) of the sampled bird
- culmen - bill culmen length (mm) of the sampled bird
- bill_depth - bill depth (mm) of the sampled bird
- bill_width - bill width (mm) of the sampled bird
- bill_plus_head - length (mm) from the back of the sampled bird’s head to the tip of its bill
- bill_SA - bill surface area (mm-squared) of the sampled bird
- crest - length (mm) of longest crest feather of the sampled bird
- keel - keel score of the sampled bird (low muscle score to high muscle score)
- fat - fat score of the sampled bird (low-fat amount to high-fat amount) body_condition - mass divided by tarsus length of the sampled bird
- delaycaught - number of minutes between when playback audio started playing and when the sampled bird was caught
- delaybled - number of minutes between when playback audio started playing and when the sampled bird was first bled
- T0delay - number of minutes between when the sampled bird was caught and was first bled
- beak_brightness - brightness score of the sampled bird’s beak, calculated in the micatoolbox plugin for ImageJ
- beak_saturation - saturation score of the sampled bird’s beak, calculated in the micatoolbox plugin for ImageJ
- beak_hue - the hue of the sampled bird’s beak, calculated in the micatoolbox plugin for ImageJ
- mask_brightness - brightness score of the sampled bird’s mask, calculated in the micatoolbox plugin for ImageJ
- mask_saturation - saturation score of the sampled bird’s mask, calculated in the micatoolbox plugin for ImageJ
- underwing_saturation - saturation score of the sampled bird’s underwing, calculated in the micatoolbox plugin for ImageJ
- underwing_hue - hue score of the sampled bird’s underwing, calculated in the micatoolbox plugin for ImageJ
- underwing_brightness - brightness score of the sampled bird’s underwing, calculated in the micatoolbox plugin for ImageJ
- back_car_saturation - carotenoid-saturation score of the sampled bird’s back, calculated in the micatoolbox plugin for ImageJ
- back_hue - hue score of the sampled bird’s back, calculated in the micatoolbox plugin for ImageJ
- back_uv_hue - ultraviolet hue score of the sampled bird’s back, calculated in the micatoolbox plugin for ImageJ
- back_saturation - saturation score of the sampled bird’s back, calculated in the micatoolbox plugin for ImageJ
- back_brightness - brightness score of the sampled bird’s back, calculated in the micatoolbox plugin for ImageJ
- breast_car_saturation - carotenoid-saturation score of the sampled bird’s breast, calculated in the micatoolbox plugin for ImageJ
- breast_hue - hue score of the sampled bird’s breast, calculated in the micatoolbox plugin for ImageJ
- breast_uv_hue - ultraviolet hue score of the sampled bird’s breast, calculated in the micatoolbox plugin for ImageJ
- breast_saturation - saturation score of the sampled bird’s breast, calculated in the micatoolbox plugin for ImageJ
- breast_brightness - brightness score of the sampled bird’s breast, calculated in the micatoolbox plugin for ImageJ
- baseline_CORT - baseline corticosterone concentration (t0 sample concentration divided by t30 sample concentration)
- T15_CORT - corticosterone concentration from blood plasma collected from sampled bird 15 minutes after capture
- T30_CORT - corticosterone concentration from blood plasma collected from sampled bird 30 minutes after capture
- T0_div_T30 - corticosterone concentration from blood plasma collected from sampled bird <3 minutes after capture divided by the sample collected 30 minutes after capture
- CORT_speed - corticosterone concentration from blood plasma collected from sampled bird 15 minutes after capture
- CORT_scope - corticosterone concentration from blood plasma collected from sampled bird 30 minutes after capture minus baseline CORT value
These data come from a wild population of Northern Cardinals (Cardinalis cardinalis) captured in South Florida from 2020-2021. Birds were captured in Tree Tops Park, Davie, FL. Data herein from each bird include 1) fitness-related parameters: coloration values of several sexual ornaments, body condition and morphometrics, and corticosterone concentrations from three sample time points during capture and 2) microbiome diversity, calculated from samples of the birds' cloacal microbiomes. Coloration was processed and calculated by photography analysis or spectroscopy (depending on which ornament is being inspected), corticosterone concentrations were estimated from blood samples using commercial enzyme immunoassay kits, and microbiome samples were processed via DNA extraction, PCR, and subsequent DNA sequencing of the V4 region of the 16S rRNA gene.