bioRxivBioinformaticsPreprint
Reference genome choice impacts SNP recovery but not evolutionary inference in young species
Luana Sousa SoaresiD, Leonardo Tresoldi GonçalvesiD, Sebastián Guzmán-RodrigueziD, Aureliano BombarelyiD, Loreta B. FreitasiD
Abstract
Reduced-representation sequencing approaches such as RAD-seq are widely used in population genomics and phylogenetics, particularly for non-model organisms. However, bioinformatics choices during data processing can strongly influence downstream analyses. One key but underexplored factor is the reference genome used for read alignment and SNP discovery. Here, we evaluate the effects of reference genome choice on RAD-seq analyses using multiple datasets spanning recent radiations in Petunia and Calibrachoa, and reference genomes that differ in phylogenetic relatedness. When using congeneric reference genomes, we observed highly consistent mapping rates, SNP recovery, and downstream population genomic patterns. In contrast, mapping to more distantly related genomes resulted in lower mapping rates and stronger effects on summary statistics. Despite these quantitative reductions, broader patterns of genetic structure and diversity, as well as evolutionary relationships, remained largely congruent across reference genomes. Overall, our results indicate that reference genome choice matters most when genomes are distantly related or when analyses target fine-scale genomic signals. For recent radiations with largely conserved genome structure, closely related reference genomes yield comparable SNP datasets and lead to the same biological conclusions regarding population structure and phylogenetic relationships. These findings provide practical guidance for RAD-seq studies in non-model systems, showing that congeneric reference genomes are sufficient for robust population and phylogenetic inference, and that more distantly related genomes can remain informative when no close reference is available.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: phylogenetics / evolution
- research focus: variant calling
- research focus: genome assembly
- research focus: GWAS / association mapping
- approach: statistical model
- approach: experimental assay
- Citations
- 1
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