Fine-scale map reveals highly variable recombination rates associated with genomic features in the European blackcap

Abstract

Recombination is responsible for breaking up haplotypes, influencing genetic variability, and the efficacy of selection. Bird genomes lack the protein PRDM9, a key determinant of recombination dynamics in most metazoans. The historical recombination maps in birds show an apparent stasis in the positioning of recombination events. This highly conserved recombination pattern over long timescales should constrain the evolution of recombination in birds, but extensive variation in recombination rate across the genome and between different species has been reported. Here, we characterise a fine-scale historical recombination map of an iconic migratory songbird, the European blackcap (Sylvia atricapilla) using a LD-based approach which accounts for population demography. We found variable recombination rates among and within chromosomes, which associate positively with nucleotide diversity and GC content, and a negatively with chromosome size. The recombination rates increased significantly at regulatory regions and not necessarily at high-dense gene regions. CpG islands associated strongly with recombination rates; however, their specific position and local DNA methylation patterns likely influenced this relationship. The association with retrotransposons varied according to specific family and location. Our results also provide evidence of a heterogeneous conservation of recombination maps between the blackcap and its closest sister taxon, the garden warbler at the intra-chromosomal level. These findings highlight the considerable variability of recombination rates at different scales and the role of specific genomic features at shaping this variation. This study opens the possibility of further investigating the impact of recombination in specific population-genomic features.

The blackcap (Sylvia atricapilla) genome reveals a species-specific accumulation of LTR retrotransposons

“…However, our categorisation of species-speci c TEs encompasses a wider age range of TEs, than can be considered "young". It's important to note that weighing in on these correlations is the TE type that composes the majority of a category, for example, the species-speci c TEs are mainly comprised of LTRs, which were previously found to be negatively correlated to recombination rate [10] and we also recover, see Supplementary Table S1. To better reconstruct this relationship, further research focussing on recently active TEs and their placement near recombination hotspots is needed.…”

“…Genes were also predicted from cDNA and protein sequences of three additional bird species, supporting accurate gene annotations. Furthermore, LD-based recombination rate estimation was performed using Pyrho [30,31] , which estimates recombination rate (r) per base and generation using population-speci c effective population sizes (Ne) and mutation rate and takes demography into account, unphased genotypes were inputted in VCF format, with optimized parameters for blackcaps as in Bascón-Cardozo et al [10] . As mutation rate, we used estimates for the collared ycatcher, i.e.…”

“…We wanted to know how the relationships differed for species-speci c TEs and nonspeci c TEs, in repeat landscape and the relations of TEs with genomic features, such as recombination rate, GC content, CpG islands and gene coverage which had been seen to correlate in blackcaps [10] . To allow for direct comparison with Bascón-Cardozo et al [10] , Kendall's rank correlation test was initially performed on all TEs and the different TE types. Additionally, we tested the correlation of all genomic features within the two categories of TEs separately, using Kendall's rank correlation test.…”

“…Additionally, we tested the correlation of all genomic features within the two categories of TEs separately, using Kendall's rank correlation test. However, as these genomic features were highly correlated with each other [10] , we also performed a partial Kendall's rank correlation test to exclude bias.…”

Historical recombination maps diverge between Eurasian blackcap populations with distinct migratory strategies

“…Recombination variation within the avian genome is associated with the presence and distribution of specific genomic features. High recombination rates are enriched in GC-rich content sequences, including CpG islands, regulatory regions such as promoters, transcription start sites, 5'UTR regions, and specific families of transposable elements (TEs) (Bascón-Cardozo et al, 2022;Kawakami et al, 2017;Singhal et al, 2015;. Low recombining regions associate with intergenic regions, chromosomal rearrangements (i.e.…”