the great tit HapMap project: a continental-scale analysis of genomic variation in a songbird

A major aim of evolutionary biology is to understand why patterns of genomic diversity vary within taxa and space. Large-scale genomic studies of widespread species are useful for studying how environment and demography shape patterns of genomic divergence. Here, we describe one of the most geographically comprehensive surveys of genomic variation in a wild vertebrate to date; the great tit (Parus major) HapMap project. We screened ca 500,000 SNP markers across 647 individuals from 29 populations, spanning ~30 degrees of latitude and 40 degrees of longitude - almost the entire geographic range of the European subspecies. Genome-wide variation was consistent with a recent colonisation across Europe from a South-East European refugiam, with bottlenecks and reduced genetic diversity in island populations. Differentiation across the genome was highly heterogeneous, with clear “islands of differentiation”, even among populations with very low levels of genome-wide differentiation. Low local ..., Genotype data was obtained by typing great tit blood samples collected by a research consortium, mostly from around Europe. Genotyping was performed on an Affymetrix high density SNP chip. Data were converted to Plink format, and from those Plink files various population genetic analyses were performed. All of the scripts are available on GitHub at https://github.com/lgs85/SpurginBosse_Hapmap/tree/main.
A manuscript describing the work has been submitted to Molecular Ecology Resources., , # Data from: the great tit HapMap project: a continental-scale analysis of genomic variation in a songbird

[https://doi.org/10.5061/dryad.w3r2280z5](https://doi.org/10.5061/dryad.w3r2280z5)

The data are the input and output files from a series of population genetics analyses performed on single nucleotide polymorphism (SNP) data generated from populations of great tits (Parus major) distributed around Europe. The majority of the analyses were run in Plink (Version 1.9) and R (Version 3.3). The pipelines and scripts used to generate the results are available on GitHub at [https://github.com/lgs85/SpurginBosse_Hapmap/tree/main.](https://github.com/lgs85/SpurginBosse_Hapmap/tree/main.)

## Description of the data and file structure

**Plink files:**

**HapMapMajor.bed**, **HapMapMajor.fam** and **HapMapMajor.bim** are Plink formatted binary files (see [https://www.cog-genomics.org/plink/1.9/input#bed)](https://www.cog-genomics.org/plink/1.9/input#bed\)) of the data before any filtering. ...