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Abstract Single‐nucleotide polymorphisms (SNPs) are preferred over microsatellite markers in many evolutionary studies, but have only recently been applied to studies of parentage. Evaluations ofSNPs and microsatellites for assigning parentage have mostly focused on special cases that require a relatively large number of heterozygous loci, such as species with low genetic diversity or with complex social structures. We developed 120SNPmarkers from a transcriptome assembled usingRNA‐sequencing of a songbird with the most common avian mating system—social monogamy. We compared the effectiveness of 97 novelSNPs and six previously described microsatellites for assigning paternity in the black‐throated blue warbler,Setophaga caerulescens. We show that the full panel of 97SNPs (meanH_o = 0.19) was as powerful for assigning paternity as the panel of multiallelic microsatellites (meanH_o = 0.86). Paternity assignments using the two marker types were in agreement for 92% of the offspring. Filtering individual samples by a 50% call rate andSNPs by a 75% call rate maximized the number of offspring assigned with 95% confidence usingSNPs. We also found that the 40 most heterozygousSNPs (meanH_o = 0.37) had similar power to assign paternity as the full panel of 97SNPs. These findings demonstrate that a relatively small number of variableSNPs can be effective for parentage analyses in a socially monogamous species. We suggest that the development ofSNPmarkers is advantageous for studies that require high‐throughput genotyping or that plan to address a range of ecological and evolutionary questions. 

ABSTRACT Animals produce a wide array of sounds with highly variable acoustic structures. It is possible to understand the causes and consequences of this variation across taxa with phylogenetic comparative analyses. Acoustic and evolutionary analyses are rapidly increasing in sophistication such that choosing appropriate acoustic and evolutionary approaches is increasingly difficult. However, the correct choice of analysis can have profound effects on output and evolutionary inferences. Here, we identify and address some of the challenges for this growing field by providing a roadmap for quantifying and comparing sound in a phylogenetic context for researchers with a broad range of scientific backgrounds. Sound, as a continuous, multidimensional trait can be particularly challenging to measure because it can be hard to identify variables that can be compared across taxa and it is also no small feat to process and analyse the resulting high‐dimensional acoustic data using approaches that are appropriate for subsequent evolutionary analysis. Additionally, terminological inconsistencies and the role of learning in the development of acoustic traits need to be considered. Phylogenetic comparative analyses also have their own sets of caveats to consider. We provide a set of recommendations for delimiting acoustic signals into discrete, comparable acoustic units. We also present a three‐stage workflow for extracting relevant acoustic data, including options for multivariate analyses and dimensionality reduction that is compatible with phylogenetic comparative analysis. We then summarize available phylogenetic comparative approaches and how they have been used in comparative bioacoustics, and address the limitations of comparative analyses with behavioural data. Lastly, we recommend how to apply these methods to acoustic data across a range of study systems. In this way, we provide an integrated framework to aid in quantitative analysis of cross‐taxa variation in animal sounds for comparative phylogenetic analysis. In addition, we advocate the standardization of acoustic terminology across disciplines and taxa, adoption of automated methods for acoustic feature extraction, and establishment of strong data archival practices for acoustic recordings and data analyses. Combining such practices with our proposed workflow will greatly advance the reproducibility, biological interpretation, and longevity of comparative bioacoustic studies.