The genetic basis of plumage coloration and elevation adaptation in a clade of recently diverged alpine and arctic songbirds
Creators: name: Funk, Erik
name: Spellman, Garth
name: Winker, Kevin
name: Withrow, Jack
name: Ruegg, Kristen
name: Taylor, Scott
Publisher: name: Zenodo
Year: 2022
Subjects: Leucosticte
rosy-finch
whole genome sequencing
melanogenesis
hypoxia-inducible factor (HIF)

description: Trait genetic architecture plays an important role in the probability that variation in that trait leads to divergence and speciation. In some cases, speciation may be driven by the generation of novel phenotypes through the recombination of genes associated with traits that are important for local adaptation or sexual selection. Here, we investigate the genetic basis of three plumage color traits, and one ecological trait, breeding elevation, in a recent avian radiation, the North American rosy-finches (<em>Leucosticte</em> spp.). We identify unique genomic regions associated with each trait and highlight 11 candidate genes. Among these are well-characterized melanogenesis genes, including Mitf and Tyrp1, and previously reported hypoxia-related genes including Egln1. Additionally, we use mitochondrial data to date the divergence of rosy-finch clades which appear to have diverged within the past 250 ky. Given the low levels of genome-wide differentiation among rosy-finch taxa, and evidence for extensive introgression in North America, plumage coloration and adaptation to high elevations have likely played large roles in generating the observed patterns of lineage divergence. The relative independence of these candidate regions across the genome suggests that recombination might have led to multiple phenotypes, and subsequent rosy-finch speciation, over short periods of time.
description: VCF file is a plain text file containing filtered genotypes for all individuals. The tree posterior used to date divergence events contains 10,000 trees as a nexus file. This file can be reanalyzed using a program such as TreeAnnotator from the Beast software distribution and visualized.Funding provided by: National Geographic Society<br>Crossref Funder Registry ID: http://dx.doi.org/10.13039/100006363<br>Award Number: WW-202R-17
description: DNA was extracted from a combination of tissues and blood samples. We prepared genomic libraries using a modified Nextera Protocol (Illumina, Inc.). We diluted extracted DNA to a concentration of 2.5 ng/uL followed by tagmentation of 1 uL gDNA. We indexed samples using the Nextera index kit (Illumina, Inc.) and amplified with KAPA HiFi Hot Start (Kapa Biosystems). We added primers with a reconditioning PCR and cleaned and size-selected the products using an AMPure XP bead clean-up (Agencourt). We pooled libraries for sequencing on four lanes of an Illumina HiSeq X ten, with a library fragment size targeting 350 base pairs. To map reads, we used a Dovetail-generated, chromosome-level reference genome (Dovetail Genomics, CA, USA) of a brown-capped rosy-finch (<em>Leucosticte</em> <em>australis</em>; DMNS:Bird:52416, NCBI JANIJU000000000) new to this study. We annotated genomic features using the program Liftoff (Shumate and Salzberg 2021) with the most recent zebra finch annotations that were available at the time of analysis (NCBI GCA_008822105.2). We numbered chromosomes according to the zebra finch using Satsuma (Grabherr et al. 2010) and visualized syntenic blocks using Satsuma's Chromosome Paint. In the discussion of our results below, we refer to different alleles as reference and alternate and note here that our reference genome is from a high-elevation individual that lacks many melanin-based traits that are of interest in this study. Details of the bioinformatic and filtering steps can be found on GitHub (https://github.com/erikrfunk/whole_genome_bioinformatics/blob/master/rosyfinch_notes.md). Briefly, we performed a quality assessment for each sample using fastQC v0.11.8 (www.bioinformatics.babraham.ac.uk/projects/fastqc) before and after trimming reads. We used Trimmomatic v0.32 (Bolger et al. 2014) in paired-end mode to perform adapter removal and to trim reads using a sliding window when average phred score dropped below 20. We aligned short reads to the reference genome using the BWA-MEM algorithm (Li and Durbin 2009), and sorted and indexed the alignment files using SAMtools v1.9 (Wysoker et al. 2009). We used the mpileup and call commands in bcftools to call variants for each individual (Li 2011), filtering out sites with a quality score below 80. We also filtered out variants with a minor allele frequency less than 0.05, and that had an average depth less than one or greater than nine to remove variants possibly coming from paralogous loci. We required 75% of individuals (42 out of 56) to have data at a given site for it to be retained in our final dataset. Finally, we confirmed there were no siblings in the sampled birds using the Ajk statistic (--relatedness) from VCFtoolsv0.1.15 (Danecek et al. 2011).