@article{f00ca7afe8904af78f7bec4c07234781,
title = "Genetic and ecological drivers of molt in a migratory bird",
abstract = "The ability of animals to sync the timing and location of molting (the replacement of hair, skin, exoskeletons or feathers) with peaks in resource availability has important implications for their ecology and evolution. In migratory birds, the timing and location of pre-migratory feather molting, a period when feathers are shed and replaced with newer, more aerodynamic feathers, can vary within and between species. While hypotheses to explain the evolution of intraspecific variation in the timing and location of molt have been proposed, little is known about the genetic basis of this trait or the specific environmental drivers that may result in natural selection for distinct molting phenotypes. Here we take advantage of intraspecific variation in the timing and location of molt in the iconic songbird, the Painted Bunting (Passerina ciris) to investigate the genetic and ecological drivers of distinct molting phenotypes. Specifically, we use genome-wide genetic sequencing in combination with stable isotope analysis to determine population genetic structure and molting phenotype across thirteen breeding sites. We then use genome-wide association analysis (GWAS) to identify a suite of genes associated with molting and pair this with gene-environment association analysis (GEA) to investigate potential environmental drivers of genetic variation in this trait. Associations between genetic variation in molt-linked genes and the environment are further tested via targeted SNP genotyping in 25 additional breeding populations across the range. Together, our integrative analysis suggests that molting is in part regulated by genes linked to feather development and structure (GLI2 and CSPG4) and that genetic variation in these genes is associated with seasonal variation in precipitation and aridity. Overall, this work provides important insights into the genetic basis and potential selective forces behind phenotypic variation in what is arguably one of the most important fitness-linked traits in a migratory bird.",
author = "Andrea Contina and Bossu, {Christen M.} and Daniel Allen and Wunder, {Michael B.} and Ruegg, {Kristen C.}",
note = "Funding Information: This work was made possible by a California Energy Commission Grant to K. Ruegg, a National Geographic Grant to K. Ruegg (WW-202R-17), and a Grant to K. Ruegg from the National Science Foundation (NSF-1942313). Postdoctoral work conducted by A. Contina was supported in part by Jeff Kelly (NSF award 1840230). The authors thank the DNA Technologies and Expression Analysis Cores at the UC Davis Genome Center (supported by NIH Shared Instrumentation Grant 1S10OD010786-01) for their assistance with the Next-Generation Sequencing. Computational allocations from the Extreme Science and Engineering Discovery Environment (Xsede), as well as UCLA{\textquoteright}s Shared Hoffman2 Cluster made this work possible. They thank Thomas B. Smith, the Department of Ecology and Evolutionary Biology, and the Center for Tropical Research at the University of California, Los Angeles, for providing laboratory and sample collection support. They also thank Eli Bridge, Tyler Michels, William Oakley, Heather LePage, Elizabeth Besozzi, John Muller, Jeff Johnson and Matt Poole for their assistance with sample collection. They thank BirdLife International for the use of range map data downloaded from http://www.birdlife.org. Funding Information: This work was made possible by a California Energy Commission Grant to K. Ruegg, a National Geographic Grant to K. Ruegg (WW-202R-17), and a Grant to K. Ruegg from the National Science Foundation (NSF-1942313). Postdoctoral work conducted by A. Contina was supported in part by Jeff Kelly (NSF award 1840230). The authors thank the DNA Technologies and Expression Analysis Cores at the UC Davis Genome Center (supported by NIH Shared Instrumentation Grant 1S10OD010786-01) for their assistance with the Next-Generation Sequencing. Computational allocations from the Extreme Science and Engineering Discovery Environment (Xsede), as well as UCLA{\textquoteright}s Shared Hoffman2 Cluster made this work possible. They thank Thomas B. Smith, the Department of Ecology and Evolutionary Biology, and the Center for Tropical Research at the University of California, Los Angeles, for providing laboratory and sample collection support. They also thank Eli Bridge, Tyler Michels, William Oakley, Heather LePage, Elizabeth Besozzi, John Muller, Jeff Johnson and Matt Poole for their assistance with sample collection. They thank BirdLife International for the use of range map data downloaded from http://www.birdlife.org . Publisher Copyright: {\textcopyright} 2023, The Author(s).",
year = "2023",
month = dec,
doi = "10.1038/s41598-022-26973-7",
language = "English (US)",
volume = "13",
journal = "Scientific reports",
issn = "2045-2322",
publisher = "Nature Publishing Group",
number = "1",
}